Insulin Resistance: Insulin Action and its Disturbances in Disease

Insulin Resistance

Insulin Resistance Insulin Action and Its Disturbances in Disease

Editors

Sudhesh Kumar Unit for Diabetes and Metabolism, Warwick Medical School, University of Warwick, Coventry CV4 7AL, UK

Stephen O’Rahilly Department of Clinical Biochemistry, University of Cambridge, Addenbrookes Hospital, Hill Road, Cambridge CB2 2QQ, UK

Copyright  2005

John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England Telephone (+44) 1243 779777

Email (for orders and customer service enquiries): [email protected] Visit our Home Page on www.wileyeurope.com or www.wiley.com 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, scanning or otherwise, except under the terms of the Copyright, Designs and Patents Act 1988 or under the terms of a licence issued by the Copyright Licensing Agency Ltd, 90 Tottenham Court Road, London W1T 4LP, UK, without the permission in writing of the Publisher. Requests to the Publisher should be addressed to the Permissions Department, John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England, or emailed to [email protected], or faxed to (+44) 1243 770620. 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. Other Wiley Editorial Offices John Wiley & Sons Inc., 111 River Street, Hoboken, NJ 07030, USA Jossey-Bass, 989 Market Street, San Francisco, CA 94103-1741, USA Wiley-VCH Verlag GmbH, Boschstr. 12, D-69469 Weinheim, Germany John Wiley & Sons Australia Ltd, 33 Park Road, Milton, Queensland 4064, Australia John Wiley & Sons (Asia) Pte Ltd, 2 Clementi Loop #02-01, Jin Xing Distripark, Singapore 129809 John Wiley & Sons Canada Ltd, 22 Worcester Road, Etobicoke, Ontario, Canada M9W 1L1 Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books.

Library of Congress Cataloging-in-Publication Data Insulin resistance : insulin action and its disturbances in disease / editors, Sudhesh Kumar, Stephen O’Rahilly. p. cm. Includes bibliographical references and index. ISBN 0-470-85008-6 1. Insulin resistance. I. Kumar, Sudhesh. II. O’Rahilly, S. (Stephen) RC662.4.I556 2004 616.4
6207 – dc22 2004016888 British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN 0-470-85008-6 Typeset in 10.5/13pt Times by Laserwords Private Limited, Chennai, India Printed and bound in Germany This book is printed on acid-free paper responsibly manufactured from sustainable forestry in which at least two trees are planted for each one used for paper production.

Contents Preface List of Contributors

xi xiii

1

The Insulin Receptor and Downstream Signalling Ken Siddle

1

1.1 1.2 1.3 1.4 1.5 1.6

Introduction Insulin receptor structure and function Insulin receptor substrates Downstream signalling pathways The basis of insulin’s signalling specificity Conclusion References

1 2 15 23 37 38 39

2

Insulin-mediated Regulation of Glucose Metabolism Daniel Konrad, Assaf Rudich and Amira Klip

63

2.1 2.2 2.3 2.4

Introduction Insulin as a master regulator of whole body glucose disposal Insulin-mediated regulation of glucose metabolic pathways Glucose uptake into skeletal muscle – the rate-limiting step in glucose metabolism Acknowledgements References

63 63 67

3

Insulin Action on Lipid Metabolism Keith N. Frayn and Fredrik Karpe

87

3.1 3.2 3.3 3.4 3.5 3.6 3.7

Introduction: does insulin affect lipid metabolism? Molecular mechanisms by which insulin regulates lipid metabolism Insulin and lipolysis Insulin, lipoprotein lipase and cellular fatty acid uptake Co-ordinated regulation of fatty acid synthesis and ketogenesis Insulin and cholesterol synthesis Insulin effects on lipoprotein metabolism Acknowledgement References

87 88 89 94 96 97 98 99 99

69 78 78

vi

CONTENTS

4

The Effect of Insulin on Protein Metabolism Laura J. S. Greenlund and K. Sreekumaran Nair

105

4.1 4.2 4.3

Introduction Molecular mechanisms of insulin’s effect on protein turnover Measurement of protein metabolism (synthesis and breakdown or turnover) in human subjects Whole body and regional protein turnover Acknowledgements References

105 107

5

Genetically Modified Mouse Models of Insulin Resistance Gema Medina-Gomez, Christopher Lelliott and Antonio J. Vidal-Puig

133

5.1 5.2

Introduction Genetic modification as a tool to dissect the mechanisms leading to insulin resistance Candidate genes involved in the mechanisms of insulin resistance Insulin signalling network Factors leading to insulin resistance Defining the function of the insulin cascade molecules through global knockouts Double heterozygous mice as models of polygenic forms of diabetes Defining tissue and/or organ relevance for the maintenance of insulin sensitivity Genetically modified mice to study modulators of insulin sensitivity Lipodystrophy versus obesity, the insulin resistance paradox Excess of nutrients as a cause of insulin resistance PPARs, key mediators of nutritional-regulated gene expression and insulin sensitivity References

133

4.4

5.3 5.4 5.5 5.6 5.7 5.8 5.9 5.10 5.11 5.12

111 114 125 125

134 134 136 137 137 139 140 142 143 147 148 148

6

Insulin Resistance in Glucose Disposal and Production in Man with Specific Reference to Metabolic Syndrome and Type 2 Diabetes 155 Henning Beck-Nielsen, Frank Alford and Ole Hother-Nielsen

6.1 6.2 6.3 6.4

Introduction Measurement of insulin resistance Insulin-resistant states Conclusion and perspectives References

155 157 162 171 172

7

Central Regulation of Peripheral Glucose Metabolism Stanley M. Hileman and Christian Bjørbæk

179

7.1 7.2 7.3 7.4

Introduction Counter-regulation of hypoglycaemia – role of the CNS Brain regions involved in counter-regulation Glucosensing neurons

179 180 182 184

CONTENTS

7.5 7.6

vii

Central control of peripheral organs involved in glucoregulation Additional afferent signals to the CNS regulating peripheral glucose metabolism Conclusions and future perspectives Acknowledgements References

187

8

Relationship between Fat Distribution and Insulin Resistance Philip G. McTernan, Aresh Anwar and Sudhesh Kumar

207

8.1 8.2 8.3 8.4 8.5 8.6 8.7 8.8 8.9 8.10 8.11 8.12 8.13 8.14 8.15 8.16 8.17 8.18 8.19 8.20 8.21 8.22 8.23

Introduction Fat and its distribution Basis for variation in adipose tissue mass Change in adipocyte phenotype with obesity Obesity and its association with insulin resistance Subcutaneous and visceral adipose tissue The pathogenic significance of abdominal adipose tissue Potential mechanisms linking central obesity to the metabolic syndrome Randle hypothesis/glucose–fatty acid hypothesis Alternatives to the Randle hypothesis Ectopic fat storage: fat content in obesity Adipose tissue as an endocrine organ Plasminogen activator–inhibitor 1 Renin angiotensin system in adipose tissue Visceral obesity and steroid hormone metabolism Glucocorticoid metabolism and obesity 11β-hydroxysteroid dehydrogenase (11β-HSD) Isoenzymes of 11β-HSD 11β-HSD and obesity Sex steroid metabolism and obesity: oestrogen biosynthesis Aromatase Sex steroids and body fat Summary Acknowledgement References

207 207 209 210 210 211 211 212 212 213 214 214 215 216 217 217 218 218 219 220 220 222 224 224 224

9

PPARγ and Glucose Homeostasis Robert K. Semple and Stephen O’Rahilly

237

9.1 9.2

Evidence from cell and rodent models Insights from human studies References

238 251 256

10

Adipokines and Insulin Resistance Daniel K. Clarke and Vidya Mohamed-Ali

269

10.1 10.2 10.3

Obesity and insulin resistance Adipokines implicated in insulin resistance Conclusions References

270 272 280 280

7.7

189 194 196 196

viii

CONTENTS

11

Dietary Factors and Insulin Resistance Jeremy Krebs and Susan Jebb

297

11.1 11.2 11.3 11.4

Introduction The importance of body fatness Specific dietary factors Summary References

297 298 302 310 311

12

Physical Activity and Insulin Resistance Nicholas J. Wareham, Søren Brage, Paul W. Franks and Rebecca A. Abbott

317

12.1 12.2

Introduction Evidence from observational studies of the association between physical activity and insulin resistance Summary of findings from observational studies in adults Summary of findings from observational studies in children and adolescents Mechanisms underlying the association between physical activity and insulin resistance Trials of the effect of physical activity on insulin sensitivity in adults Trials of the effect of physical activity on insulin sensitivity in children and adolescents Evidence of heterogeneity of the effect of physical inactivity on insulin resistance in sub-groups of the population Conclusions References

317

12.3 12.4 12.5 12.6 12.7 12.8 12.9

318 318 340 351 353 374 375 385 386

13

Genetics of the Metabolic Syndrome George Argyropoulos, Steven Smith and Claude Bouchard

401

13.1 13.2 13.3 13.4 13.5 13.6 13.7

Historical perspective Pathophysiology Genetic epidemiology Monogenic disorders Candidate genes Genomic scans Conclusions References

401 404 407 411 414 426 427 427

14

Insulin Resistance and Dyslipidaemia Benoˆıt Lamarche and Jean-Fran¸cois Mauger

451

14.1 14.2 14.3 14.4 14.5 14.6 14.7

Introduction Historical notes Obesity versus the insulin resistance syndrome Hypertriglyceridaemia Reduced HDL cholesterol concentrations Small, dense LDL particles LDL cholesterol levels versus LDL particle number

451 451 453 453 455 457 459

CONTENTS

ix

14.8 14.9

Insulin resistance, dyslipidaemia and the risk of cardiovascular disease Conclusions References

460 461 461

15

Insulin Resistance, Hypertension and Endothelial Dysfunction Stephen J. Cleland and John M. C. Connell

467

15.1 15.2 15.3 15.4 15.5 15.6 15.7 15.8

Introduction Hyperinsulinaemia, insulin resistance and hypertension Possible mechanisms linking insulin with blood pressure Atherosclerosis and insulin resistance Vascular endothelial dysfunction and mechanisms of atherothrombotic disease Direct vascular action of insulin What causes abnormal insulin signalling in metabolic and vascular tissues? Summary and conclusions (Figure 15.8) References

467 467 468 469 469 471 474 477 478

16

Insulin Resistance and Polycystic Ovary Syndrome Neus Potau

485

16.1 16.2 16.3 16.4 16.5 16.6 16.7 16.8 16.9 16.10

Introduction Definition of polycystic ovary syndrome (PCOS) and diagnostic criteria Hyperandrogenism and hyperinsulinism Assessment of insulin resistance in PCOS Gene studies on PCOS Premature pubarche, hyperinsulinism and PCOS Treatment approach with antiandrogens Treatment approach with insulin sensitizers (metformin) Treatment approach with insulin sensitizers (thiazolidinediones) Conclusion References

485 486 489 491 492 495 497 498 501 502 502

17

Syndromes of Severe Insulin Resistance (SSIRs) David Savage and Stephen O’Rahilly

511

17.1 17.2 17.3 17.4 17.5 17.6 17.7

Introduction General biochemical and clinical features of severe insulin resistance Classification of specific syndromes of insulin resistance Primary disorders of insulin action Lipodystrophic syndromes and a lipocentric approach to diabetes Complex genetic syndromes associated with severe insulin resistance Therapeutic options in the syndromes of severe insulin resistance References

511 512 514 515 518 525 526 527

18

Therapeutic Strategies for Insulin Resistance Harpal S. Randeva, Margaret Clarke and Sudhesh Kumar

535

18.1 18.2 18.3

Introduction Obesity and insulin resistance Management of obesity

535 535 537

x

CONTENTS

18.4 18.5 18.6 18.7 18.8 18.9 18.10

Dietary management of obesity Exercise and physical activity Anti-obesity drugs Surgical management of obesity Pharmacological treatment of insulin resistance Insulin sensitizers and cardiovascular risk factors Conclusions References

539 540 540 543 544 551 553 554

19

Drug Therapy for Insulin Resistance – a Look at the Future Bei B. Zhang and David E. Moller

561

19.1 19.2 19.3 19.4

Introduction Targeting molecules within the insulin signal transduction pathway Targeting negative modulators of insulin signalling Targeting obesity and insulin resistance References

561 563 567 569 575

Index

587

Preface Hormone resistance syndromes are typically thought of as rare, usually genetic, disorders with a severe but relatively stereotyped clinical and biochemical profile. While there are syndromes of severe insulin resistance that conform to this description, defective insulin action is of much more pervasive biomedical importance. Even moderate degrees of insulin resistance are closely linked to a range of common diseases, including Type 2 diabetes, polycystic ovary syndrome, obesity and hypertension. Not surprisingly, in recent years, there has been a tremendous increase in interest within the medical and scientific community in understanding the causes, consequences and treatment of insulin resistance. There are several reasons for this. Firstly, we are now witnessing a revolution in unravelling the molecular mechanism of insulin action and in understanding the molecular basis for the various syndromes associated with insulin resistance. Secondly, we are now seeing a global epidemic of Type 2 diabetes that may pose a major threat to international public health. Thirdly, the pharmaceutical and biotechnology industries are investing heavily in the development of new drugs that can improve insulin action. Therefore, we believe that the publication of this book is timely. There is considerable literature available on the subject of insulin resistance. A recent search on Medline revealed more than 20,000 articles on this subject. This information is readily accessible and one might argue that a book such as this one might become outdated as soon as it is published! One guiding principle for this book was, therefore, to bring to the reader not only a synthesis of important information, but also the wisdom of leading researchers and clinicians who are recognised as leaders in their own fields. Each chapter stands independently and is written by one or more experts on the subject. The book is divided into five sections with a total of 19 chapters. Section 1 reviews our current understanding of the normal biology of insulin action and separate chapters cover insulin action in relation to glucose, lipid and protein metabolism. Section 2 explores the pathophysiological mechanisms of insulin resistance, with discussion of the effects of glucose disposal in humans and in animal models. It also reviews the central regulation of energy metabolism and its perturbation, as well as the relationship between fat distribution and insulin action and the role of the nuclear hormone receptor PPARγ in glucose metabolism. Finally, there is a chapter discussing the role of adipose tissuesecreted products in causing insulin resistance. Section 3 examines the role of

xii

PREFACE

genetic and environmental factors that result in insulin resistance, including the effects of dietary factors and physical inactivity. The genetic basis of syndrome X, a common disorder associated with insulin resistance, is described. Section 4 discusses the relationship between insulin resistance and common diseases such as dyslipidemia, hypertension and polycystic ovary syndrome. Finally, Section 5 reviews the clinical management of insulin resistance, covering the many syndromes of severe insulin resistance, currently available therapeutic approaches and possible future options for drug therapy for this condition. Although the book aims to provide comprehensive coverage of the subject, there are some obvious omissions, for example, the relationship between insulin resistance and Type 2 diabetes. Whilst this relationship is alluded to in many places, we have not devoted a full chapter to it as there are several excellent recent reviews on the subject. The book is intended mainly for a specialist readership, although it may prove to be a useful resource for a wide variety of scientists, clinicians and postgraduate students with an interest in any of the related conditions. We hope that regardless of your background as a physician, medical researcher or scientist, you will find this book appropriate for your needs. Finally, all contributing authors have produced outstanding chapters that reflect their expertise and wisdom and spared their valuable time despite tremendous pressures from competing obligations. We wish to thank them all for their support, hard work and friendship. Sudhesh Kumar Stephen O’Rahilly August 2004

List of Contributors Rebecca A. Abbott, MRC Epidemiology Unit, Strangeways Research Laboratory, Worts Causeway, Cambridge CB1 8RN, UK Frank Alford, St. Vincent’s Hospital, Melbourne, Endocrine Unit, 41 Fitzroy Parade, Fitzroy, Victoria 3065, Australia Aresh Anwar, University Hospitals of Coventry and Warwickshire, Walsgrave Hospital, Clifford Bridge Road, Coventry CV2 2DX, UK George Argyropoulos, Pennington Biomedical Research Center, 6400 Perkins Road, Baton Rouge, LA 70808, USA Henning Beck-Nielsen, Odense University Hospital, Department of Endocrinology, Kloevervaenget 64, 5000 Odense C, Denmark Christian Bjørbæk, Division of Endocrinology, Beth Israel Deaconess Medical Center Research North, 330 Brookline Avenue, Boston, MA 02215, USA Claude Bouchard, Pennington Biomedical Research Center, 6400 Perkins Road, Baton Rouge, LA 70808, USA Søren Brage, MRC Epidemiology Unit, Strangeways Research Laboratory, Worts Causeway, Cambridge CB1 8RN, UK Daniel K. Clarke, Adipokines and Metabolism Research Group, Department of Medicine, University College London, 48 Riding House Street, London W1W 7EY, UK Margaret Clarke, Heartlands and Solihull NHS Trust, Birmingham B19 9RA, UK Stephen J. Cleland, Department of Medicine and Therapeutics, University of Glasgow, Glasgow G11 6NT, UK John M. C. Connell, Division of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow G11 6NT, UK Paul W. Franks, MRC Epidemiology Unit, Strangeways Research Laboratory, Worts Causeway, Cambridge CB1 8RN, UK

xiv

LIST OF CONTRIBUTORS

Keith N. Frayn, Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, Oxford OX3 7LJ, UK Laura J. S. Greenlund, Department of Endocrinology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA Stanley M. Hileman, Department of Physiology and Pharmacology, West Virginia University, Morgantown, WV 26506, USA Ole Hother-Nielsen, Odense University Hospital, Department of Endocrinology, Sdr. Boulevard 29, 5000 Odense C, Denmark Susan Jebb, MRC Human Nutrition Research, Elsie Widdowson Laboratory, Fulbourn Road, Cambridge CB1 9NL, UK Fredrik Karpe, Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, Oxford OX3 7LJ, UK Amira Klip, Programme in Cell Biology, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, M5G 1X8, Canada Daniel Konrad, Programme in Cell Biology, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, M5G 1X8, Canada Jeremy Krebs, Wellington Clinical School of Medicine, University of Otago, P.O. Box 7343, Wellington South, New Zealand Sudhesh Kumar, Unit for Diabetes and Metabolism, Warwick Medical School, University of Warwick, Coventry CV4 7AL, UK Benoˆıt Lamarche, Institute on Nutraceuticals and Functional Foods, 2440 Boulevard Hochelaga, Laval University, Quebec, G1K 7P4, Canada Christopher Lelliott, Department of Clinical Biochemistry and Metabolic Medicine, University of Cambridge, Addenbrooke’s Hospital, Hills Road, Cambridge CB2 2QR, UK Jean-Fran¸cois Mauger, Institute on Nutraceuticals and Functional Foods, 2440 Boulevard Hochelaga, Laval University, Quebec, G1K 7P4, Canada Philip G. McTernan, Unit for Diabetes and Metabolism, Warwick Medical School, University of Warwick, Coventry CV4 7AL, UK Gema Medina-Gomez, Department of Clinical Biochemistry and Metabolic Medicine, University of Cambridge, Addenbrooke’s Hospital, Hills Road, Cambridge CB2 2QR, UK Vidya Mohamed-Ali, Adipokines and Metabolism Research Group, Department of Medicine, University College London, 48 Riding House Street, London W1W 7EY, UK

LIST OF CONTRIBUTORS

xv

David E. Moller, Departments of Molecular Endocrinology and Metabolic Disorders, Merck Research Laboratories, Rahway, NJ 07065, USA K. Sreekumaran Nair, Department of Endocrinology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA Stephen O’Rahilly, Department of Clinical Biochemistry and Medicine, University of Cambridge, Addenbrooke’s Hospital, Hills Road, Cambridge CB2 2QQ, UK Neus Potau, Hormonal Laboratory, Hospital Matemo-Infantil Vail d’Hebron, Passeig Vail d’Hebron, 119–129, 08035 Barcelona, Spain Harpal S. Randeva, Molecular Medicine Research Group, Biomedical Research Institute, Biological Sciences, University of Warwick, CV4 7AL, UK Assaf Rudich, Programme in Cell Biology, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, M5G 1X8, Canada David Savage, Department of Clinical Biochemistry and Medicine, University of Cambridge, Addenbrooke’s Hospital, Hills Road, Cambridge CB2 2QQ, UK Robert K. Semple, Department of Clinical Biochemistry, University of Cambridge, Addenbrooke’s Hospital, Hills Road, Cambridge CB2 2QR, UK Ken Siddle, Department of Clinical Biochemistry, University of Cambridge, Addenbrooke’s Hospital (Box 232), Hills Road, Cambridge CB2 2QR, UK Stephen Smith, Pennington Biomedical Research Center, 6400 Perkins Road, Baton Rouge, LA 70808, USA Antonio J. Vidal-Puig, Department of Clinical Biochemistry and Metabolic Medicine, University of Cambridge, Addenbrooke’s Hospital, Hills Road, Cambridge CB2 2QR, UK Nicholas J. Wareham, MRC Epidemiology Unit, Strangeways Research Laboratory, Worts Causeway, Cambridge CB1 8RN, UK Bei B. Zhang, R80W180, Merck Research Laboratories, P.O. Box 2000, 126 E. Lincoln Avenue, Rahway, NJ 07065, USA

1 The Insulin Receptor and Downstream Signalling Ken Siddle

1.1 Introduction Insulin regulates diverse physiological processes in mammals, including membrane transport, intermediary metabolism and cell growth and differentiation. These actions involve rapid effects on subcellular membrane traffic, enzyme activity and protein synthesis as well as longer term actions on gene transcription. The most conspicuous metabolic effects of insulin are associated with skeletal muscle, adipose tissue and liver1 but its physiologically important actions are by no means confined to such tissues, as evidenced by the phenotypes of mice with tissue-specific knockout of insulin receptor in brain, pancreatic β-cells or endothelia.2 Insulin signalling pathways have also been implicated in accelerating the ageing process.3, 4 Understanding of the signalling pathways by which the insulin receptor is able to influence so many and such diverse cellular targets is still far from complete, although the last 20 years have seen major advances. A surprising feature is that to date the only signalling component known to be unique to insulin action is the insulin receptor (IR) itself, which is widely expressed in mammalian cells, although levels vary greatly between cell types. The IR binds insulin with high affinity and specificity, and transmits a signal to the cytosol via its intrinsic tyrosine-specific protein kinase activity. This phosphorylates a number of intracellular substrates, most especially the so-called insulin receptor substrates (IRSs), which recruit and activate an array of signalling proteins containing Src homology-2 (SH2) domains. Two signals have been shown to play major roles in insulin action, namely those transmitted by the enzyme phosphoinositide 3-kinase (PI 3-kinase), which generates PtdIns(3,4,5)tris-phosphate at Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

2

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

the cytosolic face of membranes, and the guanine nucleotide exchange factor Grb2/Sos, which activates the small G-protein Ras. These act as switch mechanisms to change the ‘currency’ of signalling from tyrosine phosphorylation to serine/threonine phosphorylation of target proteins. However, these signals, and the downstream signalling cascades involving protein kinase B and mitogenactivated protein kinases (MAPKs), have been implicated in the actions of a wide variety of hormones and growth factors as well as specific actions of insulin. This chapter will focus particularly on the IR and its substrates, and consider more briefly what is known about downstream signalling pathways, which have been reviewed in detail elsewhere.5 – 9

1.2

Insulin receptor structure and function

The insulin receptor family The IR is a large, heterotetrameric, transmembrane glycoprotein containing two types of subunit, designated α (Mr 140 kDa) and β (95 kDa), linked by disulphide bonds in a β–α–α–β configuration. The principal members of the IR family of receptor tyrosine kinases are represented in Figure 1.1, together with their high affinity ligands. It is possible that IRR may also form hybrids with IR, although because of the very restricted distribution of IRR these are unlikely to be of major significance. It is likely that the two isoforms of IR will also form heterodimers, although this has recently been questioned.22 It is assembled from a single polypeptide pro-receptor, by dimerization, proteolytic cleavage and glycosylation within the endoplasmic reticulum and Golgi apparatus, before trafficking of mature receptor to the plasma membrane. The IR was initially defined by radioligand binding studies, which provided information on affinity, specificity and tissue distribution. It was shown to bind insulin with high (sub-nanomolar) affinity, marked pH dependence (decreased affinity even at mildly acid pH) and unexpectedly complex kinetics (manifested as negative co-operativity).10 The first real insight into signalling mechanisms came with the demonstration that the receptor possessed intrinsic, tyrosine-specific protein kinase activity that was stimulated by insulin binding.11 Soon afterwards, cloning of the pro-receptor cDNA12, 13 and the receptor gene14 opened the door to analysis of receptor structure and function, which is now understood in considerable detail.15 – 18 The IR gene consists of 22 coding exons spanning 120 kilobases on chromosome 19p13.2. Exon 11, of just 36 nts, is subject to alternative splicing, resulting in the generation of two isoforms designated IR-A (Ex 11−) and IR-B (Ex 11+), which differ in sequence by 12 amino acids at the carboxyl-terminus of the α-subunit (the numbering used here includes the exon 11 sequence). The relative proportions of the two isoforms differ between tissues, IR-A predominating in brain and IR-B in liver, while both are found in similar amounts in skeletal muscle and placenta.19, 20 The isoforms differ modestly but significantly

High affinity ligands

Intracellular

S

S

Extracellular

IR-A

S S

S S

β

α

Insulin, IGF-II

β

α

S

S S

S

Figure 1.1

Insulin

IR-B

S S

S S

S

S

IGF-I, IGF-II

Type 1 IGFR

S S S

S S

S

The insulin receptor family

S

S

S S

–

IRR

S S

S S

S

S

S S

IGF-I, IGF-II

IR/IGFR hybrid

S

S

S S

S

S

INSULIN RECEPTOR STRUCTURE AND FUNCTION

3

4

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

with respect to their binding affinity for insulin and IGFs, and this is perhaps not surprising in view of the proximity of the variable sequence to a known major binding epitope at the α-subunit carboxyl-terminus. More controversially, it has been suggested that the short peptide sequence encoded by exon 11 also acts as a sorting signal, causing the isoforms to localize to different plasma membrane microdomains from which they activate distinct signalling cascades.21, 22 The IR gene is transcribed as mRNAs of 7–11 kilobases, which include substantial 5
and 3
-untranslated regions either side of the coding sequence. (NCBI database references for complete IR (InsR) cDNA and protein sequences are human NM 000208, mouse NM 010568 and rat NM 017071). The deduced sequence of the human IR precursor contains 1382 (or 1370) amino acids, including a signal sequence of 27 amino acids which is absent from mature receptor. A tetrabasic RKRR motif marks the site of proteolytic cleavage to generate the α- and βsubunits, of 731 (719) and 620 amino acids respectively. In the mature receptor the α-subunit is wholly extracellular and contains the ligand binding site, while the β-subunit contains a single predicted membrane-spanning segment and an intracellular tyrosine kinase domain. The extracellular portion of IR is heavily glycosylated, and some glycosylation is essential for normal receptor function.23 Disulphides between α-subunits are contributed by Cys524 and Cys682/3/5,24 and can readily be reduced in vitro to generate half-receptors that bind insulin with decreased affinity. In contrast the α–β disulphide between Cys647 and Cys872 can be reduced only under denaturing conditions. Experimental perturbation of glycosylation,24 proteolytic cleavage25 and disulphide bonding26 can profoundly affect receptor function. There is no compelling evidence that these processes are modulated under physiological conditions in vivo, although it remains possible that there are circumstances where this does occur. Just as insulin is structurally related to the insulin-like growth factors, so the IR is similar in structure and function to the type 1 IGF receptor (IGFR), with which it shares approx 60 per cent amino acid sequence identity.27 (The type 2 IGF receptor is an unrelated protein,28 which is not thought to have any signalling function but may have a role in clearance of IGF from the circulation.) Like the IR, the IGFR is very widely expressed, albeit at different levels. There is significant expression of IGFR in skeletal muscle, but very low levels in hepatocytes and adipocytes. The very different biological roles of IR and IGFR are emphasized by the distinct phenotypes of mouse knockout models. Mice lacking IR exhibit only slight (10 per cent) growth retardation at birth, but die within days as a result of uncontrolled hyperglycaemia and ketoacidosis,2 although lack of IR causes more severe growth retardation in humans. In contrast, mice lacking IGFR are severely growth deficient (approximately 45 per cent of normal size) and developmentally retarded and die at birth of respiratory failure.29 However, the functions of the two receptors are not completely

INSULIN RECEPTOR STRUCTURE AND FUNCTION

5

distinct as shown by the efficacy of IGF-I in reducing hyperglycaemia in human subjects lacking functional IR.30 A third member of the IR/IGFR family is the insulin-receptor-related receptor (IRR).31 Although this has a similar degree of homology to IR and IGFR as these receptors do to each other, the IRR does not bind either insulin or IGFs,32 and no ligand has yet been identified for this receptor. Expression of IRR is much more restricted than that of IR and IGFR, but it is found in kidney, neural tissue, stomach and pancreatic beta cells. Mice lacking IRR appear phenotypically normal,33 although there is evidence that, along with other members of the IR family, IRR contributes in a non-redundant fashion to testicular development in mice.34 Insulin binds to IGFR with low affinity, which would not be sufficient to permit significant activation by insulin in vivo under normal physiological conditions, but could become important under pathological conditions associated with hyperinsulinaemia. Indeed, it has been suggested that such ‘specificity spillover’ might contribute to features of insulin resistance syndromes such as acanthosis nigricans and polycystic ovaries35, 36 and it may well be responsible for effects of insulin on growth of cultured cells. The converse phenomenon, stimulation of the IR by IGFs, may be of greater physiological significance. Early studies of ligand specificity, which gave rise to the notion that IGFs bound only with low affinity to IR, commonly used rat liver as a source of receptors and such studies reflected the properties of the IR-B isoform. In fact, although the isoforms differ only slightly in affinity for insulin itself, the A isoform has substantially higher affinity for IGFs, particularly IGF-II, than the B-isoform.37, 38 Indeed the affinity of IR-A for IGF-II is comparable to that of the type 1 IGFR, and it appears that IR-A makes a significant contribution to mediating biological activity of IGF-II, both in vivo and in vitro.39, 40 When IR and IGFR are expressed in the same cells, they are can form hybrid structures containing an insulin half-receptor, disulphide linked to an IGF halfreceptor (Figure 1.1).41 – 43 Surprisingly heterodimerization of proreceptors to form hybrids seems to occur with similar efficiency to homodimerization to form classical receptors, so the proportion of receptors existing as hybrids is largely a reflection of the relative expression levels of the individual receptors.43 – 45 Hybrid receptors thus occur commonly in vivo, and in tissues such as heart and skeletal muscle, where IR is expressed at higher levels than IGFR, hybrids account for the majority of high affinity ‘IGF receptors’.44 Conversely, when IGFR is in excess, as in fibroblasts, the majority of IR is drawn into hybrids. It remains possible that mechanisms exist that promote or inhibit assembly of hybrid receptors but these have not been demonstrated. Hybrid receptors bind IGF with high affinity, comparable to classical type 1 IGFR, and would therefore be expected to contribute significantly to mediating IGF actions in vivo. However, hybrids bind insulin with relatively low affinity, especially those incorporating the IR-B isoform,46, 47 and are unlikely to contribute significantly to

6

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

insulin signalling at physiological insulin concentrations. In fact if IR are incorporated into hybrids this would be expected to decrease cellular sensitivity to insulin, and it has been suggested that an increase in the proportion of hybrid receptors in skeletal muscle of obese and diabetic subjects may contribute to insulin resistance.48, 49 However, in classical insulin target tissues such as liver, fat and muscle the proportion of IR in hybrids is always likely to be small and the potential for changes in IGFR expression to influence insulin sensitivity must be correspondingly slight. It is unclear whether hybrid receptors have unique signalling properties, which might influence the nature of cellular responses. It would be expected that binding of either insulin or IGF would lead to activation of tyrosine kinase activity within both β-subunits of hybrids.50 As discussed below, the signalling competencies of IR and IGFR are very similar but probably not identical. In this context, hybrids might in principle have the signalling properties of both IR and IGFR, or even additional novel properties reflecting synergy between the individual half-receptors.

The IR extracellular domain: ligand binding Apart from the intrinsic interest of unravelling the molecular basis of ligand binding and the mechanism of receptor activation, understanding of ligand–receptor interactions could facilitate the design of insulin mimetics with therapeutic potential. However, the large size of the IR has presented a considerable analytical challenge. Molecular modelling based on sequence analysis predicts that the extracellular portion of each half-receptor contains six distinct structural domains, while three intracellular domains are recognized.51 The N-terminal, membrane-distal half of the extracellular receptor contains two β-helical L domains flanking a cysteine-rich (CR) region (Figure 1.2). The structural domains of the IR are shown in Figure 1.2: L1 and L2 are β-helical domains; CR is the cysteine-rich domain; Fn0, Fn1 and Fn2 are fibronectin type III repeats; the inserted region within Fn1 includes the site of cleavage between α- and β-subunits; JM is the juxtamembrane region; TK is the tyrosine kinase domain; CT is the carboxyl-terminal domain. Positions of inter-subunit disulphide links and ligand binding epitopes are as indicated. The corresponding portion of the IGFR, expressed as a recombinant protein, has been crystallized and its structure has been determined.52 This reveals the L domains and disulphide-bonded modules of the CR domain surrounding a putative ligandbinding cavity (although this IGFR fragment does not itself bind IGFs). The orientation of the L domains within the crystal may not be the same as in native receptor, and of course differences in conformation between IR and IGFR might contribute to binding specificity. However, it is safe to assume that the structures of the L1/CR/L2 domains of the IR are similar to those of the IGFR. The remaining extracellular portion of both IR and IGFR is believed to consist of three fibronectin type III domains, each folded as a seven-stranded β-sandwich.

L1

CR

L2

Fn1′′

Fn2

Figure 1.2 Insulin receptor structural domains

Fn1/insert

S

S

Fn1′

Extracellular

Fn0

S

S

S

S

S

S

Ligand binding epitopes

JM

Intracellular

TK

CT

INSULIN RECEPTOR STRUCTURE AND FUNCTION

7

8

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

However, the limitations of theoretical modelling are illustrated by the fact that different groups who predicted structures for the first such domain (usually referred to as the Fn0 domain) assigned different β-strands within the FnIII fold,53, 54 and therefore proposed different positions for the inter-subunit disulphide bond formed by Cys524. The central FnIII domain (usually referred to as Fn1) contains a large inserted region as a loop between β-strands, for which no particular secondary or tertiary structure is predicted. In the middle of this are the sequence encoded by the alternatively spliced Exon 11 and the site of cleavage between α- and β-subunits. The Fn1 domain is therefore assembled from sequences within the C-terminal region of the α-subunit and the N-terminal region of the β-subunit, so that the α- and β-subunits are not readily dissociated as independent proteins but are held together by strong non-covalent forces as well as disulphide bonds. The residues in insulin that are important for receptor binding have been intensively studied by comparing the properties of insulins from different species, by chemical modification and by mutational analysis and alanine scanning.10, 55 These studies indicate that two surfaces of the insulin molecule are important for receptor binding.15 The ‘classical’ binding surface contains a number of hydrophobic residues (including B24Phe and B25Phe), while the second binding surface is more polar. Both surfaces are essentially ‘conformational’ in nature and include residues from disparate regions of primary sequence. A screen of large, random, phage-displayed peptide libraries has identified novel peptides that bind to the IR at or close to the insulin binding site and presumably mimic critical aspects of the insulin surface.56 Indeed derivatives of these peptides function as insulin mimetics and activate the receptor.57 It remains to be seen whether it will be possible to model non-peptide mimetics using information derived from the study of such peptides. The task of identifying residues in the IR/IGFR that contact ligand is more difficult, given the very large size of the receptors. The problem has been approached by cross-linking insulin analogues, constructing IR/IGFR chimeras, and by mutational analysis and alanine scanning (as reviewed in 9, 15 and 16). Four distinct binding epitopes have been identified, within the L1, CR, L2 and Fn1 insert domains. Residues in the L1 and L2 domains of IR, especially Phe39, are important for insulin specificity, although IGFR specificity for IGF-1 is more dependent on residues in the CR domain. These putative binding epitopes flank the cavity enclosed by the L1, CR and L2 domains in the crystal structure of the IGFR fragment described above, and this cavity is of appropriate dimensions to accommodate a molecule of ligand.16 Although neither this IGFR fragment nor the corresponding IR fragment bind ligand, addition to either construct of the fourth binding epitope, a short peptide sequence from the α-subunit carboxyl-terminus, confers ligand binding of moderate affinity.58 Remarkably, this peptide confers binding ability on N-terminal fragments not only when fused directly but even when added as a free peptide.59 Mutational

INSULIN RECEPTOR STRUCTURE AND FUNCTION

9

analysis also shows that this sequence, and particularly two Phe residues within it, makes a major contribution to binding affinity without influencing specificity for insulin versus IGF-I.60 Cross-linking studies show that this sequence is in proximity to the PheB25 of bound insulin, suggesting that hydrophobic interactions between these regions provide a major part of the binding energy. Remarkably, the nearby PheB29 lies close to the L1 domain of the IR,15 indicating that the N- and C-terminal domains of the receptor α-subunit are closely juxtaposed within the native structure. It is not yet clear how individual binding epitopes are assembled in three dimensions to create the high affinity, negatively co-operative insulin binding characteristic of native IR. Highest affinity binding is seen only in the context of dimeric constructs, and the preferred model of ligand binding is one in which both α-subunits contribute asymmetrically to the insulin binding site, and a single molecule of bound insulin contacts both halves of the receptor15 (Figure 1.3). Figure 1.3 shows a hypothetical model of insulin binding to IR, as viewed from perpendicular to the extracellular membrane face. The two α-subunits are aligned antiparallel, with binding epitopes e1 and e2 contributed by L1 and L2 domains respectively (other binding epitopes are not shown). The model is such that only a single molecule of insulin binds with high affinity, and cross-links the α-subunits. Such a model is compatible with many observations concerning the structural requirements and kinetics of insulin binding, not least the simple fact that, in spite of its dimeric structure, the IR binds only a single molecule of insulin with high affinity. Electron microscopic images of gold-labelled insulin bound to the receptor are also broadly consistent with this model.17 A precedent for such a binding mechanism exists in the complex of growth hormone with its receptor.61 However, crystallization of the EGFR in complex with ligand reveals a different binding mechanism, in which L1/CR/L2 receptor domains dimerize back to back and each bind a molecule of ligand.62, 63 Confirmation of the insulin binding mechanism must await crystallization of insulin–IR complexes.

The IR intracellular domain: tyrosine kinase activation and autophosphorylation Ligand binding induces conformational changes in the extracellular portion of the receptor, which in turn must alter the conformation of, or relationship between, the intracellular domains in a manner that promotes autophosphorylation. The activation of the tyrosine kinase domains depends largely on reciprocal intramolecular trans-phosphorylation between β-subunits.50, 64, 65 Both strict intramolecular phosphorylation (within β-subunits)66 and intermolecular phosphorylation (between hetero-tetrameric receptors)67 have also been demonstrated, although the latter appears not to be sufficient to stimulate substrate kinase activity.68

CR

L1

L2

e1

e2

L2′

CR′

insulin

Fn

Figure 1.3 Insulin receptor ligand binding model (adapted from reference 15)

Fn

L1′

10 THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

INSULIN RECEPTOR STRUCTURE AND FUNCTION

11

Within the intracellular portion of the IR, the tyrosine kinase domain proper, of approximately 250 amino acids, is flanked by a juxtamembrane (JM) domain of approximately 50 amino acids and carboxyl-terminal (CT) domain of approximately 100 amino acids (Figure 1.4). The principal phosphorylation sites are indicated in Figure 1.4, with their functional significance where known, together with the critical lysine 1030 required for ATP binding and catalytic activity. The crystal structure of the kinase domain has been determined.18 There are sites of tyrosine autophosphorylation in all three domains, as well as multiple potential sites of serine phosphorylation.69 However, while tyrosine phosphorylation sites have been well defined, the extent and significance of serine phosphorylation remains unclear. The IR tyrosine kinase domain has been crystallized in both basal, unphosphorylated, and activated, phosphorylated, states, and this has provided important insights into the mechanisms of catalysis and regulation.18 The bi-lobed structure is broadly typical of other protein kinases. The active site lies in a cleft between the two lobes and includes Lys1030 and other residues important in ATP binding. The size and hydrophobicity of this cleft confers specificity for phosphorylation of tyrosine rather than serine residues. In the basal state the cleft is effectively closed by a regulatory peptide loop, and the active site is inaccessible to peptide substrates. Autophosphorylation of this loop, on tyrosines 1158, 1162 and 1163, causes it to swing away from the cleft, allowing access of other substrates to the active site. The IGF receptor tyrosine kinase has a very similar structure and activation mechanism.70, 71 In addition to its critical role in tyrosine kinase activation, autophosphorylation also facilitates recruitment of substrates and adaptor proteins. Phosphorylation of a conserved NPEY motif in the JM domain of IR and IGFR creates a binding site for the PTB (phosphotyrosine-binding) domains of insulin receptor substrates (IRSs) and Shc proteins.72, 73 IRS-2 additionally has a region (the KRLB domain) that binds directly to the phosphorylated kinase regulatory loop.74, 75 The substrate APS (adaptor with PH and SH2 domains) also interacts, via its SH2 domain, with phosphotyrosine residues of the activation loop,76 as does the non-substrate adaptor Grb10.77 The CT domain of IR contains two sites of autophosphorylation, Y1328 and Y1334, of which only the latter is conserved in IGFR. These sites bind a number of SH2 domain-containing adaptors in vitro78, 79 although the contribution to insulin signalling in vivo may be small. Mutation of these sites or deletion of a larger segment of the CT domain has been reported to influence signalling specificity, and particularly to affect the relative efficiency of metabolic versus mitogenic signalling by the IR, although this has not been a consistent finding (reviewed in reference 69). The role of these sites in IR function thus remains unclear. Autophosphorylation also acts as a trigger for internalization of the activated receptor/insulin complex,80 which is important both in terminating the insulin signal and in insulin degradation (this being the major mechanism by which insulin is cleared from the circulation, particularly by the liver). The

Figure 1.4

CARBOXYL-TERMINAL REGION

TYROSINE KINASE DOMAIN

JUXTAMEMBRANE REGION

EXTRACELLULAR REGION

Insulin receptor intracellular domain

Adaptor binding ??

Tyrosine kinase activation Substrate binding (APS) Adaptor binding (Grb10)

Y1158 Y1162 Y1163

Y1328 Y1334

ATP binding

K1030

S1037

S1305 S1327 T1348

Substrate binding (IRS, Shc)

Y972

S967

12 THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

INSULIN RECEPTOR STRUCTURE AND FUNCTION

13

endocytic machinery recognizes β-turn tyrosine motifs and/or dileucine motifs in the receptor juxtamembrane domain.81 – 83 Phosphorylation of the juxtamembrane tyrosines is not required for internalization, but ligand binding and/or autophosphorylation at other sites causes conformational change that exposes these motifs, triggering movement of receptor into clathrin-coated pits. Coated vesicles deliver receptor to early endosomes, where acidification causes rapid dissociation of bound insulin, which is then degraded by specific endosomal and/or cytosolic proteases.84, 85 Endosomal IR may contribute transiently but significantly to signalling, both in terms of prolongation of signal and access to intracellular substrates.85 Indeed, phosphorylation of Shc (but not IRSs) is dependent to some extent on receptor internalization.86 – 88 Once the stimulus of bound ligand is removed the action of phosphotyrosine phosphatases results in rapid inactivation and receptor is largely recycled to the plasma membrane. Several different phosphatases act on IR in vitro, but PTP1B is of particular important in vivo.89, 90 Indeed, there is considerable interest in PTP1B as a drug target for treatment of diabetes and obesity.91 – 93 The IR is phosphorylated on serine/threonine as well as tyrosine residues, both in response to stimulation by insulin itself and as a result of cross-talk from other signalling pathways, and it has been suggested that such phosphorylation is inhibitory to IR signalling. Multiple sites of phosphorylation have been identified (see for example references 94–97), and phosphorylation by protein kinase C isoforms has been associated with inhibition of receptor function.96, 98 – 100 It has been suggested that serine/threonine phosphorylation of IR might mediate glucose-induced inhibition of insulin signalling101, 102 and contribute to insulin resistance associated with obesity103 and polycystic ovary syndrome.104 However, it has proved difficult to establish a link between inhibition of function and phosphorylation of specific sites,69, 105 and the kinases responsible for IR phosphorylation in vivo have not been well defined. Phosphorylated IGFR binds 14–3–3 proteins,106, 107 but this is probably dependent on the IGFR-specific cluster serines 1280/81/82/83, and no evidence has been presented for a comparable interaction of 14–3–3 with IR. Overall, serine/threonine phosphorylation of IR is a somewhat neglected field, in which final conclusions remain to be drawn.

Regulation of insulin receptor expression The level of IR expression is an important factor determining sensitivity of cells to insulin, and is probably dependent on controls operating at the level of both transcription and translation of mRNA. The promoter region of the IR gene has been characterized and binding sites have been identified for a number of transcription factors. Such studies have provided some insights into mechanisms that may be responsible for the almost ubiquitous expression of IR,108 – 111 the abundant expression in muscle, liver and fat,109, 110, 112 – 115 the

14

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

regulatory effects of hormones,116, 117 and increased expression in some cancer cells.118, 119 However, understanding of transcriptional regulatory mechanisms that underlie the wide divergence in levels of receptor expression in different cell types, or the modulation of receptor expression under different physiological conditions, is still far from complete. The mRNAs encoding both the IR and IGFR have unusually long and potentially structured 5’UTRs. These may inhibit the normal cap-dependent scanning mechanism of mRNA translation, and/or contain internal ribosome entry sites (IRESs), thus creating the potential for regulation of protein expression at a translational level through the involvement of additional factors not required for bulk protein synthesis. The 5’UTR of the IGFR mRNA has been shown to contain a functional IRES,120 and it is very likely that this is also the case for the IR mRNA. It remains to be explored whether expression of either receptor is modulated at a translational level under physiological conditions. The level of receptor expression must also depend on its rate of degradation. As outlined above, activated insulin/receptor complexes are rapidly internalized through clathrin-coated pits and delivered to an endosomal compartment. The receptors largely recycle back to the plasma membrane, while insulin is degraded.80 It has long been known that when cells are exposed to high concentrations of insulin for long periods receptor degradation is accelerated and expression is down-regulated,121 but IR degradation remains poorly understood. It is possible that ubiquitination is involved as has been shown to be the case with other receptors,122, 123 and this might be influenced by adapter proteins that bind to activated IR. Thus it has been proposed that both APS (through association with c-Cbl124 ) or Grb10 (through association with NEDD4125 ) may mediate receptor ubiquitination, as well as modulating signalling in other ways. There is no evidence that binding affinity of IR is susceptible to direct regulation in a way that might affect insulin sensitivity in vivo. Certainly, affinity is not thought to be influenced by intracellular phosphorylation events. Affinity regulators have from time to time been proposed126 but have not been well characterized or shown to be physiologically important. Likewise, the significance of MHC class I molecules127 or membrane glycoprotein PC-1128 as modulators of IR function remains uncertain. In principle, binding affinity might be indirectly influenced by alternative mRNA splicing events affecting the proportions of IR-A and B isoforms. Data concerning expression of IR isoforms in obesity or diabetes have been inconsistent but in general have not shown significant changes.20, 129 – 133 On the other hand, aberrant regulation of IR alternative splicing has been associated with insulin resistance in myotonic dystrophy.134 Changes in IGFR expression would also be expected indirectly to affect insulin sensitivity, by altering the proportion of IR in hybrids, which bind insulin with lower affinity than IR.47 There is evidence that the level of hybrids is increased in skeletal muscle of obese and diabetic subjects,48, 49 but the hybrid fraction

15

INSULIN RECEPTOR SUBSTRATES

of IR is small under all conditions and changes are unlikely to contribute to insulin resistance.

1.3

Insulin receptor substrates

IRS proteins The IR tyrosine kinase is a remarkable enzyme that not only catalyses autophosphorylation at six different sites, but also phosphorylates multiple sites on multiple intracellular substrates (Figure 1.5). In general these substrates do not themselves have catalytic activity, but rather their phosphorylation creates binding sites for adapter proteins or enzymes that propagate the signal. Signalling by many other receptor tyrosine kinases relies substantially on receptor autophosphorylation for recruitment of downstream signalling proteins. Although the IR also employs this strategy to some extent, its use of separate intracellular substrates avoids the constraints of stoichiometry and subcellular location inherent in autophosphorylation-dependent signalling. PtdInsP2 IRS-1 IRS-2

PH

IR-JM

p85-SH2

Grb2-SH2

pY pY

pY

SHP2-SH2 pY

pY

PTB

IR-JM

Grb2-SH2 pY

??

pY

Shc p52/p46 PTB

??

SH2

??

IR-TK

IR-TK

Cbl-SH2 pY

APS Pro

PH

BPS

SH2

APS-pY

CAP-SH3 Crk-SH2 pY

pY

c-Cbl SH2

Ring

Pro

Figure 1.5 Insulin receptor substrates: schematic representation of insulin receptor substrates, their tyrosine phosphorylation sites (pY), and their interactions with other proteins

16

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

The so-called insulin receptor substrates (IRSs) play a central role in mediating the major actions of insulin.5, 135 IRS proteins were first identified by anti-phosphotyrosine blotting of insulin-treated cells and tissues, and the original name pp185 reflected their apparent mass of 180–190 kDa as seen on polyacrylamide gels.136 pp185 was shown to be widely distributed but especially prominent in muscle and liver, and to be rapidly phosphorylated in response to insulin/IGF stimulation. Subsequent molecular cloning revealed that ‘pp185’ consisted of two distinct proteins, now designated IRS-1 and IRS-2,137, 138 and additional related proteins have since been identified. The IRS family is defined by common structural features, namely tandem pleckstrin homology (PH) and phospho-tyrosine binding (PTB) domains at the N-terminus and, in the rest of the protein, multiple potential sites of tyrosine phosphorylation including many in YxxM motifs. The IRSs are also substrates for the IGFR tyrosine kinase, and for Janus kinases (JAKs) associated with cytokine receptors.139, 140 This specificity is governed largely by the PTB domain interaction with phosphorylated NPxY motifs within an appropriate consensus sequence on the respective receptors,73, 141, 142 although it does not follow that different tyrosine kinases will necessarily phosphorylate the same spectrum of sites with equal efficiency. The PH domain of IRSs is also important for their efficient phosphorylation and downstream signalling,143 – 145 most likely due to its interaction with membrane phospholipids. The crystal structure of IRS-1 PH/PTB domains in complex with phosphorylated peptide has been determined.146, 147 The PH and PTB domains share very similar structural topology, although residues interacting with phosphates in the respective binding partners are distinct. IRS-1 and 2 each have as many as 18 potential tyrosine phosphorylation sites, of which no fewer than nine are in YxxM motifs that are preferred binding sites for the tandem SH2 domains of the p85 adaptor subunit of class 1a PI 3-kinase.135 Thus phosphorylated IRS-1 and -2 act as highly efficient scaffolds in the recruitment of PI 3-kinase activity. Both IRS-1 and IRS-2 also have binding sites for SH2 domains of the adaptor Grb2 and the phosphotyrosine phosphatase SHP-2. Other proteins also bind to phosphorylated IRSs via SH2 domains, including the adaptors Nck and Crk and the tyrosine kinase Fyn,135 but their roles in insulin action are unclear. IRSs are nominally soluble proteins but in fact are substantially localized to membranes or cytoskeletal elements. This association may depend on PH domain interaction with membrane phospholipids144, 148 and/or specific proteins,149, 150 and is influenced by phosphorylation of IRSs on serine residues.151, 152 Membrane targeting of IRSs may be important in bringing associated proteins such as PI 3-kinase and Grb2/Sos into proximity with their substrates, PtdIns(4,5)bisphosphate and Ras. Following termination of insulin stimulation, phosphotyrosine phosphatases act to dephosphorylate and inactivate IRSs. The importance of IRS-1 and IRS-2 in the actions of insulin and IGFs is confirmed by the phenotype of mice with targeted gene disruptions. Mice lacking

INSULIN RECEPTOR SUBSTRATES

17

the IRS-1 gene are substantially growth retarded but exhibit only mild insulin resistance.153, 154 However, compound heterozygotes with deletion of just one copy of the IRS-1 gene together with one copy of the IR gene are profoundly insulin resistant, developing severe hyperinsulinaemia and in some cases frank diabetes.155 Mice lacking the IRS-2 gene display only modest growth retardation, but a severe metabolic phenotype, a high proportion becoming diabetic due to a combination of insulin resistance (predominantly in liver) and failure of β-cell compensation.156 Studies with IR/IRS double mutant mice suggest that IRS-1 is the more important mediator of insulin action in muscle and IRS2 in liver.157 IRS-2 also plays an important role in hypothalamic pathways integrating feeding behaviour, energy homeostasis and female reproduction.158 Overall, the data from IRS overexpression studies and knockouts indicate some functional redundancy between IRS-1 and IRS-2, but also specific functions that may reflect their relative expression in individual tissues and/or intrinsic differences in signalling capacity.5, 159 As IRS-1 and IRS-2 similarly recruit PI 3-kinase, Grb2 and SHP2 to conserved phosphorylation sites, any differences in their signalling presumably depend on more subtle properties, affecting for instance their subcellular distribution or recruitment of other adaptors. Two further members of the IRS family have been identified, which show sequence similarity to IRS-1 and -2 but more restricted distribution. IRS-3 is a protein of approximately 60 kDa expressed in liver and adipose tissue in rodents.160 However, humans appear to lack a functional IRS-3 gene.161 Even in mice IRS-3 gene deletion does not result in any obvious phenotype in terms of glucose homeostasis or growth,162 although the double knockout of IRS1 and IRS-3 indicates that IRS-3 can function in adipogenesis.163 IRS-4 is a protein of similar size to IRS-1 and 2, with the potential to bind PI 3-kinase and Grb2.164 It was identified initially in an embryonic kidney cell line and has a very restricted distribution in vivo, being expressed predominantly in brain and thymus. Nevertheless, IRS-4 knockout mice do exhibit mild defects in glucose homeostasis, growth and reproduction.165 IRS-1 and 2 contain a very large number of potential sites of serine phosphorylation, as defined by scanning for consensus sequences that could be substrates for known kinases. A multitude of kinases phosphorylate these IRSs in vitro and/or in intact cells, including conventional, atypical and novel PKCs, PKB/Akt, ERK/MAPK, mTOR, JNK (c-Jun N-terminal kinase), IKKβ (inhibitor kappa B kinase), AMPK (AMP-dependent protein kinase), PI 3kinase, casein kinase II and GSK3 (glycogen synthase kinase-3) (reviewed in references 166–169). Serine phosphorylation can modulate IRS function either positively or negatively (Figure 1.6). A degree of ‘basal’ serine phosphorylation, at unidentified sites, facilitates IRS-1 tyrosine phosphorylation,170 while phosphorylation on serines 302 and 789 also appears to enhance tyrosine phosphorylation and insulin signalling.171 – 173 However, interest has focused especially on serine phosphorylation of IRS proteins as an inhibitory mechanism,

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

895 YVNIE

608 YMPMS 628 YMPMS 658 YMMMS

Grb2

SHP2 PTPase 1222 YASIS

p85 (PI 3-kinase)

1172 YIDLD

18

IRS-1

mTOR

IKKβ

PKB

PKC

insulin lipids

S 612 S 632 S 662 JNK

MAPK mTOR

PKC

TNFα

S 789

PTB S 307

PH

AMPK

PKB

lipids insulin exercise

Figure 1.6 IRS-1 phosphorylation sites: the major sites of tyrosine and serine phosphorylation on IRS-1 are indicated, together with some of the kinases and stimuli responsible for serine phosphorylation (adapted from reference 168)

which may normally function as a feedback control but when inappropriately stimulated can cause insulin resistance.166 – 169 Relevant sites of regulatory phosphorylation on IRS-1 include serines 307, 612, 632 and 789 (the amino acid numbering most often encountered corresponds to the sequence of rat IRS-1: corresponding residues in human IRS-1 are serines 312, 616, 636 and 794 respectively). Serine phosphorylation can inhibit IRS function in a several different ways, and binding of 14–3–3 or SOCS proteins may play a role in some of these processes.106, 174 – 177 First, serine phosphorylation may inhibit adjacent tyrosine phosphorylation and/or SH2 domain binding so that specific downstream signalling pathways are not engaged. For instance, serines 612 and 632 are adjacent to tyrosines 608 and 628, which are known to be important in binding PI 3-kinase.135, 178 Phosphorylation of serine 612 apparently underlies the inhibition of IRS-1-dependent PI 3-kinase signalling by PKC/MAPK.179 – 181 Second, serine phosphorylation may inhibit the association of IRS-1 with the IR, so that tyrosine phosphorylation of IRS-1 is impaired more generally. Serine 307 within the PTB domain has been identified as a key target in this context, but phosphorylation at other sites may have similar effects.182, 183 There is evidence that phosphorylation of serine 307 also acts as a trigger targeting

INSULIN RECEPTOR SUBSTRATES

19

IRS for protesomal degradation,184 – 186 and the consequent reduction in IRS expression further impairs insulin signalling. Several different kinases have been implicated in phosphorylating serine 307 of IRS-1, including mTOR (activated by insulin itself),186, 187 JNK (activated by cytokines such as TNFα)188, 189 and IKKβ (activated by lipids, probably acting via PKC).190 – 192 Interestingly, serine 307 is IRS-1 specific and is not conserved in IRS-2, although it is possible that IRS-2 might be similarly regulated by phosphorylation at other sites. Finally, serine phosphorylation may modulate IRS function in other ways, causing it to act as an inhibitor of the IR tyrosine kinase,193, 194 or promoting its subcellular redistribution.152, 185 There is accumulating evidence that phosphorylation of IRSs by cytokineand/or lipid-stimulated kinases may be an important mechanism contributing to obesity-associated insulin resistance.167, 168, 195 Additionally, there is evidence of a persistent increase in serine phosphorylation of IRS-1 in primary cultures of skeletal muscle from patients with type 2 diabetes, suggesting that intrinsic as well as acquired dysregulation of IRS phosphorylation may contribute to insulin resistance.196 It remains to be seen whether serine-specific kinases that act on IRS proteins, such as IKKβ, can be targeted therapeutically to ameliorate obesity-related insulin resistance.190

DOKs and Gabs Two other families of proteins, DOKs and Gabs, are structurally related to the IRS family and are also IR substrates, though their contribution to insulin action is unclear.135 The DOKs (downstream of kinases) possess N-terminal PH and PTB domains and multiple tyrosine phosphorylation sites capable of recruiting diverse adaptors such as RasGAP, Nck and Crk. However, these proteins lack phosphorylation sites in YxxM motifs and do not recruit PI 3kinases. They are expressed primarily in lymphocytes and myeloid cells, where their functions may include coupling Fcγ RIIb and other receptors to inhibition of MAP kinases. Two novel DOKs identified initially in the human genome database appear somewhat more similar to IRSs in terms of sequence and tissue distribution, but their role in insulin action remains to be determined.197 The Gabs (Grb2-associated binders) lack PTB domains but otherwise have similar architecture to IRSs, including the presence of multiple YxxM motifs as well as consensus binding motifs for Grb2 and SHP2.198 Importantly, Gabs have the potential to make additional interactions through other tyrosine-based motifs and proline-rich regions. Gabs are substrates for multiple tyrosine kinases and interact particularly with Met receptors. Gab-1 is phosphorylated by the IR and IGFR tyrosine kinases,199 – 201 and may contribute to insulin/IGF mitogenic signalling in some cells.202, 203

20

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

Shc proteins The Shc (Src homology and collagen-like) proteins were originally characterized as SH2 domain-containing transforming proteins involved in the transduction of signals from tyrosine kinases such as the EGF receptor to Ras and MAP kinase,204 but soon shown also to be substrates of the IR and IGFR tyrosine kinases.205, 206 Their role in insulin action has been recently reviewed,207 as has their more general role in intracellular signalling.208, 209 There are several members of the Shc family, of which ShcA is most widely expressed. This exists as three isoforms of approximate Mr 46, 52 and 66 kDa, p52 being the major isoform in most cells. The p66 isoform arises as a result of alternative mRNA splicing while the p46 and p52 isoforms are created from alternate translation initiation sites.208 The p52 and p46 isoforms contain an N-terminal PTB domain and C-terminal SH2 domain flanking the central CH1 domain, and the p66Shc isoform has an additional N-terminal CH2 domain. Although Shc proteins contain both SH2 and PTB domains, it is the latter that mediates recruitment to and phosphorylation by tyrosine kinases. The PTB domains of IRS-1 and Shc bind to the same phosphorylated NPEY motif in the IR juxtamembrane domain.141 However, the IR sequence flanking this motif is not optimal for binding Shc PTB domain, and IR does not phosphorylate Shc as effectively as some other receptor tyrosine kinases.73, 142 There are two sites of tyrosine phosphorylation within the Shc CH1 domain, Y239/240 and Y317, and phosphorylation of either site allows binding of Grb2 and possibly other adaptors.210 Y317 appears to be the more important for activation of Ras in mammals,208 and this is also the predominant site of insulininduced phosphorylation.211 However, Y239/240 appears the more ancient phosphorylation in evolutionary terms, being conserved in Drosophila Shc, which lacks an equivalent of Y317, while the Shc orthologue in C. elegans lacks both tyrosine phosphorylation sites. It is possible that mammalian Shc retains phosphorylation-independent functions reflecting an ancestral role. There is evidence that p52 and p66Shc are not functionally equivalent and that they may even play opposing roles in MAP kinase activation,212, 213 influenced perhaps by serine phosphorylation of p66Shc within its CH2 domain.214 Although both IRSs and Shc can mediate activation of the Ras/MAP kinase pathway through their binding of Grb2,215, 216 Shc may provide the more important route for insulin-induced MAP kinase activation in some cells.217 Because the PTB domains of Shc and IRSs bind to the same phosphotyrosine residue in the IR, they may to some extent compete so that the level of either one could influence the phosphorylation of the other.218 – 220 Thus the relative efficiency of ‘metabolic’ (IRS/PI 3-kinase-dependent) and ‘mitogenic’ (Grb2-dependent) signalling by IR and IGFR in different cell types may be influenced by the relative expression levels of IRS and Shc. It has also been reported that SOCS (suppressor of cytokine signalling) proteins can bind at the same JM phosphotyrosine,169, 221 and increased expression of these proteins therefore has potential to inhibit insulin signalling through both IRS and Shc.

INSULIN RECEPTOR SUBSTRATES

21

APS and Cbl APS (adaptor with PH and SH2 domains) is representative of another family of IR substrates, the other members being the alternatively spliced isoforms of SH2-B (of which PSM, Pro-rich PH and SH2 containing signalling mediator, is the murine orthologue) and Lnk.222 APS and SH2-B were identified as binding partners for the activated IR kinase domain in yeast two-hybrid screens, and subsequently shown to be phosphorylated, APS appearing to be a better substrate than SH2-B.223 – 225 However, like Shc, they are by no means specific IR substrates but are also phosphorylated by PDGF receptors, neurotropin (Trk) receptors, and following stimulation of B-cell receptors. Nevertheless, APS is most highly expressed in recognized insulin target tissues, including differentiated adipocytes, consistent with a role in insulin signalling. The characteristic structural features of the APS family are an N-terminal proline-rich region, a central PH domain, an SH2 domain towards the C-terminus and a C-terminal tail with a single potential tyrosine phosphorylation site. The SH2 domain mediates binding to the phosphorylated regulatory loop of the IR.76, 223, 225 Both APS and SH2-B enhance IR autophosphorylation when overexpressed and this may potentiate signalling via PI 3-kinase and MAPK/ERK.226 Similarly, murine PSM has been reported to act as a positive mediator of insulin-stimulated mitogenesis.227, 228 Tyrosine-phosphorylated APS binds other adaptors, notably Grb2 and c-Cbl, via their SH2 domains.222 This may provide yet another route for activation of the Ras/MAP kinase cascade by IR. Moreover, APS is constitutively bound to Shc, though whether this facilitates Shc phosphorylation by IR is unclear. On the other hand, there is good evidence that APS does facilitate tyrosine phosphorylation of c-Cbl,124, 229 which is not otherwise phosphorylated by the IR tyrosine kinase, although it is directly recruited and phosphorylated by other tyrosine kinases.122 In general, Cbl is thought to play an inhibitory role, through its ubiquitin ligase activity, which targets receptors for degradation.122 However, in the case of IR it has been proposed that Cbl plays a positive role in mediating stimulation of glucose uptake, in synergy with PI 3-kinase-dependent pathways, as discussed below. Surprisingly perhaps, in view of the data obtained from over-expression studies, knockout of APS in mice results in a phenotype of increased insulin sensitivity and hypoinsulinaemia.230 This increased insulin sensitivity is not dependent on any change in IR expression, suggesting that the putative APS/Cbl/ubiquitination pathway does not play a major role in IR downregulation. Nonetheless, it appears clear from these knockout studies that the dominant effect of APS on IR signalling is inhibitory rather than positive. On the other hand, knockout of SH2-B results in impaired fertility in both male and female mice, with effects on both ovarian and testicular development,231 suggesting a positive role in IR/IGFR signalling in these tissues. However, there was no obvious effect of the SH2-B knockout on glucose homeostasis.

22

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

The Grb10/Grb14 family The protein that has been most commonly identified as a binding partner for the IR kinase domain in yeast two hybrid screens is Grb10, one of a family of closely related adaptor proteins of which the other members are Grb7 and Grb14.232 – 234 Although these proteins interact also with many receptor tyrosine kinases, at least in vitro, interest has focussed on involvement in IR/IGFR signalling in the case of Grb10/Grb14 and cell motility in the case of Grb7. Grb10 is most highly expressed in muscle, and also in fat and in foetal but not adult liver. Grb14 on the other hand is most highly expressed in liver, and also in muscle. The pattern of expression of Grb7 is less certain, data for mouse and human tissues being discordant. The Grb7/10/14 proteins have are similar to APS in overall structure, having an N-terminal proline-rich region, central PH domain and C-terminal SH2 domain, although they are unrelated to APS in primary sequence. Moreover Grb10 is not phosphorylated by the IR tyrosine kinase, although it may be phosphorylated by Src family tyrosine kinases.235 Several splice variants of Grb10 have been identified, the significance of which is unclear, not least because these differ in the mouse and human. Both SH2 and BPS (between PH and SH2) domains of Grb10 have been implicated in binding to activated IR, most likely via the regulatory loop.77, 236 Binding of Grb10 may be preferential for IR as compared to IGFR.237, 238 There is as yet no consensus concerning the role of Grb10 and Grb14 in insulin action. Several studies have reported that these proteins directly inhibit IR tyrosine kinase activity in vitro, and that overexpression inhibits IRS phosphorylation and downstream signalling in intact cells.239 – 241 However, some laboratories have proposed that Grb10 functions positively and potentiates both metabolic and mitogenic signalling by IR, possibly by facilitating activation of PI 3-kinase.236, 242, 243 It is difficult to reconcile these disparate observations. Other studies have identified a ubiquitin ligase, NEDD4, as a binding partner for Grb10, suggesting a possible role in receptor degradation.125 Grb10 also binds signalling proteins such as Raf, MEK and Akt/PKB244, 245 as well as proteins of unknown function,246 leaving open the possibility that it might initiate a specific subset of signalling pathways even while inhibiting others. Expression of the Grb10 gene is imprinted, being largely from the maternal allele.247 Over-expression of Grb10 has been implicated in the growth retardation associated with Silver–Russell syndrome.248 Conversely, deletion of the Grb10 gene in mice results in tissue-selective overgrowth, affecting the liver in particular, accompanied by accumulation of hepatic glycogen and improved glucose tolerance.249 This phenotype suggests Grb10 may act as a tissue-selective inhibitor of IR function, although the overgrowth is apparently independent of IGF signalling. Deletion of the Grb14 gene in mice improves glucose tolerance and enhances insulin signalling in liver and muscle but not fat, confirming Grb14 as a tissue-specific modulator of insulin action.250

DOWNSTREAM SIGNALLING PATHWAYS

1.4

23

Downstream signalling pathways

Phosphoinositide 3-kinase Very many actions of insulin have been shown to depend on phosphoinositide (PI) 3-kinase activity, including stimulatory effects on glucose transport, glycogen synthesis and protein synthesis, and inhibitory effects on lipolysis and transcription of gluconeogenic genes.251, 252 In addition to a playing a central role in insulin action, PI 3-kinase activity is critical to mitogenic signalling by, for instance, activated PDGF receptors or viral large T antigen.253, 254 The synthesis and function of 3-phosphorylated inositol lipids and the overall cellular functions of PI 3-kinases have been comprehensively reviewed.253 – 255 The PI 3-kinase recruited to IRSs (and to other tyrosine-phosphorylated proteins, including some growth factor receptors) is designated class Ia, as opposed to the class Ib enzyme, which is activated by heterotrimeric G-proteins. Class II PI 3-kinases are also stimulated by insulin and several growth factors, but the mechanism of activation and contribution to insulin action is unclear.254 Although PI 3-kinase activity is normally assayed in vitro using PtdIns as substrate, the preferred substrate of class I PI 3-kinases in vivo is PtdIns(4,5)bisphosphate, generating PtdIns(3,4,5)tris-phosphate as product (Figure 1.7). In addition to their lipid kinase activity, class I PI 3-kinases also phosphorylate serine residues, and can catalyse both autophosphorylation of their p85 adaptor subunit256 and phosphorylation of IRSs.257, 258 Studies of the role of PI 3-kinase have been greatly facilitated by the availability of relatively specific inhibitors (wortmannin and LY294002), together with dominant negative and constitutively active constructs. Class Ia PI 3-kinases are heterodimers containing a p110 catalytic subunit and p85/p55 adaptor/regulatory subunit (Figure 1.7). There are multiple isoforms of both subunits – α,β,δ-catalytic subunits and α,β,γ-adaptors are encoded by different genes, and further complexity of the α-adaptor arises from alternative splicing.252 The adaptor subunits contain tandem SH2 domains flanking the p110 binding domain, and these bind to phosphotyrosine residues in YMxM (or YxxM) motifs on IRSs. The resulting stimulation of PI 3-kinase activity probably reflects both allosteric activation of the catalytic subunit, and the effect of bringing the enzyme into proximity with its membrane phospholipid substrate. The N-terminal portions of the p85 adaptor subunits contain additional protein interaction domains including an SH3 domain and proline-rich regions, which are lacking in p55 isoforms. The catalytic isoforms differ in kinetic properties and in tissue distribution259 but the physiological significance of these differences remains unclear. The adaptor subunit isoforms and splice variants also differ in tissue distribution and in the effectiveness with which they couple PI 3-kinase catalytic activity to tyrosine-phosphorylated IRS proteins.260 Surprisingly, targeted deletion of adaptor subunits in mice (homozygous deletion of individual p85α, p85β or p55α/p50α isoforms, or heterozygous deletion

SH3

PtdIns

(PI3K)

Bcr

(PI3K)

PtdIns 4-K

SH2

p85 binding

p110 binding

PtdIns-4-P

p110 (catalytic)

PtdIns 4-K

PtdIns-3-P

Ras binding

SH2

PtdIns 5-K

PTEN

PtdIns(3,4)P2

Phospholipase C

PTEN

PtdIns(3,4,5)P3

CaLB domain

Kinase domain

Diacylglycerol + Ins(1,4,5)P3

PtdIns(4,5)P2

PI3K

SHIP2

Figure 1.7 PI 3-kinase reaction and structure. (a) The pathways responsible for the synthesis and breakdown of the key mediator of insulin signalling, PtdIns(3,4,5)tris-phosphate, are indicated, showing the reactions catalysed by class I PI 3-kinase and the phosphatases PTEN and SHIP. (b) Class Ia PI 3-kinase is represented schematically, showing the major structural domains. The p50/p55 variants of the adaptor subunit lack the N-terminal SH3 domain

p85 (adaptor)

(b)

(a)

24 THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

DOWNSTREAM SIGNALLING PATHWAYS

25

of all p85α/p55α/p50α splice variants) results in increased insulin sensitivity and hypoglycaemia due to increased glucose transport in skeletal muscle and adipocytes.261 – 264 In muscle cells and adipocytes lacking p85α, p55α/p50α splice variants take over the role of coupling IRS phosphorylation to generation of PtdIns(3,4,5)tris-phosphate, and they apparently perform this function more effectively than p85α.261, 263 Two potential mechanisms may contribute to the paradoxical increase in insulin sensitivity upon reduction in the level of adaptor subunits. It seems that there is normally an excess of adaptor over catalytic subunits, such that free adaptor may compete with holoenzyme for binding to phosphorylated IRS proteins and thus limit the stimulation of PI 3kinase activity. Moderate reduction in the overall level of adaptors may affect primarily the concentration of monomeric free adaptor, allowing the remaining heterodimeric holoenzyme to bind more effectively to IRS proteins. However, there is evidence that p85 adaptor subunits may have additional PI 3-kinaseindependent functions, involving negative regulation of signalling downstream of PI 3-kinase.265 The subcellular distribution of PI 3-kinase activity may also be an important determinant of signalling outcome. In insulin-stimulated adipocytes PtdIns(3,4,5)tris-phosphate is generated largely in the plasma membrane.266 However, there is also some PI 3-kinase activity targeted to specific intracellular membrane sites including GLUT4 vesicles,267 and the extent of such targeting might influence the efficiency of GLUT4 translocation. Signalling by PI-3 kinases is terminated by the action of appropriate phosphatases. Two major classes of phosphatase act on PtdIns(3,4,5)tris-phosphate. PTEN possesses 3
-phosphatase activity and effectively reverses the PI 3-kinase reaction. PTEN acts as a tumour suppressor, and inactivating mutations are associated with many cancers.268 Alternatively, the SHIP family of phosphatases act on PtdIns(3,4,5)tris-phosphate to generate PtdIns(3,4)bis-phosphate. Overexpression of either PTEN or SHIP2 in adipocytes antagonizes insulin-induced increases in PtdIns(3,4,5)tris-phosphate accumulation, Akt activity and glucose transport.269, 270 Moreover, targeted disruption of SHIP2 in mice results in enhanced insulin sensitivity, suggesting that this enzyme normally plays a role in removing PtdIns(3,4,5)tris-phosphate arising from insulin action.271 However, the action of SHIP2 may not immediately terminate signalling, given that PtdIns(3,4)bis- and (3,4,5)tris-phosphates bind similarly to the PH domains of downstream signalling proteins PDK and PKB. Moreover, PtdIns(3,4)bisphosphate may have the capacity to recruit distinct signalling adaptors.272

Phosphoinositide-dependent kinases and protein kinase B/Akt The serine/threonine-specific protein kinase B (PKB, also known as Akt) was initially characterized as a 57 kDa protein related in structure to both cAMP-dependent protein kinase A and calcium/lipid-dependent protein kinase C, and as a homologue of a viral transforming protein v-Akt. An important

26

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

breakthrough in understanding insulin signalling was the demonstration that PKB/Akt is activated by insulin (and other growth factors) via a PI 3-kinasedependent mechanism.273 It is now recognized that PKB/Akt plays a central role in the regulation of cellular metabolism and growth, as documented in numerous reviews.274 – 278 Mammalian cells express three isoforms (PKBα/Akt1, PKBβ/Akt2, PKBγ/Akt3), which are the products of distinct genes but are very closely related in sequence. Structurally, PKB is characterized by its Nterminal pleckstrin homology domain and hydrophobic C-terminal tail, which flank the central kinase domain (Figure 1.8). Figure 1.8 shows activation of PKB by PDK1- (and putative PDK2-) mediated phosphorylation, following co-localization by to PtdIns(3,4,5)tris-phosphate in the plasma membrane. Major substrates of PKB thus far identified are indicated, together with functional consequences of their phosphorylation. Other substrates of PDK1 are also indicated. The PH domain of PKB binds with high affinity the lipid product of PI 3-kinase, PtdIns(3,4,5)tris-phosphate, and its immediate breakdown product, PtdIns(3,4)bis-phosphate. However, this binding is not in itself sufficient to activate the enzyme, which is dependent on its phosphorylation at two sites, one within the activation loop of the kinase domain (T308 in PKBα) and the other within a C-terminal hydrophobic motif (S473 in PKBα).274, 279 PDK1 (phosphoinositide-dependent kinase-1) was identified as a ubiquitously expressed serine/threonine kinase that phosphorylates T308 of PKB in a reaction that is dependent on the presence of PtdIns(3,4,5)tris-phosphate (or PtdIns(3,4)bis-phosphate).280 It appears that S473 is phosphorylated by a distinct kinase, and although several candidates for this putative ‘PDK2’ have been proposed the enzyme that fulfils this role in vivo has yet to be clearly identified. In unstimulated cells, PKB is cytosolic and inactive, while PDK1, also largely cytosolic, exists in an already active, phosphorylated state. The role of PtdIns(3,4,5)tris-phosphate in the activation of PKB includes several components. Importantly, PDK1 and PKB are co-localized on membranes by binding of their respective PH domains to PtdIns(3,4,5)trisphosphate (Figure 1.8). Additionally in the case of PKB this binding induces a conformational change so that T308 becomes accessible to PDK1. There may also be involvement of PtdIns(3,4,5)tris-phosphate in activation of the putative PDK2. Once phosphorylated and activated, PKB evidently dissociates from the membrane and is functional both within the cytosol and after translocation to the nucleus.281 Active PKB phosphorylates and modulates the activity of multiple cellular substrates, including GSK-3 (glycogen synthase kinase-3), PDE-3B (phosphodiesterase-3B), PFK-2 (phosphofructokinase-2), forkhead transcription factors of the FOXO family and the pro-apoptotic proteins BAD and caspase 9.274, 276, 278 Phosphorylation of GSK-3 inhibits its activity, relieving the inhibitory effect of GSK-3 on glycogen synthase, and this is a major (but perhaps not the only) mechanism by which insulin stimulates glycogen synthesis

SGK

PKCζ

PS

PS

PS p70S6K

PS

PKB/Akt

–

BAD

TSC

FOXO1

–

–

GSK3

PFK-2

PDE3B

–

+

+

IRS-1

SP

SP

SP

SP

SP

SP

SP

Figure 1.8 PDK/PKB activation and substrates (adapted from references 274 and 276)

PDK2

PDK1

PIP3

KINASE

PH

PIP3

PH

KINASE

+

Apoptosis inhibited

Protein synthesis stimulated

Gluconeogenesis inhibited

Glycogen synthesis stimulated

Glycolysis stimulated

Lipolysis inhibited

Signalling stimulated

DOWNSTREAM SIGNALLING PATHWAYS

27

28

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

in skeletal muscle.282 Phosphodiesterase-3B is activated when phosphorylated by PKB, and the resulting lowering of cyclic AMP concentration and reduced activity of PKA contributes to the anti-lipolytic effect of insulin in adipose tissue.283 Phosphorylation and activation of PFK-2 underlies stimulation of glycolysis in heart.284 Phosphorylation of FOXO transcription factors,285, 286 causes their redistribution from nucleus to cytoplasm and/or inhibits binding of the transcriptional co-activator PGC-1α and thereby inhibits expression of gluconeogenic genes such as PEPCK and G6Pase.287, 288 Phosphorylation of BAD and caspase 9 inhibits their pro-apoptotic activity, thus promoting cell survival.276 It is likely that additional PKB/Akt substrates await identification, in particular proteins involved in regulating the translocation of GLUT4 vesicles in muscle and adipose tissue. Experiments involving over-expression of constitutively active forms of PKB are generally supportive of a key role in insulin signalling, although the effects of over-expressing supposedly inactive, dominant-negative forms of PKB have been equivocal. Interpretation of such experiments is complicated by doubts as to whether constitutively active constructs are valid mimics, and dominant negative constructs effective inhibitors, of endogenous insulin-stimulated PKB.276, 278 Nonetheless, there is considerable evidence implicating PKB in insulin’s stimulation of glucose transport in muscle and adipose tissue.278 In particular, targeting of a dominant negative PKB construct to GLUT4 vesicles in adipocytes strongly inhibits insulin-stimulated vesicle translocation, whereas cytosolic expression of the same construct does not.289 Moreover, insulin has been reported to stimulate recruitment of endogenous PKB to GLUT4 vesicles.290, 291 Thus it appears that PKB may act at or close to GLUT4 vesicles in stimulating translocation and glucose uptake. However, the specific substrates of PKB that are involved in stimulation of glucose transport have remained elusive. Another outstanding question concerns the role of individual PKB isoforms. Mice deficient in individual PKB isoforms show different phenotypes: disruption of the PKBβ/Akt2 gene results in insulin resistance and a diabetes-like syndrome,292, 293 while disruption of the PKBα/Akt1 gene does not affect glucose tolerance but leads to conspicuous impairment of foetal and postnatal growth.294 PKBβ/Akt2 expression is enriched in insulin-sensitive tissues, and the different phenotypes may in part reflect tissue-specific isoform expression. However, there is also evidence that, notwithstanding their apparently similar substrate specificity as assayed in vitro, the isoforms may be adapted to preferentially transmit distinct biological signals.295 Aside from its involvement in metabolic aspects of insulin signalling, there is considerable evidence that PKB plays a major role in the control of cell growth, survival and proliferation. Insights into the role of insulin signalling pathways in controlling the growth and size of cells, and thus ultimately the size of organisms, have come from genetic studies in worms (C. elegans) and flies (D. melanogaster).296, 297 Indeed, co-ordination of cell growth and division with nutrient supply appears to represent an ancient function of insulin

DOWNSTREAM SIGNALLING PATHWAYS

29

family peptides, which in evolutionary terms predates the divergence of distinct receptors for insulin and IGFs. Control of cell growth and size reflects substantially the control of protein synthesis, although insulin also inhibits protein degradation.298 Several components of the protein synthetic machinery are regulated by insulin in a phosphorylation-dependent manner, but ribosomal protein S6 kinase (p70S6K) and the translation inhibitor 4E-BP-1 have received particular attention.299 Activation of p70S6K, leading to phosphorylation of the 40 S ribosomal subunit, has been implicated in translational up-regulation of specific mRNAs encoding components of the protein synthetic apparatus.300 Phosphorylation of 4E-BP-1 causes its dissociation from the mRNA cap-binding protein eIF-4E, making 4E available to form translationally active eIF-4F complexes.301 These effects of insulin are dependent on PI 3-kinase activation, and at least in part on the protein kinase mTOR, as shown by using the specific inhibitors wortmannin and rapamycin. At least eight phosphorylation sites mediate activation of p70S6K in a hierarchical fashion,302 and 4E-BP-1 similarly undergoes hierarchical phosphorylation on at least four sites.303 It is probable that mTOR itself is responsible for directly phosphorylating some of the sites on both these proteins,304 but other kinases may also be involved in priming events. The activity of mTOR is regulated by amino acids and thus this protein serves to integrate signals from both nutrients and growth factors.305 The pathway linking growth-factor-stimulated PI 3-kinase activity to activation of mTOR has recently been elucidated.306 – 309 A small G-protein Rheb lies upstream of mTOR, but in unstimulated cells Rheb, and therefore mTOR, is held in an inactive state by the GTPase activating (GAP) activity of the tuberous sclerosis complex, comprising the proteins hamartin and tuberin, which are products of the of Tsc1 and Tsc2 genes. (Mutations in Tsc1 and Tsc2 give rise to the human disease tuberous sclerosis.) When PKB/Akt is activated by insulin or other growth factors it phosphorylates tuberin, inhibiting the GAP activity of the complex, which in turn allows Rheb and therefore mTOR to become active and to phosphorylate p70S6K and 4E-BP-1. Additionally, PKB directly phosphorylates mTOR on Ser2448, which lies within a stringent PKB consensus sequence.310 However, in the light of recent evidence for the role of tuberin phosphorylation in mTOR activation, the significance of the direct phosphorylation of mTOR is uncertain. Although phosphorylation by PKB may be sufficient in itself to regulate the activity of some substrates, in many cases 14–3–3 proteins play an important role in determining the functional consequences of phosphorylation.284, 311 – 313 The 14–3–3 proteins are a family of abundant, widely expressed proteins that bind to phospho-serine-containing motifs (particularly favouring those in a PKB consensus). The consequences of 14–3–3 binding vary with different proteins, and can include either positive or negative effects on function. Most simply, binding of 14–3–3 may inhibit dephosphorylation or proteolysis, thus extending the lifetime of activated targets. However, 14–3–3 can also directly augment, or

30

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

inhibit, intrinsic enzymatic activity (eg Raf, PFK-2), modify subcellular localization, including nuclear/cytoplasmic partitioning (as with FOXO transcription factors), and either inhibit interaction with other binding partners, or act as a scaffold/adapter bringing two targets into proximity.311 PKB, like PI 3-kinase, has been implicated in a multitude of cellular processes including proliferation, apoptosis, differentiation and motility, quite apart from its role in the metabolic actions of insulin.277 It is not surprising therefore that, in addition to phosphorylating many substrates involved in these processes, PKB forms complexes with other proteins that act as modulators of its activity and function.314 Some of these binding partners (such as PKCζ and Grb10) may be relevant to insulin action, although their functional significance remains to be determined. Others (such as TRB3) may act as inhibitors of insulin signalling, so that their over-expression can cause insulin resistance.315 Discussion of the multiple mechanisms through which the activities of PI 3-kinase and PKB can be modulated is beyond the scope of this chapter. Changes in the insulin-dependent activation of PI 3-kinase and PKB/Akt have been documented in muscle and fat from human diabetic subjects.316 – 321 The primary defects underlying such changes are in most cases unclear, although decreased tyrosine phosphorylation of IRS-1 (secondary to its serine phosphorylation) or decreased activation of PKB (through interaction with PKCζ or TRB3) could contribute to impaired downstream signalling.

Other substrates of PDK1: atypical PKCs PDK1 phosphorylates and activates a number of other AGC family kinases in addition to PKB. Conventional and atypical PKCs, SGK (serum and glucocorticoid inducible kinase), p70S6K and p90rsk can all be phosphorylated on residues within their activation loops equivalent to T308 of PKB.274 In all cases, some form of priming is required to render these proteins effective substrates, just as with PKB where binding of PtdIns(3,4,5)tris-phosphate to the PH domain serves this function. PKCs may be primed by binding phospholipids and/or diacylglycerol, while in the case of SGK, p70S6K and p90rsk priming is by phosphorylation of sites within the C-terminal hydrophobic motif by other kinases. The extent to which PDK1-mediated phosphorylation contributes to insulin-dependent activation of these kinases in vivo is uncertain, given the dependence on appropriate priming and the possibility that other kinases (including other insulin-dependent kinases) may also have a role in activation, at least in the case of p70S6K and p90rsk. However, there is additional evidence that atypical PKCs (ζ and λ) may play a significant role in insulin signalling, particularly in relation to glucose transport. Expression of inactive, dominant negative forms of aPKC inhibits insulin-stimulated glucose transport in muscle and fat cells (in some cases, more readily than dominant negative PKB constructs), while expression of constitutively active aPKCs mimics the stimulatory effect

DOWNSTREAM SIGNALLING PATHWAYS

31

of insulin.322 The rival claims of PKB and aPKC as mediators of insulin signalling to glucose transport have been much discussed.323 – 328 It is of course possible that both pathways play a role, whether by phosphorylating the same or different substrates. Atypical PKCs have also been implicated in mediating some of insulin’s effects on induction of hepatic genes.329

The CAP/Cbl/TC-10 pathway A quite separate pathway has recently been described that appears to play an important role in insulin-stimulated glucose transport in adipocytes (and presumably also in muscle), in synergy with PI 3-kinase dependent pathways.7, 330 This involves c-Cbl, which is recruited to and phosphorylated by the IR by SH2 domain-dependent association with phosphorylated APS and/or CAP (Cblassociated protein). In turn, phospho-Cbl binds Crk, which acts as an adaptor recruiting C3G, a guanine nucleotide exchange factor for the small G-protein TC-10 (Figure 1.9). This complex assembly is localized to lipid raft microdomains within the plasma membrane by interaction of the proline-rich region of Cbl with the SH3 domain of CAP which in turn binds to flotillin, a resident protein of lipid rafts. The importance of this pathway for insulin’s stimulation of glucose transport in adipocytes has been established by expressing a variety of dominant negative constructs and isolated interaction domains which inhibit formation of the productive CAP/Cbl/Crk/C3G/TC-10 complex. What lies downstream of TC-10 is less certain, although the activated G-protein may be involved in remodelling of cortical actin,331 the generation of phosphatidylinositol 3-phosphate332 or recruitment of components of the exocyst complex believed to be involved in vesicle tethering at the plasma membrane prior to exocytosis.333 There is increasing evidence that lipid raft microdomains within the plasma membrane act as an important platform for integration of insulin signals and fusion of GLUT4 vesicles.7, 334, 335 The idea that effective stimulation of GLUT4 vesicle translocation by insulin requires synergistic action of two signals, dependent on PI 3-kinase and TC-10 respectively, is attractive even though the specific molecular targets of either pathway remain to be identified. This hypothesis would help to explain why glucose transport is specifically stimulated by insulin. In other cell types, and in relation to other receptors, both Cbl and Crk have been proposed to have quite different cellular functions (including in the case of Cbl the down-regulation of tyrosine kinases by ubiquitin-dependent degradation).122, 336 The specific role of Cbl and Crk in insulin-sensitive tissues may reflect the particular spectrum of binding partners expressed in these tissues (of the many that have been described).

The MAPK/ERK cascade The third substantial pathway for which a role in insulin signalling has been firmly established is the Ras/Raf/MEK/ERK cascade (Figure 1.10). The major

PKCζ SP

PDK

Phosphorylation of unidentified substrates ???

PKB

PIP3

PI 3-K

PIP2

APS

GLUT4 vesicles translocation to plasma membrane

PY IRS-1 PY IRS-2

IR

YP

YP Crk

C3G

TC10

Actin remodelling ?? PtdIns3P generation ?? Recruitment of exocyst??

Cbl

CAP

Flotillin

lipid rafts

Figure 1.9 Insulin signalling to GLUT4 translocation. The major known components of the two signalling pathways mediating insulin’s stimulation of glucose transport in adipose tissue and muscle are indicated

(activated)

Glycogen synthase

(inhibited)

PS GSK3

PS

PT

PIP3

bulk membrane

32 THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

Rheb GDP

TSC

Rheb GTP

PDK

PIP3

Stimulation of protein synthesis

FOXO

YP

PY IRS-1 PY IRS-2

IR

Decreased transcription of FOXO-dependent genes

Nuclear exclusion and degradation

PS

PI 3-K

PIP2

SHC

YP

RAS GDP

Grb2

SOS

Figure 1.10 Insulin signalling to gene expression

p70S6K SP

PKB

mTOR

SP 4E-BP-1

PS

PS

PT

PIP3

YP

TP

SP

ERK/MAPK

MEK

Raf

Increased transcription of growth-regulatory genes

Phosphorylation and activation of Fos, Jun, Elk1

RAS GTP

DOWNSTREAM SIGNALLING PATHWAYS

33

34

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

known components of the signalling pathways mediating insulin’s action on gene expression at the transcriptional and translational levels are indicated in Figure 1.10. It is not meant to imply that all these pathways will necessarily operate simultaneously in any given cell type. In mammalian cells insulin is just one of many extracellular signals capable of activating this cascade, which is a primordial signalling system highly conserved in evolution and important even in organisms such as yeast.337 – 339 The central role of the cascade in regulating the proliferation of mammalian cells is emphasized by the fact that both Ras and Raf are proto-oncogenes. Closely related to the growth-factor-responsive ERK cascade, which primarily regulates cell growth and differentiation, are the JNK and p38 MAP kinase cascades which function mainly in stress responses.340 There is some evidence that insulin can also stimulate these cascades, although the mechanism and significance for insulin action are unclear. Studies of the biological roles of the various MAPK cascades have been facilitated by the availability of relatively specific inhibitors, especially the PD98059 inhibitor of MEK activation. Insulin does not activate the ERK cascade as effectively as many other growth factors. Moreover, inhibitor studies have shown that the cascade does not play any role in mediating acute metabolic effects of insulin, on glucose uptake, glycogen synthesis or lipid metabolism.341 – 343 However, the ERK cascade is involved in the effects of insulin on the transcription of some genes, particularly those involved in cell growth and division.287, 344 As discussed above, phosphorylation of both IRS and Shc proteins can lead to recruitment of Grb2,215 which associates constitutively with the guanine nucleotide exchange factor SOS. This allows activation (by GTP–GDP exchange) of the small G-protein Ras, by mechanisms that are not entirely clear but may require no more than the proximity of SOS and Ras at the plasma membrane. The principal effector of Ras is the serine/threonine-specific kinase Raf-1, which is activated by interaction with GTP-bound Ras. Activated Raf acts as a MAP kinase kinase kinase, phosphorylating and activating the MAP kinase kinase MEK. MEK is a dual specificity kinase that doubly phosphorylates both threonine and tyrosine residues in a TEY motif in the activation loop of ERK. Both MEK and ERK exist exists as two functionally indistinguishable isoforms (MEK1/2, ERK1/2) that are the products of distinct genes. Activated ERK phosphorylates and activates a downstream kinase p90rsk,345 and also translocates to the nucleus where it phosphorylates Elk-1 and regulates the level and activity of components of the AP-1 transcriptional complex by multiple mechanisms.346 – 348 Many other proteins participate in the organization and regulation of the Ras/MAPK cascade.349 Raf-1 was among the first 14–3–3 binding partners to be identified.311 The scaffold proteins KSR (kinase suppressor of Ras) and MP1 (MEK partner-1) bind multiple components, contributing to the spatial organization and specificity of the cascade of phosphorylation reactions.350, 351 Grb10 has been proposed to bind both

DOWNSTREAM SIGNALLING PATHWAYS

35

Raf and MEK,244 but it is not clear whether this contributes specifically to activation of the cascade by insulin. The activity of the ERK cascade is also dependent on diverse protein phosphatases, and on the expression of the inhibitory protein RKIP (Raf kinase inhibitor protein). Feedback phosphorylation of SOS by ERK or other kinases induces disassembly of the Grb2/SOS complex and termination of Ras activation.352 – 354 The activity of the ERK cascade is also influenced by other kinase cascades including PKA and PKB.355, 356 Thus the MAPK/ERK cascade and parallel stress-activated kinase cascades are susceptible to multiple regulatory inputs, by way of both direct activation and modulatory cross-talk from other signalling cascades.

Further potential signalling components Numerous other components have been proposed to play a role in insulin signalling, including additional substrates of the IR tyrosine kinase, additional adaptor proteins and enzymes recruited by IRSs, alternative PtdIns(3,4,5)trisphosphate binding proteins, heterotrimeric G-proteins and phosphoinositolglycan mediators. Additional substrates of the IR include JAKs (Janus kinases) and Stats (signal transducers and activators of transcription) more usually associated with cytokine receptor signalling but with potential also to contribute to some of insulin’s effects on gene expression.357 – 359 The IR directly phosphorylates caveolin-1, a resident protein of lipid raft microdomains.360 The functional consequences of this phosphorylation and its relationship to other aspects of insulin signalling are unclear, although as discussed above there is growing evidence for the importance of lipid raft microdomains in insulin signalling. Yet another substrate is CEACAM-1 (carcinoembryonic antigen-related cell adhesion molecule-1), which is reportedly phosphorylated by the IR but not the IGFR tyrosine kinase.361 CEACAM-1 is a 120 kDa glycoprotein expressed predominantly in liver which enhances receptor-mediated endocytosis and degradation of insulin in a phosphorylation-dependent manner and has been proposed to play a role in hepatic clearance of insulin from the circulation rather than in signalling per se.361 Additional binding partners for tyrosine-phosphorylated IRSs include SH2/SH3 adapters such as Nck and Crk, the tyrosine kinase Fyn and the tyrosine-specific protein phosphatase SHP-2.135, 178 Of these proteins, SHP-2 has received most attention, although its role in intracellular signalling remains poorly defined. Some studies have concluded that the association of SHP-2 with IRS-1 attenuates insulin responses.362 However, unlike the majority of PTPs, which function to turn off signals generated by tyrosine kinases, SHP-2 can act as a positive contributor to signal transduction. It has been implicated in the potentiation of Ras activation and signalling through the ERK and JNK cascades363, 364 and in signalling to glucose utilization in vivo.365 However, the

36

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

specific molecular targets underlying such effects are unknown.366 Although PLCγ is not recruited by IRSs, there is some evidence that it may interact more directly with, and be activated by, the IR.367 The activation mechanism is unclear but may require PI 3-kinase.368 It has been suggested that PLCγ activity may contribute to both metabolic and mitogenic signalling by IR, perhaps by generation of activators of PKCζ.369 PH domains that bind PtdIns(3,4,5)tris-phosphate with high affinity are found in several proteins apart from PDK-1 and PKB,370 including tyrosine kinases of the Tec family,371 guanine nucleotide exchange factors for Arf GTPases (eg ARNO and Grp-1372 ), GTPase activating proteins for Arf and Rho GTPases (e.g. centaurins and cytohesins373 and ARAP3,374 ) and adaptor proteins of unknown function (e.g. DAPP1, dual adaptor for phosphotyrosine and phosphoinositides375, 376 ). PI 3-kinase can also activate the small GTPase Rac, and vice versa, though it is unclear whether this occurs by direct interaction (as has been shown for Ras) or by recruitment of GEFs and/or GAPs by PtdIns(3,4,5)tris-phosphate.377 Whether any of these potential effectors of PI 3-kinase activity play a role in insulin signalling will depend on their levels of expression in classical insulin target tissues. However, it has been shown that ARNO can indeed mediate the activation of Arf and phospholipase D by insulin.372 PI 3-kinase-dependent regulation of Rho, Rac and Arf has been implicated in remodelling of the actin cytoskeleton and intracellular membrane dynamics,373, 377, 378 but has not been specifically linked to the translocation of GLUT4 vesicles in response to insulin. Studies going back over many years have implicated heterotrimeric G-proteins in insulin action.379 There has recently been renewed interest in this area with evidence that IR and IGFR may interact with different G-proteins.380 Gαq/11 has been reported to be an important component of insulin signalling to GLUT4 translocation and stimulated glucose transport in adipocytes. Not only does the IR physically associate with and phosphorylate Gαq/11, but inhibition of Gαq/11 blocks, and constitutive activation of Gαq/11 mimics, the action of insulin on glucose transport.381 The mechanism of involvement of Gαq/11 in insulin signalling is unclear, but may involve activation of PI 3-kinase by a pathway requiring the Rho GTPase family member cdc-42.382 Gαq/11 has also been implicated in the insulin-stimulated generation of phosphoinositolglycan mediators.383 These compounds, in various guises, are reportedly derived from glycosylphosphatidylinositol-anchored plasma membrane proteins, and released as a consequence of insulin’s activation of phospholipases and peptidases. Phosphoinositolglycans and related compounds have had a long and chequered history as putative mediators of insulin action.384, 385 It was originally hypothesized that their insulin-mimetic effects involved direct interaction with intracellular targets. More recently it has been proposed that phosphoinositolglycans might potentiate insulin signalling by interacting with

THE BASIS OF INSULIN’S SIGNALLING SPECIFICITY

37

lipid raft domains and signalling via Lyn tyrosine kinase to stimulate phosphorylation of IRS proteins.386 Whether or not this pathway contributes to insulin signalling in vivo, it has been suggested that it may provide novel targets for signal transduction therapy in relation to diabetes.387

1.5 The basis of insulin’s signalling specificity Understanding of insulin signalling pathways is still far from complete, but already the picture we have is one of great complexity. There can be little doubt that phosphorylation of IRSs, recruitment of PI 3-kinases and activation of protein kinase cascades downstream of phosphoinositide-dependent kinase are of major importance in mediating many of the metabolic effects of insulin. However, there are strong indications that numerous other signalling proteins play significant roles, either in addition to, or as modulators of, the PI 3-kinase pathway, and it is likely that still further players await identification. One surprise among all this information is that there are no known signalling components that are unique to insulin action, apart from the IR itself. On the contrary, both major and minor players in insulin signalling, and especially PI 3-kinase, are apparently also involved in mediating the actions of numerous other stimuli on diverse biological endpoints. This raises very obvious questions regarding the basis of specificity in insulin signalling. Why cannot other hormones and growth factors mimic insulin action, and why does insulin not have an even broader spectrum of actions? The answer to this conundrum must lie in part in the tissue-specific expression of receptors, signalling intermediates and responsive endpoints.388, 389 The fact that a given cell only responds to certain stimuli, and in certain ways, is determined by the precise levels of expression and subcellular location of a substantial array of signalling proteins whose interactions define specificity in signal transduction.390 Under experimental situations in which components are over-expressed or mis-localized, specificity that might operate in vivo can easily be lost. In adipose tissue for instance, the ability to stimulate glucose transport is confined almost solely to insulin. Other growth factors such as PDGF do not normally stimulate PI 3-kinase activity sufficiently to stimulation GLUT4 translocation,266 although if PDGF receptors are over-expressed in they can elicit stimulation comparable to insulin.391 In fact both the amplitude and time course of PtdIns(3,4,5)tris-phosphate signals may influence downstream responses.392 Additional constraints may be imposed if responses require the simultaneous operation of multiple signalling pathways. Thus in relation to glucose transport signals from the Cbl/TC-10 pathway in addition to the PI 3-kinase pathway may contribute to the particular effectiveness of insulin as a stimulus.330, 393 Other factors such as the duration of extracellular signals, and dependence of intracellular signalling on the internalization, itinerary and lifetime of activated

38

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

receptors may also play a part in imposing specificity on otherwise promiscuous pathways. Similar arguments apply to the molecular mechanisms underlying insulin resistance, which apparently leave other growth factors, acting via similar pathways, unaffected. Nonetheless, when it comes to targeting signalling pathways for therapeutic purposes, there are very real issues of how pharmacological specificity can be achieved. This issue is particularly acute in relation to the actions of insulin and IGFs, which appear to be mediated by precisely the same set of signalling pathways. The major therapeutic need in relation to insulin action is to mimic or potentiate insulin signalling in diabetes. However, this must be done without simultaneously provoking excessive IGF action, which is increasingly recognized as a contributory factor in cancer progression and metastasis. Although IR and IGFR mediate a similar spectrum of metabolic and mitogenic effects, when studied in the same cell background, there is evidence that the receptors differ in the effectiveness with which they signal to some endpoints.9, 394 – 396 It remains to be determined whether these differences arise from subtleties in the way the two receptors utilize common substrates and signalling pathways, or whether there are receptor-specific components that modulate the activity of core pathways.

1.6

Conclusion

The actions of insulin are mediated by a single receptor protein, which is now well characterized. The determinants of specific high affinity ligand binding in the extracellular portion of the receptor are understood in outline if not yet in detail. The full physiological significance of different forms of assembly of the IR, involving splice variants and hybrids with IGFR, remains unclear. It is generally assumed that all signalling by the IR requires its intrinsic tyrosine kinase activity that is stimulated by insulin binding. It is well established that the major metabolic effects of insulin depend on IRS phosphorylation, recruitment of PI 3-kinase and activation of downstream serine kinase cascades involving PKB, atypical PKCs and mTOR. There is accumulating evidence that obesity-associated insulin resistance reflects inhibitory influences on this pathway at the level of IRSs. Other substrates of the IR tyrosine kinase initiate separate signalling pathways that contribute to specific actions of insulin. The Cbl/Crk/TC-10 pathway is implicated in stimulation of glucose transport, in synergy with PI 3-kinase-dependent pathways. The Shc/Grb2/Sos/Ras pathway and ERK/MAPK cascade are responsible for some transcriptional regulation, particularly relating to growth promoting genes. A multitude of proteins may contribute additional signalling or regulatory mechanisms, either in specific tissues or in relation to specific insulin effects, and the full significance of many of these remains to be established. There is a growing appreciation of the importance of spatial and temporal aspects of signalling in determining the nature of insulin responses. Important questions concerning the molecular basis of insulin

REFERENCES

39

resistance in diabetes, whether genetically determined or brought about by other factors, remain to be resolved.

References 1. Nakae, J., Kido, Y. and Accili, D. (2001) Distinct and overlapping functions of insulin and IGF-I receptors. Endocr Rev 22, 818–835. 2. Kitamura, T., Kahn, C. R. and Accili, D. (2003) Insulin receptor knockout mice. Annu Rev Physiol 65, 313–332. 3. Gems, D. and Partridge, L. (2001) Insulin/IGF signalling and ageing: seeing the bigger picture. Curr Opin Genet Dev 11, 287–292. 4. Tatar, M., Bartke, A. and Antebi, A. (2003) The endocrine regulation of aging by insulin-like signals. Science 299, 1346–1351. 5. White, M. F. (2002) IRS proteins and the common path to diabetes. Am J Physiol Endocrinol Metab 283, E413–E422. 6. Van Obberghen, E., Baron, V., Delahaye, L., Emanuelli, B., Filippa, N., GiorgettiPeraldi, S., Lebrun, I., Mothe-Satney, I., Peraldi, P., Rocchi, S., Sawka-Verhelle, D., Tartare-Deckert, S. and Giudicelli, J. (2001) Surfing the insulin signaling web. Eur J Clin Invest 31, 966–977. 7. Saltiel, A. R. and Pessin, J. E. (2003) Insulin signaling in microdomains of the plasma membrane. Traffic 4, 711–716. 8. Saltiel, A. R. and Kahn, C. R. (2001) Insulin signalling and the regulation of glucose and lipid metabolism. Nature 414, 799–806. 9. Siddle, K., Urso, B., Niesler, C. A., Cope, D. L., Molina, L., Surinya, K. H. and Soos, M. A. (2001) Specificity in ligand binding and intracellular signalling by insulin and insulin-like growth factor receptors. Biochem Soc Trans 29, 513–525. 10. Gammeltoft, S. (1984) Insulin receptors: binding kinetics and structure–function relationship of insulin. Physiol Rev 64, 1321–1378. 11. Kasuga, M., Zick, Y., Blithe, D. L., Crettaz, M. and Kahn, C. R. (1982) Insulin stimulates tyrosine phosphorylation of the insulin receptor in a cell-free system. Nature 298, 667–669. 12. Ebina, Y., Ellis, L., Jarnagin, K., Edery, M., Graf, L., Clauser, E., Ou, J. H., Masiarz, F., Kan, Y. W., Goldfine, I. D., Roth, R. A. and Rutter, W. J. (1985) The human insulin receptor cDNA: the structural basis for hormone-activated transmembrane signalling. Cell 40, 747–758. 13. Ullrich, A., Bell, J. R., Chen, E. Y., Herrera, R., Petruzzeli, L. M., Dull, T. J., Gray, A., Coussens, L., Liao, Y.-C., Tsubokawa, M., Mason, A., Seeburg, P. H., Grunfeld, C., Rosen, O. M. and Ramachandran, J. (1985) Human insulin receptor and its relationship to the tyrosine kinase family of oncogenes. Nature 313, 756–761. 14. Seino, S., Seino, M. and Bell, G. I. (1990) Human insulin receptor gene. Diabetes 39, 129–133. 15. De Meyts, P. and Whittaker, J. (2002) Structural biology of insulin and IGF1 receptors: implications for drug design. Nature Rev Drug Discov 1, 769–783. 16. Adams, T. E., Epa, V. C., Garrett, T. P. J. and Ward, C. W. (2000) Structure and function of the type 1 insulin-like growth factor receptor. Cell Mol Life Sci 57, 1050–1093. 17. Yip, C. C. and Ottensmeyer, P. (2003) Three-dimensional structural interactions of insulin and its receptor. J Biol Chem 278, 27 329–27 332. 18. Hubbard, S. R. and Till, J. H. (2000) Protein tyrosine kinase structure and function. Annu Rev Biochem 69, 373–398.

40

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

19. Seino, S. and Bell, G. I. (1989) Alternative splicing of human insulin receptor messenger RNA. Biochem Biophys Res Commun 159, 312–316. 20. Benecke, H., Flier, J. S. and Moller, D. E. (1992) Alternatively spliced variants of the insulin receptor protein. Expression in normal and diabetic human tissues. J Clin Invest 89, 2066–2070. 21. Leibiger, B., Leibiger, I. B., Moede, T., Kemper, S., Kulkarni, R. N., Kahn, C. R., de Vargas, L. M. and Berggren, P. O. (2001) Selective insulin signaling through A and B insulin receptors regulates transcription of insulin and glucokinase genes in pancreatic beta cells. Mol Cell 7, 559–570. 22. Uhles, S., Moede, T., Liebiger, B., Berggren, P. O. and Leibiger, I. B. (2003) Isoformspecific insulin receptor signaling involves different plasma membrane domains. J Cell Biol 163, 1327–1337. 23. Elleman, T. C., Frenkel, M. J., Hoyne, P. A., McKern, N. M., Cosgrove, L., Hewish, D. R., Jachno, K. M., Bentley, J. D., Sankovich, S. E. and Ward, C. W. (2000) Mutational analysis of the N-linked glycosylation sites of the human insulin receptor. Biochem J 347, 771–779. 24. Sparrow, L. G., McKern, N. M., Gorman, J. J., Strike, P. M., Robinson, C. P., Bentley, J. D. and Ward, C. W. (1997) The disulfide bonds in the C-terminal domains of the human insulin receptor ectodomain. J Biol Chem 272, 29 460–29 467. 25. Yoshimasa, Y., Paul, J. I., Whittaker, J. and Steiner, D. F. (1990) Effects of amino acid replacements within the tetrabasic cleavage site on the processing of the human insulin receptor precursor expressed in Chinese hamster ovary cells. J Biol Chem 265, 17 230–17 237. 26. Cheatham, B. and Kahn, C. R. (1992) Cysteine 647 in the insulin receptor is required for normal covalent interaction between alpha- and beta-subunits and signal transduction. J Biol Chem 267, 7108–7115. 27. Ullrich, A., Gray, A., Tam, A. W., Yang-Feng, T., Tsubokawa, M., Collins, C., Henzel, W., LeBon, T., Kathuria, S., Chen, E., Jacobs, S., Francke, U., Ramachandran, J. and Fujita-Yamaguchi, Y. (1986) Insulin-like growth factor I receptor primary structure: comparison with insulin receptor suggests structural determinants that define functional specificity. EMBO J 5, 2503–2512. 28. Morgan, D. O., Edman, J. C., Standring, D. N., Fried, V. A., Smith, M. C., Roth,R. A. and Rutter, W. J. (1987) Insulin-like growth factor II receptor as a multifunctional binding protein. Nature 329, 301–307. 29. Liu, J. P., Baker, J., Perkins, A. S., Robertson, E. J. and Efstratiadis, A. (1993) Mice carrying null mutations of the genes encoding insulin-like growth factor I (Igf-1) and type 1 IGF receptor (Igf1r). Cell 75, 59–72. 30. Di Cola, G., Cool, M. H. and Accili, D. (1998) Hypoglycemic effect of insulin-like growth factor-1 in mice lacking insulin receptors. J Clin Invest 99, 2538–2544. 31. Shier, P. and Watt, V. M. (1989) Primary structure of a putative receptor for a ligand of the insulin family. J Biol Chem 264, 14 605–14 608. 32. Zhang, B. and Roth, R. A. (1992) The insulin receptor-related receptor. Tissue expression, ligand binding specificity, and signaling capabilities. J Biol Chem 267, 18 320–18 328. 33. Kitamura, T., Kido, Y., Nef, S., Merenmies, J., Parada, L. F. and Accili, D. (2001) Preserved pancreatic beta-cell development and function in mice lacking the insulin receptor-related receptor. Mol Cell Biol 21, 5624–5630. 34. Nef, S., Verma-Kurvari, S., Merenmies, J., Vassalli, J. D., Efstratiadis, A., Accili, D. and Parada, L. F. (2003) Testis determination requires insulin receptor family function in mice. Nature 426, 291–295.

REFERENCES

41

35. Poretsky, L. and Kalin, M. F. (1987) The gonadotrophic function of insulin. Endocr Rev 8, 132–141. 36. Fradkin, J. E., Eastman, R. C., Lesniak, M. A. and Roth, J. (1989) Specificity spillover at the hormone receptor – exploring its role in human disease. N Engl J Med 320, 640–645. 37. Yamaguchi, Y., Flier, J. S., Benecke, H., Ransil, B. J. and Moller, D. E. (1993) Ligandbinding properties of the two isoforms of the human insulin receptor. Endocrinology 132, 1132–1138. 38. Frasca, F., Pandini, G., Scalla, P., Sciacca, L., Mineo, R., Costantino, A., Goldfine, I. D., Belfiore, A. and Vigneri, R. (1999) Insulin receptor isoform A, a newly recognized high affinity insulin-like growth factor II receptor in fetal and cancer cells. Mol Cell Biol 19, 3278–3288. 39. Louvi, A., Accili, D. and Efstratiadis, A. (1997) Growth-promoting interaction of IGFII with the insulin receptor during mouse embryonic development. Dev Biol 189, 33–48. 40. Morrione, A., Valentinis, B., Xu, S. Q., Yumet, G., Louvi, A., Efstratiadis, A. and Baserga, R. (1997) Insulin-like growth factor II stimulates cell proliferation through the insulin receptor. Proc Natl Acad Sci USA 94, 3777–3782. 41. Moxham, C. P., Duronio, V. and Jacobs, S. (1989) Insulin-like growth factor I receptor β-subunit heterogeneity. Evidence for hybrid tetramers composed of insulin-like growth factor I and insulin receptor heterodimers. J Biol Chem 264, 13 238–13 244. 42. Soos, M. A. and Siddle, K. (1989) Immunological relationships between receptors for insulin and insulin-like growth factor I. Evidence for structural heterogeneity of insulinlike growth factor I receptors involving hybrids with insulin receptors. Biochem J 263, 553–563. 43. Treadway, J. L., Morrison, B. D., Goldfine, I. D. and Pessin, J. E. (1989) Assembly of insulin/insulin-like growth factor-1 hybrid receptors in vitro. J Biol Chem 264, 21 450–21 453. 44. Bailyes, E. M., Nav´e, B. T., Soos, M. A., Orr, S. R., Hayward, A. C. and Siddle, K. (1997) Insulin receptor/IGF-I receptor hybrids are widely distributed in mammalian tissues: quantification of individual receptor species by selective immunoprecipitation and immunoblotting. Biochem J 327, 209–215. 45. Pandini, G., Vigneri, R., Costantino, A., Frasca, F., Ippolito, A., Fujita-Yamaguchi, Y., Siddle, K., Goldfine, I. D. and Belfiore, A. (1999) Insulin and insulin-like growth factor-I (IGF-I) receptor overexpression in breast cancers leads to insulin/IGF-I hybrid receptor overexpression: evidence for a second mechanism of IGF-I signaling. Clin Cancer Res 5, 1935–1944. 46. Soos, M. A., Field, C. E. and Siddle, K. (1993) Purified hybrid insulin/insulin-like growth factor-I receptors bind insulin-like growth factor-I, but not insulin, with high affinity. Biochem J 290, 419–426. 47. Pandini, G., Frasca, F., Mineo, R., Sciacca, L., Vigneri, R. and Belfiore, A. (2002) Insulin/insulin-like growth factor I hybrid receptors have different biological characteristics depending on the insulin receptor isoform involved. J Biol Chem 277, 39 684–39 695. 48. Federici, M., Zucaro, L., Porzio, O., Massoud, R., Borboni, P., Lauro, D. and Sesti, G. (1996) Increased expression of insulin/insulin-like growth factor-I hybrid receptors in skeletal muscle of noninsulin-dependent diabetes mellitus subjects. J Clin Invest 98, 2887–2893. 49. Federici, M., Porzio, O., Lauro, D., Borboni, P., Giovannone, B., Zucaro, L., Hribal, M. L. and Sesti, G. (1998) Increased abundance of insulin/insulin-like growth factor-I hybrid receptors in skeletal muscle of obese subjects is correlated with in vivo insulin sensitivity. J Clin Endocrinol Metab 83, 2911–2915.

42

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

50. Frattali, A. L., Treadway, J. L. and Pessin, J. E. (1992) Transmembrane signaling by the human insulin receptor kinase. Relationship between intramolecular beta subunit trans- and cis-autophosphorylation and substrate kinase activation. J Biol Chem 267, 19 521–19 528. 51. Marino-Buslje, C., Martin-Martinez, M., Mizuguchi, K., Siddle, K. and Blundell, T. L. (1999) The insulin receptor: from protein sequence to structure. Biochem Soc Trans 27, 715–726. 52. Garrett, T. P., McKern, N. M., Lou, M., Frenkel, M. J., Bentley, J. D., Lovrecz, G. O., Elleman, T. C., Cosgrove, L. J. and Ward, C. W. (1998) Crystal structure of the first three domains of the type-1 insulin-like growth factor receptor. Nature 394, 395–399. 53. Ward, C. W. (1999) Members of the insulin receptor family contain three fibronectin type III domains. Growth Factors 16, 315–322. 54. Marino-Buslje, C., Mizuguchi, K., Siddle, K. and Blundell, T. L. (1999) A third fibronectin type III domain in the extracellular region of the insulin receptor family. FEBS Lett 441, 331–336. 55. Kristensen, C., Kjeldsen, T., Wiberg, F. C., Sch¨affer, L., Hach, M., Havelund, S., Baas, J., Steiner, D. F. and Andersen, A. S. (1997) Alanine scanning mutagenesis of insulin. J Biol Chem 272, 12 978–12 983. 56. Pillutla, R. C., Hsiao, K., Beasley, J. R., Brandt, J., Østergaard, S., Hansen, P. H., Spetzler, J. C., Danielsen, G. M., Andersen, A. S., Brissette, R. E., Lennick, M., Fletcher, P. W., Blume, A. J., Sch¨affer, L. and Goldstein, N. I. (2002) Peptides identify the critical hotspots involved in the biological activation of the insulin receptor. J Biol Chem 277, 22 590–22 594. 57. Schaffer, L., Brissette, R. E., Spetzler, J. C., Pillutla, R. C., Ostergaard, S., Lennick, M., Brandt, J., Fletcher, P. W., Danielsen, G. M., Hsiao, K. C., Andersen, A. S., Dedova, O., Ribel, U., Hoeg-Jensen, T., Hansen, P. H., Blume, A. J., Markussen, J. and Goldstein, N. I. (2003) Assembly of high-affinity insulin receptor agonists and antagonists from peptide building blocks. Proc Natl Acad Sci USA 100, 4435–4439. 58. Kristensen, C., Wiberg, F. C. and Andersen, A. S. (1999) Specificity of insulin and insulin-like growth factor I receptors investigated using chimeric mini-receptors. Role of C-terminal of receptor alpha subunit. J Biol Chem 274, 37 351–37 356. 59. Kristensen, C., Andersen, A. S., Østergaard, S., Hansen, P. H. and Brandt, J. (2002) Functional reconstitution of insulin receptor binding site from non-binding receptor fragments. J Biol Chem 277, 18 340–18 345. 60. Mynarcik, D. C., Williams, P. F., Schaffer, L., Yu, G. Q. and Whittaker, J. (1997) Identification of common ligand binding determinants of the insulin and insulin-like growth factor 1 receptors. Insights into mechanisms of ligand binding. J Biol Chem 272, 18 650–18 655. 61. de Vos, A. M., Ultsch, M. and Kossiakoff, A. A. (1992) Human growth hormone and extracellular domain of its receptor: crystal structure of the complex. Science 255, 306–312. 62. Ogiso, H., Ishitani, R., Nureki, O., Fukai, S., Yamanaka, M., Kim, J.-H., Saito, K., Sakamoto, A., Inoue, M., Shirouzu, M. and Yokoyama, S. (2002) Crystal structure of the complex of human epidermal growth factor and receptor extracellular domains. Cell 110, 775–787. 63. Garrett, T. P. J., McKern, N. M., Lou, M., Elleman, T. C., Adams, T. E., Lovrecz, G. O., Zhu, H.-J., Walker, F., Frenkel, M. J., Hoyne, P. A., Jorissen, R. N., Nice, E. C., Burgess, A. W. and Ward, C. W. (2002) Crystal structure of a truncated epidermal growth factor receptor extracellular domain bound to transforming growth factor alpha. Cell 110, 763–773.

REFERENCES

43

64. Frattali, A. L. and Pessin, J. E. (1993) Relationship between α-subunit ligand occupancy and β-subunit autophosphorylation in insulin/insulin-like growth factor-1 hybrid receptors. J Biol Chem 268, 7393–7400. 65. Lee, J., O’Hare, T., Pilch, P. F. and Shoelson, S. E. (1993) Insulin receptor autophosphorylation occurs asymmetrically. J Biol Chem 268, 4092–4098. 66. Villalba, M., Wente, S. R., Russell, D. S., Ahn, J. C., Reichelderfer, C. F. and Rosen, O. M. (1989) Another version of the human insulin receptor kinase domain: expression, purification, and characterization. Proc Natl Acad Sci USA 86, 7848–7852. 67. Ballotti, R., Lammers, R., Scimeca, J. C., Dull, T., Schlessinger, J., Ullrich, A. and Van Obberghen, E. (1989) Intermolecular transphosphorylation between insulin receptors and EGF-insulin receptor chimerae. EMBO J 8, 3303–3309. 68. Lee, J., Shoelson, S. E. and Pilch, P. F. (1995) Intermolecular phosphorylation between insulin holoreceptors does not stimulate substrate kinase activity. J Biol Chem 270, 31 136–31 140. 69. Tavar´e, J. M. and Siddle, K. (1993) Mutational analysis of insulin receptor function: consensus and controversy. Biochim Biophys Acta 1178, 21–39. 70. Favelyukis, S., Till, J. H., Hubbard, S. R. and Miller, W. T. (2001) Structure and autoregulation of the insulin-like growth factor 1 receptor kinase. Nat Struct Biol 8, 1058–1063. 71. Munshi, S., Kornienko, M., Hall, D. L., Reid, J. C., Waxman, L., Stirdivant, S. M., Darke, P. L. and Kuo, L. C. (2002) Crystal structure of the apo, unactivated insulin-like growth factor-1 receptor kinase. J Biol Chem 277, 38 797–38 802. 72. Gustafson, T. A., He, W., Craparo, A., Schaub, C. D. and O’Neill, T. J. (1995) Phosphotyrosine-dependent interaction of SHC and insulin-receptor substrate 1 with the NPEY motif of the insulin receptor via a novel non-SH2 domain. Mol Cell Biol 15, 2500–2508. 73. Wolf, G., Trub, T., Ottinger, E., Groninga, L., Lynch, A., White, M. F., Miyazaki, M., Lee, J. and Shoelson, S. E. (1995) PTB domains of IRS-1 and Shc have distinct but overlapping binding specificities. J Biol Chem 270, 27 407–27 410. 74. He, W., Craparo, A., Zhu, Y., O’Neill, T. J., Wang, L. M., Pierce, J. H. and Gustafson, T. A. (1996) Interaction of insulin receptor substrate-2 (IRS-2) with the insulin and insulin-like growth factor I receptors. Evidence for two distinct phosphotyrosine-dependent interaction domains within IRS-2. J Biol Chem 271, 11 641–11 645. 75. Sawka-Verhelle, D., Tartare-Deckert, S., White, M. F. and Van Obberghen, E. (1996) Insulin receptor substrate-2 binds to the insulin receptor through its phosphotyrosinebinding domain and through a newly identified domain comprising amino acids 591– 786. J Biol Chem 271, 5980–5983. 76. Hu, J., Liu, J., Ghirlando, R., Saltiel, A. R. and Hubbard, S. R. (2003) Structural basis for recruitment of the adaptor protein APS to the activated insulin receptor. Mol Cell 12, 379–389. 77. Stein, E. G., Ghirlando, R. and Hubbard, S. R. (2003) Structural basis for dimerization of the Grb10 Src homology 2 domain. Implications for ligand specificity. J Biol Chem 278, 13 257–13 264. 78. Staubs, P. A., Reichart, D. R., Saltiel, A. R., Milarski, K. L., Maegawa, H., Berhanu, P., Olefsky, J. M. and Seely, B. L. (1994) Localization of the insulin receptor binding sites for the SH2 domain proteins p85, Syp, and GAP. J Biol Chem 269, 27 186–27 192. 79. Rocchi, S., Tartare-Deckert, S., Sawka-Verhelle, D., Gamha, A. and Van Obberghen, E. (1996) Interaction of SH2-containing protein tyrosine phosphatase 2 with the insulin receptor and the insulin-like growth factor-I receptor: studies of the domains involved using the yeast two-hybrid system. Endocrinology 1996, 4944–4952.

44

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

80. Carpentier, J. L. (1994) Insulin receptor internalization: molecular mechanisms and physiopathological implications. Diabetologia 37, Suppl. 2, S117–124. 81. Backer, J. M., Shoelson, S. E., Weiss, M. A., Hua, Q. X., Cheatham, R. B., Haring, E., Cahill, D. C. and White, M. F. (1992) The insulin receptor juxtamembrane region contains two independent tyrosine/beta-turn internalization signals. J Cell Biol 118, 831–839. 82. Haft, C. R., Klausner, R. D. and Taylor, S. I. (1994) Involvement of dileucine motifs in the internalization and degradation of the insulin receptor. J Biol Chem 269, 26 286– 26 294. 83. Shackleton, S., Hamer, I., Foti, M., Zumwald, N., Maeder, C. and Carpentier, J. L. (2002) Role of two dileucine-like motifs in insulin receptor anchoring to microvilli. J Biol Chem 277, 43 631–43 637. 84. Bondy, C. A., Zhou, J., Chin, E., Reinhardt, R. R., Ding, L. and Roth, R. A. (1994) Cellular distribution of insulin-degrading enzyme gene expression. Comparison with insulin and insulin-like growth factor receptors. J Clin Invest 93, 966–973. 85. Di Guglielmo, G. M., Drake, P. G., Baass, P. C., Authier, F., Posner, B. I. and Bergeron, J. J. (1998) Insulin receptor internalization and signalling. Mol Cell Biochem 182, 59–63. 86. Chow, J. C., Condorelli, G. and Smith, R. J. (1998) Insulin-like growth factor-I receptor internalization regulates signaling via the Shc/mitogen-activated protein kinase pathway, but not the insulin receptor substrate-1 pathway. J Biol Chem 273, 4672–4680. 87. Ceresa, B. P., Kao, A. W., Santeler, S. R. and Pessin, J. E. (1998) Inhibition of clathrinmediated endocytosis selectively attenuates specific insulin receptor signal transduction pathways. Mol Cell Biol 18, 3862–3870. 88. Hamer, I., Foti, M., Emkey, R., Cordier-Bussat, M., Philippe, J., De Meyts, P., Maeder, C., Kahn, C. R. and Carpentier, J. L. (2002) An arginine to cysteine(252) mutation in insulin receptors from a patient with severe insulin resistance inhibits receptor internalisation but preserves signalling events. Diabetologia 45, 657–667. 89. Elchebly, M., Payette, P., Michaliszyn, E., Cromlish, W., Collins, S., Loy, A. L., Normandin, D., Cheng, A., Himms-Hagen, J., Chan, C. C., Ramachandran, C., Gresser, M. J., Tremblay, M. L. and Kennedy, B. P. (1999) Increased insulin sensitivity and obesity resistance in mice lacking the protein tyrosine phosphatase 1B gene. Science 283, 1544–1548. 90. Klaman, L. D., Boss, O., Peroni, O. D., Kim, J. K., Martino, J. L., Zabolotny, J. M., Moghal, N., Lubkin, M., Kim, Y. B., Sharpe, A. H., Stricker-Krongrad, A., Shulman, G. I., Neel, B. G. and Kahn, B. B. (2000) Increased energy expenditure, decreased adiposity, and tissue-specific insulin sensitivity in protein tyrosine phosphatase 1B-deficient mice. Mol Cell Biol 20, 5479–5489. 91. Ukkola, O. and Santaniemi, M. (2002) Protein tyrosine phosphatase 1B: a new target for the treatment of obesity and associated co-morbidities. J Intern Med, 251, 467–475. 92. Asante-Appiah, E. and Kennedy, B. P. (2003) Protein tyrosine phosphatases: the quest for negative regulators of insulin action. Am J Physiol Endocrinol Metab 284, E663–E670. 93. Xie, L., Lee, S. Y., Andersen, J. N., Waters, S., Shen, K., Guo, X. L., Moller, N. P., Olefsky, J. M., Lawrence, D. S. and Zhang, Z. Y. (2003) Cellular effects of small molecule PTP1B inhibitors on insulin signaling. Biochemistry 42, 12 792–12 804. 94. Lewis, R. E., Volle, D. J. and Sanderson, S. D. (1994) Phorbol ester stimulates phosphorylation on serine 1327 of the human insulin receptor. J Biol Chem 269, 26 259– 26 266. 95. Liu, F. and Roth, R. A. (1994) Identification of serines-967/968 in the juxtamembrane region of the insulin receptor as insulin-stimulated phosphorylation sites. Biochem J 298, 471–477.

REFERENCES

45

96. Liu, F. and Roth, R. A. (1994) Identification of serines-1035/1037 in the kinase domain of the insulin receptor as protein kinase C alpha mediated phosphorylation sites. FEBS Lett 352, 389–392. 97. Coghlan, M. P., Pillay, T. S., Tavare, J. M. and Siddle, K. (1994) Site-specific antiphosphopeptide antibodies: use in assessing insulin receptor serine/threonine phosphorylation state and identification of serine-1327 as a novel site of phorbol ester-induced phosphorylation. Biochem J 303, 893–899. 98. Bollag, G. E., Roth, R. A., Beaudoin, J., Mochly-Rosen, D. and Koshland, D. E. (1986) Protein kinase C directly phosphorylates the insulin receptor in vitro and reduces its protein-tyrosine kinase activity. Proc Natl Acad Sci USA 83, 5822–5824. 99. Bossenmaier, B., Mosthaf, L., Mischak, H., Ullrich, A. and H¨aring, H. U. (1997) Protein kinase C isoforms beta 1 and beta 2 inhibit the tyrosine kinase activity of the insulin receptor. Diabetologia 40, 863–866. 100. Strack, V., Hennige, A. M., Krutzfeldt, J., Bossenmaiers, B., Lein, H. H., Kellerer, M., Lammers, R. and H¨aring, H. U. (2000) Serine residues 994 and 1023/25 are important for insulin receptor kinase inhibition by protein kinase C isoforms beta2 and theta. Diabetologia 43, 443–449. 101. Mosthaf, L., Berti, L., Kellerer, M., Mushack, J., Seffer, E., Bossenmaier, B., Coghlan, M., Siddle, K., Ullrich, A. and Haring, H. U. (1995) C-terminus or juxtamembrane deletions in the insulin receptor do not affect the glucose-dependent inhibition of the tyrosine kinase activity. Eur J Biochem 227, 787–791. 102. Pillay, T. S., Xiao, S. and Olefsky, J. M. (1996) Glucose-induced phosphorylation of the insulin receptor: functional effects and characterization of phosphorylation sites. J Clin Invest 97, 613–620. 103. Zhou, Q., Dolan, P. L. and Dohm, G. L. (1999) Dephosphorylation increases insulinstimulated receptor kinase activity in skeletal muscle of obese Zucker rats. Mol Cell Biochem 194, 209–216. 104. Dunaif, A., Xia, J., Book, C. B., Schenker, E. and Tang, Z. (1995) Excessive insulin receptor serine phosphorylation in cultured fibroblasts and in skeletal muscle: A potential mechanism for insulin resistance in the polycystic ovary syndrome. J Clin Invest 96, 801–810. 105. Kellerer, M., Coghlan, M., Capp, E., Muhlhofer, A., Kroder, G., Mosthaf, L., Galante, P., Siddle, K. and Haring, H. U. (1995) Mechanism of insulin receptor kinase inhibition in non-insulin-dependent diabetes mellitus patients. Phosphorylation of serine 1327 or threonine 1348 is unaltered. J Clin Invest 96, 6–11. 106. Craparo, A., Freund, R. and Gustafson, T. A. (1997) 14–3–3 (ε) interacts with the insulin-like growth factor I receptor and insulin receptor substrate I in a phosphoserinedependent manner. J Biol Chem 272, 11 663–11 669. 107. Furlanetto, R. W., Dey, B. R., Lopaczynski, W. and Nissley, S. P. (1997) 14–3–3 proteins interact with the insulin-like growth factor receptor but not the insulin receptor. Biochem J 327, 765–771. 108. Araki, E., Murakami, T., Shirotani, T., Kanai, F., Shinohara, Y., Shimada, F., Mori, M., Shichiri, M. and Ebina, Y. (1991) A cluster of four Sp1 binding sites required for efficient expression of the human insulin receptor gene. J Biol Chem 266, 3944–3948. 109. Lee, J. K., Tam, J. W., Tsai, M. J. and Tsai, S. Y. (1992) Identification of cis- and trans-acting factors regulating the expression of the human insulin receptor gene. J Biol Chem 267, 4638–4645. 110. Levy, J. R. and Hug, V. (1993) Nuclear protein-binding analysis of a GC-rich insulinreceptor promoter regulatory region. Diabetes 42, 66–73. 111. Chen, H., Walker, G. E., Taylor, S. I. and McKeon, C. (1994) Proximal enhancer of the human insulin receptor gene binds the transcription factor Sp1. Diabetes 43, 884–889.

46

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

112. Cameron, K. E., Resnik, J. and Webster, N. J. (1992) Transcriptional regulation of the human insulin receptor gene. J Biol Chem 267, 17 375–17 383. 113. Brunetti, A., Foti, D. and Goldfine, I. D. (1993) Identification of unique nuclear regulatory proteins for the insulin receptor gene, which appear during myocyte and adipocyte differentiation. J Clin Invest 92, 1288–1295. 114. Webster, N. J., Kong, Y., Cameron, K. E. and Resnik, J. L. (1994) An upstream element from the human insulin receptor gene promoter contains binding sites for C/EBPbeta and NF-1. Diabetes 43, 305–312. 115. McKeon, C., Accili, D., Chen, H., Pham, T. and Walker, G. E. (1997) A conserved region in the first intron of the insulin receptor gene binds nuclear proteins during adipocyte differentiation. Biochem Biophys Res Commun 240, 701–706. 116. Lee, J. K. and Tsai, S. Y. (1994) Multiple hormone response elements can confer glucocorticoid regulation on the human insulin receptor gene. Mol Endocrinol 8, 625–634. 117. Mamula, P. W., McDonald, A. R., Brunetti, A., Okabayashi, Y., Wong, K. Y., Maddux, B. A., Logsdon, C. and Goldfine, I. D. (1990) Regulating insulin receptor gene expression by differentiation and hormones. Diabetes Care 13, 288–301. 118. Shen, W. J., Kim, H. S. and Tsai, S. Y. (1995) Stimulation of human insulin receptor gene expression by retinoblastoma gene product. J Biol Chem 270, 20 525–20 529. 119. Webster, N. J., Resnik, J. L., Reichart, D. B., Strauss, B., Haas, M. and Seely, B. L. (1996) Repression of the insulin receptor promoter by the tumor suppressor gene product p53: a possible mechanism for receptor over-expression in breast cancer. Cancer Res 56, 2781–2788. 120. Giraud, S., Greco, A., Brink, M., Diaz, J. J. and Delafontaine, P. (2001) Translation initiation of the insulin-like growth factor I receptor mRNA is mediated by an internal ribosome entry site. J Biol Chem 276, 5668–5675. 121. Knutson, V. P., Ronnett, G. V. and Lane, M. D. (1983) Rapid, reversible internalization of cell surface insulin receptors. Correlation with insulin-induced down regulation. J Biol Chem 258, 12 139–12 142. 122. Thien, C. B. and Langdon, W. Y. (2001) Cbl: many adaptations to regulate protein tyrosine kinases. Nat Rev Mol Cell Biol 2, 294–307. 123. Haglund, K., Sigismund, S., Polo, S., Szymkiewicz, L., Di Fiore, P. P. and Dikic, I. (2003) Multiple monoubiquitination of RTKs is sufficient for their endocytosis and degradation. Nat Cell Biol 5, 461–466. 124. Ahmed, Z., Smith, B. J. and Pillay, T. S. (2000) The APS adapter protein couples the insulin receptor to the phosphorylation of c-Cbl and facilitates ligand-stimulated ubiquitination of the insulin receptor. FEBS Lett 475, 31–34. 125. Vecchione, A., Marchese, A., Henry, P., Rotin, D. and Morrione, A. (2003) The Grb10/ Nedd4 complex regulates ligand-induced ubiquitination and stability of the insulin-like growth factor I receptor. Mol Cell Biol 23, 3363–3372. 126. Helmerhorst, E. and Yip, C. (1993) Insulin binding to rat liver membranes predicts a homogeneous class of binding sites in different affinity states that may be related to a regulator of insulin binding. Biochemistry 32, 2356–2362. 127. Ramalingam, T. S., Chakrabarti, A. and Edidin, M. (1997) Interaction of class I human leukocyte antigen (HLA-I) molecules with insulin receptors and its effect on the insulin signaling cascade. Mol Biol Cell 8, 2463–2474. 128. Goldfine, I. D., Maddux, B. A., Youngren, J. F., Frittitta, L., Trischitta, V. and Dohm, G. L. (1998) Membrane glycoprotein PC-1 and insulin resistance. Mol Cell Biochem 182, 177–184. 129. Norgren, S., Zierath, J., Galuska, D., Wallberg-Henriksson, H. and Luthman, H. (1993) Differences in the ratio of RNA encoding two isoforms of the insulin receptor between

REFERENCES

130.

131.

132.

133. 134.

135. 136. 137.

138.

139.

140. 141.

142.

143.

144.

145.

47

control and NIDDM patients. The RNA variant without Exon 11 predominates in both groups. Diabetes 42, 675–681. Anderson, C. M., Henry, R. R., Knudson, P. E., Olefsky, J. M. and Webster, N. J. (1993) Relative expression of insulin receptor isoforms does not differ in lean, obese, and noninsulin-dependent diabetes mellitus subjects. J Clin Endocrinol Metab 76, 1380– 1382. Kellerer, M., Sesti, G., Seffer, E., Obermaier-Kusser, H., Pongratz, D. E., Mosthaf, L. and Haring, H. U. (1993) Altered pattern of insulin receptor isotypes in skeletal muscle membranes of type 2 (non-insulin-dependent) diabetic subjects. Diabetologia 36, 628–632. Hansen, T., Bjorbaek, C., Vestergaard, H., Gronskov, K., Bak, J. F. and Pedersen, O. (1993) Expression of insulin receptor spliced variants and their functional correlates in muscle from patients with non-insulin-dependent diabetes mellitus. J Clin Endocrinol Metab 77, 1500–1505. Sell, S. M., Reese, D. and Ossowski, V. M. (1994) Insulin-inducible changes in insulin receptor mRNA splice variants. J Biol Chem 269, 30 769–30 772. Savkur, R. S., Philips, A. V. and Cooper, T. A. (2001) Aberrant regulation of insulin receptor alternative splicing is associated with insulin resistance in myotonic dystrophy. Nat Genet 29, 40–47. White, M. F. (1998) The IRS-signaling system: a network of docking proteins that mediate insulin and cytokine action. Rec Prog Horm Res 53, 119–138. White, M. F., Maron, R. and Kahn, C. R. (1985) Insulin rapidly stimulates phosphorylation of a Mr-185,000 protein in intact cells. Nature 318, 183–186. Sun, X. J., Rothenberg, P., Kahn, C. R., Backer, J. M., Araki, E., Wilden, P. A., Cahill, D. A., Goldstein, B. J. and White, M. F. (1991) Structure of the insulin receptor substrate IRS-1 defines a unique signal transduction protein. Nature 352, 73–77. Sun, X. J., Wang, L. M., Zhang, Y., Yenush, L., Myers, M. G., Glasheen, E., Lane, W. S., Pierce, J. H. and White, M. F. (1995) Role of IRS-2 in insulin and cytokine signalling. Nature 377, 173–177. Johnston, J. A., Wang, L. M., Hanson, E. P., Sun, X. J., White, M. F., Oakes, S. A., Pierce, J. H. and O’Shea, J. J. (1995) Interleukins 2, 4, 7, and 15 stimulate tyrosine phosphorylation of insulin receptor substrates 1 and 2 in T cells. Potential role of JAK kinases. J Biol Chem 270, 28 527–28 530. Yenush, L. and White, M. F. (1997) The IRS-signalling system during insulin and cytokine action. Bioessays 19, 491–500. He, W., O’Neill, T. J. and Gustafson, T. A. (1995) Distinct modes of interaction of SHC and insulin receptor substrate-1 with the insulin receptor NPEY region via nonSH2 domains. J Biol Chem 270, 23 258–23 262. van der Geer, P., Wiley, S. and Pawson, T. (1999) Re-engineering the target specificity of the insulin receptor by modification of a PTB domain binding site. Oncogene 18, 3071–3075. Yenush, L., Makati, K. J., Smith-Hall, J., Ishibashi, O., Myers, M. G. and White, M. F. (1996) The pleckstrin homology domain is the principal link between the insulin receptor and IRS-1. J Biol Chem 271, 24 300–24 306. Jacobs, A. R., LeRoith, D. and Taylor, S. I. (2001) Insulin receptor substrate-1 pleckstrin homology and phopshotyrosine-binding domains are both involved in plasma membrane targeting. J Biol Chem 276, 40 795–40 802. Vainshtein, I., Kovacina, K. S. and Roth, R. A. (2001) The insulin receptor substrate (IRS)-1 pleckstrin homology domain functions in downstream signaling. J Biol Chem 276, 8073–8078.

48

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

146. Eck, M. J., Dhe-Paganon, S., Trub, T., Nolte, R. T. and Shoelson, S. E. (1996) Structure of the IRS-1 PTB domain bound to the juxtamembrane region of the insulin receptor. Cell 85, 695–705. 147. Dhe-Paganon, S., Ottinger, E. A., Nolte, R. T., Eck, M. J. and Shoelson, S. E. (1999) Crystal structure of the pleckstrin homology–phosphotyrosine binding (PH-PTB) targeting region of insulin receptor substrate 1. Proc Natl Acad Sci USA 96, 8378–8383. 148. Razzini, G., Ingrosso, A., Brancaccio, A., Sciacchitano, S., Esposito, D. L. and Falasca, M. (2000) Different subcellular localization and phosphoinositides binding of insulin receptor substrate protein pleckstrin homology domains. Mol Endocrinol 14, 823–836. 149. Burks, D. J., Wang, J., Towery, H., Ishibashi, O., Riedel, H. and White, M. F. (1998) IRS pleckstrin homology domains bind to acidic motifs in proteins. J Biol Chem 273, 31 061–31 067. 150. Farhang-Fallah, J., Randhawa, V. K., Nimnual, A., Klip, A., Bar-Sagi, D. and RozakisAdcock, M. (2002) The pleckstrin homology (PH) domain-interacting protein couples the insulin receptor substrate 1 PH domain to insulin signaling pathways leading to mitogenesis and GLUT4 translocation. Mol Cell Biol 22, 7325–7336. 151. Inoue, G., Cheatham, B., Emkey, R. and Kahn, C. R. (1998) Dynamics of insulin signaling in 3T3-L1 adipocytes. Differential compartmentation and trafficking of insulin receptor substrate (IRS)-1 and IRS-2. J Biol Chem 273, 11 548–11 555. 152. Clark, S. F., Molero, J. C. and James, D. E. (2000) Release of insulin receptor substrate proteins from an intracellular complex coincides with the development of insulin resistance. J Biol Chem 275, 3819–3826. 153. Araki, E., Lipes, M. A., Patti, M. E., Bruning, J. C., Haag, B., Johnson, R. S. and Kahn, C. R. (1994) Alternative pathway of insulin signalling in mice with targeted disruption of the IRS-1 gene. Nature 372, 186–190. 154. Tamemoto, H., Kadowaki, T., Tobe, K., Yagi, T., Sakura, H., Hayakawa, T., Terauchi, Y., Ueki, K., Kaburagi, Y., Satoh, S., Hisahiko, S., Yoshioka, S., Horikoshi, H., Furuta, Y., Ikawa, Y., Kasuga, M., Yazaki, Y. and Aizawa, S. (1994) Insulin resistance and growth retardation in mice lacking insulin receptor substrate-1. Nature 372, 182–186. 155. Bruning, J. C., Winnay, J., Bonner-Weir, S., Taylor, S. I., Accili, D. and Kahn, C. R. (1997) Development of a novel polygenic model of NIDDM in mice heterozygous for IR and IRS-1 null alleles. Cell 88, 561–572. 156. Withers, D. J., Gutierrez, J. S., Towery, H., Burks, D. J., Ren, J. M., Previs, S., Zhang, Y., Bernal, D., Pons, S., Shulman, G. I., Bonner-Weirt, S. and White, M. F. (1998) Disruption of IRS-2 causes type 2 diabetes in mice. Nature 391, 900–904. 157. Kido, Y., Burks, D. J., Withers, D., Bruning, J. C., Kahn, C. R., White, M. F. and Accili, D. (2000) Tissue-specific insulin resistance in mice with mutations in the insulin receptor, IRS-1 and IRS-2. J Clin Invest 105, 199–205. 158. Burks, D. J., Font de Mora, J., Schubert, M., Withers, D. J., Myers, M. J., Towery, H. H., Altamuro, S. L., Flint, C. L. and White, M. F. (2000) IRS-2 pathways integrate female reproduction and energy homeostasis. Nature 407, 377–382. 159. Br¨uning, J. C., Winnay, J., Cheatham, B. and Kahn, C. R. (1997) Differential signaling by insulin receptor substrate 1 (IRS-1) and IRS-2 in IRS-1-deficient cells. Mol Cell Biol 17, 1513–1521. 160. Lavan, B. E., Lane, W. S. and Lienhard, G. E. (1997) The 60-kDa phosphotyrosine protein in insulin-treated adipocytes is a new member of the insulin receptor substrate family. J Biol Chem 272, 11 439–11 443. 161. Bj¨ornholm, M., He, A. R., Attersand, A., Lake, S., Liu, S. C. H., Lienhard, G. E., Taylor, S., Arner, P. and Zierath, J. R. (2002) Absence of functional insulin receptor substrate-3 (IRS-3 ) gene in humans. Diabetologia 45, 1697–1702.

REFERENCES

49

162. Liu, S. C., Wang, Q., Lienhard, G. E. and Keller, S. R. (1999) Insulin receptor substrate 3 is not essential for growth or glucose homeostasis. J Biol Chem 274, 18 093–18 099. 163. Laustsen, P. G., Michael, M. D., E. C. B., Cohen, S. E., Ueki, K., Kulkarni, R. N., Keller, S. R., Lienhard, G. E. and Kahn, C. R. (2002) Lipoatrophic diabetes in Irs1(−/−)/Irs3(−/−) double knockout mice. Genes Dev 16, 3213–3222. 164. Lavan, B. E., Fantin, V. R., Chang, E. T., Lane, W. S., Keller, S. R. and Lienhard, G. E. (1997) A novel 160-kDa phosphotyrosine protein in insulin-treated embryonic kidney cells is a new member of the insulin receptor substrate family. J Biol Chem 272, 21 403–21 407. 165. Fantin, V. R., Wang, Q., Lienhard, G. E. and Keller, S. R. (2000) Mice lacking insulin receptor substrate 4 exhibit mild defects in growth, reproduction and glucose homeostasis. Am J Physiol Endocrinol Metab 278, E127–E133. 166. Zick, Y. (2001) Insulin resistance: a phosphorylation based uncoupling of insulin signaling. Trends Biochem Sci 11, 437–441. 167. Le Marchand-Brustel, Y., Gual, P., Gr´emeaux, T., Gonzalez, T., Barres, R. and Tanti, J.-F. (2003) Fatty acid-induced insulin resistance: role of insulin receptor substrate 1 serine phosphorylation in the retroregulation of insulin signalling. Biochem Soc Trans 31, 1152–1156. 168. Schmitz-Peiffer, C. and Whitehead, J. P. (2003) IRS-1 regulation in health and disease. IUBMB Life 55, 367–374. 169. Johnston, A. M., Pirola, L. and Van Obberghen, E. (2003) Molecular mechanisms of insulin receptor substrate protein-mediated modulation of insulin signalling. FEBS Lett 546, 32–36. 170. Greene, M. W. and Garofalo, R. S. (2002) Positive and negative regulatory roles of insulin receptor substrate 1 and 2 (IRS-1 and IRS-2) serine/threonine phosphorylation. Biochemistry 41, 7082–7091. 171. Paz, K., Liu, Y. F., DShorer, H., Hemi, R., LeRoith, D., Quan, M., Kanety, H., Seger, R. and Zick, Y. (1999) Phosphorylation of insulin receptor substrate-1 (IRS-1) by protein kinase B positively regulates IRS-1 function. J Biol Chem 274, 28 816–28 822. 172. Jakobsen, S. N., Hardie, D. G., Morrice, N. and Tornqvist, H. (2001) 5
-AMP-activated protein kinase phosphorylates IRS-1 on Ser-789 in mouse C2C12 myotubes in response to 5-aminoimidazole-4-carboxamide riboside. J Biol Chem 276, 46 912–46 916. 173. Giraud, J., Leshan, R., Lee, Y. H., and White, M. F. (2004) Nutrient-dependent and insulin-stimulated phosphorylation of insulin receptor substrate-1 on serine 302 correlates with increased insulin signaling. J Biol Chem 279, 3447–3454. 174. Ogihara, T., Isobe, T., Ichimura, T., Taoka, M., Funaki, M., Sakoda, H., Onishi, Y., Inukai, K., Anai, M., Fukushima, Y., Kikuchi, M., Yazaki, Y., Oka, Y. and Asano, T. (1997) 14–3–3 protein binds to insulin receptor substrate-1, one of the binding sites of which is in the phosphotyrosine binding domain. J Biol Chem 272, 25 267–25 274. 175. Kosaki, A., Yamada, K., Suga, J., Otaka, A. and Kuzuya, H. (1998) 14–3–3beta protein associates with insulin receptor substrate 1 and decreases insulin-stimulated phosphatidylinositol 3
-kinase activity in 3T3L1 adipocytes. J Biol Chem 273, 940–944. 176. Xiang, X., Yuan, M., Song, Y., Ruderman, N., Wen, R. and Luo, Z. (2002) 14–3–3 facilitates insulin-stimulated intracellular trafficking of insulin receptor substrate 1. Mol Endocrinol 16, 552–562. 177. Rui, L., Yuan, M., Frantz, D., Shoelson, S. and White, M. F. (2002) SOCS-1 and SOCS-3 block insulin signaling by ubiquitin-mediated degradation of IRS-1 and IRS-2. J Biol Chem 277, 42 394–42 398. 178. White, M. F. (1997) The insulin signalling system and the IRS proteins. Diabetologia 40 (Suppl 2), S2–17.

50

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

179. Mothe, I. and Van Obberghen, E. (1996) Phosphorylation of insulin receptor substrate-1 on multiple serine residues, 612, 632, 662, and 731, modulates insulin action. J Biol Chem 271, 11 222–11 227. 180. De Fea, K. and Roth, R. A. (1997) Protein kinase C modulation of insulin receptor substrate-1 tyrosine phosphorylation requires serine 612. Biochemistry 36, 12 939–12 947. 181. De Fea, K. and Roth, R. A. (1997) Modulation of insulin receptor substrate-1 tyrosine phosphorylation and function by mitogen-activated protein kinase. J Biol Chem 272, 31 400–31 406. 182. Paz, K., Hemi, R., LeRoith, D., Karasik, A., Elhanany, E., Kanety, H. and Zick, Y. (1997) A molecular basis for insulin resistance: elevated serine/threonine phosphorylation of IRS-1 and IRS-2 inhibits their binding to the juxtamembrane region of the insulin receptor and impairs their ability to undergo insulin-induced tyrosine phosphorylation. J Biol Chem 272, 29 911–29 918. 183. Aguirre, V., Werner, E. D., Giraud, J., Lee, Y. H., Shoelson, S. E. and White, M. F. (2002) Phosphorylation of Ser307 in insulin receptor substrate-1 blocks interactions with the insulin receptor and inhibits insulin action. J Biol Chem 277, 1531–1537. 184. Haruta, T., Uno, T., Kawahara, J., Takano, A., Egawa, K., Sharma, P. M., Olefsky, J. M. and Kobayashi, M. (2000) A rapamycin-sensitive pathway down-regulates insulin signaling via phosphorylation and proteasomal degradation of insulin receptor substrate-1. Mol Endocrinol 14, 783–794. 185. Takano, A., Usui, I., Haruta, T., Kawahara, J., Uno, T., Iwata, M. and Kobayashi, M. (2001) Mammalian target of rapamycin pathway regulates insulin signaling via subcellular redistribution of insulin receptor substrate 1 and integrates nutritional signals and metabolic signals of insulin. Mol Cell Biol 21, 5050–5062. 186. Greene, M. W., Sakaue, H., Wang, L., Alessi, D. R. and Roth, R. A. (2003) Modulation of insulin-stimulated degradation of human insulin receptor substrate-1 by serine 312 phosphorylation. J Biol Chem 278, 8199–8211. 187. Gual, P., Gremeaux, T., Gonzalez, T., Le Marchand-Brustel, Y. and Tanti, J. F. (2003) MAP kinases and mTOR mediate insulin-induced phosphorylation of insulin receptor substrate-1 on serine residues 307, 612 and 632. Diabetologia 46, 1532–1542. 188. Aguirre, V., Uchida, T., Yenush, L., Davis, R. and White, M. F. (2000) The c-Jun NH(2)-terminal kinase promotes insulin resistance during association with insulin receptor substrate-1 and phosphorylation of Ser(307). J Biol Chem 275, 9047–9054. 189. Rui, L., Aguirre, V., Kim, J., Shulman, G. I., Lee, A., Corbould, A., Dunaif, A. and White, M. F. (2001) Insulin/IGF-1 and TNF-alpha stimulate phosphorylation of IRS-1 at inhibitory Ser307 via distinct pathways. J Clin Invest 107, 181–189. 190. Kim, J. K., Kim, Y. J., Fillmore, J. J., Chen, Y., Moore, I., Lee, J., Yuan, M., Li, Z. W., Karin, M., Perret, P., Shoelson, S. E. and Shulman, G. I. (2001) Prevention of fat-induced insulin resistance by salicylate. J Clin Invest 108, 437–446. 191. Yu, C., Chen, Y., Zhong, H., Wang, Y., Bergeron, R., Kim, J. K., Cline, G. W., Cushman, S. W., Cooney, G. J., Atcheson, B., White, M. F., Kraegen, E. W. and Shulman, G. I. (2002) Mechanism by which fatty acids inhibit insulin activation of IRS-1 associated phosphatidylinositol 3-kinase activity in muscle. J Biol Chem 277, 50 230–50 236. 192. Lee, Y. H., Giraud, J., Davis, R. J. and White, M. F. (2003) c-Jun N-terminal kinase (JNK) mediates feedback inhibition of the insulin signaling cascade. J Biol Chem 278, 2896–2902. 193. Kanety, H., Feinstein, R., Papa, M. Z., Hemi, R. and Karasik, A. (1995) Tumor necrosis factor alpha-induced phosphorylation of insulin receptor substrate-1 (IRS-1).

REFERENCES

194.

195. 196.

197.

198. 199.

200.

201.

202. 203.

204.

205. 206.

207. 208. 209. 210.

211.

51

Possible mechanism for suppression of insulin-stimulated tyrosine phosphorylation of IRS-1. J Biol Chem 270, 23 780–23 784. Hotamisligil, G. S., Peraldi, P., Budavari, A., Ellis, R., White, M. F. and Spiegelman, B. M. (1996) IRS-1-mediated inhibition of insulin receptor tyrosine kinase activity in TNF-alpha- and obesity-induced insulin resistance. Science 271, 665–668. Shulman, G. I. (2000) Cellular mechanisms of insulin resistance. J Clin Invest 106, 171–176. Bouzakri, K., Roques, M., Gual, P., Espinosa, S., Guebre-Egziabher, F., Riou, J. P., Laville, M., Le Marchand-Brustel, Y., Tanti, J. F. and Vidal, H. (2003) Reduced activation of phosphatidylinositol 3-kinase and increased serine 636 phosphorylation of insulin receptor substrate-1 in primary culture of skeletal muscle cells from patients with type 2 diabetes. Diabetes 52, 1319–1325. Cai, D., Dhe-Paganon, S., Melendez, P. A., Lee, J. and Shoelson, S. E. (2003) Two new substrates in insulin signaling, IRS5/DOK4 and IRS6/DOK5. J Biol Chem 278, 25 323–25 330. Liu, Y. and Rohrschneider, L. R. (2002) The gift of Gab. FEBS Lett 515, 1–7. Holdago-Madruga, M., Emlet, D. R., Moscatello, D. K., Godwin, A. K. and Wong, A. J. (1996) A Grb2-associated docking protein in EGF- and insulin-receptor signalling. Nature 379, 560–563. Rocchi, S., Tartare-Deckert, S., Murdaca, J., Holdago-Madruga, M., Wong, A. J. and Van Obberghen, E. (1998) Determination of Gab1 (Grb2-associated binder-1) interaction with insulin receptor-signaling molecules. Mol Endocrinol 12, 914–923. Lehr, S., Kotzka, J., Herkner, A., Sikmann, A., Meyer, H. E., Krone, W. and MullerWieland, D. (2000) Identification of major tyrosine phosphorylation sites in the human insulin receptor substrate Gab-1 by insulin receptor kinase in vitro. Biochemistry 39, 10 898–10 907. Winnay, J. N., Br¨uning, J. C., Burks, D. J. and Kahn, C. R. (2000) Gab-1-mediated IGF-1 signaling in IRS-1-deficient 3T3-fibroblasts. J Biol Chem 275, 10 545–10 550. Harada, S., Esch, G. L., Holdago-Madruga, M. and Wong, A. J. (2001) Grb-2associated binder-1 is involved in insulin-induced egr-1 gene expression through its phosphatidylinositol 3
-kinase binding site. DNA Cell Biol 20, 223–229. Pelicci, G., Lanfrancone, L., Grignani, F., McGlade, J., Fomi, G., Nicoletti, I., Pawson, T. and Pelicci, P. G. (1992) A novel transforming protein (SHC) with an SH2 domain is implicated in mitogenic signal transduction. Cell 70, 93–104. Pronk, G. J., McGlade, J., Pelicci, G., Pawson, T. and Bos, J. L. (1993) Insulin-induced phosphorylation of the 46- and 52-kDa Shc proteins. J Biol Chem 268, 5748–5753. Kovacina, K. S. and Roth, R. A. (1993) Identification of SHC as a substrate of the insulin receptor kinase distinct from the GAP-associated 62 kDa tyrosine phosphoprotein. Biochem Biophys Res Commun 192, 1303–1311. Sasaoka, T. and Kobayashi, M. (2000) The functional significance of Shc in insulin signalling as a substrate of the insulin receptor. Endocr J 47, 373–381. Luzi, L., Confalonieri, S., Di Fiore, P. P. and Pelicci, P. G. (2000) Evolution of Shc functions from nematode to human. Curr Opin Genet Dev 10, 668–674. Ravichandran, K. S. (2001) Signaling via Shc family adapter proteins. Oncogene 20, 6322–6330. van der Geer, P., Wiley, S., Gish, G. D. and Pawson, T. (1996) The Shc adaptor protein is highly phosphorylated at conserved, twin tyrosine residues (Y239/240) that mediate protein–protein interactions. Curr Biol 6, 1435–1444. Ishihara, H., Sasaoka, T., Wada, T., Ishiki, M., Haruta, T., Usui, I., Iwata, M., Takano, A., Uno, T., Ueno, E. and Kobayashi, M. (1998) Relative involvement of Shc tyrosine residues 239/240 and tyrosine 317 on insulin-induced mitogenic signaling

52

212.

213.

214.

215.

216.

217.

218.

219.

220.

221.

222. 223.

224.

225. 226.

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

in rat1 fibroblasts expressing insulin receptors. Biochem Biophy Res Commun 252, 139–144. Migliaccio, E., Mele, S., Salcini, A. E., Pelicci, G., Lai, K.-M. V., Superti-Furga, G., Pawson, T., DiFiore, P. P., Lanfrancone, L. and Pelicci, P. G. (1997) Opposite effects of the p52shc/p46shc and p66shc splicing iosforms in the EGF receptor–MAP kinase–fos signalling pathway. EMBO J 16, 706–716. Okada, S., Kao, A. W., Ceresa, B. P., Blaikie, P., Margolis, B. and Pessin, J. E. (1997) The 66-kDa Shc isoform is a negative regulator of the epidermal growth factorstimulated mitogen-activated protein kinase pathway. J Biol Chem 272, 28 042–28 049. Kao, A. W., Waters, S. B., Okada, S. and Pessin, J. E. (1997) Insulin stimulates the phosphorylation of the 66- and 52-kilodalton Shc isoforms by distinct pathways. Endocrinology 138, 2472–2480. Skolnik, E., Lee, C. H., Batzer, A., Vicentini, L. M., Zhou, M., Daly, R., Myers, M. J., Backer, J. M., Ullrich, A. and White, M. F. (1993) The SH2/SH3 domain-containing protein GRB2 interacts with tyrosine-phosphorylated IRS1 and Shc: implications for insulin control of ras signalling. EMBO J 12, 1929–1936. Myers, M. G., Wang, L. M., Sun, X. J., Zhang, Y., Yenush, L., Schlessinger, J., Pierce, J. H. and White, M. F. (1994) Role of IRS-1-GRB-2 complexes in insulin signaling. Mol Cell Biol 14, 3577–3587. Sasaoka, T., Draznin, B., Leitner, J. W., Langlois, W. J. and Olefsky, J. M. (1994) Shc is the predominant signaling molecule coupling insulin receptors to activation of guanine nucleotide releasing factor and p21ras-GTP formation. J Biol Chem 269, 10 734–10 738. Valentinis, B., Romano, G., Peruzzi, F., Morrione, A., Prisco, M., Soddu, S., Cristofanelli, B., Sacchi, A. and Baserga, R. (1999) Growth and differentiation signals by the insulin-like growth factor 1 receptor in hemopoietic cells are mediated through different pathways. J Biol Chem 274, 12 423–12 430. Sasaoka, T., Ishiki, M., Wada, T., Hori, H., Hirai, H., Haruta, T., Ishihara, H. and Kobayashi, M. (2001) Tyrosine phosphorylation-dependent and -independent role of Shc in the regulation of IGF-1-induced mitogenesis and glycogen synthesis. Endocrinology 142, 5226–5235. Poy, N. M., Ruch, R. J., Fernstrom, M. A., Okabayashi, Y. and Najjar, S. M. (2002) Shc and CEACAM1 interact to regulate the mitogenic action of insulin. J Biol Chem 277, 1076–1084. Emanuelli, B., Peraldi, P., Filloux, C., Sawka-Verhelle, D., Hilton, D. and Van Obberghen, E. (2000) SOCS-3 is an insulin-induced negative regulator of insulin signaling. J Biol Chem 275, 15 985–15 991. Ahmed, Z. and Pillay, T. S. (2001) Functional effects of APS and SH2-B on insulin receptor signalling. Biochem Soc Trans 29, 529–534. Kotani, K., Wilden, P. and Pillay, T. S. (1998) SH2-Bα is an insulin-receptor adapter protein and substrate that interacts with the activation loop of the insulin-receptor kinase. Biochem J 335, 103–109. Ahmed, A., Smith, B. J., Kotani, K., Wilden, P. and Pillay, T. S. (1999) APS, an adapter protein with a PH and SH2 domain, is a substrate for the insulin receptor kinase. Biochem J 341, 665–668. Moodie, S. A., Alleman-Sposeto, J. and Gustafson, T. A. (1999) Identification of the APS protein as a novel insulin receptor substrate. J Biol Chem 274, 11 186–11 193. Ahmed, Z. and Pillay, T. S. (2003) Adapter protein with a pleckstrin homology (PH) and an Src homology 2 (SH2) domain (APS) and SH2-B enhance insulin-receptor autophosphorylation, extracellular-signal-regulated kinase and phosphoinositide 3kinase-dependent signalling. Biochem J 371, 405–412.

REFERENCES

53

227. Riedel, H., Yousaf, N., Zhao, Y., Dai, H., Deng, Y. and Wang, J. (2000) PSM, a mediator of PDGF-BB-, IGF-I- and insulin-stimulated mitogenesis. Oncogene 19, 39–50. 228. Yousaf, N., Deng, Y., Kang, Y. and Riedel, H. (2001) Four PSM/SH2-B alternative splice variants and their differential roles in mitogenesis. J Biol Chem 276, 40 940–40 948. 229. Liu, J., Kimura, A., Baumann, C. A. and Saltiel, A. R. (2002) APS facilitates c-Cbl tyrosine phosphorylation and GLUT4 translocation in response to insulin in 3T3-L1 adipocytes. Mol Cell Biol 22, 3599–3609. 230. Minami, A., Iseki, M., Kishi, K., Wang, M., Ogura, M., Furukawa, N., Hayashi, S., Yamada, M., Obata, T., Takeshita, Y., Nakaya, Y., Bando, Y., Izumi, K., Moodie, S. A., Kajiura, F., Matsumoto, M., Takatsu, K., Takaki, S. and Ebina, Y. (2003) Increased insulin sensitivity and hypoinsulinaemia in APS knockout mice. Diabetes 52, 2657–2665. 231. Ohtsuka, S., Takaki, S., Iseki, M., Miyoshi, K., Nakagata, N., Kataoka, Y., Yoshida, N., Takatsu, K. and Yoshimura, A. (2002) SH2-B is required for both male and female reproduction. Mol Cell Biol 22, 3066–3077. 232. Daly, R. J. (1998) The Grb7 family of signalling proteins. Cell Signal 10, 613–618. 233. Han, D. C., Shen, T. L. and Guan, J. L. (2001) The Grb7 family proteins: structure, interactions with other signaling molecules and potential cellular functions. Oncogene 20, 6315–6321. 234. Morrione, A. (2003) Grb10 adapter protein as a regulator of insulin-like growth factor signaling. J Cell Physiol 197, 307–311. 235. Langlais, P., Dong, L. Q., Hu, D. and Liu, F. (2000) Identification of Grb10 as a direct substrate for members of the Src tyrosine kinase family. Oncogene 2000, 2895–2903. 236. O’Neill, T. J., Rose, D. W., Pillay, T. S., Hotta, K., Olefsky, J. M. and Gustafson, T. A. (1996) Interaction of a Grb-IR splice variant (a human Grb10 homolog) with the insulin and insulin-like growth factor-I receptors. Evidence for a role in mitogenic signaling. J Biol Chem 271, 22 506–22 513. 237. Laviola, L., Giorgino, F., Chow, J. C., Baquero, J. A., Hansen, H., Ooi, J., Zhu, J., Riedel, H. and Smith, R. J. (1997) The adapter protein Grb10 associates preferentially with the insulin receptor as compared with the IGF-I receptor in mouse fibroblasts. J Clin Invest 99, 830–837. 238. He, W., Rose, D. W., Olefsky, J. M. and Gustafson, T. A. (1998) Grb10 interacts differentially with the insulin receptor, insulin-like growth factor I receptor, and epidermal growth factor receptor via the Grb10 Src homology 2 (SH2) domain and a second novel domain located between the pleckstrin homology and SH2 domains. J Biol Chem 273, 6860–6867. 239. Hemming, R., Agatep, R., Badiani, K., Wyant, K., Arthur, G., Gietz, R. D. and TriggsRaine, B. (2001) Human growth factor receptor bound 14 binds the activated insulin receptor and alters the insulin-stimulated tyrosine phosphorylation levels of multiple proteins. Biochem Cell Biol 79, 21–32. 240. Bereziat, V., Kasus-Jacobi, A., Perdereau, D., Cariou, B., Girard, J. and Burnol, A. F. (2002) Inhibition of insulin receptor catalytic activity by the molecular adapter Grb14. J Biol Chem 277, 4845–4852. 241. Wick, K. R., Werner, E. D., Langlais, P., Ramos, F. J., Dong, L. O., Shoelson, S. E. and Liu, F. (2003) Grb10 inhibits insulin-stimulated insulin receptor substrate (IRS)phosphatidylinositol 3-kinase/Akt signaling pathway by disrupting the association of IRS-1/IRS-2 with the insulin receptor. J Biol Chem 278, 8460–8467. 242. Wang, J., Dai, H., Yousaf, N., Moussaif, M., Deng, Y., Boufelliga, A., Swamy, O. R., Leone, M. E. and Riedel, H. (1999) Grb10, a positive, stimulatory signaling adapter in

54

243.

244.

245. 246.

247.

248.

249.

250.

251. 252. 253. 254.

255. 256.

257.

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

platelet-derived growth factor BB-, insulin-like growth factor I- and insulin-mediated mitogenesis. Mol Cell Biol 19, 6217–6228. Deng, Y., Bhattacharya, S., Swamy, O. R., Tandon, R., Wang, Y., Janda, R. and Riedel, H. (2003) Growth factor receptor-binding protein 10 (Grb10) as a partner of phosphatidylinositol 3-kinase in metabolic insulin action. J Biol Chem 278, 39 311–39 322. Nantel, A., Mohammad-Ali, K., Sherk, J., Bosner, B. I. and Thomas, D. Y. (1998) Interaction of the Grb10 adapter protein with the Raf1 and MEK1 kinases. J Biol Chem 273, 10 475–10 484. Jahn, T., Seipel, P., Urschel, S., Peschel, C. and Duyster, J. (2002) Role for the adaptor protein Grb10 in the activation of Akt. Mol Cell Biol 22, 979–991. Giovannone, B., Lee, E., Laviola, L., Giorgino, F., Cleveland, K. A. and Smith, R. J. (2003) Two novel proteins that are linked to insulin-like growth factor (IGF-I) receptors by the Grb10 adaptor and modulate IGF-I signalling. J Biol Chem 278, 31 564–31 573. Blagitko, N., Mergenthaler, S., Schulz, U., Wollmann, H. A., Craigen, W., Eggermann, T., Ropers, H. H. and Kalscheuer, V. M. (2000) Human GRB10 is imprinted and expressed from the paternal and maternal allele in a highly tissue- and isoform-specific fashion. Hum Mol Genet 9, 1587–1595. Miyoshi, N., Kuroiwa, Y., Kohda, T., Shitara, H., Yonekawa, H., Kawabe, T., Hasegawa, H., Barton, S. C., Surani, M. A., Kaneko-Ishino, T. and Ishino, F. (1998) Identification of the Meg1/Grb10 imprinted gene on mouse proximal chromosome 11, a candidate for the Silver–Russell syndrome gene. Proc Natl Acad Sci USA 95, 1102–1107. Charalambous, M., Smith, F. M., Bennett, W. R., Crew, T. E., Mackenzie, F. and Ward, A. (2003) Disruption of the imprinted Grb10 gene leads to disproportionate overgrowth by an Igf2-independent mechanism. Proc Natl Acad Sci USA 100, 8292–8297. Cooney, G. J., Lyons, R. J., Crew, A. J., Jensen, T. E., Molero, J. C., Mitchell, C. J., Biden, T. J., Ormandy, C. J., James, D. E. and Daly, R. J. (2004) Improved glucose homeostasis and enhanced insulin signalling in Grb14-deficient mice. EMBO J 23, 582–593. Alessi, D. R. and Downes, C. P. (1998) The role of PI 3-kinase in insulin action. Biochim Biophys Acta 1436, 151–164. Shepherd, P. R., Withers, D. J. and Siddle, K. (1998) Phosphoinositide 3-kinase: the key switch mechanism in insulin signalling. Biochem J 333, 471–490. Cantrell, D. A. (2001) Phosphoinositide 3-kinase signalling pathways. J Cell Sci 114, 1439–1445. Katso, R., Okkenhaug, K., Ahmadi, K., White, S., Timms, J. and Waterfield, M. D. (2001) Cellular function of phosphoinositide 3-kinases: implications for development, immunity, homeostasis and cancer. Annu Rev Cell Dev Biol 17, 615–675. Cantley, L. C. (2002) The phosphoinositide 3-kinase pathway. Science 296, 1655–1657. Dhand, R., Hiles, I., Panayotou, G., Roche, S., Fry, M. J., Gout, I., Totty, N. F., Truong, O., Vicendo, P. and Yonezawa, K. (1994) PI 3-kinase is a dual specificity enzyme: autoregulation by an intrinsic protein-serine kinase activity. EMBO J 13, 522–533. Tanti, J. F., Gremeaux, T., Van Obberghen, E. and Le Marchand-Brustel, Y. (1994) Insulin receptor substrate 1 is phosphorylated by the serine kinase activity of phosphatidylinositol 3-kinase. Biochem J 304, 17–21.

REFERENCES

55

258. Lam, K., Carpenter, C. L., Ruderman, N. B., Friel, J. C. and Kelly, K. L. (1994) The phosphatidylinositol 3-kinase serine kinase phosphorylates IRS-1. Stimulation by insulin and inhibition by wortmannin. J Biol Chem 269, 20 648–20 652. 259. Beeton, C. A., Chance, E. M., Foukas, L. C. and Shepherd, P. R. (2000) Comparison of the kinetic properties of the lipid- and protein-kinase activities of the p110alpha and p110beta catalytic subunits of class-Ia phosphoinositide 3-kinases. Biochem J 350, 353–359. 260. Lefai, E., Roques, M., Vega, N., Laville, M. and Vidal, H. (2001) Expression of the splice variants of the p85alpha regulatory subunit of phosphoinositide 3-kinase in muscle and adipose tissue of healthy subjects and type 2 diabetic patients. Biochem J 360, 117–125. 261. Terauchi, Y., Tsuji, Y., Satoh, S., Minoura, H., Murakami, K., Okuno, A., Inukai, K., Asano, T., Kaburagi, Y., Ueki, K., Nakajima, H., Hanafusa, T., Matsuzawa, Y., Sekihara, H., Yin, Y., Barrett, J. C., Oda, H., Ishikawa, H., Akanuma, Y., Komuro, I., Suzuki, M., Yamamura, K., Kodama, T., suzuki, H., Koyasu, S., Aizawa, S., Tobe, K., Fukui, Y., Yazaki, Y. and Kadowaki, T. (1999) Increased insulin sensitivity and hypoglycaemia in mice lacking the p85alpha subunit of phosphoinositide 3-kinase. Nat Genet 21, 230–235. 262. Ueki, K., Yballe, C. M., Brachmann, S. M., Vincent, D., Watt, J. M., Kahn, C. R. and Cantley, L. C. (2001) Increased insulin sensitivity in mice lacking p85beta subunit of phosphoinositide 3-kinase. Proc Natl Acad Sci USA 99, 419–424. 263. Mauvais-Jarvis, F., Ueki, K., Fruman, D. A., Hirshman, M. F., Sakamoto, K., Goodyear, L. J., Iannacone, M., Accili, D., Cantley, L. C. and Kahn, C. R. (2002) Reduced expression of the murine p85alpha subunit of phosphoinositide 3-kinase improves insulin signaling and ameliorates diabetes. J Clin Invest 109, 141–149. 264. Chen, D., Mauvais-Jarvis, F., Bluher, M., Fisher, S. J., Jozsi, A., Goodyear, L. J., Ueki, K. and Kahn, C. R. (2004) p50alpha/p55alpha phosphoinositide 3-kinase knockout mice exhibit enhanced insulin sensitivity. Mol Cell Biol 24, 320–329. 265. Ueki, K., Fruman, D. A., Yballe, C. M., Fassaur, M., Klein, J., Asano, T., Cantley, L. C. and Kahn, C. R. (2003) Positive and negative roles of p85alpha and p85beta regulatory subunits of phosphoinositide 3-kinase in insulin signaling. J Biol Chem 278, 48 453–48 466. 266. Oatey, P. B., Venkateswarlu, K., Williams, A. G., Fletcher, L. M., Foulstone, E. J., Cullen, P. J. and Tavare, J. M. (1999) Confocal imaging of the subcellular distribution of phosphatidylinositol 3,4,5-trisphosphate in insulin- and PDGF-stimulated 3T3-L1 adipocytes. Biochem J 344, 511–518. 267. Heller-Harrison, R. A., Morin, M., Guilherme, A. and Czech, M. P. (1996) Insulinmediated targeting of phosphatidylinositol 3-kinase to GLUT4-containing vesicles. J Biol Chem 271, 10 200–10 204. 268. Leslie, N. R. and Downes, C. P. (2002) PTEN: the down side of PI 3-kinase signalling. Cell Signal 14, 285–295. 269. Ono, H., Katagiri, H., Funaki, M., Anai, M., Inukai, K., Fukushima, Y., Sakoda, H., Ogihara, T., Onishi, Y., Fujishiro, M., Kikuchi, M., Oka, Y. and Asano, T. (2001) Regulation of phosphoinositide metabolism, Akt phosphorylation, and glucose transport by PTEN (phosphatase and tensin homolog deleted on chromosome 10) in 3T3-L1 adipocytes. Mol Endocrinol 15, 1411–1422. 270. Wada, T., Sasaoka, T., Funaki, M., Hori, H., Murakami, S., Ishiki, M., Haruta, T., Asano, T., Ogawa, W., Ishihara, H. and Kobayashi, M. (2001) Overexpression of SH2containing inositol phosphatase 2 results in negative regulation of insulin-induced metabolic actions in 3T3-L1 adipocytes via its 5
-phosphatase catalytic activity. Mol Cell Biol 21, 1633–1646.

56

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

271. Clement, S., Krause, U., Desmedt, F., Tanti, J. F., Behrends, J., Pesesse, X., Sasaki, T., Penninger, J., Doherty, M., Malaisse, W., Dumont, J. E., Le Marchand-Brustel, Y., Erneux, C., Hue, L. and Schurmans, S. (2001) The lipid phosphatase SHIP2 controls insulin sensitivity. Nature 409, 92–97. 272. Kimber, W. A., Deak, M., Prescott, A. R. and Alessi, D. R. (2003) Interaction of the protein tyrosine phosphatase PTPL1 with the PtdIns(3,4)P2-binding adaptor protein TAPP1. Biochem J 376, 525–535. 273. Burgering, B. M. and Coffer, P. J. (1995) Protein kinase B (c-Akt) in phosphatidylinositol-3-OH kinase signal transduction. Nature 376, 599–602. 274. Vanhaesebroeck, B. and Alessi, D. R. (2000) The PI3K–PDK1 connection: more than just a road to PKB. Biochem J 346, 561–576. 275. Brazil, D. P. and Hemmings, B. A. (2001) Ten years of protein kinase B signalling: a hard Akt to follow. Trends Biochem Sci 26, 657–664. 276. Lawlor, M. A. and Alessi, D. R. (2001) PKB/Akt: a key mediator of cell proliferation, survival and insulin responses? J Cell Sci 114, 2903–2910. 277. Vivanco, I. and Sawyers, C. L. (2002) The phosphatidylinositol 3-kinase-Akt pathway in human cancer. Nat Rev Cancer 2, 489–501. 278. Whiteman, E. L., Cho, H. and Birnbaum, M. J. (2002) Role of Akt/protein kinase B in metabolism. Trends Endocrinol Metab 13, 444–451. 279. Scheid, M. P. and Woodgett, J. R. (2003) Unravelling the activation mechanism of protein kinase B/Akt. FEBS Lett 546, 108–112. 280. Alessi, D. R., James, S. R., Downes, C. P., Holmes, A. B., Gaffney, P. R., Reese, C. B. and Cohen, P. (1997) Characterization of a 3-phosphoinositide-dependent protein kinase which phosphorylates and activates protein kinase Balpha. Curr Biol 7, 261–269. 281. Meier, R. and Hemmings, B. A. (1999) Regulation of protein kinase B. J Recep Signal Transduct Res 19, 121–128. 282. Frame, S. and Cohen, P. (2001) GSK3 takes centre stage more than 20 years after its discovery. Biochem J 359, 1–16. 283. Kitamura, T., Kitamura, Y., Kuroda, S., Hino, Y., Ando, M., Kotani, K., Konishi, H., Matsuzaki, H., Kikkawa, U., Ogawa, W. and Kasuga, M. (1999) Insulin-induced phosphorylation and activation of cyclic nucleotide phosphodiesterase 3B by the serine–threonine kinase Akt. Mol Cell Biol 19, 6286–6296. 284. Pozuelo Rubio, M., Peggie, M., Wong, B. H., Morrice, N. and MacKintosh, C. (2003) 14–3–3s regulate fructose-2,6-bisphosphate levels by binding to PKB-phosphorylated cardiac fructose-2,6-bisphosphate kinse/phosphatase. EMBO J 22, 3514–3523. 285. Carlsson, P. and Mahlapuu, M. (2002) Forkhead transcription factors: key players in development and metabolism. Dev Biol 250, 1–23. 286. Burgering, B. M. and Kops, G. J. (2002) Cell cycle and death control: long live forkheads. Trends Biochem. Sci. 27, 352–360. 287. O’Brien, R. M., Streeper, R. S., Ayala, J. E., Stadelmaier, B. T. and Hornbuckle, L. A. (2001) Insulin-regulated gene expression. Biochem Soc Trans 29, 552–558. 288. Puigserver, P., Rhee, J., Donovan, J., Walkey, C. J., Yoon, J. C., Oriente, F., Kitamura, Y., Altomonte, J., Dong, H., Accili, D. and Spiegelman, B. M. (2003) Insulinregulated hepatic gluconeogenesis through FOXO1-PGC-1alpha interaction. Nature 423, 550–555. 289. Ducluzeau, P. H., Fletcher, L. M., Welsh, G. I. and Tavar´e, J. M. (2002) Functional consequence of targeting protein kinase B/Akt to GLUT4 vesicles. J Cell Sci 115, 2857–2866. 290. Calera, M. R., Martinez, C., Liu, H., Jack, A. K., Birnbaum, M. J. and Pilch, P. F. (1998) Insulin increases the association of Akt-2 with Glut4-containing vesicles. J Biol Chem 273, 7201–7204.

REFERENCES

57

291. Kupriyanova, T. A. and Kandror, K. V. (1999) Akt-2 binds to Glut4-containing vesicles and phosphorylates their component proteins in response to insulin. J Biol Chem 274, 1458–1564. 292. Cho, H., Mu, J., Kim, J. K., Thorvaldsen, J. L., Chu, Q., Crenshaw, E. B., Kaestner, K. H., Bartolomel, M. S., Shulman, G. I. and Birnbaum, M. J. (2001) Insulin resistance and a diabetes mellitus-like syndrome in mice lacking the protein kinase Akt2 (PKBbeta). Science 292, 1728–1731. 293. Garofalo, R. S., Orena, S. J., Rafidi, C., Torchia, A. J., Stock, J. L., Hildebrandt, A. L., Coskran, T., Black, S. C., Brees, D. J., Wicks, J. R., McNeish, J. D. and Coleman, K. G. (2003) Severe diabetes, age-dependent loss of adipose tissue, and mild growth deficiency in mice lacking Akt2/PKBbeta. J Clin Invest 112, 197–208. 294. Cho, H., Thorvaldsen, J. L., Chu, Q., Feng, F. and Birnbaum, M. J. (2001) Akt1/PKBalpha is required for normal growth but dispensable for maintenance of glucose homeostasis in mice. J Biol Chem 276, 38 349–38 352. 295. Bae, S. S., Han, C., Mu, J. and Birnbaum, M. J. (2003) Isoform-specific regulation of insulin-dependent glucose uptake by Akt/PKB. J Biol Chem 278, 49 530–49 536. 296. Garofalo, R. S. (2002) Genetic analysis of insulin signaling in Drosophila. Trends Endocrinol Metab 13, 156–162. 297. Nelson, D. W. and Padgett, R. W. (2003) Insulin worms its way into the spotlight. Genes Dev 17, 813–818. 298. Faridi, J., Fawcett, J., Wang, L. and Roth, R. A. (2003) Akt promotes an increase in mammalian cell size by stimulating protein synthesis as well as by inhibiting protein degradation. Am J Physiol Endocrinol Metab 285, E964–E972. 299. Shah, O. J., Anthony, J. C., Kimball, S. R. and Jefferson, L. S. (2000) 4E-BP1 and S6K1: translational integration sites for nutritional and hormonal information in muscle. Am J Physiol Endocrinol Metab 279, E715–E729. 300. Thomas, G. (2002) The S6 kinase signaling pathway in the control of development and growth. Biol Res 35, 305–313. 301. Kleijn, M., Scheper, G. C., Voorma, H. O. and Thomas, A. A. (1998) Regulation of translation initiation factors by signal transduction. Eur J Biochem 253, 531–544. 302. Dufner, A. and Thomas, G. (1999) Ribosomal S6 kinase signaling and the control of translation. Exp Cell Res 253, 100–109. 303. Gingras, A. C., Raught, B., Gygi, S. P. A. N., Miron, M., Burley, S. K., Polakiewicz, R. D., Wyslouch-Cieszynska, A., Aebersold, R. and Sonnenberg, N. (2001) Hierarchical phosphorylation of the translation inhibitor 4E-BP1. Genes Dev 15, 2852–2864. 304. Yonezawa, K., Yoshino, K. I., Tokunaga, C. and Hara, K. (2004) Kinase activities associated with mTOR. Curr Top Microbiol Immunol 279, 271–282. 305. Martin, K. A. and Blenis, J. (2002) Coordinate regulation of translation by the PI 3kinase and mTOR pathways. Adv Cancer Res 86, 1–39. 306. Inoki, K., Li, Y., Xu, T. and Guan, K. L. (2003) Rheb GTPase is a direct target of TSC2 GAP activity and regulates mTOR signaling. Genes Dev 17, 1829–1834. 307. Tee, A. R., Manning, R. D., Roux, P. P., Cantley, L. C. and Blenis, J. (2003) Tuberous sclerosis gene products, tuberin and hamartin, control mTOR signaling by acting as a GTPase-activating protein complex towards Rheb. Curr Biol 13, 1259–1268. 308. Zhang, Y., Gao, X., Saucedo, L. J., Ru, B., Edgar, B. A. and Pan, D. (2003) Rheb is a direct target of the tuberous sclerosis tumour suppressor proteins. Nat Cell Biol 5, 578–581. 309. Garami, A., Zwartkruis, F. J. T., Nobukuni, T., Joaquin, M., Roccio, M., Stocker, H., Kozma, S. C., Hafen, E., Bos, J. L. and Thomas, G. (2003) Insulin activation of Rheb, a mediator of mTOR/S6K/4E-BP signaling, is inhibited by TSC1 and 2. Mol Cell 11, 1457–1466.

58

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

310. Nav´e, B. T., Ouwens, M., Withers, D. J., Alessi, D. R. and Shepherd, P. R. (1999) Mammalian target of rapamycin is a direct target for protein kinase B: identification of a convergence point for opposing effects of insulin and amino-acid deficiency on protein translation. Biochem J 344, 427–431. 311. Tzivion, G. and Avruch, J. (2002) 14–3–3 proteins: active cofactors in cellular regulation by serine/threonine phosphorylation. J Biol Chem 277, 3061–3064. 312. Shumway, S. D., Li, Y. and Xiong, Y. (2003) 14–3–3beta binds to and negatively regulates the tuberous sclerosis complex 2 (TSC2) tumor suppressor gene product, tuberin. J Biol Chem 278, 2089–2092. 313. Zhao, X., Gan, L., Pan, H., Kan, D., Majeski, M., Adam, S. A. and Unterman, T. G. (2004) Multiple elements regulate nuclear/cytoplasmic shuttling of FOXO1: characterization of phosphorylation- and 14–3–3-dependent and -independent mechanisms. Biochem J (in press). 314. Brazil, D. P., Park, J. and Hemmings, B. A. (2002) PKB binding proteins: getting in on the Akt. Cell 111, 293–303. 315. Du, K., Herzig, S., Kulkarni, R. N. and Montminy, M. (2004) TRB3: a tribbles homolog that inhibits Akt/PKB activation by insulin in liver. Science 300, 1574–1577. 316. Kim, Y. B., Nikoulina, S. E., Ciaraldi, T. P., Henmry, R. R. and Kahn, B. B. (1999) Normal insulin-dependent activation of Akt/protein kinase B, with diminished activation of phosphoinositide 3-kinase, in muscle in type 2 diabetes. J Clin Invest 104, 733–741. 317. Krook, A., Bjornholm, M., Galuska, D., Jiang, X. J., Fahlman, R., Myers, M. G., Wallberg-Henriksson, H. and Zierath, J. R. (2000) Characterization of signal transduction and glucose transport in skeletal muscle from type 2 diabetic patients. Diabetes 49, 284–292. 318. Carvalho, E., Eliasson, B., Wesslau, C. and Smith, U. (2000) Impaired phosphorylation and insulin-stimulated translocation to the plasma membrane of protein kinase B/Akt in adipocytes from Type II diabetic subjects. Diabetologia 43, 1107–1115. 319. Tsuchida, H., Bjornholm, M., Fernstrom, M., Galuska, D., Johansson, P., WallbergHenriksson, H., Zierath, J. R., Lake, S. and Krook, A. (2002) Gene expression of the p85alpha regulatory subunit of phosphatidylinositol 3-kinase in skeletal muscle from type 2 diabetic subjects. Pflugers Arch 445, 25–31. 320. Smith, U. (2002) Impaired (‘diabetic’) insulin signaling and action occur in fat cells long before glucose intolerance – is insulin resistance initiated in the adipose tissue? Int J Obes Relat Metab Disord 26, 897–904. 321. Kim, Y. B., Kotani, K., Ciaraldi, T. P., Henry, R. R. and Kahn, B. B. (2003) Insulinstimulated protein kinase C lambda/zeta activity is reduced in skeletal muscle of humans with obesity and type 2 diabetes: reversal with weight reduction. Diabetes 52, 1935–1942. 322. Farese, R. V. (2002) Function and dysfunction of aPKC isoforms for glucose transport in insulin-sensitive and insulin-resistant states. Am J Physiol Endocrinol Metab 283, E1–E11. 323. Cong, L. N., Chen, H., Li, Y., Zhou, L., McGibbon, M. A., Taylor, S. I. and Quon, M. J. (1997) Physiological role of Akt in insulin-stimulated translocation of GLUT4 in transfected rat adipose cells. Mol Endocrinol 11, 1881–1890. 324. Kohn, A. D., Barthel, A., Kovacina, K. S., Boge, A., Wallach, B., Summers, S. A., Birnbaum, M. J., Scott, P. H., Lawrence, J. C. and Roth, R. A. (1998) Construction and characterization of a conditionally active version of the serine/threonine kinase Akt. J Biol Chem 273, 11 937–11 943. 325. Kotani, K., Ogawa, W., Matsumoto, M., Kitamura, T., Sakaue, H., Hino, Y., Miyake, K., Sano, W., Akimoto, K., Ohno, S. and Kasuga, M. (1998) Requirement of atypical

REFERENCES

326.

327.

328.

329.

330. 331.

332.

333.

334. 335. 336. 337. 338.

339. 340.

341. 342.

59

protein kinase Clambda for insulin stimulation of glucose uptake but not for Akt activation in 3T3-L1 adipocytes. Mol Cell Biol 18, 6971–6982. Kitamura, T., Ogawa, W., Sakaue, H., Hino, Y., Kuroda, S., Takata, M., Matsumoto, M., Maeda, T., Konishi, H., Kikkawa, U. and Kasuga, M. (1998) Requirement for activation of the serine–threonine kinase Akt (protein kinase B) in insulin stimulation of protein synthesis, but not of glucose transport. Mol Cell Biol 18, 3708–3717. Bandyopadhyay, G., Standaert, M. L., Sajan, M. P., Karnitz, L. M., Cong, L., Quon, M. J. and Farese, R. V. (1999) Dependence of insulin-stimulated glucose transporter 4 translocation on 3-phosphoinositide-dependent protein kinase-1 and its target threonine410 in the activation loop of protein kinase C-zeta. Mol Endocrinol 13, 1766–1772. Imamura, T., Huang, J., Usui, I., Satoh, H., Bever, J. and Olefsky, J. M. (2003) Insulininduced GLUT4 translocation involves protein kinase C-lambda-mediated functional coupling between Rab4 and the motor protein kinesin. Mol Cell Biol 23, 4892–4900. Matsumoto, M., Ogawa, W., Akimoto, K., Inoue, H., Miyake, K., Furukawa, K., Hayashi, Y., Iguchi, H., Matsuki, Y., Hiramatsu, R., Shimano, H., Yamada, N., Ohno, S., Kasuga, M. and Noda, T. (2003) PKClambda in liver mediates insulininduced SREBP-1c expression and determines both hepatic lipid content and overall insulin sensitivity. J Clin Invest 112, 935–944. Baumann, C. A. and Saltiel, A. R. (2001) Spatial compartmentalization of signal transduction in insulin action. Bioessays 23, 215–222. Chunqiu Hou, J. and Pessin, J. E. (2003) Lipid raft targeting of the TC10 amino terminal domain is responsible for disruption of adipocyte cortical actin. Mol Biol Cell 14, 3578–3591. Maffucci, T., Brancaccio, A., Piccolo, E., Stein, R. C. and Falasca, M. (2003) Insulin induces phosphatidylinositol-3-phosphate formation through TC10 activation. EMBO J 22, 4178–4189. Inoue, M., Chang, L., Hwang, J., Chiang, S. H. and Saltiel, A. R. (2003) The exocyst complex is required for targeting of Glut4 to the plasma membrane by insulin. Nature 422, 629–635. Cohen, A. W., Combs, T. P., Scherer, P. E. and Lisanti, M. P. (2003) Role of caveolin and caveolae in insulin signaling. Am J Physiol Endocrinol Metab 285, E1151–E1160. Kanzaki, M. and Pessin, J. E. (2003) Insulin signaling: GLUT4 vesicles exit via the exocyst. Curr Biol 13, R574–R576. Feller, S. M. (2001) Crk family adaptors – signalling complex formation and biological roles. Oncogene 20, 6348–6371. Schaeffer, H. J. and Weber, M. J. (1999) Mitogen-activated protein kinases: specific messages from ubiquitous messengers. Mol Cell Biol 19, 2435–2444. Avruch, J., Khokhlatchev, A., Kyriakis, J. M., Luo, Z., Tzivion, G., Vavvas, D. and Zhang, X. F. (2001) Ras activation of the Raf kinase: tyrosine kinase recruitment of the MAP kinase cascade. Rec Prog Horm Res 56, 127–155. Johnson, G. L. and Lapadat, R. (2002) Mitogen-activated protein kinase pathways mediated by ERK, JNK, and p38 protein kinases. Science 298, 1911–1912. Kyriakis, J. M. and Avruch, J. (2001) The mammalian mitogen-activated protein kinase signal transduction pathways activated by stress and inflammation. Physiol Rev 81, 807–869. Denton, R. M. and Tavar´e, J. M. (1995) Does mitogen-activated-protein kinase have a role in insulin action? The cases for and against. Eur J Biochem 227, 597–611. Lazar, D. F., Wiese, R. J., Brady, M. J., Mastick, C. C., Waters, S. B., Yamauchi, K., Pessin, J. E., Cuatrecasas, P. and Saltiel, A. R. (1995) Mitogen-activated protein kinase kinase inhibition does not block the stimulation of glucose utilization by insulin. J Biol Chem 270, 20 801–20 807.

60

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

343. Azpiazu, I., Saltiel, A. R., DePaoli-Roach, A. A. and Lawrence, J. C. (1996) Regulation of both glycogen synthase and PHAS-I by insulin in rat skeletal muscle involves mitogen-activated protein kinase-independent and rapamycin-sensitive pathways. J Biol Chem 271, 5033–5039. 344. O’Brien, R. M. and Granner, D. K. (1996) Regulation of gene expression by insulin. Physiol Rev 76, 1109–1161. 345. Frodin, M. and Gammeltoft, S. (1999) Role and regulation of 90 kDa ribosomal S6 kinase (RSK) in signal transduction. Mol Cell Endocrinol 151, 65–77. 346. Whitmarsh, A. J. and Davis, R. J. (1996) Transcription factor AP-1 regulation by mitogen-activated protein kinase signal transduction pathways. J Mol Med 74, 589–607. 347. Hurd, T. W., Culbert, A. A., Webster, K. J. and Tavare, J. M. (2002) Dual role for mitogen-activated protein kinase (Erk) in insulin-dependent regulation of Fra-1 (fosrelated antigen-1) transcription and phosphorylation. Biochem J 368, 573–580. 348. Shaw, P. E. and Saxton, J. (2003) Ternary complex factors: prime nuclear targets for mitogen-activated protein kinases. Int J Biochem Cell Biol 35, 1210–1226. 349. Kolch, W. (2000) Meaningful relationships: the regulation of the Ras/Raf/MEK/ERK pathway by protein interactions. Biochem J 351, 289–305. 350. Garrington, T. P. and Johnson, G. L. (1999) Organization and regulation of mitogenactivated protein kinase signaling pathways. Curr Opin Cell Biol 11, 211–218. 351. Morrison, D. K. (2001) KSR: a MAPK scaffold of the Ras pathway? J Cell Sci 114, 1609–1612. 352. Langlois, W. J., Sasaoka, T., Saltiel, A. R. and Olefsky, J. M. (1995) Negative feedback regulation and desensitization of insulin- and epidermal growth factorstimulated p21ras activation. J Biol Chem 270, 25 320–25 323. 353. Dong, C., Waters, S. B., Holt, K. H. and Pessin, J. E. (1996) SOS phosphorylation and disassociation of the Grb2–SOS complex by the ERK and JNK signaling pathways. J Biol Chem 271, 6328–6332. 354. Zhao, H., Okada, S., Pessin, J. E. and Koretzky, G. A. (1998) Insulin receptormediated dissociation of Grb2 from Sos involves phosphorylation of Sos by kinase(s) other than extracellular signal-regulated kinase. J Biol Chem 273, 12 061–12 067. 355. Dhillon, A. S., Pollock, C., Steen, H., Shaw, P. E., Mischak, H. and Kolch, W. (2002) Cyclic AMP-dependent kinase regulates Raf-1 kinase mainly by phosphorylation of serine 259. Mol Cell Biol 22, 3237–3246. 356. Galetic, I., Maira, S. M., Andjelkovic, M. and Hemmings, B. A. (2003) Negative regulation of ERK and Elk by protein kinase B modulates c-Fos transcription. J Biol Chem 278, 4416–4423. 357. Gual, P., Baron, V., Lequoy, V. and Van Obberghen, E. (1998) The interaction of Janus kinases JAK-1 and JAK-2 with the insulin receptor and insulin-like growth factor-1 receptor. Endocrinology 139, 884–893. 358. Sawka-Verhelle, D., Tartare-Deckert, S., Decaux, J. F., Girard, J. and Van Obberghen, E. (2000) Stat 5B, activated by insulin in a Jak-independent fashion, plays a role in glucokinase gene transcription. Endocrinology 141, 1977–1988. 359. Le, M. N., Kohanski, R. A., Wang, L. H. and Sadowski, H. B. (2002) Dual mechanism of signal transducer and activator of transcription 5 activation by the insulin receptor. Mol Endocrinol 16, 2764–2779. 360. Kimura, A., Mora, S., Shigematsu, S., Pessin, J. E. and Saltiel, A. R. (2002) The insulin receptor catalyzes the tyrosine phosphorylation of caveolin-1. J Biol Chem 277, 30 153–30 158. 361. Najjar, S. (2002) Regulation of insulin action by CEACAM1. Trends Endocrinol Metab 13, 240–245.

REFERENCES

61

362. Myers, M. G., Mendez, R., Shi, P., Pierce, J. H., Rhoads, R. and White, M. F. (1998) The COOH-terminal tyrosine phosphorylation sites on IRS-1 bind SHP-2 and negatively regulate insulin signaling. J Biol Chem 273, 26 908–26 914. 363. Ogawa, W., Matozaki, T. and Kasuga, M. (1998) Role of binding proteins to IRS-1 in insulin signalling. Mol Cell Biochem 182, 13–22. 364. Fukunaga, K., Noguchi, T., Takeda, H., Matozaki, T., Hayashi, Y., Itoh, H. and Kasuga, M. (2000) Requirement for protein tyrosine phosphatase SHP-2 in insulininduced activation of c-Jun NH(2)-terminal kinase. J Biol Chem 275, 5208–5213. 365. Maegawa, H., Hasegawa, M., Sugai, S., Obata, T., Ugi, S., Morino, K., Egawa, K., Fujita, T., Sakamoto, T., Nishio, Y., Kojima, H., Haneda, M., Yasuda, H., Kikkawa, R. and Kashiwagi, A. (1999) Expression of a dominant negative SHP-2 in transgenic mice induces insulin resistance. J Biol Chem 274, 30 236–30 243. 366. Neel, B. G., Gu, H. and Pao, L. (2003) The ‘Shp’ing news: SH2 domain-containing tyrosine phosphatases in cell signaling. Trends Biochem Sci 28, 284–293. 367. Kayali, A. G., Eichhorn, J., Haruta, T., Morris, A. J., Nelson, J. G., Vollenweider, P., Olefsky, J. M. and Webster, N. J. G. (1998) Association of the insulin receptor with phospholipase Cγ (PLCγ) in 3T3-L1 adipocytes suggests a role for PLCγ in metabolic signaling by insulin. J Biol Chem 273, 13 808–13 818. 368. Eichhorn, J., Kayali, A. G., Austin, D. A. and Webster, N. J. (2001) Insulin activates phospholipase C-gamma 1 via a PI 3-kinase dependent mechanism in 3T3-L1 adipocytes. Biochem Biophys Res Commun 282, 615–620. 369. Lorenzo, M., Teruel, T., Hernandez, R., Kayali, A. G. and Webster, N. J. (2002) PLCgamma participates in insulin stimulation of glucose uptake through activation of PKCzeta in brown adipocytes. Exp Cell Res 278, 146–157. 370. Lemmon, M. A. and Ferguson, K. M. (2000) Signal-dependent membrane targeting by pleckstrin homology (PH) domains. Biochem J 350, 1–18. 371. Chan, T. O., Rittenhouse, S. E. and Tsichlis, P. N. (1999) AKT/PKB and other D3 phosphoinositide-regulated kinases: kinase activation by phosphoinositide-dependent phosphorylation. Annu Rev Biochem 68, 965–1014. 372. Li, H. S., Shome, K., Rojas, R., Rizzo, M. A., Vasudevan, C., Fluharty, F., Santy, L. C., Casanova, J. E. and Romero, G. (2003) The guanine nucleotide exchange factor ARNO mediates the activation of ARF and phospholipase D by insulin. BMC Cell Biol 4, 13. 373. Jackson, T. R., Kearns, B. G. and Theibert, A. B. (2000) Cytohesins and centaurins: mediators of PI 3-kinase-regulated Arf signaling. Trends Biochem Sci 25, 489–495. 374. Krugmann, S., Anderson, K. E., Ridley, S. H., Risso, N., McGregor, A., Coadwell, J., Davidson, K., Eguinoa, A., Ellson, C. D., Lipp, P., Manifava, M., Ktistakis, N., Painter, G., Thuring, J. W., Cooper, M. A., Lim, Z. Y., Holmes, A. B., Dove, S. K., Michell, R. H., Grewal, A., Nazarian, A., Erdjument-Bromage, H., Tempst, P., Stephens, L. R. and Hawkins, P. T. (2002) Identification of ARAP3, a novel PI3K effector regulating both Arf and Rho GTPases, by selective capture on phosphoinositide affinity matrices. Mol Cell 9, 95–108. 375. Dowler, S., Currie, R. A., Downes, C. P. and Alessi, D. (1999) DAPP1: a dual adaptor for phosphotyrosine and 3-phosphoinositides. Biochem J 342, 7–12. 376. Anderson, K. E., Lipp, P., Bootman, M., Ridley, S. H., Coadwell, J., R¨onnstrand, L., Lennartsson, J., Holmes, A. B., Painter, G. F., Thuring, J., Lim, Z. Y., ErdjumentBromage, H., Grewal, A., Tempst, P., Stephens, L. R. and Hawkins, P. T. (2000) DAPP1 undergoes a PI 3-kinase-dependent cycle of plasma-membrane recruitment and endocytosis upon cell stimulation. Curr Biol 10, 1403–1412. 377. Welch, H. C., Coadwell, W. J., Stephens, L. R. and Hawkins, P. T. (2003) Phosphoinositide 3-kinase-dependent activation of Rac. FEBS Lett 546, 93–97.

62

THE INSULIN RECEPTOR AND DOWNSTREAM SIGNALLING

378. Etienne-Manneville, S. and Hall, A. (2002) Rho GTPases in cell biology. Nature 420, 629–635. 379. Houslay, M. D. and Siddle, K. (1989) Molecular basis of insulin receptor function. Br Med Bull 45, 264–284. 380. Dalle, S., Ricketts, W., Imamura, T., Vollenweider, P. and Olefsky, J. M. (2001) Insulin and IGF-I receptors utilize different G-protein signaling components. J Biol Chem 276, 15 688–15 695. 381. Imamura, T., Vollenweider, P., Egawa, K., Clodi, M., Ishibashi, K., Nakashima, N., Ugi, S., Adams, J. W., Brown, J. H. and Olefsky, J. M. (1999) G alpha-q/11 protein plays a key role in insulin-induced glucose transport in 3T3-L1 adipocytes. Mol Cell Biol 19, 6765–6774. 382. Usui, I., Imamura, T., Huang, J., Satoh, H. and Olefsky, J. M. (2003) Cdc42 is a Rho GTPase family member that can mediate insulin signaling to glucose transport in 3T3L1 adipocytes. J Biol Chem 278, 13 765–13 774. 383. Sleight, S., Wilson, B. A., Heimark, D. B. and Larner, J. (2002) G(q/11) is involved in insulin-stimulated inositol phosphoglycan putative mediator generation in rat liver membranes: co-localization of G(q/11) with the insulin receptor in membrane vesicles. Biochem Biophys, Res Commun 295, 561–569. 384. Romero, G. and Larner, J. (1993) Insulin mediators and the mechanism of insulin action. Adv Pharmacol 24, 21–50. 385. Saltiel, A. R. (1996) Structural and functional roles of glycosylphosphoinositides. Subcell Biochem 26, 165–185. 386. Muller, G., Jung, C., Frick, W., Bandlow, W. and Kramer, W. (2002) Interaction of phosphatidylinositolglycan(-peptides) with plasma membrane lipid rafts triggers insulinmimetic signaling in rat adipocytes. Arch Biochem Biophys 408, 7–16. 387. Muller, G. and Frick, W. (1999) Signalling via caveolin: involvement in the cross-talk between phosphoinositolglycans and insulin. Cell Mol Life Sci 56, 945–970. 388. Dumont, J. E., P´ecasse, F. and Maenhaut, C. (2001) Cross-talk and specificity in signalling: are we cross-talking ourselves into general confusion? Cell Signal 13, 457–463. 389. Dumont, J. E., Dremier, S., Pirson, I. and Maenhaut, C. (2002) Cross-signalling, cell specificity, and physiology. Am J Physiol Cell Physiol 283, C2–C28. 390. Pawson, T. and Nash, P. (2000) Protein–protein interactions define specificity in signal transduction. Genes Dev 14, 1027–1047. 391. Whiteman, E. L., Chen, J. J. and Birnbaum, M. J. (2003) Platelet-derived growth factor (PDGF) stimulates glucose transport in 3T3-L1 adipocytes overexpressing PDGF receptor by a pathway independent of insulin receptor substrates. Endocrinology 144, 3811–3820. 392. Tengholm, A. and Meyer, T. (2002) A PI3-kinase signaling code for insulin-triggered insertion of glucose transporters into the plasma membrane. Curr Biol 12, 1871–1876. 393. Khan, A. H. and Pessin, J. E. (2002) Insulin regulation of glucose uptake: a complex interplay of intracellular signaling pathways. Diabetologia 45, 1475–1485. 394. Kim, J. J. and Accili, D. (2002) Signalling through IGF-I and insulin receptors: where is the specificity? Growth Horm IGF Res 12, 84–90. 395. Dupont, J., Khan, J., Qu, B. H., Metzler, P., Helman, L. and LeRoith, D. (2001) Insulin and IGF-1 induce different patterns of gene expression in mouse fibroblast NIH-3T3 cells: identification by cDNA microarray analysis. Endocrinology 142, 4969–4975. 396. Mulligan, C., Rochford, J., Denyer, G., Stephens, R., Yeo, G., Freeman, T., Siddle, K. and O’Rahilly, S. (2002) Microarray analysis of insulin and IGF-1 receptor signalling reveals the selective up-regulation of the mitogen HB-EGF by IGF-1. J Biol Chem 277, 42 480–42 487.

2 Insulin-mediated Regulation of Glucose Metabolism Daniel Konrad, Assaf Rudich and Amira Klip

2.1 Introduction Insulin was identified in the early 1920s as the major hypoglycaemic hormone, capable of restoring normal blood glucose levels in pancreatectomized animals and insulin-deficient humans. This physiological action of insulin is brought about by its effects on glucose metabolism in its ‘classical’ target organs, namely liver, skeletal muscle and adipose tissue. Decades of intense scientific effort involving complementary disciplines have unravelled cellular mechanisms whereby insulin regulates glucose metabolism in these tissues, resulting in the control of blood glucose in diverse physiological states. In this chapter we first outline the actions of insulin as the master switch for whole body glucose distribution and summarize its effects on the main biochemical pathways of glucose metabolism. We then focus on the effect of insulin on glucose disposal in muscle and fat. As glucose uptake is rate limiting for glucose metabolism in these tissues, we describe in more detail the complex mechanisms through which insulin regulates this process.

2.2

Insulin as a master regulator of whole body glucose disposal

Direct and indirect regulation of glucose metabolism by insulin in its classical target tissues Insulin is more than an endocrine messenger for the transition from fasted- to fed-state metabolism; it is in fact a required regulator in all physiological states. Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

64

INSULIN-MEDIATED REGULATION OF GLUCOSE METABOLISM

During fasting, circulating insulin levels are 5–20 per cent of those measured after a meal. These low circulating concentrations of the hormone are required to maintain the balance with counter-regulatory hormones to prevent ketoacidosis. The brain and cells such as erythrocytes that rely solely on glucose as their energy source consume glucose evenly in the fed and overnight fasted states.1 Therefore, maintaining normoglycaemia despite fluctuations in the availability of exogenous glucose relies on a coordinated regulation of glucose disposal and endogenous glucose production. During fasting, the liver, and to a lesser degree the kidney, release glucose to the blood, matching its utilization by glucosedependent tissues such as the brain. Under these conditions, glucose disposal into skeletal muscle and adipocytes is low, where lipids are consumed as the major fuel. Upon a meal, when circulating glucose and insulin levels rise, glucose is disposed of from the blood into muscle, fat and liver.1 These tissues therefore constitute the ‘classical target organs’ for insulin action through which the hypoglycaemic response of the hormone is directly achieved (Table 2.1). In addition to increasing glucose uptake into skeletal muscle and adipose tissue, insulin promotes glucose storage as either glycogen (mainly in muscle and liver) or lipids (mainly in fat and liver). To avoid futile metabolic cycles, insulin simultaneously inhibits the breakdown of these macromolecules through glycogenolysis and lipolysis, respectively. Similarly, in the liver and kidney endogenous glucose production is curbed by insulin through the inhibition of glycogenolysis and gluconeogenesis.3, 4 Research of recent years utilizing tissue-specific gene deletions of the insulin receptor in animal models largely confirmed the direct effects of insulin on glucose metabolism in its classical target organs. Mice lacking the insulin receptor in the liver (liver insulin receptor knock-out (LIRKO) mice) fail to suppress endogenous glucose production during hyperinsulinaemic clamps.5 Likewise, ablation of the insulin receptor gene in skeletal muscle (MIRKO mice) blunts insulin-stimulated glucose transport and glycogen synthesis in this tissue.6 Remarkably, glucose uptake into adipose tissue is elevated in MIRKO mice, suggesting that insulin’s direct effects on its classical target tissues are coordinated, allowing for complex adaptive responses and balances in the regulation of whole body glucose metabolism, as discussed further below. Hence, insulin can be viewed as a glucose flux regulator, promoting peripheral glucose uptake and hepatic glucose storage during a meal, and allowing hepatic glucose output while preventing ketoacidosis between meals. On top of the major direct effects of insulin on glucose fluxes in its classical target organs (Table 2.1), the hormone also engages indirect mechanisms in the regulation of glucose metabolism. These include insulin-mediated alterations in lipid and protein metabolism (described in detail in Chapters 3 and 4 of this book) that in turn impact on glucose metabolism, coordination of glucose fluxes between its various target tissues, and regulation of circulating factors involved in cross-talk between skeletal muscle, adipose tissue and liver.

INSULIN AS A MASTER REGULATOR OF WHOLE BODY GLUCOSE DISPOSAL

65

Table 2.1 ‘Classical’ and ‘non-classical’ target organs for insulin-regulated glucose metabolism Main effect of insulin on glucose metabolism Organ/tissue ‘Classical targets’ Skeletal and cardiac muscle Liver

Adipose tissue

Direct ↑ ↑ ↑ ↓ ↑ ↑ ↑ ↑ ↑ ↑ ↑

‘Non-classical targets’ Pancreatic beta cells ?

Brain/CNS Vascular cells

? ?

glucose uptake glucose oxidation glycogen synthesis glucose output – • ↓ glycogenolysis • ↓ gluconeogenesis glycogen synthesis glycolysis lipogenesis hexose monophosphate shunt∗ glucose uptake hexose monophosphate shunt∗ lipogenesis

Indirect ↓ NEFA availability and oxidation ↓ NEFA availability and oxidation

Regulation of adipokines synthesis and/or secretion ↓ lipolysis Permissive effect on glucose-stimulated insulin secretion (phase 1 release) ↓ Food intake ↑ blood flow (vasodilatation) ↑ capillary recruitment ↑ NO secretion

A ‘direct effect’ of insulin on glucose metabolism is defined as an insulin-stimulated change in the flux of glucose through a specific metabolic pathway that is initiated by the insulin receptor in the same tissue. An ‘indirect effect’ is the regulation of glucose metabolism in one organ resulting from the effect of insulin on other macronutrients (such as lipids) or in other organs. ∗ Insulin-stimulated lipogenesis consumes NADPH, and the resulting drop in NADPH/NADP+ increases the activity of G6PD, i.e. G6P flux through the shunt. In addition, insulin regulates the mRNA levels of G6PD – the rate-limiting enzyme in this pathway.2

Insulin is a key regulator of the interplay between glucose and fatty acids metabolism, as follows. Insulin-mediated inhibition of lipolysis, i.e. the release of non-esterified fatty acids (NEFAs) from adipose tissue, contributes to the acute inhibition of hepatic glucose production induced by the hormone.7, 8 This is brought about by lowering NEFA oxidation, since in this process high intracellular ATP/ADP, NADH/NAD+ and acetyl-CoA/CoA ratios are achieved, providing the metabolite milieu required for gluconeogenesis. In addition, NEFA availability to skeletal muscle also influences insulin-regulated glucose utilization by this tissue. The original hypothesis of Randle9 suggested that increased NEFA availability as a fuel source to the muscle (as occurs physiologically during fasting) blocks glycolysis through the elevated generation of acetyl-CoA and

66

INSULIN-MEDIATED REGULATION OF GLUCOSE METABOLISM

citrate, resulting in allosteric inhibition of pyruvate dehydrogenase and phosphofructokinase-1, respectively. The ensuing accumulation of glucose-6-phosphate (G6P) would then secondarily diminish glucose uptake. However, while a glucose–NEFA cycle probably exists, recent studies using nuclear magnetic resonance (NMR) spectroscopy demonstrate that, in skeletal muscle, increased NEFA availability reduces, rather than elevates, intracellular G6P and free glucose levels.10, 11 These findings suggest that insulin-stimulated glucose uptake is itself a primary site of inhibition by NEFA in skeletal muscle. Further examples of the indirect actions of insulin emerge from knockout animal models. In particular, tissue-specific gene deletions have allowed investigators to manipulate glucose flux in a single tissue and then assess the ensuing changes in the non-targeted organs. As mentioned above, MIRKO mice exhibited decreased insulin-stimulated glucose flux into the skeletal muscle, accompanied by an increased glucose flux in adipose tissue.6 Similarly, mice lacking the insulin-responsive glucose transporter GLUT4 selectively in the adipose tissue show not only reduced glucose uptake in fat cells but also blunted insulin regulation of glucose metabolism in muscle and liver.12 Such dependency of glucose metabolism among the different organs suggests the existence of mechanisms that mediate inter-organ cross-talk. An exciting development in this regard has been the identification of adipose-derived factors (adipokines) that modulate glucose metabolism and insulin responsiveness in muscle and the liver.13, 14 While factors such as tumour necrosis factor α and interleukin 6 are not uniquely expressed in adipocytes, adiponectin and leptin are largely considered as adipose-specific gene products. Adiponectin (ACRP30) increases whole body insulin sensitivity largely by suppressing glucose production in the liver, as well as by increasing glucose uptake into skeletal muscle.15, 16 Leptin, the product of the obesity (ob) gene, signals through receptors in the hypothalamus to decrease food intake and increase energy expenditure,17 and may also act peripherally to regulate whole body insulin sensitivity.18 Insulin positively regulates both the gene expression and the secretion of leptin from adipose tissue,19, 20 and may also regulate the gene expression of adiponectin.21, 22 Affecting the circulating concentrations of these regulatory factors provides a newly recognized potent indirect mechanism through which insulin regulates glucose metabolism in its classical target organs.

Non-classical targets of insulin in the regulation of total body glucose metabolism Although the major effect of insulin in controlling glucose metabolism is on its classical target organs (muscle, liver and fat), virtually every cell type expresses the insulin receptors. This raises the possibility that additional sites exist for insulin action on carbohydrate metabolism. Tissue-specific ablation of the insulin receptor has provided new insights about ‘non-classical’ target tissues for insulin action (Table 2.1). Target tissues include pancreatic β-cells, the central nervous

INSULIN-MEDIATED REGULATION OF GLUCOSE METABOLIC PATHWAYS

67

system and vascular cells. The findings suggest that these tissues may exert important effects on glucose metabolism at the whole body level. For example, mice lacking insulin receptors in β-cells manifest impaired glucose-mediated insulin secretion. Conversely, mice in which the insulin receptor was ablated in neuronal cells exhibit elevated food intake and diet-induced obesity, suggesting that insulin delivers an anorexogenic input to the central nervous system.23 Such a role of insulin in the brain was suggested in early studies where the hormone was administered intra-cerebroventricularly to monkeys.24 Finally, vascular cells are a target for insulin-induced vasodilatation and capillary recruitment that, by enhancing glucose delivery, may complement the hormone’s direct stimulatory effect on glucose uptake in muscle.25 Given that quantitatively β-cells, neuronal and vascular cells have only a minor contribution to insulin-stimulated whole body glucose disposal, these studies suggest that the actions of insulin in ‘nonclassical insulin targets’ are indirectly involved in the regulation of total body glucose metabolism. It will be interesting to see whether in addition insulin regulates glucose metabolism in these sites. In summary, insulin engages both ‘classical’ and ‘non-classical’ target organs in orchestrating the control of glucose metabolism (Table 2.1). In its classical target organs insulin directly modulates glucose uptake, metabolism and production. In addition, the hormone affects glucose metabolism secondarily to alterations in the metabolism of other macronutrients, and by utilizing complex inter-organ cross-talk mechanisms.

2.3

Insulin-mediated regulation of glucose metabolic pathways

Entry of the hydrophilic glucose molecule into the cell through a lipid membrane requires a ‘gateway’ offered by glucose transporters (discussed later in this chapter). Once in the cytosol, glucose is phosphorylated into glucose-6phosphate, and from this initial step its biochemical fate is diverse. Glucose-6phosphate is catabolized through glycolysis, the hexose monophosphate shunt and mitochondrial oxidation, yielding high-energy compounds such as ATP and NAD(P)H. Alternatively, glucose can be stored in polymer form (glycogen) or converted to triglycerides. In addition, glucose can be metabolized through several quantitatively minor pathways: it is a precursor for de novo synthesis of nucleotides and certain amino acids, it can be converted to other sugars and alcohols (e.g. sorbitol) and it is required for the generation of complex compounds such as glycoproteins and glycolipids. At the cellular level, insulin regulates the flow of glucose through these biochemical pathways by two basic mechanisms: (a) by increasing uptake from the blood, as described in Section 2.4; (b) by affecting regulatory enzymes in the various pathways of glucose metabolism, as outlined next.

68

INSULIN-MEDIATED REGULATION OF GLUCOSE METABOLISM

Table 2.2 Major target proteins of insulin in the regulation of glucose metabolism, and the main mechanism(s) of regulation Biochemical process

Protein

Stimulatory effect by insulin Glucose uptake GLUT4

Glucose Glucokinase phosphorylation Hexokinase II Glycolysis Phospho-fructokinase 2

Major mechanism of regulation by insulin Translocation from intracellular pools to the plasma membrane Increased activity Expressional regulation? Transcriptional activation

Transcriptional activation Reversible phosphorylation? Allosteric activation Phosphofructokinase 1 Allosteric activation Phosphorylation and actin binding Pyruvate kinase Transcriptional/post-transcriptional activation Dephosphorylation Glycogenesis Glycogen synthase Dephosphorylation: inhibited GS kinase (GSK3) stimulated dephosphorylation (PP1) Glucose oxidation Pyruvate dehydrogenase Dephosphorylation by inhibition of PDK-4/2 expression Allosteric activation Lipogenesis Acetyl CoA carboxylase Transcriptional activation Allosteric activation Reversible phosphorylation? Inhibitory effect by insulin Glycogenolysis Glycogen phosphorylase Dephosphorylation GP-kinase Dephosphorylation Gluconeogenesis G6Pase Transcriptional repression Acute inhibition by 3-PIPs? PEPCK Transcriptional repression Pyruvate carboxylase Transcriptional repression

Reference 26 27 28 29 30 31

32 33

34 35 36 37

38, 39 40

41

GLUT4 – glucose transporter 4, GP-kinase – glycogen phosphorylase kinase, G6Pase – glucose-6phosphatase, GSK3 – glycogen synthase kinase 3, PDK – pyruvate dehydrogenase (PDH) kinase, PEPCK – phosphoenolpyruvate carboxykinase, 3-PIPs – 3
-phosphoinositide phosphates, PP1 – protein phosphatase 1. ? – ambiguity exists regarding the precise effect of insulin or its physiological relevance.

Enzyme regulation is achieved by changes in the phosphorylation state and/or in expression levels. The result is a change in Km and/or Vmax in the first case, or only Vmax in the second. In addition, the rise in glucose flux alters the intracellular concentration of metabolites that in turn act as allosteric modulators, and may regulate the expression levels of specific enzymes. Frequently, these

GLUCOSE UPTAKE INTO SKELETAL MUSCLE – THE RATE-LIMITING STEP

69

different mechanisms operate in a concerted fashion, translating metabolic and hormonal information into both short and long term regulation of enzymatic activity. Short term (seconds to minutes) regulation is frequently achieved by allosteric modulation and reversible phosphorylation, whereas long term (hours to days) regulation largely employs alterations in gene and protein expression. Table 2.2 summarizes the major molecular mechanism(s) engaged by insulin in regulating its major protein targets. An example of combined allosteric modulation, covalent modifications and expressional regulation is offered by the pyruvate dehydrogenase complex (PDH). This large enzymatic complex catalyses the irreversible oxidative decarboxylation of pyruvate to form acetyl CoA, linking glycolysis to the mitochondrial citric acid cycle. PDH is negatively regulated allosterically mainly by its products acetyl CoA and NADH, curbing energy production from glucose when NEFA are abundant as a fuel source. In addition, reversible phosphorylation is achieved by at least four PDH kinases and two phosphatases, which respectively decrease or increase the overall catalytic activity of the complex. Insulin rapidly decreases the expression level of PDH kinases 4 and 2, reducing the phosphorylation input on PDH and ultimately elevating its catalytic activity. The above sections discussed the complex mechanisms utilized by insulin to regulate glucose metabolism and its homeostasis in the context of total body fuel metabolism. Among these, the stimulation of glucose uptake by insulin into skeletal muscle remains quantitatively at the centre of the hypoglycaemic actions of this hormone under normal physiological conditions. Impairment of this process calls into action extreme adaptive responses to maintain glucose homeostasis, in the form of compensatory hyperinsulinaemia and/or glucose funnelling into alternative sites (as demonstrated by the MIRKO mice). Decompensation of these mechanisms results in pathological manifestations (e.g. diabetes). We next focus on the cellular and molecular mechanisms by which insulin stimulates the uptake of glucose into skeletal muscle.

2.4 Glucose uptake into skeletal muscle – the rate-limiting step in glucose metabolism As discussed above, glucose entering muscle cells encounters various fates, but it rarely accumulates as free glucose in the sarcoplasm.42 – 44 This observation has led to the concept that, under both fasting and fed conditions, glucose transport across the membrane of the muscle fibre is rate limiting for glucose utilization. This notion was further confirmed by the use of magnetic resonance spectroscopy, which allows detection of intracellular glucose-6-phosphate43 as well as intracellular glucose levels.10 However, under certain physiological conditions (e.g. exercise)45 or in other tissues (e.g. cardiomyocytes)46 steps

70

INSULIN-MEDIATED REGULATION OF GLUCOSE METABOLISM

beyond glucose transport such as glucose phosphorylation might become rate limiting.

Does GLUT4 dictate glucose uptake in muscle and fat cells? The GLUT family comprises 13 members, but only seven of these (GLUTs 1–4, 6, 8 and 11) have demonstrated glucose transport activity.47 Muscle and fat cells express predominantly GLUT4. From this expression pattern as well as functional studies showing that GLUT4 translocates to the plasma membrane in response to insulin, GLUT4 is generally believed to mediate insulin-stimulated glucose uptake. This notion was further confirmed recently by experiments using GLUT4 gene ablation or a rather selective inhibitor of GLUT4 (the HIV protease inhibitor indinavir), as outlined below. Mice lacking GLUT4 have diminished glucose uptake in response to insulin or exercise,48, 49 and mice lacking GLUT4 selectively in skeletal muscle50 or in adipose tissues12 have impaired glucose and insulin tolerance. Similarly, heterozygous GLUT4-null mice are severely insulin resistant and develop diabetes.51 Overall, these findings underline the importance of GLUT4 for insulinand contraction-dependent glucose uptake. In addition, muscle-specific GLUT4 knockout mice demonstrate the important regulatory role of skeletal muscle in glucose homeostasis.50 Surprisingly, homozygous GLUT4-null mice had normal glucose tolerance even though they showed impaired insulin tolerance, suggesting insulin resistance. The mechanism by which homozygous GLUT4null mice are protected from diabetes is still unclear. The most likely explanation is that compensatory mechanisms are induced.52, 48 For example, other GLUT isoforms may be expressed at higher levels, which then compensate for GLUT4. Although no up-regulation of GLUT1, GLUT3 or GLUT5 could be detected,52, 48 glucose uptake into isolated soleus muscle was mediated by a saturable glucose-transport process and blocked by the classical inhibitor of GLUTs, cytochalasin B.48 Thus glucose uptake into soleus muscle from GLUT4null mice appears to be mediated by some other member of the GLUT family (potentially GLUT8). Genetic ablation of GLUT4 has confirmed its importance for normal insulin sensitivity; however, it does not reveal the quantitative contribution of GLUT4 to glucose influx into normal tissues, since compensatory mechanisms in the affected tissue are induced. Until recently, glucose uptake through a specific GLUT isoform could not be directly assessed given the lack of inhibitors with sufficient selectivity for any given GLUT. The HIV protease inhibitor indinavir was recently found to selectively block GLUT4-mediated glucose uptake into Xenopus laevis oocytes exogenously expressing different GLUTs.53 The IC50 of indinavir on glucose uptake was much lower in oocytes expressing GLUT4 compared with those expressing GLUT2, GLUT1, GLUT3 or a GLUT8 mutant directed to the cell surface.54 Using this approach, we studied the contribution

GLUCOSE UPTAKE INTO SKELETAL MUSCLE – THE RATE-LIMITING STEP

71

Table 2.3 Percentage inhibition of glucose uptake by the HIV protease inhibitor indinavir (100 µM) in skeletal muscle and adipocytes

Soleus EDL L6 GLUT4myc myotubes L6 wild type myotubes White adipocytes Brown adipocytes 3T3-L1 adipocytes

Basal

Insulin

61.1 ± 4.8 67.9 ± 12.8 80.0 ± 2.1 32.1 ± 6.3 93.2 ± 2.4 48.7 ± 18.1 45.4 ± 6.6

64.8 ± 7.4 80.3 ± 4.9 73.2 ± 2.6 49.6 ± 3.2 78.1 ± 4.9 93.2 ± 3.5 67.2 ± 3.0

Cells or tissues were stimulated for 20–30 min without (basal) or with 100 nM insulin, followed by the measurement of 2-deoxyglucose uptake in the absence or presence of 100 µM indinavir. Values are the percentage inhibition by indinavir.

of GLUT4 to insulin-stimulated glucose uptake in mammalian cell lines as well as in primary adipocytes and isolated skeletal muscles.55 We found that GLUT4 is the major contributor to insulin-stimulated glucose uptake into skeletal muscle, white and brown adipocyte and L6 wild type muscle cells as well as L6 cells overexpressing a myc-tagged GLUT4 (Table 2.3). However, in 3T3-L1 adipocytes, the effect of indinavir on glucose uptake was more variable, averaging a 67 per cent inhibition of insulin-stimulated glucose uptake. These results confirm the high contribution of GLUT4 to insulin-stimulated glucose uptake in mature muscle and cells; however, the contribution of GLUT4 to basal glucose uptake is less clear. Among cell lines representing these tissues, only in L6 cells (over)expressing GLUT4myc, but not wild-type L6 or 3T3-L1 adipocytes, GLUT4 accounted functionally for the majority of basal glucose uptake.

Insulin-mediated GLUT4 traffic Glucose transport into skeletal muscle fibres probably occurs along the two domains of the sarcolemma: the plasma membrane and the transverse tubules. This assumption is based on the detection of GLUT4 glucose transporters in both domains when isolated by subcellular fractionation,56 or imaged upon GLUT4 photolabelling,57 immunoelectron microscopy58, 59 or fluorescence microscopy of GLUT4-GFP.60 GLUT1 can also be detected on isolated plasma membranes of rodent and human muscle (but not on isolated transverse tubules),56 and by immunocytochemistry on muscle sections.61, 56 However, contributions from endothelial cells to the isolated fractions, or ambiguity in the immunofluorescence detection, cast doubt on the significance of GLUT1 presence at the muscle surface. Moreover, as discussed above, it is GLUT4 that has preponderance in dictating to glucose influx into skeletal muscle in the absence and presence of insulin.

72

INSULIN-MEDIATED REGULATION OF GLUCOSE METABOLISM

Insulin increases the rate of glucose influx into skeletal muscle measured in vivo, ex vivo (in isolated muscles, teased fibres) or in muscle cells in culture. The magnitude of this response ranges from two- to eightfold, with a mean around threefold when 20 studies were analysed.62 This is in contrast to the larger response observed in rodent (but not in human) adipose cells. How does GLUT4 mediate the increase in glucose uptake caused by insulin? In 1981 it was first reported that isolated plasma membrane from insulintreated rat diaphragm had a higher number of cytochalasin B-binding sites than membranes from control muscles.63 Cytochalasin B is a rather specific ligand of GLUT-family proteins, and hence the results suggested that, as in rat adipocytes, there is a gain in the number of glucose transporters in response to the hormone. Shortly thereafter, we and others reported that purified plasma membranes and transverse tubules of hindlimb skeletal muscles show a gain in cytochalasin B-binding sites,64, 65 and these were then identified as GLUT4 upon immunoblotting with specific antibodies.66, 56 The gain in GLUT4 at the surface of muscles was further established by a variety of techniques including immunoelectron microscopy of ultrathin muscle slices,58 surface affinity photolabelling with bis-mannose derivates followed by either GLUT4 immunoprecipitation57 or avidin pull-down of the photolabel followed by GLUT4 immunoblotting,67 and more recently detection of electrotransfected GLUT4-GFP by fluorescence microscopy.60 Interestingly, when analysed, there was a qualitatively parallel reduction in the GLUT4 in intracellular membranes. None of the techniques listed above provide the opportunity to quantitatively recover the surface membranes and the intracellular membranes. Some, surface affinity photolabelling for example, do not afford detection of the intracellular pool. Hence, to date it has not been possible to quantitatively account for the gain in surface glucose transporters vis-`a-vis their loss in intracellular stores. Moreover, the gain in surface GLUT4 remains a semiquantitative measurement, as all the approaches listed have confounding factors such as contamination with intracellular membranes, incomplete immunoprecipitation or limited sampling of the cell surface in ultrathin sections. The limitations of these approaches are discussed in a recent publication.68 Muscle cells in culture offer the possibility to examine in more detail the mechanism of GLUT4 translocation to the cell surface, the signals involved and the distribution of the intracellular pools. Although primary cultures of muscle have been of limited use to answer these questions (largely due to their low levels of GLUT4, their low response to insulin and the variability from culture to culture69, 70 ) muscle cell lines have been more yielding. The L6 muscle cell line, originally derived from satellite cells of thigh muscle from day-old rats, expresses GLUT4 upon cell differentiation from myoblasts into myotubes.a Moreover, these cells have the capacity to express large levels of a As with most cell lines, there is currently diversity in the clones available. Not all clones express GLUT4, and not all clones show myoblast fusion into myotubes.

GLUCOSE UPTAKE INTO SKELETAL MUSCLE – THE RATE-LIMITING STEP

73

exogenous GLUT4 without mistargetting it.71 We have established and characterized an L6 muscle cell line expressing myc-tagged GLUT4 at levels about fivefold higher than those of endogenous GLUT4 in skeletal muscle. The myc tag is present in the first exofacial loop, allowing one to detect surface GLUT4 immunologically without cell lysis. This feature provides a means to measure GLUT4 translocation to the cell surface without interference from intracellular GLUT4 either stored or docked below the plasma membrane, and in parallel to measure glucose uptake.71, 72 The exofacial tag is also instrumental in tracing the intracellular route of GLUT4 as it internalizes from the cell surface and reemerges in response to insulin. Using this tool, we have established the following features of GLUT4myc stably expressed in L6 muscle cells (L6GLUT4myc). (a) GLUT4myc continuously cycles to and from the cell surface. The half-time of this cycling is 2 h in the basal state and 40 min in the presence of insulin. It takes 6 h for all the intracellular GLUT4myc to cycle to the surface in the basal state, and this time is reduced to 3 h in the presence of insulin.73 (b) GLUT4myc largely resides intracellularly, with only 10 per cent of the total content being present at the surface of unstimulated muscle cells. Insulin causes a two- to threefold gain in surface GLUT4myc.74 (c) The large intracellular depot of GLUT4myc segregates away from GLUT1 but coincides with the insulin-responsive aminopeptidase (IRAP).71 The latter protein has been used to characterize the insulin-sensitive GLUT4 compartment in fat cells and skeletal muscle.75 (d) GLUT4myc dictates glucose uptake, given its almost 100-fold excess over endogenous GLUT4, GLUT1 or GLUT3.76 This was functionally demonstrated by the nearly complete inhibition of basal and insulin-stimulated glucose uptake by indinavir. (e) GLUT4myc responds to insulin, hyperosmolarity, mitochondrial uncouplers and anti-diabetic drugs.77, 74, 78, 72 (f) Surface-labelled GLUT4myc traverses the recycling endosomes, in both the absence and presence of insulin. Strikingly, the hormone accelerates the transit time through these endosomes, presumably as part of the mechanism of speeding up GLUT4myc recycling to the cell surface.73 (g) A large proportion (70 per cent) of the insulin-dependent gain in surface GLUT4myc requires intact VAMP2,79 a vesicular SNARE that mediates fusion of vesicles in the regulated exocytic pathway in differentiated cells.80 This property is shared by the endogenous GLUT4 in adipose cells81 and muscle cells.82 (h) A subset of GLUT4myc segregates into the actin mesh that forms below the cell surface in response to insulin. This location also includes vesicles

74

INSULIN-MEDIATED REGULATION OF GLUCOSE METABOLISM

containing VAMP2 and IRAP. Actin remodelling is required for effective GLUT4myc translocation to the cell surface.83 – 85 All of these features lead us to propose a model for GLUT4myc cycling in muscle cells, as outlined next and depicted in Figure 2.1. Specific comparisons are made with GLUT4 traffic in adipose cells in culture (3T3-L1). The model offers paradigms that should now be tested in mature muscle fibres. In the basal state, GLUT4 continuously cycles to and from the plasma membrane, re-entering the endosomal system and reaching the perinuclear endosomes containing transferrin receptor. Here, GLUT4 appears to be sorted into a storage or specialized compartment that however is not static, since all GLUT4 molecules eventually reach the muscle plasma membrane.73 (In 3T3-L1 adipocytes about half of the GLUT4 molecules are also segregated away from the transferrin receptor.86 ) This specialized compartment is marked by the presence of VAMP2 and the lack of transferrin receptor. In fact, imaging of the perinuclear GLUT4

Exocytosis Endocytosis

Recycling vesicle Specialized vesicle

Sorting (recycling) endosome

Insulin Transferrin receptor VAMP2 GLUT4myc

Figure 2.1 The GLUT4 cycle and its regulation by insulin: proposed model for GLUT4 translocation in muscle cells (see the text for details)

GLUCOSE UPTAKE INTO SKELETAL MUSCLE – THE RATE-LIMITING STEP

75

compartment shows a tight perinuclear ring containing both GLUT4 and transferrin receptor, and a pointed ‘cone’ emanating from it devoid of the latter receptor.87 (A recent model also proposes the existence of a storage compartment in 3T3-L1 adipocytes that is in equilibrium with the endosomal/transGolgi network.26 ) Recycling GLUT4 molecules are envisaged to exit the recycling endosome directly en route to the plasma membrane. Such basal traffic is not affected by ablating VAMP2 or VAMP3 with tetanus toxin.79 Insulin stimulation causes the loss of the GLUT4 ‘cone’, presumably due to budding of GLUT4 containing vesicles. These vesicles find their way to the plasma membrane presumably via microtubules88, 89 and eventually are trapped in a submembranous, insulin-dependent actin mesh.83, 84 As well, the transit of GLUT4 through the endosomal system is accelerated,73 presumably to continuously feed the storage compartment and vesicles emanating from it (sorting of GLUT4 at a post-recycling endosome step also occurs in 3T3-L1 adipocytes90 and primary fat cells91 ). Vesicles gathered by the actin mesh contain VAMP2 and IRAP–a marker of GLUT4 compartments. GLUT4 eventually fuses with the plasma membrane via VAMP2 binding to plasma membrane target-SNAREs syntaxin4 and SNAP23.80 GLUT4 emerges all over the muscle cell surface but with certain predominance above actin-remodelled sites, in regions resembling membrane ruffles.84 Whether GLUT4 vesicles contribute to ruffle formation or the ruffle membrane curvature facilitates their fusion remains to be determined. In adipose cells, the actin cytoskeleton also participates in GLUT4 translocation to the plasma membrane, but actin remodelling appears to involve filaments perpendicular to caveolae and parallel to the plasma membrane. Other stimuli, such as hyperosmolarity and potentially agents that lower ATP levels, cause GLUT4 translocation via vesicles not requiring VAMP2 nor involving the cytoskeleton and without taxing the GLUT4 ‘cone’.87 The simplest interpretation is that such stimuli promote GLUT4 exit directly from the recycling endosome. An attractive hypothesis is that the endosome is the store of GLUT4 molecules recruited to the plasma membrane in response to exercise in skeletal muscle, a scenario supported by immunofluorescence detection of GLUT4 in the intact tissue.59

Signals regulating GLUT4 traffic The above segregation of GLUT4 in specialized compartments is likely brought about by so far unidentified proteins involved in retention and sorting of the transporter, presumably interacting via distinctive sequences at its amino- and carboxy-terminal cytosolic tails.92 The acceleration of GLUT4 interendosomal transit and distinct mobilization of GLUT4 from the specialized compartment require input from signals elicited by the occupied insulin receptor. There is now little doubt that phosphorylation of insulin receptor substrates (IRS) is important for the insulin-dependent mobilization of GLUT4.93 This participation is manifest by binding and activation of phosphatidylinositol 3-kinase (PI3K), a

76

INSULIN-MEDIATED REGULATION OF GLUCOSE METABOLISM

lipid kinase that phosphorylates inositol phospholipids (PIPs) in the 3
position, mostly PI3,4,5-P3 . This lipid product is membrane bound and is generated on both the plasma membranes and membranes gathered by the insulin-dependent actin mesh.94 PI3,4,5-P3 serves a dual function, activating phosphatidylinositol dependent kinase (PDK) and attracting PDK substrates such as protein kinase B (PKB)/Akt. There is increasing support for the concept that Akt is required for insulin-dependent translocation of GLUT495 – 97 as is another PDK substrate, the atypical protein kinase C.98, 99 At which level in the cycle of GLUT4 traffic these enzymes exert their input remains to be determined. In muscle cells, the interendosomal acceleration of GLUT4 requires input of PI3K → PKB, and the formation of the actin mesh requires input of PI3K but not PKB.97 In this instance, PI3K leads to activation of the small GTPase Rac that determines actin remodelling. Atypical PKC appears to phosphorylate VAMP2 and this may promote GLUT4 insertion into the plasma membrane.100 Additional inputs may occur at the level of vesicle docking, leading to membrane fusion, involving these or other enzymes. Regulation is also envisaged for additional functions such as GLUT4 budding from the specialized compartment and loading onto microtubules. In 3T3-L1 adipocytes, a signalling pathway emanating from the receptor but distinct from the IRS → PI3K → PKB pathway has been recently described. In this case, the receptor leads to tyrosine phosphorylation on Cbl aided by the proteins CAP and APS.101 – 103 The CAP–pCbl complex then migrates to caveolae, where it links to flotillin, and through a relay of binding events links the proteins CrkII and C3G to the small GTPase TC10, ultimately regulating cortical actin dynamics independently of PI3K. Interplay between the TC10 pathway and the PI3K pathway appears to occur at the level of atypical PKC.104, 105 Whether the TC10 pathway also operates in skeletal muscle is currently unknown, but it does not seem to be a major regulator of actin dynamics in muscle cells in culture.106 With the exception of VAMP2, the pertinent phosphorylated substrates of atypical PKC or PKB remain to be mapped. Recent advances in the use of targeted elimination of specific genes, such as through small interference RNA, may bring us closer to this goal.

Does GLUT4 translocation explain the full increase in glucose uptake? From the above accounts, it is clear that insulin increases glucose uptake into skeletal muscle and adipose tissue via translocation of GLUT4 from intracellular compartments to the cell surface, and that GLUT4 is responsible for insulindependent glucose uptake. Does translocation account for the full gain in glucose uptake in response to insulin? Several studies showed a discrepancy between the extent of GLUT4 translocation and the stimulation of glucose uptake in response to insulin in skeletal muscle,107, 108, 56 rat white adipocytes109 and brown adipocytes.110, 111 In addition, the percentage increase of glucose uptake

GLUCOSE UPTAKE INTO SKELETAL MUSCLE – THE RATE-LIMITING STEP

77

was greater than the change in GLUT4 content in plasma membrane vesicles isolated from untreated or insulin-stimulated skeletal muscle tissue.112 It is therefore possible that GLUT4 activation may occur in addition to its translocation. In order to establish valid comparisons between insulin-stimulated glucose uptake and GLUT4 translocation, it is necessary to quantify GLUT4 translocation in intact cells and tissues. From such a comparison it will be possible to assess the contribution of changes in the intrinsic activity of GLUT4, as long as there is no contribution to glucose uptake from other transporters. As discussed above, studies in mice lacking GLUT4 in muscle as well as experiments using the HIV protease inhibitor indinavir confirmed the important and exclusive contribution of GLUT4 to insulin-stimulated glucose uptake. The documentation of GLUT4 translocation has largely relied on subcellular fractionation and affinity photolabelling. Even though these techniques were very helpful in documenting GLUT4 translocation in response to insulin, both methods have their limitations. Subcellular fractionation does not afford accurate calculation of the number of transporters present in the plasma membrane of intact tissues since the yield of membrane is low and separation of the individual membrane compartments is incomplete. In addition, fractionation cannot distinguish GLUT4 vesicles incorporated into the plasma membrane from those docked but unfused or occluded. Affinity photolabelling with impermeant sugar-containing ligands followed by selective immunoprecipitation was developed as an alternative to subcellular fractionation. Using this technique, the reported changes in cell surface GLUT4 in response to insulin are higher and often parallel changes in glucose uptake. However, since the photolabels used (e.g. ATB-BMPA) bind to the exofacial glucose binding site,113 GLUT4 translocation may be overestimated due to preferential labelling of activated surface GLUT4.114, 115 Therefore, none of the existing methodologies allow for accurate quantification of GLUT4 translocation. To circumvent this problem we recently developed the L6 GLUT4myc cell line, expressing GLUT4 encoding a myc epitope in its first exofacial loop. The intracellular distribution, segregation, recycling, exocytic and endocytic rates and insulin response of GLUT4myc are virtually identical to those of GLUT4.73, 74, 79, 71 The change in GLUT4 at the cell surface of intact myotubes is determined by immunofluorescent and immunochemical labelling of the myc epitope.74, 72, 97 In order to assess a potential contribution of GLUT4 activation on insulinstimulated glucose uptake in intact tissues and cells, we recently developed a line of transgenic mice expressing GLUT4myc in skeletal and cardiac as well as brown and white adipose tissue.117 GLUT4myc translocation was studied in isolated brown adipocytes by immunochemical labelling of the myc epitope. The percentage increase in insulin-stimulated glucose uptake exceeded markedly the percentage increase in insulin-induced GLUT4myc translocation. These results suggest that indeed there may be a contribution of activation of GLUT4 to insulin-stimulated glucose uptake.

78

INSULIN-MEDIATED REGULATION OF GLUCOSE METABOLISM

What could this additional input be? We got closer to answering this question by the observation that preincubation with the pyridinylimidazoles SB203580 and SB202190, selective inhibitors of the p38 mitogen-activated protein kinase (MAPK), reduced insulin-stimulated glucose uptake significantly but did not affect cell surface GLUT4myc levels in L6 GLUT4myc myotubes or brown adipocytes.117, 116, 118 Further studies should address the pyridinylimidazole targets involved in GLUT4 activation.

Acknowledgements We thank Dr. Nava Bashan for helpful insight, and the members of the Klip laboratory for their participation in the studies summarized herein. The original work from the Klip laboratory quoted was supported by grants from the Canadian Institutes of Health Research and from the Canadian Diabetes Association. A.R. was supported by a fellowship from the Hospital for Sick Children. D.K. was supported by the University of Toronto Scholarship Fund at The Hospital for Sick Children through the Clinician–Scientist Training Program.

References 1. DeFronzo, R. A. (1988) Lilly lecture 1987. The triumvirate: beta-cell, muscle, liver. A collusion responsible for NIDDM. Diabetes 37, 667–687. 2. Kletzien, R. F., Harris, P. K. and Foellmi, L. A. (1994) Glucose-6-phosphate dehydrogenase: a ‘housekeeping’ enzyme subject to tissue-specific regulation by hormones, nutrients, and oxidant stress. FASEB J 8, 174–181. 3. Gerich, J. E., Meyer, C., Woerle, H. J. and Stumvoll, M. (2001) Renal gluconeogenesis: its importance in human glucose homeostasis. Diabetes Care 24, 382–391. 4. Moller, N., Rizza, R. A., Ford, G. C. and Nair, K. S. (2001) Assessment of postabsorptive renal glucose metabolism in humans with multiple glucose tracers. Diabetes 50, 747–751. 5. Michael, M. D., Kulkarni, R. N., Postic, C., Previs, S. F., Shulman, G. I., Magnuson, M. A. and Kahn, C. R. (2000) Loss of insulin signaling in hepatocytes leads to severe insulin resistance and progressive hepatic dysfunction. Mol Cell 6, 87–97. 6. Kim, J. K., Michael, M. D., Previs, S. F., Peroni, O. D., Mauvais-Jarvis, F., Neschen, S., Kahn, B. B., Kahn, C. R. and Shulman, G. I. (2000) Redistribution of substrates to adipose tissue promotes obesity in mice with selective insulin resistance in muscle. J Clin Invest 105, 1791–1797. 7. Lewis, G. F., Zinman, B., Groenewoud, Y., Vranic, M. and Giacca, A. (1996) Hepatic glucose production is regulated both by direct hepatic and extrahepatic effects of insulin in humans. Diabetes 45, 454–462. 8. Rebrin, K., Steil, G. M., Getty, L. and Bergman, R. N. (1995) Free fatty acid as a link in the regulation of hepatic glucose output by peripheral insulin. Diabetes 44, 1038–1045. 9. Randle, P. J., Garland, P. B., Hales, C. N. and Newsholme, E. A. (1963) The glucose fatty-acid cycle: its role in insulin sensitivity and the metabolic disturbances of diabetes mellitus. Lancet i, 785–789.

REFERENCES

79

10. Cline, G. W., Petersen, K. F., Krssak, M., Shen, J., Hundal, R. S., Trajanoski, Z., Inzucchi, S., Dresner, A., Rothman, D. L. and Shulman, G. I. (1999) Impaired glucose transport as a cause of decreased insulin-stimulated muscle glycogen synthesis in type 2 diabetes. N Engl J Med 341, 240–246. 11. Roden, M., Price, T. B., Perseghin, G., Petersen, K. F., Rothman, D. L., Cline, G. W. and Shulman, G. I. (1996) Mechanism of free fatty acid-induced insulin resistance in humans. J Clin Invest 97, 2859–2865. 12. Abel, E. D., Peroni, O., Kim, J. K., Kim, Y. B., Boss, O., Hadro, E., Minnemann, T., Shulman, G. I. and Kahn, B. B. (2001) Adipose-selective targeting of the GLUT4 gene impairs insulin action in muscle and liver. Nature 409, 729–733. 13. Fruhbeck, G., Gomez-Ambrosi, J., Muruzabal, F. J. and Burrell, M. A. (2001) The adipocyte: a model for integration of endocrine and metabolic signaling in energy metabolism regulation. Am J Physiol 280, E827–847. 14. Havel, P. J. (2002) Control of energy homeostasis and insulin action by adipocyte hormones: leptin, acylation stimulating protein, and adiponectin. Curr Opin Lipidol 13, 51–59. 15. Combs, T. P., Berg, A. H., Obici, S., Scherer, P. E. and Rossetti, L. (2001) Endogenous glucose production is inhibited by the adipose-derived protein Acrp30. J Clin Invest 108, 1875–1881. 16. Tomas, E., Tsao, T. S., Saha, A. K., Murrey, H. E., Zhang, C., Itani, S. I., Lodish, H. F. and Ruderman, N. B. (2002) Enhanced muscle fat oxidation and glucose transport by ACRP30 globular domain: acetyl-CoA carboxylase inhibition and AMP-activated protein kinase activation. Proc Natl Acad Sci USA 99, 16 309–16 313. 17. Leibel, R. L. (2002) The role of leptin in the control of body weight. Nutr Rev 60, S15–19; discussion S68–84, 85–17. 18. Ceddia, R. B., Koistinen, H. A., Zierath, J. R. and Sweeney, G. (2002) Analysis of paradoxical observations on the association between leptin and insulin resistance. FASEB J 16, 1163–1176. 19. Bradley, R. L. and Cheatham, B. (1999) Regulation of ob gene expression and leptin secretion by insulin and dexamethasone in rat adipocytes. Diabetes 48, 272–278. 20. Kim, J. B., Sarraf, P., Wright, M., Yao, K. M., Mueller, E., Solanes, G., Lowell, B. B. and Spiegelman, B. M. (1998) Nutritional and insulin regulation of fatty acid synthetase and leptin gene expression through ADD1/SREBP1. J Clin Invest 101, 1–9. 21. Fasshauer, M., Klein, J., Neumann, S., Eszlinger, M. and Paschke, R. (2002) Hormonal regulation of adiponectin gene expression in 3T3-L1 adipocytes. Biochem Biophys Res Commun 290, 1084–1089. 22. Stefan, N. and Stumvoll, M. (2002) Adiponectin – its role in metabolism and beyond. Horm Metab Res 34, 469–474. 23. Bruning, J. C., Gautam, D., Burks, D. J., Gillette, J., Schubert, M., Orban, P. C., Klein, R., Krone, W., Muller-Wieland, D. and Kahn, C. R. (2000) Role of brain insulin receptor in control of body weight and reproduction. Science 289, 2122–2125. 24. Woods, S. C., Lotter, E. C., McKay, L. D. and Porte, D., Jr. (1979) Chronic intracerebroventricular infusion of insulin reduces food intake and body weight of baboons. Nature 282, 503–505. 25. Clark, M. G., Wallis, M. G., Barrett, E. J., Vincent, M. A., Richards, S. M., Clerk, L. H. and Rattigan, S. (2003) Blood flow and muscle metabolism: a focus on insulin action. Am J Physiol 284, E241–258. 26. Bryant, N. J., Govers, R. and James, D. E. (2002) Regulated transport of the glucose transporter GLUT4. Nat Rev Mol Cell Biol 3, 267–277. 27. Furtado, L. M., Somwar, R., Sweeney, G., Niu, W. and Klip, A. (2002) Activation of the glucose transporter GLUT4 by insulin. Biochem Cell Biol 80, 569–578.

80

INSULIN-MEDIATED REGULATION OF GLUCOSE METABOLISM

28. Charron, M. J., Katz, E. B. and Olson, A. L. (1999) GLUT4 gene regulation and manipulation. J Biol Chem 274, 3253–3256. 29. Barzilai, N. and Rossetti, L. (1993) Role of glucokinase and glucose-6-phosphatase in the acute and chronic regulation of hepatic glucose fluxes by insulin. J Biol Chem 268, 25 019–25 025. 30. Printz, R. L., Koch, S., Potter, L. R., O’Doherty, R. M., Tiesinga, J. J., Moritz, S. and Granner, D. K. (1993) Hexokinase II mRNA and gene structure, regulation by insulin, and evolution. J Biol Chem 268, 5209–5219. 31. Okar, D. A., Manzano, A., Navarro-Sabate, A., Riera, L., Bartrons, R. and Lange, A. J. (2001) PFK-2/FBPase-2: maker and breaker of the essential biofactor fructose- 2,6bisphosphate. Trends Biochem Sci 26, 30–35. 32. Chen-Zion, M., Livnat, T. and Beitner, R. (1992) Insulin rapidly stimulates binding of phosphofructokinase and aldolase to muscle cytoskeleton. Int J Biochem 24, 821–826. 33. Yamada, K. and Noguchi, T. (1999) Nutrient and hormonal regulation of pyruvate kinase gene expression. Biochem J 337, 1–11. 34. Cohen, P. and Frame, S. (2001) The renaissance of GSK3. Nat Rev Mol Cell Biol 2, 769–776. 35. Brady, M. J. and Saltiel, A. R. (2001) The role of protein phosphatase-1 in insulin action. Recent Prog Horm Res 56, 157–173. 36. Harris, R. A., Bowker-Kinley, M. M., Huang, B. and Wu, P. (2002) Regulation of the activity of the pyruvate dehydrogenase complex. Adv Enzyme Regul 42, 249–259. 37. Munday, M. R. and Hemingway, C. J. (1999) The regulation of acetyl-CoA carboxylase – a potential target for the action of hypolipidemic agents. Adv Enzyme Regul 39, 205–234. 38. Johnson, L. N. (1992) Glycogen phosphorylase: control by phosphorylation and allosteric effectors. FASEB J 6, 2274–2282. 39. Roach, P. J. (2002) Glycogen and its metabolism. Curr Mol Med 2, 101–120. 40. van Schaftingen, E. and Gerin, I. (2002) The glucose-6-phosphatase system. Biochem J 362, 513–532. 41. Jitrapakdee, S. and Wallace, J. C. (1999) Structure, function and regulation of pyruvate carboxylase. Biochem J 340, 1–16. 42. Katz, A., Nyomba, B. L. and Bogardus, C. (1988) No accumulation of glucose in human skeletal muscle during euglycemic hyperinsulinemia. Am J Physiol 255, E942–945. 43. Rothman, D. L., Shulman, R. G. and Shulman, G. I. (1992) 31 P nuclear magnetic resonance measurements of muscle glucose-6-phosphate. Evidence for reduced insulindependent muscle glucose transport or phosphorylation activity in non-insulin-dependent diabetes mellitus. J Clin Invest 89, 1069–1075. 44. Ziel, F. H., Venkatesan, N. and Davidson, M. B. (1988) Glucose transport is rate limiting for skeletal muscle glucose metabolism in normal and STZ-induced diabetic rats. Diabetes 37, 885–890. 45. Halseth, A. E., Bracy, D. P. and Wasserman, D. H. (1999) Overexpression of hexokinase II increases insulin and exercise-stimulated muscle glucose uptake in vivo. Am J Physiol 276, E70–77. 46. Manchester, J., Kong, X., Nerbonne, J., Lowry, O. H. and Lawrence, J. C., Jr. (1994) Glucose transport and phosphorylation in single cardiac myocytes: rate- limiting steps in glucose metabolism. Am J Physiol 266, E326–333. 47. Joost, H. G., Bell, G. I., Best, J. D., Birnbaum, M. J., Charron, M. J., Chen, Y. T., Doege, H., James, D. E., Lodish, H. F., Moley, K. H. et al. (2002) Nomenclature of the GLUT/SLC2A family of sugar/polyol transport facilitators. Am J Physiol 282, E974–976.

REFERENCES

81

48. Ryder, J. W., Kawano, Y., Galuska, D., Fahlman, R., Wallberg-Henriksson, H., Charron, M. J. and Zierath, J. R. (1999) Postexercise glucose uptake and glycogen synthesis in skeletal muscle from GLUT4-deficient mice. FASEB J 13, 2246–2256. 49. Stenbit, A. E., Burcelin, R., Katz, E. B., Tsao, T. S., Gautier, N., Charron, M. J. and Le Marchand-Brustel, Y. (1996) Diverse effects of Glut 4 ablation on glucose uptake and glycogen synthesis in red and white skeletal muscle. J Clin Invest 98, 629–634. 50. Zisman, A., Peroni, O. D., Abel, E. D., Michael, M. D., Mauvais-Jarvis, F., Lowell, B. B., Wojtaszewski, J. F., Hirshman, M. F., Virkamaki, A., Goodyear, L. J. et al. (2000) Targeted disruption of the glucose transporter 4 selectively in muscle causes insulin resistance and glucose intolerance. Nat Med 6, 924–928. 51. Stenbit, A. E., Tsao, T. S., Li, J., Burcelin, R., Geenen, D. L., Factor, S. M., Houseknecht, K., Katz, E. B. and Charron, M. J. (1997) GLUT4 heterozygous knockout mice develop muscle insulin resistance and diabetes. Nat Med 3, 1096–1101. 52. Katz, E. B., Stenbit, A. E., Hatton, K., DePinho, R. and Charron, M. J. (1995) Cardiac and adipose tissue abnormalities but not diabetes in mice deficient in GLUT4. Nature 377, 151–155. 53. Murata, H., Hruz, P. W. and Mueckler, M. (2000) The mechanism of insulin resistance caused by HIV protease inhibitor therapy. J Biol Chem 275, 20 251–20 254. 54. Murata, H., Hruz, P. W. and Mueckler, M. (2002) Indinavir inhibits the glucose transporter isoform Glut4 at physiologic concentrations. Aids 16, 859–863. 55. Rudich, A., Konrad, D., T¨or¨ok, D., Ben-Romano, R., Huang, C., Niu, W., Garg, R. R., Wijesekara, N., Germinario, R. J., Bilan, P. J. and Klip, A. (2003) Indinavir uncovers different contributions of GLUT4 and GLUT1 towards glucose uptake in muscle and fat cells and tissues. Diabetologia 46, 649–658. 56. Marette, A., Richardson, J. M., Ramlal, T., Balon, T. W., Vranic, M., Pessin, J. E. and Klip, A. (1992) Abundance, localization, and insulin-induced translocation of glucose transporters in red and white muscle. Am J Physiol 263, C443–452. 57. Wilson, C. M. and Cushman, S. W. (1994) Insulin stimulation of glucose transport activity in rat skeletal muscle: increase in cell surface GLUT4 as assessed by photolabelling. Biochem J 299, 755–759. 58. Friedman, J. E., Dudek, R. W., Whitehead, D. S., Downes, D. L., Frisell, W. R., Caro, J. F. and Dohm, G. L. (1991) Immunolocalization of glucose transporter GLUT4 within human skeletal muscle. Diabetes 40, 150–154. 59. Ploug, T., van Deurs, B., Ai, H., Cushman, S. W. and Ralston, E. (1998) Analysis of GLUT4 distribution in whole skeletal muscle fibers: identification of distinct storage compartments that are recruited by insulin and muscle contractions. J Cell Biol 142, 1429–1446. 60. Lauritzen, H. P., Reynet, C., Schjerling, P., Ralston, E., Thomas, S., Galbo, H. and Ploug, T. (2002) Gene gun bombardment-mediated expression and translocation of EGFP-tagged GLUT4 in skeletal muscle fibres in vivo. Pflugers Arch 444, 710–721. 61. Handberg, A., Kayser, L., Hoyer, P. E. and Vinten, J. (1991) Distribution of the glucose transporter GLUT1 in rat skeletal muscle evaluated by immunocytochemistry and immunoblotting. Proceedings of the satellite symposium on ‘Diabetes and Exercise’, Vermont. 62. Bonen, A., Clark, M. G. and Henriksen, E. J. (1994) Experimental approaches in muscle metabolism: hindlimb perfusion and isolated muscle incubations. Am J Physiol 266, E1–16. 63. Wardzala, L. J. and Jeanrenaud, B. (1981) Potential mechanism of insulin action on glucose transport in the isolated rat diaphragm. Apparent translocation of intracellular transport units to the plasma membrane. J Biol Chem 256, 7090–7093.

82

INSULIN-MEDIATED REGULATION OF GLUCOSE METABOLISM

64. Hirshman, M. F., Wallberg-Henriksson, H., Wardzala, L. J., Horton, E. D. and Horton, E. S. (1988) Acute exercise increases the number of plasma membrane glucose transporters in rat skeletal muscle. FEBS Lett 238, 235–239. 65. Klip, A., Ramlal, T., Young, D. A. and Holloszy, J. O. (1987) Insulin-induced translocation of glucose transporters in rat hindlimb muscles. FEBS Lett 224, 224–230. 66. Douen, A. G., Ramlal, T., Rastogi, S., Bilan, P. J., Cartee, G. D., Vranic, M., Holloszy, J. O. and Klip, A. (1990) Exercise induces recruitment of the ‘insulinresponsive glucose transporter’. Evidence for distinct intracellular insulin- and exerciserecruitable transporter pools in skeletal muscle. J Biol Chem 265, 13 427–13 430. 67. Ryder, J. W., Yang, J., Galuska, D., Rincon, J., Bjornholm, M., Krook, A., Lund, S., Pedersen, O., Wallberg-Henriksson, H., Zierath, J. R. and Holman, G. D. (2000) Use of a novel impermeable biotinylated photolabeling reagent to assess insulin- and hypoxiastimulated cell surface GLUT4 content in skeletal muscle from type 2 diabetic patients. Diabetes 49, 647–654. 68. Klip, A. and Marette, A. (2001) Regulation of glucose transporters by insulin and exercise: cellular effects and implications for diabetes. In: Jefferson, L. S. and Cherrington, A. D., eds. Handbook of Physiology, Section 7: The Endocrine System. New York: Oxford University Press, 451–494. 69. Sarabia, V., Lam, L., Burdett, E., Leiter, L. A. and Klip, A. (1992) Glucose transport in human skeletal muscle cells in culture. Stimulation by insulin and metformin. J Clin Invest 90, 1386–1395. 70. Mitsumoto, Y. and Klip, A. (1992) Development regulation of the subcellular distribution and glycosylation of GLUT1 and GLUT4 glucose transporters during myogenesis of L6 muscle cells. J Biol Chem 267 (7), 4957–4962. 71. Ueyama, A., Yaworsky, K. L., Wang, Q., Ebina, Y. and Klip, A. (1999) GLUT-4myc ectopic expression in L6 myoblasts generates a GLUT-4- specific pool conferring insulin sensitivity. Am J Physiol 277, E572–578. 72. Wang, Q., Khayat, Z., Kishi, K., Ebina, Y. and Klip, A. (1998) GLUT4 translocation by insulin in intact muscle cells: detection by a fast and quantitative assay. FEBS Lett 427, 193–197. 73. Foster, L. J., Li, D., Randhawa, V. K. and Klip, A. (2001) Insulin accelerates interendosomal GLUT4 traffic via phosphatidylinositol 3-kinase and protein kinase B. J Biol Chem 276, 44 212–44 221. 74. Li, D., Randhawa, V. K., Patel, N., Hayashi, M. and Klip, A. (2001) Hyperosmolarity reduces GLUT4 endocytosis and increases its exocytosis from a VAMP2-independent pool in l6 muscle cells. J Biol Chem 276, 22 883–22 891. 75. Sumitani, S., Ramlal, T., Somwar, R., Keller, S. R. and Klip, A. (1997) Insulin regulation and selective segregation with glucose transporter-4 of the membrane aminopeptidase vp165 in rat skeletal muscle cells. Endocrinology 138, 1029–1034. 76. Huang, C., Somwar, R., Patel, N., Niu, W., Torok, D. and Klip, A. (2002) Sustained exposure of L6 myotubes to high glucose and insulin decreases insulin-stimulated GLUT4 translocation but upregulates GLUT4 activity. Diabetes 51, 2090–2098. 77. Konrad, D., Somwar, R., Sweeney, G., Yaworsky, K., Hayashi, M., Ramlal, T. and Klip, A. (2001) The antihyperglycemic drug alpha-lipoic acid stimulates glucose uptake via both GLUT4 translocation and GLUT4 activation: potential role of p38 mitogenactivated protein kinase in GLUT4 activation. Diabetes 50, 1464–1471. 78. Patel, N., Khayat, Z. A., Ruderman, N. B. and Klip, A. (2001) Dissociation of 5
AMPactivated protein kinase activation and glucose uptake stimulation by mitochondrial uncoupling and hyperosmolar stress: differential sensitivities to intracellular Ca2+ and protein kinase C inhibition. Biochem Biophys Res Commun 285, 1066–1070.

REFERENCES

83

79. Randhawa, V. K., Bilan, P. J., Khayat, Z. A., Daneman, N., Liu, Z., Ramlal, T., Volchuk, A., Peng, X. R., Coppola, T., Regazzi, R. et al. (2000) VAMP2, but not VAMP3/cellubrevin, mediates insulin-dependent incorporation of GLUT4 into the plasma membrane of L6 myoblasts. Mol Biol Cell 11, 2403–2417. 80. Foster, L. J. and Klip, A. (2000) Mechanism and regulation of GLUT-4 vesicle fusion in muscle and fat cells. Am J Physiol 279, C877–890. 81. Cain, C. C., Trimble, W. S. and Lienhard, G. E. (1992) Members of the VAMP family of synaptic vesicle proteins are components of glucose transporter-containing vesicles from rat adipocytes. J Biol Chem 267, 11 681–11 684. 82. Volchuk, A., Mitsumoto, Y., He, L., Liu, Z., Habermann, E., Trimble, W. and Klip, A. (1994) Expression of vesicle-associated membrane protein 2 (VAMP-2)/synaptobrevin II and cellubrevin in rat skeletal muscle and in a muscle cell line. Biochem J 304, 139–145. 83. Khayat, Z., Tong, P., Yaworsky, K., Bloch, R. and Klip, A. (2000) Insulin-induced actin filament remodeling: colocalization with phosphatidylinositol 3-kinase and GLUT4 in L6 myotubes. J Cell Sci 113, 279–290. 84. Tong, P., Khayat, Z. A., Huang, C., Patel, N., Ueyama, A. and Klip, A. (2001) Insulininduced cortical actin remodeling promotes GLUT4 insertion at muscle cell membrane ruffles. J Clin Invest 108, 371–381. 85. Tsakiridis, T., Taha, C., Grinstein, S. and Klip, A. (1996) Insulin activates a p21activated kinase in muscle cells via phosphatidylinositol 3-kinase. J Biol Chem 271, 19 664–19 667. 86. Zeigerer, A., Lampson, M. A., Karylowski, O., Sabatini, D. D., Adesnik, M., Ren, M. and McGraw, T. E. (2002) GLUT4 retention in adipocytes requires two intracellular insulin-regulated transport steps. Mol Cell Biol 13, 2421–2435. 87. Randhawa, V. K., Thong, F., Lim, D. Y., Li, D., Garg, R. R., Rudge, R., Galli, T., Rudich, A. and Klip, A. (2004) Insulin and hypertonicity recruit GLUT4 to the plasma membrane of muscle cells using NSF-dependent SNARE mechanism but different VSNAREs: Role of TI-VAMP. Mol Cell Biol submitted. 88. Emoto, M., Langille, S. E. and Czech, M. P. (2001) A role for kinesin in insulinstimulated glut4 glucose transporter translocation in 3T3-L1 adipocytes. J Biol Chem 276, 10 677–10 682. 89. Olson, A. L., Trumbly, A. R. and Gibson, G. V. (2001) Insulin-mediated GLUT4 translocation is dependent on the microtubule network. J Biol Chem 276, 10 706– 10 714. 90. Lampson, M. A., Schmoranzer, J., Zeigerer, A., Simon, S. M. and McGraw, T. E. (2001) Insulin-regulated release from the endosomal recycling compartment is regulated by budding of specialized vesicles. Mol Biol Cell 12, 3489–3501. 91. Hah, J. S., Ryu, J. W., Lee, W., Kim, B. S., Lachaal, M., Spangler, R. A. and Jung, C. Y. (2002) Transient changes in four GLUT4 compartments in rat adipocytes during the transition, insulin-stimulated to basal: implications for the GLUT4 trafficking pathway. Biochemistry 41, 14 364–14 371. 92. Lalioti, V., Vergarajauregui, S. and Sandoval, I. V. (2001) Targeting motifs in GLUT4 [review]. Mol Membr Biol 18, 257–264. 93. Esposito, D. L., Li, Y., Cama, A. and Quon, M. J. (2001) Tyr(612) and Tyr(632) in human insulin receptor substrate-1 are important for full activation of insulin-stimulated phosphatidylinositol 3-kinase activity and translocation of GLUT4 in adipose cells. Endocrinology 142, 2833–2840. 94. Patel, N., Rudich, A., Khayat, Z., Garg, R. R. and Klip, A. (2003) Intracellular segregation of phosphatidylinositol-3,4,5-trisphosphate by insulin-dependent actin remodeling in L6 skeletal muscle cells. Mol Cell Biol 23 (13), 4611–4626.

84

INSULIN-MEDIATED REGULATION OF GLUCOSE METABOLISM

95. Hill, M. M., Clark, S. F., Tucker, D. F., Birnbaum, M. J., James, D. E. and Macaulay, S. L. (1999) A role for protein kinase Bbeta/Akt2 in insulin-stimulated GLUT4 translocation in adipocytes. Mol Cell Biol 19, 7771–7781. 96. Kohn, A. D., Summers, S. A., Birnbaum, M. J. and Roth, R. A. (1996) Expression of a constitutively active Akt Ser/Thr kinase in 3T3-L1 adipocytes stimulates glucose uptake and glucose transporter 4 translocation. J Biol Chem 271, 31 372–31 378. 97. Wang, Q., Somwar, R., Bilan, P. J., Liu, Z., Jin, J., Woodgett, J. R. and Klip, A. (1999) Protein kinase B/Akt participates in GLUT4 translocation by insulin in L6 myoblasts. Mol Cell Biol 19, 4008–4018. 98. Kotani, K., Ogawa, W., Matsumoto, M., Kitamura, T., Sakaue, H., Hino, Y., Miyake, K., Sano, W., Akimoto, K., Ohno, S. and Kasuga, M. (1998) Requirement of atypical protein kinase clambda for insulin stimulation of glucose uptake but not for Akt activation in 3T3-L1 adipocytes. Mol Cell Biol 18, 6971–6982. 99. Standaert, M. L., Galloway, L., Karnam, P., Bandyopadhyay, G., Moscat, J. and Farese, R. V. (1997) Protein kinase C-zeta as a downstream effector of phosphatidylinositol 3-kinase during insulin stimulation in rat adipocytes. Potential role in glucose transport. J Biol Chem 272, 30 075–30 082. 100. Braiman, L., Alt, A., Kuroki, T., Ohba, M., Bak, A., Tennenbaum, T. and Sampson, S. R. (2001) Activation of protein kinase C zeta induces serine phosphorylation of VAMP2 in the GLUT4 compartment and increases glucose transport in skeletal muscle. Mol Cell Biol 21, 7852–7861. 101. Baumann, C. A., Ribon, V., Kanzaki, M., Thurmond, D. C., Mora, S., Shigematsu, S., Bickel, P. E., Pessin, J. E. and Saltiel, A. R. (2000) CAP defines a second signalling pathway required for insulin-stimulated glucose transport. Nature 407, 202–207. 102. Chiang, S. H., Baumann, C. A., Kanzaki, M., Thurmond, D. C., Watson, R. T., Neudauer, C. L., Macara, I. G., Pessin, J. E. and Saltiel, A. R. (2001) Insulin-stimulated GLUT4 translocation requires the CAP-dependent activation of TC10. Nature 410, 944–948. 103. Liu, J., Kimura, A., Baumann, C. A. and Saltiel, A. R. (2002) APS facilitates c-Cbl tyrosine phosphorylation and GLUT4 translocation in response to insulin in 3T3-L1 adipocytes. Mol Cell Biol 22, 3599–3609. 104. Kanzaki, M. and Pessin, J. E. (2002) Caveolin-associated filamentous actin (Cav-actin) defines a novel F-actin structure in adipocytes. J Biol Chem 277, 25867–25869. 105. Standaert, M. L., Kanoh, Y., Sajan, M. P., Bandyopadhyay, G. and Farese, R. V. (2002) Cbl, IRS-1, and IRS-2 mediate effects of rosiglitazone on PI3K, PKC-lambda, and glucose transport in 3T3/L1 adipocytes. Endocrinology 143, 1705–1716. 106. JeBailey, L., Rudich, A., Huang, X., Di Ciano-Oliveira, C., Kapus, A. and Klip, A. (2004) Skeletal muscle cells and adipocytes differ in their reliance on TC10 and Rac for insulin–induced actin remodeling. Mol Endocrinol 18, 359–372. 107. Goodyear, L. J., Hirshman, M. F., Smith, R. J. and Horton, E. S. (1991) Glucose transporter number, activity, and isoform content in plasma membranes of red and white skeletal muscle. Am J Physiol 261, E556–561. 108. Guma, A., Zierath, J. R., Wallberg-Henriksson, H. and Klip, A. (1995) Insulin induces translocation of GLUT-4 glucose transporters in human skeletal muscle. Am J Physiol 268, E613–622. 109. Ferrara, C. M. and Cushman, S. W. (1999) GLUT4 trafficking in insulin-stimulated rat adipose cells: evidence that heterotrimeric GTP-binding proteins regulate the fusion of docked GLUT4-containing vesicles. Biochem J 343 Pt 3, 571–577. 110. Omatsu-Kanbe, M., Zarnowski, M. J. and Cushman, S. W. (1996) Hormonal regulation of glucose transport in a brown adipose cell preparation isolated from rats that shows a large response to insulin. Biochem J 315, 25–31.

REFERENCES

85

111. Shimizu, Y., Satoh, S., Yano, H., Minokoshi, Y., Cushman, S. W. and Shimazu, T. (1998) Effects of noradrenaline on the cell-surface glucose transporters in cultured brown adipocytes: novel mechanism for selective activation of GLUT1 glucose transporters. Biochem J 330, 397–403. 112. King, P. A., Horton, E. D., Hirshman, M. F. and Horton, E. S. (1992) Insulin resistance in obese Zucker rat (fa/fa) skeletal muscle is associated with a failure of glucose transporter translocation. J Clin Invest 90, 1568–1575. 113. Holman, G. D., Kozka, I. J., Clark, A. E., Flower, C. J., Saltis, J., Habberfield, A. D., Simpson, I. A. and Cushman, S. W. (1990) Cell surface labeling of glucose transporter isoform GLUT4 by bis- mannose photolabel. Correlation with stimulation of glucose transport in rat adipose cells by insulin and phorbol ester. J Biol Chem 265, 18 172–18 179. 114. Asano, T., Katagiri, H., Takata, K., Lin, J. L., Ishihara, H., Inukai, K., Tsukuda, K., Kikuchi, M., Hirano, H., Yazaki, Y. et al. (1991) The role of N-glycosylation of GLUT1 for glucose transport activity. J Biol Chem 266, 24 632–24 636. 115. Harrison, S. A., Clancy, B. M., Pessino, A. and Czech, M. P. (1992) Activation of cell surface glucose transporters measured by photoaffinity labeling of insulin-sensitive 3T3L1 adipocytes. J Biol Chem 267, 3783–3788. 116. Niu, W., Huang, C., Nawaz, Z., Levy, M., Somwar, R., Li, D., Bilan, P. J. and Klip, A. (2003) Maturation of the regulation of GLUT4 activity by p38 MAPK during L6 cell myogenesis. J Biol Chem 278, 17 953–17 962. 117. Konrad, D., Bilan, P. J., Nawaz, Z., Sweeney, G., Niu, W., Liu, Z., Antonescu, C. N., Rudich, A. and Klip, A. (2002) Need for GLUT4 activation to reach maximum effect of insulin-mediated glucose uptake in brown adipocytes isolated from GLUT4mycexpressing mice. Diabetes 51, 2719–2726. 118. Sweeney, G., Somwar, R., Ramlal, T., Volchuk, A., Ueyama, A. and Klip, A. (1999) An inhibitor of p38 mitogen-activated protein kinase prevents insulin-stimulated glucose transport but not glucose transporter translocation in 3T3-L1 adipocytes and L6 myotubes. J Biol Chem 274, 10 071–10 078.

3 Insulin Action on Lipid Metabolism Keith N. Frayn and Fredrik Karpe

3.1 Introduction: does insulin affect lipid metabolism? The effects of insulin have traditionally been assessed by measurements of glucose metabolism. Glycaemic control in diabetes mellitus was long monitored by measuring urinary glucose. The body’s sensitivity to insulin is almost always measured in terms of glucose disposal; indeed, the measurement of insulindependent glucose disposal using the euglycaemic–hyperinsulinaemic clamp technique1 is usually considered the ‘gold standard’ method.2 Yet sufferers from diabetes mostly die not directly from hyperglycaemia, but from cardiovascular disease, a process in which lipids are generally considered to be intimately involved. Moreover, the marked wasting seen in young patients who are deficient in insulin suggests anabolic actions of insulin on both fat and protein stores. Indeed, Vincent Marks once famously declared that if it were as easy to measure plasma fatty acid concentrations as it is those of glucose, we would think of diabetes primarily as a disorder of fat metabolism (personal communication); and the late Denis McGarry wrote ‘What if Minkowski had been ageusic?’ (lacking a sense of taste, so he would not have detected glucose in the urine in diabetes), again posing the question of whether we should think of diabetes primarily in terms of disturbed fat metabolism.3 In this chapter we will show that insulin does, indeed, have profound effects on fat metabolism. This is not surprising. Insulin is undoubtedly the major hormonal co-ordinator of metabolic events related to fasting and feeding. We do not feed upon carbohydrate alone. It seems entirely appropriate that insulin should integrate the metabolism of carbohydrate, protein and fat, and we will illustrate in this chapter to some extent how that integration is brought about. Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

88

INSULIN ACTION ON LIPID METABOLISM

3.2 Molecular mechanisms by which insulin regulates lipid metabolism The molecular signalling pathways by which insulin regulates lipid metabolism can be divided into effects elicited by post-receptor intracellular phosphorylations with subsequent regulation of activity states of intracellular enzymes, and effects on transcription. A prime example of the first chain of events is the downregulation of hormone-sensitive lipase (HSL) in adipocytes by insulin, described in detail below. Examples of regulation of gene transcription by insulin involve the sterol regulatory element binding protein 1c (SREBP-1c) and the Forkhead (Fox), in particular the FoxO subfamily. These mechanisms have recently been reviewed.4 Microarray technology provides a powerful demonstration of insulin action on gene transcription. In human skeletal muscle, exposed in vivo to elevated insulin concentrations by a hyperinsulinaemic, normoglycaemic clamp, more than 800 genes showed a short-term regulation.5 Due to the metabolic perturbation in such a metabolic situation and secondary effects, only some of these genes are likely to have been directly regulated by insulin, i.e. through a direct mechanism linking cell surface insulin receptor activation with the activation of an insulin response element (IRE) in a gene promoter. The IRE is a consensus nucleotide sequence motif of the bases T(G/A)TTT(TG)(GT). The signalling pathway from the insulin receptor, eventually leading to the binding of a transcription factor to an IRE in a gene promoter, is not fully elucidated and it does not seem to consist of a single mechanism. However, a pathway shared between several genes appears to be that of phosphoinositide 3-kinase (PI3 -kinase) activation forming phosphatidylinositol (3
,4
,5
)-trisphosphate (PIP3 ), which activates protein kinase B (PKB, also known as Akt), which in turn phosphorylates one of the variants of the Fox family members of transcription factors. The phosphorylated Fox protein loses affinity for the IRE and show signs of nuclear exclusion. The end result is decreased transcriptional activity. A physiological example of negative regulation of insulin in line with decreased transcriptional activity is the gene encoding for apolipoprotein C-III (apoC-III).6 Insufficient down-regulation of the gene product may lead to overproduction of apoC-III. ApoC-III is a known inhibitor of lipoprotein lipase (LPL) and it also interferes with the receptor-mediated removal of triacylglycerol- (TG-) rich lipoprotein particles from plasma. This is likely to provide one of the molecular mechanisms for the link between hypertriglyceridaemia and insufficient insulin action such as in insulin resistance. The strongest evidence for a link between insulin action and gene transcription regulating lipid metabolism comes from the investigation of SREBP-1c. Insulin strongly induces the transcription of SREBP-1c. The effect is specific for SREBP-1c as there is no effect on the splice variant originating from the same gene, SREBP-1a, nor on the related gene product SREBP-2. In line with

INSULIN AND LIPOLYSIS

89

the insulin-elicited signal transduction chain ending with the FoxO-mediated transcriptional depression, the effect on SREBP-1c transcription is mediated through the insulin receptor, the insulin-receptor substrate 1 (IRS-1) phosphorylation and subsequent PKB/Akt phosphorylation. The ultimate links between SREBP-1c-mediated transcriptional events and insulin-mediated effects on cellular lipid homeostasis are however subject to intracellular sterol sensing. SREBP1 is localized to the endoplasmic reticulum (ER) and the protein undergoes a sequence of protein cleavages. The membrane-spanning SREBP cleavage activating peptide (SCAP) is sensitive to membrane lipid/cholesterol content. The SCAP molecule has seven membrane-spanning domains, which convey the true membrane sterol sensing. When activated, SCAP promotes the activity of a site1 protease. This allows, in turn, for a site-2 protease that cleaves off the final signalling peptide derived from the SREBP-1c protein. The site-2 protease is strictly dependent on the site-1 cleavage. The cleaved peptide leaves the ER location, enters the nucleus and ultimately binds to a sterol regulated element (SRE). The consensus sequence of the SRE is 5
-TCACNCCAC-3
, where N represents any base. A number of genes involved in regulatory steps in fatty acid synthesis are induced by activation of the SREBP-1c signalling pathway. Fatty acid synthase (FAS), acetyl CoA carboxylase (ACC), stearoyl CoA desaturase (SCD-1) and glycerol-3-phosphate acyltransferase (GPAT) have SREs and they will coordinately promote synthesis of TGs. Insulin may also affect transcription indirectly by stabilizing mRNA. These mechanisms are poorly understood, but prolonging the life of the mRNA molecule may provide more opportunities for translation.

3.3 Insulin and lipolysis Effects of insulin in vivo If insulin is injected or infused and plasma levels of fat-related compounds monitored, then the most immediate and pronounced effect of insulin is to lower the plasma concentration of non-esterified fatty acids (NEFAs). This effect is actually more pronounced than the blood-glucose-lowering effect of insulin. It is achieved primarily through a direct effect of insulin on adipocytes to suppress NEFA release. There may be some effect on other tissues causing increased NEFA clearance, but this must be relatively minor as, under most circumstances, the plasma NEFA concentration is related closely to the NEFA production rate.7, 8 Dose–response curves in vivo show this to be a potent effect8, 9 (Figure 3.1). The data in Figure 3.1 show glucose production rate (glucose Ra , dotted line with diamonds) and glucose utilization rate (glucose Rd , dotted line with triangles)69 and the rate of appearance of nonesterified fatty acids (Ra NEFA, solid line with circles).9 They are recalculated

90

INSULIN ACTION ON LIPID METABOLISM

Percentage of maximal value

100 Glucose Ra

80

Glucose Rd

60 40

NEFA Ra

20 0

50

150

500 1500 Plasma insulin (pmol/l)

4500

15 000

Figure 3.1 Dose–response curves for the effects of insulin on glucose and fatty acid metabolism in vivo. A range of insulin concentrations was produced in normal, healthy subjects using incremental insulin infusion/euglycaemic clamp techniques

so 100 per cent represents the maximal value. The horizontal dotted line represents 50 per cent of maximal rate. Note that suppression of NEFA appearance is the most sensitive to insulin (i.e. crosses the 50 per cent line furthest to the left). NEFAs are released into the blood primarily from the hydrolysis of TG stores in adipocytes. In this process, glycerol is also produced. Glycerol release from adipocytes or adipose tissue is often taken as a marker of lipolysis, since adipose tissue expresses relatively low levels of (according to some sources no) glycerol kinase activity, which would be necessary for reutilization of glycerol released from triacylglycerol hydrolysis. When insulin is infused, glycerol release from adipose tissue is reduced, but not suppressed so completely as is NEFA release (Figure 3.2). In Figure 3.2, solid points show concentrations in arterialized blood/plasma; open points, concentrations in blood/plasma from adipose tissue venous drainage. The release of NEFA from adipose tissue (venoarterial difference) is completely suppressed by insulin, whereas the release of glycerol is not so completely suppressed. The explanation is that insulin must also stimulate re-esterification of the fatty acids released, something that has been recognized for many years.10 How insulin does this is still unclear. It may increase glucose uptake by adipocytes, and since glucose is a precursor for the glycerol 3-phosphate needed for esterification this might increase fatty acid retention. But it is also likely that insulin stimulates the esterification pathway directly, although the locus of action is not known. Insulin increases transcription of GPAT as noted above, but there are probably also acute effects on activity of the pathway.11 There is a suggestion that the fatty acids that are re-esterified have to go through an extracellular pathway.12 In that case, insulin may also increase adipocyte fatty acid re-uptake through activation of membrane transport, as described in more detail below.

INSULIN AND LIPOLYSIS

91

Blood glycerol, µmol/l

200

150

100

50

0

Plasma NEFA, µmol/l

1000 800 600 400 200 0

–40

–20

0

30

60

90

120

Time, min

Figure 3.2 Effects of insulin on glycerol and non-esterified fatty acid (NEFA) release from subcutaneous abdominal adipose tissue in vivo. Insulin was infused for 2 h from time 0 to achieve high physiological insulin concentrations; glucose concentrations were ‘clamped’ at 5 mmol/l (replotted from data in reference 70)

In normal physiological states, the main effectors of NEFA release from adipose tissue are catecholamines and insulin. After an overnight fast, the catecholamine effect is actually a tonic inhibition via α-adrenoceptors13, 14 balanced by stimulation via β-receptors, and, of importance, the lowest possible suppressive effect by insulin in this state. Accordingly, absence of insulin is not enough to fully stimulate lipolysis and further adrenergic activation is needed. The effect of insulin to reduce circulating NEFA concentrations is an important part of the coordination of metabolic processes that occurs after a meal. At that time, glucose becomes the major oxidative fuel for skeletal muscle and it is appropriate that ‘substrate competition’ from fatty acids is minimized. Also, plasma NEFAs are a potent stimulus for hepatic gluconeogenesis and glucose

92

INSULIN ACTION ON LIPID METABOLISM 400

NEFA

40 200 30 Insulin 20 100

Plasma Insulin

Plasma NEFA

300

10 Meals 0 8 a.m.

Noon

4 p.m.

8 p.m.

0 Midnight

Time of day (hours)

Figure 3.3 Twenty-four hour pattern of plasma non-esterified fatty acid (NEFA, solid line, solid points) and insulin concentrations (dashed line, open points). After each meal, as the plasma insulin concentration rises, so the plasma NEFA concentration falls (redrawn from data in reference 71 with permission)

output,15, 16 and again this stimulus is not appropriate in the postprandial period when hepatic glucose output needs to be suppressed to maintain glucose homeostasis. This means that plasma NEFA concentrations display a marked diurnal variation, the reverse of insulin concentrations, with troughs after meals and peaks before the next meal (Figure 3.3).

Molecular regulation of lipolysis by insulin and other hormones The key regulatory enzyme in the process of fat mobilization is HSL,17, 18 which preferentially hydrolyses the sn-1 and 3 ester bonds.17 The remaining fatty acid is liberated by a constitutively active monoacylglycerol lipase.19 In white adipocytes, the role of HSL is hydrolysis of the TG in the TG droplet. HSL is highly regulated, mainly by reversible phosphorylation of serine residues. Mobilization of non-esterified fatty acids from adipocyte triglycerides is stimulated primarily (at least acutely) by catecholamines acting through β-adrenoceptors, seven-transmembrane-domain GTP-binding protein-coupled receptors in the cell membrane. These stimulate adenylyl cyclase, producing 3
,5
-cyclic adenosine monophosphate (cAMP) from ATP. HSL is active when phosphorylated. Ser659

INSULIN AND LIPOLYSIS

93

and Ser660 were shown to be responsible for in vitro activation of HSL by cAMPdependent protein kinase (protein kinase A, PKA), which, in turn, is activated by binding of cAMP generated as described above. Ser565 , which is phosphorylated by AMP-activated protein kinase (AMP-kinase), may play an antilipolytic role, as its phosphorylation prevents HSL activation and impairs lipolysis. The powerful inhibitory control of adipose tissue fat mobilization by insulin is mediated through the signal chain described earlier, i.e. from the insulin receptor, via PI3 -kinase forming PIP3 , which activates PKB/Akt. PKB then phosphorylates and activates a specific isoform of cAMP-phosphodiesterase (PDE), PDE3B. PDE3B hydrolyses cAMP to AMP, so reducing cAMP concentrations.20 The cellular cAMP concentration is therefore a major integrator for the regulation of fat mobilization. Although insulin is considered the major antilipolytic hormone, other pathways involve α2 -adrenergic receptors, A1 -adenosine receptors, EP3 prostaglandin E2 receptors and neuropeptide Y/peptide YY (NPY-1) receptors. The existence of inhibitory nicotinic acid receptors is proposed to explain the well known antilipolytic action of nicotinic acid. A receptor protein for nicotinic acid in adipose tissue was postulated 40 years ago21 and has only recently been identified.22, 23 This system is summarized in Figure 3.4. HSL has a wide tissue distribution and the antilipolytic action of insulin is probably instrumental in other tissues as well. An exception to the role of insulin as chief antilipolytic hormone is found in the pancreatic β-cell. The secretion of insulin from the β-cell is strongly modulated by fatty acid concentrations and intracellular regulation of lipolysis is likely to be part of this regulation. However, as this cell is constantly flooded by high insulin concentration a Insulin (Cortisol)

Catecholamines (β) Growth hormone Insulin (Cortisol) Adenosine ANP Catecholamines (α)

Insulin

+

+

LPL

+−

FA LPL TRL particles

Lipid droplet (TG)

HSL

FA

Perilipin

Endothelium

Figure 3.4 Co-ordination by insulin of fat deposition and fat mobilization in adipose tissue. ANP, atrial natriuretic peptide (a possible signal for lipolysis); FA, fatty acids; HSL, hormone-sensitive lipase; LPL, lipoprotein lipase; TG, triacylglycerol (from reference 72)

94

INSULIN ACTION ON LIPID METABOLISM

regulation of HSL by insulin is not likely. Instead, the role of insulin appears to be substituted by GLP-1 to provide the signal for β-cell antilipolysis in the postprandial state.24

3.4 Insulin, lipoprotein lipase and cellular fatty acid uptake Lipoprotein lipase (LPL) is an extracellular enzyme, bound to the luminal aspect of the capillary endothelium. Its role is to hydrolyse circulating lipoprotein-TG in order to deliver fatty acids to extra-hepatic tissues. It is expressed in many tissues but, in terms of TG clearance from the circulation, skeletal muscle, myocardium, adipose tissue and, during lactation, mammary gland predominate. It has long been recognized that LPL activity is regulated in a tissue-specific manner according to the needs of tissues for fatty acids in different nutritional states.25, 26 Adipose tissue LPL activity is increased by insulin. This activation is not as rapid as the suppression of NEFA release from adipose tissue: in experimental situations it takes a matter of some hours of insulin infusion to become apparent.27 LPL activity in skeletal and heart muscle is down-regulated in the fed state. The effect of insulin on skeletal muscle LPL in humans is not as marked as in rodents; continuous insulin infusion for 6 h in normal volunteers increased adipose tissue LPL activity by 210 per cent, whereas skeletal muscle LPL activity was reduced by 14 per cent28 (Figure 3.5). In Figure 3.5, insulin was infused for 6 h while glucose concentrations were ‘clamped’ at the fasting level. Biopsies of adipose tissue (solid points and line) and skeletal muscle (open circles, dotted line) were taken at the beginning and end of insulin infusion. Adipose tissue LPL activity was increased by insulin whilst that in muscle was slightly decreased. In humans, a major factor regulating skeletal muscle LPL 6

25

5 15

10 4

Skeletal muscle LPL

Adipose tissue LPL

20

5

0

3 0

2

4

6

Time of insulin infusion (hours)

Figure 3.5 Tissue-specific regulation of lipoprotein lipase (LPL) activity by insulin in healthy subjects (data adapted from reference 28 with permission)

INSULIN, LIPOPROTEIN LIPASE AND CELLULAR FATTY ACID UPTAKE

95

activity is physical exercise, which up-regulates muscle LPL gene expression and enzyme activity, albeit with a lag period of several hours.29, 30 Therefore, dietary fatty acids will be preferentially delivered to adipose tissue rather than muscle in the fed state. In fasting, adipose tissue LPL activity is down-regulated, whereas that in muscle is increased, so diverting fatty acids from adipose tissue to muscle. The activation of adipose tissue LPL by insulin is multi-factorial. When changes in LPL activity in fasting and feeding have been examined in humans31 and rats,32 increased mRNA is only a small component of increased activity seen in the fed state. The major regulation appears to be the diversion of adipose tissue LPL between active and inactive forms, the latter probably destined for degradation without export to the capillary endothelium.32 LPL is active as a homodimer, and the inactive form in adipose tissue is monomeric.33 In skeletal muscle, regulation of gene expression seems to be more prominent, at least in the response to exercise.30 The fatty acids released by the action of LPL are, in general, taken up into the underlying tissue. In mammary gland their fate would largely be milk production, in skeletal and heart muscle either oxidation or storage as intracellular TG. In adipose tissue the fate of the fatty acids released by LPL from circulating TG is dependent upon nutritional state. It has long been recognized that a proportion of these fatty acids may be released directly into the plasma as NEFAs. This proportion is under nutritional control, via insulin, in adipose tissue. In the fed state, a larger proportion is directed into the tissue and a correspondingly smaller proportion released as NEFAs.34 This can be mimicked by infusion of insulin,35 which considerably alters the partitioning of LPL-derived fatty acids in adipose tissue. This effect of insulin is presumably brought about in two ways, each discussed earlier: suppression of the activity of the intracellular HSL will reduce the intracellular fatty acid concentration and increase the concentration gradient for fatty acid uptake, and stimulation of the pathway of fatty acid uptake and esterification will have a similar effect. The net effect is to increase fat deposition in adipose tissue in the postprandial period, and also to reduce postprandial circulating NEFA concentrations. The latter may be important in the co-ordination of substrate supply in the postprandial period by insulin. Cellular transport of fatty acids occurs through passive diffusion and by facilitated transfer via fatty acid transporters. One of these transporters, the fatty acid transport protein-1 (FATP-1), has recently been shown to be regulated by insulin in adipocytes.36 The regulation shows striking similarities with that of the facilitated transport of glucose via the GLUT-4 transporter, with recruitment of cell-membrane transporters from an intracellular (perinuclear) pool. FATP-1 is also highly expressed in skeletal muscle. In adipocytes, the other major fatty acid transporter is fatty acid translocase (FAT), also known as CD36.37 In cardiac myocytes, FAT, like FATP-1 and GLUT-4, is recruited from an intracellular pool to the cell membrane on stimulation by insulin.38 If this also occurred in adipocytes, these observations would suggest that FAT and FATP-1 are mainly

96

INSULIN ACTION ON LIPID METABOLISM

involved in the transport of fatty acids into adipocytes during the process of fat deposition by the LPL pathway. It is not yet clear whether FAT or FATP-1 also mediate outward transport of fatty acids delivered by intracellular lipolysis, and how the regulation by insulin would be involved in that pathway.

3.5

Co-ordinated regulation of fatty acid synthesis and ketogenesis

Ketone body concentrations are low in the fed state, and rise in starvation, greatly so if starvation is prolonged. Typical values for the combined concentrations of acetoacetate and 3-hydroxybutyrate in the overnight fasted state are <0.2 mmol/l, but in prolonged starvation concentrations reach 7–8 mmol/l.39 In diabetic ketoacidosis, caused by insulin deficiency, their combined concentrations may reach 10–20 mmol/l. Ketone bodies are a product of the β-oxidation of fatty acids in the liver. These variations in ketone body concentration reflect in part regulation of NEFA supply to the liver: plasma NEFA concentrations are low in the fed state, rise in prolonged starvation and are yet higher still in insulin deficiency. However, there must be regulation beyond fatty acid availability, since the range of ketone body concentrations is considerably wider than the range of NEFA concentrations. Indeed, in experiments with perfused rodent livers, livers taken from fed animals will not make ketone bodies to any great extent even when perfused with high concentrations of fatty acids.40 Observations such as this led to the discovery by McGarry et al. in 1977 of the role of malonyl-CoA in regulation of fatty acid oxidation.41 This is now recognized as the major point for integration of glucose and fat metabolism. In the fed state, glucose can be converted to (mitochondrial) acetyl-CoA through the pathway of glycolysis and the action of pyruvate dehydrogenase; both are activated when insulin concentrations are high. Mitochondrial acetyl-CoA can be exported to the cytosol by incorporation into citrate and transport by the tricarboxylate transporter, then cleaved by ATP:citrate lyase, an enzyme whose expression is increased by insulin, to liberate (cytosolic) acetyl-CoA. Cytosolic acetyl-CoA is the starting point for de novo synthesis of both fatty acids and cholesterol. The first step in fatty acid synthesis is the action of ACC, forming malonyl-CoA, which is then the substrate for stepwise addition by fatty acid synthase of twocarbon units to create the fatty acid chain. Gene expression of both ACC and fatty acid synthase is increased by insulin; hence the pathway for disposal of excess carbohydrate as fat is stimulated by persisting high insulin concentrations. McGarry and his colleagues discovered that malonyl-CoA is a potent inhibitor of fatty acid oxidation and ketogenesis.41 This is brought about by allosteric inhibition of the enzyme carnitine–palmitoyl transferase-1 (CPT1), responsible for transport of fatty acids into the mitochondrion for oxidation. (The fatty acids are present in the cytosol as acyl-CoA, which cannot penetrate the mitochondrial membrane. CPT1 transfers the acyl chain to carnitine, which is

INSULIN AND CHOLESTEROL SYNTHESIS

97

than translocated across the mitochondrial membranes, before another isoform of carnitine–palmitoyl transferase, CPT2, transfers the acyl chain to CoA again, the substrate for β-oxidation.) Therefore, in the fed, insulinized state, stimulation of malonyl-CoA formation from excess glucose inhibits fatty acid oxidation and ketogenesis. It is now recognized that this control mechanism operates in tissues other than the liver, for instance skeletal muscle and the pancreatic β-cell.42, 43 In fact, the skeletal muscle isoform of CPT1 is 10–100 times more sensitive to inhibition by malonyl-CoA than is the liver isoform.43 This is interesting because fatty acid synthase is not expressed in skeletal muscle: ACC is presumably present solely to generate malonyl-CoA for regulatory purposes. There are, in fact, two isoforms of ACC, commonly called either ACC1 and ACC2, or α and β. ACC1 is expressed in tissues where lipogenesis is quantitatively important, for instance liver and adipose tissue. ACC2 is the predominant isoform in skeletal and heart muscle, and is associated with the mitochondrial membrane (ACC1 is cytosolic).44 The suggestion is that ACC2 has a regulatory rather than a biosynthetic role, generating malonyl-CoA close to CPT1.

3.6

Insulin and cholesterol synthesis

As noted above, cytosolic acetyl-CoA is the precursor for synthesis of both fatty acids and cholesterol, and its production is increased when glucose and insulin levels are high. The next step in the synthesis of cholesterol is the production from three molecules of acetyl-CoA of the six-carbon compound, 3-hydroxy, 3-methylglutaric acid (HMG), esterified to CoA (HMG-CoA). The reactions are the same as those of ketone body synthesis, which also proceeds through HMGCoA, but ketogenesis involves different isoforms of the enzymes, expressed within the mitochondrial matrix; cholesterol synthesis is entirely cytosolic and regulated differently. Cytosolic HMG-CoA is reduced with NADPH to form mevalonate (and free CoA) by the enzyme HMG-CoA reductase. This enzyme is an important control step in cholesterol synthesis. It is tightly controlled at both transcriptional and post-translational levels. Transcriptional regulation is brought about by cellular sterol levels through the SREBP2 system, which operates in a similar way to the SREBP1 system described earlier. The mature (nuclear) active form of SREBP2 is formed through proteolytic cleavage in response to low cellular cholesterol levels as described in Section 3.2. Insulin does not appear to be directly involved in SREBP2 action. However, insulin does play an additional role in increasing HMG-CoA reductase gene expression.45 Post-translational regulation of HMG-CoA reductase involves mainly reversible phosphorylation; it becomes active when dephosphorylated but is inactive in its phosphorylated form. Insulin leads to dephosphorylation, and hence activation, of HMGCoA reductase.46, 47 Phosphorylation of HMG-CoA reductase is brought about by AMP-kinase,48, 49 which is often regarded as a ‘cellular fuel gauge’.49, 50 AMP-kinase is active when cellular energy levels are low and hence is usually less active when insulin levels are high.

98

INSULIN ACTION ON LIPID METABOLISM

3.7

Insulin effects on lipoprotein metabolism

Insulin has the potential to regulate both production and clearance of lipoproteins. In the case of the ‘exogenous pathway’ in which chylomicrons transport dietary fat, there is no direct evidence that insulin affects chylomicron-TG secretion, a process that is regulated primarily by the delivery of dietary fat into the small intestine. Expression of the intestinal microsomal triglyceride transfer protein, MTP, is up-regulated in animal models of insulin resistance and may increase chylomicron particle secretion,51 but there is no evidence for a direct effect of insulin. Chylomicron-TG clearance, on the other hand, is a function of lipoprotein lipase activity and this is up-regulated, at least in adipose tissue, by insulin. Since insulin also tends to down-regulate LPL in other tissues, there is no net effect of raising plasma insulin concentrations on the extent of postprandial lipaemia.52 However, insulin under these conditions will tend to deliver dietary fatty acids selectively to adipose tissue.35 The ‘endogenous pathway’ of lipoprotein metabolism is far more clearly influenced by insulin. This pathway consists of the secretion of TG-rich very low density lipoprotein (VLDL) particles from the liver, removal of TG by LPL, and eventual uptake of particles by cell-surface receptors. VLDL particles may be removed as such by the VLDL receptor, or their TG may be reduced to such an extent that they are mainly carriers of cholesteryl esters, in the form of low density lipoprotein (LDL) particles. LDL particles are removed by the LDL receptor, expressed mainly in the liver but also in most other tissues. In the insulin-deficient state of type 2 diabetes, plasma TG concentrations are high and are reduced by insulin treatment,53 and it is a common observation that insulin infusion acutely lowers plasma TG concentrations, especially in the VLDL fraction.54, 55 This effect of insulin has been studied in detail with infusions of insulin and measurements of VLDL secretion rates. It is usually the secretion of apolipoprotein B100 (apoB100), the structural protein of VLDL particles, that is measured; since each VLDL particle contains one molecule of apoB100, this is a marker of the number of particles secreted. Insulin infusion over a matter of a few hours selectively reduces secretion of VLDL particles in the larger size range (VLDL-1).56 The suppression of VLDL-1 apoB100 secretion is evident within 30 min of insulin infusion.56 Suppression of VLDL-TG secretion during insulin infusion has been observed directly by hepatic venous catheterization.55 The interpretation of this effect is complicated because insulin has a powerful suppressive effect on NEFA delivery to the liver, as noted earlier, and this in itself might well be expected to reduce VLDL-TG secretion. If NEFA concentrations are manipulated independently of insulin (either lowered or raised), there is an effect on VLDL-TG secretion but not on particle (apoB100) secretion.57, 58 In other words, insulin appears to have a specific effect on VLDL particle secretion, and this is confined to the larger, more TG-rich particles.58

REFERENCES

99

This direct effect of insulin on VLDL particle secretion is mediated via effects on the assembly process of VLDL within the hepatocyte.59 In essence, the assembly of VLDL is strictly sensitive to TG availability and TG transfer from intracellular lipid storage pools. VLDL appears to be produced in two steps and the second step involves addition of TG to the precursor lipoprotein. The second step is modulated by an adenosine diphosphate (ADP)-ribosylation factor-1 (ARF-1), which is negatively regulated by PI3 -kinase activation through insulin signalling (as described earlier). Accordingly, during insulin signalling the second step maturation of VLDL is impaired and the immature and lipidpoor lipoproteins undergo intracellular degradation instead of being secreted. Additional effects by insulin in the hepatocyte to inhibit TG availability for VLDL assembly involve the stimulation of TG storage promoted by insulin, via malonyl-CoA/CPT-1 and activation of fatty acid esterification as described earlier. Active storage of fatty acids into hepatocyte cytosolic TG stimulated by insulin will also limit the availability of TG for incorporation into VLDL. The acute inhibitory effect of insulin on VLDL secretion has been studied in detail in isolated hepatocytes.60, 61 This effect is short term. With longer exposure to insulin (beyond about 24 h), hepatocyte VLDL-TG secretion is increased.61 This is not unexpected. Insulin, as noted earlier, reduces fatty acid oxidation in hepatocytes, and hence hepatocyte TG stores will increase and must, in the end, be exported. There has been confusion in the literature about the effects of insulin on VLDL secretion, with earlier claims that insulin stimulates hepatic TG secretion.62 Recently it has been suggested that frequent stimulation by insulin switches the metabolic state of the liver, by chronic inhibition of CPT-1, so that insulin now becomes a stimulator of VLDL-TG secretion.63 This might provide an explanation for the high plasma TG concentrations that characterize the early period of adaptation to high carbohydrate, low fat diets.64 Insulin does not, in itself, increase VLDL removal rates56 , perhaps because, as noted above, it may have different effects on LPL activity in different tissues. However, it has often been noted that plasma (or LDL-) cholesterol concentrations fall somewhat during insulin infusion.54, 65, 66 This may reflect increased expression of LDL receptors. Insulin has been shown to increase LDL receptor expression in a cellular systems and in vivo.67, 68

Acknowledgement The authors acknowledge the support of the Wellcome Trust for their own studies of insulin and lipid metabolism in vivo.

References 1. DeFronzo, R. A., Tobin, J. and Andres, R. (1979) Glucose clamp technique: a method for quantifying insulin secretion and resistance. Am J Physiol 237, E214–E223.

100

INSULIN ACTION ON LIPID METABOLISM

2. Matsuda, M. and DeFronzo, R. A. (1997) In vivo measurement of insulin sensitivity in humans. In: Draznin B, Rizza R, eds. Clinical Research in Diabetes and Obesity, Part 1: Methods, Assessment, and Metabolic Regulation. Totowa, NJ: Humana, 23–65. 3. McGarry, J. D. (1992) What if Minkowski had been ageusic? An alternative angle on diabetes. Science 258, 766–770. 4. Foufelle, F. and Ferr´e, P. (2002) New perspectives in the regulation of hepatic glycolytic and lipogenic genes by insulin and glucose: a role for the transcription factor sterol regulatory element binding protein-1c. Biochem J 366, 377–391. 5. Rome, S., Cl´ement, K., Rabasa-Lhoret, R., Loizon, E., Poitou, C., Barsh, G., Riou, J., Laville, M. and Vidal, H. (2003) Microarray profiling of human skeletal muscle reveals that insulin regulates ∼800 genes during an hyperinsulinemic clamp. J Biol Chem 278, 18 063–18 068. 6. Li, W. W., Dammerman, M. M., Smith, J. D., Metzger, S., Breslow, J. L. and Leff, T. (1995) Common genetic variation in the promoter of the human apo CIII gene abolishes regulation by insulin and may contribute to hypertriglyceridemia. J Clin Invest 96, 2601–2605. 7. Issekutz, B., Bortz, W. M., Miller, H. I. and Paul, P. (1967) Turnover rate of plasma FFA in humans and in dogs. Metabolism 16, 1001–1009. 8. Bonadonna, R. C., Groop, L. C., Zych, K., Shank, M. and DeFronzo, R. A. (1990) Dose-dependent effect of insulin on plasma free fatty acid turnover and oxidation in humans. Am J Physiol 259, E736–E750. 9. Campbell, P. J., Carlson, M. G., Hill, J. O. and Nurjhan, N. (1992) Regulation of free fatty acid metabolism by insulin in humans: role of lipolysis and reesterification. Am J Physiol 263, E1063–E1069. 10. Leboeuf, B. (1965) Regulation of fatty acid esterification in adipose tissue incubated in vitro. In: Renold A. E, Cahill G. F, eds. Handbook of Physiology Section 5: Adipose Tissue. Washington, DC: American Physiological Society, 385–391. 11. Coleman, R. A., Lewin, T. M. and Muoio, D. (2000) Physiological and nutritional regulation of enzymes of triacylglycerol synthesis. Ann Rev Nutr 20, 77–103. 12. Edens, N. K., Leibel, R. L. and Hirsch, J. (1990) Mechanism of free fatty acid reesterification in human adipocytes in vitro. J Lipid Res 31, 1423–1431. 13. Arner, P., Kriegholm, E. and Engfeldt, P. (1990) In situ studies of catecholamine-induced lipolysis in human adipose tissue using microdialysis. J Pharmacol Exp Ther 254, 284–288. 14. Galitzky, J., Lafontan, M., Nordenstr¨om, J. and Arner, P. (1993) Role of vascular alpha2 adrenoceptors in regulating lipid mobilization from human adipose tissue. J Clin Invest 91, 1997–2003. 15. Boden, G., Chen, X., Ruiz, J., White, J. V. and Rossetti, L. (1994) Mechanisms of fatty acid-induced inhibition of glucose uptake. J Clin Invest 93, 2438–46. 16. Chen, X., Iqbal, N. and Boden, G. (1999) The effects of free fatty acids on gluconeogenesis and glycogenolysis in normal subjects. J Clin Invest 103, 365–372. 17. Holm, C., Osterlund, T., Laurell, H. and Contreras, J. A. (2000) Molecular mechanisms regulating hormone-sensitive lipase and lipolysis. Ann Rev Nutr 20, 365–393. 18. Kraemer, F. B. and Shen, W. J. (2002) Hormone-sensitive lipase: control of intracellular tri-(di-)acylglycerol and cholesteryl ester hydrolysis. J Lipid Res 43, 1585–1594. 19. Fredrikson, G., Tornqvist, H. and Belfrage, P. (1986) Hormone-sensitive lipase and monoacylglycerol lipase are both required for complete degradation of adipocyte triacylglycerol. Biochim Biophys Acta 876, 288–293. 20. Degerman, E., Belfrage, P. and Manganiello, V. C. (1997) Structure, localization, and regulation of cGMP-inhibited phosphodiesterase (PDE3). J Biol Chem 272, 6823–6826.

REFERENCES

101

˚ (1964) Initial distribution in mice of 3H-labelled nico21. Carlson, L. A. and Hanngren, A. tinic acid studied with autoradiography. Life Sciences 3, 867–871. 22. Wise, A., Foord, S. M. and Fraser, N. J. et al. (2003) Molecular identification of high and low affinity receptors for nicotinic acid. J Biol Chem 278, 9869–9874. 23. Tunaru, S., Kero, J., Schaub, A., Wufka, C., Blaukat, A., Pfeffer, K. and Offermanns, S. (2003) PUMA-G and HM74 are receptors for nicotinic acid and mediate its anti-lipolytic effect. Nat Med 9, 352–355. 24. Yaney, G. C., Civelek, V. N., Richard, A. M., Dillon, J. S., Deeney, J. T., Hamilton, J. A., Korchak, H. M., Tornheim, K., Corkey, B. E. and Boyd, A. E. III. (2001) Glucagon-like peptide 1 stimulates lipolysis in clonal pancreatic beta-cells (HIT). Diabetes 50, 56–62. 25. Robinson, D. S., Cryer, A. and Davies, P. (1975) The role of clearing-factor lipase (lipoprotein lipase) in the transport of plasma triglycerides. Proc Nutr Soc 34, 211–215. 26. Cryer, A. (1981) Tissue lipoprotein lipase activity and its action in lipoprotein metabolism. Internat J Biochem 13, 525–541. 27. Sadur, C. N. and Eckel, R. H. (1982) Insulin stimulation of adipose tissue lipoprotein lipase. Use of the euglycemic clamp technique. J Clin Invest 69, 1119–1125. 28. Farese, R. V., Yost, T. J. and Eckel, R. H. (1991) Tissue-specific regulation of lipoprotein lipase activity by insulin/glucose in normal-weight humans. Metabolism 40, 214–216. 29. Kiens, B., Lithell, H., Mikines, K. J. and Richter, E. A. (1989) Effects of insulin and exercise on muscle lipoprotein lipase activity in man and its relationship to insulin action. J Clin Invest 84, 1124–1129. 30. Seip, R. L., Angelopoulos, T. J. and Semenkovich, C. F. (1995) Exercise induces human lipoprotein lipase gene expression in skeletal muscle but not adipose tissue. Am J Physiol 268, E229–E236. 31. Ong, J. M. and Kern, P. A. (1989) Effect of feeding and obesity on lipoprotein lipase activity, immunoreactive protein, and messenger RNA levels in human adipose tissue. J Clin Invest 84, 305–311. 32. Berg¨o, M., Olivecrona, G. and Olivecrona, T. (1996) Forms of lipoprotein lipase in rat tissues: in adipose tissue the proportion of inactive lipase increases on fasting. Biochem J 313, 893–898. 33. Berg¨o, M., Olivecrona, G. and Olivecrona, T. (1997) Regulation of adipose tissue lipoprotein lipase in young and old rats. Int J Obes Relat Metab Disord 21, 980–986. 34. Evans, K., Burdge, G. C., Wootton, S. A., Clark, M. L. and Frayn, K. N. (2002) Regulation of dietary fatty acid entrapment in subcutaneous adipose tissue and skeletal muscle. Diabetes 51, 2684–2690. 35. Frayn, K. N., Shadid, S., Hamlani, R., Humphreys, S. M., Clark, M. L., Fielding, B. A., Boland, O. and Coppack, S. W. (1994) Regulation of fatty acid movement in human adipose tissue in the postabsorptive-to-postprandial transition. Am J Physiol 266, E308–E317. 36. Stahl, A., Evans, J. G., Pattel, S., Hirsch, D. and Lodish, H. F. (2002) Insulin causes fatty acid transport protein translocation and enhanced fatty acid uptake in adipocytes. Dev Cell 2, 477–488. 37. Abumrad, N., Coburn, C. and Ibrahimi, A. (1999) Membrane proteins implicated in longchain fatty acid uptake by mammalian cells: CD36, FATP and FABPm. Biochim Biophys Acta 1441, 4–13. 38. Luiken, J. J. F. P., Koonen, D. P. Y., Willems, J., Zorzano, A., Becker, C., Fischer, Y., Tandon, N. N., van der Vusse, G. J., Bonen, A. and Glatz, J. F. C. (2002) Insulin stimulates long-chain fatty acid utilization by rat cardiac myocytes through cellular redistribution of FAT/CD36. Diabetes 51, 3113–3119.

102

INSULIN ACTION ON LIPID METABOLISM

39. Owen, O. E., Morgan, A. P., Kemp, H. G., Sullivan, J. M., Herrera, M. G. and Cahill, G. F. (1967) Brain metabolism during fasting. J Clin Invest 46, 1589–1595. 40. McGarry, J. D. and Foster, D. W. (1980) Regulation of hepatic fatty acid oxidation and ketone body production. Annu Rev Biochem 49, 395–420. 41. McGarry, J. D., Mannaerts, G. P. and Foster, D. W. (1977) A possible role for malonylCoA in the regulation of hepatic fatty acid oxidation and ketogenesis. J Clin Invest 60, 265–270. 42. Ruderman, N. B., Saha, A. K., Vavvas, D. and Witters, L. A. (1999) Malonyl-CoA, fuel sensing, and insulin resistance. Am J Physiol 276, E1–E18. 43. Zammit, V. A. (1999) The malonyl-CoA-long-chain acyl-CoA axis in the maintenance of mammalian cell function. Biochem J 343, 505–515. 44. Abu-Elheiga, L., Brinkley, W. R., Zhong, L., Chirala, S. S., Woldegiorgis, G. and Wakil, S. J. (2000) The subcellular localization of acetyl-CoA carboxylase 2. Proc Natl Acad Sci USA 97, 1444–1449. 45. Ness, G. C., Zhao, Z. and Wiggins, L. (1994) Insulin and glucagon modulate hepatic 3-hydroxy-3-methylglutaryl-coenzyme A reductase activity by affecting immunoreactive protein levels. J Biol Chem 269, 29 168–29 172. 46. Parker, R. A., Miller, S. J. and Gibson, D. M. (1986) Phosphorylation state of HMG CoA reductase affects its catalytic activity and degradation. Adv Enzyme Regul 25, 329–343. 47. Easom, R. A. and Zammit, V. A. (1987) Acute effects of starvation and treatment of rats with anti-insulin serum, glucagon and catecholamines on the state of phosphorylation of hepatic 3-hydroxy-3-methylglutaryl-CoA reductase in vivo. Biochem J 241, 183–188. 48. Clarke, P. R. and Hardie, D. G. (1990) Regulation of HMG-CoA reductase: identification of the site phosphorylated by the AMP-activated protein kinase in vitro and in intact rat liver. EMBO J 9, 2439–2446. 49. Hardie, D. G. and Carling, D. (1997) The AMP-activated protein kinase–fuel gauge of the mammalian cell? Eur J Biochem 246, 259–273. 50. Winder, W. W. (2001) Energy-sensing and signaling by AMP-activated protein kinase in skeletal muscle. J Appl Physiol 91, 1017–1028. 51. Phillips, C., Owens, D., Collins, P. and Tomkin, G. H. (2002) Microsomal triglyceride transfer protein: does insulin resistance play a role in the regulation of chylomicron assembly? Atherosclerosis 160, 355–360. 52. Cohen, J. C. and Schall, R. (1988) Reassessing the effects of simple carbohydrates on the serum triglyceride responses to fat meals. Am J Clin Nutr 48, 1031–1034. 53. Taskinen, M.-R., Packard, C. J. and Shepherd, J. (1990) Effect of insulin therapy on metabolic fate of apolipoprotein B-containing lipoproteins in NIDDM. Diabetes 39, 1017–1027. 54. Yki-J¨arvinen, H., Taskinen, M.-R., Koivisto, V. A. and Nikkil¨a, E. A. (1984) Response of adipose tissue lipoprotein lipase activity and serum lipoproteins to acute hyperinsulinaemia in man. Diabetologia 27, 364–369. 55. B¨ulow, J., Simonsen, L., Wiggins, D., Humphreys, S. M., Frayn, K. N., Powell, D. and Gibbons, G. F. (1999) Co-ordination of hepatic and adipose tissue lipid metabolism after oral glucose. J Lipid Res 40, 2034–2043. 56. Malmstr¨om, R., Packard, C. J., Watson, T. D. G., Rannikko, S., Caslake, M., Bedford, D., Stewart, P., Yki-J¨arvinen, H., Shepherd, J. and Taskinen, M.-R. (1997) Metabolic basis of hypotriglyceridemic effects of insulin in normal men. Arterioscler Thromb Vasc Biol 17, 1454–1464. 57. Lewis, G. F., Uffelman, K. D., Szeto, L. W., Weller, B. and Steiner, G. (1995) Interaction between free fatty acids and insulin in the acute control of very low density lipoprotein production in humans. J Clin Invest 95, 158–166.

REFERENCES

103

58. Malmstr¨om, R., Packard, C. J., Caslake, M., Bedford, D., Stewart, P., Yki-J¨arvinen, H., Shepherd, J. and Taskinen, M. R. (1998) Effects of insulin and acipimox on VLDL1 and VLDL2 apolipoprotein B production in normal subjects. Diabetes 47, 779–787. 59. Gibbons, G. F., Brown, A. M., Wiggins, D. and Pease, R. (2002) The roles of insulin and fatty acids in the regulation of hepatic very-low-density lipoprotein assembly. J Royal Soc Med 95 (Suppl. 42), 23–32. 60. Durrington, P. N., Newton, R. S., Weinstein, D. B. and Steinberg, D. (1982) Effects of insulin and glucose on very low density lipoprotein triglyceride secretion by cultured rat hepatocytes. J Clin Invest 70, 63–73. 61. Bartlett, S. M. and Gibbons, G. F. (1988) Short- and longer-term regulation of verylow-density lipoprotein secretion by insulin, dexamethasone and lipogenic substrates in cultured hepatocytes. A biphasic effect of insulin. Biochem J 249, 37–43. 62. Topping, D. L. and Mayes, P. A. (1982) Insulin and non-esterified fatty acids. Acute regulators of lipogenesis in perfused rat liver. Biochem J 204, 433–439. 63. Zammit, V. A., Waterman, I. J., Topping, D. and McKay, G. (2001) Insulin stimulation of hepatic triacylglycerol secretion and the etiology of insulin resistance. J Nutr 131, 2074–2077. 64. Koutsari, C., Malkova, D. and Hardman, A. E. (2000) Postprandial lipemia after shortterm variation in dietary fat and carbohydrate. Metabolism 49, 1150–1155. 65. Sadur, C. N. and Eckel, R. H. (1983) Insulin-mediated increases in the HDL cholesterol/cholesterol ratio in humans. Arteriosclerosis 3, 339–343. 66. Baynes, C., Henderson, A. D., Richmond, W., Johnston, D. G. and Elkeles, R. S. (1992) The response of hepatic lipase and serum lipoproteins to acute hyperinsulinaemia in type 2 diabetes. Eur J Clin Invest 22, 341–346. 67. Streicher, R., Kotzka, J., Muller-Wieland, D., Siemeister, G., Munck, M., Avci, H. and Krone, W. (1996) SREBP-1 mediates activation of the low density lipoprotein receptor promoter by insulin and insulin-like growth factor-I. J Biol Chem 271, 7128–7133. 68. Swami, S., Sztalryd, C. and Kraemer, F. B. (1996) Effects of streptozotocin-induced diabetes on low density lipoprotein receptor expression in rat adipose tissue. J Lipid Res 37, 229–236. 69. Rizza, R. A., Mandarino, L. J. and Gerich, J. E. (1981) Dose–response characteristics for effects of insulin on production and utilization of glucose in man. Am J Physiol 240, E630–E639. 70. Coppack, S. W., Frayn, K. N., Humphreys, S. M., Dhar, H. and Hockaday, T. D. R. (1989) Effects of insulin on human adipose tissue metabolism in vivo. Clin Sci 77, 663–670. 71. Singer, P., G¨odicke, W., Voigt, S., Hajdu, I. and Weiss, M. (1985) Postprandial hyperinsulinemia in patients with mild essential hypertension. Hypertension 7, 182–186. 72. Frayn, K. N., Karpe, F., Fielding, B. A., Macdonald, I. A. and Coppack, S. W. (2003) Integrative physiology of human adipose tissue. Int J Obesity 27, 875–888.

4 The Effect of Insulin on Protein Metabolism Laura J. S. Greenlund and K. Sreekumaran Nair

4.1 Introduction Historical perspective It has long been appreciated that insulin, or lack of insulin, has dramatic effects on the body composition.1 Before insulin therapy became available, severe weight loss, stunted growth and cachexia were prominent features of type 1 diabetes. Descriptions of patients date back to ancient times. The Greek physician Aretaeus (A.D. 30–90) described the condition as ‘melting of the flesh into the urine’.2 In ancient Sanskrit writings diabetes is described as ‘honey urine disease’,3 implying sweetness in urine. More than 100 years ago Sir William Osler described the ‘progressive emaciation’ and massive urinary losses of both glucose and urea in type 1 diabetic patients.4 Once insulin therapy became available, it was apparent that its use could stop the wasting that was such a recognizable feature of insulin-deficient diabetes. Early on, it was demonstrated that insulin therapy resulted in preservation of body protein stores as measured by normalization of urinary nitrogen losses.5 Insulin therefore has historically been considered an anti-catabolic hormone. In this chapter we shall discuss the evidence that insulin does indeed affect protein turnover and the molecular mechanisms by which this occurs. In addition, we will review methods for measuring protein turnover in human subjects and how these have been applied to study insulin’s effect on protein turnover in vivo.

Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

106

THE EFFECT OF INSULIN ON PROTEIN METABOLISM

Protein turnover – a balance between synthesis and breakdown (Figure 4.1) In Figure 4.1 proteins in the whole body are assigned to one compartment, which includes proteins that turn over fast (a) and those that turnover slowly (b). When whole body protein turnover is measured it is the average of all these proteins with different turnover rates. Proteins such as muscle proteins with slow turnover contribute less than 30 per cent to the whole body protein turnover6 although muscle contributes more than 60 per cent of cell mass. The appearance of amino acids in the free plasma pool is derived from protein pool, non-essential amino acids from endogenous production and from the diet. During the fasted state the only source of essential amino acids appearing in the free amino acid pool is from protein breakdown. Protein breakdown (PB) and protein synthesis (PS) and amino acid oxidative nitrogen loss (urine) can be measured by techniques described elsewhere.7 Maintenance of healthy tissue requires a continuous turnover of protein whereby old or damaged tissue proteins are broken down into amino acids and new protein is synthesized to regenerate tissue. A balance in this process is required for retention of body mass. If overall protein breakdown exceeds protein synthesis there will be a net wasting of body protein. Synthesis of specific proteins occurs for specific biological functions (e.g. mitochondrial proteins for oxidative phosphorylation), which is essential for maintaining body function. The regulation of synthesis and breakdown of proteins with specific functions including structural proteins is dependent on many factors. The amount of whole body protein and the concentration of a specific protein are determined by the balance of breakdown and synthesis. Free AA pool

CO2

Extracellular Plasma

Diet

Cell

PB

PS Nitrogen

a

b

Proteins

Figure 4.1 Model of protein turnover in the whole body

MOLECULAR MECHANISMS OF INSULIN’S EFFECT ON PROTEIN TURNOVER

107

Specific proteins are synthesized and catabolized at differing rates depending on cellular requirements. For example, in the fasting state there is an increased level of the gluconeogenic enzyme phosphoenolpyruvate carboxykinase (PEPCK) within hepatocytes and kidney cells. Upon refeeding, when there is a lesser need for endogenous production of glucose, levels of PEPCK are promptly decreased in liver and kidney cells.8, 9 Similarly, administration of insulin and amino acids while maintaining glucose levels stimulate synthesis of muscle mitochondrial proteins,10 which are needed for oxidative phosphorylation. Tight regulation of protein concentrations can be achieved by altering the synthesis rate, the breakdown rate or both. Small changes in protein concentration may result in dramatic changes in cellular function. Protein turnover is regulated by several factors – some that affect synthesis rates and some that affect breakdown rates. Among those that affect synthesis rates are messenger RNA (mRNA) availability, mRNA stability, efficiency of translation initiation and ribosomal content. The availability of mRNAs (transcripts) depends not only on transcriptional factors but also on the structural integrity of DNA. Some of the factors that can influence breakdown rates include the abundance of cellular proteases and the relative activity of lysosomal and ubiquitin-mediated proteolytic pathways. Circulating hormones are important regulators of these intracellular processes. There is good evidence to support a role for insulin in regulating the intracellular events that control protein synthesis and breakdown.

4.2

Molecular mechanisms of insulin’s effect on protein turnover

Effect of insulin on intracellular events controlling protein synthesis The synthesis of a protein is a complex process. There is evidence to suggest that insulin may play an important regulatory role at several steps in protein synthesis: (1) expression of specific mRNAs, (2) stability of specific mRNAs, (3) initiation of translation, (4) protein elongation and (5) ribosomal content (Figure 4.1).11 Insulin is known to affect the expression of specific RNAs by acting through insulin response elements (IREs) in the promoter region of specific genes. Depending on the gene, this effect may be positive or negative. For example, insulin acts to up-regulate the mRNA expression of glyceraldehyde-3phosphate dehydrogenase but to down-regulate expression of PEPCK. Insulin’s effect on gene expression has been reviewed in detail elsewhere.12 Insulin may also influence the stability of select mRNAs. It has been shown that within the same cell insulin can destabilize mRNA encoding one protein while enhancing the stability of other mRNAs. For example, in cultured rat hepatocytes treatment with insulin has been shown to destabilize mRNA encoding PEPCK but to stabilize mRNA encoding glycogen phosphorylase.13 The specific

108

THE EFFECT OF INSULIN ON PROTEIN METABOLISM

mechanisms whereby insulin selectively affects mRNA stability have not been well defined. Initiation of mRNA translation into protein begins with formation of the 7methyl guanine cap at the 5-prime end of the RNA. A number of cap-associated proteins including eukaryotic initiation factor 4E (eIF-4E), eIF-4G and phosphorylated heat–acid-stable protein (PHAS-1) are influenced by insulin. PHAS-1 binds to the eIF-4E cap binding protein, insulin enhances phosphorylation of PHAS-1 and favours dissociation of eIF-4E and PHAS-1.14 This allows for binding of eIF-4E to eIF-4G and hence favours association with the 40S ribosomal subunit and translation initiation.15, 16 Also important in the binding of the 40S ribosomal subunit is eIF-2, and the binding of this initiation factor is dependent on its association with GTP. Controlling the recycling of the GTP/GDP-bound state of eIF-2 is eIF-2B. Insulin increases the activity of eIF2B and favours the GTP-bound (active) state of eIF-2, which in turn enhances translation initiation.16, 17 Protein elongation depends on the action of multiple elongation factors. Among these are elongation factor 2 (eEF-2). This factor is important for movement of the ribosomal complex along the mRNA and for the migration of the amino acyl-tRNA from the acceptor site to the peptidyl site of the ribosome.18 Insulin enhances eEF-2 activity by reducing its phosphorylation via inhibition of its kinase.19 A comprehensive description of the molecular mechanisms of insulin’s effect on translation is available in review form.20 The abundance of ribosomes and RNA content in part determines the cellular capacity to synthesize protein.21 Ribosomes are made up of approximately 80 proteins and 4 ribosomal RNA (rRNA) species. Production and assembly of ribosomes takes place in the nuclei. In chick embryo fibroblasts insulin has been shown to induce a fourfold increase in the synthesis of ribosomal proteins.22 Similar findings have been made in mouse myoblasts.23 This appears to in part be due to post-transcriptional events. Messenger RNAs that encode ribosomal proteins appear to be preferentially associated with polysomes in mouse myoblasts treated with insulin.23 The synthesis of rRNAs has been shown to increase after insulin treatment in a variety of cell types including fibroblasts,22, 24 myoblasts23 and hepatocytes.25 Finally, insulin may also reduce the rate of ribosome degradation.25 – 27

Effect of insulin on intracellular events controlling protein breakdown Cellular protein breakdown is a tightly controlled and highly specific process. In catabolic states such as starvation, sepsis or insulin deprivation, protein breakdown can markedly increase. At the intracellular level, proteins can be degraded through several pathways including the lysosomal pathway, the calcium-dependent protease pathway or the ubiquitin–proteosome path.28 The majority of proteins in mammalian cells are degraded through the ubiquitin–proteosome

MOLECULAR MECHANISMS OF INSULIN’S EFFECT ON PROTEIN TURNOVER

109

pathway. Proteins are targeted for breakdown by covalent conjugation to ubiquitin. This is an ATP-dependent process, and multiple ubiquitin molecules are added such that a ubiquitin chain is formed.29 Proteins with a ubiquitin chain attached are degraded by the ATP-dependent 26S proteosome complex. The rate-limiting step in this process is ubiquitin conjugation. Indirect evidence from animal studies suggests that ubiquitin-dependent protein degradation is important in states of insulin deprivation. Protein breakdown rates increase markedly in rats that are made insulinopenic by treatment with streptozotocin. Treatment with selective inhibitors of the lysosomal or calcium-dependent protease pathways did not affect protein breakdown. When ATP synthesis was blocked, however, protein breakdown declined.30 This suggests that ATP-dependent ubiquitin–proteosome-mediated protein breakdown is important in insulin deficiency. Others have shown that mRNAs for ubiquitin–proteosome proteins are increased in the insulin-deficient state.31 If diabetic rats are treated with insulin, protein breakdown is reduced, and ubiquitin–proteosome mRNAs are reduced to control levels.32 Acidosis and increased cortisol levels, which occur following insulin deprivation, stimulate protein degradation in the ubiquitin–proteosome pathway.32, 30 In summary, insulin deficiency in a diabetic animal model shows coordinate time-dependent changes in different proteolytic pathways in muscle, resulting in increased overall proteolysis. Only the capacity of non-lysosomal processes seems to be altered in muscle in response to insulin deficiency. The many intracellular mechanisms of insulin action to affect protein turnover are summarized in Figure 4.2.

Insulin effect on protein synthesis

mRNA transcription -IRE promoter elements

mRNA stability

Translation initiation -PHAS-1 phosphorylation - eIF-2B activity

Elongation - eEF-2 phosphorylation

Insulin effect on protein breakdown

Ubiquinone–proteosome path - activity - mRNA

Figure 4.2 Effect of insulin on protein turnover

ribosomes

110

THE EFFECT OF INSULIN ON PROTEIN METABOLISM

Insulin as a regulator of protein turnover in vitro and in situ Studying the effect of insulin on protein turnover in humans is complicated. The body is an intricate system with many hormonal mechanisms that interact with one another. Therefore, altering a single hormone such as insulin can lead to changes in other hormones, including growth hormone, glucagon, cortisol and epinephrine to name a few. These in turn can lead to changes in concentrations of substrates, such as amino acids, glucose and fatty acids, in heart rate and in blood flow or have more direct effects on protein synthesis and breakdown. Because of these complexities several in vitro and in situ systems have been used to study insulin’s effect on protein turnover. By using an in vitro or in situ model one can simplify the experiment by removing confounding factors like other hormones and alterations in other parameters such as blood flow. The simplest model is an in vitro cell culture system. In this system a homogeneous population of cells can be studied under very controlled conditions. Using a specific cell line such as L6, a rat skeletal muscle myoblast line, allows one to determine insulin’s effect on protein turnover within a single cell type. The components of the cell medium and the insulin concentration can be well defined. Using this model, it has been shown that insulin stimulates protein synthesis in L6 myoblasts.33, 34 This type of model is ideal for studies of signal transduction pathways stimulated by insulin.35, 36 The biggest disadvantage of a cell culture model is that it may not be representative of the whole body system. Cell lines are generally transformed in some manner and even when differentiated the cells lack some characteristics of cells in vivo. For example, even when L6 myoblasts are differentiated into myotubes, they do not express the same myosin heavy chain isoforms as adult skeletal muscle.37 In addition, within a tissue such as skeletal muscle, there are many different cell types such as fibroblasts, vascular muscle cells, vascular epithelium etc. These may be important modulators of skeletal muscle cells and the effect would be missed in a simple cell culture system. In order to account for these parameters but to still maintain a very controlled system, several investigators have used in situ methods to study the effect of insulin on protein turnover. These models have utilized perfused animal diaphragm, heart, skeletal muscle, or whole limbs.38 – 40, 16 Consistently, insulin reduces tissue protein breakdown. Although in situ studies provide a simplified system that may be optimal for understanding mechanisms behind insulin’s effect on protein metabolism, they too may not fully represent the in vivo situation. Ultimately, to fully understand insulin’s regulation of protein metabolism in humans, one must study an in vivo system. A number of methods have been used to measure protein turnover in animal models and in human subjects.

Animal studies Rodent models have been extensively used to study insulin effect on protein metabolism. In studies performed in growing rodents indicated that insulin

MEASUREMENT OF PROTEIN METABOLISM

111

deficiency was associated with reduced synthesis rates of muscle proteins, whereas in fully grown rodents insulin failed to stimulate muscle protein synthesis.41 Similarly, in piglets insulin stimulates muscle protein synthesis rates42 and with increasing age the magnitude of synthesis rates decreases.43, 44 These measurements were performed on mixed tissue proteins, representing the average fractional synthesis rates of many proteins. Recent studies in sexually matured miniature pigs demonstrated that when the insulin effect was determined on different subfractions of muscle proteins a specific stimulatory effect on muscle mitochondrial protein synthesis was observed, with no significant effect on synthetic rates of sarcoplasmic and myosin heavy chain proteins.45 In contrast, the insulin effect on liver proteins in mini-pigs is variable, showing no effect on liver tissue protein synthesis whereas synthesis rate of fibrinogen was inhibited.46 Since human adult life is much longer than that of rodents and pigs it is important to study the insulin effect on adult humans to understand the regulation of protein turnover in humans after the genetic potential for growth is passed.

4.3

Measurement of protein metabolism (synthesis and breakdown or turnover) in human subjects

Measurement of protein turnover Net protein turnover, a result of both synthesis and breakdown, can be quantified using a number of different methods. Some of the more global techniques include whole body nitrogen balance, 3-methylhistidine excretion (specifically for myofibrillar protein breakdown), regional amino-acid balance and systemic amino-acid tracer incorporation. By using biopsies or separation techniques, protein synthesis can also be measured within a specific tissue or for a specific protein. Ultimately, the regulation of protein concentrations may be a result of many factors including changes in gene expression, mRNA stability and translation efficiency. Assessment of changes in protein turnover induced by insulin can take place at many levels: (1) the cellular level, where one may observe the mRNA changes and changes in translation efficiency; (2) the tissue level, where one can study the effect of insulin on a specific tissue or set of proteins (such as skeletal muscle on myofibrillar proteins); (3) the regional or whole body level, where one can more globally assess insulin’s effects (Figure 4.3). In this section, the various methods of studying protein turnover in human subjects will be discussed. Following the description of each method, we shall review the use of the method to assess the effect of insulin on protein turnover.

Whole body nitrogen balance When protein is broken down, free amino acids and their metabolites are released into the circulation. All amino acids contain at least one nitrogen molecule. Transamination is a critical process necessary to transfer nitrogen for synthesis

112

THE EFFECT OF INSULIN ON PROTEIN METABOLISM

Regional Whole body Tissue

DNA and mRNA

Specific proteins Amino-acid availability Transcriptional and translational regulation

Figure 4.3 Sites to assess insulin effect on protein metabolism

of non-essential amino acids. Amino acids that are oxidized or transaminated can give rise to ammonia. Most of this circulating ammonia is converted to urea in the liver via the ornithine cycle and can be excreted in the urine. Urinary nitrogen is composed of 80–85 per cent urea and ammonia. Another 5–10 per cent of urinary nitrogen is accounted for by creatine, creatinine, uric acid and free amino acids.47 By collecting urine and stool for 24 hours, one can quantify total body nitrogen loss. To determine net nitrogen loss daily nitrogen intake also has to be measured. This reflects the summation of multiple processes including changes in protein breakdown, protein synthesis, dietary protein intake, and alterations in the recycling of amino acids. Although this method seems straightforward in concept, there are several problems with it. First, results can be affected by changes in renal function, hydration status, certain medications and the amount of protein that is ingested. Generally, subjects are asked to maintain a specific diet (normalized for protein intake) for several days before a study. This reduces the variability in nitrogen generated by dietary protein intake. In diabetic patients with reduced renal function, proteinuria or renal tubular acidosis, the results of whole body nitrogen balance can be unreliable.

Insulin effect as measured by nitrogen balance and free amino-acid concentrations Early studies on diabetic patients used whole body nitrogen balance to assess the effect of insulin on whole body protein metabolism. Withdrawal of insulin

MEASUREMENT OF PROTEIN METABOLISM

113

treatment has been shown to increase urinary nitrogen losses and to increase the concentrations of several essential amino acids, especially branched chain amino acids.48, 1, 49 Insulin treatment normalizes the increased urinary nitrogen loss and the increased circulating amino-acid concentrations.5, 49, 50 In 1976, Walsh and colleagues51 studied 18 uncontrolled diabetic patients before and after 6–8 weeks of treatment. This group was a mixture of type 1 and type 2 diabetic patients. In subjects who were given insulin to control blood sugars, there was an average weight gain of 8.7 per cent and average nitrogen balance of +13 per cent. In the diabetic patients treated with diet alone or with diet and an oral agent there was no change in weight, and only a +3.8 per cent nitrogen balance.51 This increase in body mass and a positive nitrogen balance shows that in patients who are relatively insulin deficient (diabetic patients) treatment with insulin has an anabolic effect.

3-methylhistidine quantification Skeletal muscle actin and myosin contain 3-methylhistidine (3-MH). This modified amino acid is not further metabolized or reutilized after release from actin or myosin. The only fate is urinary excretion. These properties make 3-MH a potential surrogate for muscle protein breakdown. 3-MH measurements comparing arterial versus venous concentrations have been made across local tissue beds (the forearm or leg). In this type of study, the increase in venous concentration of 3-MH can provide good estimates of muscle protein breakdown. Whole body studies quantifying urinary excretion of 3-MH are difficult to interpret and do not necessarily reflect only skeletal muscle protein breakdown because smooth muscle (particularly intestinal) can give rise to as much as 10 per cent of urinary 3-MH.47 Moreover, myofibrillar proteins have slow turnover (approximately 1–2 per cent/day), which makes it difficult to perform short term studies on the effect of insulin on myofibrillar protein breakdown.

Insulin effect as measured by 3-MH In healthy volunteers, insulin infusion does not change the flux of 3-MH across the leg or forearm.52, 53 In contrast, in a study of poorly controlled diabetic patients there was a substantially greater excretion of urinary 3-MH as compared with healthy volunteers. When the same diabetic patients were restudied after achieving satisfactory glycemic control, urinary 3-MH excretion was not different from that of healthy volunteers.54 This suggests that insulin deficiency results in increased muscle (we cannot differentiate between skeletal and smooth) protein breakdown and that replacement of insulin inhibits this breakdown. The available techniques to measure 3-MH have widely varying coefficients of variation, which makes these measurements insensitive to small differences.

114

THE EFFECT OF INSULIN ON PROTEIN METABOLISM

4.4 Whole body and regional protein turnover The effect of amino-acid availability Amino acids are the building blocks of proteins. The availability of these building blocks can determine whether protein synthesis can take place. Based on the km value of amino-acyl tRNA ligase it was argued that normal physiological changes in free amino acids have little effect on protein synthesis. However, recent studies have clearly demonstrated that amino acids by themselves enhance translational efficiency of gene transcripts.55, 56 Amino acids can be provided by reuse of amino acids provided by protein breakdown or they can be provided in the form of a meal or infusion. Amino-acid availability is of great importance when considering insulin’s effect on protein turnover, because amino-acid availability has been shown to be a major factor controlling muscle protein synthesis.57 – 59 Systemic or regional infusion of insulin has been shown to reduce blood concentrations of amino acids (hypoaminoacidemia).60, 48, 61, 62 A reduced rate of protein breakdown by insulin is the likely cause of this insulin-induced hypoamino acidaemia. Another potential site of the insulin effect is on transmembrane transport of amino acids. Transmembrane transport of neutral amino acids in skeletal muscle is mediated by at least four different systems (A, ASC, L and Nm ). Regional studies of forearm skeletal muscle using methylaminoisobutyric acid (MeAIB), a non-metabolizable amino-acid analogue specific for system A amino-acid transport, showed that physiologic hyperinsulinaemia stimulates the activity of system A amino-acid transport.63 This effect may play a role in determining the response of muscle amino-acid transport and protein metabolism in response to insulin. When trying to reconcile the results of whole body and regional studies in humans, it is important to note whether blood amino-acid concentrations were monitored and/or clamped during the study. When discussing results below, we shall note this.

Amino-acid tracer techniques Use of a labelled amino-acid tracer allows simultaneous determination of protein synthesis and breakdown rates at the whole body level and across tissue beds. Quantifying incorporation of the tracer into a specific protein or protein fraction or mixed proteins can yield the synthesis rate. Measuring the dilution of the tracer (provided it is a labelled essential amino acid) in the free tracee (amino-acid) pool in the steady state is extensively used for calculation of protein breakdown rates. During a steady state condition the rate of appearance of an essential amino acid such as leucine is the same as its disappearance rate. Therefore, in a fasted state, rate of appearance is equivalent to protein breakdown because essential amino acids only appear from protein breakdown, and rate of disappearance (sum of catabolism and incorporation into protein) can be estimated. Once the catabolic rate (e.g. leucine oxidation, phenylalanine

WHOLE BODY AND REGIONAL PROTEIN TURNOVER

115

hydroxylation to tyrosine etc.) and flux (appearance or disappearance rate) are measured, rate of incorporation of amino acid into protein (protein synthesis) can be calculated by subtracting the catabolic rate of the amino acid from its flux7 (Figure 4.3). In addition, from tracer and tracee measurements in artery and vein (e.g. femoral vein for leg or hepatic vein for splanchnic bed) as well as blood flow measurements (usually based on indicator dye dilution) the kinetics of protein (breakdown and synthesis) and net balances can be estimated in the respective tissue beds.49 In addition, serial needle biopsy of skeletal muscle and infusion of an isotopic tracer and measurements of isotopic abundance of the tracer in muscle protein or proteins will allow the estimation of fractional synthesis rates of mixed proteins or specific proteins.64 Similar approaches can be applied to measure fractional synthesis rates of circulating plasma proteins.65, 66 The tracer technique, therefore, can be used to determine whole body, regional and specific protein (such as myosin heavy chain) synthesis rates. In most cases, if the appropriate samples are taken (including blood, breath samples and tissue biopsies), a single experiment can determine all of these parameters. Two tracer methods are widely used for determination of tissue protein synthesis rates in humans – flooding dose and continuous infusion.

The flooding dose technique With the flooding dose a large amount of unlabelled amino acid (tracee) is injected as a bolus along with the labelled amino acid (tracer).67 The goal of infusing this large dose is to quickly achieve an equilibrium of tracer concentration between the plasma and the intracellular ‘precursor pool’. The obligatory ‘precursor pool’ is the amino acid acylated to its transfer RNA (amino-acyl tRNA). This is the step just prior to incorporation of the amino acid into a protein. To accurately calculate synthesis rates based on extracellular tracer enrichment, the extracellular tracer enrichment and intracellular ‘precursor pool’ enrichment must be in equilibrium. The primary advantage of this technique is that protein synthesis rates can be determined in a short period of time (10–30 minutes). Since a large amount of tracer is infused, it will make up a greater percentage of the amino acids incorporated into protein. This is particularly useful in studies of acute interventions such as short term infusion of a compound. The main disadvantage of this technique is that a number of assumptions need to be made. First, the large bolus of amino acid must be assumed to have no effect on protein dynamics. Second, in order for rates of synthesis and breakdown to be calculated, one must assume that enrichment is at steady state during the study period, which may not be the case during a declining phase of both tracer and tracee. These assumptions can be incorrect if certain requirements of the flooding dose condition are not met, particularly if the concentration of

116

THE EFFECT OF INSULIN ON PROTEIN METABOLISM

the ‘flooding dose’ is too low or the study period is too long. Either of these can cause non-equilibrium conditions in tracer enrichment between extracellular and intracellular compartments. The tracer in this approach is not truly in the ‘tracer amount’ and the high concentration of ‘tracer’ may affect the protein synthesis measurements.68 The advantages and disadvantages of this technique have been described in detail elsewhere.69 – 74

The continuous infusion technique With the continuous infusion technique, a continuous lower level infusion of tracer is given. In order to reach a steady state more quickly, the continuous infusion is typically preceded by a priming bolus of tracer.75 The continuous infusion technique allows study over a long period of time (several hours). Hence, this technique is better suited to the study of proteins that have a slow rate of turnover. Most skeletal muscle proteins fall into this category. On the other hand, this technique is not ideal for quick turn over proteins because of the amino-acid recycling that can occur over a prolonged time period. Another disadvantage is that in most cases a surrogate measure of the obligatory precursor (amino-acyl tRNA) has to be used for calculation of protein synthesis. This results in underestimation of protein synthesis calculation.76 For whole body measurements surrogate measures of intracellular pool, such as ketoisocaprioate in the case of leucine tracer, have been used with some strong theoretical reasons.77 However, this approach is not practical with every amino-acid tracer.

Amino-acid tracers In the past, radiolabelled amino acids were used as tracers. More recently, stable isotope amino-acid tracers have been more widely used, which has many theoretical advantages and is more acceptable for volunteers for studies and institutional ethical committees. The incorporation of the tracer into protein can then be quantified by mass spectrometry. The amount of incorporated tracer is a reflection of the amount of newly synthesized protein over the time of the infusion.7 The amino acid chosen for the tracer varies from study to study, and it is not uncommon to use more than one tracer within a single study.7 For whole body studies tracers such as L[1-13 C] leucine and labelled phenylalanine (e.g. L[15 N] phenylalanine L[2 H5 ] phenylalanine) are extensively used. For regional studies involving skeletal muscle bed phenylalanine has many advantages, which include its small intracellular pool and thus the shorter period needed to equilibrate with the free amino-acid pool. Within skeletal muscle and the other tissues of the forearm or leg, phenylalanine is not metabolized. Protein synthesis rates can be determined by measuring the rate of disappearance of phenylalanine. However, if one is studying the splanchnic bed (liver and intestine), it is important to account for the conversion of phenylalanine

WHOLE BODY AND REGIONAL PROTEIN TURNOVER

117

to tyrosine within the liver using an independent tracer of tyrosine.7 Recent studies have also demonstrated that phenylalanine is converted to tyrosine in the kidney78 besides in the liver. Therefore, for regional studies involving kidney as well, phenylalanine and tyrosine tracers have to be used to measure protein turnover. Leucine is an essential amino acid that composes 6–8 per cent of protein. Because leucine concentrations are high within most proteins, it provides large enrichment when used as a tracer. This is particularly useful when studying synthesis rates of proteins that have slow rates of turnover. Use of leucine in regional studies, however, can make calculations more complicated because it can be either directly incorporated into protein (non-oxidative metabolism) or reversibly transaminated to form ketoisocaproic acid (KIC). KIC can then be further oxidized to carbon dioxide and isovaleryl CoA (Figure 4.3) or reaminated back into leucine. If leucine is labelled at the carboxyl carbon (e.g. 13 C) and the amino group with 15 N, it is possible to quantify leucine transamination rates. Leucine tracers with both labels have been used to measure transamination rates at the whole body79 and regional levels.80, 49 In order to account for the metabolic products one must collect breath samples for measurement of label within expired carbon dioxide or 13 CO2 production across tissue beds in regional studies.80 Measurement of 13 C-KIC enrichment can be a useful surrogate of the precursor pool leucyl-tRNA enrichment. Measurement of this compound requires far less muscle tissue and labour than does direct measurement of leucyl tRNA. It has been demonstrated in human studies to be a good surrogate81 although muscle tissue fluid is closer to tRNA enrichment.81 For studies involving liver proteins (plasma proteins such as albumin, fibrinogen, APOB100 etc.) plasma [13 C] KIC is an excellent surrogate measure of liver leucyl-tRNA enrichment. For skeletal muscle, muscle tissue fluid leucine enrichment is a better indicator of leucyl tRNA. Amino-acid tracers can thus be used to study protein kinetics of the whole body, of a region, of a certain tissue or of specific proteins.

Insulin and protein turnover in type 1 diabetic patients using whole body leucine flux Type 1 diabetic patients are deficient in insulin, so perhaps the most dramatic effects of insulin can be observed in these subjects. One can study these patients in the insulin deficient state and compare these results to the insulin replete state. Using the whole body leucine flux technique, several groups have confirmed that insulin deprivation in type 1 diabetic patients results in increased protein breakdown as demonstrated by increased leucine flux, phenylalanine and tyrosine flux.82 – 85, 62, 49, 86 – 89 In the majority of studies, insulin infusion normalized leucine flux, providing strong evidence that insulin suppresses protein breakdown. Somewhat surprisingly, whole body protein synthesis also increased

118

THE EFFECT OF INSULIN ON PROTEIN METABOLISM

with insulin deprivation and was suppressed with insulin treatment. The magnitude of synthesis suppression is less than breakdown suppression. In whole body leucine flux studies that also included an amino-acid infusion to maintain levels, there was a further decrease in protein breakdown and leucine oxidation in response to insulin treatment.82, 90, 84 Results are mixed regarding whole body protein synthesis when amino acids were infused and leucine flux was measured. Some studies showed an increase in whole body protein synthesis (as measured by non-oxidative leucine flux)90, 84 and others did not.83 During insulin deprivation there is also a marked increase in amino-acid oxidation, which is largely due to a substantial increase in the transamination process in the case of leucine.7 Not all of the changes in type 1 diabetic patients during insulin deficiency are directly related to insulin deficiency per se. There are many secondary events that occur following insulin withdrawal in type 1 diabetic patients. Such secondary changes include increase in levels of circulating amino acids (especially branched chain amino acids), glucagon, non-esterified fatty acids and β hydroxybutyrate levels. Increased amino-acid levels (due to increased protein breakdown) contribute substantially to the large increase in leucine transamination and leucine oxidation. Increased amino acid levels also cause increased protein synthesis in splanchnic bed.59 Increased glucagon levels also cause increased oxidation of leucine, which has been shown in patients with type 1 diabetes.91 Beta-hydroxybutyrate has been shown to stimulate synthesis of muscle protein synthesis.7 This effect of β-hydroxybutyrate and the inhibitory effect of fatty acids on protein breakdown may limit the catabolic effect of insulin deficiency.

Regional protein turnover Within a local area – across the forearm, across the leg or across the splanchnic bed – protein turnover can be assessed by amino-acid balance and tracer measurements. Amino-acid balance and tracer enrichment are determined by infusing, systemically, a labelled amino-acid tracer to achieve a steady state in the plasma and precursor pools. The amount of tracer enrichment and aminoacid concentration present in the venous and arterial sides are then determined. Amino-acid balance is the arterio-venous difference in amino acid multiplied by blood flow. Rate of appearance (protein breakdown) and rate of disappearance (synthesis and catabolism) can be estimated by mathematical equations.92, 7 The estimation of catabolic rate and synthesis rates are possible using multiple amino-acid tracers. The details of the models used for these measurements are given elsewhere.93, 49, 7 Measurement of protein turnover in a region accounts for turnover in all of the tissues of that region. In the leg or forearm this would include skin, connective tissue, adipose tissue and skeletal muscle although skeletal muscle accounts for the major portion when deep veins such as femoral vein are used to sample. In the splanchnic bed, tissues of the abdomen including liver and intestine are the main contributors to protein turnover.

WHOLE BODY AND REGIONAL PROTEIN TURNOVER

119

Insulin and regional protein metabolism in type 1 diabetic patients and healthy controls The results of regional studies across the leg or forearm using either phenylalanine or leucine as tracers in type 1 diabetic patients are mixed. Some show a reduction in protein breakdown after insulin infusion83, 49, 94 while others show no effect.95 None of these studies showed any effect on protein synthesis. However, the relative fraction of muscle protein synthesis to whole body protein synthesis increases after insulin replacement.92 Results from the splanchnic bed are interesting. In the insulin deprived state, splanchnic bed protein synthesis exceeds breakdown49 (Figure 4.4). Figure 4.4 shows that insulin deprivation I(−) results in increased protein breakdown particularly in skeletal muscle (sk. muscle). I(−) also increases protein synthesis (only in the splanchnic bed) but to a lesser degree. Insulin treatment I(+) results in suppressed protein breakdown, particularly in skeletal muscle and protein synthesis (only in splanchnic bed) Insulin levels are the lowest in the fasting state between meals. It has been suggested that since there is a net breakdown in skeletal muscle protein during insulin deficient states muscle may serve as a reservoir of amino acids. Figure 4.5 shows that between meals, when insulin levels are low, there is a preservation of splanchnic bed protein synthesis while there is a net degradation of muscle protein. After a meal, when insulin levels are high, there is a net gain in muscle protein and a decline in splanchnic bed protein. The regulatory sites of insulin and amino acids are indicated in the figure. During the fasting state, expendable muscle proteins could be broken down in order to provide the necessary amino-acid supply to the splanchnic Breakdown

Synthesis

3.5 3

mmol/h

2.5 2

other splanchnic sk. muscle

1.5 1 0.5 0 I(−)

I(+)

I(−)

I(+)

Figure 4.4 Effect of insulin on protein breakdown and synthesis in type 1 diabetic patients

120

THE EFFECT OF INSULIN ON PROTEIN METABOLISM

Circulating proteins (a) PS PB AA efflux

AA efflux

Insulin

PB

Circulating proteins (b) PS PB

AA

PB

PS

AA uptake

AA efflux Insulin

PB

AA

PB

PS

Figure 4.5 Sites of protein accretion between and after meals – based on studies with insulin and AA infusion59

bed for synthesis of crucial proteins such as clotting factors. Studies performed in non-diabetic people demonstrated that protein synthesis in splanchnic bed is higher than protein breakdown in the fasted state.96 Muscle releases amino acids in the fasted state because muscle protein breakdown is higher than muscle protein synthesis. Therefore muscle is a provider of amino acids to the splanchnic bed to maintain synthesis of proteins. Recent studies have shown the kidney is a net producer of tyrosine and contributes to the systemic circulation.78 When insulin levels increase muscle protein breakdown decreases and the output of amino acids decreases. This occurs in association with a decrease in splanchnic protein synthesis. However, if amino acids are infused along with insulin, there is a further reduction in muscle protein breakdown and there is an increase in muscle protein synthesis.59 Amino acids have an independent effect on splanchnic protein synthesis and increase in splanchnic protein synthesis. While insulin is the major regulator of muscle protein turnover with minimal effect on splanchnic protein turnover, amino acids have major effects on both these two tissue beds. Based on these studies, it is proposed that reduced insulin levels during

WHOLE BODY AND REGIONAL PROTEIN TURNOVER

121

the fasted state result in an increased output of amino acids from muscle bed and these amino acids are vital for synthesis of essential proteins in the liver. Following a mixed meal the amino acids from meal enhance protein accretion in both splanchnic and muscle beds. Insulin plays a key facilitative role in all these processes. In type 1 diabetic patients insulin deficiency causes a substantial increase in muscle and splanchnic protein breakdown (Figure 4.4). While muscle protein synthesis is not significantly affected by short term insulin deficiency in type 1 diabetic patients, splanchnic protein synthesis increases. The net effect is that both protein breakdown and protein synthesis increase at the whole body level. However the greater increase in protein breakdown results in net protein catabolism. The increased splanchnic protein synthesis and prevention of decline in muscle protein synthesis during short term insulin deficiency is thought to be related to increased circulating amino acids, based on studies in non-diabetic people.59

Tissue-specific protein synthesis Biopsy of a specific tissue during an infusion or flooding dose of a tracer is particularly useful when one wishes to study a tissue with a slow rate of turnover such as skeletal muscle. A biopsy is taken at baseline and then at some point after an intervention. In these biopsy samples one can measure the synthesis rates of particular groups of proteins by determining the amount of tracer incorporated over the intervention time from a defined precursor pool. In skeletal muscle samples our laboratory typically determines the tracer incorporation into mixed muscle protein (a mixture of the proteins present in the muscle), into sarcoplasmic protein (protein present within the cytosol) and into myosin heavy chain (a key structural and contractile protein). In addition, mitochondria are isolated and the amount of tracer incorporated into mitochondrial proteins is determined. The purification of these fractions and measurement techniques is described elsewhere.97 Similarly, fractional synthesis rates of circulating proteins can be measured after purifying specific proteins.65, 98, 66, 99

Insulin and mixed muscle protein in type 1 diabetic patients Several groups have looked at the effect of insulin on the synthesis of mixed muscle protein in type 1 diabetic patients after insulin treatment. In none of these was there a change in the mixed muscle protein synthesis,82, 91, 85, 86 even with amino-acid infusion.82

Fractional synthesis rate of a specific protein If a specific protein can be purified from a biopsy specimen it is possible to determine the fractional synthesis rate of the protein.100, 97 In our laboratory

122

THE EFFECT OF INSULIN ON PROTEIN METABOLISM

we use SDS PAGE protein electrophoresis to purify myosin heavy chain from muscle myofibrillar protein fraction separated by ultracentrifugation.101 Mass spectrometry is used in measuring the isotopic abundance of a protein such as myosin heavy chain102 that has a very slow turnover rate. After protein or proteins are purified one has to hydrolyse the protein into amino acids and use gas chromatography/combustion/isotope ratio mass spectrometry to determine the change of isotopic enrichment between two biopsy periods. Knowing the precursor pool isotopic enrichment (amino-acyl tRNA or its surrogate measures), fractional synthesis rates of specific protein or protein subfractions (e.g. mitochondrial proteins or sarcoplasmic proteins) can be measured.7

Insulin’s effect on specific proteins When the synthesis rate of myosin heavy chain was studied in type 1 diabetic patients before and following insulin treatment, there was no change observed.91 Insulin, however, has a specific effect on muscle mitochondrial protein synthesis. When insulin was infused at high physiological levels while replacing glucose and amino acids, muscle mitochondrial protein synthesis was stimulated (Figure 4.3).10 This increase in muscle mitochondrial protein synthesis occurred in association with an increase in muscle mitochondrial enzyme activity and ATP production. This important finding demonstrated a pivotal role of insulin and amino acids in the regulation of mitochondrial oxidative phosphorylation in skeletal muscle. Certain liver proteins appear to be responsive to changes in insulin concentration. De Feo and colleges65, 98 have studied the fractional synthesis rates of albumin, antithrombin III, fibrinogen and apoB-100 in healthy volunteers and in type 1 diabetic patients. In type 1 diabetic patients deprived of insulin, the synthesis of albumin was reduced but the synthesis of fibrinogen was increased.98 The authors proposed that the increase in fibrinogen represented an acute phase response, because in healthy subjects insulin infusion stimulated the synthesis of albumin but reduced the synthesis of fibrinogen and antithrombin III.

Effect of insulin in healthy volunteers Some of the insulin effect on protein metabolism has already been discussed in comparison with type 1 diabetes. Healthy volunteers are typically studied in the post-absorptive (fasting) state. Baseline insulin levels are low in this state and calculations of amino-acid flux are simplified because there is no dilution of tracer due to dietary intake of amino acid. With only a few exceptions,52, 103 – 105 there seems to be good agreement that insulin inhibits protein breakdown in normal subjects. Using a variety of tracers, many regional and whole body studies have reached the same conclusion.82, 106 – 112, 53, 113 However, there is not good agreement regarding the effect of insulin on protein synthesis in healthy volunteers – about half of the studies show no effect of insulin on protein

WHOLE BODY AND REGIONAL PROTEIN TURNOVER

123

synthesis.52, 82, 106, 108, 110, 112, 114, 96, 104 Several others show an increase in regional or whole body synthesis with insulin.103, 109, 115, 105 These differences may be related to insulin dose, methodologies, duration of insulin infusion and levels of circulating amino acids and other substrates. On the whole, there is quite convincing data to suggest that insulin can inhibit protein breakdown in healthy volunteers. If protein synthesis rates are unchanged or increased, the overall effect of insulin would be a whole body accretion of protein. Based on recent studies it is clear that plasma amino acids have a critical role in stimulating muscle protein synthesis and insulin alone reduces circulating amino acids in vivo, which may explain some of the discrepancies between in vivo and in vitro studies. Insulin also has a specific effect on synthesis of certain muscle protein fractions such as mitochondrial proteins and plasma proteins such as albumin.

Effect of insulin in type 2 diabetics patients Type 2 diabetic patients are insulin resistant and as a result, at least early in the course of the disease, they have chronically high insulin levels. The effect of this insulin resistance to glucose metabolism and hyperinsulinaemia on protein turnover is not well defined. Oral hypoglycemic agents (glyburide) have been shown to reduce endogenous glucose production in type 2 diabetic patients but have no effect on protein turnover.116 When type 2 diabetic patients have been infused with relatively high dose insulin over a short three hour clamp period, there is a suppression of protein breakdown similar to that seen in matched control subjects.107, 117 However, intensive insulin treatment had no effect on protein turnover in comparison with less stringent glycemic control with insulin.118 Interestingly, after a longer term infusion (overnight) after 10 days of subcutaneous insulin there appears to be a resistance to the insulin effect on protein breakdown. Under these conditions, insulin does not significantly suppress protein breakdown.119 This resistance to the effect of insulin to suppress protein breakdown is important. Since type 2 diabetic patients have chronically high insulin levels, normal tissue turnover could not take place if protein breakdown continued to be suppressed. A resistance to the action of insulin on glucose disposal is not necessarily coupled with resistance to insulin’s suppression of protein breakdown. This allows for normal protein turnover to take place even in the face of high insulin levels. At this point, it is unclear whether the intracellular mechanisms behind the resistance to insulin’s effect on glucose disposal and protein metabolism are similar or whether they are independent. As in control subjects, the fractional synthesis rates of mixed muscle protein, myosin heavy chain and mitochondrial protein were unchanged in diabetic patients infused with insulin.120 It is interesting that intensive insulin treatment in type 2 diabetic patients did not stimulate mitochondrial protein synthesis, which is consistent with the recent report that increasing insulin levels to the

124

THE EFFECT OF INSULIN ON PROTEIN METABOLISM

same extent failed to increase muscle mitochondrial ATP production in type 2 diabetic patients, in contrast with non-diabetic control subjects.10

Summary Considering all of the data, including those from intracellular studies, in situ studies and human subject studies, there is good evidence that insulin can regulate protein turnover in many ways. Insulin can (1) selectively enhance the transcription of certain mRNAs through insulin response elements in promoters, (2) selectively enhance the stability of certain RNAs, (3) enhance translation initiation and elongation and (4) enhance ribosomal abundance. Insulin can also selectively inhibit the degradation of some proteins through the ubiquitin–proteosome system. Studies in the whole organism help us to understand the relative influence of changes in protein synthesis and breakdown in the overall protein balance. They also help us understand the differential effects within certain tissue beds. Studies in type 1 diabetic patients and non-diabetic people indicate that insulin has differential effects on skeletal muscle protein turnover from those on the splanchnic bed protein turnover. This is particularly important when considering the fluctuation in insulin levels in relation to meals. The effects observed in type 1 diabetic patients are more dramatic than those in healthy controls because they can be studied in the insulin deficient state. It may be that this same paradigm is true in healthy subjects but that it is more difficult to detect the differences. Insulin stimulates muscle mitochondrial protein synthesis and mitochondrial biogenesis when amino acids are provided. Insulin-induced fall in circulating amino acids blunts the stimulatory effect of insulin on synthesis of muscle proteins. Insulin’s primary effect on muscle appears to be an inhibition of protein breakdown. While amino acids have a key role in modulating insulin effect on muscle protein synthesis, amino acids are the main regulators of splanchnic protein synthesis. Insulin, however, has highly specific effects on certain liver proteins and muscle mitochondrial proteins and more research in the area is warranted. In type 2 diabetic patients, there is a resistance to insulin’s effect on glucose disposal, and there is also a resistance to insulin-induced suppression of protein breakdown. The mechanism is unclear; however, this resistance is important in maintenance of normal protein turnover in type 2 diabetic patients. Insulin has no stimulatory effect on muscle mito-protein synthesis in type 2 diabetic patients. The question of how insulin might regulate protein turnover, and hence tissue mass, is complicated. Currently, the limiting factor in more thoroughly understanding this process is one of technology. We have been limited to studying, for the most part, groups of proteins. For example, the measurement of mixed muscle protein or mitochondrial protein fractional synthesis rates may be the summation of results from hundreds of different proteins. The currently available

REFERENCES

125

techniques make it difficult to analyse the effect of insulin on a large number of specific proteins. As techniques become more refined for the purification and profiling of many proteins simultaneously (proteomics), we will gain a detailed understanding of the regulation of the entire network of proteins within specific cell types in response to insulin.

Acknowledgements This work was supported by NIH grants RO1 DK41973 and MO1RR00585, the David Murdock-Dole Professorship (K. S. Nair) and the Mayo Clinic Clinician Investigator Training Program (L. J. S. Greenlund).

References 1. Geyelin, H. R. and Du Bois, E. F. (1916) A case of diabetes of maximum severity with marked improvement: a study of blood, urine and respiratory metabolism. J Am Med Assoc 66 (20), 1532–1534. 2. Reed, J. A. (1954) Arataeus, the Cappadocian: history enlightens the present. Diabetes 3, 419–421. 3. Frank, L. L. (1957) Diabetes mellitus in the texts of old Hindu medicine (Charaka, Susruta, Vagbhata). Am J Gastroenterol 27, 76–95. 4. Osler, W., ed. (1895) Practice of Medicine. New York: Appleton. 5. Atchley, D. W., Loeb, R. F., Richards, D. W., Jr., Benedict, E. M. and Driscoll, M. E. (1933) On diabetic acidosis – a detailed study of electrolyte balances following the withdrawal and reestablishment of insulin therapy. J Clin Invest 12, 297–326. 6. Nair, K. S., Halliday, D., and Griggs, R. C. (1988) Leucine incorporation into mixed skeletal muscle protein in humans. Am J Physiol 254 (Endo Metab 17), E208–E213. 7. Nair, K. S. (1995) Assessment of protein metabolism in diabetes. In: Draznin, B. and Rizza, R. A., eds. Clinical Research in Diabetes and Obesity, Part I: Methods, Assessment, and Metabolic Regulation. Totowa, NJ: Humana, 137–170. 8. Giffin, B. F., Drake, R. L., Morris, R. E. and Cardell, R. R. (1993) Hepatic lobular patterns of phosphoenolpyruvate carboxykinase, glycogen synthase, and glycogen. J Histochem Cytochem 41, 1849–1862. 9. Van Remmen, H. and Ward, W. F. (1997) Effect of age on the activity of phosphoenolpyruvate carboxykinase in the kidney following fasting and refeeding. Mech Ageing Dev 97, 237–248. 10. Stump, C. S., Short, K. R., Bigelow, M. L., Schimke, J. C. and Nair, K. S. (2003) Effect of insulin on human skeletal muscle mitochondrial ATP production, protein synthesis, and mRNA transcripts. Proc Natl Acad Sci USA 100, 7996–8001. 11. Jefferson, L. S. and Kimball, S. R. (1989) Insulin Regulation of Protein Synthesis Insulin Action. New York: Liss, 133–142. 12. O’Brien, R. M. and Granner, D. K. (1996) Regulation of gene expression by insulin. Physiol Rev 76, 1109–1161. 13. Christ, B. and Nath, A. (1993) The glucagons–insulin antagonism in the regulation of cystosolic protein binding to the 3
end of phosphoenolpyruvate carboxykinase mRNA in cultured rat hepatocytes. Possible involvement in the stabilization of the mRNA. Eur J Biochem 215, 541–547.

126

THE EFFECT OF INSULIN ON PROTEIN METABOLISM

14. Lawrence, J. C., Jr., Fadden, P. and Haystead, T. A. (1997) PHAS proteins as mediators of the actions of insulin, growth factors, and cAMP on protein synthesis and cell proliferation. Adv Enzyme Regulation 37, 239–267. 15. Kimball, S. R., Jefferson, L. S., Fadden, P., Haystead, T. A. J., and Lawrence, J. C., Jr. (1996) Insulin and diabetes cause reciprocal changes in the association of eIF-4E and PHAS-I in rat skeletal muscle. Am J Physiol 270, C705–C709. 16. Kimball, S. R., Juransinski, C. V., Lawrence, J. C., Jr., and Jefferson, L. S. (1997) Insulin stimulates protein synthesis in skeletal muscle by enhancing the association of eIF-4E and eIF-4G. Am J Physiol 272, C754–C759. 17. Welsh, G. I. and Proud, C. G. (1993) Evidence for a role for protein kinase C in the stimulation of protein synthesis by insulin in Swiss 3T3 fibroblasts. FEBS Lett 316, 241–246. 18. Proud, C. G. (1994) Peptide-chain elongation in eukaryotes. Mol Biol Rep 19, 161–170. 19. Redpath, N. T., Price, N. T., Severinov, K. V. and Proud, C. G. (1993) Regulation of elongation factor-2 by multisite phosphorylation. Eur J Biochem 213, 689–699. 20. Proud, C. G. and Denton, R. M. (1997) Molecular mechanisms for the control of translation by insulin. Biochem J 328 (Pt 2), 329–341. 21. Millward, D. J., Garlick, P. J., James, W. P. T., Nnanyelugo, D. O. and Ryatt, J. S. (1973) Relationship between protein synthesis and RNA content in skeletal muscle. Nature 241, 204–205. 22. DePhilip, R. M., Chadwick, D. E., Ignotz, R. A., Lynch, W. E. and Lieberman, I. (1979) Rapid stimulation by insulin of ribosome synthesis in cultured chick embryo fibroblasts. Biochemistry 18, 4812–4817. 23. Hammond, M. L. and Bowman, L. H. (1988) Insulin stimulates the translation of ribosomal proteins and the transcription of rDNA in mouse myoblasts. J Biol Chem 263, 17 785–17 791. 24. Hannan, K. M., Rothblum, L. I. and Jefferson, L. S. (1998) Regulation of ribosomal DNA transcription by insulin. Am J Physiol 275, C130–C138. 25. Antonetti, D. A., Kimball, S. R. and Horetsky, R. L. (1993) Regulation of rDNA transcription by insulin in primary cultures of rat hepatocytes. J Biol Chem 268, 25 277–25 284. 26. Ashford, A. J. and Pain, V. M. (1986) Effect of diabetes on the rates of synthesis and degradation of ribosomes in rat muscle and liver in vivo. J Biol Chem 261, 4059–4065. 27. Kimball, S. R., Vary, T. C. and Jefferson, L. S. (1994) Regulation of protein synthesis by insulin. Annu Rev Physiol 56, 321–348. 28. Goldberg, A. L. and St. John, A. C. (1976) Intracellular protein degradation in mammalian and bacterial cells: Part 2. In: Snell, E. E., Boyer, P. D., Meister, A. and Richardson, C. C., eds. Annual Review of Biochemistry, Vol. 45. Palo Alto, CA: Annual Reviews, 747–803. 29. Mitch, M. E. and Goldberg, A. L. (1996) Mechanism of muscle wasting. The role of ubiquitin–proteosome pathway. N Engl J Med 335, 1897–1905. 30. Pepato, M. T., Migliorini, R. H., Goldberg, A. L. and Kettelhut, I. C. (1996) Role of different proteolytic pathways in degradation of muscle protein from streptozotocindiabetic rats. Am J Physiol 271, E340–E347. 31. Price, S. R., Bailey, J. L., Wang, X., England, B. K., Ding, X., Phillips, L. S. and Mitch, W. E. (1996) Muscle wasting in insulinopenic rats results from activation of the ATP-dependent, ubiquitin–proteasome proteolytic pathway by a mechanism including gene transcription. J Clin Invest 98, 1703–1708. 32. Mitch, W. E., Medina, R., Grieber, S., May, R. C., England, B. K., Price, S. R., Bailey, J. L. and Goldberg, A. L. (1994) Metabolic acidosis stimulates muscle protein

REFERENCES

33.

34. 35.

36.

37. 38. 39.

40.

41. 42.

43.

44.

45.

46.

47. 48. 49.

127

degradation by activating the adenosine triphosphate-dependent pathway involving ubiquitin and proteasomes. J Clin Invest 93, 2127–2133. Kimball, S. R., Horetsky, R. L. and Jefferson, L. S. (1998) Signal transduction pathways involved in the regulation of protein synthesis by insulin in L6 myoblasts. Am J Physiol 274, C221–C228. Southorn, B. G. and Palmer, R. M. (1990) Inhibitors of phospholipase A2 block the stimulation of protein synthesis by insulin in L6 myoblasts. Biochem J 270, 737–739. Somwar, R., Kim, D. Y., Sweeney, G., Huang, C., Niu, W., Lador, C., Ramlal, T. and Klip, A. (2001) GLUT4 translocation precedes the stimulation of glucose uptake by insulin in muscle cells: potential activation of GLUT4 via p38 mitogen-activated protein kinase. Biochem J 359, 639–649. Tsakiridis, T., Taha, C., Grinstein, S. and Klip, A. (1996) Insulin activates a p21activated kinase in muscle cells via phosphatidylinositol 3-kinase. J Biol Chem 271, 19 664–19 667. Pin, C. L. and Merrifield, P. A. (1997) Developmental potential of rat L6 myoblasts in vivo following injection into regenerating muscles. Dev Biol 188, 147–166. Fulks, R. M., Li, J. B., and Goldberg, A. L. (1975) Effects of insulin, glucose, and amino acids on protein turnover in rat diaphragm. J Biol Chem 250, 290–298. Jefferson, L. S., Koehler, J. O. and Morgan, H. E. (1972) Effect of insulin on protein synthesis in skeletal muscle of an isolated perfused preparation of rat hemicorpus. Proc Natl Acad Sci USA 69, 816–820. Jefferson, L. S., Rannels, D. E., Munger, B. L. and Morgan, H. E. (1974) Insulin in the regulation of protein turnover in heart and skeletal muscle. Fed Proc 33, 1098– 1104. Baillie, A. G. S. and Garlick, P. J. (1992) Attenuated responses of muscle protein synthesis to fasting and insulin in adult female rats. Am J Physiol 262, E1–E5. Davis, T. A., Nguyen, H. V., Suryawan, A., Bush, J. A., Jefferson, L. S. and Kimball, S. R. (2000) Developmental changes in the feeding-induced stimulation of translation initiation in muscle of neonatal pigs. Am J Physiol Endocrinol Metab 279, E1226–E1234. Kimball, S. R., Farrell, P. A., Nguyen, H. V., Jefferson, L. S. and Davis, T. A. (2002) Developmental decline in components of signal transduction pathways regulating protein synthesis in pig muscle. Am J Physiol Endocrinol Metab 282, E585–E592. Wray-Cahen, D., Nguyen, H. V., Burrin, D. G., Beckett, P. R., Fiorotto, M. L., Reeds, P. J., Wester, T. J. and Davis, T. A. (1998) Response of skeletal muscle protein synthesis to insulin in suckling pigs decreases with development. Am J Physiol 275, E602–E609. Boirie, Y., Short, K. R., Ahlman, B., Charlton, M. and Nair, K. S. (2001) Tissuespecific regulation of mitochondrial and cytoplasmic protein synthesis rates by insulin. Diabetes 50, 2652–2658. Ahlman, B., Charlton, M., Fu, A., Berg, C., O’Brien, P. C. and Nair, K. S. (2001) Insulin’s effect on synthesis rates of liver proteins: a swine model comparing various precursors of protein synthesis. Diabetes 50, 947–954. Albright, R. A. and Nair, K. S. (1999) Methods for Investigation of Protein and Amino Acid Metabolism in Diabetes Mellitus. Boca Raton, FL: CRC Press. Felig, P., Wahren, J., Sherwin, R. and Paliologos, G. (1977) Amino acid and protein metabolism in diabetes mellitus. Arch Intern Med 137, 507–513. Nair, K. S., Ford, G. C., Ekberg, K., Fernqvist-Forbes, E. and Wahren, J. (1995) Protein dynamics in whole body and in splachnic and leg tissues in type I diabetic patients. J Clin Invest 95, 2926–2937.

128

THE EFFECT OF INSULIN ON PROTEIN METABOLISM

50. Sokhey, S. S. and Allan, F. N. (1924) The relationship of phosphates to carbohydrate metabolism. I, Time relationship of the changes in phosphate excretion caused by insulin and sugar. Biochem J 18, 1170–1184. 51. Walsh, C. H., Soler, N. G., James, H., Harvey, T. C., Thomas, B. J., Fremlin, J. H., Fitzgerald, M. G. and Malins, J. M. (1976) Studies in whole body potassium and whole body nitrogen in newly diagnosed diabetics. Quart J Med 45, 295–301. 52. Arfvidsson, B., Zachrisson, H., Moller-Loswick, A. C., Hyltander, A., Sandstrom, R. and Lundholm, K. (1991) Effect of systemic hyperinsulinemia on amino acid flux across human legs in postabsorptive state. Am J Physiol 260, E46–E52. 53. Moller-Loswick, A. C., Zachrisson, H., Hyltander, A., Korner, U., Matthews, D. E. and Lundholm, K. (1994) Insulin selectively attenuates breakdown of nonmyofibrillary proteins in peripheral tissues of normal men. Am J Physiol Endocrinol Metab 266, E645–E652. 54. Marchesini, G., Forlani, G., Zoli, M., Vannini, P. and Pisi, E. (1982) Muscle protein breakdown in uncontrolled diabetes as assessed by urinary 3-methylhistidine excretion. Diabetologia 23, 456–458. 55. Davis, T. A., Burrin, D. G., Fiorotto, M. L., Reeds, P. J. and Jahoor, F. (1998) Roles of insulin and amino acids in the regulation of protein synthesis in the neonate. J Nutr 128, 347S–350S. 56. Shah, O. J., Antonetti, D. A., Kimball, S. R. and Jefferson, L. S. (1999) Leucine, glutamine, and tyrosine reciprocally modulate the translation initiation factors eIF4F and eIF2B in perfused rat liver. J Biol Chem 274, 36 168–36 175. 57. Biolo, G.,Gastaldelli, A., Zhang, X. -J. and Wolfe, R. R. (1994) Protein synthesis and breakdown in skin and muscle: a leg model of amino acid kinetics. Am J Physiol 267, E467–E474. 58. Biolo, G., Tipton, K. D., Klein, S. and Wolfe, R. R. (1997) An abundant supply of amino acids enhances the metabolic effect of exercise on muscle protein. Am J Physiol Endocrinol Metab 273, E122–E129. 59. Nygren, J. and Nair, K. S. (2003) Differential regulation of protein dynamics in splanchnic and skeletal muscle beds by insulin and amino acids in healthy human subjects. Diabetes 52, 1377–1385. 60. Luck, J. M., Morrison, G. and Wilbur, L. F. (1928) The effect of insulin on the amino acid content of blood. J Biol Chem 77, 151–156. 61. Fukagawa, N. K., Minaker, K. L., Rowe, J. W., Goodman, M. N., Matthews, D. E., Bier, D. M. and Young, V. R. (1985) Insulin-mediated reduction of whole body protein breakdown: dose–response effects on leucine metabolism in postabsorptive men. J Clin Invest 76, 2306–2311. 62. Nair, K. S., Ford, G. C., and Halliday, D. (1987) Effect of intravenous insulin treatment on in vivo whole body leucine kinetics and oxygen consumption in insulin-deprived type I diabetic patients. Metabolism 36 (5), 491–495. 63. Bonadonna, R. C., Saccomani, M. P., Cobelli, C. and DeFronzo, R. A. (1993) Effect of insulin on system A amino acid transport in human skeletal muscle. J Clin Invest 91, 514–521. 64. Rooyackers, O. E., Balagopal, P. and Nair, K. S. (1997) Measurement of synthesis rates of specific muscle proteins using needle biopsy samples. Muscle Nerve Suppl 5, S93–S96. 65. De Feo, P., Gan Gaisano, M. and Haymond, M. W. (1991) Differential effects of insulin deficiency on albumin and fibrinogen synthesis in humans. J Clin Invest 88, 833–840. 66. Fu, A., Morris, J. C., Ford, G. C. and Nair, K. S. (1996) Sequential purification of human apolipoprotein B-100, albumin, and fibrinogen by immunoaffinity chromatography for measurement of protein synthesis. Anal Biochem 247, 228–236.

REFERENCES

129

67. Garlick, P. J., McNurlan, M. A., and Preedy, V. R. (1980) A rapid and convenient technique for measuring the rate of protein synthesis in tissues by injection of [3H]phenylalanine. Biochem J 192, 719–723. 68. Caso, G., Ford, G. C., Nair, K. S., Vosswinkel, J. A., Garlick, P. J. and McNurlan, M.A. (2001) Increased concentration of tracee affects estimates of muscle protein synthesis. Am J Physiol Endocrinol Metab 280, E937–E946. 69. Chinkes, D. L., Rosenblatt, J. and Wolfe, R. R. (1993) Assessment of the mathematical issues involved in measuring the fractional synthesis rate of protein using the flood dose technique. Clin Sci 84, 177–183. 70. Davis, T. A. and Reeds, P. J. (2001) Of flux and flooding: the advantages and problems of different isotopic methods for quantifying protein turnover in vivo: II. Methods based on the incorporation of a tracer. Curr Opin Clin Nutr Metab Care 4, 51–56. 71. Garlick, P. J., Wernerman, J., McNurlan, M. A. and Heys, S. D. (1991) Organ-specific measurements of protein turnover in man. Proc Nutr Soc 50, 217–225. 72. Rennie, M. J., Smith, K. and Watt, P. W. (1994) Measurement of human tissue protein synthesis: an optimal approach. Am J Physiol 266, E298–E307. 73. Smith, K., Downie, S., Barua, J. M., Watt, P. W., Scrimgeour, C. M. and Rennie, M. J. (1994) Effect of a flooding dose of leucine in stimulating incorporation of constantly infused valine into albumin. Am J Physiol 266, E640–E644. 74. Smith, K., Reynolds, N., Downie, S., Patel, A. and Rennie, M. J. (1998) Effects of flooding amino acids on incorporation of labeled amino acids into human muscle protein. Am J Physiol 275, E73–E78. 75. Matthews, D. E., Motil, K. J., Rohrbaugh, D. K., Burke, J. F., Young, V. R. and Bier, D. M. (1980) Measurement of leucine metabolism in man from a primed, continuous infusion of L-[1-C-13]leucine. Am J Physiol 238, E473–E479. 76. Toffolo, G., Albright, R. A., Joyner, M. J., Dietz, N. M., Cobelli, C. and Nair, K. S. (2003) Model to assess muscle protein turnover: domain of validity using amino acyltRNA vs. surrogate measures of precursor pool. Am J Physiol Endocrinol Metab 285, E1142–E1149. 77. Schwenk, W. F., Beaufr`ere, B. and Haymond, M. W. (1985) Use of reciprocal pool specific activities to model leucine metabolism in humans. Am J Physiol 249, E646–E650. 78. Moller, N., Meek, S., Bigelow, M., Andrews, J. and Nair, K. S. (2000) The kidney is an important site for in vivo phenylalanine-to-tyrosine conversion in adult humans: a metabolic role of the kidney. Proc Natl Acad Sci USA 97, 1242–1246. 79. Matthews, D. E., Bier, D. M., Rennie, M. J., Edwards, R. H. T., Halliday, D., Millward, D. J. and Clugston, G. A. (1981) Regulation of leucine metabolism in man: a stable isotope study. Science 214, 1129–1131. 80. Cheng, K. N., Dworzak, F., Ford, G. C., Rennie, M. J. and Halliday, D. (1985) Direct determination of leucine metabolism and protein breakdown in humans using L-(113 15 C, N) leucine and forearm model. Eur J Clin Invest 15, 345–353. 81. Barazzoni, R., Meek, S. E., Ekberg, K., Wahren, J. and Nair, K. S. (1999) Arterial KIC as marker of liver and muscle intracellular leucine pools in healthy and type 1 diabetic humans. Am J Physiol Endocrinol Metab 277, E238–E244. 82. Bennet, W. M., Connacher, A. A., Smith, K., Jung, R. T., and Rennie, M. J. (1990) Inability to stimulate skeletal muscle or whole body protein synthesis in type I (insulindependent) diabetes patients by insulin-plus-glucose during amino acid infusion: studies of incorporation and turnover of tracer L-[1–13 C]leucine. Diabetologia 33, 43–51. 83. Bennet, W. M., Connacher, A. A., Jung, R. T., Stehle, P. and Rennie, M. J. (1991) Effects of insulin and amino acids on leg protein turnover in IDDM patients. Diabetes 40, 499–508.

130

THE EFFECT OF INSULIN ON PROTEIN METABOLISM

84. Luzi, L., Castellino, P., Simonson, D. C., Petrides, A. S. and DeFronzo, R. A. (1990) Leucine metabolism in IDDM. Role of insulin and substrate availability. Diabetes 39, 38–48. 85. Nair, K. S. (1984) Energy and Protein Metabolism in Diabetes and Obesity. Council of National Academic Awards. 1994. 86. Pacy, P. J., Nair, K. S., Ford, C. and Halliday, D. (1989) Failure of insulin infusion to stimulate fractional muscle protein synthesis in type I diabetic patients – anabolic effect of insulin and decreased proteolysis. Diabetes 38, 618–624. 87. Robert, J. J., Beaufr`ere, B., Koziet, J., Desjeux, J. F., Bier, D. M., Young, V. R. and Lestradet, H. (1985) Whole body de novo amino acid synthesis in type I (insulindependent) diabetes studied with stable isotope-labeled leucine, alanine, and glycine. Diabetes 34, 67–73. 88. Tessari, P., Nosadini, R., Trevisan, R., De Kreutzemberg, S. V., Inchiostro, S., Duner, E., Biolo, G., Marescotti, M. C., Tiengo, A. and Crepaldi, G. (1986) Defective suppression by insulin of leucine-carbon appearance and oxidation in type 1, insulindependent diabetes mellitus. J Clin Invest 77, 1797–1804. 89. Umpleby, A. M., Boroujerdi, M. A., Brown, P. M., Carson, E. R. and Sonksen, P. H. (1986) The effect of metabolic control on leucine metabolism in type 1 (insulindependent) diabetic patients. Diabetologia 29, 131–141. 90. Inchiostro, S., Biolo, G., Bruttomesso, D., Fongher, C., Sabadin, L., Carlini, M., Duner, E., Tiengo, A. and Tessari, P. (1992) Effects of insulin and amino acid infusion on leucine and phenylalanine kinetics in type 1 diabetes. Am J Physiol 262 (25), E203–E210. 91. Charlton, M. R., Balagopal, P. and Nair, K. S. (1997) Skeletal muscle myosin heavy chain synthesis in type 1 diabetes. Diabetes 46, 1336–1340. 92. Nair, K. S. (1997) Regional protein dynamics in type I diabetic patients. In: Tessari, P., Pittoni, G., Tiengo, A. and Soeters, P. B., eds. Amino Acids and Protein Metabolism in Health and Disease. London: Smith-Gordon, 133–139. 93. Barrett, E. J., Revkin, J. H., Young, L. H., Zaret, B. L., Jacob, R. and Gelfand, R. A. (1987) An isotopic method for measurement of muscle protein synthesis and degradation in vivo. Biochem J 245, 223–228. 94. Pacy, P. J., Bannister, P. A. and Halliday, D. (1991) Influence of insulin on leucine kinetics in the whole body and across the forearm in post-absorptive insulin dependent diabetic (type 1) patients. Diabetes Res 18, 155–162. 95. Tessari, P., Biolo, G., Inchiostro, S., Sacca, L., Nosadini, R., Boscarato, M. T., Trevisan, R., De Kreutzemberg, S. V. and Tiengo, A. (1990) Effects of insulin on whole body and forearm leucine and KIC metabolism in type 1 diabetes. Am J Physiol 259, E96–E103. 96. Meek, S. E., Persson, M., Ford, G. C., and Nair, K. S. (1998) Differential regulation of amino acid exchange and protein dynamics across splanchnic and skeletal muscle beds by insulin in healthy human subjects. Diabetes 47, 1824–1835. 97. Rooyackers, O. E., Adey, D. B., Ades, P. A. and Nair, K. S. (1996) Effect of age in vivo rates of mitochondrial protein synthesis in human skeletal muscle. Proc Natl Acad Sci USA 93, 15 364–15 369. 98. De Feo, P., Volpi, E., Lucidi, P., Cruciani, G., Reboldi, G., Siepi, D., Mannarino, E., Santeusanio, F., Brunetti, P., and Bolli, G. B. (1993) Physiological increments in plasma insulin concentrations have selective and different effects on synthesis of hepatic proteins in normal humans. Diabetes 42, 995–1002. 99. Fu, A. and Nair, K. S. (1998) Age effect on fibrinogen and albumin synthesis in humans. Am J Physiol 275, E1023–E1030.

REFERENCES

131

100. Balagopal, P., Nair, K. S., and Stirewalt, W. S. (1994) Isolation of myosin heavy chain from small skeletal muscle samples by preparative continuous elution gel electrophoresis: application to measurement of synthesis rate in humans and animal tissue. Anal Biochem 221, 72–77. 101. Balagopal, P., Ljungqvist, O. and Nair, K. S. (1997) Skeletal muscle myosin heavychain synthesis rate in healthy humans. Am J Physiol 272, E45–E50. 102. Balagopal, P., Ford, G. C., Ebenstein, D. B., Nadeau, D. A. and Nair, K. S. (1996) Mass spectrometric methods for determination of [13C]leucine enrichment in human muscle protein. Anal Biochem 239, 77–85. 103. Biolo, G., Fleming, R. Y. D. and Wolfe, R. R. (1995) Physiologic hyperinsulinemia stimulates protein synthesis and enhances transport of selected amino acids in human skeletal muscle. J Clin Invest 95, 811–819. 104. Tessari, P., Inchiostro, S., Biolo, G., Vincenti, E., Sabadin, L. and Vettore, M. (1991) Effects of acute systemic hyperinsulinemia on forearm muscle proteolysis in healthy man. J Clin Invest 88, 27–33. 105. Wolf, R. F., Heslin, M. J., Newman, E., Pearlstone, D. B., Gonenne, A. and Brennan, M. F. (1992) Growth hormone and insulin combine to improve whole-body and skeletal muscle protein kinetics. Surgery 112, 284–291. 106. Denne, S. C., Liechty, E. A., Liu, Y. M., Brechtel, G. and Baron, A. D. (1991) Proteolysis in skeletal muscle and whole body in response to euglycemic hyperinsulinemia in normal adults. Am J Physiol 261, E809–E814. 107. Denne, S. C., Brechtel, G., Johnson, A., Liechty, E. A., and Baron, A. D. (1995) Skeletal muscle proteolysis is reduced in noninsulin-dependent diabetes mellitus and is unaltered by euglycemic hyperinsulinemia or intensive insulin therapy. J Clin Endocrinol Metab 80, 2371–2377. 108. Fryburg, D. A., Barrett, E. J., Louard, R. J. and Gelfand, R. A. (1990) Effect of starvation on human muscle protein metabolism and its response to insulin. Am J Physiol 259 (22), E477–E482. 109. Fryburg, D. A., Jahn, L. A., Hill, S. A., Oliveras, D. M. and Barrett, E. J. (1995) Insulin and insulin-like growth factor-I enhance human skeletal muscle protein anabolism during hyperaminoacidemia by different mechanisms. J Clin Invest 96, 1722–1729. 110. Gelfand, R. A. and Barrett, E. J. (1987) Effect of physiologic hyperinsulinemia on skeletal muscle protein synthesis and breakdown in man. J Clin Invest 80, 1–6. 111. Heslin, M. J., Newman, E., Wolf, R. F., Pisters, P. W. T. and Brennan, M. F. (1992) Effect of hyperinsulinemia on whole body and skeletal muscle leucine carbon kinetics in humans. Am J Physiol 262 (25), E911–E918. 112. Louard, R. J., Fryburg, D. A., Gelfand, R. A., and Barrett, E. J. (1992) Insulin sensitivity of protein and glucose metabolism in human forearm skeletal muscle. J Clin Invest 90, 2348–2354. 113. Newman, E., Heslin, M. J., Wolf, R. F., Pisters, P. W. T. and Brennan, M. F. (1994) The effect of systemic hyperinsulinemia with concomitant amino acid infusion on skeletal muscle protein turnover in the human forearm. Metab Clin Exp 43, 70–78. 114. McNurlan, M. A., Essen, P., Thorell, A., Calder, A. G., Anderson, S. E., Ljungqvist, O., Sandgren, A., Grant, I., Tjader, I., Ballmer, P. E., Wernerman, J. and Garlick, P. J. (1994) Response of protein synthesis in human skeletal muscle to insulin: an investigation with L-[2 H5 ]phenylalanine. Am J Physiol 267, E102–E108. 115. Hillier, T. A., Fryburg, D. A., Jahn, L. A. and Barrett, E. J. (1998) Extreme hyperinsulinemia unmasks insulin’s effect to stimulate protein synthesis in the human forearm. Am J Physiol 274, E1067–E1074.

132

THE EFFECT OF INSULIN ON PROTEIN METABOLISM

116. Welle, S. L. and Nair, K. S. (1990) Failure of glyburide and insulin treatment to decrease leucine flux in obese type II diabetic patients. Int J Obesity 14, 701–710. 117. Luzi, L., Petrides, A. S., and DeFronzo, R. A. (1993) Different sensitivity of glucose and amino acid metabolism to insulin in NIDDM. Diabetes 42, 1868–1877. 118. Staten, M. A., Matthews, D. E. and Bier, D. M. (1986) Leucine metabolism in type 2 diabetes mellitus. Diabetes 35, 1249–1253. 119. Halvatsiotis, P., Short, K. R., Bigelow, M. L. and Nair, K. S. (2002) Synthesis rate of muscle proteins, muscle functions, and amino acid kinetics in type 2 diabetes. Diabetes 51, 2395–2404. 120. Halvatsiotis, P., Turk, D., Alzaid, A. A., Dinneen, S. F., Rizza, R. A. and Nair, K. S. (2002) Insulin effect on leucine kinetics in type 2 diabetes mellitus. Diab Nutr Metab 15, 136–142.

5 Genetically Modified Mouse Models of Insulin Resistance Gema Medina-Gomez, Christopher Lelliott and Antonio J. Vidal-Puig

5.1 Introduction Insulin resistance is a syndrome characterized by a diminished ability of insulin to perform its normal physiological functions. Insulin resistance is the main feature of type 2 diabetes and is the key factor in the development of the metabolic syndrome. Thus, it is very important to determine the mechanisms regulating insulin sensitivity. After initial attempts to characterize insulin signalling pathways in vitro it became evident that the system was too complex, and to establish any physiological correlates it was necessary to develop in vivo models. This complexity is derived from the fact that insulin not only regulates glucose homeostasis but also exerts effects on lipid and protein metabolism that may be affected in insulin-resistant states. Furthermore, it was clear that upon activation of the insulin receptor, specific yet divergent signals and signalling pathways were generated that could regulate multiple metabolic pathways and that defects at different locations in these pathways may lead to apparently paradoxical effects. A further degree of complexity resulted from tissue-specific peculiarities of the insulin signalling network that may confer different degrees of susceptibility to the defects leading to insulin resistant states. This may create heterogeneity in the insulin sensitivity in different tissues, which may ultimately affect the partitioning of energy between organs. Moreover, the possibility of cross talk between the insulin and other signalling networks (e.g. insulin-like growth factors, IGFs) added further complications to the mechanisms controlling energy homeostasis. Thus, it was important to have an in vivo system to Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

134

GENETICALLY MODIFIED MOUSE MODELS OF INSULIN RESISTANCE

explore how a complete organism reacted and adapted to states of insulin resistance. Genetically modified animal models have emerged as extremely valuable tools to assist in this task. In this chapter we review how the use of genetically modified mice has helped to elucidate the physiological role of insulin and the defects associated with insulin resistance in vivo.

5.2

Genetic modification as a tool to dissect the mechanisms leading to insulin resistance

Transgenesis and homologous recombination technologies offer powerful tools for the study of the molecular mechanism of disease in vivo. Using these technologies almost any genetic modification can be introduced into a given genome. For instance, mice can be engineered to overexpress specific genes in selected tissues constitutively (transgenic models), or at a particular stage within development (inducible models). Similarly, mice can also be engineered lacking a specific gene (knockout mice), either in the whole animal (global knockout), or in a specific tissue (tissue specific knockout), at a specific time. Genetic manipulation can be used to recreate human diseases in mice by introducing mutated human genes into the mouse genome (humanized knockin mice). These mice are extremely useful tools to test the beneficial effects of drugs and ensure that their effects in rodents may be more readily extrapolated to humans. Breeding strategies can concentrate in the same mouse several genetic modifications in a heterozygous state, recreating models close to polygenic forms of the disease. Thus it is clear that molecular biology technology allows the development of well defined genetic manipulations to answer very specific biological questions.

5.3 Candidate genes involved in the mechanisms of insulin resistance For a gene to be considered a candidate to mediate insulin resistance directly, it is required that (a) this gene encodes a protein known to be involved in the insulin signalling pathway, and/or (b) there is solid physiological evidence to support the view that this protein may interfere with the normal events of the insulin signalling cascade. The number of reasonable candidates is increasing in parallel with our understanding of the molecular mechanisms controlling insulin sensitivity. This initial candidate list focused on genes integrated in the insulin signalling network. More recently, genes related to lipid and cytokine metabolism have been demonstrated to interfere with insulin sensitivity. Rodents harbouring modifications in those genes provide crucial information about their relevance for insulin sensitivity, their role in specific tissues and how insulin resistance in a specific tissue affects whole organism energy homeostasis (Table 5.1).

135

CANDIDATE GENES INVOLVED IN INSULIN RESISTANCE

Table 5.1

Genetically modified mouse models of insulin resistance

Genetic modification IR −/− IR −/+ IRS1 −/−

IRS2 −/− IRS3 −/− IRS4 −/− IRS1 −/− IRS3 −/− PI3kinase animal models P85α and β − /− P85α and β + /− PDK1 −/− PDK1 +/− Akt1 −/−

Main phenotype Lethal 10% diabetic Insulin resistance No diabetes β-cell hyperplasia Growth retarded Insulin resistance β-cell hypoplasia Diabetes No diabetes No diabetes Lipoatrophic diabetes

Glut 4 −/− Glut 4 +/−

Lethal Hypoglycaemia Lethal Growth retarded Growth retarded No diabetes Insulin resistance Diabetes Late diabetes Late diabetes

tSNARE −/− FOXO1 haploinsuficiency FOXO1 transgenic PTP-1B −/− SHIP2 −/− JNK1

Impaired glucose tolerance Increased insulin sensitivity Increased insulin sensitivity Enhanced insulin/leptin sensitivity Increased insulin sensitivity/hypoglycemia Increased insulin sensitivity

Akt2 −/−

Tissue-specific knockout mice MIRKO

Reference 8, 9 11, 12

13

14 15 57 16 18, 17 18, 19 20 20

21 58, 59 60 24 61 25 22 62 26 27 28 30

Bat IRKO Muscle GLUT4 KO

Normal insulin sensitivity Obesity, dyslipidaemia Lean, insulin sensitive Insulin resistance, diabetes Glucose intolerance Obesity and insulin resistance Altered reproduction. Defective insulin secretion Obesity, insulin resistance

Other knockout mice TNFα (−/−) TNFα receptor (−/−) Adiponectin/ACRP30 (−/−) FABPs (−/−) PPARγ (−/−) PPARγ (+/−) SREBP1c (−/−) SREBP1c LPL

Increased insulin sensitivity Increased insulin sensitivity Increased insulin resistance Obesity/maintained insulin sensitivity Lethal Lean/increased insulin sensitivity Lethal 70% Transgenic lipodystrophic adipose tissue Transgenic muscle

65 66 38

FIRKO LIRKO BIRKO NIRKO

32 35 36 37 63 64

55 55 67 68 34, 33

136

GENETICALLY MODIFIED MOUSE MODELS OF INSULIN RESISTANCE

5.4 Insulin signalling network The insulin signalling network has been discussed in Chapter 1. Thus it is not the objective of this chapter to describe in detail all its different components. In summary, this network is composed of an insulin receptor1 that, when activated by insulin, phosphorylates and activates soluble intracellular adaptor molecules (e.g. IRS and Shc family). Once activated, these adaptors interact with downstream signal transduction molecules. Two main pathways emerge from the insulin receptor: (a) the mitogenic Grb2/Sos and the Ras-MAP kinase pathway and (b) the PI3kinase pathway, which exerts most of the metabolic actions of insulin. Figure 5.1 shows a representative scheme of insulin signalling pathways. Upon insulin binding to the insulin receptor there is a divergent cascade of coupled phosphorylation/dephosphorylation processes modulated by kinase and phosphatase enzymes. These signalling pathways elicit specific responses spanning not only metabolic pathways (e.g. PI3kinase) but also pathways controlling cell proliferation (e.g. MAP kinases). The cell-specific response to insulin is determined by the repertoire of substrates. Thus alteration in selected molecules may influence some tissues more specifically than others and may result in paradoxical effects.

I

Ras-GTP

P

P

SHIP

2

rb

G

S/

SO

MEK

Glut-4

c

Sh Raf-1

GLUCOSE TRANSPORT

IRS1,2,3,4 p85

MAPK

JKN

PKC Akt PKB

PI3K p90 rsk

p110

GskPTP-1B

PP-1G

PDK-1 p70S6 kinase

Glycogen synthase

Transcription factors (e.g. FOXO1) MITOGENESIS

GLYCOGENESIS

Figure 5.1 Insulin signalling pathways

PROTEIN SYNTHESIS

INSULIN SIGNALLING AND GLOBAL KNOCKOUTS

5.5

137

Factors leading to insulin resistance

Insulin resistance may arise from abnormalities in the molecules involved in the insulin signalling cascade. Alternatively, insulin resistance may also be caused by factors that, although they are not strictly part of the insulin network, are capable of interfering with or modifying some of these molecules. This is the type of insulin resistance typically associated with obesity. In this situation, cytokines such as tumour necrosis factor-alpha (TNFα) produce insulin resistance by inactivating molecules of the insulin signalling network through several mechanisms, including phosphorylation of key serine residues, downregulation of the insulin receptor (IR), defects of the IR tyrosine kinase activity and decreased activity of IRS1 and PI3 kinase.2, 3 TNFα also may promote insulin resistance through down-regulation of other molecules such as peroxisome proliferator-activated receptor gamma (PPARγ)4 or leptin. The search for insulin sensitivity modulators has identified adiponectin/ACRP30 and resistin as new potential candidate molecules to mediate insulin resistance.5 – 7 In fact, defects in ACRP30 and resistin have been identified as potential links between obesity and insulin resistance. It is unclear as yet whether the development of insulin resistance in the context of obesity is a specifically designed adaptive mechanism to counteract the excess of fuel, or the unexpected effect of lipotoxicity on a system that was primarily designed to survive conditions of fuel deprivation. Alternatively, it may be possible that under conditions of lipotoxicity mechanisms primarily designed for other purposes, such as apoptosis or host defence, are inappropriately activated.

5.6 Defining the function of the insulin cascade molecules through global knockouts The first approach usually performed to determine whether a specific gene is relevant for insulin signalling is probably the generation of a global knockout. An early conclusion of this type of study was, in the case of insulin receptor (IR) knockout mice, that the IR is required for survival outside the maternal uterus. Homozygous IR knockouts are born live, but die within the first week of life with marked signs of ketoacidosis.8, 9 However, heterozygous IR knockout are viable and around 10 per cent become diabetic.10 The second line of events in the insulin signalling transduction cascade involves a family of four types of insulin receptor substrate (IRS). Ablation of IRS1 (IRS1KO) results in small mice with skeletal muscle insulin resistance that was compensated by β-cell hyperplasia.11, 12 However, the pancreatic islets of the IRS1KO mice had defective insulin production and secretion, albeit enough to keep these mice euglycemic. Other interesting phenotypes of the IRS1KO mice were the development of hypertension due to defects in vascular relaxation, and hypertriglyceridaemia secondary to defective lipoprotein lipase activity in adipose tissue. Thus a global defect in IRS1 reproduces some of the metabolic

138

GENETICALLY MODIFIED MOUSE MODELS OF INSULIN RESISTANCE

syndrome features. The global knockout of IRS2 produced a strong phenotype with insulin resistance in liver and frank diabetes at a young age. Unlike IRS1KO mice, in this animal model defects in PDX, a β-cell transcription factor regulated by IRS2, prevented β-cell compensatory hyperplasia.13 This results in insufficient insulin secretion to compensate for the insulin resistance. The knockouts of IRS3 and IRS4 did not result in any phenotype that suggested that these substrates of the insulin receptor are involved in carbohydrate metabolism.14, 15 The third line in the insulin signalling cascade, regulating more especially carbohydrate metabolism, involves phosphoinositide 3 kinases (PI3kinase). This is a group of enzymes that phosphorylate inositol rings within membrane phospholipids, which then act as secondary message molecules. PI3kinases form dimers of regulatory and catalytic subunits. Several forms of the regulatory (p85α, p55α, p50α, p85β, p55γ) and catalytic subunits (p110α, β) exist. As indicated before, PI3kinase is a key element in the metabolic response to insulin, specifically modulating glucose transport, antilipolysis, fatty acid synthesis or glycogen synthesis. Complete ablation of all p85 regulatory subunits results in early death after birth.16, 17 However, heterozygous mice, with a decrease in the dosage of the regulatory subunits p85α, β55 and 50α, show increased insulin sensitivity, leading to hypoglycaemia.18, 19 It seems that ablation of regulatory subunits increases the availability of the catalytic subunits, indicating that the stoichiometry of p85 to p110 may be a key factor regulating signal transduction via PI3kinase. 3
-phosphorylated lipids generated by PI3 kinase serve as a membrane recruitment signal for the following kinase in the signalling pathway, PDK-1 (3
phosphoinositide-dependent protein kinase). The global knockout of PDK1 is lethal at embryonic day 9.5 due to multiple abnormalities. However hypomorphic PDK1 mice, expressing only 10 per cent of PDK1, are viable. These mice are markedly smaller (40–50 per cent) than their wild type littermates. Interestingly, their decrease in size is due to diminished cell volume, while cell number and proliferation are conserved.20 This animal model also provides evidence that the expression of PDK1 is required to normally activate PKB/Akt, S6K and RSK kinases. The next level of insulin signalling regulation after PDK1 is PKB/Akt. Three different isoforms of this enzyme exist but only Akt2 seems to mediate insulin sensitivity in skeletal muscle and liver.21 Indeed, genetic ablation of Akt2 produces insulin resistance in liver and skeletal muscle that results in a diabetic phenotype. Conversely, ablation of Akt1/PKBα does not result in insulin resistance or glucose intolerance, although these animals’ growth is severely compromised. Thus these animal models establish that Akt2 is the only essential isoform for the maintenance of normal glucose homeostasis. This cascade of kinases finally phosphorylates several transcription factors, modifying their transcriptional activity. The transcriptional effects of insulin involve positive and negative effects on gene expression. One of the most recently identified insulin-regulated transcription factors is the forkhead factor

MOUSE MODELS OF POLYGENIC DIABETES

139

Foxo1, a factor that represses gene transcription. Its phosphorylation by insulin results in nuclear exclusion that leads to de-repression of insulin-responsive genes. As expected, haplo-insufficient Foxo1 mice are more insulin sensitive, whereas transgenic expression of Foxo1 leads to insulin resistance. Thus these animal models clearly establish Foxo1 as one of the transcription factors mediating the effects of insulin on glucose metabolism.22, 23 The final effect of insulin facilitating glucose transport requires the insulinresponsive glucose transporter Glut 4. Decreased numbers of these transporters, as in the Glut 4 global heterozygous mice, induce not only glucose intolerance and insulin resistance but also hypertension. However, none of these changes results in frank diabetes.24 In fact, not even the homozygous Glut 4 knockout mouse develops diabetes early in life, which clearly suggests that compensatory mechanisms must occur. These animals are growth retarded and show diminished lifespan, probably related to dysfunctional cardiac hypertrophy. As they get older, around 50–60 per cent of the mice become diabetic. The process of insulin-mediated glucose transport requires a complex network of proteins that facilitates the transfer of Glut transporters from intracellular vesicles to the plasma membrane. Disruption of these molecules may potentially be a cause of insulin resistance as indicated by the genetic ablation of t-SNARE protein syntaxin 4, which produces impaired glucose tolerance and reduction in skeletal muscle glucose uptake in vivo and in vitro.25 Interestingly, the network of proteins supporting the transport of glucose has tissue specificities, which may ultimately result in energy partitioning differences. The activity of the insulin signalling cascade is modulated by some inhibitory signals such as the activity of protein phosphatases or serine phosphorylases of IRS. The relevance of these molecules as modulators of insulin sensitivity has been recently illustrated by knockout of protein-tyrosine-phosphatase-1B (PTP1B), which resulted in enhanced insulin and leptin action.26 Ablation of another phosphatase, SH2 domain-containing inositol 5-phosphatase (SHIP2), also led to a dramatic increase in insulin sensitivity, resulting in severe neonatal hypoglycaemia, decreased gluconeogenesis and perinatal death.27 Other potential insulin signalling negative modulators include PKCθ, a serine kinase potentially involved in lipotoxicity-associated insulin resistance, and c-Jun N terminal kinase (JNK), which phosphorylates serine residues and inactivates IRS1. Genetic ablation of JNK1 produced a lean phenotype and improvement in insulin signaling.28

5.7 Double heterozygous mice as models of polygenic forms of diabetes The most common forms of insulin resistance and diabetes are not the result of monogenic genetic defects. Indeed, it is likely that insulin-resistant diabetes results from several minor defects that, when found in the same individual and exposed to specific environmental factors, determine the development of

140

GENETICALLY MODIFIED MOUSE MODELS OF INSULIN RESISTANCE

diabetes. This concept has been fully validated by animal models involving double heterozygous genetic modifications. One example is the double heterozygous IR/IRS1 knockout mouse, which exhibits insulin resistance in muscle and liver with associated β-cell hyperplasia and evolves to diabetes at a specific age.29 Also, the double heterozygous IRS1/glucokinase shows that the combination of mild defects in insulin sensitivity and insulin secretion may give rise to frank diabetes. A similar strategy has been used to show that heterozygous PI3kinase regulatory proteins compensate for decreased levels of IRS1 in heterozygous mice, improving insulin sensitivity and preventing diabetes. All these animal models give support to the idea that combinations of minor defects in insulin signalling can synergize to produce diabetes.

5.8

Defining tissue and/or organ relevance for the maintenance of insulin sensitivity

Different organs may have a specific relevance for the maintenance of body energy homeostasis. Several animal models have provided important insights about the relative contribution of muscle, liver, fat or pancreatic β-cells to carbohydrate homeostasis. This type of experiment not only has academic interest; they also provide information about the organ to target and types of strategy that could be more successful in improving diabetes. Furthermore, since the repertoire of molecules and mechanisms involved in insulin signalling exhibits tissue specificities, these experiments also provide insights into the relevance of these molecules in specific tissues. Tissue-specific knockouts are invaluable tools to address these aspects of energy homeostasis in vivo. This type of genetic modification takes advantage of Cre–Lox or Flp recombinase systems, which can target specific genetic modifications to specific cell types. This type of strategy is not only useful to determine the role and relevance of a molecule in a specific tissue but also allows insights into the metabolic adaptive response of the whole organism to cope with the defect. This may potentially identify alternative metabolic pathways of therapeutic interest. A key area in the pathophysiology of diabetes is elucidating the relative importance of adipose tissue and skeletal muscle insulin resistance for the development of diabetes. Since skeletal muscle is the most important organ for glucose disposal, it was a relative surprise that the muscle-specific insulin receptor knockout mice (MIRKO)30 did not show alterations in glucose homeostasis, despite elevated triglycerides and fatty acids, and development of visceral obesity. This suggests that skeletal muscle insulin resistance may divert glucose flux to the adipose tissue, promoting the development of obesity. Not surprisingly, skeletal muscle storages of glycogen were decreased. Ablation of IR in the adipose tissue (FIRKO) produced a lean animal protected against obesity-related glucose intolerance, indicating that expansion of the adipose tissue is required to fully develop the metabolic abnormalities associated with

INTER-ORGAN COMMUNICATION AND INSULIN SENSIBILITY

141

insulin resistance.31 Of interest, the FIRKO mouse exhibits extended longevity.32 Mice with combined ablation of IRs in muscle and adipose tissue developed impaired glucose tolerance without diabetes. Another example illustrating the importance of the adipose tissue for insulin sensitivity came from transgenic overexpression of lipoprotein lipase in adipose tissue. These animals showed increased triglyceride deposition in adipose tissue that was associated with insulin resistance.33, 34 Another important organ involved in glucose homeostasis is the liver. Increased hepatic glucose production is considered an important factor leading to hyperglycaemia in diabetic patients. By specific targeting of the insulin receptor disruption to the liver, the LIRKO mouse fully supported this concept. The LIRKO mouse showed severe glucose intolerance and insulin resistance, suggesting that insulin effects on hepatic glucose output suppression may be more relevant than skeletal muscle uptake to maintain glucose homeostasis.35 Full development of type 2 diabetes requires a defect in insulin secretion. Thus it was important to determine whether the failure of the pancreatic β-cells may be another manifestation of insulin resistance specific to this type of cell. The BIRKO, a mouse with targeted disruption of the insulin receptor in the pancreatic β-cell, supports this hypothesis. These mice lose the acute insulin release response to glucose and progressively develop glucose intolerance.36 This insulin secretory defect seems to be due to decreased levels of glucokinase. Other animal models such as IRS1KO mice also support pancreatic β-cell insulin resistance as a cause of insulin secretory defects. Furthermore, IRS2KO mice illustrate how defects in insulin signalling may specifically affect pancreatic βcell proliferation. Thus all these animals point to a unified concept in which insulin secretory defects would be another manifestation of insulin resistance. The brain, and more specifically the hypothalamus, plays an important role in energy homeostasis. Hypothalamic neurons integrate nutritional/hormonal signals such as insulin, glucose, or leptin producing homeostatic responses involving the mechanisms controlling food intake and energy expenditure. Thus it was important to determine whether and how insulin may affect energy homeostasis through the brain. The first strategy was to target the insulin receptor in neurons, creating a neuronal-specific insulin receptor knockout mouse (NIRKO). This animal model has provided direct evidence that insulin controls energy homeostasis through its actions in the brain. NIRKO mice have increased food intake and develop obesity and insulin resistance.37 Disruption of the insulin receptor in the brain also affects reproduction through its effects on GnRH that result in altered spermatogenesis and ovarian follicle maturation. Thus insulin is a key mediator of the brain effects on energy disposal, fuel metabolism and reproduction. Obviously targeting the insulin receptor of every single neuron does not allow discrimination of which neuronal groups are involved in each of the responses mediated by insulin. Thus the creation of new Cre mouse models

142

GENETICALLY MODIFIED MOUSE MODELS OF INSULIN RESISTANCE

targeted to specific subsets of neurons using specific promoters will be necessary to delineate these effects.

5.9 Genetically modified mice to study modulators of insulin sensitivity Adipose tissue is a key modulator of insulin sensitivity in vivo. Figure 5.2 shows that the main function of the AT is to serve as a reservoir of energy. However, the AT is a key organ within the energy homeostasis system capable of providing timely and accurate information to the central nervous system about the energy reserves. To fulfill this purpose the AT produces and secretes hormones better known as adipokines (e.g. leptin, ACRP30, resistin etc.) that modulate insulin sensitivity in central and peripheral organs (e.g. skeletal muscle, liver, CNS). Furthermore, adipose tissue is now considered an active endocrine gland that synthesizes and secretes hormones and cytokines, some of which appear to be important modulators of systemic insulin sensitivity. One of them, tumour necrosis factor-alpha (TNFα), is a cytokine produced and secreted by adipose tissue that may play a key role in modulating insulin resistance associated with obesity. Indeed, TNFα is overexpressed in adipose tissue of obese humans as well as in animal models of obesity. Furthermore, TNFα exerts its effects through two specific receptors. Thus to determine whether the TNFα network is physiologically relevant for insulin sensitivity in vivo, obese animal models without TNFα and/or TNFα receptors have been generated. Studies have clearly White adipose tissue

Leptin

TNFα

Acrp30

FFAs

Resistin

−

+ Brain

AMPK

+

+

–

Liver

Muscle

Figure 5.2 Adipose tissue (AT) as an endocrine organ

LIPODYSTROPHY VERSUS OBESITY, THE INSULIN RESISTANCE PARADOX

143

demonstrated that ablation of TNFα and/or its receptor prevents the development of insulin resistance and that this is associated with decreased levels of fatty acids and improved insulin signalling in skeletal muscle and fat tissues.4 Adiponectin/ACRP30 is another fat-derived hormone, which exerts positive effects on insulin signalling. ACRP30 gene expression is decreased in obesity-associated insulin resistance, and interestingly drugs that increase insulin sensitivity restore its expression. Thus it was not surprising that the ACRP30 knockout mice seemed to develop insulin resistance when exposed to a high fat diet.38 These animals have been reported to have increased levels of fatty acids and TNFα in plasma and have defective PI3kinase insulin signalling in muscle. Interestingly, this phenotype was reverted by adenoviral-mediated gene complementation of ACRP30. Although these findings basically agreed with the expected phenotype, other laboratories using an independently generated mouse have not been able to replicate the findings in a different background.39 Thus further characterization is awaited to clarify the in vivo effects of ACRP30. When analysing the phenotype of all these animal models it becomes clear that in one way or another all of them develop dysregulation of fatty acid metabolism, leading to lipotoxicity. In fact, more and more evidence is accumulating to suggest that development of lipotoxicity may be a key pathogenic event for insulin resistance. Among the different molecules involved in fatty acid metabolism, the fatty acid binding proteins (FABPs) have emerged as important candidates to affect insulin sensitivity. FABPs are cytoplasmic proteins that bind to fatty acids and seem to act as reservoirs of fatty acids in the cell. Adipocyte-specific ablation of the fatty acid binding protein aP2 was associated with development of dietary obesity, but paradoxically these mice did not develop insulin resistance or diabetes.40 Furthermore, these animals failed to express TNFα. These results were unexpected since the increased availability of free fatty acids was supposed to induce insulin resistance. However, the compensatory upregulation of the fibroblast-expressed homologue of aP2 may suggest that the improvement in insulin sensitivity was the result of the increased fatty acid binding capacity of this homologue. As a whole, these results indicate that changes in FABPs may link fatty acid metabolism to expression of TNFα and insulin resistance.

5.10

Lipodystrophy versus obesity, the insulin resistance paradox

Insulin resistance and obesity are closely associated. However, it is less intuitively explained how lipodystrophy, a phenotype which may be considered as the opposite to obesity, may be also associated with insulin resistance. A closer look at both phenotypes shows that the similarities are striking, including dyslipidaemia, hypertension and accumulation of fat in liver, heart and β-cells, so what do obesity and lipodystrophy have in common? In both situations there is a limitation on the ability to deposit fat. In the case of morbid obesity the

144

GENETICALLY MODIFIED MOUSE MODELS OF INSULIN RESISTANCE

Impaired fat deposition

First scenario

Marked lipotoxicity

Compensatory attempts to increase fat oxidation

Insulin secretion failure

Fatty liver Insulin resistance

Insulin resistance

Metabolic syndrome

(a)

Expansion of adipose tissue. HYPERTROPHY

Second scenario

Variable degrees lipotoxicity

Insulin secretion failure

Compensatory attempts to increase fat oxidation

Fatty liver Insulin resistance Insulin resistance Metabolic syndrome

(b)

Figure 5.3

Inter-organ communication and fuel partitioning

adipose tissue storage may be limited by impossibility of further expansion both physically by lack of preadipocytes and by physiologically impaired uptake of substrates, while in lipodystrophy there is no adipose tissue to fill. In both cases, the fat accumulates ectopically (e.g. liver, muscle, pancreatic β-cell), promoting lipotoxicity that leads to insulin resistance and diabetes. Animal models have been crucial to establishing this concept.41 Figure 5.3 shows a representative

LIPODYSTROPHY VERSUS OBESITY, THE INSULIN RESISTANCE PARADOX

Expansion of adipose tissue. HYPERPLASTY

Third scenario

Protection against lipotoxicity

Insulin secretion conserved

145

Pattern of adipokines more favourable

No fatty liver No insulin resistance

Insulin sensitivity maintained

Obesity without metabolic syndrome

(c)

Fourth scenario Increased fatty acid uptake and oxidation

Muscle activity driven FA uptake + disposal

Decreased fat accumulation

(d)

NO insulin resistance

Figure 5.3

(continued )

scheme showing how selective defects in specific organs may affect energy homeostasis and fuel partitioning in other organs. Through five potential scenarios ((a)–(e)) it is hypothesized how organ-specific defects may be compensated depending on the type of defect and its site of origin. Tissue-specific genetic modification offers the unique opportunity of not only identifying the effect of a genetic modification in a specific tissue but also promoting compensatory

146

GENETICALLY MODIFIED MOUSE MODELS OF INSULIN RESISTANCE

Adipocyte impairment–driven muscle FA uptake + disposal

Fifth scenario

Fatty acid

Impaired fat deposition

(e)

Increased fatty acid oxidation

NO insulin resistance

Figure 5.3

(continued )

mechanisms of potential therapeutic use. Mice engineered to impair fat development have shown that a minimum amount of fat is required to maintain insulin sensitivity and that leptin, the hormone produced in adipose tissue, is key to maintain insulin sensitivity. Indeed, leptin administration42 or adipose tissue transplantation43 into these mice prevents the development of insulin resistance and diabetes. The insulin-sensitizing effects of leptin may be mediated by AMPK activation and fatty acid oxidation resulting in glucose transport stimulation. Lipodystrophic animal models have clearly demonstrated that defects in adipose tissue can induce insulin resistance in other tissues through a combination of gluco/lipotoxic-dependent and independent mechanisms (e.g. Glut 4 KO in adipose tissue is associated with insulin resistance in other tissues, which is not associated with gluco- or lipotoxicity).44 Another example of a lipodystrophic mouse came from the study of prolipogenic factors. Sterol-regulatory element binding protein 1 (SREBP1) is an important transcriptional regulator of fatty acid metabolism and lipogenesis in liver and adipose tissue. Unexpectedly, the transgenic overexpression of active SREBP1c in adipose tissue produced a lipodystrophic mouse with severe insulin resistance and fat deposition in the liver.45 It is unclear how the expression of a prolipogenic gene in adipose tissue resulted in lipodystrophy, although it has been suggested that this may result from the unregulated overexpression of the transcription factor interfering in the normal pattern of expression of the other proadipogenic genes. Nonetheless, these animals also showed that insulin resistance affects lipid and glucose

EXCESS OF NUTRIENTS AS A CAUSE OF INSULIN RESISTANCE

147

metabolism differently in liver in insulin-resistant states. This effect probably depends on the peculiarities of the tissue-specific insulin signalling network. In the active SREBP1 transgenic model, as well as in the ob/ob deficient leptin model of obesity, insulin resistance in liver results in decreased levels of IRS2, whereas SREBP1 and lipogenesis are maintained.46 This suggests that, while some specific pathways of insulin signalling are impaired, other insulin signalling pathways are active and continue to stimulate SREBP1c expression. Thus defects in specific molecules of the insulin signalling network are expected to have different impacts, depending on the tissue considered.

5.11

Excess of nutrients as a cause of insulin resistance

Genetically modified mice have been a key tool to address the effect of partitioning of energy between the adipose tissue, liver and muscle and its relevance for the development of insulin resistance. Mouse models engineered to facilitate the entrance of glucose or fatty acids into a specific tissue have shown that this is enough to promote the development of insulin resistance. For instance, overexpression of lipoprotein lipase in muscle or liver results in triglyceride deposition in these tissues and increased insulin resistance.34, 33 Similarly, overexpression of enzymes involved in the glucosamine (e.g. glutamine fructose aminotransferase) pathway also results in insulin resistance.47 Several other animal models have only become markedly insulin resistant when exposed to a high fat diet. A clear example is the triple β1, β2, β3 adrenergic receptor knockouts that only become obese and insulin resistant when exposed to a high fat diet.48 This model also illustrates the concept of functional redundancy, since ablation of the β3 receptor49 seems to be compensated by upregulation of the β2 receptor. A potential strategy to prevent the toxic effects of overnutrition on insulin sensitivity is to promote fatty acid oxidation. The proof of the viability of this concept is well represented by transgenic models overexpressing either UCP150 or UCP3 mitochondrial uncoupling proteins.51 The mitochondria of these animals are uncoupled and therefore oxidize more fatty acids. These animals are lean and more insulin sensitive, suggesting that strategies designed to prevent excess of fuel may have positive effects on insulin sensitivity. Another potential strategy to increase the oxidative capacity of skeletal muscle includes increasing the number of mitochondria. The recent identification of key modulators of mitochondrial biogenesis such PGC1α52 may indicate good targets to prevent lipotoxicity-mediated insulin resistance. In fact, overexpression of PGC1α53 in skeletal muscle promotes development of pro-oxidative red fibres associated with an increased number of mitochondria. Future characterization of this model should clarify whether this mouse model is also more insulin sensitive.

148

5.12

GENETICALLY MODIFIED MOUSE MODELS OF INSULIN RESISTANCE

PPARs, key mediators of nutritional-regulated gene expression and insulin sensitivity

Peroxisome proliferator-activated receptors (PPARs) are transcription factors activated by lipid derivatives that regulate aspects such as fatty acid oxidation, adipogenesis and insulin sensitivity. The PPAR family is comprised of three members, PPARα, γ and δ.54 PPARγ is the receptor for the class of insulin sensitizer drugs termed thiazolidinediones. Paradoxically, besides promoting insulin sensitivity, PPARγ activation also plays a crucial role promoting adipocyte differentiation. To elucidate the molecular mechanisms behind this paradox, several groups attempted and failed to generate a global PPARγ knockout mouse. These animals were not viable due to inappropriate vascularization of the placenta. The study of the heterozygous PPARγ (+/−)55, 56 brought new surprises. When fed a high fat diet, these animals were protected against weight gain and more surprisingly were also more insulin sensitive, through a mechanism probably related to upregulation of leptin. For the sceptics this could be a clear example showing that genetically modified animals can sometimes be inconclusive, raising more questions than they solve. However, this unexpected finding also provides unique opportunities to uncover new aspects of biology and this possibility is probably what keeps most of us in this ‘business’. In summary, genetically modified mice have proved to be powerful tools to characterize in vivo the molecular mechanisms leading to insulin resistance. From these studies have emerged very important concepts that have a direct impact in our understanding of insulin resistance with great implications for our approach to human diabetes. The concept of tissue-specific insulin resistance heterogeneity, the relevance of inter-organ communication for energy partitioning, the importance of adipose tissue and liver as key organs to control glucose homeostasis in vivo and defects in insulin secretion as another manifestation of insulin resistance are some examples. The extensive work described in this chapter could appear as the end of this type of research. But, in fact, it should be considered more as the proof that the approach is valid and that there is a fertile area of research supported by the availability of more and more sophisticated biological tools that will allow us to address specific questions in more detail.

References 1. Vidal-Puig, A. and O’Rahilly, S. (2002) Insulin receptor. In: Encyclopedia of Molecular Medicine Vol. 5. Hoboken, NJ: Wiley, pp. 1774–1780. 2. Hotamisligil, G. S. and Spiegelman, B. M. (1994) Tumor necrosis factor alpha: a key component of the obesity–diabetes link. Diabetes 43, 1271–1278. 3. Hotamisligil, G. S., Arner, P., Caro, J. F., Atkinson, R. L. and Spiegelman, B. M. (1995) Increased adipose tissue expression of tumor necrosis factor-alpha in human obesity and insulin resistance. J Clin Invest 95, 2409–2415.

REFERENCES

149

4. Moller, D. E. (2000) Potential role of TNF-alpha in the pathogenesis of insulin resistance and type 2 diabetes. Trends Endocrinol Metab 11, 212–217. 5. Tomas, E., Tsao, T. S., Saha, A. K., Murrey, H. E., Zhang Cc, C., Itani, S. I., Lodish, H. F. and Ruderman, N. B. (2002) Enhanced muscle fat oxidation and glucose transport by ACRP30 globular domain: acetyl-CoA carboxylase inhibition and AMP-activated protein kinase activation. Proc Natl Acad Sci USA 99, 16 309–16 313. 6. McTernan, P. G., McTernan, C. L., Chetty, R., Jenner, K., Fisher, F. M., Lauer, M. N., Crocker, J., Barnett, A. H. and Kumar, S. (2002) Increased resistin gene and protein expression in human abdominal adipose tissue. J Clin Endocrinol Metab 87, 2407–2410. 7. McTernan, C. L., McTernan, P. G., Harte, A. L., Levick, P. L., Barnett, A. H. and Kumar, S. (2002) Resistin, central obesity, and type 2 diabetes. Lancet 359, 46–47. 8. Joshi, R. L., Lamothe, B., Cordonnier, N., Mesbah, K., Monthioux, E., Jami, J. and Bucchini, D. (1996) Targeted disruption of the insulin receptor gene in the mouse results in neonatal lethality. EMBO J 15, 1542–1547. 9. Accili, D., Drago, J., Lee, E. J., Johnson, M. D., Cool, M. H., Salvatore, P., Asico, L. D., Jose, P. A., Taylor, S. I. and Westphal, H. (1996) Early neonatal death in mice homozygous for a null allele of the insulin receptor gene. Nat Genet 12, 106–109. 10. Shirakami, A., Toyonaga, T., Tsuruzoe, K., Shirotani, T., Matsumoto, K., Yoshizato, K., Kawashima, J., Hirashima, Y., Miyamura, N., Kahn, C. R. and Araki, E. (2002) Heterozygous knockout of the IRS-1 gene in mice enhances obesity-linked insulin resistance: a possible model for the development of type 2 diabetes. J Endocrinol 174, 309–319. 11. Araki, E., Lipes, M. A., Patti, M. E., Bruning, J. C., Haag, B., III, Johnson, R. S. and Kahn, C. R. (1994) Alternative pathway of insulin signalling in mice with targeted disruption of the IRS-1 gene. Nature 372, 186–190. 12. Tamemoto, H., Kadowaki, T., Tobe, K., Yagi, T., Sakura, H., Hayakawa, T., Terauchi, Y., Ueki, K., Kaburagi, Y., Satoh, S. et al. (1994) Insulin resistance and growth retardation in mice lacking insulin receptor substrate-1. Nature 372, 182–186. 13. Kubota, N., Tobe, K., Terauchi, Y., Eto, K., Yamauchi, T., Suzuki, R., Tsubamoto, Y., Komeda, K., Nakano, R., Miki, H., Satoh, S., Sekihara, H., Sciacchitano, S., Lesniak, M., Aizawa, S., Nagai, R., Kimura, S., Akanuma, Y., Taylor, S. I. and Kadowaki, T. (2000) Disruption of insulin receptor substrate 2 causes type 2 diabetes because of liver insulin resistance and lack of compensatory beta-cell hyperplasia. Diabetes 49, 1880–1889. 14. Liu, S. C., Wang, Q., Lienhard, G. E. and Keller, S. R. (1999) Insulin receptor substrate 3 is not essential for growth or glucose homeostasis. J Biol Chem 274, 18 093–18 099. 15. Fantin, V. R., Wang, Q., Lienhard, G. E. and Keller, S. R. (2000) Mice lacking insulin receptor substrate 4 exhibit mild defects in growth, reproduction, and glucose homeostasis. Am J Physiol Endocrinol Metab 278, E127–133. 16. Terauchi, Y., Tsuji, Y., Satoh, S., Minoura, H., Murakami, K., Okuno, A., Inukai, K., Asano, T., Kaburagi, Y., Ueki, K., Nakajima, H., Hanafusa, T., Matsuzawa, Y., Sekihara, H., Yin, Y., Barrett, J. C., Oda, H., Ishikawa, T., Akanuma, Y., Komuro, I., Suzuki, M., Yamamura, K., Kodama, T., Suzuki, H., Kadowaki, T. et al. (1999) Increased insulin sensitivity and hypoglycaemia in mice lacking the p85 alpha subunit of phosphoinositide 3-kinase. Nat Genet 21, 230–235. 17. Ueki, K., Yballe, C. M., Brachmann, S. M., Vicent, D., Watt, J. M., Kahn, C. R. and Cantley, L. C. (2002) Increased insulin sensitivity in mice lacking p85beta subunit of phosphoinositide 3-kinase. Proc Natl Acad Sci USA 99, 419–424. 18. Fruman, D. A., Mauvais-Jarvis, F., Pollard, D. A., Yballe, C. M., Brazil, D., Bronson, R. T., Kahn, C. R. and Cantley, L. C. (2000) Hypoglycaemia, liver necrosis and perinatal death in mice lacking all isoforms of phosphoinositide 3-kinase p85 alpha. Nat Genet 26, 379–382.

150

GENETICALLY MODIFIED MOUSE MODELS OF INSULIN RESISTANCE

19. Mauvais-Jarvis, F., Kulkarni, R. N. and Kahn, C. R. (2002) Knockout models are useful tools to dissect the pathophysiology and genetics of insulin resistance. Clin Endocrinol (Oxf) 57, 1–9. 20. Lawlor, M. A., Mora, A., Ashby, P. R., Williams, M. R., Murray-Tait, V., Malone, L., Prescott, A. R., Lucocq, J. M. and Alessi, D. R. (2002) Essential role of PDK1 in regulating cell size and development in mice. EMBO J 21, 3728–3738. 21. Cho, H., Mu, J., Kim, J. K., Thorvaldsen, J. L., Chu, Q., Crenshaw, E. B., III, Kaestner, K. H., Bartolomei, M. S., Shulman, G. I. and Birnbaum, M. J. (2001) Insulin resistance and a diabetes mellitus-like syndrome in mice lacking the protein kinase Akt2 (PKB beta). Science 292, 1728–1731. 22. Nakae, J., Kitamura, T., Silver, D. L. and Accili, D. (2001) The forkhead transcription factor Foxo1 (Fkhr) confers insulin sensitivity onto glucose-6-phosphatase expression. J Clin Invest 108, 1359–1367. 23. Nakae, J., Kitamura, T., Ogawa, W., Kasuga, M. and Accili, D. (2001) Insulin regulation of gene expression through the forkhead transcription factor Foxo1 (Fkhr) requires kinases distinct from Akt. Biochemistry 40, 11 768–11 776. 24. Stenbit, A. E., Tsao, T. S., Li, J., Burcelin, R., Geenen, D. L., Factor, S. M., Houseknecht, K., Katz, E. B. and Charron, M. J. (1997) GLUT4 heterozygous knockout mice develop muscle insulin resistance and diabetes. Nat Med 3, 1096–1101. 25. Maier, V. H., Melvin, D. R., Lister, C. A., Chapman, H., Gould, G. W. and Murphy, G. J. (2000) v- and t-SNARE protein expression in models of insulin resistance: normalization of glycemia by rosiglitazone treatment corrects overexpression of cellubrevin, vesicleassociated membrane protein-2, and syntaxin 4 in skeletal muscle of Zucker diabetic fatty rats. Diabetes 49, 618–625. 26. Klaman, L. D., Boss, O., Peroni, O. D., Kim, J. K., Martino, J. L., Zabolotny, J. M., Moghal, N., Lubkin, M., Kim, Y. B., Sharpe, A. H., Stricker-Krongrad, A., Shulman, G. I., Neel, B. G. and Kahn, B. B. (2000) Increased energy expenditure, decreased adiposity, and tissue-specific insulin sensitivity in protein-tyrosine phosphatase 1B-deficient mice. Mol Cell Biol 20, 5479–5489. 27. Clement, S., Krause, U., Desmedt, F., Tanti, J. F., Behrends, J., Pesesse, X., Sasaki, T., Penninger, J., Doherty, M., Malaisse, W., Dumont, J. E., Le Marchand-Brustel, Y., Erneux, C., Hue, L. and Schurmans, S. (2001) The lipid phosphatase SHIP2 controls insulin sensitivity. Nature 409, 92–97. 28. Hirosumi, J., Tuncman, G., Chang, L., Gorgun, C. Z., Uysal, K. T., Maeda, K., Karin, M. and Hotamisligil, G. S. (2002) A central role for JNK in obesity and insulin resistance. Nature 420, 333–336. 29. Bruning, J. C., Winnay, J., Cheatham, B. and Kahn, C. R. (1997) Differential signaling by insulin receptor substrate 1 (IRS-1) and IRS-2 in IRS-1-deficient cells. Mol Cell Biol 17, 1513–1521. 30. Bruning, J. C., Michael, M. D., Winnay, J. N., Hayashi, T., Horsch, D., Accili, D., Goodyear, L. J. and Kahn, C. R. (1998) A muscle-specific insulin receptor knockout exhibits features of the metabolic syndrome of NIDDM without altering glucose tolerance. Mol Cell 2, 559–569. 31. Bluher, M., Michael, M. D., Peroni, O. D., Ueki, K., Carter, N., Kahn, B. B. and Kahn, C. R. (2002) Adipose tissue selective insulin receptor knockout protects against obesity and obesity-related glucose intolerance. Dev Cell 3 (1), 25–38. 32. Bluher, M., Kahn, B. B. and Kahn, C. R. (2003) Extended longevity in mice lacking the insulin receptor in adipose tissue. Science 299, 572–574. 33. Ferreira, L. D., Pulawa, L. K., Jensen, D. R. and Eckel, R. H. (2001) Overexpressing human lipoprotein lipase in mouse skeletal muscle is associated with insulin resistance. Diabetes 50 (5), 1064–1068.

REFERENCES

151

34. Kim, J. K., Fillmore, J. J., Chen, Y., Yu, C., Moore, I. K., Pypaert, M., Lutz, E. P., Kako, Y., Velez-Carrasco, W., Goldberg, I. J., Breslow, J. L. and Shulman, G. I. (2001) Tissuespecific overexpression of lipoprotein lipase causes tissue-specific insulin resistance. Proc Natl Acad Sci USA 98, 7522–7527. 35. Michael, M. D., Kulkarni, R. N., Postic, C., Previs, S. F., Shulman, G. I., Magnuson, M. A. and Kahn, C. R. (2000) Loss of insulin signaling in hepatocytes leads to severe insulin resistance and progressive hepatic dysfunction. Mol Cell 6, 87–97. 36. Kulkarni, R. N., Bruning, J. C., Winnay, J. N., Postic, C., Magnuson, M. A. and Kahn, C. R. (1999) Tissue-specific knockout of the insulin receptor in pancreatic beta cells creates an insulin secretory defect similar to that in type 2 diabetes. Cell 96, 329–339. 37. Bruning, J. C., Gautam, D., Burks, D. J., Gillette, J., Schubert, M., Orban, P. C., Klein, R., Krone, W., Muller-Wieland, D. and Kahn, C. R. (2000) Role of brain insulin receptor in control of body weight and reproduction. Science 289, 2122–2125. 38. Maeda, N., Shimomura, I., Kishida, K., Nishizawa, H., Matsuda, M., Nagaretani, H., Furuyama, N., Kondo, H., Takahashi, M., Arita, Y., Komuro, R., Ouchi, N., Kihara, S., Tochino, Y., Okutomi, K., Horie, M., Takeda, S., Aoyama, T., Funahashi, T. and Matsuzawa, Y. (2002) Diet-induced insulin resistance in mice lacking adiponectin/ACRP30. Nat Med 8, 731–737. 39. Ma, K., Cabrero, A., Saha, P. K., Kojima, H., Li, L., Chang, B. H., Paul, A. and Chan, L. (2002) Increased beta-oxidation but no insulin resistance or glucose intolerance in mice lacking adiponectin. J Biol Chem 277, 34 658–34 661. 40. Hotamisligil, G. S., Johnson, R. S., Distel, R. J., Ellis, R., Papaioannou, V. E. and Spiegelman, B. M. (1996) Uncoupling of obesity from insulin resistance through a targeted mutation in aP2, the adipocyte fatty acid binding protein. Science 274, 1377–1379. 41. Moitra, J., Mason, M. M., Olive, M., Krylov, D., Gavrilova, O., Marcus-Samuels, B., Feigenbaum, L., Lee, E., Aoyama, T., Eckhaus, M., Reitman, M. L. and Vinson, C. (1998) Life without white fat: a transgenic mouse. Genes Dev 12, 3168–3181. 42. Shimomura, I., Hammer, R. E., Ikemoto, S., Brown, M. S. and Goldstein, J. L. (1999) Leptin reverses insulin resistance and diabetes mellitus in mice with congenital lipodystrophy. Nature 401, 73–76. 43. Gavrilova, O., Marcus-Samuels, B., Graham, D., Kim, J., Shulman, G., Castle, A., Vinson, C., Eckhaus, M. and Reitman, M. (2000) Surgical implantation of adipose tissue reverses diabetes in lipoatrophic mice. J Clin Invest 105, 271–278. 44. Abel, E. D., Peroni, O., Kim, J. K., Kim, Y. B., Boss, O., Hadro, E., Minnemann, T., Shulman, G. I. and Kahn, B. B. (2001) Adipose-selective targeting of the GLUT4 gene impairs insulin action in muscle and liver. Nature 409, 729–733. 45. Shimomura, I., Hammer, R. E., Richardson, J. A., Ikemoto, S., Bashmakov, Y., Goldstein, J. L. and Brown, M. S. (1998) Insulin resistance and diabetes mellitus in transgenic mice expressing nuclear SREBP-1c in adipose tissue: model for congenital generalized lipodystrophy. Genes Dev 12, 3182–3194. 46. Shimomura, I., Matsuda, M., Hammer, R. E., Bashmakov, Y., Brown, M. S. and Goldstein, J. L. (2000) Decreased IRS-2 and increased SREBP-1c lead to mixed insulin resistance and sensitivity in livers of lipodystrophic and ob/ob mice. Mol Cell 6, 77–86. 47. Veerababu, G., Tang, J., Hoffman, R. T., Daniels, M. C., Hebert, L. F., Jr., Crook, E. D., Cooksey, R. C. and McClain, D. A. (2000) Overexpression of glutamine: fructose-6phosphate amidotransferase in the liver of transgenic mice results in enhanced glycogen storage, hyperlipidemia, obesity, and impaired glucose tolerance. Diabetes 49, 2070–2078. 48. Bachman, E. S., Dhillon, H., Zhang, C. Y., Cinti, S., Bianco, A. C., Kobilka, B. K. and Lowell, B. B. (2002) betaAR signaling required for diet-induced thermogenesis and obesity resistance. Science 297, 843–845.

152

GENETICALLY MODIFIED MOUSE MODELS OF INSULIN RESISTANCE

49. Grujic, D., Susulic, V. S., Harper, M. E., Himms-Hagen, J., Cunningham, B. A., Corkey, B. E. and Lowell, B. B. (1997) Beta3-adrenergic receptors on white and brown adipocytes mediate beta3-selective agonist-induced effects on energy expenditure, insulin secretion, and food intake. A study using transgenic and gene knockout mice. J Biol Chem 272, 17 686–17 693. 50. Kopecky, J., Hodny, Z., Rossmeisl, M., Syrovy, I. and Kozak, L. P. (1996) Reduction of dietary obesity in aP2-Ucp transgenic mice: physiology and adipose tissue distribution. Am J Physiol 270, E768–E775. 51. Clapham, J. C., Arch, J. R., Chapman, H., Haynes, A., Lister, C., Moore, G. B., Piercy, V., Carter, S. A., Lehner, I., Smith, S. A., Beeley, L. J., Godden, R. J., Herrity, N., Skehel, M., Changani, K. K., Hockings, P. D., Reid, D. G., Squires, S. M., Hatcher, J., Trail, B., Latcham, J., Rastan, S., Harper, A. J., Cadenas, S., Buckingham, J. A., Brand, M. D. and Abuin, A. (2000) Mice overexpressing human uncoupling protein-3 in skeletal muscle are hyperphagic and lean. Nature 406, 415–418. 52. Wu, Z., Puigserver, P., Andersson, U., Zhang, C., Adelmant, G., Mootha, V., Troy, A., Cinti, S., Lowell, B., Scarpulla, R. C. and Spiegelman, B. M. (1999) Mechanisms controlling mitochondrial biogenesis and respiration through the thermogenic coactivator PGC-1. Cell 98, 115–124. 53. Lin, J., Wu, H., Tarr, P. T., Zhang, C. Y., Wu, Z., Boss, O., Michael, L. F., Puigserver, P., Isotani, E., Olson, E. N., Lowell, B. B., Bassel-Duby, R. and Spiegelman, B. M. (2002) Transcriptional co-activator PGC-1 alpha drives the formation of slow-twitch muscle fibres. Nature 418, 797–801. 54. Sewter, C. and Vidal-Puig, A. (2002) Diabetes Obes Metab 4, 239–248. 55. Kubota, N., Terauchi, Y., Miki, H., Tamemoto, H., Yamauchi, T., Komeda, K., Satoh, S., Nakano, R., Ishii, C., Sugiyama, T., Eto, K., Tsubamoto, Y., Okuno, A., Murakami, K., Sekihara, H., Hasegawa, G., Naito, M., Toyoshima, Y., Tanaka, S., Shiota, K., Kitamura, T., Fujita, T., Ezaki, O., Aizawa, S., Kadowaki, T. et al. (1999) PPAR gamma mediates high-fat diet-induced adipocyte hypertrophy and insulin resistance. Mol Cell 4, 597–609. 56. Rosen, E. D., Sarraf, P., Troy, A. E., Bradwin, G., Moore, K., Milstone, D. S., Spiegelman, B. M. and Mortensen, R. M. (1999) PPAR gamma is required for the differentiation of adipose tissue in vivo and in vitro. Mol Cell 4, 611–617. 57. Laustsen, P. G., Michael, M. D., Crute, B. E., Cohen, S. E., Ueki, K., Kulkarni, R. N., Keller, S. R., Lienhard, G. E. and Kahn, C. R. (2002) Lipoatrophic diabetes in Irs1(−/−)/Irs3(−/−) double knockout mice. Genes Dev 16, 3213–3222. 58. Garofalo, R. S., Orena, S. J., Rafidi, K., Torchia, A. J., Stock, J. L., Hildebrandt, A. L., Coskran, T., Black, S. C., Brees, D. J., Wicks, J. R., McNeish, J. D. and Coleman, K. G. (2003) Severe diabetes, age-dependent loss of adipose tissue, and mild growth deficiency in mice lacking Akt2/PKB beta. J Clin Invest 112, 197–208. 59. Peng, X. D., Xu, P. Z., Chen, M. L., Hahn-Windgassen, A., Skeen, J., Jacobs, J., Sundararajan, D., Chen, W. S., Crawford, S. E., Coleman, K. G. and Hay, N. (2003) Dwarfism, impaired skin development, skeletal muscle atrophy, delayed bone development, and impeded adipogenesis in mice lacking Akt1 and Akt2. Genes Dev 17, 1352–1365. 60. Rossetti, L., Stenbit, A. E., Chen, W., Hu, M., Barzilai, N., Katz, E. B. and Charron, M. J. (1997) Peripheral but not hepatic insulin resistance in mice with one disrupted allele of the glucose transporter type 4 (GLUT4) gene. J Clin Invest 100, 1831–1839. 61. Li, J., Houseknecht, K. L., Stenbit, A. E., Katz, E. B. and Charron, M. J. (2000) Reduced glucose uptake precedes insulin signaling defects in adipocytes from heterozygous GLUT4 knockout mice. FASEB J 14, 1117–1125. 62. Altomonte, J., Richter, A., Harbaran, S., Suriawinata, J., Nakae, J., Thung, S. N., Meseck, M., Accili, D. and Dong, H. (2003) Inhibition of Foxo1 function is associated with improved fasting glycemia in diabetic mice. Am J Physiol Endocrinol Metab 52 (8), 958–963.

REFERENCES

153

63. Guerra, C., Navarro, P., Valverde, A. M., Arribas, M., Bruning, J., Kozak, L. P., Kahn, C. R. and Benito, M. (2001) Brown adipose tissue-specific insulin receptor knockout shows diabetic phenotype without insulin resistance. J Clin Invest 108, 1205–1213. 64. Zisman, A., Peroni, O. D., Abel, E. D., Michael, M. D., Mauvais-Jarvis, F., Lowell, B. B., Wojtaszewski, J. F., Hirshman, M. F., Virkamaki, A., Goodyear, L. J., Kahn, C. R. and Kahn, B. B. (2000) Targeted disruption of the glucose transporter 4 selectively in muscle causes insulin resistance and glucose intolerance. Nat Med 6, 924–928. 65. Uysal, K. T., Wiesbrock, S. M., Marino, M. W. and Hotamisligil, G. S. (1997) Protection from obesity-induced insulin resistance in mice lacking TNF-alpha function. Nature 389, 610–614. 66. Uysal, K. T., Wiesbrock, S. M. and Hotamisligil, G. S. (1998) Functional analysis of tumor necrosis factor (TNF) receptors in TNF-alpha-mediated insulin resistance in genetic obesity. Endocrinology, 139, 4832–4838. 67. Shimano, H., Shimomura, I., Hammer, R. E., Herz, J., Goldstein, J. L., Brown, M. S. and Horton, J. D. (1997) Elevated levels of SREBP-2 and cholesterol synthesis in livers of mice homozygous for a targeted disruption of the SREBP-1 gene. J Clin Invest 100, 2115–2124. 68. Shimano, H., Horton, J. D., Hammer, R. E., Shimomura, I., Brown, M. S. and Goldstein, J. L. (1996) Overproduction of cholesterol and fatty acids causes massive liver enlargement in transgenic mice expressing truncated SREBP-1a. J Clin Invest 98, 1575– 1584.

6 Insulin Resistance in Glucose Disposal and Production in Man with Specific Reference to Metabolic Syndrome and Type 2 Diabetes Henning Beck-Nielsen, Frank Alford and Ole Hother-Nielsen

6.1 Introduction Insulin is a multipotent hormone with several metabolic effects, but the most important and best described effect is the effect on glucose homeostasis. This effect relies not only on insulin secretion but also on insulin action at the cellular level. The discovery of the insulin receptor more than 30 years ago opened the field of insulin action at the cellular level and highlighted the clinical importance of insulin resistance.1 However, insulin resistance, which today is known as a major factor in the development of type 2 diabetes (T2D), was first described in the forties by Himsworth and Kerr.2 Unfortunately, their ideas were not followed up and not until the time of the discovery of the radio-immuno-assay for measurement of insulin were their ideas confirmed.3 Insulin action varies in different physiological and pathophysiological situations as a continuum without any cut-off point separating normal subjects from insulin-resistant subjects. However, WHO has decided that insulin resistance can be defined as the lowest quartile of insulin action (see below). In fact, this value discriminates very well between normal subjects and for example subjects with T2D. Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

156

INSULIN RESISTANCE IN GLUCOSE DISPOSAL AND PRODUCTION IN MAN

Table 6.1

Classification of insulin resistance states (based on reference 9)

Physiological

Secondary Hormone excess

Growth hormone deficiency Organ failure Primary

Genetic Lipodystrophies

Aging Puberty Pregnancy Obesity Starvation Diurnal variation Stress (catecholamine↑, surgery, illness) Cushing’s Acromegaly Phaechromocytoma Glucagonoma Chronic renal failure, cirrhosis, haemochromatosis T2D PCOS ‘Metabolic syndrome’ Insulin receptor defects (leprechaunism) Syndromes (Prader-Willi, Laron dwarfism) Congenital (generalized or partial lipoatrophy syndromes) Acquired (HIV-1 protease inhibitor treatment)

The impact of insulin resistance or insulin sensitivity on glucose metabolism has wide implications for human disease, such as the development of T2D, obesity, hypertension, atheromatous cardiac and vascular diseases, dyslipidaemia and polycystic ovarian disease, as well as other numerous pathological and physiological states (Table 6.1). In this chapter we will present an overview of the importance of insulin resistance to glucose processing and glucose turnover, including the tissues affected. There are numerous excellent reviews of this area4 – 7 and we will therefore present our view of the important sites of insulin resistance, its interaction with genetic background and its pathophysiology. This personalized approach will, we hope, stimulate the reader to further explore insulin resistance and its pathogenesis in various disease states and compare the current formulation to those of others. The initial section of this chapter will present a definition of insulin resistance/insulin sensitivity and a brief outline and critique of the various methods for its measurement; next a discussion of the role of glucose transport, glycogen synthesis and the insulin-action cascade in insulin resistance will be presented, followed by a review of the skeletal muscle metabolic pathways affected by insulin resistance, including the potential important role of the adipocyte in the pathogesis of insulin resistance, and finally the role of the liver in the insulin resistant state. The main emphasis will be put on T2D and the metabolic syndrome.

MEASUREMENT OF INSULIN RESISTANCE

6.2

157

Measurement of insulin resistance

The definition and accurate quantification are important and a seemingly bewildering number of methods are available for its measurement. Nevertheless, there are basic mathematical principles common to the various methods.8 Thus, the decision of which method to use in a particular study is most dependent on the aims, the biological questions being asked and the limitations imposed by the experimental population and study design. This section will briefly outline the key methods available to the researcher, including their advantages and limitations. For more detailed discussion of the various methods employed for the measurement of insulin resistance, readers are referred to several excellent recent reviews of the methodology.8 – 10 Three major factors control overall glucose tolerance of an individual: the amount of circulating insulin; the biological effect or action of insulin (i.e. insulin sensitivity, Si ); and the impact of glucose itself on its own disposal, independent of insulin action (i.e. glucose sensitivity, Sg , or glucose effectiveness).10 The latter parameter (Sg ) is usually not separately quantitated by most workers, on the assumption that its contribution to Si is quite small or even negligible. This may apply to situations of normal or only modestly reduced Si , especially if a hyperinsulinaemic method is employed to measure Si . In more severe insulin resistant states, such as T2D, where hyperglycaemia and relative hypoinsulinaemia coexist, the contribution from Sg to the overall insulin-resistant state may be considerable and equal or exceed that of Si .10, 11 This is particularly important if the method chosen to measure Si employs only basal fasting conditions.8, 9 The researcher must therefore be aware of this compounding issue when Si is measured in severe insulin-resistant states. There also exists a close reciprocal relationship between Si and the magnitude of insulin secretion, particularly acute phase insulin release, as measured during oral or intravenous glucose tolerance tests.12 Thus, to quantify the contribution of absolute insulin secretion on glucose tolerance, measurements of both Si and insulin secretion must be known. Often overlooked is the fact that the definitions of insulin resistance and Si are different. Insulin resistance ‘is a reduced biological effect for any given concentration of insulin’.9 On the other hand, Si represents ‘a quantitative measure of a specific biological effect of insulin’, i.e. Si is the biological response to a given change of insulin as measured at euglycaemia (Figure 6.1).10 Importantly, insulin resistance is the reciprocation of Si , a factor that needs to be considered when comparing different methodologies.8 Finally, insulin action occurs in numerous tissue sites: the liver, skeletal muscle and adipose tissue. In addition, different metabolic pathways within these tissues may also be involved, including the glycolytic, oxidative and

158

INSULIN RESISTANCE IN GLUCOSE DISPOSAL AND PRODUCTION IN MAN Response

c b c′

a a′

b′ Insulin (mU/l)

10 50 x y

Si =

100 z

1000

∆ response (Rd or HGP or GF or GS) ∆ insulin

c−b a S i = by − − x or z − y

versus

S i′ = b ′ − a′ or c ′ − b ′ y−x z−y (based on Bergmann et al.)

Figure 6.1

Definition: insulin resistance/insulin sensitivity

non-oxidative-glycogen synthetic and fat synthetic pathways, as well as the inhibition of lipolysis. Whole body measurements of Si therefore represent a composite, the components of which may not be affected equally by the insulinresistant state. It is, however, possible to differentiate between these tissue sites and metabolic pathways by the addition of extra experimental procedures during the measurement of Si , employing the clamp technique (Figure 6.2).

Non-dynamic measurements of Si These tests, which include fasting insulin alone, the HOMA test (homeostasis assessment model)13 and the QUICKI (quantitative insulin-sensitivity check index)14 have been extensively reviewed.8, 9 These tests are simple to perform, being based on fasting insulin and glucose measurements alone. However, even this simple procedure needs to be carried out in a carefully standardized manner if reliable measurements of insulin resistance are to be obtained. Factors that must be controlled are the accuracy and precision of the insulin assay; the duration and site (hospital versus home) of the fast; transport and processing of samples to the laboratory before its assay.9 Also, once significant β-cell dysfunction occurs (i.e. impaired and diabetic glucose-intolerant states), which compromises the β-cell’s ability to respond to the insulin-resistant state, these techniques can be misleading. Nevertheless, these methods, in particular HOMA resistance, are very useful in epidemiological studies.

MEASUREMENT OF INSULIN RESISTANCE Bolus

159

Bolus [3-3H]-glucose (HOT-GINF) Muscle biopsy Indirect calorimetry Insulin infusion (±other hormones)

MBx

MBx

Steady state

–150 –120

–30

0

120–150

Time (minutes)

Method

Basal state

Insulin clamp

No tracer

–

M or M/I

Tracer

HGPb= Rab Rdb

RdI HGPI = RdI–GINFHOT GFI (from 3H2O) GSI = RdI–GFI

GFb (from 3H2O) Indirect calorimetry

GOxb LOb RQb

GOxI LOI RQI Non-Ox GS = RdI – GOI

Muscle biopsy

Glycogenb Glucoseb, G-6-Pb, lactateb etc Enzyme activitiesb Lipid metabolitesb

GlycogenI GlucoseI, G-6-PI, lactateI etc Enzyme activitiesI Lipid metabolitesI

Figure 6.2 Description of the hyperinsulinaemic euglycaemic clamp technique together with indirect calorimetry and skeletal muscle biopsies

The euglycaemic clamp technique For in vivo assessment of Si the hyperinsulinaemic euglycaemic clamp technique has become the gold standard method. With this technique insulin concentrations are elevated using a constant intravenous insulin infusion, and plasma glucose is maintained constant by a variable intravenous glucose infusion.15 The clamp can be performed at different insulin levels on the same day or on different days to obtain a dose–response curve for the insulin effect.16 The glucose infusion rate necessary to maintain euglycaemia during the clamp represents the net effect of insulin on glucose metabolism. The average glucose infusion rate during the last hour of the clamp is often termed the M-value. Insulin sensitivity or resistance is estimated by comparison to a normal control group. The clamp technique can be combined with several other techniques (Figure 6.2) as required in order to obtain a more differentiated picture of insulin action on various aspects of metabolism.17 When the clamp is combined with the primedconstant tracer infusion technique, not only insulin-stimulated rates, but also basal rates and thereby the response from basal to the insulin-stimulated state, can be measured. With the tracer technique both the rate of glucose appearance (Ra ) and disappearance (Rd ) is estimated, and hepatic glucose production

160

INSULIN RESISTANCE IN GLUCOSE DISPOSAL AND PRODUCTION IN MAN

(HGP) can be calculated as the difference between Ra and glucose infusion rate. Infusing labelled gluconeogenic substrates or using the deuterated water method as described by Landau,18, 19 the fraction of glucose production from gluconeogenesis can be estimated. Several other combinations have been used to gain insight into regulation of various metabolic pathways, e.g. tissue biopsies for assessment of effects on receptors, enzymes, regulatory substances or substrates, regional catheterization using the a–v balance technique across forearm, leg or splanchnic bed, a combination with NMR technique to assess glycogen build-up or depletion, the microdialysis technique assessing substances in the interstitial fluid, and many more techniques, including indirect calorimetry, which can be used to estimate the contributions of whole body glucose (and fat) oxidation and non-oxidative glucose metabolism (i.e. glycogen synthesis and anaerobic glycolysis) to net glucose disposal. The latter technique has been extensively and critically reviewed previously and is not discussed further here.20 However, it is important to note that this technique measures whole body substrate oxidation in all body tissues of net irreversible loss of glucose carbons, regardless of their intracellular and extracellular origin,20 including brain, liver, kidney and skeletal muscle tissues. Furthermore, under basal resting conditions, skeletal muscle contributes only a small fraction (as opposed to exercising muscle or during hyperinsulinaemia) to overall body substrate oxidation, and this fraction is overwhelmed by the substrate oxidation occurring at rest in the other metabolically active tissues, such as brain and liver. Given these facts and the relative imprecision of whole body indirect calorimetry measurements, it is not possible to accurately quantitative skeletal muscle glucose (or fat) oxidation in the basal state using whole body indirect calorimetry. When attempted, mis-information about the relative contributions of basal resting fat and glucose oxidative metabolism in skeletal muscle has emerged, particularly in various insulin-resistant states, as recently summarized by Kelly and Mandarino.21 Although the measurement of whole body glycolytic flux, employing the 3 H2 O accumulation technique,22 provides a more direct measure of skeletal muscle glucose metabolism, this represents oxidative and non-oxidative glycolysis, and not skeletal muscle glucose oxidation alone. To specifically measure in vivo skeletal muscle partitioning of basal substrate utilization into glucose and fat oxidation and glycogen balance, indirect calorimetry measurements across the arm or leg muscle bed, or direct measurements of oxidation of infused exogenous labelled glucose and/or fat must be undertaken.21, 23

The measurement of whole body glycolytic flux rates Detailed descriptions and validation of the technique to measure in vivo whole body glycolytic flux (GF) rates in rats,22 dogs24 and man25 are described elsewhere. An advantage of the GF method is that, during hyperinsulinaemic clamps,

MEASUREMENT OF INSULIN RESISTANCE

161

the net rate of glycogen synthesis in skeletal muscle is accurately quantitated from the difference between total glucose uptake and GF. This latter measurement of glycogen synthesis matches closely the glycogen synthesis estimated directly in skeletal muscle for man.25 Thus, when endogenous glycogenolysis is negligible the extracellular [3 H2 O] estimate of GF equates with whole body GF. This contrasts with the glucose storage estimations calculated from the whole body indirect calorimetric technique (i.e. total glucose uptake – non-oxidative glucose metabolism), which gives results similar to the 3 H2 O technique, but the techniques are not identical. The indirect calorimetric technique is less precise and includes non-oxidative glucose metabolism of tissues other than skeletal muscle (liver, kidney, adipocytes) and non-oxidative GF (i.e. conversion of glucose to lactate), the latter being quite significant (10–30 per cent in T2D.26, 27 )

The frequently sampled IVGTT – minimal model measurement of insulin sensitivity This technique is based on a complex computer modelling analysis of the glucose and insulin profiles obtained following a rapid (1 minute) intravenous injection of glucose (20 per cent dextrose) into a peripheral vein with frequent sampling (25 samples) for serial measurements of glucose and insulin over the next 180 minutes.28, 29 The IVGTT technique itself and the modelling procedure have undergone several modifications over the years,10 the most basic one being the introduction of a small bolus of intravenous insulin, given 20 minutes after the glucose bolus, in order to improve the resolution of the simultaneous measurements of Si and Sg . However, the additional insulin bolus may erroneously elevate the subsequent calculation of Sg (but not Si ).30 It must also be remembered that this technique gives whole body measurements of Si and Sg . Attempts to differentiate between the periphery and liver by employing [3-3 H]-glucose have proven problematic.31 Nevertheless, the standard and insulin-modified minimal model estimates of Si have been validated against the gold standard euglycaemic clamp,32 and information concerning whole body glucose utilization (oxidative versus non-oxidative glucose metabolism), employing indirect calorimetry and skeletal muscle biopsies during the IVGTT, has been obtained.33 Most recently, validation of the dynamic estimate of Sg against the hyper-euglycaemic clamp has been reported (Henriksen, J. E., unpublished information). Overall, the actual performance of the IVGTT is simpler than performing a euglycaemic clamp and measurements of Si , Sg and acute phase insulin release (AIR) are obtained simultaneously with the one test, as well as glucose tolerance (Kg ). However, the subsequent modelling procedure is complex and time consuming, and the application of the technique (without the additional insulin bolus) to subjects with impaired glucose tolerance and diabetes (i.e. subjects with a small or absent AIR) is usually not possible.34, 35 This test is primarily a

162

INSULIN RESISTANCE IN GLUCOSE DISPOSAL AND PRODUCTION IN MAN

technique to explore the pathophysiology of the glucose tolerance in a limited group of individuals in cross-sectional studies36 or over time,37 in particular the relationships between Si , Sg and AIR and glucose tolerance. More recently, a simplified (10 samples only), non-computer-model-based IVGTT technique (∼40 minute test) for use in larger population samples has been introduced.38 This latter technique, which measures Si , AIR and Kg simultaneously, has an acceptable correlation with the gold standard clamp estimation of Si .38, 39

6.3

Insulin-resistant states

The most common and clinical important states of insulin resistance are T2D and obesity, which are often linked together in the metabolic syndrome. We therefore refer specifically to these clinical states in this review, but a complete list of insulin-resistant states is given in Table 6.1. In vivo insulin resistance is related not only to glucose disposal but also to insulin resistance in the liver (i.e. the inhibition of glucose production) and in fat cells (i.e. inhibition of lipolysis). These latter factors are important in the development of the metabolic syndrome. However, when most authors refer to the phenomenon of insulin resistance, they are mainly referring to insulin-mediated glucose disposal as measured in vivo by the golden standard hyperinsulinaemic euglycaemic clamp technique.40 Therefore, in practice, insulin resistance equates with reduced insulin-mediated glucose disposal. Since about 90 per cent of insulin-mediated glucose disposed in peripheral tissues is taken up in skeletal muscle, this tissue is central to the insulin-resistant states. The majority of glucose taken up is channelled towards glycogen, and therefore insulin sensitivity is due mainly to reduced insulin-mediated glycogen synthesis. When insulin-mediated glucose disposal is reduced to the lowest quartile of a control group of normal subjects, insulin resistance is present. In the following discussion, we will therefore concentrate mainly on glucose disposal in skeletal muscle as estimated by the above-mentioned clamp technique.

Glucose disposal in normal subjects In the basal state, euglycaemic glucose uptake in skeletal muscle is very modest and intracellular glucose utilization is mainly from glycogenolysis. However, during insulin stimulation glucose uptake is increased several-fold (Figure 6.3).41 Moreover, the capacity for storing glycogen is very high, which explains why most insulin-mediated glucose disposal takes place in the muscle. Glucose uptake is initiated by a stimulation of the translocation of GLUT4 proteins from the intracellular vesiscles into the membrane. Intracellular glucose is immediately phosphorylated into glucose-6-phosphate (G-6-P), which, for the major part, is converted to glycogen by insulin activation of the enzyme glycogen synthase, and by allosteric activation by G-6-P itself. Thus, most glucose is

INSULIN-RESISTANT STATES

163

Glucose turnover (mg/m2/min)

350 300 250

Rd

200

* 150

*

100

*

50 0

HGP

* 10

20 30 40 50 Plasma insulin (mU/l)

60

70

Figure 6.3 The effect of insulin on glucose disposal (Rd ) and hepatic glucose production (HGP) in type 2 diabetic patients ( ) and in control subjects ( ) (reproduced with permission from Staehr et al. (2001) Diabetes 50, 136341 )

ž

Ž

disposed of as glycogen during a hyperinsulinaemic clamp procedure, with a fraction being directed to glycolysis. These different fates of glucose have been confirmed by in vivo NMR studies.42 In normal insulin-sensitive individuals, with euglycaemic hyperinsulinaemia, GOX and GF increase by ∼2.5-fold to reach a maximum response by ∼700 pmol/l insulin,43 – 46 whereas glycogen synthase continues to rise sharply with higher insulin levels. Thus, at euglycaemia during a clamp study, the net contribution of GOX and GF to net glucose uptake falls progressively from ∼95 per cent at hypoinsulinaemia and ∼85 per cent at basal insulinaemia to ∼40 per cent at modest hyperinsulinaemia (∼700 pmol/l). With hyperglycaemia, GOX and GF rates are higher than at their matched euglycaemia insulinaemic states, but the relative contributions of GF and GOX to overall glucose disposal are less, i.e. ∼80 per cent at hypoinsulinaemia and falling to ∼40 per cent at modest hyperinsulinaemia.24 Of importance, hyperglycaemia per se does not enhance GOX 47, 48 until modest hyperinsulinaemia (>700 pmol/l) intervenes, presumably at the time when free fatty acid (FFA) levels are adequately suppressed. However, the GF rates are increased by hyperglycaemia at low and modest hyperinsulinaemia, independently of the prevailing plasma FFA, although the incremental response of GF induced by hyperglycaemia is greater when FFA levels are suppressed.24

Insulin resistance of glucose disposal in skeletal muscle (in vivo insulin resistance) Subjects with metabolic syndrome are characterized by insulin resistance in skeletal muscle. The basal glucose uptake in skeletal muscle in vivo is normal during euglycaemia, whereas it may be slightly increased (10–20 per cent)

164

INSULIN RESISTANCE IN GLUCOSE DISPOSAL AND PRODUCTION IN MAN

during hyperglycaemia. When the muscles are stimulated by insulin at euglycaemia, the insulin-mediated glucose disposal is found to be significantly reduced (Figure 6.3). The dose–response curve is right shifted, but the major defect is in maximal glucose disposal (Vmax defect), which may be reduced by more than 50 per cent in type 2 diabetic subjects (Figure 6.3).41 This defect in glucose disposal is mainly due to a reduced glycogen synthesis and, consequently, the glycogen stores in skeletal muscle from type 2 diabetic subjects are reduced by about 50 per cent.49 Predictably, the key in vivo enzyme in glycogen synthesis, namely glycogen synthase, has been found to be completely resistant to insulin50, 51 (Figure 6.4). Therefore, glycogen synthesis in insulin-resistant subjects increasingly relies on the substrate flux and the allosteric activation by G-6-P only. There are only minimal data available on GF rates in non-diabetic insulinresistant states. In one study, insulin-resistant subjects with impaired glucose tolerance (IGT), who were the non-diabetic twins of identical twins with T2D, GF and GOX (measured by whole body indirect calorimetry), as well as nonoxidative GF, were similar to matched healthy control subjects.52 In these IGT twins, glycogen synthesis was already significantly reduced. On the other hand, there is a vast body of data employing the whole body indirect calorimetry technique, which demonstrates that basal and insulin-stimulated GOX is reduced in IGT and insulin-resistant obese normal subjects.26, 27, 52 – 56 . Because plasma FFA levels are usually raised in these individuals, it is postulated that the insulin resistance is due to the operation of the Randle FFA cycle with its accompanying reduction of GOX .57 These data were extrapolated

Glycogen synthase activity (% fractional velocity)

50

40

30

**

20

10

0 Control

Diabetic

Figure 6.4 The effect of insulin (steady-state plasma insulin concentration of about 400 pmol/l) on stimulation of glycogen synthase activity in skeletal muscle from obese type 2 diabetic subjects and controls. ∗∗ p < 0.01 versus controls (reproduced with permission from Hojlund et al. (2003) Diabetes 52, 139351 )

INSULIN-RESISTANT STATES

165

to imply reduced GOX in skeletal muscle of these subjects, given that this tissue is responsible for ∼90 per cent of insulin-mediated glucose disposal during a clamp.43 Moreover, the importance of the Randle FFA cycle in the insulinresistant–GOX -reduced state was supported by the many studies employing short and long term58 – 60 FFA insulin infusions and indirect calorimetry, and skeletal muscle biopsies showing reduced pyruvate dehydrogenase activity.60 However, as indicated above, whole body indirect calorimetry is a relatively imprecise technique and resting muscles under basal conditions contribute only a small amount to whole body substrate oxidation.61 In contrast to these data, when skeletal muscle GOX is measured directly across the leg by indirect calorimetry in insulin-resistant obese women,62 simple generalized obesity63 and type 2 diabetic subjects,64 skeletal muscle GOX is significantly increased (and FA oxidation is reduced) as compared with insulinsensitive lean control subjects. Subsequently, skeletal muscle GOX was also found to be increased in type 2 diabetic subjects when indirect calorimetry across the arm combined with 14 [C]-palmatate oxidation techniques were used.23 Thus, in insulin-resistant states, basal resting GOX is increased (whilst FA oxidation is decreased) in skeletal muscle, despite the accompanying basal hyperinsulinaemia (secondary to the insulin resistance) and raised circulating FFA levels.21 Importantly, when insulin-resistant subjects are exposed to hyperinsulinaemia, the raised basal GOX in skeletal muscle changes little, in contrast to the significant rise of GOX in insulin-sensitive individuals.63 These insulin-resistant subjects demonstrate severe blunting or metabolic inflexibility with respect to insulin-stimulated GOX and FAOX .21 Thus, although the Randle fatty acid cycle can be shown to be operative acutely in man under certain experimental conditions, it seems unlikely that it is a pathological factor in the slow genesis of chronic insulin resistance in skeletal muscle. Only a limited number of studies have compared GF and GOX in skeletal muscle in insulin-resistant subjects and have employed combined 3 H2 O accumulation, whole body indirect calorimetry and whole body [14 C]-glucose oxidation techniques, which allow a separation of GF into oxidative and non-oxidative GF rates. Basal GF was similar in BMI-matched type 2 diabetic and control subjects, but with an elevation of basal resting non-oxidative GF in the type 2 diabetic subjects.27 However, the GF responses to modest hyperinsulinaemia were blunted in diabetic subjects at euglycaemia,26, 27 as were GOX responses (measured by the 14 [C]-glucose oxidation technique).26 In contrast, the non-oxidative GF response to modest euglycaemic hyperinsulinaemia was increased twofold in the type 2 diabetic individuals.26 When hyperglycaemia was superimposed during the modest hyperinsulinaemia, total and oxidative GF rates increased so that total GF was normalized, although non-oxidative GF remained significantly elevated, in the type 2 diabetic subjects.26 In contrast, Kelley and Mandarino, who employed direct across the leg indirect calorimetry in T2D, found that hyperglycaemia normalized skeletal muscle GF, as well as GOX and glycogen

166

INSULIN RESISTANCE IN GLUCOSE DISPOSAL AND PRODUCTION IN MAN

synthesis. These findings are in accordance with our ‘compensation theory’: i.e., that the hyperglycaemia in type 2 diabetic subjects develops in order to compensate for the reduced skeletal muscle insulin-mediated glucose disposal.

Cellular defects in insulin-resistant skeletal muscle As mentioned above, the diminished responsiveness of glycogen synthase is a key finding in insulin-resistant skeletal muscle, and consequently glycogen synthesis and content are reduced in in vivo biopsies49 (Figure 6.4). Furthermore, insulin stimulation of the translocation of GLUT4 transport proteins from the Golgi area to the cell membrane seems to be reduced.65 However, the latter phenomena cannot be studied in vivo. Thus, in vitro incubation of muscle strips from insulin-resistant subjects shows that insulin-mediated glucose uptake is reduced and that this defect correlates to a reduced GLUT4 translocation.66 This finding is confirmed by animal studies.67 Therefore, insulin-resistant skeletal muscle is characterized by defects both in glucose transport and in glycogen synthesis. Although these findings have been reproduced by several investigators, it is still uncertain whether there are two separate defects (one in each pathway) or a single defect that can explain both abnormalities in skeletal muscle glucose processing. Measurement of intracellular G-6-P has been used to answer this question, based on the assumption that a reduced concentration of G-6-P would indicate that glucose transport was rate limiting (and therefore could determine the rate of glycogen synthesis). Conversely, an increased G-6-P would indicate a rate-determining defect in glycogen synthesis. However, the methods to estimate G-6-P have been questioned as well as the conditions under which G-6-P has been investigated. In order to use G-6-P as a discriminator between defects in the two pathways, the glucose flow through the G-6-P pool must be identical in the situations compared, i.e. in normal versus diabetic. However, this is not the case in most situations. Therefore, at the present time, it is not possible to confidently distinguish between these two theories by measuring G-6-P. An alternative view is that a reduced activity of the phosphatidylinositol 3-kinase (PI-3-K) links the reduced glucose transport and reduced glycogen synthase activities.65, 68, 69 However, not all studies find that PI-3-K activity is reduced in insulin-resistant muscle.70 Furthermore, the importance of this signal protein for activation of the glycogen synthase, even in normal subjects, has been questioned.71 Besides the PI-3-K, no other signalling proteins have been found to convincingly explain insulin resistance in skeletal muscle, although a few reports on separate candidate proteins, e.g. PKB/Akt, have been published.72 Thus, with the exception of the PI-3-K, which in some situations may play a role, defects in the classical insulin-signalling cascade may not explain insulin resistance in skeletal muscle in humans. The number of GLUT4 transporters in muscle biopsies of mixed fibre types (intracellular plus the membrane pool) has been found to be normal in insulinresistant states. However, recent data from our group clearly indicate that the

INSULIN-RESISTANT STATES

167

number of transporters in most insulin-sensitive fibres, namely type 1 fibres, is reduced.73 A reduction in the number of GLUT4 transporters per cell could therefore be a primary defect in insulin-resistant skeletal muscle. Insulin activates the enzyme glycogen synthase by consecutive dephosphorylation of the serine residues located at sites 1, 2 and 3. Therefore, changes in regulation of the phosphorylation status of the enzyme itself may play a primary pathophysiological role in the development of insulin resistance. Using antityrosine antibodies, our group has for the first time been able to measure the phosphorylation status of glycogen synthase. The results indicate that in T2D site 2 cannot be desphosphorylated during insulin stimulation, and site 2 is in fact hyperphosphorylated in skeletal muscle from type 2 diabetic subjects.51 This defect appears not to be secondary to changes in the insulin signalling pathway and therefore could be of primary origin. However, it may also be a secondary phenomenon: for example to intracellular fat accumulation or the hyperglycaemia itself, as discussed below. In conclusion, several defects in glucose processing intracellularly can explain the defects in insulin stimulation, i.e. insulin resistance, and these defects may have both primary (genetic) and secondary origin (fat accumulation and/or glucose toxicity). To date, no single factor appears to be able to account for all the defects present in insulin-resistant skeletal muscle. An obvious scenario could therefore be that genetic defects could explain the early defects of insulin action and that the insulin resistance, which develops later in the natural history of metabolic syndrome, is secondary to the metabolic abnormalities themselves.

Primary/genetic defects in insulin action in skeletal muscle By using cultured myotubes grown from satellite cells from human skeletal muscle, it is possible in vitro to study primary defects in insulin action, since metabolic defects preserved after several passages under ‘physiological’ conditions (physiological concentrations ex vivo of glucose, insulin, etc.) may represent a primary defect(s) and probably is/are of genetic origin. Using this model, we found that defects in both glucose uptake and glycogen synthesis were preserved when studying muscle biopsies from type 2 diabetic subjects.74 The reduced glucose transport was found only in the basal state, which is in accordance with a reduced number of GLUT4 transporters. The defect in activation of glycogen synthase only took place after insulin stimulation, and was mainly a defect in the covalent activation (Figure 6.5). In contrast, glucose oxidation was found to be normal. These data clearly indicate that there are both primary and probably genetic defects in the number of GLUT4 transporters and in the activation of glycogen synthase. These data fit with our in vivo data and confirm that insulin resistance in skeletal muscle may have both a genetic and a metabolic component involving skeletal muscle glucose transport and glycogen synthesis.

168

INSULIN RESISTANCE IN GLUCOSE DISPOSAL AND PRODUCTION IN MAN 0.3 bc *

bc *

bc bc bc

0.2 ∆Fv0.1 (%)

bc

b

0.1 b

b b ab

a

c ab

0 –14

–12 –10 –8 log insulin concentration (mol/l)

a –6

Figure 6.5 The effect of insulin at different concentrations on glycogen synthase activation in cultured myotubes from obese type 2 diabetic subjects and controls. The curves show the difference (insulin-stimulated minus basal values) in glycogen synthase activity in obese type 2 diabetic subjects and in controls (reproduced with permission from Gaster et al. (2002) Diabetes 51, 921–92774 )

Secondary defects in insulin action in skeletal muscle Raised intramyofibril tryglyceride and long chain acyl CoA concentrations are found in skeletal muscle from insulin-resistant obese subjects, normal glucose tolerant relatives of T2D and type 2 diabetic subjects.49 This accumulation of intramyofibrillar fat may be a primary defect of the muscle resistance or be secondary to the obesity itself. Regardless of its origin, the fat accumulation appears to directly affect muscle insulin action and lead to metabolic insulin resistance, as discussed in Chapter 8. These findings explain why insulin resistance is so common in obese subjects.

Pathophysiology Insulin resistance in skeletal muscle usually leads to compensatory hyperinsulinaemia, which may itself play a pathophysiological role in the development of the metabolic syndrome. If β-cell function declines, hyperglycaemia develops and T2D is manifest.27

Insulin resistance of hepatic glucose production (in vivo insulin resistance) Hepatic insulin resistance appears well documented in T2D. This is based on numerous studies that found markedly elevated basal glucose production rates

INSULIN-RESISTANT STATES

169

in T2D. Since this elevation was in direct proportion to fasting glucose levels, hepatic insulin resistance was believed to be of central importance for the development of fasting hyperglycaemia in T2D. It is now known that, using an appropriate tracer priming technique with adjustment for the level of fasting hyperglycaemia75, 76 or a more appropriate mathematical modelling approach,77 the basal glucose production is normal or only slightly elevated in T2D.78, 79, 41, 80 However, since both elevated fasting glucose and insulin levels would normally suppress glucose production, the presence of normal or slightly elevated basal glucose production rates in T2D may be suggestive of hepatic insulin resistance. Similarly, normal basal glucose production rates and fasting hyperinsulinaemia in obesity and metabolic syndrome are compatible with hepatic insulin resistance. However, evidence from basal turnover measurements is not all inclusive of factors impacting on hepatic glucose production. In vivo, many other factors, besides insulin, may influence regulation of hepatic glucose production, and the basal fasting state in T2D may be regarded as a compensated situation where these other factors compensate for insulin resistance in order to maintain normal glucose metabolic rates.81, 82 Therefore, for evaluation of in vivo hepatic insulin sensitivity it may be necessary to measure the response to insulin, e.g. by using the clamp technique. Assessment of hepatic insulin sensitivity is further complicated by the fact that suppression of glucose production is not only determined by the direct action of insulin on the liver cell but also through indirect effects of insulin via suppression of lipolysis in adipocytes, suppression of glucagon secretion from the pancreatic α-cells and suppression of gluconeogenic substrate supply from muscle and other tissues.83 – 86 Using state of the art tracer technique (adequately primed constant tracer infusion in combination with labelled glucose infusates for maintenance of constant specific activity),76, 16, 87 we have evaluated hepatic insulin sensitivity in obese type 2 diabetic patients in comparison with matched control subjects.41 The diabetic patients were maintained normoglycaemic overnight before studies by a small intravenous insulin infusion in order to avoid the confounding influence of different glucose levels during the clamp studies. The insulin dose response (Figure 6.3) illustrates that hepatic insulin resistance in T2D is mainly expressed at low insulin levels below 40–50 mU/l. Suppression in the type 2 diabetic subjects was impaired at insulin levels of 30 mU/l. Basal glucose production was slightly elevated (13 per cent), but this occurred at much higher insulin levels than in control subjects. Somewhat surprisingly, glucose production in the type 2 diabetic subjects was suppressed rapidly when insulin was increased by only 10 mU/l from 20 to 30 mU/l. A similar effect has been observed by Turk et al.,88 and may represent a defect in the direct effect of insulin on glycogenolysis, which expresses itself as a right shift in the insulin dose–response curve. Cherrington and co-workers have shown that glycogenolysis is very sensitive to small increases in insulin whereas gluconeogenic flux is not.89 Furthermore, glycogenolysis is already markedly suppressed at basal insulin levels.85 Using a

170

INSULIN RESISTANCE IN GLUCOSE DISPOSAL AND PRODUCTION IN MAN

different approach Lewis et al.90 also found evidence of resistance to the direct suppressive effect of insulin on hepatic glucose production in T2D. In addition, we found that suppression of both plasma FFA and glucagon levels were markedly impaired in T2D (Figure 6.3).41 This may reflect impaired insulinmediated suppression of lipolysis in adipocytes and impaired suppression of glucagon secretion from the α-cells. Since elevated FFA levels per se have been shown to stimulate both glycogenolysis as well as gluconeogenesis,91, 92 impaired insulin-mediated suppression of FFA may obviously influence hepatic insulin sensitivity. Similarly, because hepatic glucagon sensitivity is normal in T2D,93, 94 impaired insulin-mediated suppression of glucagon secretion may also influence hepatic insulin sensitivity.95 Using the tracer technique in combination with the 2 H2 O technique, Gastaldelli et al. have quantitated gluconeogenesis in obesity and in T2D. In obese subjects, the gluconeogenic rate was directly related to the degree of obesity,96 and in clamp studies of type 2 diabetic subjects gluconeogenic fluxes were elevated in the basal state and suppression in response to insulin was markedly impaired during the clamp.97 Thus, from in vivo studies, there is evidence of hepatic insulin resistance both in the direct and in the indirect actions (through FFA and glucagon), and both in the glycogenolytic and in the gluconeogenic pathways.

Biochemical defects in hepatic insulin action Control of hepatic glucose output may occur through regulation of gluconeogenesis or glycogenolysis. However, glucose-6-phosphatase [G6Pase] and glucokinase [GK] are believed to play prominent roles in the regulation of glucose production by controlling the rate of glucose efflux and uptake in hepatocytes. The competing activity between the two enzymes has been described as the glucose cycle and represents an important potential site of regulation.98 Glucose cycling has been found to be increased in mild T2D.98 Insulin sensitivity of the glucose cycle is reduced in obese non-diabetic and more so in obese type 2 diabetic patients,99 suggesting that G6Pase activity is increased in both groups.99 This increased activity may be secondary to a decreased insulin-induced suppression of the enzyme activity at the level of the liver cell. Alternatively, it may possibly be secondary to the increased peripheral lipolysis and enhanced plasma FFA concentrations, since chronically elevated plasma FFAs have been shown to enhance liver G6Pase gene expression.100 Moreover, in liver biopsies from type 2 diabetic patients, G6Pase activity has been found to be increased101 and GK activity to be reduced.101, 102

Increased hepatic VLDL production Another important aspect of hepatic insulin resistance is an atherogenic dyslipidaemia profile characterized by hypertriglyceridaemia, low plasma HDLcholesterol and raised small dense LDL-cholesterol profile. The physiologic

CONCLUSION AND PERSPECTIVES

171

basis for this metabolic dyslipidaemia appears to be hepatic overproduction of apoB-containing VLDL particles, which may result from a composite set of factors including increased flux of FFAs from adipose tissue to the liver and directly from lipoprotein remnant uptake, increased de novo fatty acid synthesis, preferential esterification versus oxidation of fatty acids, reduced post-translational degradation of apo-B and overexpression of microsomal triglyceride transfer protein (MTP).103, 104 These conditions, together with resistance to the normal suppressive effect of insulin on VLDL secretion, act in concert to channel fatty acids into secretory and storage rather than degradative pathways.105, 106

Primary/genetic defects in insulin action in liver Whether hepatic insulin resistance is a primary trait or a secondary phenomenon is as yet undetermined. However, if hepatic insulin resistance is a secondary phenomenon it may be reversible. Given the serious consequences of hepatic insulin resistance, both for glucose metabolism and, in particular, for development of dyslipidaemia, the answer to this question and possible rational treatments might be quite important.

6.4 Conclusion and perspectives Insulin resistance in glucose disposal and production seems to play an important role for the development of the metabolic syndrome and T2D. Both diseases dispose to cardiovascular disease and cardiovascular mortality. Therefore, insulin resistance may be considered as a serious risk factor in the modern society, and because insulin resistance is in itself symptomless it has been named ‘the secret killer’. In this short description of insulin resistance, and glucose disposal and hepatic glucose production, we have focused on various aspects of methodologies to measure insulin resistance, in order to alert researchers and clinicians to the importance of accurate diagnosis of insulin resistance. We have also focused on the potential cellular mechanisms that could explain the development of insulin resistance. In skeletal muscle, insulin-mediated glucose disposal is clearly dependent on glycogen synthesis. This pathway is impaired, due to hyperphosphorylation of the key enzyme, glycogen synthase. Therefore, regulation of glycogen synthase activity may be central to our understanding of insulin resistance in the metabolic syndrome and T2D. We believe that obesity is linked to insulin resistance, metabolic syndrome and T2D, through the accumulation of lipids, particularly long chain acylCoAs in the skeletal muscle, and that these intracellular fatty acids and triglycerides may directly inhibit the dephosphorylation of glycogen synthase and thereby impair glucose disposal. Thus, future studies will need to examine the relationship between intramyofibril lipid accumulation, skeletal muscle glycogen synthase activity and GLUT4

172

INSULIN RESISTANCE IN GLUCOSE DISPOSAL AND PRODUCTION IN MAN

translocation. Although hepatic insulin resistance may play only a minor role in the development of the metabolic syndrome per se, the role of the liver in the dyslipidaemia of the syndrome is important. Also, the altered peripheral regulation of FFAs and their effect on hepatic glyconeogenesis and glycogenolysis is a critical factor in the dysregulation of glucose metabolism in the metabolic syndrome. These latter observations also highlight the importance of a direct effect of peripheral insulin resistance on hepatic glucose production and hepatic insulin resistance. Finally, as mentioned, the increased secretion of lipoproteins from the liver represents a vital link between hepatic insulin resistance and the arteriosclerosis and cardiovascular diseases of the metabolic syndrome. Therefore, the relationship between insulin resistance in the liver and lipoprotein turnover remains an important area of future research.

References 1. Freychet, P., Roth, J. and Neville, D. M., Jr. (1971) Insulin receptors in the liver: specific binding of (125 I) insulin to the plasma membrane and its relation to insulin bioactivity. Proc Natl Acad Sci USA 68, 1833–1837. 2. Himsworth, H. P. and Kerr, R. B. (1939) Insulin-sensitive and insulin insensitive types of diabetes mellitus. Clin Sci 4, 119–152. 3. Yalow, R. S. and Berson, S. A. (1960) Plasma insulin concentrations in nondiabetic and early diabetic subjects. Determinations by a new sensitive immuno-assay technic. Diabetes 9, 254–260. 4. Ferrannini, E. (1998) Insulin resistance versus insulin deficiency in non-insulindependent diabetes mellitus: problems and prospects. Endocr Rev 19, 477–490. 5. Beck-Nielsen, H. and Groop, L. C. (1994) Metabolic and genetic characterization of prediabetic states. Sequence of events leading to non-insulin-dependent diabetes mellitus. J Clin Invest 94, 1714–1721. 6. Matthaei, S., Stumvoll, M., Kellerer, M. and Haring, H. U. (2000) Pathophysiology and pharmacological treatment of insulin resistance. Endocr Rev 21, 585–618. 7. Reaven, G. M. (1995) Pathophysiology of insulin resistance in human disease. Physiol Rev 75, 473–486. 8. Radziuk, J. (2000) Insulin sensitivity and its measurement: structural commonalities among the methods. J Clin Endocrinol Metab 85, 4426–4433. 9. Wallace, T. M. and Matthews, D. R. (2002) The assessment of insulin resistance in man. Diabet Med 19, 527–534. 10. Bergman, R. N., Finegood, D. T. and Ader, M. (1985) Assessment of insulin sensitivity in vivo. Endocr Rev 6, 45–86. 11. Best, J. D., Kahn, S. E., Ader, M., Watanabe, R. M., Ni, T. C. and Bergman, R. N. (1996) Role of glucose effectiveness in the determination of glucose tolerance. Diabetes Care 19, 1018–1030. 12. Kahn, S. E., Prigeon, R. L., McCulloch, D. K., Boyko, E. J., Bergman, R. N., Schwartz, M. W., Neifing, J. L., Ward, W. K., Beard, J. C. and Palmer, J. P., et al. (1993) Quantification of the relationship between insulin sensitivity and beta-cell function in human subjects. Evidence for a hyperbolic function. Diabetes 42, 1663–1672. 13. Matthews, D. R., Hosker, J. P., Rudenski, A. S., Naylor, B. A., Treacher, D. F. and Turner, R. C. (1985) Homeostasis model assessment: insulin resistance and beta-cell

REFERENCES

14.

15. 16.

17. 18.

19.

20. 21. 22.

23.

24.

25.

26.

27.

28. 29.

30.

173

function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28, 412–419. Katz, A., Nambi, S. S., Mather, K., Baron, A. D., Follmann, D. A., Sullivan, G. and Quon, M. J. (2000) Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab 85, 2402–2410. DeFronzo, R. A., Tobin, J. D. and Andres, R. (1979) Glucose clamp technique: a method for quantifying insulin secretion and resistance. Am J Physiol 237, E214–E223. Hother-Nielsen, O., Henriksen, J. E., Holst, J. J. and Beck Nielsen, H. (1996) Effects of insulin on glucose turnover rates in vivo: isotope dilution versus constant specific activity technique. Metabolism 45, 82–91. Scheen, A. J., Paquot, N., Castillo, M. J. and Lefebvre, P. J. (1994) How to measure insulin action in vivo. Diabetes Metab Rev 10, 151–188. Landau, B. R., Wahren, J., Chandramouli, V., Schumann, W. C., Ekberg, K. and Kalhan, S. C. (1996) Contributions of gluconeogenesis to glucose production in the fasted state. J Clin Invest 98, 378–385. Chandramouli, V., Ekberg, K., Schumann, W. C., Kalhan, S. C., Wahren, J. and Landau, B. R. (1997) Quantifying gluconeogenesis during fasting. Am J Physiol 273, E1209–E1215. Ferrannini, E. (1988) The theoretical bases of indirect calorimetry: a review. Metabolism 37, 287–301. Kelley, D. E. and Mandarino, L. J. (2000) Fuel selection in human skeletal muscle in insulin resistance: a reexamination. Diabetes 49, 677–683. Rossetti, L. and Giaccari, A. (1990) Relative contribution of glycogen synthesis and glycolysis to insulin-mediated glucose uptake. A dose–response euglycemic clamp study in normal and diabetic rats. J Clin Invest 85, 1785–1792. Blaak, E. E., Wagenmakers, A. J., Glatz, J. F., Wolffenbuttel, B. H., Kemerink, G. J., Langenberg, C. J., Heidendal, G. A. and Saris, W. H. (2000) Plasma FFA utilization and fatty acid-binding protein content are diminished in type 2 diabetic muscle. Am J Physiol Endocrinol Metab 279, E146–E154. Christopher, M. J., Rantzau, C., Ward, G. M. and Alford, F. P. (1994) Impact of variable insulinemia and glycemia on in vivo glycolysis and glucose storage in dogs. Am J Physiol 266, E62–71. Rossetti, L., Lee, Y. T., Ruiz, J., Aldridge, S. C., Shamoon, H. and Boden, G. (1993) Quantitation of glycolysis and skeletal muscle glycogen synthesis in humans. Am J Physiol 265, E761–E769. Del Prato, S., Bonadonna, R. C., Bonora, E., Gulli, G., Solini, A., Shank, M. and DeFronzo, R. A. (1993) Characterization of cellular defects of insulin action in type 2 (non-insulin-dependent) diabetes mellitus. J Clin Invest 91, 484–494. Vaag, A., Alford, F., Henriksen, F. L., Christopher, M. and Beck Nielsen, H. (1995) Multiple defects of both hepatic and peripheral intracellular glucose processing contribute to the hyperglycaemia of NIDDM. Diabetologia 38, 326–336. Bergman, R. N., Ider, Y. Z., Bowden, C. R. and Cobelli, C. (1979) Quantitative estimation of insulin sensitivity. Am J Physiol 236, E667–E677. Weber, K. M., Martin, I. K., Best, J. D., Alford, F. P. and Boston, R. C. (1989) Alternative method for minimal model analysis of intravenous glucose tolerance data. Am J Physiol 256, E524–E535. Finegood, D. T. and Tzur, D. (1996) Reduced glucose effectiveness associated with reduced insulin release: an artifact of the minimal-model method. Am J Physiol 271, E485–E495.

174

INSULIN RESISTANCE IN GLUCOSE DISPOSAL AND PRODUCTION IN MAN

31. Vicini, P., Caumo, A. and Cobelli, C. (1997) The hot IVGTT two-compartment minimal model: indexes of glucose effectiveness and insulin sensitivity. Am J Physiol 273, E1024–E1032. 32. Bergman, R. N., Prager, R., Volund, A. and Olefsky, J. M. (1987) Equivalence of the insulin sensitivity index in man derived by the minimal model method and the euglycemic glucose clamp. J Clin Invest 79, 790–800. 33. Henriksen, J. E., Alford, F., Handberg, A., Vaag, A. and Beck Nielsen, H. (1996) Glucose processing during the intravenous glucose tolerance test. Metabolism 45, 598–605. 34. Ward, G. M., Walters, J. M., Barton, J., Alford, F. P. and Boston, R. C. (2001) Physiologic modeling of the intravenous glucose tolerance test in type 2 diabetes: a new approach to the insulin compartment. Metabolism 50, 512–519. 35. Ward, G. M., Weber, K. M., Walters, I. M., Aitken, P. M., Lee, B., Best, J. D., Boston, R. C. and Alford, F. P. (1991) A modified minimal model analysis of insulin sensitivity and glucose-mediated glucose disposal in insulin-dependent diabetes. Metabolism 40, 4–9. 36. Henriksen, J. E., Alford, F., Handberg, A., Vaag, A., Ward, G. M., Kalfas, A. and Beck-Nielsen, H. (1994) Increased glucose effectiveness in normoglycemic but insulinresistant relatives of patients with non-insulin-dependent diabetes mellitus. A novel compensatory mechanism. J Clin Invest 94, 1196–1204. 37. Martin, B. C., Warram, J. H., Krolewski, A. S., Bergman, R. N., Soeldner, J. S. and Kahn, C. R. (1992) Role of glucose and insulin resistance in development of type 2 diabetes mellitus: results of a 25-year follow-up study. Lancet 340, 925–929. 38. Galvin, P., Ward, G., Walters, J., Pestell, R., Koschmann, M., Vaag, A., Martin, I., Best, J. D. and Alford, F. (1992) A simple method for quantitation of insulin sensitivity and insulin release from an intravenous glucose tolerance test. Diabet Med 9, 921–928. 39. Anderson, R. L., Hamman, R. F., Savage, P. J., Saad, M. F., Laws, A., Kades, W. W., Sands, R. E. and Cefalu, W. (1995) Exploration of simple insulin sensitivity measures derived from frequently sampled intravenous glucose tolerance (FSIGT) tests. The Insulin Resistance Atherosclerosis Study. Am J Epidemiol 142, 724–732. 40. Alberti, K. G. and Zimmet, P. Z. (1998) Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation [see comments]. Diabet Med 15, 539–553. 41. Staehr, P., Hother-Nielsen, O., Levin, K., Holst, J. J. and Beck-Nielsen, H. (2001) Assessment of hepatic insulin action in obese type 2 diabetic patients. Diabetes 50, 1363–1370. 42. Shulman, G. I., Rothman, D. L., Jue, T., Stein, P., DeFronzo, R. A. and Shulman, R. G. (1990) Quantitation of muscle glycogen synthesis in normal subjects and subjects with non-insulin-dependent diabetes by 13C nuclear magnetic resonance spectroscopy. N Engl J Med 322, 223–228. 43. DeFronzo, R. A., Jacot, E., Jequier, E., Maeder, E., Wahren, J. and Felber, J. P. (1981) The effect of insulin on the disposal of intravenous glucose. Results from indirect calorimetry and hepatic and femoral venous catheterization. Diabetes 30, 1000–1007. 44. Thiebaud, D., Jacot, E., DeFronzo, R. A., Maeder, E., Jequier, E. and Felber, J. P. (1982) The effect of graded doses of insulin on total glucose uptake, glucose oxidation, and glucose storage in man. Diabetes 31, 957–963. 45. Mandarino, L. J., Wright, K. S., Verity, L. S., Nichols, J., Bell, J. M., Kolterman, O. G. and Beck-Nielsen, H. (1987) Effects of insulin infusion on human skeletal muscle pyruvate dehydrogenase, phosphofructokinase, and glycogen synthase. Evidence for their role in oxidative and nonoxidative glucose metabolism. J Clin Invest 80, 655–663.

REFERENCES

175

46. Young, A. A., Bogardus, C., Wolfe Lopez, D. and Mott, D. M. (1988) Muscle glycogen synthesis and disposition of infused glucose in humans with reduced rates of insulinmediated carbohydrate storage. Diabetes 37, 303–308. 47. Thorburn, A. W., Gumbiner, B., Brechtel, G. and Henry, R. R. (1990) Effect of hyperinsulinemia and hyperglycemia on intracellular glucose and fat metabolism in healthy subjects. Diabetes 39, 22–30. 48. Yki-Jarvinen, H., Bogardus, C. and Howard, B. V. (1987) Hyperglycemia stimulates carbohydrate oxidation in humans. Am J Physiol 253, E376–E382. 49. Levin, K., Daa, S. H., Alford, F. P. and Beck-Nielsen, H. (2001) Morphometric documentation of abnormal intramyocellular fat storage and reduced glycogen in obese patients with Type II diabetes. Diabetologia 44, 824–833. 50. Damsbo, P., Vaag, A., Hother-Nielsen, O. and Beck-Nielsen, H. (1991) Reduced glycogen synthase activity in skeletal muscle from obese patients with and without type 2 (non-insulin-dependent) diabetes mellitus. Diabetologia 34, 239–245. 51. Højlund, K., Staehr, P., Hansen, B. F., Green, K. A., Hardie, D. G., Richter, E. A., Beck-Nielsen, H. and Wojtaszewski, J. F. (2003) Increased phosphorylation of skeletal muscle glycogen synthase at NH2-terminal sites during physiological hyperinsulinemia in type 2 diabetes. Diabetes 52, 1393–1402. 52. Vaag, A., Alford, F. and Beck-Nielsen, H. (1996) Intracellular glucose and fat metabolism in identical twins discordant for non-insulin-dependent diabetes mellitus (NIDDM): acquired versus genetic metabolic defects? Diabet Med 13, 806–815. 53. Golay, A., DeFronzo, R. A., Ferrannini, E., Simonson, D. C., Thorin, D., Acheson, K., Thiebaud, D., Curchod, B., Jequier, E. and Felber, J. P. (1988) Oxidative and nonoxidative glucose metabolism in non-obese type 2 (non-insulin-dependent) diabetic patients. Diabetologia 31, 585–591. 54. Groop, L. C., Bonadonna, R. C., DelPrato, S., Ratheiser, K., Zyck, K., Ferrannini, E. and DeFronzo, R. A. (1989) Glucose and free fatty acid metabolism in non-insulindependent diabetes mellitus. Evidence for multiple sites of insulin resistance. J Clin Invest 84, 205–213. 55. Felber, J. P., Golay, A., Felley, C. and Jequier, E. (1988) Regulation of glucose storage in obesity and diabetes: metabolic aspects. Diabetes Metab Rev 4, 691–700. 56. Thorburn, A. W., Gumbiner, B., Bulacan, F., Wallace, P. and Henry, R. R. (1990) Intracellular glucose oxidation and glycogen synthase activity are reduced in noninsulin-dependent (type II) diabetes independent of impaired glucose uptake. J Clin Invest 85, 522–529. 57. Randle, P. J., Garland, P. B., Hales, C. N. and Newsholme, E. A. (1963) The glucose fatty-acid cycle. Its role in insulin sensitivity and the metabolic disturbances of diabetes mellitus. Lancet 1, 785–789. 58. Boden, G., Jadali, F., White, J., Liang, Y., Mozzoli, M., Chen, X., Coleman, E. and Smith, C. (1991) Effects of fat on insulin-stimulated carbohydrate metabolism in normal men. J Clin Invest 88, 960–966. 59. Roden, M., Price, T. B., Perseghin, G., Petersen, K. F., Rothman, D. L., Cline, G. W. and Shulman, G. I. (1996) Mechanism of free fatty acid-induced insulin resistance in humans. J Clin Invest 97, 2859–2865. 60. Kelley, D. E., Mokan, M., Simoneau, J. A. and Mandarino, L. J. (1993) Interaction between glucose and free fatty acid metabolism in human skeletal muscle. J Clin Invest 92, 91–98. 61. Andres, R., Cadar, G. and Zierler, K. (1956) The quantitative minor role of oxidative metabolism by skeletal muscle in intact man in the basal state. J Clin Invest 35, 671–682.

176

INSULIN RESISTANCE IN GLUCOSE DISPOSAL AND PRODUCTION IN MAN

62. Colberg, S. R., Simoneau, J. A., Thaete, F. L. and Kelley, D. E. (1995) Skeletal muscle utilization of free fatty acids in women with visceral obesity [see comments]. J Clin Invest 95, 1846–1853. 63. Kelley, D. E., Goodpaster, B., Wing, R. R. and Simoneau, J. A. (1999) Skeletal muscle fatty acid metabolism in association with insulin resistance, obesity, and weight loss. Am J Physiol 277, E1130–E1141. 64. Kelley, D. E. and Simoneau, J. A. (1994) Impaired free fatty acid utilization by skeletal muscle in non-insulin-dependent diabetes mellitus. J Clin Invest 94, 2349–2356. 65. Shulman, G. I. (2000) Cellular mechanisms of insulin resistance. J Clin Invest 106, 171–176. 66. Zierath, J. R., Krook, A. and Wallberg-Henriksson, H. (2000) Insulin action and insulin resistance in human skeletal muscle. Diabetologia 43, 821–835. 67. Lund, S., Pedersen, O., Holman, G. D., Clark, A. E., Zierath, J. R. and WallbergHenriksson, H. (1997) GLUT4 translocation in human muscle strips. Biochem Soc Trans 25, 466S. 68. Dresner, A., Laurent, D., Marcucci, M., Griffin, M. E., Dufour, S., Cline, G. W., Slezak, L. A., Andersen, D. K., Hundal, R. S., Rothman, D. L., Petersen, K. F. and Shulman, G. I. (1999) Effects of free fatty acids on glucose transport and IRS-1associated phosphatidylinositol 3-kinase activity. J Clin Invest 103, 253–259. 69. Krook, A., Bjornholm, M., Galuska, D., Jiang, X. J., Fahlman, R., Myers, M. G., Jr., Wallberg-Henriksson, H. and Zierath, J. R. (2000) Characterization of signal transduction and glucose transport in skeletal muscle from type 2 diabetic patients. Diabetes 49, 284–292. 70. Meyer, M. M., Levin, K., Grimmsmann, T., Beck-Nielsen, H. and Klein, H. H. (2002) Insulin signalling in human skeletal muscle of subjects with or without Type II-diabetes and first degree relatives of patients with the disease. Diabetologia 45, 813–822. 71. Grimmsmann, T., Levin, K., Meyer, M. M., Beck-Nielsen, H. and Klein, H. H. (2002) Delays in insulin signaling towards glucose disposal in human skeletal muscle. J Endocrinol 172, 645–651. 72. Krook, A., Roth, R. A., Jiang, X. J., Zierath, J. R. and Wallberg-Henriksson, H. (1998) Insulin-stimulated Akt kinase activity is reduced in skeletal muscle from NIDDM subjects. Diabetes 47, 1281–1286. 73. Gaster, M., Staehr, P., Beck-Nielsen, H., Schroder, H. D. and Handberg, A. (2001) GLUT4 is reduced in slow muscle fibers of type 2 diabetic patients: is insulin resistance in type 2 diabetes a slow, type 1 fiber disease? Diabetes 50, 1324–1329. 74. Gaster, M., Petersen, I., Hojlund, K., Poulsen, P. and Beck-Nielsen, H. (2002) The diabetic phenotype is conserved in myotubes established from diabetic subjects: evidence for primary defects in glucose transport and glycogen synthase activity. Diabetes 51, 921–927. 75. Hother-Nielsen, O. and Beck-Nielsen, H. (1990) On the determination of basal glucose production rate in patients with type 2 (non-insulin-dependent) diabetes mellitus using primed-continuous 3-3H-glucose infusion. Diabetologia 33, 603–610. 76. Hother-Nielsen, O. (1996) Constant tracer infusion technique for assessment of glucose turnover in vivo: current status. In: Marshall SM, Home PD, Rizza RA, eds. Diabetes Annual/10. Amsterdam: Elsevier, 301–336. 77. Radziuk, J. and Pye, S. (2002) Quantitation of basal endogenous glucose production in Type II diabetes: importance of the volume of distribution. Diabetologia 45, 1053–1084. 78. Hother-Nielsen, O. and Beck-Nielsen, H. (1991) Insulin resistance, but normal basal rates of glucose production in patients with newly diagnosed mild diabetes mellitus. Acta Endocrinol Copenh 124, 637–645.

REFERENCES

177

79. Hother-Nielsen, O. and Beck-Nielsen, H. (1991) Basal glucose metabolism in type 2 diabetes. A critical review. Diabet Metab 17, 136–145. 80. Rigalleau, V., Beylot, M., Laville, M., Guillot, C., Deleris, G., Aubertin, J. and Gin, H. (1996) Measurement of post-absorptive glucose kinetics in non-insulin-dependent diabetic patients: methodological aspects. Eur J Clin Invest 26, 231–236. 81. Beck-Nielsen, H., Hother-Nielsen, O., Vaag, A. and Alford, F. (1994) Pathogenesis of type 2 (non-insulin-dependent) diabetes mellitus: the role of skeletal muscle glucose uptake and hepatic glucose production in the development of hyperglycaemia. A critical comment. Diabetologia 37, 217–221. 82. Beck-Nielsen, H., Hother-Nielsen, O. and Staehr, P. (2002) Is hepatic glucose production increased in Type 2 diabetes mellitus? Curr Diabetes Rep 2 (3), 231–236. 83. Vranic, M. (1992) Banting Lecture: Glucose turnover. A key to understanding the pathogenesis of diabetes (indirect effects of insulin). Diabetes 41, 1188–1206. 84. Giacca, A., Fisher, S. J., Shi, Z. Q., Gupta, R., Lickley, H. L. and Vranic, M. (1992) Importance of peripheral insulin levels for insulin-induced suppression of glucose production in depancreatized dogs. J Clin Invest 90, 1769–1777. 85. Cherrington, A. D., Edgerton, D. and Sindelar, D. K. (1998) The direct and indirect effects of insulin on hepatic glucose production in vivo. Diabetologia 41, 987–996. 86. Cherrington, A. D. (1999) Banting Lecture 1997. Control of glucose uptake and release by the liver in vivo. Diabetes 48, 1198–1214. 87. Hother-Nielsen, O., Henriksen, J. E., Staehr, P. and Beck-Nielsen, H. (1995) Labelled glucose infusate technique in clamp studies. Is precise matching of glucose specific activity important? Endocrinol Metab 2, 275–287. 88. Turk, D., Alzaid, A., Dinneen, S., Nair, K. S. and Rizza, R. (1995) The effects of noninsulin-dependent diabetes mellitus on the kinetics of onset of insulin action in hepatic and extrahepatic tissues. J Clin Invest 95, 755–762. 89. Edgerton, D. S., Cardin, S., Emshwiller, M., Neal, D., Chandramouli, V., Schumann, W. C., Landau, B. R., Rossetti, L. and Cherrington, A. D. (2001) Small increases in insulin inhibit hepatic glucose production solely caused by an effect on glycogen metabolism. Diabetes 50, 1872–1882. 90. Lewis, G. F., Carpentier, A., Vranic, M. and Giacca, A. (1999) Resistance to insulin’s acute direct hepatic effect in suppressing steady-state glucose production in individuals with type 2 diabetes. Diabetes 48, 570–576. 91. Staehr, P., Hother-Nielsen, O., Landau, B. R., Chandramouli, V., Holst, J. J. and BeckNielsen, H. (2003) Effects of free fatty acids per se on glucose production, gluconeogenesis, and glycogenolysis. Diabetes 52, 260–267. 92. Boden, G., Cheung, P., Stein, T. P., Kresge, K. and Mozzoli, M. (2002) FFA cause hepatic insulin resistance by inhibiting insulin suppression of glycogenolysis. Am J Physiol Endocrinol Metab 283, E12–E19. 93. Matsuda, M., DeFronzo, R. A., Glass, L., Consoli, A., Giordano, M., Bressler, P. and DelPrato, S. (2002) Glucagon dose–response curve for hepatic glucose production and glucose disposal in type 2 diabetic patients and normal individuals. Metabolism 51, 1111–1119. 94. Nielsen, M. F., Wise, S., Dinneen, S. F., Schwenk, W. F., Basu, A. and Rizza, R. A. (1997) Assessment of hepatic sensitivity to glucagon in NIDDM: use as a tool to estimate the contribution of the indirect pathway to nocturnal glycogen synthesis. Diabetes 46, 2007–2016. 95. Shah, P., Vella, A., Basu, A., Basu, R., Schwenk, W. F. and Rizza, R. A. (2000) Lack of suppression of glucagon contributes to postprandial hyperglycemia in subjects with type 2 diabetes mellitus. J Clin Endocrinol Metab 85, 4053–4059.

178

INSULIN RESISTANCE IN GLUCOSE DISPOSAL AND PRODUCTION IN MAN

96. Gastaldelli, A., Baldi, S., Pettiti, M., Toschi, E., Camastra, S., Natali, A., Landau, B. R. and Ferrannini, E. (2000) Influence of obesity and type 2 diabetes on gluconeogenesis and glucose output in humans: a quantitative study. Diabetes 49, 1367–1373. 97. Gastaldelli, A., Toschi, E., Pettiti, M., Frascerra, S., Quinones-Galvan, A., Sironi, A. M., Natali, A. and Ferrannini, E. (2001) Effect of physiological hyperinsulinemia on gluconeogenesis in nondiabetic subjects and in type 2 diabetic patients. Diabetes 50, 1807–1812. 98. Efendic, S., Karlander, S. and Vranic, M. (1998) Mild type II diabetes markedly increases glucose cycling in the postabsorptive state and during glucose infusion irrespective of obesity. J Clin Invest 81, 1953–1961. 99. Paquot, N., Scheen, A. J., Dirlewanger, M., Lefebvre, P. J. and Tappy, L. (2002) Hepatic insulin resistance in obese non-diabetic subjects and in type 2 diabetic patients. Obes Res 10, 129–134. 100. Massillon, D., Barzilai, N., Hawkins, M., Prus-Wertheimer, D. and Rossetti, L. (1997) Induction of hepatic glucose-6-phosphatase gene expression by lipid infusion [published erratum appears in Diabetes 1997 Mar; 46 (3): 536]. Diabetes 46, 153–157. 101. Clore, J. N., Stillman, J. and Sugerman, H. (2000) Glucose-6-phosphatase flux in vitro is increased in type 2 diabetes. Diabetes 49, 969–974. 102. Caro, J. F., Triester, S., Patel, V. K., Tapscott, E. B., Frazier, N. L. and Dohm, G. L. (1995) Liver glucokinase: decreased activity in patients with type II diabetes. Horm Metab Res 27, 19–22. 103. Adeli, K., Taghibiglou, C., Van Iderstine, S. C. and Lewis, G. F. (2001) Mechanisms of hepatic very low-density lipoprotein overproduction in insulin resistance. Trends Cardiovasc Med 11, 170–176. 104. Taghibiglou, C., Carpentier, A., Van Iderstine, S. C., Chen, B., Rudy, D., Aiton, A., Lewis, G. F. and Adeli, K. (2000) Mechanisms of hepatic very low density lipoprotein overproduction in insulin resistance. Evidence for enhanced lipoprotein assembly, reduced intracellular ApoB degradation, and increased microsomal triglyceride transfer protein in a fructose-fed hamster model. J Biol Chem 275, 8416–8425. 105. Malmstrom, R., Packard, C. J., Caslake, M., Bedford, D., Stewart, P., Yki-Jarvinen, H., Shepherd, J. and Taskinen, M. R. (1997) Defective regulation of triglyceride metabolism by insulin in the liver in NIDDM. Diabetologia 40, 454–462. 106. Lewis, G. F., Carpentier, A., Adeli, K. and Giacca, A. (2002) Disordered fat storage and mobilization in the pathogenesis of insulin resistance and type 2 diabetes. Endocr Rev 23, 201–229.

7 Central Regulation of Peripheral Glucose Metabolism Stanley M. Hileman and Christian Bjørbæk

7.1 Introduction Glucose is the primary and preferred fuel for the brain. Thus, maintaining glucose homeostasis is of critical concern for this organ. Mechanisms in the central nervous system (CNS) have evolved both to detect changes in available energy and to initiate appropriate responses, including effects on appetite and modulation of peripheral glucose levels, to ensure sufficient supply of glucose. Plasma glucose level is the most important determinant of the secretion of classical glucoregulatory hormones, such as insulin and glucagon. Clearly, hypoglycaemia can be sensed directly by the brain and counter-regulatory mechanisms can be mounted in the CNS to drive glucose levels back toward the normoglycaemic range. Activation of neuroendocrine systems and the autonomic nervous system are the main effector pathways invoked by the brain. Combined, these central and peripheral regulatory events result in increased production of glucose by the liver and decreased utilization by peripheral tissues. Counter-regulatory responses are relevant during prolonged starvation and are particularly important for diabetic patients using insulin, where hypoglycaemia often occurs inadvertently. We will herein discuss the role of the brain in counter-regulation to severe hypoglycaemia and mechanisms whereby the CNS may sense small day-to-day changes in glucose levels. This chapter will also focus on a number of other afferent signals to the CNS, including leptin, insulin and free fatty acids, that may influence glucose homeostasis independent of their effects on feeding behaviour. Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

180

CENTRAL REGULATION OF PERIPHERAL GLUCOSE METABOLISM

7.2 Counter-regulation of hypoglycaemia – role of the CNS Although the brain depends primarily upon glucose for energy, it does not synthesize glucose and brain glycogen stores are very limited. It is therefore not surprising that mechanisms are in place to ensure a sufficient supply of glucose to protect brain function during hypoglycaemia. The importance of these mechanisms in regulating glucose levels from meal to meal or during overnight fasting in normal individuals is not clear, but they are critical during extended fasts, acute insulin-induced hypoglycaemia, prolonged or repeated hypoglycaemia due to insulinomas or intensive diabetic therapy and hypoglycaemic episodes that occur in diabetic patients overnight. They may also be important during periods of prolonged undernutrition such as occurs during cachexia or anorexia nervosa. Counter-regulation of hypoglycaemia involves a compendium of hormones and neurotransmitters that are released with the goal of providing glucose for brain utilization while decreasing glucose need in peripheral tissues (Figure 7.1). The primary players involved in counter-regulation are insulin, glucagon, epinephrine, norepinephrine, cortisol and growth hormone. A hierarchy exists for invoking release of these factors.1 – 3 Decreased insulin release occurs when glucose levels drop to ∼4.5 mM from a normal level of ∼6.0 mM. Glucose levels that trigger decreased insulin release lie just at or below values normally seen during the postadsorptive state (∼4.5–5.0 mM), so further absence of food leads to compensatory reduction in pancreatic insulin release. Increases in counter-regulatory release of glucagon, epinephrine, norepinephrine, cortisol and growth hormone occur when glucose levels reach ∼3.6–3.8 mM. Symptoms of hypoglycaemia that are of neural origin (i.e. sweating, hunger, tingling, weakness, dizziness) and cognitive dysfunction appear at glucose levels of ∼3.0 and ∼2.6 mM, respectively. Counter-regulatory mechanisms are invoked at glycaemic thresholds that are higher than thresholds for symptoms of hypoglycaemia. Of particular importance to diabetic patients is the fact that these thresholds are not absolute, but instead are dynamic and vary depending on the antecedent glucose levels. Thus, thresholds are lowered in diabetic individuals receiving intense insulin therapy as they undergo recurring bouts of hypoglycaemia, and this is thought to be an underlying cause of hypoglycaemia unawareness.4 – 8 As described above, the earliest response to falling glucose is decreased pancreatic secretion of insulin, and this is also the major means of regulating circulating glucose levels between meals. Further reductions in blood glucose stimulate glucagon release from the α-cells of the pancreas, stimulating hepatic glucose production, but unlike insulin glucagon does not influence glucose utilization.9 Decreasing levels of glucose also elicit release of epinephrine from the adrenal medulla, which stimulates glucose production and limits glucose utilization through a β2-adrenergic-receptor-mediated mechanism. Epinephrine also stimulates mobilization of fatty acids and inhibits pancreatic insulin secretion.10

COUNTER-REGULATION OF HYPOGLYCAEMIA – ROLE OF THE CNS

181

Less critical to the initial counter-regulatory response are norepinephrine (NE), growth hormone and cortisol. Circulating NE levels increase markedly during hypoglycaemia and mainly reflect release from the sympathetic nervous system. As discussed later, sympathetic innervation of the liver and pancreas plays a role in controlling glucagon and insulin release, and influences hepatic glucose production. Release of growth hormone from the anterior pituitary and of cortisol from the adrenal cortex plays a role during prolonged hypoglycaemia, leading to elevation of alternative fuels such as free fatty acids and ketones.11 Cortisol and growth hormone, along with catecholamines, may play a role in the Somogyi phenomenon, wherein hypoglycaemia leads to rebound hyperglycaemia and posthypoglycaemic insulin resistance due to the inputs of counter-regulatory hormones outweighing that of insulin.12 – 14 Growth hormone is also thought to be involved in the ‘dawn phenomenon’, wherein early morning hyperglycaemia occurs in the absence of antecedent hypoglycaemia.15 In response to acute hypoglycaemia, fasting and prolonged starvation, the CNS regulates several efferent signals. Key sensory and effector sites are located in the hypothalamus, the brainstem and in the spinal cord, which communicate with each other via direct or indirect neuronal circuitries. Efferent signals are of neuronal (dotted lines) and humoral (full lines) nature. Hypoglycaemia reduces the activity of the parasympathetic nervous system (PNS) and stimulates the sympathetic nervous system (SNS), which innervates the adrenals, the pancreas and the liver, and ultimately leads to increased glucose production (GP) by the liver. Additional hypothalamic-pituitary hormonal systems play a role during fasting and prolonged starvation, stimulating release into the circulation of free fatty acids (FFA) and ketones, which serve as alternative fuels. Stimulatory or inhibitory effects on hepatic glucose production are indicated by (+) and (−), respectively; DMV = dorsal motor complex of the vagus nerve; PIT = pituitary. The idea that the brain is important in generating the counter-regulatory response to hypoglycaemia was proposed as early as 1849 by Claude Bernard,16 who found that puncturing the fourth cerebroventricle caused glucosuria in dogs. Subsequent investigators observed that damage to the ventral hypothalamus led to hyperglycaemia or glucosuria.17 In addition, electrical stimulation of the ventromedial hypothalamus (VMH) increases blood glucose levels within 3 minutes18 and intracerebroventricular delivery of 2-deoxyglucose (2-DG), a glucose antagonist, stimulates serum glucose levels and increases glucagon, cortisol, epinephrine and norepinephrine levels,19, 20 a response attenuated by hypothalamic deafferentation.21 A combination of spinal cord and vagal transection blocked the counter-regulatory increase of glucose following insulin administration in dogs.22 Moreover, insulin infusion into the carotid artery induces a hypoglycemic state,23 and preventing neuroglucopenia by infusing glucose through the carotid and/or vertebral arteries24, 25 significantly attenuates the glucoregulatory response to systemic hypoglycaemia. Frizzell et al.26 showed that selective carotid or vertebral artery glucose infusion was not nearly as effective

182

CENTRAL REGULATION OF PERIPHERAL GLUCOSE METABOLISM Brainstem Spinal cord Hypothalamus DMV PNS PIT

Vagal efferents

ACTH Growth hormone

SNS

Pancreas α β

Adrenal Cortisol Epinephrine

FFA

(+)

Glucagon

Insulin

(–) (+)

Ketones Fat

FFA

Liver GP

(+) (–)

GLUCOSE

Figure 7.1 Central efferent responses to hypoglycaemia

as infusion through both arteries in preventing the glucoregulatory response to insulin-induced hypoglycemia. Since vertebral and carotid artery infusion target different areas of the brain, this finding implies that several distinct regions are involved in counter-regulation to hypoglycaemia.

7.3

Brain regions involved in counter-regulation

Food intake and energy balance are primarily controlled by the hypothalamus and by the brainstem.27 – 31 As described below, evidence also supports roles for these two brain regions in controlling central responses to hypoglycaemia (Figure 7.2). The importance of the hypothalamus is supported by studies showing that injections of the glucose antagonist 3-O-methyl glucose into the ventrolateral hypothalamus results in epinephrine secretion and hyperglycaemia, an effect that is blocked by functional denervation of the adrenal gland.32 In addition, electrical stimulation of the VMH elicits a rapid increase in plasma glucose, which is attenuated by adrenalectomy and by injection of glucagon antiserum.18 Borg et al.33 lesioned the VMH, LHA or cortex and then manipulated serum glucose concentrations to achieve euglycaemia (6.0 mM) or hypoglycaemia (3.0 mM) by insulin clamp. As expected, hypoglycaemia increased epinephrine, norepinephrine and glucagon. VMH lesions reduced the magnitude of this response by about 60 per cent whereas lesions of the LHA or frontal lobe were ineffective. In less invasive studies, Borg et al.34 reported an increase in plasma glucose in freely moving rats within 30 minutes of inducing glucopenia in the

BRAIN REGIONS INVOLVED IN COUNTER-REGULATION

183

CTX

CER

Spinal cord 1

PIT 2

1

2

Hypothalamus

Caudal brainstem PVN LHA

CER AP

DMH

NTS

DMV

VMH 3V CC OT

ARC

ME

Figure 7.2 Key regions of the CNS involved in peripheral gluceregulation

VMH by local delivery of 2-DG via microdialysis. Delivery of glucose to the same site had the opposite effect,35 and delivery of 2-DG to the frontal lobes of the brain were ineffective.33 The figure above shows a schematic drawing of a sagital section of the rodent brain. Coronal sections of the hypothalamus and caudal brainstem are indicated 1 and
2 , respectively. CTX = cortex; CER = by vertical lines and marked as
1 Schematic drawing of key nuclei in a coronal cerebellum; PIT = pituitary.
section of the hypothalamus. PVN = paraventricular hypothalamic nucleus; LHA = lateral hypothalamic area; DMH = dorsomedial hypothalamic nucleus; VMH = ventromedial hypothalamic nucleus; ARC = arcuate nucleus; ME = 2 Schematic median eminence; OT = optical tract; 3V = third ventricle.
drawing of key nuclei in a coronal section of the caudal brainstem. CER = cerebellum; AP = area postrema; NTS = nucleus of the solitary tract; DMV = dorsal motor complex of the vagus nerve; CC = central canal. Ritter et al.36 localized glucoregulatory sites in the hindbrain of awake rats using the 5-thio-D-glucose (5TG) glucose analogue. Multiple injection sites were analysed for hyperglycaemic or hyperphagic responses between 30 min and 4 hours post-injection, and many injection sites, including the nucleus of the solitary tract (NTS), were associated with increased blood glucose. However, in the same study and in contrast to the results by Borg et al., Ritter et al. did not find any responsive sites in the VMH. The explanation for this discrepancy is unclear,

184

CENTRAL REGULATION OF PERIPHERAL GLUCOSE METABOLISM

but one possibility is that the 2-DG compound used by Borg et al. reached the hindbrain sites identified by Ritter et al., although Borg et al. reported that hypothalamic regions close to the injection site did not contain 2-DG following injection. In further support of the hindbrain sites, but not of the forebrain region, Ritter et al.37 showed that blood glucose levels were unaffected by 5TG injections into the third ventricle when flow of cerebrospinal fluid from the third to fourth ventricle was blocked, yet 5TG injections into the fourth ventricle were still effective. Also pointing to the presence of hindbrain glucoresponsive regions as primary mediators of the counter-regulatory response are findings by DiRocco and Grill27, 38 demonstrating hyperglycaemic responses to systemic administration of 2-DG in decerebrate rats. While further studies are needed to resolve the discrepancy between these studies, the data clearly support the notion that specific regions within the central nervous system can sense hypoglycemia. In addition, injections of glucose into the carotid artery supplying the brain, in amounts that do not affect systemic glycemia, rapidly increase plasma insulin concentrations,39 an effect probably mediated by the parasympathetic nervous system. Combined with the above data, these data demonstrate a role of the brain in sensing both low and high glucose levels, and the ability of the CNS to generate an appropriate response affecting peripheral glucose metabolism.

7.4 Glucosensing neurons As described above, the CNS can sense and respond to changes in available glucose.40, 41 However, these studies have mostly been carried out under conditions where local glucose levels were outside the normal physiological range and not in response to the complete changes in blood glucose that only vary slightly from meal to meal or with the diurnal swing. In order for the brain to influence peripheral glucose metabolism under such circumstances, it must at least be able to sense relatively minor changes in blood glucose. All brain neurons become silent when they experience a rapid fall in glucose levels below 1 mM,42 a response that may be protective in the short term.43 In contrast to neuronal silencing at very low glucose levels, rare but highly specialized neurons exist in the CNS that are sensitive to changes in blood glucose that are only slightly above or below the normal range. Generally, two approaches have been taken to study this in detail. One involves single-cell recordings in brain-slice preparations during exposure to varying concentrations of glucose, the other using implanted electrodes in animals and measuring neuronal activity in response to changes in blood glucose levels in situ. By recording individual neuronal discharge frequencies in anaesthetized cats, Oomura et al.44 reported that hypothalamic neurons either became increasingly active (glucose stimulated) or increasingly inactive (glucose inhibited) in response to intracarotid injection of glucose. In later studies, Oomura et al.45, 46 showed that about 30 per cent of all tested cells in the LHA reduced their firing rates and about 20 per

GLUCOSENSING NEURONS

185

cent were activated in response to local intrahypothalamic delivery of glucose in rats. In contrast, approximately 35 per cent of examined VMH cells were activated and only a few were inhibited. Using similar methods, 45 per cent of tested neurons in the NTS increase firing frequency in response to locally injected glucose.47 An elegant and more recent investigation has studied this in further detail. Silver and Erecinska48 measured blood glucose, brain extracellular glucose and neuronal firing rates in anaesthetized rats while gradually increasing or decreasing circulating blood glucose levels within the physiological range. In the LHA, increasing glucose inhibited 33 per cent of the tested neurons while about seven per cent were activated and 60 per cent were unresponsive. The investigators classified the cellular responses into four groups. The predominant type gradually decreased firing as glucose rose (maximal firing rate at 3 mM blood glucose), becoming completely inhibited at 10–12 mM. In the VMH, most cells were silent at blood glucose of 3–4 mM and progressively increased their activity as glucose rose to ∼15 mM, and could not be inhibited by higher glucose levels. No cells in the VMH were inhibited by glucose, consistent with earlier reports.45 In summary, this work by Silver and Erecinska suggests that highly specialized cells in the hypothalamus alter firing rates in response to very small, physiological changes in blood glucose levels. The study by Silver and Erecinska could not entirely exclude the possibility that circulating factors other than glucose were mediating the effect on the hypothalamic neurons. Furthermore, it could not be determined whether the affected cells were directly influenced by extracellular glucose, or whether they were indirectly modulated via synaptic inputs from true glucosensing cells. Other investigators49, 43 have addressed this question by using thin brain slices and patch clamp recordings, while controlling glucose concentrations present in the medium. Neurons were found that were directly inhibited or directly stimulated by glucose as well as other neurons that were activated or inhibited via presynaptic modulation, presumably by the true glucosensing neurons. Several additional brain regions harbouring glucosensing cells have been reported using similar methods, including the arcuate nucleus (ARC),50 the paraventricular nucleus of the hypothalamus (PVN),51 and the hindbrain.52 These in vitro studies demonstrate that specific brain regions contain specialized neurons that respond to physiologically relevant changes in extracellular glucose levels. However, it remains to be determined whether these specific cells play a role in regulating peripheral glucose metabolism, either in the counterregulatory response to hypoglycemia or within meal-to-meal variation of blood glucose levels. The exact cellular mechanism by which glucosensing neurons detect changes in extracellular glucose is not fully understood. Evidence suggesting that hypothalamic glucose-stimulated neurons utilize an ATP-sensitive K+ channel was first reported by Ashford et al.53, 54 They showed that blocking the K+ -ATP channel activates neurons in isolated hypothalamic slices. Furthermore, injection

186

CENTRAL REGULATION OF PERIPHERAL GLUCOSE METABOLISM

of another K+ -ATP blocker, glibenclamide, into the VMH impairs the counterregulatory increase in blood glucose after insulin-induced hypoglycaemia, and decreases blood glucose in normoglycemic rats.55 In pancreatic β-cells, membrane-bound K+ -ATP channels are comprised of a pore-forming subunit (Kir6.2) through which potassium ions travel out of the cell, and of a regulatory unit (SUR1) that binds synthetic sulfonylureas (tolbutamide, glibenclamide), which close the channel and lead to increased insulin secretion.56 The SUR regulates Kir6.2 in response to the intracellular ATP/ADP ratio. Thus, stimulating β-cells with glucose increases the ATP/ADP ratio, inhibiting Kir6.2 activity, and causing accumulation of intracellular K+ . Influx of calcium ions via Ca2+ channels finally triggers insulin secretion.57 This model has led to the hypothesis that hypothalamic glucose-stimulated neurons have significant similarities to pancreatic β-cells. The neuronal model envisions that glucose induces depolarization of the neuron by closing K+ -ATP channels, leading to increased firing rates and increased cellular Ca2+ at axon terminals, ultimately causing release of neurotransmitters and neuropeptides. Less is known about how glucose-inhibited neurons sense glucose, since these cells become hyperpolarized with increasing glucose levels. Lee et al. have shown by single-cell PCR that glucosensing neurons express ATP-sensitive potassium channels.58 Additional evidence for a role of the K+ ATP channel in glucosensing by the brain arises from recent results of Miki et al.59 Mice lacking the Kir6.2 gene were devoid of glucose-stimulated neurons in brain slices containing the VMH. Furthermore, in response to systemic hypoglycaemia or neuroglucopenia, the ability to increase circulating glucagon and glucose levels was greatly impaired. Based on this, the authors concluded that K+ -ATP channels in VMH-glucose-stimulated neurons are required for glucose responsiveness and that K+ -ATP channels in this brain region are essential for maintenance of glucose homeostasis. While the first conclusion is clearly supported by the data, the latter must be considered speculative, since it is doubtful that the VMH is solely responsible for the counterregulatory response. Also, the K+ -ATP channel (Kir6.2) is widely expressed throughout the brain and is not restricted to the VMH.42, 60 – 62 Thus, presence of this channel is not sufficient to act as the only critical component of glucosensing neurons. Of higher potential for use in defining glucosensing neurons is the pancreatic form of hexokinase, i.e. glucokinase (GK). This enzyme is rate limiting for glycolysis in the β-cell because its Km , in contrast to the Km of other hexokinases, lies within the physiological range for blood glucose.63 The CNS sites of expression include the VMH, DMH, PVN, ARC, LHA and the caudal brain stem.42, 64 – 67 This expression pattern thus resembles that of glucosensing neurons and opens the possibility that GK is expressed in these cells. In dissociated neurons from the VMH, about 70 per cent of both glucose-inhibited and stimulated cells are affected by inhibition of GK,66 while non-glucosensing

CONTROL OF PERIPHERAL ORGANS INVOLVED IN GLUCOREGULATION

187

neurons are largely unaffected. This suggests that GK is not expressed in nonglucosensing cells, although this requires further investigation since GK expression is relatively wide as described above. Although GK is expressed in both glucose-inhibited and glucose-stimulated neurons and may be a component of the glucosensing mechanism, the question remains that if GK is expressed in both cells, what then distinguishes the two types of neuron?

7.5

Central control of peripheral organs involved in glucoregulation

The liver The liver is richly innervated by both sympathetic and parasympathetic nerves.68, 69 The sympathetic fibres derive from the splanchnic nerves and their postganglionic fibres originate from the celiac ganglia. Parasympathetic innervation arises from both the left and right vagus nerves. The majority of the nerve supply enters along the common hepatic artery and portal vein. Stimulation of the vagus nerve increases the activity of liver glycogen synthase, the rate-limiting enzyme in glycogen synthesis from glucose-6phosphate.70 This effect is not influenced by pancreatectomy, suggesting that this occurs directly in the liver and is not mediated by changing insulin levels. Systemic infusion of glucose increases vagal efferent activity, a relationship that is linear over the physiological range of circulating glucose concentrations.71 In contrast, stimulation of the splanchnic nerves depletes glycogen reserves and increases serum glucose levels.72, 73 Furthermore, splanchnic nerve stimulation in rabbits activates two glycogenolytic enzymes, phosphorylase and glucose-6-phosphatase, within 30 seconds, suggesting a direct effect on liver glucoregulation.73, 74 Moreover, decreases in serum glucose levels in response to a carotid artery insulin injection have been ascribed to direct neural effects on liver glucose production and glucose uptake.23 Altogether, this data points to a role for the CNS in regulating liver glucose metabolism, although the exact quantitative impact of this regulation under physiological circumstances is unclear.

The pancreas As the primary source of insulin and glucagon, the pancreas is of obvious importance in regulating peripheral glucose levels. Regulation of insulin and glucagon release from the pancreas by the central nervous system arises from three inputs, two of which are neural while one is hormonal: (1) parasympathetic innervation, (2) sympathetic innervation and (3) sympathoadrenal input. Innervation of the pancreas by the parasympathetic nervous system is accomplished by the vagus nerve and consists mainly of cholinergic input,75 although there appears to be some peptidergic innervation as well, namely vasoactive intestinal

188

CENTRAL REGULATION OF PERIPHERAL GLUCOSE METABOLISM

peptide and gastric releasing peptide.76 Postganglionic sympathetic input enters the pancreas in conjunction with the arterial blood vessels to enter as part of the mixed autonomic nerve. There may also be preganglionic sympathetic efferents that enter the pancreas directly and innervate intrapancreatic sympathetic ganglia.78, 79 These sympathetic nerve fibres contain mostly norepinephrine, but may also include neuropeptides such as neuropeptide Y and galanin.77 Insulin-induced decreases in blood glucose decrease the firing rate of the pancreatic branch of the vagus nerve.80 In contrast, carotid artery infusion of isotonic glucose stimulates coeliac–pancreatic vagus firing rate and intracarotid infusion is more effective than intravenous administration.80 Stimulation of parasympathetic inputs increases insulin release in the dog and the baboon81, 19 and increases glucagon release from α-cells in dogs and calves.82, 83 Furthermore, stimulation of the mixed pancreatic nerve increases insulin levels in the pancreatic duodenal vein and vagal stimulation increases insulin release in perfused preparations of pancreas, responses that are blocked by administration of the anticholinergic drug atropine.10 Stimulation of sympathetic input or of the splanchnic nerve decreases insulin release, likely via the α-adrenoreceptor, and increases glucagon release.84 – 88 Norepinephrine release from the pancreatic sympathetic nervous system increases with increased severity of glucopenia89 and ganglionic blockade inhibits this response.90 Pancreatic sympathetic nerve activity is stimulated by 2-DG administration to the lateral cerebroventricles.91 Finally, denervation of the pancreas blocks the response to systemically administered 2-DG and intrapancreatic arterial infusion of 2-DG fails to reproduce the pancreatic norepinephrine response, clearly supporting a central role in these processes.91

The adrenal glands As mentioned above, the adrenal glands provide input for glucoregulation both via epinephrine release and via secretion of glucocorticoids. Regarding the former, the adrenals receive sympathetic input through the greater and lesser splanchnic nerves and lumbar ganglia of the abdominal sympathetic chains.69 The vagus does not appear to contribute directly.69 Cannon92 first showed that hypoglycaemia elicited epinephrine release, a response later shown to increase progressively with the magnitude of glucopenia.2, 89, 93, 94 Additionally, epinephrine release in response to hypoglycemia or to the 3-O-methylglucose is blocked by isolating the adrenal glands from neural input.94, 95, 90, 96 The hypothalamus appears to be involved in the sympathoadrenal response to hypoglycaemia since hypothalamic deafferentation reduces the adrenomedullary response to 2-DG.21 Indeed, VMH lesions increase adrenal nerve activity and catecholamine release, while LHA stimulation and lesions increase and decrease adrenal nerve activity, respectively.97 In contrast, VMH stimulation did not affect adrenal nerve activity. Intracerebroventricular administration of 2-DG increased adrenal nerve activity,

ADDITIONAL AFFERENT SIGNALS TO THE CNS

189

a response blocked by LHA lesions but unaffected by VMH lesions. However, stimulation of the VMH prior to 2-DG treatment reduced the 2-DG-induced increase in adrenal nerve activity.97 Based on this data, the authors concluded that the LHA is sensitive to 2-DG and comprises a major part of the sympathoadrenal response, but that the VMH response may depend on antecedent adrenal nerve activity and be mediated by other neuronal structures that function as relay points of integrating sites between the VMH and sympathetic efferents. Also, adrenalectomy influences the insulin and glucose response to VMH stimulation.18 Thus, the brain is an important component of the pathways influencing sympathoadrenal epinephrine release during hypoglycemia. Release of cortisol (humans) or corticosterone (rodents) is increased during hypoglycaemia.11 This reflects hypothalamic output of corticotropin-releasing hormone (CRH), which in turn stimulates adrenocorticotrophic hormone (ACTH) release from the anterior pituitary, ultimately leading to increased glucocorticoid secretion from the adrenals. As mentioned earlier, increased cortisol release probably plays a minor role in glucoregulation, mainly during the later stages of prolonged hypoglycaemia. However, there is some indication that CRH itself influences sympathoadrenal activity, since CRH administration prior to hypoglycemia blunts the counter-regulatory epinephrine response, a result not observed after prior treatment with ACTH or corticosterone.98

7.6 Additional afferent signals to the CNS regulating peripheral glucose metabolism Pancreatic and hepatic glucosensing Russek99 first postulated that specific receptors in the liver monitor glucose levels and send information via the vagus nerve to brain regions important for controlling food intake. These glucosensing entities appear to be localized specifically to the portal vein100 and histological studies have revealed extensive afferent innervation of the portal vein adventitia.101 – 103 Portal vein glucose infusion decreases the firing rate of the hepatic branch of the afferent vagus nerve in perfused liver preparations104 and discharge rates of hepatic vagal afferents are inversely proportional to portal vein glucose concentrations.105 Furthermore, systemic infusion of 2-DG increases the hepatic vagal afferent discharge rate.106 Interestingly, fluctuations in portal vein glucose levels influence the firing rate of neurons in the LHA and NTS.107 Thus, hepatoportal vagal afferents carry information regarding portal vein glucose levels to hypothalamic areas known for generating a counter-regulatory response (Figure 7.3). This figure depicts factors and pathways that can act on the CNS to influence peripheral glucose metabolism, independent of long-term effects on energy intake. Glucose is sensed by specialized glucosensing neurons located primarily in the hypothalamus and in the caudal brainstem. Neurons that are regulated by leptin are

190

CENTRAL REGULATION OF PERIPHERAL GLUCOSE METABOLISM

Brainstem

Hypothalamus

NTS

BLOOD GLUCOSE

FFA

Leptin

Insulin

Vagal afferents

Liver

Fat Pancreas

Figure 7.3

Central afferent signals involved in regulation of peripheral glucose metabolism

located in the same regions of the brain and may overlap directly with those that sense glucose. Moreover, both insulin and FFA may act in similar regions of the hypothalamus to affect peripheral glucose metabolism. Glucosensory neurons of the vagus nerve are also present in the pancreas and in the portal vain of the liver, transmitting information to the CNS about local glucose levels. NTS = nucleus of the solitary tract; FFA = free fatty acids. Perseghin et al.108 assessed the importance of neural input from and to the liver in glucoregulation by examining liver transplant patients. They observed that glucose levels in liver transplant patients were maintained in the lower physiological range within a few weeks of transplant. These authors also observed that fasting glucose levels and glucose production were lower, that glucose production during insulin-induced hypoglycaemia was significantly less and that the counterregulatory response was blunted in transplant patients. Bolli et al.109 pharmacologically blocked counter-regulatory hormone influences on glucose production and observed that counter-regulatory hormones account for practically all of the glucose produced at blood glucose levels of 50 mg/dl, but that hepatic glucose production increased twofold over controls at blood glucose levels of 30 mg/dl. As mentioned previously, peripheral hypoglycaemia induced by insulin leads to large increases in epinephrine and norepinephrine release. This increase is blunted by about 50–60 per cent in rats wherein the portal vein is denervated.110 It has been estimated that the liver can produce anywhere from 12 to 50 per cent of circulating glucose during hypoglycaemia independent of counter-regulatory hormone influence.111 – 115 Confounding many of these studies is the fact that, during severe hypoglycaemia, the liver can produce glucose

ADDITIONAL AFFERENT SIGNALS TO THE CNS

191

in the absence of neural or counterregulatory hormone input.109, 115 – 118 Thus, the relative importances of neural influences in the liver on glucoregulation are difficult to assess, but probably account for less than 25 per cent of hepatic glucose production during moderate hypoglycaemia. The relative importance of the CNS in generating a response to hypoglycaemia in the pancreas has not been addressed in detail. Clearly, decreases in blood glucose can be directly detected within the pancreas and a response generated by the α- and β-cells. However, it is possible that pancreatic vagal afferents send information regarding local glucose levels to the brain since intravenous glucose or 2-DG increases and intravenous insulin decreases the pancreatic vagal afferent firing rate.80 In pancreas transplant patients, glucose levels are normal, suggesting that humoral regulation of pancreatic function is sufficient for dealing with normal day-to-day changes in glucose levels. However, deficits in glucoregulation during hypoglycemia have been noted in these patients. Diem et al.119 reported that, although glucose recovery improved in diabetics with pancreatic transplants, recovery of hepatic glucose production during hypoglycaemia increased by only 34 per cent over baseline in transplant patients compared with 58 per cent in control individuals. Battezzati et al.120 observed that, in response to mild hypoglycaemia, hepatic glucose production initially decreased and then returned to baseline in controls by 1 h, but was still depressed at 2 h in transplant patients despite normal glucagon and epinephrine responses. Kendall et al.121 showed that in type 1 diabetic transplant patients subjected to stepped hypoglycaemia the glucagon response and symptom awareness were normalized, but the epinephrine and norepinephrine responses were muted or absent. Thus, it appears that neural outflow or input from the pancreas influences hepatic glucose production, though the relative importance it has in counter-regulation remains to be defined.

Leptin Leptin, the fat-derived hormone discovered in 1994,122 circulates at levels proportional to body fat mass and delivers information to the brain about energy stores.29, 30, 123 – 125 Mutations in leptin or its receptor cause morbid obesity and severe insulin resistance.122, 126 In addition to decreasing food intake and body weight, leptin influences neuroendocrine function, reproduction, adaptive responses to fasting, bone development, blood pressure, energy expenditure, sensory nerve input and autonomic outflow. Pertinent to this review is recent data suggesting that leptin also influences peripheral glucose homeostasis via actions in the CNS, independent of changes in feeding and body weight. Kamohara et al.127 showed that intracerebroventricular (ICV) delivery of small doses of leptin to fasted mice acutely increased glucose turnover and whole body glucose uptake. Leptin-induced glucose uptake into muscle was nearly ablated following denervation of the muscle tissue, suggesting that the effect occurred via autonomic efferent signals. Furthermore, ICV injection of leptin rapidly

192

CENTRAL REGULATION OF PERIPHERAL GLUCOSE METABOLISM

regulates hepatic glucose fluxes128 and leptin improves insulin sensitivity in lipodystrophic rodents and patients, independent of feeding.129 – 132 Functional leptin receptors are found in the ARC, the VMH and the DMH, and to a lesser degree in the PVN and the LHA.133 – 136 Outside the hypothalamus, expression can be detected in the caudal brain stem.137, 138, 134 Consistent with this, leptin affects the firing rates of neurons in isolated brain slices from the ARC, the VMH and the NTS.139 – 141 Thus, these locations overlap with centres that are involved in regulating energy homeostasis and the autonomic nervous system,142 and with sites containing glucosensing neurons. Indeed, microinjection of leptin into the VMH, but not the LHA, of freely moving rats increased glucose uptake in peripheral tissues, including brown adipose tissue (BAT), heart and skeletal muscle.143 Subsequent studies showed that the effect on BAT is mediated by the sympathetic nervous system.144 It remains to be determined whether physiological changes in leptin levels induce the same effects and whether other sites in the CNS have similar capacities. Neuropeptide Y (NPY) and proopiomelanocortin (POMC) cells in the ARC of the hypothalamus have received particular attention due to their key role in regulating energy homeostasis.145 NPY potently stimulates food intake146 – 148 and NPY neurons co-express the melanocortin receptor antagonist, agouti-related peptide (AgRP).149 The POMC-derived neuropeptide, α-melanocyte stimulating hormone (α-MSH), induces robust anorexigenic responses in rodents.150 – 152 Both NPY/AgRP and POMC neurons are directly regulated by leptin via the leptin receptor, but in opposing fashions.153, 154 Leptin stimulates POMC neurons while NPY/AgRP neurons are inhibited.139 When leptin levels are low (fasting, leptindeficient mice), pomc gene expression decreases, indicating that the melanocortin system mediates at least some of the effects of leptin.155, 156 This conclusion is supported by powerful pharmacological and genetic evidence.157 – 160 NPY and AgRP expression is strongly activated in the absence of leptin.161 When leptin levels are high (fed state, during leptin administration), POMC expression increases while NPY and AgRP expression decreases.162, 156 Both the GK enzyme and the K+ -ATP (Kir6.2/SUR1) channel are expressed in POMC139, 66, 163 and in NPY neurons.164, 62 However, the importance of Kir6.2 channels in leptin action is unclear since leptin still inhibits food intake in Kir6.2−/− mice,59 although it is possible that other aspects of leptins pleiotrophic actions could be affected in these mice. Firing rates of POMC neurons are stimulated by glucose163 and NPY cells are inhibited.164 Thus, both leptin and glucose probably inhibit orexigenic NPY peptide release and stimulate anorexigenic α-MSH release. Evidence also suggests that central administration of melanocortin receptor agonists rapidly affects peripheral glucose metabolism,165 providing a link between the activity of POMC neurons and the regulation of glucose and energy homeostasis, a view that is supported by additional anatomical, genetic, pharmacological and electrophysiological studies.166, 153, 167, 145, 123, 163

ADDITIONAL AFFERENT SIGNALS TO THE CNS

193

Insulin Insulin plays a critical role in regulating glucose homeostasis via direct actions on insulin receptors expressed in muscle, liver and adipocytes. Insulin receptor mRNA is also expressed in the brain, including in the cerebral cortex, the cerebellum, the dentate gyrus, layers of the pyriform cortex and of the hippocampus, the choroid plexus and the ARC of the hypothalamus.168 – 170 In anaesthetized rats, insulin injected into the carotid artery immediately decreases systemic blood sugar23 and delivery of insulin into the VMH or the LHA of rats rapidly affects neuronal discharge frequency.45 ICV injection of insulin reduces food intake and body weight in baboons and rodents171, 172 and administration of anti-insulin antibodies into the rat hypothalamus increases food intake.173 In more recent studies, complete loss of neuronal insulin receptors by conditional knockout in mice or partial loss by hypothalamic injection of insulin receptor anti-sense oligonucleotides results in hyperphagia and increased bodyweight.174 – 176 Insulin given ICV into awake rats rapidly inhibits glucose production by the liver,175, 176 supporting a centrally mediated effect of insulin on glucose metabolism. While the above studies were mostly chronic and/or pharmacological in nature, a later study shows that minute amounts of insulin delivered into the brain arteries of fasted dogs rapidly alter peripheral glucose homeostasis,177 strongly supporting a physiological role for central insulin signalling. Neurons that are inhibited by insulin are present in the ARC and VMH. Like leptin, insulin activates ATP-sensitive K+ channels in hypothalamic brain slices178 and a role of K+ -ATP channels in decreasing hepatic glucose production in response to insulin has recently been reported.176 Interestingly, insulinsensitive neurons also have glucosensing capabilities.45, 178 Moreover, insulin does not affect the activity of neurons from rats lacking functional leptin receptors, suggesting that aspects of insulin action in the CNS require leptin signalling, and opening the possibility that receptors for insulin and leptin are co-expressed in glucosensing neurons.179 Indeed, insulin receptors have recently been identified in hypothalamic POMC neurons,180 cells that are activated by leptin and glucose. Whether POMC neurons increase or decrease firing rates in response to insulin is unknown, although activation seems more likely since the melanocortin system appears to be required for insulin-mediated inhibition of food intake180 and fat mass.181 In addition, central administration of melanocortin receptor agonists rapidly reduces serum insulin levels, an effect mediated via the sympathetic nervous system.165 However, blockade of melanocortin signalling did not affect inhibition of liver glucose production by insulin.181 Combined, these data suggest that the central melanocortin system regulates peripheral glucose metabolism via effects on insulin release, but that another system regulates glucose production. Further studies of POMC neurons will illuminate the role of these neurons in insulin action, and of the interplay between insulin, glucose and leptin signalling in the brain.

194

CENTRAL REGULATION OF PERIPHERAL GLUCOSE METABOLISM

Fatty acids Increased quantities of free fatty acids (FFAs) are released from adipocytes under conditions of starvation, diabetes and obesity. These molecules can be utilized interchangeably with glucose for energy in most tissues, with the notable exception of brain tissue. However, FFAs are present in the cerebrospinal fluid182 and FFA extracts delivered to the VMH or LHA of anaesthetized rats rapidly affect neuronal discharge rates,183 implying a function for FFAs in the CNS. Effects on neuronal activity also occur with purified long chain fatty acids such as oleic acid or palmitic acid, the major FFA in blood.45 FFAs activate some neurons, while inhibiting others. Interestingly, the majority of glucosensing neurons respond to FFAs, while the majority of non-glucosensing neurons are unaffected by FFAs, suggesting that sensitivity to FFAs may be relatively specific to rare glucosensing neurons, and that these cells integrate multiple metabolic signals. Like glucose, insulin and leptin, central administration of oleic acid reduces food intake in rodents184 and alteration of central fatty acid metabolism affects energy intake in rodents.185 Obici et al.184 showed that central infusion of oleic acid in fasted rats inhibited liver glucose production, suggesting that fatty acids can act within the CNS to affect peripheral glucose metabolism independent of food intake. This inhibition required activation of the K+ -ATP channel, possibly via direct binding of long chain fatty acyl CoA esters to the K+ -ATP channel.186, 187 Since the brain does not usually use lipids as a significant fuel, these studies indicate that FFAs can act as afferent signals informing the brain about metabolic status, although the exact brain regions involved and the cellular mechanisms by which FFAs are sensed remain unclear. Difficult to reconcile, however, is the finding that oleic acid inhibits food intake and decreases hepatic glucose production, since circulating FFAs increase during starvation, a state characterized by increased appetite and hepatic glucose production. Moreover, the hyperlipidaemia present in human and rodent obesity is associated with hyperphagia, not hypophagia. Finally, it has been shown that physiological increases of systemic FFAs in humans increase glucose production and induce mild hyperglycaemia.188 – 190 Although the latter effect is presumably mediated by FFAs acting peripherally, these data imply that central actions of FFAs to decrease glucose production are of minor importance in the regulation of whole body glucose metabolism.

7.7

Conclusions and future perspectives

It is clear that the CNS can detect large changes in glucose availability and respond appropriately in order to maintain adequate glucose supply for the brain. The most noticeable evidence for this is the rapid counter-regulatory

CONCLUSIONS AND FUTURE PERSPECTIVES

195

response to hypoglycaemia, where neuroendocrine and autonomic efferent signals regulate functions of the pancreas, liver and the adrenals, which combined with direct communications between peripheral tissues leads to increased blood glucose concentrations. The brain regions important for these responses include the brainstem and regions of the hypothalamus, areas that also contain specialized neurons with unique capabilities to detect alterations in extracellular glucose by changing neuronal activity. Although likely, there is as yet no direct evidence that these ‘glucosensing’ neurons are actually responsible for initiating the counterregulatory response. Furthermore, specific physiological functions of these cells in individual hypothalamic nuclei have yet to be assigned. These issues need to be examined using new and more conclusive methods, including systematic genetic targeting of neurons in each brain region. Inherent to glucosensing neurons are systems enabling them to be influenced by small, physiological changes in extracellular glucose levels, suggesting that meal-to-meal variation and diurnal rhythms in blood glucose levels can be sensed by the brain. The cellular mechanism by which glucosensing occurs may require the activity of specialized glucokinase enzymes and K+ ATP channels that are also critical for pancreatic β-cells to regulate insulin release in response to glucose. However, these proteins are not sufficient to characterize glucosensing neurons, since it is evident that their expression is not restricted to these rare cells in the brain. In addition to glucose, circulating hormones such as leptin and insulin can influence the brain to affect peripheral glucose metabolism, possibly via regulation of neurons that also have glucosensing capabilities. Further analyses are required to elucidate the glucosensing mechanism and the mechanisms that distinguish glucose-stimulated and glucose-inhibited neurons. Although this review has focused on signals to the brain that affect glucose metabolism independent of alterations in food intake and body weight, at least some glucosensing cells, including POMC and NPY neurons, are also likely to serve more complex functions such as regulation of food-seeking behaviour, appetite and meal size. In addition, vagal sensory input and gut- and stomachderived hormones such as ghrelin and cholecystokinin may influence food intake and energy homeostasis via neuronal circuitries that overlap with those of leptin and insulin.31, 29, 28, 191, 192 . Additional studies are needed to identify the mechanisms whereby glucosensing neurons integrate multiple metabolic inputs, and how these cells are connected to efferent systems that regulate glucose homeostasis. Finally, studies of the pathogenesis of type 2 diabetes have focused on peripheral tissues (muscle, β-cells, liver and fat). However, central mechanisms can clearly influence glucose metabolism and control fat mass and energy balance, suggesting that defects in the brain may exist that cause or worsen insulin resistance and type 2 diabetes. This possibility deserves further investigation.

196

CENTRAL REGULATION OF PERIPHERAL GLUCOSE METABOLISM

Acknowledgements C.B. is supported by a grant from the NIH (RO1 DK-60673) and S.M.H. by USDA (2001-35203-10835). We thank Dr. A. N. Hollenberg (BIDMC, Boston) for critically reviewing the manuscript and Dr. H. Grill (University of Pennsylvania) for providing us with helpful advice, and C. Romanosky (West Virginia University) for assistance with organizing the references. We apologize if certain authors and papers were not acknowledged in the review due to space limitations.

References 1. Mitrakou, A., Ryan, C., Veneman, T., Mokan, M., Jenssen, T., Kiss, I., Durrant, J., Cryer, P. and Gerich, J. (1991) Hierarchy of glycemic thresholds for counterregulatory hormone secretion, symptoms, and cerebral dysfunction. Am J Physiol 260, E67–E74. 2. Schwartz, N. S., Clutter, W. E., Shah, S. D. and Cryer, P. E. (1987) Glycemic thresholds for activation of glucose counterregulatory systems are higher than the threshold for symptoms. J Clin Invest 79, 777–781. 3. Fanelli, C., Pampanelli, S., Epifano, L., Rambotti, A. M., Ciofetta, M., Modarelli, F., Di Vincenzo, A., Annibale, B., Lepore, M. and Lalli, C. (1994) Relative roles of insulin and hypoglycaemia on induction of neuroendocrine responses to, symptoms of, and deterioration of cognitive function in hypoglycaemia in male and female humans. Diabetologia 37, 797–807. 4. Chalmers, T. M. and Keele, C. H. (1952) The nervous and chemical control of sweating. Br J Dermatol 64, 43–54. 5. Cryer, P. E. (1997) Hypoglycemia: Pathophysiology, Diagnosis and Treatment. New York: Oxford University Press. 6. Cranston, I., Lomas, J., Maran, A., Macdonald, I. and Amiel, S. A. (1994) Restoration of hypoglycaemia awareness in patients with long-duration insulin-dependent diabetes. Lancet 344, 283–287. 7. Dagogo-Jack, S., Rattarasarn, C. and Cryer, P. E. (1994) Reversal of hypoglycemia unawareness, but not defective glucose counterregulation, in IDDM. Diabetes 43, 1426–1434. 8. Dagogo-Jack, S. E., Craft, S. and Cryer, P. E. (1993) Hypoglycemia-associated autonomic failure in insulin-dependent diabetes mellitus. Recent antecedent hypoglycemia reduces autonomic responses to, symptoms of, and defense against subsequent hypoglycemia. J Clin Invest 91, 819–828. 9. De Feo, P., Perriello, G., Torlone, E., Fanelli, C., Ventura, M. M., Santeusanio, F., Brunetti, P., Gerich, J. E. and Bolli, G. B. (1991) Evidence against important catecholamine compensation for absent glucagon counterregulation. Am J Physiol 260, E203–E212. 10. Woods, S. C. and Porte, D., Jr. (1974) Neural control of the endocrine pancreas. Physiol Rev 54, 596–619. 11. Bolli, G. B. and Fanelli, C. G. (1999) Physiology of glucose counterregulation to hypoglycemia. Endocrinol Metab Clin North Am 28, 467–493. 12. De Feo, P., Gallai, V., Mazzotta, G., Crispino, G., Torlone, E., Perriello, G., Ventura, M. M., Santeusanio, F., Brunetti, P. and Bolli, G. B. (1988) Modest decrements in plasma glucose concentration cause early impairment in cognitive

REFERENCES

13.

14.

15.

16. 17. 18. 19. 20.

21.

22.

23. 24.

25.

26.

27. 28.

29. 30.

197

function and later activation of glucose counterregulation in the absence of hypoglycemic symptoms in normal man. J Clin Invest 82, 436–444. Kollind, M., Adamson, U., Lins, P. E. and Efendic, S. (1987) Diabetogenic action of GH and cortisol in insulin-dependent diabetes mellitus. Aspects of the mechanisms behind the Somogyi phenomenon. Horm Metab Res 19, 156–159. Popp, D. A., Shah, S. D. and Cryer, P. E. (1982) Role of epinephrine-mediated beta-adrenergic mechanisms in hypoglycemic glucose counterregulation and posthypoglycemic hyperglycemia in insulin-dependent diabetes mellitus. J Clin Invest 69, 315–326. Campbell, P. J., Bolli, G. B., Cryer, P. E. and Gerich, J. E. (1985) Pathogenesis of the dawn phenomenon in patients with insulin-dependent diabetes mellitus. Accelerated glucose production and impaired glucose utilization due to nocturnal surges in growth hormone secretion. N Engl J Med 312, 1473–1479. Bernard, C. (1849) Chiens rendus diabetiques. Compt End Soc Biol 1, 60. Benzo, C. A. (1983) Minireview. The hypothalamus and blood glucose regulation. Life Sci 32, 2509–2515. Frohman, L. A. and Bernardis, L. L. (1971) Effect of hypothalamic stimulation on plasma glucose. Am J Physiol Endocrinol Metab 221, 1596–1603. Frohman, L. A., Ezdinli, E. Z. and Javid, R. (1967) Effect of vagotomy and vagal stimulation on insulin secretion. Diabetes 16, 443–448. Molina, P. E., Eltayeb, K., Hourani, H., Okamura, K., Nanney, L. B., Williams, P. and Abumrad, N. N. (1993) Hormonal and metabolic effects of neuroglucopenia. Brain Res 614, 99–108. Sun, C. L., Thoa, N. B. and Kopin, I. J. (1979) Comparison of the effects of 2deoxyglucose and immobilization on plasma levels of catecholamines and corticosterone in awake rats. Endocrinology 105, 306–311. Dolnikoff, M. S., Kadekaro, M., Timo-Iaria, C. and Hell, N. S. (1983) Neural mechanisms involved in the recovery from insulin hypoglycemia in dogs. J Auton Nerv Syst 8, 129–139. Szabo, A. J. and Szabo, O. (1975) Influence of the insulin sensitive central nervous system glucoregulator receptor on hepatic glucose metabolism. J Physiol 253, 121–133. Keller-Wood, M. E., Wade, C. E., Shinsako, J., Keil, L. C., van Loon, G. R. and Dallman, M. F. (1983) Insulin-induced hypoglycemia in conscious dogs: effect of maintaining carotid arterial glucose levels on the adrenocorticotropin, epinephrine, and vasopressin responses. Endocrinology 112, 624–632. Biggers, D. W., Myers, S. R., Neal, D., Stinson, R., Cooper, N. B., Jaspan, J. B., Williams, P. E., Cherrington, A. D. and Frizzell, R. T. (1989) Role of brain in counterregulation of insulin-induced hypoglycemia in dogs. Diabetes 38, 7–16. Frizzell, R. T., Jones, E. M., Davis, S. N., Biggers, D. W., Myers, S. R., Connolly, C. C., Neal, D. W., Jaspan, J. B. and Cherrington, A. D. (1993) Counterregulation during hypoglycemia is directed by widespread brain regions. Diabetes 42, 1253–1261. Grill, H. J. and Kaplan, J. M. (2002) The neuroanatomical axis for control of energy balance. Front Neuroendocrinol 23, 2–40. Havel, P. J. (2001) Peripheral signals conveying metabolic information to the brain: short-term and long-term regulation of food intake and energy homeostasis. Exp Biol Med (Maywood) 226, 963–977. Schwartz, M. W., Woods, S. C., Porte, D., Jr., Seeley, R. J. and Baskin, D. G. (2000) Central nervous system control of food intake. Nature 404, 661–671. Woods, S. C. and Seeley, R. J. (2000) Adiposity signals and the control of energy homeostasis. Nutrition 16, 894–902.

198

CENTRAL REGULATION OF PERIPHERAL GLUCOSE METABOLISM

31. Woods, S. C., Schwartz, M. W., Baskin, D. G. and Seeley, R. J. (2000) Food intake and the regulation of body weight. Annu Rev Psychol 51, 255–277. 32. Himsworth, R. L. (1970) Hypothalamic control of adrenaline secretion in response to insufficient glucose. J Physiol 206, 411–417. 33. Borg, W. P., During, M. J., Sherwin, R. S., Borg, M. A., Brines, M. L. and Shulman, G. I. (1994) Ventromedial hypothalamic lesions in rats suppress counterregulatory responses to hypoglycemia. J Clin Invest 93, 1677–1682. 34. Borg, W. P., Sherwin, R. S., During, M. J., Borg, M. A. and Shulman, G. I. (1995) Local ventromedial hypothalamus glucopenia triggers counterregulatory hormone release. Diabetes 44, 180–184. 35. Borg, M. A., Sherwin, R. S., Borg, W. P., Tamborlane, W. V. and Shulman, G. I. (1997) Local ventromedial hypothalamus glucose perfusion blocks counterregulation during systemic hypoglycemia in awake rats. J Clin Invest 99, 361–365. 36. Ritter, S., Dinh, T. T. and Zhang, Y. (2000) Localization of hindbrain glucoreceptive sites controlling food intake and blood glucose. Brain Res 856, 37–47. 37. Ritter, R. C., Slusser, P. G. and Stone, S. (1981) Glucoreceptors controlling feeding and blood glucose: location in the hindbrain. Science 213, 451–452. 38. DiRocco, R. J. and Grill, H. J. (1979) The forebrain is not essential for sympathoadrenal hyperglycemic response to glucoprivation. Science 204, 1112–1114. 39. Atef, N., Laury, M. C., N’Guyen, J. M., Mokhtar, N., Ktorza, A. and Penicaud, L. (1997) Increased pancreatic islet blood flow in 48-hour glucose-infused rats: involvement of central and autonomic nervous systems. Endocrinology 138, 1836–1840. 40. Mobbs, C. V., Kow, L. M. and Yang, X. J. (2001) Brain glucose-sensing mechanisms: ubiquitous silencing by aglycemia vs. hypothalamic neuroendocrine responses. Am J Physiol Endocrinol Metab 281, E649–E654. 41. Levin, B. E., Dunn-Meynell, A. A. and Routh, V. H. (2002) CNS sensing and regulation of peripheral glucose levels. Int Rev Neurobiol 51, 219–258. 42. Yang, X. J., Kow, L. M., Funabashi, T. and Mobbs, C. V. (1999) Hypothalamic glucose sensor: similarities to and differences from pancreatic beta-cell mechanisms. Diabetes 48, 1763–1772. 43. Routh, V. H. (2002) Glucose-sensing neurons: are they physiologically relevant? Physiol Behav 76, 403–413. 44. Oomura, Y., Kimura, K., Ooyama, H., Maeno, T., Iki, M. and Kuniyoshi, M. (1964) Reciprocal activities of the ventromedial and lateral hypothalamic areas of cats. Science 143, 484–485. 45. Oomura, Y. (1976) Hunger: Basic Mechanisms and Clinical Implications. New York: Raven. 46. Oomura, Y., Ono, T., Ooyama, H. and Wayner, M. J. (1969) Glucose and osmosensitive neurones of the rat hypothalamus. Nature 222, 282–284. 47. Himmi, T., Perrin, J., Dallaporta, M. and Orsini, J. C. (2001) Effects of lactate on glucose-sensing neurons in the solitary tract nucleus. Physiol Behav 74, 391–397. 48. Silver, I. A. and Erecinska, M. (1998) Glucose-induced intracellular ion changes in sugar-sensitive hypothalamic neurons. J Neurophysiol 79, 1733–1745. 49. Song, Z., Levin, B. E., McArdle, J. J., Bakhos, N. and Routh, V. H. (2001) Convergence of pre- and postsynaptic influences on glucosensing neurons in the ventromedial hypothalamic nucleus. Diabetes 50, 2673–2681. 50. Funahashi, H., Yada, T., Muroya, S., Takigawa, M., Ryushi, T., Horie, S., Nakai, Y. and Shioda, S. (1999) The effect of leptin on feeding-regulating neurons in the rat hypothalamus. Neurosci Lett 264, 117–120.

REFERENCES

199

51. Kow, L. M. and Pfaff, D. W. (1989) Responses of hypothalamic paraventricular neurons in vitro to norepinephrine and other feeding-relevant agents. Physiol Behav 46, 265–271. 52. Mizuno, Y. and Oomura, Y. (1984) Glucose responding neurons in the nucleus tractus solitarius of the rat: in vitro study. Brain Res 307, 109–116. 53. Ashford, M. L., Boden, P. R. and Treherne, J. M. (1990) Tolbutamide excites rat glucoreceptive ventromedial hypothalamic neurones by indirect inhibition of ATP-K+ channels. Br J Pharmacol 101, 531–540. 54. Ashford, M. L., Boden, P. R. and Treherne, J. M. (1990) Glucose-induced excitation of hypothalamic neurones is mediated by ATP-sensitive K+ channels. Pflugers Arch 415, 479–483. 55. Zhang, Y. and Roane, D. S. (2001) Glibenclamide’s action in the hypothalamus alters peripheral glucose homeostasis. Eur J Pharmacol 424, R1–R2. 56. Aguilar-Bryan, L., Clement, J. P., Gonzalez, G., Kunjilwar, K., Babenko, A. and Bryan, J. (1998) Toward understanding the assembly and structure of KATP channels. Physiol Rev 78, 227–245. 57. Newgard, C. B. and McGarry, J. D. (1995) Metabolic coupling factors in pancreatic beta-cell signal transduction. Annu Rev Biochem 64, 689–719. 58. Lee, K., Dixon, A. K., Richardson, P. J. and Pinnock, R. D. (1999) Glucose-receptive neurones in the rat ventromedial hypothalamus express KATP channels composed of Kir6.1 and SUR1 subunits. J Physiol 515 (Pt 2), 439–452. 59. Miki, T., Liss, B., Minami, K., Shiuchi, T., Saraya, A., Kashima, Y., Horiuchi, M., Ashcroft, F., Minokoshi, Y., Roeper, J. and Seino, S. (2001) ATP-sensitive K+ channels in the hypothalamus are essential for the maintenance of glucose homeostasis. Nat Neurosci 4, 507–512. 60. Treherne, J. M. and Ashford, M. L. (1991) The regional distribution of sulphonylurea binding sites in rat brain. Neuroscience 40, 523–531. 61. Karschin, C., Ecke, C., Ashcroft, F. M. and Karschin, A. (1997) Overlapping distribution of K(ATP) channel-forming Kir6.2 subunit and the sulfonylurea receptor SUR1 in rodent brain. FEBS Lett 401, 59–64. 62. Dunn-Meynell, A. A., Rawson, N. E. and Levin, B. E. (1998) Distribution and phenotype of neurons containing the ATP-sensitive K+ channel in rat brain. Brain Res 814, 41–54. 63. Matschinsky, F. M., Glaser, B. and Magnuson, M. A. (1998) Pancreatic beta-cell glucokinase: closing the gap between theoretical concepts and experimental realities. Diabetes 47, 307–315. 64. Roncero, I., Alvarez, E., Vazquez, P. and Blazquez, E. (2000) Functional glucokinase isoforms are expressed in rat brain. J Neurochem 74, 1848–1857. 65. Lynch, R. M., Tompkins, L. S., Brooks, H. L., Dunn-Meynell, A. A. and Levin, B. E. (2000) Localization of glucokinase gene expression in the rat brain. Diabetes 49, 693–700. 66. Dunn-Meynell, A. A., Routh, V. H., Kang, L., Gaspers, L. and Levin, B. E. (2002) Glucokinase is the likely mediator of glucosensing in both glucose-excited and glucoseinhibited central neurons. Diabetes 51, 2056–2065. 67. Jetton, T. L., Liang, Y., Pettepher, C. C., Zimmerman, E. C., Cox, F. G., Horvath, K., Matschinsky, F. M. and Magnuson, M. A. (1994) Analysis of upstream glucokinase promoter activity in transgenic mice and identification of glucokinase in rare neuroendocrine cells in the brain and gut. J Biol Chem 269, 3641–3654. 68. Lautt, W. W. (1980) Hepatic nerves: a review of their functions and effects. Can J Physiol Pharmacol 58, 105–123.

200

CENTRAL REGULATION OF PERIPHERAL GLUCOSE METABOLISM

69. Yamaguchi, N. (1992) Sympathoadrenal system in neuroendocrine control of glucose: mechanisms involved in the liver, pancreas, and adrenal gland under hemorrhagic and hypoglycemic stress. Can J Physiol Pharmacol 70, 167–206. 70. Shimazu, T. (1967) Glycogen synthetase activity in liver: regulation by the autonomic nerves. Science 156, 1256–1257. 71. Niijima, A. (1985) Blood glucose levels modulate efferent activity in the vagal supply to the rat liver. J Physiol 364, 105–112. 72. Edwards, A. V. and Silver, M. (1970) The glycolytic response to stimulation of the splanchnic nerves in adrenalectomized calves. J Physiol 211, 109–124. 73. Shimazu, T. and Amakawa, M. (1968) Regulation of glycogen metabolism in liver by the autonomic nervous system. 2. Neural control of glycogenolytic enzymes. Biochim Biophys Acta 165, 335–348. 74. Shimazu, T. and Amakawa, A. (1968) Regulation of glycogen metabolism in liver by the autonomic nervous system. 3. Different effects of sympathetic nerve stimulation and catecholamines on liver phosphorylase. Biochim Biophys Acta 165, 349–356. 75. Miller, R. E. (1981) Pancreatic neuroendocrinology: peripheral neural mechanisms in the regulation of the islets of Langerhans. Endocr Rev 2, 471–494. 76. Anand, B. K. and Brobek, J. R. (1951) Hypothalamic control of food intake in rats and cats. Yale J Biol Med 77, 123–146. 77. Ahren, B., Taborsky, G. J., Jr., and Porte, D., Jr. (1986) Neuropeptidergic versus cholinergic and adrenergic regulation of islet hormone secretion. Diabetologia 29, 827–836. 78. Luiten, P. G., ter Horst, G. J., Buijs, R. M. and Steffens, A. B. (1986) Autonomic innervation of the pancreas in diabetic and non-diabetic rats. A new view on intramural sympathetic structural organization. J Auton Nerv Syst 15, 33–44. 79. Luiten, P. G., ter Horst, G. J., Koopmans, S. J., Rietberg, M. and Steffens, A. B. (1984) Preganglionic innervation of the pancreas islet cells in the rat. J Auton Nerv Syst 10, 27–42. 80. Niijima, A. (1986) Neural control of blood glucose level. Jpn J Physiol 36, 827–841. 81. Kaneto, A., Kosaka, K. and Nakao, K. (1967) Effect of stimulation of the vagus nerve on insulin secretion. Endocrinology 80, 530–536. 82. Kaneto, A., Miki, E. and Kosaka, K. (1974) Effects of vagal stimulation on glucagon and insulin secretion. Endocrinology 95, 1005–1010. 83. Bloom, S. R., Edwards, A. V. and Vaughan, N. J. (1974) The role of the autonomic innervation in the control of glucagon release during hypoglycaemia in the calf. J Physiol 236, 611–623. 84. Kaneto, A., Kajinuma, H. and Kosaka, K. (1975) Effect of splanchnic nerve stimulation on glucagon and insulin output in the dog. Endocrinology 96, 143–150. 85. Bloom, S. R. and Edwards, A. V. (1975) The release of pancreatic glucagon and inhibition of insulin in response to stimulation of the sympathetic innervation. J Physiol 253, 157–173. 86. Bloom, S. R., Edwards, A. V. and Vaughan, N. J. (1973) The role of the sympathetic innervation in the control of plasma glucagon concentration in the calf. J Physiol 233, 457–466. 87. Esterhuizen, A. C. and Howell, S. L. (1970) Ultrastructure of the A-cells of cat islets of Langerhans following sympathetic stimulation of glucagon secretion. J Cell Biol 46, 593–598. 88. Porte, D., Jr. (1967) A receptor mechanism for the inhibition of insulin release by epinephrine in man. J Clin Invest 46, 86–94.

REFERENCES

201

89. Havel, P. J., Flatness, D. E., Halter, J. B., Best, J. D., Veith, R. C. and Taborsky, G. J., Jr. (1987) Halothane anesthesia does not suppress sympathetic activation produced by neuroglucopenia. Am J Physiol 252, E667–E672. 90. Raghu, P. K., Taborsky, G. J., Jr., Paquette, T. L., Halter, J. B. and Palmer, J. P. (1984) Evidence for noncholinergic ganglionic neural stimulation of B cell secretion. Am J Physiol 247, E265–E270. 91. Havel, P. J., Veith, R. C., Dunning, B. E. and Taborsky, G. J., Jr. (1988) Pancreatic noradrenergic nerves are activated by neuroglucopenia but not by hypotension or hypoxia in the dog. Evidence for stress-specific and regionally selective activation of the sympathetic nervous system. J Clin Invest 82, 1538–1545. 92. Cannon, W. B., Mcluer, M. A. and Bliss, S. W. (1924) Studies on the condition of activity in endocrine glands. XIII. A sympathetic and adrenal mechanism for mobilizing sugar in hypoglycemia. Am J Physiol 69, 46–66. 93. Gale, E. A., Bennett, T., Macdonald, I. A., Holst, J. J. and Matthews, J. A. (1983) The physiological effects of insulin-induced hypoglycaemia in man: responses at differing levels of blood glucose. Clin Sci (Lond) 65, 263–271. 94. Cantu, R. C., Wise, B. L., Goldfein, A., Gullixson, K. S., Fisher, N. J. and Ganong, W. F. (1963) Neural pathways mediating the increase in adrenal medullary secretion produced by hypoglycemia. Proc Soc Exp Biol Med 114, 10–13. 95. Ikeda, H. (1968) Adrenal medullary secretion in response to insulin hypoglycemia in dogs with transection of the spinal cord. Tohoku J Exp Med 95, 153–168. 96. Haito, K., Takeda, A., Kagawa, S., Shimizu, S. and Matsuoka, A. (1984) Cholinergic effect of 2-deoxy-D-glucose on plasma glucagon levels in conscious rats. Horm Metab Res 16 (Suppl. 1), 110–113. 97. Yoshimatsu, H., Oomura, Y., Katafuchi, T. and Niijima, A. (1987) Effects of hypothalamic stimulation and lesion on adrenal nerve activity. Am J Physiol 253, R418–R424. 98. Flanagan, D. E., Keshavarz, T., Evans, M. L., Flanagan, S., Fan, X., Jacob, R. J. and Sherwin, R. S. (2003) Role of corticotrophin-releasing hormone in the impairment of counterregulatory responses to hypoglycemia. Diabetes 52, 605–613. 99. Russek, M. (1963) Participation of hepatic glucoreceptors in the control of food intake. Nature 197, 79–80. 100. Hevener, A. L., Bergman, R. N. and Donovan, C. M. (1997) Novel glucosensor for hypoglycemic detection localized to the portal vein. Diabetes 46, 1521–1525. 101. Berthoud, H. R., Kressel, M. and Neuhuber, W. L. (1992) An anterograde tracing study of the vagal innervation of rat liver, portal vein and biliary system. Anat Embryol (Berl) 186, 431–442. 102. Barja, F. and Mathison, R. (1984) Sensory innervation of the rat portal vein and the hepatic artery. J Auton Nerv Syst 10, 117–125. 103. Berthoud, H. R., Kressel, M. and Neuhuber, W. L. (1995) Vagal afferent innervation of rat abdominal paraganglia as revealed by anterograde DiI-tracing and confocal microscopy. Acta Anat (Basel) 152, 127–132. 104. Niijima, A. (1969) Afferent impulse discharges from glucoreceptors in the liver of the guinea pig. Ann NY Acad Sci 157, 690–700. 105. Niijima, A. (1982) Glucose-sensitive afferent nerve fibres in the hepatic branch of the vagus nerve in the guinea-pig. J Physiol 332, 315–323. 106. Niijima, A. (1981) Visceral afferents and metabolic function. Diabetologia 20 (Suppl.), 325–330. 107. Shimizu, N., Oomura, Y., Novin, D., Grijalva, C. V. and Cooper, P. H. (1983) Functional correlations between lateral hypothalamic glucose-sensitive neurons and hepatic portal glucose-sensitive units in rat. Brain Res 265, 49–54.

202

CENTRAL REGULATION OF PERIPHERAL GLUCOSE METABOLISM

108. Perseghin, G., Regalia, E., Battezzati, A., Vergani, S., Pulvirenti, A., Terruzzi, I., Baratti, D., Bozzetti, F., Mazzaferro, V. and Luzi, L. (1997) Regulation of glucose homeostasis in humans with denervated livers. J Clin Invest 100, 931–941. 109. Bolli, G., De Feo, P., Perriello, G., De Cosmo, S., Ventura, M., Campbell, P., Brunetti, P. and Gerich, J. E. (1985) Role of hepatic autoregulation in defense against hypoglycemia in humans. J Clin Invest 75, 1623–1631. 110. Hevener, A. L., Bergman, R. N. and Donovan, C. M. (2000) Portal vein afferents are critical for the sympathoadrenal response to hypoglycemia. Diabetes 49, 8–12. 111. Connolly, C. C., Adkins-Marshall, B. A., Neal, D. W., Pugh, W., Jaspan, J. B. and Cherrington, A. D. (1992) Relationship between decrements in glucose level and metabolic response to hypoglycemia in absence of counterregulatory hormones in the conscious dog. Diabetes 41, 1308–1319. 112. Hansen, I., Firth, R., Haymond, M., Cryer, P. and Rizza, R. (1986) The role of autoregulation of the hepatic glucose production in man. Response to a physiologic decrement in plasma glucose. Diabetes 35, 186–191. 113. Frizzell, R. T., Hendrick, G. K., Brown, L. L., Lacy, D. B., Donahue, E. P., Carr, R. K., Williams, P. E., Parlow, A. F., Stevenson, R. W. and Cherrington, A. D. (1988) Stimulation of glucose production through hormone secretion and other mechanisms during insulin-induced hypoglycemia. Diabetes 37, 1531–1541. 114. Frizzell, R. T., Hendrick, G. K., Biggers, D. W., Lacy, D. B., Donahue, D. P., Green, D. R., Carr, R. K., Williams, P. E., Stevenson, R. W. and Cherrington, A. D. (1988) Role of gluconeogenesis in sustaining glucose production during hypoglycemia caused by continuous insulin infusion in conscious dogs. Diabetes 37, 749–759. 115. McCraw, E. F., Peterson, M. J. and Ashmore, J. (1967) Autoregulation of glucose metabolism in the isolated perfused rat liver. Proc Soc Exp Biol Med 126, 232–236. 116. Bucolo, R. J., Bergman, R. N., Marsh, D. J. and Yates, F. E. (1974) Dynamics of glucose autoregulation in the isolated, blood-perfused canine liver. Am J Physiol 227, 209–217. 117. Ruderman, N. B. and Herrera, M. G. (1968) Glucose regulation of hepatic gluconeogenesis. Am J Physiol 214, 1346–1351. 118. Davidson, M. B. (1981) Autoregulation by glucose of hepatic glucose balance: permissive effect of insulin. Metabolism 30, 279–284. 119. Diem, P., Redmon, J. B., Abid, M., Moran, A., Sutherland, D. E., Halter, J. B. and Robertson, R. P. (1990) Glucagon, catecholamine and pancreatic polypeptide secretion in type I diabetic recipients of pancreas allografts. J Clin Invest 86, 2008–2013. 120. Battezzati, A., Luzi, L., Perseghin, G., Bianchi, E., Spotti, D., Secchi, A., Vergani, S., Di, C. V. and Pozza, G. (1994) Persistence of counter-regulatory abnormalities in insulin-dependent diabetes mellitus after pancreas transplantation. Eur J Clin Invest 24, 751–758. 121. Kendall, D. M., Rooney, D. P., Smets, Y. F., Salazar, B. L. and Robertson, R. P. (1997) Pancreas transplantation restores epinephrine response and symptom recognition during hypoglycemia in patients with long-standing type I diabetes and autonomic neuropathy. Diabetes 46, 249–257. 122. Zhang, Y., Proenca, R., Maffei, M., Barone, M., Leopold, L. and Friedman, J. M. (1994) Positional cloning of the mouse obese gene and its human homologue. Nature 372, 425–432. 123. Cone, R. D., Cowley, M. A., Butler, A. A., Fan, W., Marks, D. L. and Low, M. J. (2001) The arcuate nucleus as a conduit for diverse signals relevant to energy homeostasis. Int J Obes Relat Metab Disord 25 (Suppl. 5), S63–S67. 124. Flier, J. S. and Maratos-Flier, E. (1998) Obesity and the hypothalamus: novel peptides for new pathways. Cell 92, 437–440.

REFERENCES

203

125. Friedman, J. M. and Halaas, J. L. (1998) Leptin and the regulation of body weight in mammals. Nature 395, 763–770. 126. Montague, C. T., Farooqi, I. S., Whitehead, J. P., Soos, M. A., Rau, H., Wareham, N. J., Sewter, C. P., Digby, J. E., Mohammed, S. N., Hurst, J. A., Cheetham, C. H., Earley, A. R., Barnett, A. H., Prins, J. B. and O’Rahilly, S. (1997) Congenital leptin deficiency is associated with severe early-onset obesity in humans. Nature 387, 903–908. 127. Kamohara, S., Burcelin, R., Halaas, J. L., Friedman, J. M. and Charron, M. J. (1997) Acute stimulation of glucose metabolism in mice by leptin treatment. Nature 389, 374–377. 128. Liu, L., Karkanias, G. B., Morales, J. C., Hawkins, M., Barzilai, N., Wang, J. and Rossetti, L. (1998) Intracerebroventricular leptin regulates hepatic but not peripheral glucose fluxes. J Biol Chem 273, 31 160–31 167. 129. Shimomura, I., Hammer, R. E., Ikemoto, S., Brown, M. S. and Goldstein, J. L. (1999) Leptin reverses insulin resistance and diabetes mellitus in mice with congenital lipodystrophy. Nature 401, 73–76. 130. Gavrilova, O., Marcus-Samuels, B., Leon, L. R., Vinson, C. and Reitman, M. L. (2000) Leptin and diabetes in lipoatrophic mice. Nature 403, 850–851. 131. Petersen, K. F., Oral, E. A., Dufour, S., Befroy, D., Ariyan, C., Yu, C., Cline, G. W., DePaoli, A. M., Taylor, S. I., Gorden, P. and Shulman, G. I. (2002) Leptin reverses insulin resistance and hepatic steatosis in patients with severe lipodystrophy. J Clin Invest 109, 1345–1350. 132. El Haschimi, K., Dufresne, S. D., Hirshman, M. F., Flier, J. S., Goodyear, L. J. and Bjorbaek, C. (2003) Insulin resistance and lipodystrophy in mice lacking ribosomal S6 kinase 2. Diabetes 52, 1340–1346. 133. Hubschle, T., Thom, E., Watson, A., Roth, J., Klaus, S. and Meyerhof, W. (2001) Leptin-induced nuclear translocation of STAT3 immunoreactivity in hypothalamic nuclei involved in body weight regulation. J. Neurosci 21, 2413–2424. 134. Munzberg, H., Huo, L., Nillni, E. A., Hollenberg, A. N. and Bjorbaek, C. (2003) Role of signal transducer and activator of transcription 3 in regulation of hypothalamic proopiomelanocortin gene expression by leptin. Endocrinology 144, 2121–2131. 135. Mercer, J. G., Hoggard, N., Williams, L. M., Lawrence, C. B., Hannah, L. T. and Trayhurn, P. (1996) Localization of leptin receptor mRNA and the long form splice variant (Ob-Rb) in mouse hypothalamus and adjacent brain regions by in situ hybridization. FEBS Lett 387, 113–116. 136. Elmquist, J. K., Bjorbaek, C., Ahima, R. S., Flier, J. S. and Saper, C. B. (1998) Distributions of leptin receptor mRNA isoforms in the rat brain. J Comp Neurol 395, 535–547. 137. Grill, H. J., Schwartz, M. W., Kaplan, J. M., Foxhall, J. S., Breininger, J. and Baskin, D. G. (2002) Evidence that the caudal brainstem is a target for the inhibitory effect of leptin on food intake. Endocrinology 143, 239–246. 138. Hosoi, T., Kawagishi, T., Okuma, Y., Tanaka, J. and Nomura, Y. (2002) Brain stem is a direct target for leptin’s action in the central nervous system. Endocrinology 143, 3498–3504. 139. Cowley, M. A., Smart, J. L., Rubinstein, M., Cerdan, M. G., Diano, S., Horvath, T. L., Cone, R. D. and Low, M. J. (2001) Leptin activates anorexigenic POMC neurons through a neural network in the arcuate nucleus. Nature 411, 480–484. 140. Schwartz, G. J. and Moran, T. H. (2002) Leptin and neuropeptide y have opposing modulatory effects on nucleus of the solitary tract neurophysiological responses to gastric loads: implications for the control of food intake. Endocrinology 143, 3779–3784.

204

CENTRAL REGULATION OF PERIPHERAL GLUCOSE METABOLISM

141. Spanswick, D., Smith, M. A., Groppi, V. E., Logan, S. D. and Ashford, M. L. (1997) Leptin inhibits hypothalamic neurons by activation of ATP-sensitive potassium channels. Nature 390, 521–525. 142. Steffens, A. B., Scheurink, A. J., Luiten, P. G. and Bohus, B. (1988) Hypothalamic food intake regulating areas are involved in the homeostasis of blood glucose and plasma FFA levels. Physiol Behav 44, 581–589. 143. Minokoshi, Y., Haque, M. S. and Shimazu, T. (1999) Microinjection of leptin into the ventromedial hypothalamus increases glucose uptake in peripheral tissues in rats. Diabetes 48, 287–291. 144. Haque, M. S., Minokoshi, Y., Hamai, M., Iwai, M., Horiuchi, M. and Shimazu, T. (1999) Role of the sympathetic nervous system and insulin in enhancing glucose uptake in peripheral tissues after intrahypothalamic injection of leptin in rats. Diabetes 48, 1706–1712. 145. Baskin, D. G., Hahn, T. M. and Schwartz, M. W. (1999) Leptin sensitive neurons in the hypothalamus. Horm Metab Res 31, 345–350. 146. Clark, J. T., Kalra, P. S., Crowley, W. R. and Kalra, S. P. (1984) Neuropeptide Y and human pancreatic polypeptide stimulate feeding behavior in rats. Endocrinology 115, 427–429. 147. Stanley, B. G. and Leibowitz, S. F. (1984) Neuropeptide Y: stimulation of feeding and drinking by injection into the paraventricular nucleus. Life Sci 35, 2635–2642. 148. Levine, A. S. and Morley, J. E. (1984) Neuropeptide Y: a potent inducer of consummatory behavior in rats. Peptides 5, 1025–1029. 149. Hahn, T. M., Breininger, J. F., Baskin, D. G. and Schwartz, M. W. (1998) Coexpression of Agrp and NPY in fasting-activated hypothalamic neurons. Nat Neurosci 1, 271–272. 150. Tsujii, S. and Bray, G. A. (1989) Acetylation alters the feeding response to MSH and beta-endorphin. Brain Res Bull 23, 165–169. 151. Kask, A., Rago, L., Mutulis, F., Pahkla, R., Wikberg, J. E. and Schioth, H. B. (1998) Selective antagonist for the melanocortin 4 receptor (HS014) increases food intake in free-feeding rats. Biochem Biophys Res Commun 245, 90–93. 152. Murphy, B., Nunes, C. N., Ronan, J. J., Harper, C. M., Beall, M. J., Hanaway, M., Fairhurst, A. M., Van der Ploeg, L. H., MacIntyre, D. E. and Mellin, T. N. (1998) Melanocortin mediated inhibition of feeding behavior in rats. Neuropeptides 32, 491–497. 153. Elias, C. F., Lee, C., Kelly, J., Aschkenasi, C., Ahima, R. S., Couceyro, P. R., Kuhar, M. J., Saper, C. B. and Elmquist, J. K. (1998) Leptin activates hypothalamic CART neurons projecting to the spinal cord. Neuron 21, 1375–1385. 154. Elias, C. F., Saper, C. B., Maratos-Flier, E., Tritos, N. A., Lee, C., Kelly, J., Tatro, J. B., Hoffman, G. E., Ollmann, M. M., Barsh, G. S., Sakurai, T., Yanagisawa, M. and Elmquist, J. K. (1998) Chemically defined projections linking the mediobasal hypothalamus and the lateral hypothalamic area. J Comp Neurol 402, 442–459. 155. Schwartz, M. W., Seeley, R. J., Woods, S. C., Weigle, D. S., Campfield, L. A., Burn, P. and Baskin, D. G. (1997) Leptin increases hypothalamic pro-opiomelanocortin mRNA expression in the rostral arcuate nucleus. Diabetes 46, 2119–2123. 156. Mizuno, T. M., Kleopoulos, S. P., Bergen, H. T., Roberts, J. L., Priest, C. A. and Mobbs, C. V. (1998) Hypothalamic pro-opiomelanocortin mRNA is reduced by fasting and [corrected] in ob/ob and db/db mice, but is stimulated by leptin. Diabetes 47, 294–297. 157. Fan, W., Boston, B. A., Kesterson, R. A., Hruby, V. J. and Cone, R. D. (1997) Role of melanocortinergic neurons in feeding and the agouti obesity syndrome. Nature 385, 165–168.

REFERENCES

205

158. Huszar, D., Lynch, C. A., Fairchild-Huntress, V., Dunmore, J. H., Fang, Q., Berkemeier, L. R., Gu, W., Kesterson, R. A., Boston, B. A., Cone, R. D., Smith, F. J., Campfield, L. A., Burn, P. and Lee, F. (1997) Targeted disruption of the melanocortin-4 receptor results in obesity in mice. Cell 88, 131–141. 159. Boston, B. A., Blaydon, K. M., Varnerin, J. and Cone, R. D. (1997) Independent and additive effects of central POMC and leptin pathways on murine obesity. Science 278, 1641–1644. 160. Kask, A., Rago, L., Wikberg, J. E. and Schioth, H. B. (1998) Evidence for involvement of the melanocortin MC4 receptor in the effects of leptin on food intake and body weight. Eur J Pharmacol 360, 15–19. 161. Mizuno, T. M., Makimura, H., Silverstein, J., Roberts, J. L., Lopingco, T. and Mobbs, C. V. (1999) Fasting regulates hypothalamic neuropeptide Y, agouti-related peptide, and proopiomelanocortin in diabetic mice independent of changes in leptin or insulin. Endocrinology 140, 4551–4557. 162. Korner, J., Savontaus, E., Chua, S. C., Jr., Leibel, R. L. and Wardlaw, S. L. (2001) Leptin regulation of Agrp and Npy mRNA in the rat hypothalamus. J Neuroendocrinol 13, 959–966. 163. Ibrahim, N., Bosch, M. A., Smart, J. L., Qiu, J., Rubinstein, M., Ronnekleiv, O. K., Low, M. J. and Kelly, M. J. (2003) Hypothalamic proopiomelanocortin neurons are glucose responsive and express K(ATP) channels. Endocrinology 144, 1331–1340. 164. Muroya, S., Yada, T., Shioda, S. and Takigawa, M. (1999) Glucose-sensitive neurons in the rat arcuate nucleus contain neuropeptide Y. Neurosci Lett 264, 113–116. 165. Fan, W., Dinulescu, D. M., Butler, A. A., Zhou, J., Marks, D. L. and Cone, R. D. (2000) The central melanocortin system can directly regulate serum insulin levels. Endocrinology 141, 3072–3079. 166. Palkovits, M. (1999) Interconnections between the neuroendocrine hypothalamus and the central autonomic system. Geoffrey Harris Memorial Lecture, Kitakyushu, Japan, October 1998. Front Neuroendocrinol 20, 270–295. 167. Haynes, W. G., Morgan, D. A., Djalali, A., Sivitz, W. I. and Mark, A. L. (1999) Interactions between the melanocortin system and leptin in control of sympathetic nerve traffic. Hypertension 33, 542–547. 168. Havrankova, J., Roth, J. and Brownstein, M. (1978) Insulin receptors are widely distributed in the central nervous system of the rat. Nature 272, 827–829. 169. Marks, J. L., Porte, D., Jr., Stahl, W. L. and Baskin, D. G. (1990) Localization of insulin receptor mRNA in rat brain by in situ hybridization. Endocrinology 127, 3234–3236. 170. Werther, G. A., Hogg, A., Oldfield, B. J., McKinley, M. J., Figdor, R., Allen, A. M. and Mendelsohn, F. A. (1987) Localization and characterization of insulin receptors in rat brain and pituitary gland using in vitro autoradiography and computerized densitometry. Endocrinology 121, 1562–1570. 171. Woods, S. C., Lotter, E. C., McKay, L. D. and Porte, D., Jr. (1979) Chronic intracerebroventricular infusion of insulin reduces food intake and body weight of baboons. Nature 282, 503–505. 172. Schwartz, M. W., Marks, J. L., Sipols, A. J., Baskin, D. G., Woods, S. C., Kahn, S. E. and Porte, D., Jr. (1991) Central insulin administration reduces neuropeptide Y mRNA expression in the arcuate nucleus of food-deprived lean (Fa/Fa) but not obese (fa/fa) Zucker rats. Endocrinology 128, 2645–2647. 173. McGowan, M. K., Andrews, K. M. and Grossman, S. P. (1992) Chronic intrahypothalamic infusions of insulin or insulin antibodies alter body weight and food intake in the rat. Physiol Behav 51, 753–766.

206

CENTRAL REGULATION OF PERIPHERAL GLUCOSE METABOLISM

174. Bruning, J. C., Gautam, D., Burks, D. J., Gillette, J., Schubert, M., Orban, P. C., Klein, R., Krone, W., Muller-Wieland, D. and Kahn, C. R. (2000) Role of brain insulin receptor in control of body weight and reproduction. Science 289, 2122–2125. 175. Obici, S., Feng, Z., Karkanias, G., Baskin, D. G. and Rossetti, L. (2002) Decreasing hypothalamic insulin receptors causes hyperphagia and insulin resistance in rats. Nat Neurosci 5, 566–572. 176. Obici, S., Zhang, B. B., Karkanias, G. and Rossetti, L. (2002) Hypothalamic insulin signaling is required for inhibition of glucose production. Nat Med 8, 1376–1382. 177. Davis, S. N., Dunham, B., Walmsley, K., Shavers, C., Neal, D., Williams, P. and Cherrington, A. D. (1997) Brain of the conscious dog is sensitive to physiological changes in circulating insulin. Am J Physiol 272, E567–E575. 178. Spanswick, D., Smith, M. A., Mirshamsi, S., Routh, V. H. and Ashford, M. L. (2000) Insulin activates ATP-sensitive K+ channels in hypothalamic neurons of lean, but not obese rats. Nat Neurosci 3, 757–758. 179. Porte, D., Jr., Baskin, D. G. and Schwartz, M. W. (2002) Leptin and insulin action in the central nervous system. Nutr Rev 60, S20–S29. 180. Benoit, S. C., Air, E. L., Coolen, L. M., Strauss, R., Jackman, A., Clegg, D. J., Seeley, R. J. and Woods, S. C. (2002) The catabolic action of insulin in the brain is mediated by melanocortins. J Neurosci 22, 9048–9052. 181. Obici, S., Feng, Z., Tan, J., Liu, L., Karkanias, G. and Rossetti, L. (2001) Central melanocortin receptors regulate insulin action. J Clin Invest 108, 1079–1085. 182. Goto, M. and Spitzer, J. J. (1971) Fatty acid profiles of various lipids in the cerebrospinal fluid. Proc Soc Exp Biol Med 136, 1294–1296. 183. Oomura, Y., Nakamura, T., Sugimori, M. and Yamada, Y. (1975) Effect of free fatty acid on the rat lateral hypothalamic neurons. Physiol Behav 14, 483–486. 184. Obici, S., Feng, Z., Morgan, K., Stein, D., Karkanias, G. and Rossetti, L. (2002) Central administration of oleic acid inhibits glucose production and food intake. Diabetes 51, 271–275. 185. Loftus, T. M., Jaworsky, D. E., Frehywot, G. L., Townsend, C. A., Ronnett, G. V., Lane, M. D. and Kuhajda, F. P. (2000) Reduced food intake and body weight in mice treated with fatty acid synthase inhibitors. Science 288, 2379–2381. 186. Larsson, O., Deeney, J. T., Branstrom, R., Berggren, P. O. and Corkey, B. E. (1996) Activation of the ATP-sensitive K+ channel by long chain acyl-CoA. A role in modulation of pancreatic beta-cell glucose sensitivity. J Biol Chem 271, 10 623–10 626. 187. Branstrom, R., Leibiger, I. B., Leibiger, B., Corkey, B. E., Berggren, P. O. and Larsson, O. (1998) Long chain coenzyme A esters activate the pore-forming subunit (Kir6. 2) of the ATP-regulated potassium channel. J Biol Chem 273, 31 395–31 400. 188. Staehr, P., Hother-Nielsen, O., Landau, B. R., Chandramouli, V., Holst, J. J. and BeckNielsen, H. (2003) Effects of free fatty acids per se on glucose production, gluconeogenesis, and glycogenolysis. Diabetes 52, 260–267. 189. Boden, G. and Jadali, F. (1991) Effects of lipid on basal carbohydrate metabolism in normal men. Diabetes 40, 686–692. 190. Ferrannini, E., Barrett, E. J., Bevilacqua, S. and DeFronzo, R. A. (1983) Effect of fatty acids on glucose production and utilization in man. J Clin Invest 72, 1737–1747. 191. Burdakov, D. and Ashcroft, F. M. (2002) Cholecystokinin tunes firing of an electrically distinct subset of arcuate nucleus neurons by activating A-type potassium channels. J Neurosci 22, 6380–6387. 192. Batterham, R. L., Cowley, M. A., Small, C. J., Herzog, H., Cohen, M. A., Dakin, C. L., Wren, A. M., Brynes, A. E., Low, M. J., Ghatei, M. A., Cone, R. D. and Bloom, S. R. (2002) Gut hormone PYY(3–36) physiologically inhibits food intake. Nature 418, 650–654.

8 Relationship Between Fat Distribution and Insulin Resistance Philip G. McTernan, Aresh Anwar and Sudhesh Kumar

8.1 Introduction Obesity is an important risk factor for the development of type 2 diabetes. Already type 2 diabetes mellitus affects over 23 million people in Europe with more than a million diagnosed in the UK alone.1 Clearly, the increase in prevalence of obesity is resulting in an epidemic of diabetes. While the reduction in physical activity and ‘change in diet’ has led to the increased incidence of obesity in adults and children, it is increasingly apparent that the distribution of fat impacts the risk of type 2 diabetes through its link with insulin resistance. This chapter will review our current understanding of the relationship of fat distribution to insulin resistance and related health risks.

8.2 Fat and its distribution Increased body weight derives from the capacity of adipose tissue to markedly alter its own mass, a feature specific to this tissue since no other organ is capable of such a vast change in adulthood. It is also apparent that a small increase in adipose tissue can have a dramatic effect on the increased risk of type 2 diabetes (Figure 8.1).2 The dynamic capacity of adipose tissue is illustrated by the variation in mass that can occur between individuals (Table 8.1). Adipose mass can range from as little as two to three per cent in highly conditioned athletes to 60–70 per cent of body mass in the morbidly obese.3 Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

208

RELATIONSHIP BETWEEN FAT DISTRIBUTION AND INSULIN RESISTANCE

Increased risk of diabetes

100

93.2

80

60

54.0 40.3

40 27.6 20

15.8 1.0

2.9

4.3

5.0

<22

22– 22.9

23– 23.9

24– 24.9

8.1 25– 27– 29– 26.9 28.9 30.9 BMI (kg/m2)

31– 32.9

33– 34.9

≥35

Figure 8.1 The associated risk of type 2 diabetes with increasing adiposity shown as body mass index (BMI) (adapted from reference 2)

A substantial gain in adipose tissue, as in obesity, arises as a consequence of a chronic imbalance between energy intake and energy expenditure (referred to as ‘positive energy balance’) and is also defined as a pathological excess of fat mass.4, 5 While there is increasing evidence that fat accumulation results in insulin resistance and metabolic diseases, it was work by Jean Vague that specifically examined the role of fat distribution.6 Genetic factors (40 per cent) have an important influence on the variation in body fat accumulation, but the obvious gender-specific pattern of adipose tissue deposition suggests a role for sex hormones. Women display the gynoid pattern of fat distribution, which is more commonly referred to as the ‘pear shape’, due to the accumulation of fat on the hips and thighs. Males have a different fat distribution and exhibit the android pattern of adiposity, also referred to as the ‘apple shape,’ where fat is stored centrally7 . These gender-specific variations in adipose distribution appear to be partly attributed to circulating sex steroid hormone levels, as indicated by the android pattern of adiposity that accompanies the post-menopausal state, as well as studies examining the effects of sex steroids on transsexuals.6, 8 – 11 These gender-related differences also impact upon the risk of developing obesityassociated co-morbidities, with men at heightened risk of disease compared with women of the same age (Figure 8.2).6 Men with a waist circumference of 94 cm (∼37 inches) or more are at an increased risk of obesity-associated metabolic diseases, while women with a waist circumference of 80 cm (∼32 inches) or more are at an increased risk. However, following menopause the female advantage in protection from heart disease appears to be lost. This is also accompanied by an associated change in fat distribution in women, which becomes ‘android’-like as oestrogen

BASIS FOR VARIATION IN ADIPOSE TISSUE MASS

209

Relative risk of type II diabetes

Health risks of fatness and fat distribution

20 15 10 III

5

II I

0 III

II BMI tertiles

/H

s

le

r ti

te

W

I

Ohlsen et al. (1985) Diabetes 34, 1055–1058

Figure 8.2 Central obesity confers a higher risk of metabolic and cardiovascular complications from obesity for a given degree of obesity as illustrated in this figure Table 8.1 Typical body fat composition in men and women Weight Normal weight Overweight Obese

Male (body fat percentage)

Female (body fat percentage)

9–18% 18–22% >22%

14–28% 29–32% >32%

synthesis by the ovaries is lost and fat becomes the main source of oestrogen production.7, 12

8.3 Basis for variation in adipose tissue mass Adipose tissue mass could be accounted for by an increase in adipocyte number as a result of proliferation and differentiation of pre-adipocytes into adipocytes.13 These changes in adipose mass may occur through autocrine or paracrine mechanisms since adipose tissue is known to secrete a variety of proteins and cytokines. Alternatively, circulating hormones and cytokines can also modulate pre-adipocyte cell growth. The pre-adipocyte cells undergo extensive change in appearance, gene expression (increased levels of enzymes involved in fat metabolism) and hormone sensitivity during differentiation.14 Weight in most normal, healthy individuals remains relatively constant, generally fluctuating between certain parameters. This implies that there are processes through which adipocyte volume and number are gained and lost, although most of the time these processes are in equilibrium. The balance may drastically shift

210

RELATIONSHIP BETWEEN FAT DISTRIBUTION AND INSULIN RESISTANCE

when dietary intake increases excessively or declines drastically. Lipogenesis (the storage of fat) and lipolysis are continuous processes occurring within the adipocytes, and the net outcome of these two processes basically determines the net flux of lipids from adipocyte tissue. Hence, alterations in adipocyte volume are due to the relative rates of lipogenesis and lipolysis. The same principle applies to the number of adipocytes present in any particular adipose depot. Pre-adipocytes are continuously undergoing proliferation and entering the differentiation pathway. However, the potential for pre-adipocytes to undergo differentiation is site specific as subcutaneous pre-adipocytes are predisposed to differentiate more easily than visceral pre-adipocytes. Simultaneously, there is adipocyte loss,14 which is most likely to be a result of apoptosis although there is the possibility that dedifferentiation may have a role.15 At present, studies suggest there are changes in pre-adipocyte number and adipocyte cell volume as more weight is gained.14

8.4 Change in adipocyte phenotype with obesity Adipose tissue mass is altered by the number of adipocytes present (through proliferation, differentiation and apoptosis) and adipocyte volume (which is altered by lipolysis, lipogenesis and enzyme metabolism). Consequently, the size and number of adipocytes in an individual are not fixed. Hypertrophic (increased cell volume) and hyperplastic (expansion of adipocyte number) growth can occur at any time when excess energy intake occurs. This activity is regulated at the hormonal and genetic level with key genes activating lipogenesis or lipolysis, thereby controlling the rate and intensity of fat accretion.5 At present, studies suggest that adipose mass undergoes both hypertrophic and hyperplastic growth, as more weight is gained.14 When adipose mass increases, hypertrophy generally precedes hyperplasia in a cyclical manner.5 Usually, adipose tissue contains a mixed population of adipocytes in terms of cell size. However, as fat mass increases and the adipocyte population expands, the cell population loses its heterogeneity with mature adipocytes increasing in cellular size. This supports the hypothesis of the critical cell size theory, in which adipocytes do not have a limitless capacity to store triglycerides, and, as such, activate cellular hyperplasia when they reach a critical size.16 It also has implications for insulin sensitivity in these subjects, as larger adipocytes are less insulin responsive than smaller cells. Furthermore, rodent studies have demonstrated that larger adipocytes secrete greater quantities of potentially pathogenic cytokines, such as TNF-α.17 Hence, the severest forms of obesity are associated with hyperplasia and have the poorest prognosis for treatment.18 – 20

8.5

Obesity and its association with insulin resistance

Insulin resistance is defined as a smaller than expected biological response to a given dose of insulin and is present within all obese subjects, although there is

THE PATHOGENIC SIGNIFICANCE OF ABDOMINAL ADIPOSE TISSUE

211

a large degree of variation in its severity.21 The link between increasing body weight and reduced insulin sensitivity was first demonstrated in 1962 in a study involving insulin infusion via the brachial artery.22 Subsequent studies in human and animal subjects have substantiated a cause and effect relationship between obesity and insulin resistance based on the observation that weight gain or loss correlates closely with increasing or decreasing insulin sensitivity.23, 24 Importantly, insulin resistance related to central obesity forms part of the metabolic syndrome: a cluster of metabolic and physiological abnormalities that includes central adiposity, hypertension, hyperinsulinaemia, insulin resistance, impaired fibrinolysis, dyslipidaemia and glucose intolerance.25 – 27 The importance of different fat depots for adipose-tissue-related insulin resistance is considered in the following section.

8.6

Subcutaneous and visceral adipose tissue

Evidence as to the relative importance of subcutaneous versus visceral fat in the pathogenesis of the metabolic syndrome is conflicting. Many in vitro and in vivo studies suggest that intra-peritoneal (visceral) fat is accountable for the central-obesity-linked health risks. Visceral fat constitutes only 6–20 per cent of total body fat volume but is the more metabolically active depot.28 The smaller visceral adipocytes are more responsive to the lipolytic effects of the catecholamines and less receptive to the anabolic effects of insulin.29, 30 Increased lipolysis (the breakdown of fat stores) in this depot would therefore result in non-esterified fatty acid (NEFA) release, and NEFAs are implicated in the development of insulin resistance. In vivo studies conducted in normal weight subjects, where insulin resistance was induced by lipid infusion, demonstrated that excess NEFAs reduced glucose uptake, glucose oxidation and glycogen synthesis.31 As well as this, the visceral depot drains directly into the portal vein, from which the liver obtains 80 per cent of its blood supply. The anatomy of the portal circulation results in increased hepatic uptake of NEFAs in the liver of viscerally obese individuals. Nevertheless, several studies maintain that subcutaneous adipose tissue, which comprises 80 per cent of total adipose tissue, has a significant role in the progression of central-obesity-linked health risks. Studies have shown that lipolysis within abdominal depots of subcutaneous adipose tissue is twice as high as the gluteofemoral adipose tissue in males;32 consequently, individuals with central adiposity, as a result of increased subcutaneous mass, also have higher plasma levels of NEFAs.33

8.7 The pathogenic significance of abdominal adipose tissue Central obesity encompasses both abdominal subcutaneous and intra-abdominal (visceral or omental) depots, which differ in their metabolic properties. At

212

RELATIONSHIP BETWEEN FAT DISTRIBUTION AND INSULIN RESISTANCE

present, controversy surrounds the relative contribution of abdominal subcutaneous versus visceral fat to the pathogenesis of the metabolic syndrome. Many in vitro and in vivo studies suggest that the visceral fat is accountable for the health risks linked to central obesity.34 Visceral fat constitutes only 6–20 per cent of total body fat volume but is the more metabolically active depot.28 The smaller visceral adipocytes are more responsive to the lipolytic effects of the catecholamines and less receptive to the anabolic effects of insulin.29, 30 Increased lipolysis in this depot would therefore result in greater NEFA release, and NEFAs are implicated in the development of insulin resistance. In vivo studies conducted in normal weight subjects, where insulin resistance was induced by lipid infusion, demonstrated that excess NEFAs reduced glucose uptake, glucose oxidation and glycogen synthesis.31 Nevertheless, several studies maintain that subcutaneous adipose tissue, which comprises approximately 80 per cent of total adipose tissue,35 has a significant role in the pathogenesis of central obesity associated disease.36 – 38 Studies have shown that lipolysis within abdominal depots of subcutaneous adipose tissue is twice as high as in the gluteofemoral adipose tissue in males;32 consequently individuals with central adiposity, as a result of increased subcutaneous mass, also have higher plasma levels of NEFAs.33

8.8 Potential mechanisms linking central obesity to the metabolic syndrome At present, several different paradigms have been offered to explain the association between the metabolic syndrome, type 2 diabetes and central obesity. However, these are not mutually exclusive and the progression of the disease probably arises from a complex interplay between several of these mechanisms.

8.9 Randle hypothesis/glucose–fatty acid hypothesis The glucose–fatty acid hypothesis, proposed by Randle et al. in 1963,39 attempted to delineate the relationship between increased NEFAs and insulin resistance (Figure 8.3). Randle and co-workers conducted a series of in vitro experiments in rat cardiac muscle that suggested substrate competition between NEFAs and glucose as an energy source for muscle. These studies observed a relative increase in the rate of fat oxidation compared with carbohydrate metabolism in response to increased NEFAs. In addition, studies revealed an accompanied reduction in insulin-stimulated glucose uptake and utilization by the cardiac muscle.39 Several studies support Randle’s glucose–fatty acid hypothesis by confirming the link between a high fat intake and increased gluconeogenesis. Increased portal NEFA levels and decreased hepatic insulin extraction have been observed in

ALTERNATIVES TO THE RANDLE HYPOTHESIS (b)

(c) 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

18 16 14 12 10 8 6 4 2 0

FFA levels (mmol/l)

45 40 35 30 25 20 15 10 5 0

Glucose production (µmol kg–1 min–1)

Glucose disposal (µmol kg–1 min–1)

(a)

213

Healthy controls

Type 2 diabetes

NAFLD

Values at end of clamp study

Figure 8.3 (a) Glucose disposal during the euglycaemic clamp and (b) hepatic glucose production in normal healthy subjects, patients with type 2 diabetes and NAFLD subjects; (c) plasma FFA concentrations in normal healthy subjects, patients with type 2 diabetes and NAFLD subjects. Data are presented as means with 95 per cent confidence intervals (adapted from reference 40)

obese rodents fed high fat diets.41 Furthermore, in human studies the NEFA fasting levels of obese individuals (BMI ≥ 30 kg/m2 ) were found to be higher than those of their lean counterparts (BMI < 25 kg/m2 ), establishing the obese individuals’ reduced capacity to suppress lipolysis. It is therefore apparent that in obese individuals the surplus fat stores combined with the reduced efficiency at inhibiting lipolysis of those fat stores means there is a sustained excess of NEFAs for skeletal muscle metabolism.42 The mechanism through which NEFAs bring about insulin resistance may be explained by recent studies that reveal that NEFAs induce different isoforms of protein kinase C. These isoforms can interfere with the intracellular signalling pathway of insulin and ultimately block glucose transport activity.43

8.10 Alternatives to the Randle hypothesis There is emerging evidence that the Randle hypothesis may not be the sole answer. Several studies have reported an association between subcutaneous abdominal adipose tissue and insulin resistance in obese non-diabetic men and men with type 2 diabetes.44 – 46 The subcutaneous fat depot does not drain into the portal vein, which implies that subcutaneous adipose tissue induces these effects via a non-portal mechanism. As a result of these findings, some of the deleterious consequences of obesity have been attributed to subcutaneous fat, resulting in the interest in two new theories. The two emerging models suggested are ‘the ectopic fat storage syndrome’ and ‘the adipose tissue as an endocrine organ’.47

214

RELATIONSHIP BETWEEN FAT DISTRIBUTION AND INSULIN RESISTANCE

8.11 Ectopic fat storage: fat content in obesity Hepatic steatosis (fatty liver), also referred to as non-alcoholic steatohepatitis (NASH), forms part of a larger spectrum of non-alcoholic fatty liver diseases (NAFLD). Studies indicate that NAFLD is associated with insulin resistance and that excess lipid in muscle and pancreas are features common to the pathogenesis of obesity-mediated type 2 diabetes.48 These characteristics are thought to arise as a result of the failure of adipocytes to store excess triglyceride, which leads to the deposition of lipid in the liver49 and skeletal muscle.50, 37 Insulin resistance is thought to occur due to the ectopic deposition of lipid in these organs, which interferes with their normal physiological function; in addition, glucose intolerance and diabetes ensues.51, 40 Examination of the role of ectopic fat in NAFLD has shown that patients have central fat accumulation, increased triglycerides, increased uric acid levels and low HDL cholesterol concentrations, irrespective of BMI. Furthermore, analysis of insulin sensitivity by use of a euglycaemic clamp technique in NAFLD patients, compared with type 2 diabetic patients and healthy controls, indicated that glucose disposal during the clamp was reduced by nearly 50 per cent in NAFLD patients, to an extent similar to that of type 2 diabetic patients (Figure 8.3). These findings suggest that NAFLD patients are characterized by a severe reduction in insulin sensitivity, with decreased insulin effects on both glucose and lipid metabolism. It appears that adipocyte size is the best correlate for diabetes onset in this group, a finding that implies difficulty in pre-adipocyte differentiation. Clinical analysis of obese Pima Indians apparently supports this theory.52 Furthermore, insulin sensitivity during overfeeding shows a positive correlation with recruitment of new adipocytes.53 Similar findings to those found in diabetic patients are observed in lipodystrophy patients (which is either an acquired or a hereditary syndrome) characterized by a severe reduction in adipose tissue with increased triglyceride storage in the liver and skeletal muscle54, 55 and subsequent type 2 diabetes. However, when rodent models of lipodystrophy receive surgical implantation of adipose tissue, their type 2 diabetes is reversed.56 These observations suggest that in either the obese or lipodystrophic state adipose tissue mass is unable to sequester dietary lipid away from the liver, skeletal muscle or pancreas. As a result, too much or too little adipose tissue mass leads to ectopic fat storage, which may further predispose individuals to insulin resistance and finally type 2 diabetes.

8.12

Adipose tissue as an endocrine organ

Adipose tissue is known to produce a vast array of hormones and cytokine signals, as well as components of the alternative complement system and sex steroid hormones. Due to the apparent interaction between adipose tissue and other organs, there is wider appeal to view adipose tissue acts as an endocrine

PLASMINOGEN ACTIVATOR–INHIBITOR 1

215

Table 8.2 Differences between adipocytes from subcutaneous (Sc) and visceral depots Factor Leptin mRNA and protein TNF-α IL-6 PAI-1 Angiotensinogen mRNA Resistin Adiponectin Androgen receptor mRNA PPARγ TZD stimulated pre-adipocyte differentiation Lipolytic response to catecholamines Antilipolytic effect of insulin β1 and β2-adrenergic receptor binding and mRNA Dexamethasone-induced increase in LPL α2-adrenergic receptor agonist inhibition of cAMP Insulin receptor affinity IRS-1 protein expression Insulin receptor (exon 11 deleted) Glucocorticoid receptor mRNA

Regional difference Sc > visceral Sc > visceral visceral > Sc visceral > Sc visceral > Sc visceral = Sc Sc > visceral visceral > Sc Sc = visceral Sc > visceral visceral > sc Sc > visceral visceral > Sc visceral > Sc Sc > visceral Sc > visceral Sc > visceral visceral > Sc visceral > Sc

Reference 58–60 61 62 63 64 65 66 67 68 69 70 71, 58 72, 73 74 75 71 71 58 76

Adapted from reference 77.

gland. While under ‘normal’ physiological metabolism adipose tissue effects energy homeostasis, fuel storage and mobilization of adipose tissue,57 these effects may be substantially altered with increase in adiposity and specifically central adiposity. Recent studies have revealed a plethora of factors produced by adipose tissue depots; this list is continually increasing, with many of these factors being implicated in the pathogenesis of the metabolic syndrome (Table 8.2). This list includes factors such as tumour necrosis factor alpha (TNF-α), interleukin-6 (IL6), leptin, resistin, the renin–angiotensin system (RAS), plasminogen activator inhibitor-1 (PAI-1) and more recently omentin and visfatin.79 The role of TNF-α, leptin, Il-6, resistin and adiponectin in linking obesity to metabolic disease are described in detail elsewhere in this book. Other adipose-tissue-secreted products include factors that may explain the link between central obesity with hypertension and hypercoagulable state. These are considered in the following section.

8.13 Plasminogen activator–inhibitor 1 Obesity and type 2 diabetes are associated with reduced fibrinolytic activity.79, 80 The fibrinolytic pathway is a proteolytic system that regulates the degradation of fibrin in the vasculature, and the relationship between attenuated fibrinolysis and coronary disease has long been established. Within the fibrinolytic pathway,

216

RELATIONSHIP BETWEEN FAT DISTRIBUTION AND INSULIN RESISTANCE

the main enzyme, plasmin, is derived from its inactive precursor, plasminogen, via the activities of tissue-type and urokinase-type plasminogen activators (t-PA and u-PA). Plasminogen activator inhibitor-1 (PAI-1) belongs to the family of serine protease inhibitors and regulates thrombus formation via the inhibition of t-PA. Consequently, elevated levels of PAI-1 result in a hypercoagulable and hypofibrinolytic state that promotes atherogenesis and presents as cardiovascular disease.81, 82 Studies have indicated PAI-1 levels as a marker for the risk of atherosclerosis and as a predictor of cardiovascular events. Epidemiological and experimental data confirm this association between the presence of coronary artery disease and low plasma fibrinolytic activity as a consequence of increased PAI-1 levels.83 – 88 While obesity is an independent risk factor for cardiovascular disease, studies also reveal that PAI-1 is elevated in subjects with increased BMI, central adiposity and diabetes.82, 89 – 91, 63, 92, 93 These studies suggest the involvement of the adipocyte in the association between PAI-1 levels and the metabolic syndrome.90, 94, 89 However, controversy remains as to the contributory roles of subcutaneous versus visceral adipose tissue with regard to circulating PAI-1 levels. Several in vitro studies have identified visceral adipose as the predominant source of PAI-1 through mRNA expression studies conducted in samples from the same individual. Further findings indicate that PAI-1 activity is also greater in the visceral depot.95 However, a study by Eriksson and coworkers, which examined protein secretion and gene expression in subcutaneous and visceral depots from the same individual, found that subcutaneous had greater PAI-1 levels at the gene and protein levels.28 Alessi and colleagues, on the other hand, found no difference in PAI-1 expression between visceral and subcutaneous adipose tissue from morbidly obese subjects.96 Insulin resistance exhibits the strongest correlation with increased plasma PAI-1 concentrations and this is concomitant with suppressed fibrinolysis. This may be a consequence of compensatory hyperinsulinaemia, as in vitro studies have demonstrated that insulin and its precursor, proinsulin, increase PAI-1 gene expression in human cell lines as well as human hepatocytes.97, 98 Recent studies conducted in mice and humans have shown that hyperinsulinaemia increases PAI-1 mRNA expression in abdominal subcutaneous adipose tissue.99, 93, 100, 101

8.14

Renin angiotensin system in adipose tissue

The renin angiotensin system (RAS) is known to regulate blood pressure and electrolyte homeostasis and investigations have revealed that both cultured adipose cells and isolated human adipocytes have detectable levels of AGT present.102, 103 Furthermore, related components in the RAS pathway are present, including renin and ACE, as well as secretion of angiotensin II, as shown by radioimmunoassay.102, 103 Therefore, the presence of the RAS in adipose

GLUCOCORTICOID METABOLISM AND OBESITY

217

tissue provides a potential explanation for the association between obesity and hypertension. After the liver, adipose tissue is the second major source of angiotensin 104 II and both epidemiological and physiological data implicate circulating angiotensinogen (AGT) levels for regulation of blood pressure and with increased prevalence of hypertension in obesity.105, 106 Several studies have also implicated angiotensin II as an adipogenic factor with a possible contributory role in the development of obesity. Cellularity measurements show that angiotensin II induces adipocyte enlargement through the upregulation of the fatty acid synthetase gene and increased lipid synthesis and storage in adipocytes.107 In vitro studies have also revealed that angiotensin II stimulates the production and release of prostacyclin from adipocytes and through this mechanism induces differentiation of precursor cells into new adipocytes.108 The possibility of this adipogenic role for angiotensin II is further supported by experimental data from rodent and human in vivo studies. AGT tissue knockout mice showed the mice to have significantly less adipose tissue mass than their control littermates, while experiments conducted in humans and rodent models have shown that obesity correlates with greater RAS activity.109 – 111 It seems that reports on the roles of AGT are conflicting, since several studies have produced data indicating that increased activity of the RAS inhibits differentiation of pre-adipocytes to mature adipocytes. As such, RAS may have a pathological role in the development of type 2 diabetes through its inhibitory effects on differentiation.112, 113 Angiotensin II also has the capacity to induce PAI-1 expression and secretion, which provides further evidence of its association with inflammatory disease. In vivo studies with infusion of angiotensin II into healthy subjects resulted in associated elevated PAI-1 plasma levels,114 although a more recent study has failed to support these.115

8.15

Visceral obesity and steroid hormone metabolism

Adipose tissue also appears to play a pivotal role in the metabolism of glucocorticoids and sex steroids. Specificity is achieved by specific receptors and by location of specific enzyme systems. These hormones, glucocorticoids and sex steroids, appear to play a critical, if as yet not fully understood, role in the determination of body fat distribution. The following section will consider the metabolism of cortisol and sex steroids by adipose tissue and implications for body fat distribution.

8.16

Glucocorticoid metabolism and obesity

Observations that in patients with Cushing’s syndrome visceral adiposity resolves with therapy have stimulated a number of investigators to examine

218

RELATIONSHIP BETWEEN FAT DISTRIBUTION AND INSULIN RESISTANCE

the hypothalamo-pituatary–adrenal (HPA) axis in obesity. Increased rate of cortisol production, increased urinary free cortisol excretion, normal circulating levels, impaired suppression of the hypothalamo-pituitary axis (HPA) with dexamethasone and enhanced secretion of adrenocorticotrophin hormone (ACTH) and cortisol following stimulation by corticotrophin-releasing hormone (CRF) and ACTH respectively in simple obesity116 – 118 have all been demonstrated in a variety of studies. Further evidence for a critical role for glucocorticoids has been provided by in vitro studies on adipose tissue in which they have been shown to play a critical role in regulation of stromal cell proliferation, differentiation and enhancement of LPL activity (in combination with insulin).119, 120 These latter effects are mediated via a combination of effects on gene transcription stimulation and posttranslational stabilization of the enzyme.121 – 123 Glucocorticoids also directly regulate the function of mature adipocytes, in which they regulate expression of leptin124 and PPARγ.125 Furthermore, in the ob/ob rodent model, adrenalectomy prevents the development of obesity.126 In an attempt to further investigate the basis for the increased metabolic clearance of cortisol and its site-specific effects within adipose tissue, recent studies have concentrated on the regulation of glucocorticoid at local pre-receptor level by the two isoenzymes of 11β-hydroxysteroid dehydrogenase.

8.17

11β-hydroxysteroid dehydrogenase (11β-HSD)

11β-HSD is a microsomal enzyme responsible for the interconversion of active glucocorticoids, cortisol (F) and corticosterone, to their hormonally inactive metabolites, cortisone (E) and 11-dehydrocorticosterone. It can therefore regulate the amount of hormone that binds to the nuclear receptor, ultimately regulating gene expression.127 Two 11β-HSD isoenzymes, type 1 and type 2, have been isolated, and their tissue distribution reflects their important role in protecting both the glucocorticoid and mineralocorticoid receptors from cortisol excess.128

8.18

Isoenzymes of 11β-HSD

11β-HSD1 is a 292-amino-acid protein and a member of the short chain alcohol dehydrogenase super-family. It requires glycosylation for full activation and is bi-directional, catalysing oxidation and reduction using NADP(H) as a co-factor; i.e., it will inactivate cortisol to cortisone and vice versa. The human gene is located on chromosome 1q32.2 and the enzyme is localized to glucocorticoid target tissues including liver, lung, gonad, diciduas, adipose tissue, the pituitary and the cerebellum with minimal expression in the kidney and colon. In vitro studies examining enzyme affinity (Km for E 0.3 µmol; Km for F 2.1 µmol) suggest that in vivo 11β-HSD1 acts principally as an oxoreductase generating F from E.128

11β-HSD AND OBESITY

219

11β-HSD2, a 405-amino-acid protein, is encoded for on chromosome 16, and is localized to tissue expressing mineralocorticoid receptor. In contrast to 11βHSD1, 11β-HSD2 is a unidirectional enzyme responsible for conversion of F to E. It is expressed in the kidney, colon and salivary gland, where it appears to protect the mineralocorticoid receptor from overexposure to glucocorticoid. 11β-HSD2 is not expressed in human adipose tissue.

8.19

11β-HSD and obesity

On the basis of in vitro data, in which 11β-HSD has been shown to facilitate glucocorticoid action in the liver, gonad, skin and brain, combined with the already noted clinical features of Cushing’s syndrome, there have been a number of recent studies that have tried to assess the contribution of 11β-HSD in obesity both in vivo and in vitro. Using data from in vitro studies examining primary cell cultures of human adipose stromal cells and adipocytes, Bujalska and colleagues have shown that 11β-HSD1 acts predominantly as a reductase (i.e. E to F) in adipose tissue and demonstrates site specificity (visceral  subcutaneous).129 Omental preadipocytes express higher levels of 11β-HSD than omental adipocytes while expression is similar in the subcutaneous adipose cells.130 Expression of 11βHSD1 is enhanced by glucocorticoids and cytokines (IL-1β and TNFα) and attenuated by insulin and IGF 1.131, 132 As adipocyte differentiation is dependent on the presence of glucocorticoid, local metabolism of glucocorticoids by 11βHSD1 may, therefore, control differentiation of adipose tissue in a site specific fashion and may be a novel susceptibility factor, explaining the predisposition of some individuals, but not others, to central obesity.133 A small number of studies have attempted to address this question in vivo, utilizing urinary metabolites as markers of 11β-HSD activity, with conflicting results.134 – 137 In fact, in contrast to the activity expected from the in vitro studies, some studies have demonstrated that there is reduction of E to F conversion with increasing adiposity.135, 138 Urinary metabolites, however, are a measure of ‘global’ 11β-HSD activity while the downregulation of 11β-HSD1 appears to be tissue specific. The liver is the major organ responsible for E to F conversion, and it has been suggested that 11β-HSD1 may be regulated differently in the adipose tissue to liver with reduction of activity in the liver and upregulation in omental adipose tissue.139 Experimental findings demonstrate that omental adipose tissue has a significantly higher 11β-HSD activity than subcutaneous adipose tissue and that the increase in 11β-HSD activity with obesity is confined mainly to the omental tissue.139 This enhanced rate of peripheral glucocorticoid clearance (hepatic mediated) would help limit the metabolic complications of obesity.139, 140 It may also provide one mechanism to explain the increased drive to the hypothalamo-pituitary axis and hence the cortisol secretion rates observed in simple obesity. This phenomenon is observed in the 11β-HSD knockout

220

RELATIONSHIP BETWEEN FAT DISTRIBUTION AND INSULIN RESISTANCE

mouse in which enhanced insulin sensitivity and decreased gluconeogenesis are observed as a consequence of reduced intracellular glucocorticoids.140 Furthermore, transgenic mice overexpressing 11β-HSD1 selectively in adipose tissue have been shown to develop visceral adiposity associated with insulin-resistant diabetes, hyperlipidaemia and hyperphagia.141 The ability to downregulate 11β-HSD activity may therefore act not only to limit the metabolic consequences of obesity (e.g. diabetes mellitus) but also as a physiological/adaptive mechanism to halt further weight gain.

8.20

Sex steroid metabolism and obesity: oestrogen biosynthesis

Oestrogens and androgens are the endpoint of a chain of reactions in which the C27 sterol cholesterol is converted first to C21 steroids (progestins), then to C19 steroids (androgens) and to C18 steroids (oestrogens). The last step in the reaction in which C19 steroids (androgens) are converted to C18 steroids (oestrogens) is catalysed by a unidirectional enzyme, aromatase. Ovarian granulosa cells are the main source of circulating systemic oestrogen in pre-menopausal, non-pregnant women. Adipose tissue, however, acts as the main source of oestrogen after the menopause.142 Osteoblasts and osteoclasts in bone143, 144 and vascular endothelium145 are among tissues also thought to produce ‘significant’ quantities of oestrogens. For men, the picture is significantly different, as the gonadal contribution to circulating oestrogen levels has been estimated at 15 per cent. In light of these findings, it is clear that extragonadal oestrogen production plays an important physiological role throughout adult life. Simpson and Labrie have proposed that, in at least some of these sites, the oestrogen produced is only biologically active at a local tissue level.9, 146, 147 As a result local tissue concentrations of oestrogens, while high enough to exert significant biological influence locally, are likely to contribute only minimally to the circulating pool. In one study, the total steroid content of adipose tissue (estimated with a mean body fat mass of 20 kg) was 40–400 times greater than total plasma content.148

8.21

Aromatase

Aromatase is a member of a super-family of enzymes known collectively as cytochrome P450. Located in the endoplasmic reticulum, it has the capacity to metabolize three precursors – androstenedione, testosterone and 16αhydroxyepiandrostenedione – into oestrone (adipose tissue), oestradiol (ovary) and oestriol (placenta) respectively.149 Aromatase is currently the sole member of gene family 19, designated CYP 19–based on the oxidation of the C19 angular methyl group. It is in expressed in ovary, testis, placenta, brain, adipose tissue and skin.

AROMATASE

221

Considerable confusion exists regarding the tissue expression of aromatase in adipose tissue. While early reports suggested that both stromal cells and adipocytes expressed aromatase, later reports examining expression and regulation of aromatase are based on activity being solely in the stromal faction of adipose tissue.149, 150 The in vivo findings of increasing fractional conversion of circulating androstenedione to oestrone with increasing age have been supported by molecular studies demonstrating increases in P450 transcripts with increasing age in adipose tissue, with highest levels in the buttocks and thighs compared with the abdomen.151 In adipose tissue, oestrogen biosynthesis is stimulated by glucocorticoid with the P450 transcript containing untranslated exon 1.4. This upregulation, however, appears to be dependent upon an upstream TATA-less promoter, a glucocorticoid response element (GRE) and an SP1 sequence within the untranslated exon. Furthermore, this upstream region also appears to contain a region known as an interferon-γ-activating element (GAS element) and is of particular significance when examining regulation of aromatase activity by cytokines as it binds members of the STAT family (signal transducers and transcription activators) of transcription factors. While dependent on the presence of glucocorticoids and the SP1 element, class I cytokines appear to activate aromatase through a JAK/STAT pathway. Ligand binding and receptor dimerization are associated with the binding of JAK1 to the common subunit gp130 and its activation following phosphorylation. This is followed by recruitment and phorphorylation of STAT3, its dimerization and translocation to the nucleus and binding to the GAS element of promoter 1.4. Transcription of the aromatase gene from promoter 1.4 follows thereafter.152, 153 The potentially important roles that aromatase and sex steroids play in the regulation of body fat volume and distribution have been highlighted recently by descriptions of the changes noted in adipose tissue mass and distribution in both animals and man in whom there has been a disruption of aromatase activity. In the aromatase knockout mouse (ArKO), mild obesity develops as early as 12 weeks after birth and becomes progressively more pronounced with increasing age. At one year, in both female and male mice, infrarenal and gonadal fat mass Table 8.3 Adipose tissue in aromatase knockout mice as determined by MRI (adapted from reference 154) % adipose tissue Mice

10 weeks

1 year

Females

ArKO Wild type

17.6 ± 4.4(5)* 4.9 ± 1.0(5)

64.3 ± 11.0(19)* 42.1 ± 6.7(9)

Males

ArKO Wild type

15.2 ± 2.3(5)* 7.3 ± 1.7(5)

40.3 ± 3.8(13)* 29.5 ± 3.7(16)

222

RELATIONSHIP BETWEEN FAT DISTRIBUTION AND INSULIN RESISTANCE

is double that found in the wild type (Table 8.3).154 Despite this increase in fat mass, their body weight either did not increase (male) or did so minimally (female), suggesting a decrease in lean fat mass–which was also demonstrated. This increase in fat mass was not due to hyperphagia but was associated with reduced spontaneous physical activity, a feature also previously demonstrated in postmenopausal women.155 It has additionally been suggested that these changes observed in body composition are secondary to oestrogen’s role in nutrient partitioning. In rats, oestrogen deficiency results in reduced skeletal muscle glucose utilization with a resultant increase in the availability of glucose for lipogenesis. More recently, studies in ovariectomized rats have demonstrated reduced uncoupling protein 2 mRNA levels in skeletal but not adipose tissue.156 In a study aimed at characterizing cellular and molecular characteristics of the adipose tissue depot in ArKO mice, the ArKO adipocytes were larger and more abundant than adipocytes isolated from wild type mice. Treatment with 17β-oestradiol resulted in a marked reduction of cell volume but a less pronounced reduction in adipocyte number. As a result of these studies, it has been suggested that regulation of lipid uptake from the circulation is the main mechanism by which oestrogen regulates lipid metabolism in ArKO mice.157, 158 A similar clinical picture has been observed in humans with aromatase deficiency, which in the male is associated with obesity, a eunuchoid skeletal distribution and hyperinsulinaemia.159

8.22 Sex steroids and body fat Sex steroids, rather like glucocorticoids, appear to be able to regulate body fat volume and distribution at several levels.160 Girls and pre-pubertal boys have a similar distribution and percentage of adipose tissue. The onset of puberty is associated with gluteofemoral fat deposition in women, in whom thereafter, regardless of how body fat is measured, adipose tissue mass is larger than in men. It has been suggested that gonadal steroids largely account for this. In pre-menopausal women, femoral adipocytes are larger and have both a higher LPL activity and a blunted lipolytic response in comparison with abdominal adipocytes. Post-menopausally, this difference is lost with a decrease in femoral LPL activity and a blunting of the abdominal lipolytic response, with a subsequent increase in abdominal adipocyte size.161, 162, 32, 163 This is reflected by the increase in the waist:hip ratio and visceral fat mass and therefore the android phenotype observed in post-menopausal women.164, 165 Despite the clear relationship between the changes in adipocyte biology and puberty and menarche their aetiology has been difficult to delineate. The changes in body fat distribution observed with the menopause are at least partly reversed with the administration of oestrogen.166, 167 This regulation of adipocyte mass appears to be, in part, through regulation of lipoprotein lipase activity, although the results of studies have been contradictory.

SEX STEROIDS AND BODY FAT

223

In animal studies, oestrogen stimulates lipolysis while progesterone increases LPL activity in a site-specific manner.168, 169 There is data to support similar effects in man. Iverius and colleagues have demonstrated an inverse correlation between serum oestradiol and LPL activity, although the study population was small and heterogeneous and ranged in age from 22 to 66 years, and no details were available regarding the pattern of fat distribution.170 This data has been recently reinforced by studies from Price and colleagues, who found lipoprotein lipase activity to be lower under dermal patches of 17β-oestradiol.163 In studies by Rebuff´e-Scrive and colleagues, topical administration of progesterone patches and the administration of a sequential oral preparation of oestradiol valerate and levonorgesterol to post-menopausal women resulted in a significant increase in adipose tissue lipoprotein lipase.171, 162 Based on this data Price and colleagues have proposed that in pre-menopausal women the relatively high levels of progesterone increase lipoprotein lipase activity, which is greater in the gluteofemoral than in the abdominal region. They propose that the loss of progesterone in the post-menopausal state is associated with predominant activity of oestrone which, once again, is greater in the gluteofemoral than in the abdominal region, and which results in a decrease in LPL activity in this region.163 This concept is further consolidated by in vitro studies, which demonstrate regulation of progesterone receptors by oestrogen.172 Furthermore, oestrogens have been shown to promote stromal cell proliferation in vitro, and there are putative reports that they promote stromal cell differentiation.173 – 175 They also regulate leptin secretion, and ultimately energy intake and expenditure, in a gender- and site-specific manner.176 Androgens also exert marked effects on adipose tissue. In men a lower plasma testosterone is associated with central adiposity and administration of exogenous testosterone results in loss of visceral fat.177 Administration of supraphysiological doses of testosterone (e.g. 600 mg testosterone enanthate weekly for 10 weeks) to eugonadal men, however, has not been found to result in further changes in total fat mass.178 Using radiolabelled oleic acid to determine triglyceride turnover and fat biopsies, Marin and colleagues have recently studied the effect of androgens (testosterone and dihydrotestosterone) on regional fat metabolism both in vivo and in vitro, in obese men. Dihydrotestosterone was without effect in either region whilst treatment with testosterone alone resulted in reduced LPL activity in abdominal fat as well as reduced uptake and increased turnover of triglyceride.179 Androgens, therefore, rather like oestrogens, appear to exert a lipolytic effect on adipose tissue when examined in vitro. This effect is mediated in part through transcription effects on the lipolytic β-adrenergic receptor genes, as well as interactions at the level of protein kinase and/or hormone-sensitive lipase.180, 181, 123, 182 These effects, however, appear to be sex dependent, since in women it is hyperandrogenicity that is associated with central obesity, although there is limited data on both the in vivo and in vitro effects of

224

RELATIONSHIP BETWEEN FAT DISTRIBUTION AND INSULIN RESISTANCE

androgens. In post-menopausal women exogenous administration of nandrolone for 9 months has been found to be associated with loss of overall fat mass. This, however, mainly represented loss of subcutaneous adipose tissue, as the visceral depot was in fact enlarged.183 Similar effects are observed in transsexuals treated with long term androgens as well as in women with virilizing tumours.11

8.23

Summary

The inter-relationship between fat distribution and insulin resistance is complex. The recently developed concepts of ‘ectopic fat’ deposition leading to insulin resistance would suggest that central obesity is in the main a marker of insulin resistance. The insulin resistance, according to this hypothesis, is due to alteration in insulin signalling due to lipid deposits in muscle and liver. Adipose-tissue-secreted products also clearly mediate obesity-associated metabolic disorders, and visceral fat may contribute proportionately more to circulatory adipocytokines. While the simplest way to reduce obesity and ultimately its co-morbidities would be for everybody to change the ‘modern lifestyle’ of less physical activity and more ‘fast food’, it is clear that this approach in itself is unlikely to occur without major lifestyle changes in society. However, even modest degrees of weight loss in those with central obesity may help to reduce some of the adverse risks associated with obesity, possible because ectopic and central fat are lost first. The role of pharmacologically induced favourable change in the phenotype of the adipocyte and/or change in fat distribution as an adjunct to modest weight loss needs to be explored in future studies.

Acknowledgement We thank Ms Sharae Deckard for her assistance with preparation of this manuscript.

References 1. Diabetes UK. (2000) Health Awareness Billboard. London: Diabetes UK. 2. Colditz, G. A., Willett, W. C., Rotnitzky, A. and Manson, J. E. (1995) Weight gain as a risk factor for clinical diabetes mellitus in women. Ann Intern Med 122 (7), 481–486. 3. DiGirolamo, M. and Fine, J. B. (2001) Cellularity measurements. Methods Mol Biol 155, 65–75. 4. Frayn, K. N., Coppack, S. W., Fielding, B. A. and Humphreys, S. M. (1995) Coordinated regulation of hormone sensitive lipase in human adipose tissue in vivo: implications for the control of fat storage and fat mobilization. Adv Enzyme Regulation 35, 163–178. 5. Gregoire, F. M., Smas, C. M. and Sul, H. S. (1998) Understanding adipocyte differentiation. Physiol Rev 78 (3), 783–807.

REFERENCES

225

6. Vague, J. (1956) The degree of masculine differentiation of obesity: a factor determining predisposition to diabetes. Atherosclerosis, gout and uric calculus disease. Am J Clin Nutr 4, 20–34. 7. Arner, P. (1997) Obesity and the adipocyte: regional adiposity in man. J Endocrinol 155, 191–192. 8. Haffner, S. M., Karhapaa, P., Mykkanen, L. and Laakso, M. (1994) Insulin resistance, body fat distribution, and sex hormones in men. Diabetes 43, 212–219. 9. Simpson, E. R., Rubin, G., Clyne, C., Robertson, K., O’Donnell, L., Jones, M. and Davi, S. (2000) The role of local estrogen biosynthesis in males and females. Trends Endocrinol Metab 11, 184–188. 10. Elbers, J. M., Giltay, E. J., Teerlink, T., Scheffer, P. G., Asscheman, H., Seidell, J. C. and Gooren, L. J. (2003) Effects of sex steroids on components of the insulin resistance syndrome transsexual subjects. Clin Endocrinol 58, 562–571. 11. Elbers, J. M., de Jong, S., Teerlink, T., Asscheman, H., Seidell, J. C. and Gooren, L. J. (1999) Changes in fat cell size and in vitro lipolytic activity of abdominal and gluteal adipocytes after a one-year cross-sex hormone administration in transexuals. Metabolism 48 (11), 1371–1377. 12. Garaulet, M., Perez-Lamas, F., Baraza, J. C., Garcia-Prieto, M. D., Fardy, P. S., Tebar, F. J. and Zamora, S. (2002) Body fat distribution in pre-and post-menopausal women: metabolic and anthropometric variables. J Nutr Health Aging 6, 123–126. 13. Hirsch, J. (1971) Adipose cellularity in relation to human obesity. In: Stollerman, G. H., ed. Advances in Internal Medicine, Vol. 17. Chicago, IL: Year Book, 289–300. 14. Prins, J. B. and O’Rahilly, S. (1997) Regulation of human adiposity. Clin Sci 92, 3–11. 15. Miller, W. H. Jr., Faust, I. M., Goldberger, A. C. and Hirsch, J. (1983) Effects of severe long-term food deprivation and refeeding on adipose tissue cells in the rat. Am J Physiol 245, E74–E80. 16. Faust, I. M., Johnson, P. R., Stern, J. S. and Hirsch, J. (1978) Diet-induced adipocyte number increase in adult rats: a new model of obesity. Am J Physiol 235 (3), E279–E286. 17. Morin, C. L., Pagliassotti, M. J., Windmiller, D. and Eckel, R. H. (1997) Adipose tissuederived tumor necrosis factor-alpha activity is elevated in older rats. J Gerontol A Biol Sci Med Sci 52 (4), B190–B195. 18. Hirsch, J., Fried, S. K., Edens, N. K. and Leibel, R. L. (1989) The fat cell. Med Clin North Am 73 (1), 83–96. 19. Bjorntorp, P. and Yang, M. U. (1982) Refeeding after fasting in the rat: effects on body composition and food efficiency. Am J Clin Nutr 36 (3), 444–449. 20. Bonnet, F. (1979) Could one prevent childhood obesity? Diabetes Metab 5 (1), 71–73. 21. Prentki, M., Tornheim, K. and Corkey, B. E. (1997) Signal transduction mechanisms in nutrient-induced insulin secretion. Diabetologia 40 (Suppl. 2), S32–S41. 22. Rabinowitz, D. and Zierler, K. L. (1962) Forearm metabolism in obesity and its response to intra-arterial insulin. Characterization of insulin resistance and evidence for adaptive hyperinsulinism. J Clin Invest 41, 2173–2181. 23. Friedman, J. E., Dohm, G. L., Leggett-Frazier, N., Elton, C. W., Tapscott, E. B., Pories, W. P. and Caro, J. F. (1992) Restoration of insulin responsiveness in skeletal muscle of morbidly obese patients after weight loss. Effect on muscle glucose transport and glucose transporter GLUT4. J Clin Invest 89 (2), 701–705. 24. Bak, J. F., Moller, N., Schmitz, O., Saaek, A. and Pedersen, O. (1992) In vivo insulin action and muscle glycogen synthase activity in type 2 (non-insulin-dependent) diabetes mellitus: effects of diet treatment. Diabetologia 35 (8), 777–784. 25. Koffler, M., Ramirez, L. C. and Raskin, P. (1989) Insulin resistance and diabetes, mechanism and possible intervention. Diabetes Res Clin Pract 7 (2), 83–98.

226

RELATIONSHIP BETWEEN FAT DISTRIBUTION AND INSULIN RESISTANCE

26. Reaven, G. M. (1988) Role of insulin resistance in human disease. Banting Lecture. Diabetes 37, 1595–1607. 27. Reaven, G. M. (1995) Pathophysiology of insulin resistance in human disease. Physiol Rev 75 (3), 473–486. 28. Eriksson, P., Van Harmelen, V., Hoffstedt, J., Lundquist, P., Vidal, H., Stemme, V., Hamsten, A., Arner, P. and Reynisdottir, S. (2000) Regional variation in plasminogen activator inhibitor-1 expression in adipose tissue from obese individuals. Thromb Haemost 83, 545–548. ˜ 29. Ostman, J., Arner, P., Engfeldt, P. and Kager, L. (1979) Regional differences in the control of lipolysis in human adipose tissue. Metabolism 28, 1198–1205. 30. Engfeldt, P. and Arner, P. (1998) Lipolysis in human adipocytes, effects of cell size, age and of regional differences. Horm Metab Res Suppl 19, 26–29. 31. Ferrannini, E., Barrett, E. J., Bevilaequa, S. and DeFronzo, R. A. (1983) Effect of fatty acids on glucose production and utilization in man. J Clin Invest 72 (5), 1737–1747. 32. Arner, P., Lithell, H., Whrenberg, H. and Bronnegard, M. (1991) Expression of lipoprotein lipase in different human subcutaneous adipose tissue regions. J Lipid Res 32, 423–429. 33. Abate, N. (1996) Insulin resistance and obesity. The role of fat distribution pattern. Diabetes Care 19 (3), 292–294. 34. Kissebah, A. H. and Krakower, G. R. (1994) Regional adiposity and morbidity. Physiol Rev 74 (4), 761–811. 35. Arner, P. (2001) Regional differences in protein production by human adipose tissue. Biochem Soc Trans 29 (Pt 2), 72–75. 36. Sardinha, L. B., Teixeira, P. J., Guedes, D. P., Going, S. B. and Lohman, T. G. (2000) Subcutaneous central fat is associated with cardiovascular risk factors in men independently of total fatness and fitness. Metabolism 49 (11), 1379–1385. 37. Goodpaster, B. H., Thaete, F. L., Simoneau, J. A. and Kelley, D. E. (1997) Subcutaneous abdominal fat and thigh muscle composition predict insulin sensitivity independently of visceral fat. Diabetes 46 (10), 1579–1585. 38. Tai, E. S., Lau, T. N., Ho, S. C., Fok, A. C. and Tan, C. E. (2000) Body fat distribution and cardiovascular risk in normal weight women. Associations with insulin resistance, lipids and plasma leptin. Int J Obes Relat Metab Disord 24 (6), 751–757. 39. Randle, P. J., Hales, C. N., Garland, P. B. and Newsom, E. A. (1963) The glucose fatty acid cycle: it role in insulin sensitivity and metabolic disturbances of diabetes mellitus. Lancet 1, 785–789. 40. Marchesini, G., Brizi, M., Bianchi, G., Tomassetti, S., Bugianesi, E., Lenzi, M., McCullough, A. J., Natale, S., Forlani, G. and Melchionda, N. (2001) Nonalcoholic fatty liver disease. A feature of the metabolic syndrome. Diabetes 50, 1844–1850. 41. Svedberg, J., Stomblad, G., Wirth, A., Smith, U. and Bjorntorp, P. (1991) Fatty acids in the portal vein of the rat regulate hepatic insulin clearance. J Clin Invest 88, 2054– 2058. 42. Ferrannini, E. (1995) Physiological and metabolic consequences of obesity. Metabolism 44 (9, Suppl. 3), 15–17. 43. Griffin, M. E., Marcucci, M. J., Cline, G. W., Bell, K., Barucci, N., Lee, D., Goodyear, L. J., Kraegen, E. W., White, M. F. and Shulman, G. I. (1999) Free fatty acid-induced insulin resistance is associated with activation of protein kinase C theta and alterations in the insulin signaling cascade. Diabetes 48 (6), 1270–1274. 44. Kelley, D. E. and Mandarino, L. J. (2000) Fuel selection in human skeletal muscle in insulin resistance: a reexamination. Diabetes 49 (5), 677–683. 45. Smith, S. R. and Ravussin, E. (2002) Emerging paradigms for understanding fatness and diabetes risk. Curr Diab Rep 2 (3), 223–230.

REFERENCES

227

46. Abate, N. (1996) Insulin resistance and obesity. The role of fat distribution pattern. Diabetes Care 19 (3), 292–294. 47. Ravussin, E. and Smith, S. R. (2002) Increased fat intake, impaired fat oxidation, and failure of fat cell proliferation result in ectopic fat storage, insulin resistance, and type 2 diabetes mellitus. Ann N Y Acad Sci 967, 363–378. 48. McGarry, J. D. (2002) Banting lecture 2001: dysregulation of fatty acid metabolism in the etiology of type 2 diabetes. Diabetes 51 (1), 7–18. 49. Ryysy, L., Hakkinen, A. M., Goto, T., Vehkavaara, S., Westerbacka, J., Halavaara, J. and Yki-Jarvinen, H. (2000) Hepatic fat content and insulin action on free fatty acids and glucose metabolism rather than insulin absorption are associated with insulin requirements during insulin therapy in type 2 diabetic patients. Diabetes 49 (5), 749–758. 50. Goodpaster, B. H. and Kelley, D. E. (1998) Role of muscle in triglyceride metabolism. Curr Opin Lipidol 9 (3), 231–236. 51. Marchesini, G., Brizi, M., Morselli Labate, A. M., Bianchi, G., Bugianesi, E., McCullough, A. J., Forlani, G. and Melchionda, N. (1999) Association of non-alcoholic fatty liver disease to insulin resistance. Am J Med 107, 450–455. 52. Paolisso, G., Tataranni, P. A., Foley, J. E., Bogardus, C., Howard, B. V. and Ravussin, E. (1995) A high concentration of fasting plasma non-esterified fatty acids is a risk factor for the development of NIDDM. Diabetologia 38 (10): 1213–1217. 53. Sharma, A. M., Engeli, S. and Pischon, T. (2001) New developments in mechanisms of obesity-induced hypertension: role of adipose tissue. Curr Hypertens Rep 3 (2): 152–156. 54. Robbins, D. C., Danforth, E., Jr., Horton, E. S., Burse, R. L., Goldman, R. F. and Sims, E. A. (1979) The effect of diet on thermogenesis in acquired lipodystrophy. Metabolism 28 (9), 908–916. 55. Robbins, D. C., Horton, E. S., Tulp, O. and Sims, E. A. (1982) Familial partial lipodystrophy: complications of obesity in the non-obese? Metabolism 31 (5), 445–452. 56. Gavrilova, O., Marcus-Samuels, B., Graham, D., Kim, J. K., Shulman, G. I., Castle, A. L., Vinson, C., Eckhaus, M. and Reitman, M. L. (2000) Surgical implantation of adipose tissue reverses diabetes in lipoatrophic mice. J Clin Invest 105 (3), 271–278. 57. Mohammed-Ali, V., Pinkney, J. H. and Coppack, S. W. (1998) Adipose tissue as an endocrine and paracrine organ. Int J Obes Relat Metab Disord 22 (12), 1145–1158. 58. Lefebvre, A.-M., Laville, M., Vega, N., Riou, J. P., van Gaal, L., Auwerx, J. and Vidal, H. (1998) Depot-specific differences in adipose tissue gene expression in lean and obese subjects. Diabetes 47, 98–103. 59. Montague, C. T., Prins, J. B., Sanders, L., Digby, J. E. and O’Rahilly, S. (1997) Depot and sex specific differences in human leptin mRNA expression. Diabetes 46, 342–347. 60. Harmelen, V. V., Reynisdottir, S., Eriksson, P., Thorne, A., Hoffstedt, J., Lonnqvist, F. and Arner, P. (1998) Leptin secretion from subcutaneous and visceral adipose tissue in women. Diabetes 47, 913–917. 61. Hube, F., Birgel, M., Lee, Y. M. and Hauner, H. (1999) Expression pattern of tumour necrosis factor receptors in subcutaneous and omental human adipose tissue: role of obesity and non-insulin dependent diabetes mellitus. Eur J Clin Invest 29 (8), 672– 678. 62. Fried, S. K., Bunkin, D. A. and Greenberg, A. S. (1998) Omental and subcutaneous adipose tissues of obese subjects release interleukin-6: depot difference and regulation by glucocorticoid. J Clin Endocrinol Metab 83, 847–850. 63. Shimomura, I., Funahashi, T., Takahashi, M., Maeda, K., Kotari, K., Nakamura, T., Yamashita, S., Miura, M., Fukuda, Y., Takemura, K., Tokunaga, K. and Matsuzawa, Y. (1996) Enhanced expression of PAI-1 in visceral fat: possible contributor to vascular disease in obesity. Nat Med 2, 800–803.

228

RELATIONSHIP BETWEEN FAT DISTRIBUTION AND INSULIN RESISTANCE

64. Van Harmelen, V., Elizalde, M., Ariapart, P., Bergstedt-Lindqvist, S., Reynisdottir, S., Hoffstedt, J., Lundkvist, I., Bringman, S. and Arner, P. (2000) The association of human adipose angiotensinogen gene expression with abdominal fat distribution in obesity. Int J Obes 24, 673–678. 65. McTernan, C. L., McTernan, P. G., Harte, A. L., Barnett, A. H. and Kumar, S. (2002) Resistin central obesity and type 2 diabetes. Lancet 35, 46–47. 66. Fisher, F. M., McTernan, P. G., Valsamakis, G., Chetty, R., Harte, A. L., Anwar, A. J., Starcynski, J., Crocker, J., Barnett, A. H., McTernan, C. L. and Kumar, S. (2002) Differences in adiponectin protein expression: effect of fat depots and type 2 diabetic status. Horm Metab Res 34 (11/12), 650–654. 67. Dieudonne, M., Pecquery, R., Boumedienne, A., Leneveu, M. and Giudicelli, Y. (1998) Androgen receptors in human preadipocytes and adipocytes: regional specificities and regulation by sex steroids. Am J Physiol 274, C1645–C1652. 68. Montague, C., Prins, J., Sanders, L., Zhang, J., Sewter, C., Digby, J., Byrne, C. and O’Rahilly, S. (1998) Depot-related gene expression in human subcutaneous and omental adipocytes. Diabetes 47, 1384–1391. 69. Adams, M., Montague, C. T., Prins, J. B., Holder, J. C., Smith, S. A., Sanders, L., Sewter, C. P., Digby, J. E., Lazar, M. A., Chatterjee, V. K. K. and O’Rahilly, S. (1997) Activators of PPARγ have depot-specific effects on human pre-adipocyte differentiation. J Clin Invest 100, 3149–3153. 70. Rebuff´e-Scrive, M., Andersson, B., Olbe, L. and Bjorntorp, P. (1989) Metabolism of adipose tissue in intraabdominal depots of nonobese men and women. Metabolism 38, 453–458. 71. Zierath, J., Livingston, J., Thorne, A., Bolinder, J., Reynisdottir, S., Lonnqvist, F. and Arner, P. (1998) Regional difference in insulin inhibition of non-esterified fatty acid release from human adipocytes: relation to insulin receptor phosphorylation and intracellular signalling through the insulin receptor substrate-1 pathway. Diabetologia 41, 1343–1354. 72. Hellm´er, J., Marcus, C., Sommefeld, T. and Arner, P. (1992) Mechanisms for differences in lipolysis between human subcutaneous and omental fat cells. J Clin Endocrinol Metab 75, 15–20. 73. Arner, P., Hellstrom, L., Wahrenberg, H. and Bronnegard, M. (1990) Beta-adrenoreceptor expression in human fat cells from different regions. J Clin Invest 86, 1595–1600. 74. Fried, S. K., Russel, C. D., Grauso, N. L. and Brolin, R. E. (1993) Lipoprotein lipase regulation by insulin and glucocorticoid in subcutaneous and omental adipose tissues of obese women and men. J Clin Invest 92, 2192–2198. 75. Vikman, H.-L., Savola, J.-M., Raasmaja, A. and Ohisalo, J. J. (1996) 2A-Adrenergic regulation of cyclic AMP accumulation and lipolysis in human omental and subcutaneous adipocytes. Int J Obes 20, 185–189. 76. Rebuff´e-Scrive, M., Bronnegard, M., Nilsson, A., Eldh, J., Gustafsson, J.-A. and Bjorntorp, P. (1990) Steroid hormone receptors in human adipose tissues. J Clin Endocrinol Metab 71, 1215–1219. 77. Montague, C. T. and O’Rahilly, S. (2000) The perils of portliness: causes and consequences of visceral adiposity. Diabetes 49 (6), 883–888. 78. Fasshauer, M. and Paschke, R. (2003) Regulation of adipocytokines and insulin resistance. Diabetologia 46 (12), 1594–1603. 79. McGill, J. B., Schneider, D. J., Arften, C. L., Lucore, C. L. and Sobel, B. E. (1994) Factors responsible for impaired fibrinolysis in obese subjects and NIDDM patients. Diabetes 43, 104–109.

REFERENCES

229

80. Schneider, D. J. and Sobel, B. E. (1991) Augmentation of synthesis of plasminogen activator inhibitor type 1 by insulin and insulin-like growth factor type 1: implications for vascular disease in hyperinsulinaemic states. Proc Natl Acad Sci USA 88, 9959–9963. 81. Juhan-Vague, I. (1996) Haemostatic parameters and vascular risk. Atherosclerosis 124, S49–S55. 82. Juhan-Vague, I., Alessi, M. C. and Morange, P. E. (2000) Hypofibrinolysis and increased PAI-1 are linked to atherothrombosis via insulin resistance and obesity. Ann Med 32 (Suppl. 1), 78–84. 83. Hamsten, A., deFaike, U., Walldius, G., Dahlen, G., Szamosi, A., Blomb¨ack, M., De Faire, U., Dahl´en, G., Landou, C. and Wiman, B. (1987) Plasminogen activator inhibitor in plasma: risk factor for recurrent myocardial infarction. Lancet 2, 3–9. 84. Juhan-Vague, I., Thompson, S. G. and Jespersen, J. on behalf of the ECAT Angina Pectoris Study Group. (1993) Involvement of the haemostatic system in the insulin resistance syndrome. Arterioscler Thromb 13, 1865–1873. 85. Schneiderman, J., Sawdey, M. S., Keeton, M. R., Bordin, G. M., Bernstein, E. F., Dilley, R. B. and Loskutoff, D. J. (1992) Increased type plasminogen activator inhibitor gene expression in atherosclerotic human arteries. Proc Natl Acad Sci USA 89, 6998–7002. 86. Lupu, F., Bergonzelli, G. E., Heim, D. A., Cousin, E., Genton, C. Y., Bachmann, F. and Kruithof, E. K. O. (1993) Localization and production of plasminogen activator inhibitor1 in human healthy and atherosclerotic human arteries. Arterioscler Thromb 13, 1090– 1100. 87. Meade, T. W., Ruddock, V., Stirling, Y., Chakrabarti, R. and Miller, G. J. (1993) Fibrinolytic activity, clotting factors and long-term incidence of ischaemic heart disease in the Northwick Park Heart Study. Lancet 342, 1076–1079. 88. Th¨ogerson, A. M., Jansson, J. H., Boman, K., Nilsson, T. K., Weinehall, L., Huhtasaari, F. and Hallmans, G. (1998) High plasminogen activator inhibitor and tissue plasminogen activator levels in plasma precede a first acute myocardial infarction in both men and women. Evidence for the fibrinolytic system as an independent primary risk factor. Circulation 98: 2241–2247. 89. Juhan-Vague, I. and Alessi, M. C. (1997) PAI-1, obesity, insulin resistance and risk of cardiovascular events. Thromb Haemost 78, 656–660. 90. Landin, K., Stigendal, L., Eriksson, E., Krotkiewski, M., Risberg, B., Tengborn, L. and Smith, U. (1990) Abdominal obesity is associated with an impaired fibrinolytic activity and elevated plasminogen activator inhibitor-1. Metabolism 39, 1044–1048. 91. Nagi, D. K., Tracy, R. and Pratley, R. (1996) Relationship of hepatic and peripheral insulin resistance with plasminogen activator inhibitor-1 in Pima Indians. Metabolism 45, 1243–1247. 92. Eriksson, P., Reynisdottir, S., Lonnqvist, F., Stemme, V., Hamsten, A. and Arner, P. (1998) Adipose tissue secretion of plasminogen activator inhibitor-1 in non-obese and obese individuals. Diabetologia 41, 65–71. 93. Koistinen, H. A., Dusserre, E., Ebeling, P., Vallier, P., Koivisto, V. A. and Vidal, H. (2000) Subcutaneous adipose tissue expression of plasminogen activator inhibitor-1 (PAI-1) in non-diabetic and type 2 diabetic subjects. Diabetes Metab Res Rev 16, 364–369. 94. Meilahn, E. N., Cauley, J. A., Tracy, R. P., Macy, E. O., Gutai, J. P. and Kuller, L. H. (1996) Association of sex hormones and adiposity with plasma levels of fibrinogen and PAI-1 in postmenopausal women. Am J Epidemiol 143, 159–166.

230

RELATIONSHIP BETWEEN FAT DISTRIBUTION AND INSULIN RESISTANCE

95. Alessi, M. C., Peiretti, F., Morange, P., Henry, M., Nalbone, G. and Juhan-Vague, I. (1997) Production of plasminogen activator inhibitor 1 by human adipose tissue: possible link between visceral fat accumulation and vascular disease. Diabetes 46, 860–867. 96. Alessi, M. C., Bastelica, D., Morange, P., Berthet, B., Leduc, I., Verdier, M., Geel, O. and Juhan-Vague, I. (2000) Plasminogen activator inhibitor-1 transforming growth factor and BMI are closely associated in human adipose tissue during morbid obesity. Diabetes 49, 1374–1380. 97. Nordt, T. K., Schneider, D. J. and Sobel, B. E. (1994) Augmentation of the synthesis of plasminogen activator inhibitor type-1 by precursors of insulin. A potential risk factor for vascular disease. Circulation 89 (1), 321–330. 98. Anfosso, F., Alessi, M. C., Nalbone, G., Chomiki, N., Henry, M. and Juhan-Vague, I. (1995) Up-regulated expression of plasminogen activator inhibitor-1 in Hep G2 cells: interrelationship between insulin and insulin like growth factor 1. Thromb Haemost 73 (2), 268–274. 99. Gabriely, I., Yang, X. M., Cases, J. A., Ma, X. H., Rossetti, L. and Barzilai, N. (2002) Hyperglycaemia induces PAI-1 gene expression in adipose tissue by activation of the hexosamine biosynthetic pathway. Atherosclerosis 160, 115–122. 100. Morange, P. E, Aubert, J., Peiretti, F., Lijnen, H. R., Vague, P., Verdier, M., Negrel, R., Juhan-Vague, I. and Alessi, M. C. (1999) Glucocorticoids and insulin promote plasminogen activator inhibitor 1 production by human adipose tissue. Diabetes 48, 890–895. 101. Calles-Escandon, J., Mirza, S. A., Sobel, B. E. and Schneider, D. J. (1998) Induction of hyperinsulinaemia combined with hyperglycemia and hypertriglyceridaemia increases plasminogen activator inhibitor 1 in blood in normal human subjects. Diabetes 47 (2), 290–293. 102. Karlsson, C., Lindell, K., Ottosson, M., Sjostrom, L., Carlsson, B. and Carlsson, L. M. S. (1998) Human adipose tissue expresses angiotensinogen and enzymes required for its conversion to angiotensin II. J Clin Endocrinol Metab 83, 3925–3929. 103. Schling, P., Mallow, H., Trindl, A. and Loffler G. (1999) Evidence for a local renin angiotensin system in primary cultured human pre-adipocytes. Int J Obes Relat Metab Disord 23, 336–341. 104. Campbell, D. J., Bouhnik, J., Coezy, E., Menard, J. and Corvol, P. (1985) Characterization of precursor and secreted forms of human angiotensinogen. J Clin Invest 75 (6), 1880–1893. 105. Must, A., Spandano, J., Coakley, E. H., Field, A. E., Colditz, G. and Dietz, W. H. (1999) The disease burden associated with overweight and obesity. JAMA 282, 1523– 1529. 106. McFarlane, S. I., Banerji, M. and Sowers, J. R. (2001) Insulin resistance and cardiovascular disease. J Clin Endocrinol Metab 86 (7), 713–718. 107. Jones, B. H., Standridge, M. K., Taylor, J. W. and Moustaid, N. (1997) Angiotensinogen gene expression in adipose tissue: analysis of obese models and hormonal and nutritional control. Am J Physiol 273, R236–R242. 108. Darimont, C., Vassaux, G., Ailhaud, G. and N´egrel, R. (1994) Differentiation of preadipose cells: paracrine role of prostacylcin upon stimulation of adipose cells by angiotensin II. Endocrinology 135, 2030–2036. 109. Tanimoto, K., Sugiyama, F., Goto, Y., Ishida, J., Takimoto, E., Yagami, K., Fukamizu, A, Murakami, K. (1994) Angiotensinogen-deficient mice with hypotension. J Biol Chem 269, 31 334–31 337. 110. Barton, M., Carmona, R., Morawietz, H., d’Uscio, L. V., Goettsch, W., Hillen, H., Haudenschild, C. C., Krieger, J. E., M¨unter, K., Lattmann, T., L¨uscher, T. F. and Shaw, S. (2000) Obesity is associated with tissue-specific activation of renal

REFERENCES

111.

112.

113. 114.

115.

116.

117. 118.

119.

120. 121. 122. 123. 124.

125.

126. 127. 128.

129.

231

angiotensin-converting enzyme in vivo – evidence for a regulatory role of endothelin. Hypertension 35, 329–336. Schorr, U., Blaschke, K., Turan, S., Distler, A. and Sharma, A. M. (1998) Relationship between angiotensinogen, leptin and blood pressure levels in young normotensive men. J Hypertens 16, 1475–1480. Janke, J., Engeli, S., Gorzelniak, K., Luft, F. C. and Sharma, A. M. (2002) Mature adipocytes inhibit in vitro differentiation of human preadipocytes via angiotensin type-1 receptors. Diabetes 51, 1699–1707. Sharma, A. M., Janke, J., Gorzelniak, K., Engeli, S. and Luft, F. C. (2002) Angiotensin blockade prevents type 2 diabetes by formation of fat cells. Hypertension 40, 609–611. Ridker, P. M., Gaboury, C. L., Conlin, P. R., Seely, E. W., Williams, G. H. and Vaughan, D. E. (1993) Stimulation of plasminogen activator inhibitor in vivo by infusion of angiotensin II. Circulation 87, 1969–1973. Labinjoh, C., Newby, D. E., Dawson, P., Johnston, N. R., Ludlam, C. A., Boon, N. A. and Webb, D. J. (2000) Fibrinolytic actions of intra-arterial angiotensin II and bradykinin in vivo in man. Cardiovasc Res 47, 707–714. Marin, P., Darin, M., Amemiya, T., Andersson, B., Jern, S. and Bjorntorp, P. (1992) Cortisol secretion in relation to body fat distribution in obese pre-menopausal women. Metabolism 41, 882–886. Migeon, C. J., Green, O. C. and Eckert, J. P. (1963) Study of adrenocortical function in obesity. Metabolism 12 (8), 718–739. Ljung, T., Andersson, B., Bengtsson, B., Bjorntorp, P. and Marin, P. (1996) Inhibition of cortisol secretion by dexamathasone in relation to body fat distribution: a dose response study. Obes Res 4, 277–282. Hauner, H., Schmid, P. and Pfeiffer, E. F. (1987) Glucocorticoids and insulin promote the differentiation of human adipocyte precursor cells into fat cells. J Clin Endocrinol Metab 64, 832–835. Gaillard, D., Wabitsch, M., Pipy, B. and Negrel, R. (1991) Control of terminal differentiation of adipose precursor cells by glucocorticoids. J Lipid Res 32, 569–579. Cigolini, M. and Smith, U. (1979) Human adipose tissue in culture VIII. Studies on the insulin antagonistic effect of glucocorticoids. Metabolism 20, 502–510. Appel, B. and Fried, S. K. (1992) Effect of insulin and dexamethasone on lipoprotein lipase in human adipose tissue. Am J Physiol 262, E692–E695. Bjorntorp, P. (1993) Visceral obesity: a ‘civilisation syndrome’. Obesity Res 1 (3), 206–222. Sleiker, L. J., Sloop, K. W., Surface, P. L., Kriauciunas, A., La Quier, F., Manetta, J., Bue-Valleskey, J. and Stephens, T. W. (1995) Regulation of expression of ob mRNA and protein by glucocorticoids. J Biol Chem 271, 5301–5304. Vidal-Puig, A. J., Considine, R. V., Jimenez-Linan, M., Werman, A., Pories, W. J., Caro, J. F. and Flier, J. S. (1997) Peroxisome proliferator-activated receptor gene expression in human tissues. Effects of obesity, weight loss and regulation by insulin and glucocorticoids. J Clin Invest 99, 2416–2422. Naeser, P. (1973) Effects of adrenalectomy in the obese–hyperglycaemic syndrome in mice (gene symbol ob). Diabetologia 9, 376–379. Stewart, P. M. (1996) 11β hydroxysteroid dehydrogenase – implications for clinical medicine. Clin Endocrinol 44, 493–499. Stewart, P. M., Boulton, A., Kumar, S., Clark, P. M. and Shackleton, C. H. (1999) Cortisol metabolism in human obesity: impaired cortisone → cortisol conversion in subjects with central adiposity. J Clin Endocrinol Metab 84 (3), 1022–1027. Bujalska, I. J., Kumar, S. and Stewart, P. M. (1997) Does central obesity reflect ‘Cushing’s disease of the omentum’? Lancet 349 (9060), 1210–1213.

232

RELATIONSHIP BETWEEN FAT DISTRIBUTION AND INSULIN RESISTANCE

130. Tomlinson, J. W., Sinha, B., Bujalska, I., Hewison, M. and Stewart, P. M. (2002) Expression of 11beta-hydroxysteroid dehydrogenase type 1 in adipose tissue is not increased in human obesity. J Clin Endocrinol Metab 87 (12), 5630–5635. 131. Moore, J. S., Monson, J. P., Kaltsas, G., Putignano, P., Wood, P. J., Sheppard, M. C., Besser, G. M., Taylor, N. F. and Stewart, P. M. (1999) Modulation of 11betahydroxysteroid dehydrogenase isozymes by growth hormone and insulin-like growth factor: in vivo and in vitro studies. J Clin Endocrinol Metab 84 (11), 4172–4177. 132. Tomlinson, J. W., Moore, J., Cooper, M. S., Bujalska, I., Shahmanesh, M., Burt, C., Strain, A., Hewison, M. and Stewart, P. M. (2001) Regulation of expression of 11betahydroxysteroid dehydrogenase type 1 in adipose tissue: tissue-specific induction by cytokines. Endocrinology 142 (5), 1982–1989. 133. Bujalska, I. J., Kumar, S., Hewison, M. and Stewart, P. M. (1999) Differentiation of adipose stromal cells: The roles of glucocorticoids and 11β hydroxysteroid dehydrogenase. Endocrinology 140 (7), 3188–3196. 134. Palermo, M., Shackleton, C. H. L., Mantero, F. and Stewart, P. M. (1996) Urinary free cortisone and the assessment of 11β hydroxysteroid dehydrogenase activity in man. Clin Endocrinol (Oxf) 45, 605–611. 135. Stewart, P. M. and Krozowski, Z. S. (1999) 11 beta-hydroxysteroid dehydrogenase. Vit Horm 57, 249–324. 136. Rask, E., Olsson, T., Soderberg, S., Andrew, R., Livingstone, D. E., Johnson, O. and Walker, B. R. (2001) Tissue-specific dysregulation of cortisol metabolism in human obesity. J Clin Endocrinol Metab 86 (3), 1418–1421. 137. Rask, E., Walker, B. R., Soderberg, S., Livingstone, D. E., Eliasson, M., Johnson, O., Andrew, R. and Olsson, T. (2002) Tissue-specific changes in peripheral cortisol metabolism in obese women: increased adipose 11beta-hydroxysteroid dehydrogenase type 1 activity. J Clin Endocrinol Metab 87 (7), 3330–3336. 138. Weaver, J. U., Taylor, N. F., Monson, J. P., Wood, P. J. and Kelly, W. F. (1998) Sexual dimorphism in 11 beta hydroxysteroid dehydrogenase activity and its relation to fat distribution and insulin sensitivity; a study in hypopituitary subjects. Clin Endocrinol (Oxf) 49 (1), 13–20. 139. Livingstone, D. E., Jones, G. C., Smith, K., Jamieson, P. M., Andrew, R., Kenyon, C. J. and Walker, B. R. (2000) Understanding the role of glucocorticoids in obesity: tissuespecific alterations of corticosterone metabolism in obese Zucker rats. Endocrinology 141 (2), 560–563. 140. Kotelevtsev, Y., Brown, R. W., Fleming, S., Kenyon, C., Edwards, C. R., Seckl, J. R. and Mullins, J. J. (1999) Hypertension in mice lacking 11beta-hydroxysteroid dehydrogenase type 2. J Clin Invest 103 (5), 683–689. 141. Masuzaki, H., Paterson, J., Shinyama, H., Morton, N. M., Mullins, J. J., Seckl, J. R. and Flier, J. S. (2001) A transgenic model of visceral obesity and the metabolic syndrome. Science 294 (5549), 2166–2170. 142. Horton, R. and Tait, J. F. (1966) Androstenedione production and interconversion rates measured in peripheral blood and studies on the possible site of its conversion to testosterone. J Clin Invest 45, 301–313. 143. Bruch, H. R., Wolf, L., Budde, R., Romalo, G. and Schweikert, H. U. (1992) Androstenedione metabolism in cultured human osteoblast-like cells. J Clin Endocrinol Metab 75 (1), 101–105. 144. Jakob, F., Hormann, D., Seufert, J., Schneider, D. and Kohrle, J. (1995) Expression and regulation of aromatase cytochrome P450 in THP-1 human myeloid leukemia cells. Mol Cell Endocrinol 110, 27–33.

REFERENCES

233

145. Baynard, F., Clamens, S., Delsol, G., Blaes, N., Maret, A. and Faye, J. C. (1995) Oestrogen biosynthesis, oestrogen metabolism and functional oestrogen receptors in bovine aortic endothelial cells. Ciba Foundation Symp 191, 122–132. 146. Labrie, F. (1991) Intracrinology. Mol Cell Endocrinol 78, 113–118. 147. Labrie, F., Belanger, A., Cusan, L. and Candas, B. (1997) Physiological changes in dehydroepiandrosterone are not reflected by serum levels of active androgens and estrogens but their metabolites: intracrinology. J Clin Endocrinol Metab 82, 2403–2409. 148. Deslypere, J. P., Verdonck, L. and Vermeulen, A. (1985) Fat tissue: a steroid reservoir and site of steroid metabolism. J Clin Endocrinol Metab 61 (3), 564–570. 149. Simpson, E. R., Merrill, J. C., Hollub, A. J., Lorence, S. G. and Mendelson, C. R. (1989) Regulation of oestrogen biosynthesis by human adipose cells. Endo Rev 10, 136–148. 150. Simpson, E. R., Mahendroo, M. S., Means, G. D., Kilgore, M. W., Hinselwood, M. M., Graham-Lorence, S., Amarneh, B., Ito, Y., Fisher, C. R., Micheal, M. D., Mendelson, C. R. and Bulun, S. E. (1994) Aromatase cytochrome P450, the enzyme responsible for estrogen biosynthesis. Endo Rev 15, 352–354. 151. Bulun, S. E. and Simpson, E. R. (1994) Competitive reverse transcription-polymerase chain reaction analysis indicates that levels of aromatase cytochrome P450 transcripts in adipose tissue of buttocks, thighs, and abdomen of women increase with advancing age. J Clin Endocrinol Metab 78 (2), 428–432. 152. Zhao, Y., Nichols, J. E., Valdez, R., Mendelson, C. R. and Simpson, E. R. (1996) Tumor necrosis factor-alpha stimulates aromatase gene expression in human adipose stromal cells through use of an activating protein-1 binding site upstream of promoter 1.4. Mol Endocrinol 10 (11), 1350–1357. 153. Simpson, E. R., Zhao, Y., Agarwal, V. R., Michael, M. D., Bulun, S. E., Hinshelwood, M. M., Graham-Lorence, S., Sun, T., Fisher, C. R., Qin, K. and Mendelson, C. R. (1997) Aromatase expression in health and disease. Recent Prog Horm Res 52, 185–213. 154. Jones, M. E. E., Thornburn, A. W., Britt, K. L., Hewitt, K. N., Wreford, N. G., Proietto, J., Oz, O. K., Leury, B. J., Robertson, K. M., Yao, S. and Simpson, E. R. (2000) Aromatase-deficient (ArKO) mice have a phenotype of increased adiposity. Proc Natl Acad Sci 97, 12 735–12 740. 155. Poehlman, E. T. and Tchernof, A. (1998) Traversing the menopause: changes in energy expenditure and body composition. Coron Artery Dis 9 (12), 799–803. 156. Hope, P. J., Turnbull, H., Breed, W., Morley, J. E., Horowitz, M. and Wittert, G. A. (2000) The effect of ovarian steroids and photoperiod on body fat stores and uncoupling protein 2 in the marsupial Sminthopsis crassicaudata. Physiol Behav 69 (4/5), 463–470. 157. Misso, M. L., Murata, Y., Boon, W. C., Jones, M. E., Britt, K. L. and Simpson, E. R. (2003) Cellular and molecular characterization of the adipose phenotype of the aromatase-deficient mouse. Endocrinology 144 (4), 1474–1480. 158. Belanger, C., Luu-The, V., Dupont, P. and Tchernof, A. (2002) Adipose tissue intracrinology: potential importance of local androgen/estrogen metabolism in the regulation of adiposity. Horm Metab Res 34 (11/12), 737–745. 159. Bulun, S. E. (1998) The syndrome of aromatase deficiency. Curr Opin Endo Diab 5, 350–356. 160. Rosenbaum, M. and Leibel, R. (1999) Role of gonadal steroids in the sexual dimorphism in body composition and circulating concentrations of leptin. J Clin Endocrinol Metab 84 (6), 1784–1789.

234

RELATIONSHIP BETWEEN FAT DISTRIBUTION AND INSULIN RESISTANCE

161. Rebuff´e-Scrive, M., Enk, L., Crona, N., Lonnroth, P., Abrahamsson, L., Smith, U. and Bjorntorp, P. (1985) Fat cell metabolism in different regions in women. Effect of menstrual cycle, pregnancy, and lactation. J Clin Invest 75, 1973–1976. 162. Rebuff´e-Scrive, M., Eldh, J., Haafstrom, L. and Bjorntorp, P. (1986) Metabolism of mammary, abdominal and femoral adipocytes in women before and after the menopause. Metabolism 35, 792–797. 163. Price, T. M., O’Brien, S. N., Welter, B. H., George, R., Anandjiwala, J. and Kilgore, M. (1998) Estrogen regulation of adipose tissue lipoprotein lipase – possible mechanism of body fat distribution. Am J Obstet Gynecol 178, 101–107. 164. Wing, R. R., Matthews, K. A., Kuller, L. H., Meilahn, E. N. and Plantinga, P. L. (1991) Weight gain at the time of the menopause. Arch Intern Med 151, 97–102. 165. Pasquali, R., Casimirri, F., Labate, A. M., Tortelli, O., Pascal, G., Anconetani, B., Gatto, M. R., Flamia, R., Capelli, M. and Barbara, L. (1994) Body weight, fat distribution and the menopausal status in women. The VMH Collaborative Group. Int J Obes Relat Metab Disord 18 (9), 614–621. 166. Haarbo, J., Mareslew, U., Gotfredsen, A. and Kritiansen, C. (1991) Postmenopausal hormone replacement therapy prevents central redistribution of body fat after the menopause. Metabolism 10, 1323–1326. 167. Troisi, R., Wolf, A., Mason, J., Klinger, K. and Colditz, G. (1995) Relationship of body fat distribution to reproductive factors in pre-and postmenopausal women. Obesity Res 3, 143–151. 168. Krotkiewski, M. and Bjorntorp, P. (1976) The effect of progesterone and of insulin administration on regional adipose tissue cellularity in the rat. Acta Physiol Scand 96, 122–127. 169. Steingrimsdottir, L., Greenwood, M. R. C. and Brasel, J. A. (1980) Effect of pregnancy, lactation and a high fat diet on adipose tissue in Osborne-Mendal rats. J Nutr 110, 600–609. 170. Iverius, P.-H. and Brunzell, J. D. (1988) Relationship between lipoprotein lipase activity and plasma sex steroid levels in obese women. J Clin Invest 82, 1106–1111. 171. Rebuff´e-Scrive, M., Basdevant, A. and Guy-Grand, B. (1983) Effect of local application of progesterone on human adipose tissue lipoprotein lipase. Horm Metab Res 15, 566. 172. Mayes, J. S., McCann, J. P., Ownbey, T. C. and Watson, G. H. (1996) Regional differences and up-regulation of progesterone receptors in adipose tissues from oestrogentreated sheep. J Endocrinol 148, 19–25. 173. Roncari, D. A. K. and Van, L. R. (1978) Promotion of human adipocyte precursor replication by 17β -estradiol in culture. J Clin Invest 62, 503–508. 174. Rubin, G., Jones, M., Clyne, C., Zhao, Y. and Simpson, E. (1997) PPARgamma estrogens and aromatase expression in adipose tissue. 80th Annual Meeting of The Endocrine Society, New Orleans, LA, P1–22. 175. Anderson, L. A., McTernan, P. G., Barnett, A. H. and Kumar, S. (2001) The roles of androgen and oestrogen on proliferation: effect of site and gender. J Clin Endocrinol Metab 86, 5045–5051. 176. Casabiell, X., Pineiro, V., Peino, R., Lage, M., Camina, J., Gallego, R., Vallejo, L. G., Dieguez, C. and Casanueva, F. F. (1998) Gender differences in both spontaneous and stimulated leptin secretion by omental adipose tissue ‘in-vitro’: dexamethasone and estradiol stimulate leptin release in women but not in men. J Clin Endocrinol Metab 83, 2149–2155. 177. Marin, P. and Arvers, S. (1998) Androgens and abdominal obesity. Ballieres Clin Endocrinol Metab 12 (3), 441–451 [review].

REFERENCES

235

178. Bhasin, S., Storer, T. W., Berman, N., Callegari, C., Clevenger, B., Phillips, J., Bunnell, T. J., Tricker, R., Shirazi, A. and Casaburi, R. (1996) The effects of supraphysiologic doses of testosterone on muscle size and strength in man. N Engl J Med 335, 1–7. 179. Marin, P., Od´en, B. and Bjorntorp, P. (1995) Assimilation and mobilisation of triglycerides in subcutaneous abdominal and femoral adipose tissue in-vivo in men. J Clin Endocrinol Metab 80, 239–243. 180. Xu, X., De Pergola, G. and Bjorntorp, P. (1991) Testosterone increases lipolysis and the number of beta-adrenoceptors in the rat male adipocyte. Endocrinology 128, 379–382. 181. Xu, X., De Pergola, G., Eriksson, P. S., Fu, L., Carlsson, B., Yang, S., Eden, S. and Bjorntorp, P. (1993) Postreceptor events involved in the up-regulation of beta-adrenergic receptor mediated lipolysis by testosterone in rat white adipocytes. Endocrinology 132, 1651–1657. 182. Anderson, L. A., McTernan, P. G., Harte, A. L., Barnett, A. H. and Kumar, S. (2002) Androgen mediated regulation for altering lipolysis and lipogenesis by dihydrotestosterone in human adipose tissue. Diabetes Obesity Metab 4 (3), 209–214. 183. Lovejoy, J. C., Bray, G. A., Bourgeois, M. O., Macchiavelli, R., Rood, J. C., Greeson, C. and Partington, C. (1996) Exogenous androgens influence body composition and regional fat distribution in obese postmenopausal women – a clinical research centre study. J Clin Endocrinol Metab 82, 2198–2203.

9 PPARγ and Glucose Homeostasis Robert K. Semple and Stephen O’Rahilly

It has long been known that various xenobiotic compounds, when administered to mice, give rise to exuberant proliferation of hepatic peroxisomes, and ultimately to tumour development. In 1990 the mediator of this response was cloned and identified as a nuclear hormone receptor subsequently called peroxisome proliferator-activated receptor (PPAR).1 When two homologues were later cloned in Xenopus 2 and then in all mammalian species studied, the three receptors were designated PPARα, PPARγ and PPARδ. Independently of these developments, large scale chemical screening in the 1980s identified thiazolidinediones as potent agents for lowering blood glucose and improving lipid profiles in animal models of diabetes and obesity.3 The convergence of these two lines of investigation with the realization that the molecular target of the thiazolidinediones was PPARγ4 placed this receptor right at the centre of the interplay between lipid and glucose metabolism. This occurred at a time in the early 1990s when the ‘glucocentric’ view of type 2 diabetes as a disease principally of glucose metabolism (perhaps, in part, a historical accident)5 was being usurped by the resurgent appreciation that it is a complex metabolic disease in which abnormal lipid and glucose homeostasis are intimately and inextricably linked. In the decade since then, a wealth of experimental data has confirmed the importance of PPARγ as a central regulator of the metabolic cross-talk between insulin-sensitive tissues, and thiazolidinediones have proved beneficial therapeutically as the first new class of insulin-sensitizing agents for several decades. While PPARγ has afforded investigators a valuable handle on the intractable pathophysiology of this most prevalent condition, many questions remain about

Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

238

PPARγ AND GLUCOSE HOMEOSTASIS

its biology. Here the progress of investigation to date and the outstanding issues will briefly be reviewed.

9.1

Evidence from cell and rodent models

PPARγ binds to specific promoter response elements as a heterodimer with the retinoic acid receptor (RXR). In the presence of ligand it recruits coactivator molecules, which target chromatin-decondensing complexes to the promoter region and render it accessible for the initiation of transcription. Conversely, in the presence of an antagonist, and perhaps in the unliganded state, PPARγ recruits co-repressor molecules, which lead to the condensation of chromatin and sequestration of promoter elements. In addition, there is an evolving appreciation that PPARγ may influence gene expression indirectly, and usually negatively, through competition with other transcription factors for such accessory molecules. Although thiazolidinediones have been identified as potent synthetic ligands of PPARγ, it is not clear whether any physiologically relevant, potent endogenous ligands exist. The most widely studied candidate has been 15 deoxy-
12,14 -prostaglandin J2, identified as a potent activator in in vitro studies, but a more recent reanalysis has suggested not only that in vivo concentrations are too low for it to be a relevant ligand, but also that levels fail to correlate with PPARγ activity.6 Furthermore, a large number of unsaturated fatty acids, eicosanoids and prostaglandins have also been shown in vitro to activate the receptor. The binding affinities of these agents tend to be rather low, leading to the suggestion that, instead of conforming to the paradigm of receptors with single, very high affinity ligands, PPARγ functions as a more generic sensor of fatty acid flux, a property which might help subserve a role as a nutritional sensor and co-ordinator of metabolic responses. Further complexity is attested to by the ability of RXR ligands, too, to stimulate the transactivational activity of the PPARγ–RXR heterodimer, and the further modulation of this activity by phosphorylation of PPARγ.7 PPARγ is expressed at the highest levels in brown and white adipose tissue, where around 30 per cent of its protein expression is accounted for by a splice variant known as PPARγ2 .8, 9 This variant has an additional 28 N-terminal amino acids, and appears to be specific to white adipose tissue. PPARγ is also expressed at high levels in large intestine and white blood cells of both the lymphoid and myeloid lineages, and at lower levels in kidney, liver, skeletal and smooth muscles, pancreas and small intestine.9 – 11 The relative importance of PPARγ in each of these tissues from the point of view of glucose homeostasis is incompletely understood, and will form the remainder of this discussion.

White adipose tissue Although obesity is robustly associated with impaired insulin sensitivity, the severe insulin resistance of both humans with lipodystrophy and of mice with

EVIDENCE FROM CELL AND RODENT MODELS

239

genetically ablated white adipose tissue bears witness to the importance of normal amounts of this tissue in glucose homeostasis.12 Murine models of complete13 or near complete14 lipoatrophy exhibit ectopic fat accumulation in liver and muscle with severe insulin resistance progressing to diabetes.15 Importantly, transplantation of white adipose tissue into these mice dramatically improves insulin sensitivity and related parameters,16 demonstrating that it is the absence of fat per se that leads to the abnormal metabolic phenotype. Human subjects with lipodystrophy exhibit a similar pattern of severe insulin resistance and dyslipidaemia, and are discussed in detail in Section 17.5. PPARγ is known to play a pivotal role in preadipocyte differentiation in well characterized in vitro models of adipogenesis, as detailed in Figure 9.1. Mouse embryo-derived preadipocyte cell lines such as 3T3-L1 have been key tools in establishing the transcriptional cascade of adipogenesis. Comparison of this data (a) ERK C/EBPδ C/EBPβ PPARγ C/EBPα aP2, Glut4 etc. 48 h 10% serum Insulin Dexamethasone IBMX (raises cAMP)

96 h 10% serum Insulin

10% serum

Anti-adipogenic factors

(b)

GATA-2,3, TGFβ, wnt10b dexamethasone

C/EBPδ

PPARγ Adipocyte genes

cAMP

C/EBPβ

C/EBPα

P

IGF-1

ERKs

O/E-1, FGF10, FGF2, FBI Proadipogenic factors

Figure 9.1

Role of PPARγ in adipogenesis in vitro

240

PPARγ AND GLUCOSE HOMEOSTASIS

with adipose phenotypes of genetically modified animals suggests that they do, at least in part, model the in vivo situation, although it is also clear that many more influences on in vivo adipogenesis remain to be discovered. Figure 9.1(a) shows a typical pattern of expression of some of the key genes implicated in 3T3L1 differentiation, showing details of the artificial differentiation medium used. Figure 9.1(b) shows a simplified model of the transcriptional cascade, showing a complex series of kindling reactions leading to a robust mutually sustaining expression of PPARγ and C/EBPα, which then drive the full programme of adipocyte gene expression. In view of the physiological importance of adipose tissue, the simplest interpretation of the role of PPARγ in modulating insulin sensitivity is that the beneficial effects of its activation derive solely from its ability to promote the expansion of adipose tissue. However, thiazolidinediones are not used in clinical practice principally as a means of inducing adipogenesis in lipodystrophic subjects, but rather are used effectively in patients of normal or more commonly increased adiposity to enhance insulin sensitivity. Thus, apparently paradoxically, a pro-adipogenic agent is used to treat a condition that is often precipitated by the development of excessive adipose tissue. This paradox is at least partly resolved by consideration of the complex biology of adipose tissue in vivo, which cannot be replicated fully in vitro: far from the historical perception of adipose tissue as a relatively inert reservoir for excess dietary fat, it is now understood that white adipose tissue is a complex ‘organ’, which plays a key role in orchestrating numerous metabolic processes. It is constantly sensing the nutritional status of the whole organism, is in continuous communication with other tissues such as liver and muscle and is moreover spatially heterogeneous, with fat depots at different anatomical sites exhibiting markedly different patterns of gene expression, presumably reflecting distinct metabolic functions. Thus, modifying the hypothesis by invoking depot-selective responses of adipose tissue to PPARγ activation is necessary. Support for the concept of such depot-selective PPARγ effects is provided by pharmacological studies in mice: administration of potent and selective thiazolidinediones results in a preferential expansion of inguinal fat, analogous to human subcutaneous adipose tissue, at the expense of retroperitoneal and other depots.17 Possibly because this remodelling favours the accretion of lipid in depots that are less hormonally sensitive, and that do not have direct access to the portal circulation and hence the liver, insulin sensitivity is enhanced. However, the increased mass of inguinal fat pads is not simply due to accumulation of more tissue of the same morphology: analysis of the distribution of adipocyte size reveals that, while the total number of cells does increase, these cells are of smaller size due to a combination of hyperplasia of precursor cells and apoptosis of larger, hypertrophic adipocytes.18 – 22 Correlational studies in different genetic and dietary models of obesity have consistently revealed a positive relationship between adipocyte size and insulin resistance,23 – 28 and so

EVIDENCE FROM CELL AND RODENT MODELS

241

PPARγ is instrumental not only in modulating the amount and distribution of adipose tissue, but also in regulating the function of that mature tissue. A further experimental approach to the question of PPARγ and glucose sensitivity has been to manipulate mice genetically in order to look at the effects of altering PPARγ expression. Attempts to generate homozygous knockout animals foundered due to the embryonic lethality of the deficiency,22 but study of heterozygous knockout mice has been instructive, and has revealed some surprising results. Two groups have determined independently that PPARγ heterozygote knockout mice are more insulin sensitive than their wild type counterparts at baseline,22, 29 but only one of these groups found these animals to be protected from high-fat-induced insulin resistance.22 Further analysis of the mechanism underlying this showed that, as in thiazolidinedione-treated wild type animals, the mean size of the adipocytes decreased, though in this case they also declined in number, so that body weight and fat mass of the heterozygotes was reduced. However, when these heterozygous knockout mice were treated with antagonists of PPARγ and/or RXR they did indeed become insulin resistant,30 consistent with data from humans harbouring rare loss-of-function mutations in PPARγ, discussed later. The other group generating PPARγ heterozygote knockout mice found no difference in adipocyte hypertrophy and insulin resistance between heterozygous knockout and wild type animals, but did find the heterozygous animals to be relatively protected from the age-related decline in insulin sensitivity.31 A second, and complementary, genetic approach involved generation of mice with homozygous PPARγ alleles which have a point mutation preventing serine phosphorylation at position 112.32 Phosphorylation at this site has been shown in vitro to reduce PPARγ transactivational activity, and so loss of the potential for phosphorylation would be expected to result in a more active PPARγ, at least intermittently. The homozygous mice had no more adipose tissue than wild type counterparts, and were protected from high-fat-diet-induced insulin resistance and adipocyte hypertrophy. Thus the relationship between the level of PPARγ activity and insulin sensitivity is more complex than first imagined, with either stimulation or a moderate reduction in its action apparently leading to metabolic benefits. These metabolic benefits are lost when PPARγ activity drops below a certain critical threshold. It appears that the unifying feature of the two situations is a change in adipocyte morphology, such that the cells are predominantly smaller and less lipid laden. The possible functional connections between these adipocyte morphological changes and enhanced insulin sensitivity may broadly be classified into three groups: first, PPARγ may influence glucose tolerance through direct effects on the insulin sensitivity of the adipocytes, thus augmenting the rate of glucose disposal in adipose tissue. Second, the trapping of fatty acids in adipose tissue in the fed state may be rendered more efficient, and finally the change in adipocyte phenotype may result in an altered profile of secretory factors, which have remote effects on other insulin-sensitive tissues.

242

PPARγ AND GLUCOSE HOMEOSTASIS

Direct effects on adipose tissue insulin sensitivity

To the extent that preadipocyte differentiation involves the expression of many genes that confer insulin sensitivity upon adipose tissue, it is to be expected that thiazolidinediones, via PPARγ, will enhance the insulin-stimulated glucose uptake of adipose tissue. However, besides effects on the total number of adipocytes and on the population distribution of differentiated and undifferentiated cells, there is also evidence that enhanced glucose uptake in response to insulin results directly from PPARγ activation in mature adipocytes. Thus, in the 3T3-L1 murine embryo fibroblast model of adipogenesis, it has been shown that in cells differentiated for 15 days, and regarded as equivalent to mature adipocytes, exposure to rosiglitazone markedly induces expression of IRS-233 and Glut4.34 Conversely, a decline in the expression of these genes and a reduction in cell size and triglyceride content are seen in the presence of a dominant negative PPARγ.35 The induction of Glut4 expression and glucose transport in response to insulin is known to depend in part on activation of phosphatidyl inositol-3-kinase downstream from IRS1 and 2. However, a second pathway, involving interaction of the tyrosine kinase cCbl with the insulin receptor, is also thought to be involved. This, too, has been implicated directly in the PPARγ-mediated sensitization of adipocytes to insulin: cCbl interacts with the insulin receptor only via the adaptor protein CAP, or cCbl-associated protein, and expression of CAP appears to be rate limiting for the recruitment of cCbl to the insulin receptor.36 – 38 Thiazolidinediones have been shown to upregulate CAP expression,39 and promoter analysis of the CAP gene has confirmed the presence therein of a functional PPARγ-binding response element.40 In the presence of CAP, cCbl is phosphorylated by the receptor, and the CAP–cCbl complex then translocates to specific lipid membrane rafts enriched in caveolin.38 The presence of the CAP–cCbl complex in these rafts further recruits the CrkII–C3G complex to the rafts, which phosphorylates the small GTP-binding protein TC10. This step has been shown to be necessary for normal translocation of Glut4-containing vesicles to the cell surface.36 Thus PPARγ appears to enhance signalling through the two characterized arms of the signalling network that links insulin binding to Glut4 translocation and increased glucose uptake in adipose tissue. However, as glucose uptake into adipose tissue accounts for only a small proportion of whole body glucose disposal, this is likely to account at most for only part of the enhanced insulin sensitivity that results from PPARγ activation. Effects on dietary lipid handling

The central metabolic role played by adipose tissue is in the storage of excess caloric intake as triglycerides in the postprandial state, the controlled release of this stored energy under fasting conditions and above all the tight coupling

EVIDENCE FROM CELL AND RODENT MODELS

243

of these processes to the prevailing nutritional conditions. Consonant with this, expression of PPARγ does appear to be entrained to nutritional status, with significantly lower levels of mRNA found in adipose tissue in the fasting state and in experimental states of insulin deficiency, and higher levels seen after high fat feeding.41 Furthermore, it is likely that, if the relevant endogenous ligands are indeed a constellation of polyunsaturated fatty acids and their derivatives, the post-prandial state correlates with a period of high PPARγ activity. Hence it is likely to be of great functional significance that the transcriptional response elaborated by activated PPARγ encompasses a range of genes that play key roles in lipid uptake and trapping. Thus, lipoprotein lipase,42 which acts at the cell surface to hydrolyse chylomicron triglycerides, CD36 and FATP,43 which mediate uptake of the resulting free fatty acids into the adipocyte, fatty acid binding protein8 and acyl-CoA synthase44 are upregulated by PPARγ, while genes that induce lipolysis and release of fatty acids, such as the β3 -adrenergic receptor45 and leptin,46, 47 are repressed. In order for free fatty acids to be stored in the adipocyte as triglyceride, glycerol is also required. This may be provided by uptake of circulating glycerol, mediated by the adipocyte homologue of aquaporin (also upregulated by PPARγ)48 or by glyceroneogenesis. The rate-limiting step in this last process is catalysed by phosphoenolpyruvate carboxykinase, which, too, is upregulated by PPARγ.49 – 52 Finally, activation of glycerol prior to esterification with fatty acids is undertaken by glycerol kinase. Until recently, the dogma has been that this enzyme is not present in adipocytes, preventing a futile cycle between triglyceride hydrolysis and resynthesis being established. However, one report has now shown not only that this enzyme is present, but also that it is strongly upregulated by PPARγ activation in both mouse and human adipocytes,53 although the human findings have subsequently been strongly countered by negative findings from a second group.54 Thus the sum of these actions of PPARγ strongly favours free fatty acid trapping in adipose tissue in situations where ligand and receptor are plentiful. This is schematized in Figure 9.2. As indicated by the asterisks and bold lines, PPARγ upregulates the transcription of almost all stages of fatty acid trapping, from fatty acid release from lipoproteins and uptake into adipocytes, to esterification to glycerol. The futile glycerol cycle recently proposed to be stimulated by PPARγ is illustrated by the open circular arrows. These actions of PPARγ form the basis of the ‘lipid steal hypothesis’, which provides at present the best supported and most widely held explanation for the insulin-sensitizing action of thiazolidinediones. According to this hypothesis, PPARγ, by ensuring that almost all circulating free fatty acid is trapped efficiently in adipose tissue, prevents the exposure of other insulin-sensitive tissues such as liver and skeletal muscle to these molecules. It is well established that there is a strong correlation between ectopic accumulation of lipid at these sites (particularly in the form of intracellular fatty acyl-CoA)55 and insulin resistance, and so activation of PPARγ enhances insulin sensitivity and glucose disposal.

FFA

Figure 9.2

glycerol

*upregulated by PPARγ

glycerol

FFA FATP*

CD36*

DHAP

acylCoA

GK*

FFA

pyruvate

PEPCK*

GK*

ACS*

ADIPOCYTE

glycerol

FFA

CAPILLARY

FFA

glycerol

HSL glycerol

TG

HSL

Actions of PPARγ that promote fatty acid trapping in adipocytes

TG-rich LP

DHAP = dihydroxyacetone phosphate

TG = triglyceride

FFA = free fatty acids

HSL = hormone-sensitive lipase

LPL = lipoprotein lipase

PEPCK = phosphoenolpyruvate carboxykinase

GK = glycerol kinase

ACS = acylCoA synthetase

aquaporin*

244 PPARγ AND GLUCOSE HOMEOSTASIS

EVIDENCE FROM CELL AND RODENT MODELS

245

In type 2 diabetes, the habitually tight coupling between fatty acid trapping in adipose tissue and nutritional state is dysregulated, rendering lipid metabolism relatively inflexible in the face of fluctuating nutritional states. Because of this, mean circulating levels of free fatty acids are high. Pharmacological activation of PPARγ in this context allows these abnormally high fatty acids to be safely sequestered in adipocytes, ‘stealing’ them from the other insulin-sensitive tissues such as skeletal muscle. Indeed, the level of improvement of insulin sensitivity upon PPARγ activation seems to be tightly associated with a diminution in lipid accumulation in skeletal muscle.56 More direct support for this model of PPARγ function comes from a report describing fatty acid kinetics in rodents treated with PPARγ agonists: this found that thiazolidinediones increase insulinstimulated free fatty acid clearance, and also the rate of fasting free fatty acid appearance.57 These findings illustrate that determinations of fasting free fatty acid levels alone are likely to be only crude indicators of subtly dysregulated coupling of free fatty acid flux to nutritional status, and perhaps explain some of the inconsistent findings in human studies. Effects on adipocytokines

Fatty acids, as metabolic substrates themselves, provide an appealing link between adipose tissue and other insulin-sensitive tissues, and provide perhaps the simplest explanation of thiazolidinedione action. However, in the last decade it has become apparent that adipose tissue also has the capacity to elaborate a wide variety of small molecules with autocrine, paracrine or endocrine activity, and many of these molecules are subject to regulation by PPARγ. The term ‘adipocytokine’ has been coined for some of these molecules, and they have been grouped into those that enhance insulin sensitivity (such as leptin and adiponectin) and those that blunt insulin sensitivity (such as TNFα, resistin, and nitric oxide). Each of these has potential to account for some of the beneficial effects of PPARγ. The prototypic adipocyte-derived hormone is leptin, cloned in 1994.58 This cytokine-like peptide hormone is secreted in proportion to total body fat mass, and is best characterized as a centrally acting suppressor of appetite and food intake. Acting principally through the autonomic nervous system, it also induces increased energy expenditure and oxidation of lipid in various tissues.59 There is in addition some evidence in rodents that it has direct local actions on skeletal muscle and liver to enhance fatty acid catabolism.60, 61 There are also leptin receptors on adipocytes themselves, and on pancreatic β-cells. Evidence for the importance of leptin in glucose homeostasis is most compelling in fatless or lipodystrophic mice, where insulin sensitivity is significantly enhanced either by infusion of leptin62 or by its transgenic overexpression,63 although the degree of metabolic improvement is contingent upon the particular fatless model used, genetic background and details of the leptin regimen. Further to these observations, it has been demonstrated in A-ZIP/F1 fatless mice that the marked

246

PPARγ AND GLUCOSE HOMEOSTASIS

metabolic benefit seen with transplantation of adipose tissue is not observed with white adipose tissue from ob/ob mice, which does not secrete leptin.64 Thus, at least in the context of this model of complete lipodystrophy, leptin seems to be pre-eminent as the mediator of the beneficial effects of fat. Disappointingly, it appears that the dramatically beneficial effects of leptin may only be relevant to complete lipodystrophy, or genetic deficiency of the hormone, as the vast majority of models of obesity feature high leptin levels, often posited as evidence of ‘leptin resistance’. Such differences between the situation of dramatically low levels of leptin and that of normal or increased fat mass and high leptin perhaps accounts for the observation that PPARγ, though increasing insulin sensitivity, suppresses expression of leptin. This is apparent in the decreased circulating leptin in mice treated with thiazolidinediones, and the higher levels of leptin seen in heterozygous PPARγ knockout animals.21 Furthermore, the oxidative response to administration of leptin appears to be enhanced in mice with only one functional PPARγ allele.21 Thus, although leptin appears to be permissive for normal glucose homeostasis, its beneficial metabolic effects are not proportional to its concentration over the higher part of its range, and in cases of insulin resistance in animals that have normal or increased adipose stores other factors override it in determining insulin sensitivity. PPARγ activation, while decreasing leptin levels, enhances insulin sensitivity. Unlike leptin, adiponectin, an adipocyte-derived multimeric hormone with homology to complement factor 1q, circulates at levels that are inversely related to the amount of white adipose tissue. Also unlike leptin, circulating levels of adiponectin have been shown to correlate with insulin sensitivity in both genetic and dietary models of murine insulin resistance and obesity,65, 66 while infusion of adiponectin markedly improves hepatic insulin sensitivity.67 Furthermore, it has been shown that in a murine model of lipoatrophy (this time heterozygous PPARγ knockout mice treated with an RXR antagonist) infusion of adiponectin alone substantially improved insulin sensitivity, while co-administration of leptin normalized it.65 Importantly, these salutary effects of adiponectin were also seen in two genetic models of obesity-related insulin resistance.68, 69 Further analysis suggested that these effects of adiponectin were mediated by an enhanced capacity to oxidize fatty acids in muscle and liver, possibly via AMP-activated protein kinase,70 with resulting depletion of the ectopic triglyceride accumulated at these sites. Interestingly, this protein kinase has also been suggested recently to mediate the insulin-sensitizing action of metformin.71 In conjunction with the observation that PPARγ activation increases adiponectin expression and production both in vitro and in vivo, these findings render adiponectin a more appealing candidate than leptin as a mediator of some of PPARγ’s insulin-sensitizing action. However, the picture has been clouded by the contradictory findings from different workers who have produced adiponectin knockout mice: while one report suggested this resulted in moderate insulin resistance without body weight change, the other failed to find any alterations in insulin sensitivity.72, 73

EVIDENCE FROM CELL AND RODENT MODELS

247

Also confusingly, the second report suggested increased levels of β-oxidation in muscle and liver of knockout animals.73 One unifying feature of the two reports, however, was the observation of a marked reduction in neointimal proliferation and vascular stenosis.72 – 74 PPARγ also influences the expression of further secreted factors which may reduce insulin sensitivity: tumour-necrosis factor α (TNFα) is an adipocytederived signalling molecule that reduces insulin-stimulated glucose uptake75 and is found in high concentrations in obese and insulin-resistant individuals.76, 77 TNFα expression is inhibited by PPARγ activation in adipocytes,78 which could be relevant to the observed improvement of glycaemic control on PPARγ activation. Most support for this idea comes from studies in mice lacking TNFα. Compared with wild type animals, these mice are mildly resistant to obesity and insulin resistance induced by high fat feeding or gold thioglucose lesioning of the hypothalamus.79, 80 Studies of mice in which both isoforms of the TNFα receptor have been knocked out are less clearcut, however. Although the double-knockout mice were protected from insulin resistance and hyperglycaemia when put on a ob/ob background, the same mice, exposed to high fat diets, were equally or even more insulin resistant in comparison to wild type animals.79 Thus, further work remains to be done before the role of TNFα in the insulin-sensitizing action of PPARγ can be defined with confidence. Another gene downregulated by PPARγ encodes the secreted dimeric protein resistin, first identified in 3T3-L1 adipocytes by virtue of this downregulation.82 Plasma resistin levels are approximately in proportion to adipose tissue mass, and in some reports correlate with insulin resistance in both dietary and genetic models of obesity.82 Infusion of resistin has also been reported to induce marked hepatic insulin resistance in mice, but had no effect on the insulin sensitivity of other peripheral tissues in the same report.83 However, the relevance of resistin as a mediator of PPARγ activity remains to be clarified, as other reports have found that PPARγ activators stimulate rather than decrease resistin expression in vivo in several different models of obesity and insulin resistance.84 A further possible link between PPARγ action in adipose tissue and insulin sensitization lies in its effects on nitric oxide (NO) production: in diet-induced obesity and insulin resistance it is known that NO is overproduced in adipose tissue and muscles by inducible nitric oxide synthase (iNOS),85 and NO has been shown to impair insulin-stimulated glucose uptake in L6 myotubes and isolated skeletal muscle.86 It also exerts effects on skeletal muscle triglyceride metabolism through an action on lipoprotein lipase activity.87 Although it has yet to be demonstrated that PPARγ can repress iNOS expression in adipocytes, this has already been shown in other cell types, and so NO may potentially play a role in the improvement of glucose homeostasis resulting from PPARγ activation. Thus, tantalizing clues from these studies of adipocytokines suggest that they may well be important mediators of the action of PPARγ on insulin sensitivity,

248

PPARγ AND GLUCOSE HOMEOSTASIS

but the many confusing and contradictory findings from different experimental protocols and animal models mean that consensus has yet to be reached.

Skeletal muscle Although investigation of the role of PPARγ in insulin sensitization has focused on adipose tissue, it is also expressed in other insulin-sensitive tissues. Indeed, although the level of PPARγ protein is relatively low in skeletal muscle, the total mass of muscle and its importance as the site of most insulin-mediated glucose disposal mean that physiologically relevant effects of PPARγ in muscle cannot be excluded. Discrimination of the relative importance of PPARγ in adipose tissue and elsewhere has been attempted by administration of thiazolidinediones to lipoatrophic mice, but once again results have been inconsistent between different models: while rosiglitazone and troglitazone failed to have any effect on glucose or insulin levels in A-ZIP/F1 fatless mice (although circulating triglycerides were lowered),88 troglitazone greatly improved insulin and glucose levels in mice that had had 90 per cent of their adipose tissue ablated by coupling of the diphtheria toxin gene to the fat-specific aP2 promoter.20 It is possible that even the tiny residual amount of adipose tissue in the second model may have permitted a beneficial effect of troglitazone to have been expressed through its effects on those remaining adipocytes. Direct investigation of the part played by PPARγ in skeletal muscle is complicated by the potential for phenomena that are secondary to improved systemic insulin sensitivity during administration of PPARγ agonists. This problem has been circumvented experimentally in two ways: first, isolated cells in culture have been examined, and positive effects of thiazolidinediones on insulin-stimulated glucose uptake have been reported in both rat-derived L6 myotubes and in cultured human skeletal muscle cells, mediated by enhancement of insulin-stimulated PI3-kinase activity and translocation of GLUT4.89 – 94 Second, the muscle-specific deletion of PPARγ has recently been reported, and has permitted experimentation in a whole animal setting.95 These animals exhibit modest whole body insulin resistance, but surprisingly the glucose disposal into muscle is normal, with the effect attributable instead to hepatic and perhaps adipose insulin resistance. Moreover, the knockout animals accumulate adipose tissue at a faster rate than wild type controls despite reduced food consumption. This evidence of metabolic cross-talk between different insulin-sensitive tissues is a recurring theme of different tissue-specific genetic manipulations, including liver-specific deletion of PPARγ96 (see below) and adipose-specific deletion of Glut4, but the mechanisms are at best only partly understood. In this case no excess of intracellular lipid was seen in the livers of the knockout animals, and no increase in whole animal fatty acid oxidation was observed. However, when knockout animals were treated with thiazolidinediones, their response was as good as that of wild type controls, reinforcing the view that, while PPARγ may

EVIDENCE FROM CELL AND RODENT MODELS

249

have complex roles in normal physiology, the principal site of the therapeutic action of potent agonists is adipose tissue. This genetic model failed to provide support for the previous suggestion, based on gene expression profiling in PPARγ agonist-treated Zucker fatty rats, that pyruvate dehydrogenase kinase 4 (PDK4) may be a physiologically relevant target of PPARγ in muscle. PDK4 phosphorylates and inhibits pyruvate dehydrogenase, downregulating glucose oxidation and reciprocally promoting fatty acid oxidation, and was found to be downregulated eightfold by PPARγ activation.97 This may have been an example of indirect effects on muscle mediated by PPARγ activity elsewhere.

Pancreatic β-cells Pancreatic β-cells have been demonstrated to express PPARγ,98 and there is some evidence that its activation can both enhance insulin secretion and protect β-cells from the apoptosis thought to be triggered by excessive accumulation of triglyceride in the metabolic milieu of insulin resistance.98, 99 Although activation of PPARγ does not acutely improve insulin secretion in isolated human pancreatic islets, treatment of insulin-resistant animals with thiazolidinediones has been shown to increase fatty acid β-oxidation, thus blunting the accumulation of intracellular triglyceride in pancreatic β-cells, and delaying β-cell failure.98, 99 Similar prolongation of β-cell survival has been seen on administration of troglitazone to mice with streptozotocin-induced type I diabetes.100 Levels of intracellular triglyceride may not only affect cell survival, but are also likely to interfere with insulin secretion. A second, more direct mode of enhancement of insulin secretion has also been suggested, based on the finding of a functional PPARγ response element in the GLUT2 promoter region: PPARγmediated stimulation of GLUT2 expression would increase glucose uptake and hence lead ultimately to insulin release.101 Thus PPARγ appears not only to be an important player in systemic insulin resistance, but also to play a role in the β-cell response to that increased demand, the other key process in the pathogenesis of type 2 diabetes.

Liver The data relating to effects of chronic thiazolidinedione administration on hepatic glucose output in humans is conflicting,102 – 104 and together with the low levels of expression of PPARγ in the liver (around 10–30 per cent of levels in adipose tissue) they suggest that the liver is not a physiologically important site of action of PPARγ. However, in a range of different rodent models of diabetes and insulin resistance, encompassing both lipoatrophy and hyperphagic obesity, hepatic expression of PPARγ is markedly elevated.41, 20, 105 – 108 All these models feature hepatic steatosis, and patterns of gene expression suggest that the upregulation of PPARγ may contribute to this. Proof that PPARγ may

250

PPARγ AND GLUCOSE HOMEOSTASIS

indeed stimulate lipid accumulation in hepatocytes in vivo has recently been established using adenovirally mediated hepatic overexpression of PPARγ in mice.109 This resulted in hepatic steatosis accompanied by the upregulation in expression of a wide range of known PPARγ-responsive genes. However, in fatty liver induced by fasting or choline deficiency in PPARα knockout mice no evidence of PPARγ upregulation could be found,109 suggesting that not all hepatic steatosis is the same, and further that fat accumulation per se is insufficient to induce PPARγ expression. The clearest evidence that PPARγ, at least in some circumstances, has a significant role in the liver comes from two complementary approaches. First, detailed analysis of tissue-specific insulin sensitivity in A-ZIP/F-1 fatless mice treated with rosiglitazone demonstrated improvement of muscle insulin sensitivity at the expense of increased intracellular triglyceride and reduced insulin sensitivity in the liver,110 and second, two groups have reported liver-specific genetic ablation of PPARγ, in the context of wild type animals, of the A-ZIP/F1 fatless model, and ob/ob genetic obesity models. Compared to ob/ob animals with intact PPARγ, those with no hepatic PPARγ had decreased triglyceride accumulation in the liver, with concomitantly enhanced hepatic insulin sensitivity. However circulating levels of free fatty acids and triglycerides were increased, and insulin sensitivity in muscle and adipose tissue was further impaired. Despite the absence of PPARγ in the liver, rosiglitazone still resulted in marked improvement in these indices, further supporting the view that the principal site of its action is elsewhere.111 Correspondingly, in A-ZIP/F1 mice, loss of hepatic PPARγ also led to increased circulating triglyceride and worsened muscle insulin sensitivity, but this time the effect of rosiglitazone on whole body insulin sensitivity was abolished.96 Interestingly, even on a wild type background, deletion of liver PPARγ led to increased adiposity, hyperlipidaemia and insulin resistance compared with controls in the face of a high fat diet. Thus the evolving picture is that, while hepatic PPARγ may have little significance in lean animals, in those with obesity and insulin resistance it undergoes compensatory upregulation to accommodate excess lipid in the liver. Furthermore, considering all the studies of tissue-specific ablation of PPARγ suggests that there is a hierarchy of triglyceride storage: by far the largest site of storage, and probably the only one of relevance in lean animals, is the white adipose tissue. However, when presented with chronic caloric excess, the liver also has a significant capacity for fat storage. Only when both these depots are overwhelmed does skeletal muscle experience the adverse effects of lipid accumulation and insulin resistance. In this regard it is worth reflecting that the diet of large parts of Western industrialized society most closely resembles the types of high fat diet used in rodent studies. A summary of the possible roles of PPARγ in glucose homeostasis is shown in Figure 9.3. As well reducing adipocyte size, improving the profile of secreted adipokines, and enhancing lipid trapping in adipose tissue, PPARγ may also

INSIGHTS FROM HUMAN STUDIES

251

FFAs

LOW PPARγ activity

Resistin TNFα Leptin NO

Adiponectin

liver

HIGH PPARγ activity

muscle

pancreas

Resistin TNFα Leptin NO

Adiponectin

FFAs

Figure 9.3 Potential mechanisms of the insulin-sensitizing effect of PPARγ activation

permit excess triglyceride to be stored in the liver, giving further buffering capacity before skeletal muscle and β-cells are affected by accumulating intracellular lipid. However, loss of PPARγ from any one of these tissues is likely to have deleterious consequences for the insulin sensitivity (or secretion) of the others.

9.2 Insights from human studies Informing and motivating these rodent and cellular studies has been the established utility of potent and selective PPARγ agonists in the treatment of insulin resistance and type 2 diabetes in humans. As ever, caution must be exercised in extrapolating the results in these model systems to human pathophysiology, but the evolving evidence suggests that this is, in large part, appropriate. The principal sources of in vivo human data are clinical trials of potent PPARγ agonists and studies of subjects harbouring naturally occurring PPARγ variants. These will be considered in turn.

Pharmacological studies Effects on insulin sensitivity

Three potent and selective PPARγ agonists have been used in large scale clinical practice. The prototype, troglitazone, was unfortunately withdrawn by

252

PPARγ AND GLUCOSE HOMEOSTASIS

the manufacturer due to the occurrence in a small proportion of patients of serious, and sometimes fatal, hepatotoxicity, but subsequently both rosiglitazone and pioglitazone have been used with no evidence of similar problems. Extensive clinical trial data has accumulated for all three agents. Results have been consistent: used as monotherapy in patients with type 2 diabetes, troglitazone,112 – 114 rosiglitazone115, 116 and pioglitazone117 all reduce fasting and postprandial plasma glucose by around 2 mmol/l, and glycosylated haemoglobin A1 by between 1 and 1.5 per cent. When combined with either a sulfonylurea,117 – 120 metformin104, 121 or subcutaneous insulin,122, 123 similarly beneficial results are seen. When analysed in more detail by hyperinsulinaemic clamp studies, significant improvements in whole body insulin sensitivity have been seen with all three agents,104, 113, 114, 118, 117 accounted for mostly by increased glucose disposal rates, although a minor suppression of hepatic glucose output has sometimes been found.102, 103 Interestingly, one report that examined the effects of metformin and troglitazone in parallel suggested that their effects were complementary, with metformin principally suppressing hepatic glucose output, and troglitazone preferentially acting to increase the rate of glucose disposal.104 The response to thiazolidinediones is not confined to patients with diabetes: when used in 18 obese patients with normal glucose tolerance, troglitazone still reduced insulin levels in the fasting state and after glucose challenge, concomitant with a significant increase in insulin sensitivity measured directly by euglycaemic clamp.124 Effects on adipose tissue

As in rodents, human PPARγ1 and γ2 are highly expressed in adipose tissue,125 and exposure of cultured primary human preadipocytes to PPARγ agonists induces their differentiation,126 while overexpression of a potent dominantnegative mutant PPARγ has been shown to block this process.127 Treatment with thiazolidinediones promotes weight gain in humans and several studies have shown that the increase in body weight associated with thiazolidinedione treatment is accounted for principally by accumulation of subcutaneous fat (reviewed in reference128 ), whereas visceral adipose tissue volume is reduced or unchanged. These observations are in keeping with ex vivo studies in which preadipocytes isolated from subcutaneous abdominal adipose tissue differentiated more readily in response to thiazolidinediones than cells from visceral depots of the same subjects.129, 126 It is not known whether TZD treatment increases subcutaneous fat mass in all body regions equally, a question that is of interest in light of the burgeoning evidence of important functional metabolic differences between upper body (abdominal) and lower body (including femoro-gluteal) subcutaneous fat.130 Beyond gross effects on white adipose tissue distribution, whether TZD treatment in humans induces apoptosis of hypertrophic adipocytes and increased

INSIGHTS FROM HUMAN STUDIES

253

differentiation of preadipocytes, leading to alterations in average adipocyte size as seen in rodents, remains unresolved. Other aspects of thiazolidinedione action on adipose tissue appear to correspond rather variably with data from animal models. Thus, thiazolidinediones have generally been reported to lower free fatty acid (FFA) levels in clinical trials, consistent with the ‘lipid steal’ hypothesis of insulin sensitization. It is likely that many of the mechanisms subserving this are the same as those outlined earlier in mice, although whether the induction of glycerol kinase expression and activity in human adipocytes is significant appears doubtful.54 As in rodents, alterations of the profile of adipocyte-secreted proteins may play a role in the therapeutic actions of thiazolidinediones. Of those adipocytokines discussed earlier, adiponectin appears to be the best candidate in humans: plasma levels correlate with insulin sensitivity,131 – 133 and are inversely proportional to fat mass,134, 135 and thiazolidinediones increase adiponectin gene expression.136, 137 Moreover, circulating adiponectin levels were found to be dramatically lower in three individuals harbouring loss-of-function PPARγ mutations when compared with healthy controls or subjects with non-PPARγmediated severe insulin resistance, suggesting a direct correlation between PPARγ activity and adiponectin expression.138 Further studies should help to determine the extent to which this contributes to the insulin-sensitizing effects of PPARγ agonists. It is not clear whether resistin is significantly expressed in mature human adipocytes,139 – 141 and levels were undetectable in subjects carrying dominant negative PPARγ mutations.139 Definitive data on the role of nitric oxide and TNFα in PPARγ-mediated insulin sensitization in humans have also yet to be presented.

Studies of human genetic variants Rare mutations

Recently, three groups have independently identified loss-of-function mutations in the LBD of human PPARγ.142 – 144 Together these reports describe eight adult subjects, all of whom exhibit a stereotyped form of partial lipodystrophy and severe insulin resistance, with the insulin resistance being evident even in early childhood in affected individuals.145 Loss of subcutaneous fat from the limbs and gluteal region, with relative preservation of both the subcutaneous and visceral abdominal depots was uniformly reported, although some differences were observed in facial adipose tissue, said either to be reduced, preserved and increased in different kindreds carrying different point mutations. Although these findings are broadly in keeping with the role of PPARγ as a key regulator of adipogenesis, it is difficult to reconcile the pattern of selective partial lipodystrophy observed with current knowledge about adipose tissue PPARγ expression and the adipogenic response to receptor agonists in humans.

254

PPARγ AND GLUCOSE HOMEOSTASIS

As both partial and generalized lipodystrophy have consistently been found to be associated with insulin resistance in man as in rodents,146 it is likely that the dramatic diminution in peripheral limb and gluteal fat contributes to the severe insulin resistance of these rare patients. Additionally, even the residual adipose tissue depots in the individuals studied so far is metabolically inflexible, probably exacerbating the exposure of skeletal muscle and liver to dysregulated fatty acid fluxes.145 The findings in mice with tissue-specific ablation of PPARγ expression with or without lipodystrophy, discussed earlier, permit the speculation that the presence of a dominant negative PPARγ species in the liver and skeletal muscle of these subjects further denies them the compensatory FFA-buffering capacity afforded in lipodystrophy by the liver in particular, and so abnormalities in these tissues also may contribute significantly to the severe systemic insulin resistance observed. Although study of the metabolic cross-talk between insulin-sensitive tissues in humans is hampered by the lack of tissue-specific genetic deletions, the recent report of a kindred with a digenic pattern of severe insulin resistance may offer a rare opportunity for this type of investigation:147 in the kindred described, the combination of a frameshift mutation in PPARγ (effectively a null allele) and a premature stop mutation in the muscle-specific glycogen-targeting subunit of protein phosphatase 1 (PPP1R3A) cosegregated with severe insulin resistance, while either mutation alone appeared to have no effect on insulin sensitivity in the small number of subjects described. As PPARγ is most highly expressed in adipose tissue, while the PPP1R3A product is specific for cardiac and skeletal muscle, further investigation of these subjects, and of analogous animal models, may provide important insights into the factors mediating the metabolic dialogue between insulin-sensitive tissues, which has been a prominent but ill understood feature of many of the genetic models already described. This kindred may also be a first step away from rare monogenic insulin resistance towards the oligo- or polygenic patterns which account for most of the population burden of insulin resistance and diabetes. With loss-of-function mutations resulting in lipodystrophy, and PPARγ agonists promoting adipogenesis, gain-of-function PPARγ mutations might be anticipated to increase body fat mass. Indeed, four morbid subjects have been described who are heterozygous for a proline to glutamine substitution in the N-terminal domain of PPARγ2.148 This mutation is adjacent to a phosphorylation site thought to mediate downregulation of PPARγ transcriptional activity.7 The mutation interferes with this phosphorylation, resulting in a receptor with constitutive transcriptional function and enhanced adipogenic activity in vitro.148 However, no segregation studies were reported, and no more similar mutations were found in a larger screen of morbidly obese subjects. Furthermore, the observed severely obese phenotype is at odds with the recently reported mouse harbouring a mutation at the phosphorylation site itself: even homozygous animals had no more tendency to weight gain than wild type littermates, and moreover were protected from

INSIGHTS FROM HUMAN STUDIES

255

diet-induced insulin resistance.32 Although three of the human subjects were also reported to have low insulin levels relative to their massive obesity, all three also had type 2 diabetes, making inferences about their insulin sensitivity impossible. Pro12Ala polymorphism

The receptor mutations described hitherto are rare, and although they have provided unique insights into the role of PPARγ in human glucose homeostasis, with profound phenotypic effects in affected individuals, they make a negligible contribution to the risk of insulin resistance or type 2 diabetes in the general population. In contrast, by far the most prevalent human PPARγ genetic variant reported to date is a polymorphism, replacing alanine for proline at codon 12 (Pro12Ala) in the unique PPARγ2 amino-terminal domain, with an allelic frequency that approaches 15 per cent in some Caucasian populations.149, 150 Adipose tissue mRNA levels of PPARγ2 are increased in morbidly obese individuals, whereas expression of PPARγ1 is unchanged,125 and isoform-specific knockout studies suggest that PPARγ2 is the critical isoform mediating adipogenesis.151 In some functional assays, the Pro12Ala variant exhibits reduced binding to DNA and modest impairment in transcriptional activation, and these functional properties have been correlated with the association of this polymorphism with reduced body mass index (BMI), although subsequent studies have failed to confirm this finding.150, 152 Evidence for an association between Pro12Ala and type 2 diabetes was first reported in a Finnish population, in whom a lower BMI appeared to correlate with improved insulin sensitivity in those carrying the Ala allele, while in a group of second generation Japanese Americans the Pro/Pro genotype was found to associate with type 2 diabetes.152 However, this association was initially poorly reproducible, with only one of five subsequent studies showing statistically significant linkage with diabetes risk.153 – 157 Nevertheless, a meta-analysis of published association studies confirmed a modest (1.25-fold) but significant (p = 0.002) increase in diabetes risk with the Pro allele,149 the discrepancy being accounted for by the underpowering of many of the individual studies. Thus, if an entire population carried the Ala allele, the global prevalence of type 2 diabetes would be reduced by 25 per cent, making PPARγ potentially the most important common ‘diabetogene’ thus far discovered. Further reports have strengthened this association further,158, 159 although the caveat that publication bias may have favoured positive studies is a significant one. If the association does stand the test of time, it raises the question of how the Ala genetic variant influences diabetes risk. In the index study carriers of the Ala polymorphism had a significantly lower BMI, and after correcting for this there was no difference in insulin sensitivity between genotypes.152 This, in conjunction with the lower transcriptional activity of the Ala variant in vitro, led to the hypothesis that improved insulin sensitivity might be accounted for entirely by changes in adiposity. Although this would unify the observation that

256

PPARγ AND GLUCOSE HOMEOSTASIS

Whole body insulin sensitivity

thiazolidinedione treatment • heterozygous knockout mice • ?Pro12Ala

lean, healthy • dominant negative mutations • heterozygous knockout mice + PPARγ/RXR antagonist

PPARγ activity

Figure 9.4 sensitivity

Integrated model of the relationship between PPARγ activity and insulin

PPARγ2 has a unique regulatory role in adipogenesis,151 with the knowledge that body fat mass is a strong determinant of insulin sensitivity, subsequent studies have failed to yield consistent findings, with some even demonstrating a modestly greater BMI in carriers of the Ala allele.160 – 162 Germane to this are likely to be lessons from rodent studies, where not only the amount of fat, but also the size and function of individual adipocytes within it, is crucial to the optimal physiological function of the adipose tissue. Such issues have yet to be examined in human subjects. Furthermore, gene–environment interactions are likely to be more complex in humans, as evidenced by a recent study indicating that variations in dietary polyunsaturated fat versus saturated fat intake can influence BMI in carriers of the Ala variant.163 An attempt to simplify and integrate the relationship between PPARγ activity and insulin sensitivity in humans, based on the above diverse observations, is represented in Figure 9.4.

References 1. Issemann, I. and Green, S. (1990) Activation of a member of the steroid hormone receptor superfamily by peroxisome proliferators. Nature 347, 645–650. 2. Dreyer, C., Krey, G., Keller, H., Givel, F., Helftenbein, G. and Wahli, W. (1992) Control of the peroxisomal beta-oxidation pathway by a novel family of nuclear hormone receptors. Cell 68, 879–887. 3. Day, C. (1999) Thiazolidinediones: a new class of antidiabetic drugs. Diabet Med 16, 179–192. 4. Lehmann, J. M., Moore, L. B., Smith-Oliver, T. A., Wilkison, W. O., Willson, T. M. and Kliewer, S. A. (1995) An antidiabetic thiazolidinedione is a high affinity ligand for

REFERENCES

5. 6.

7. 8.

9.

10.

11.

12. 13.

14.

15. 16.

17.

18.

19.

20.

257

peroxisome proliferator-activated receptor gamma (PPAR gamma). J Biol Chem 270, 12 953–12 956. McGarry, J. D. (1992) What if Minkowski had been ageusic? An alternative angle on diabetes. Science 258, 766–770. Bell-Parikh, L. C., Ide, T., Lawson, J. A., McNamara, P., Reilly, M. and FitzGerald, G. A. (2003) Biosynthesis of 15-deoxy-delta12,14-PGJ2 and the ligation of PPARgamma. J Clin Invest 112, 945–955. Desvergne, B. and Wahli, W. (1999) Peroxisome proliferator-activated receptors: nuclear control of metabolism. Endocr Rev 20, 649–688. Tontonoz, P., Hu, E., Graves, R. A., Budavari, A. I. and Spiegelman, B. M. (1994) mPPAR gamma 2: tissue-specific regulator of an adipocyte enhancer. Genes Dev 8, 1224–1234. Escher, P., Braissant, O., Basu-Modak, S., Michalik, L., Wahli, W. and Desvergne, B. (2001) Rat PPARs: quantitative analysis in adult rat tissues and regulation in fasting and refeeding. Endocrinology 142, 4195–4202. Iijima, K., Yoshizumi, M., Ako, J., Eto, M., Kim, S., Hashimoto, M., Sugimoto, N., Liang, Y. Q., Sudoh, N., Toba, K. and Ouchi, Y. (1998) Expression of peroxisome proliferator-activated receptor gamma (PPARgamma) in rat aortic smooth muscle cells. Biochem Biophys Res Commun 247, 353–356. Braissant, O., Foufelle, F., Scotto, C., Dauca, M. and Wahli, W. (1996) Differential expression of peroxisome proliferator-activated receptors (PPARs): tissue distribution of PPAR-alpha, -beta, and -gamma in the adult rat. Endocrinology 137, 354–366. Reitman, M. L. (2002) Metabolic lessons from genetically lean mice. Annu Rev Nutr 22, 459–482. Moitra, J., Mason, M. M., Olive, M., Krylov, D., Gavrilova, O., Marcus-Samuels, B., Feigenbaum, L., Lee, E., Aoyama, T., Eckhaus, M., Reitman, M. L. and Vinson, C. (1998) Life without white fat: a transgenic mouse. Genes Dev 12, 3168–3181. Shimomura, I., Hammer, R. E., Richardson, J. A., Ikemoto, S., Bashmakov, Y., Goldstein, J. L. and Brown, M. S. (1998) Insulin resistance and diabetes mellitus in transgenic mice expressing nuclear SREBP-1c in adipose tissue: model for congenital generalized lipodystrophy. Genes Dev 12, 3182–3194. Kim, J. K., Gavrilova, O., Chen, Y., Reitman, M. L. and Shulman, G. I. (2000) Mechanism of insulin resistance in A-ZIP/F-1 fatless mice. J Biol Chem 275, 8456–8460. Gavrilova, O., Marcus-Samuels, B., Graham, D., Kim, J. K., Shulman, G. I., Castle, A. L., Vinson, C., Eckhaus, M. and Reitman, M. L. (2000) Surgical implantation of adipose tissue reverses diabetes in lipoatrophic mice. J Clin Invest 105, 271–278. Laplante, M., Sell, H., MacNaul, K. L., Richard, D., Berger, J. P. and Deshaies, Y. (2003) PPAR-gamma activation mediates adipose depot-specific effects on gene expression and lipoprotein lipase activity: mechanisms for modulation of postprandial lipemia and differential adipose accretion. Diabetes 52, 291–299. Okuno, A., Tamemoto, H., Tobe, K., Ueki, K., Mori, Y., Iwamoto, K., Umesono, K., Akanuma, Y., Fujiwara, T., Horikoshi, H., Yazaki, Y. and Kadowaki, T. (1998) Troglitazone increases the number of small adipocytes without the change of white adipose tissue mass in obese Zucker rats. J Clin Invest 101, 1354–1361. de Souza, C. J., Eckhardt, M., Gagen, K., Dong, M., Chen, W., Laurent, D. and Burkey, B. F. (2001) Effects of pioglitazone on adipose tissue remodeling within the setting of obesity and insulin resistance. Diabetes 50, 1863–1871. Burant, C. F., Sreenan, S., Hirano, K., Tai, T. A., Lohmiller, J., Lukens, J., Davidson, N. O., Ross, S. and Graves, R. A. (1997) Troglitazone action is independent of adipose tissue. J Clin Invest 100, 2900–2908.

258

PPARγ AND GLUCOSE HOMEOSTASIS

21. Yamauchi, T., Kamon, J., Waki, H., Murakami, K., Motojima, K., Komeda, K., Ide, T., Kubota, N., Terauchi, Y., Tobe, K., Miki, H., Tsuchida, A., Akanuma, Y., Nagai, R., Kimura, S. and Kadowaki, T. (2001) The mechanisms by which both heterozygous peroxisome proliferator-activated receptor gamma (PPARgamma) deficiency and PPARgamma agonist improve insulin resistance. J Biol Chem 276, 41 245–41 254. 22. Kubota, N., Terauchi, Y., Miki, H., Tamemoto, H., Yamauchi, T., Komeda, K., Satoh, S. et al. (1999) PPAR gamma mediates high-fat diet-induced adipocyte hypertrophy and insulin resistance. Mol Cell 4, 597–609. 23. Soria, A., D’Alessandro, M. E. and Lombardo, Y. B. (2001) Duration of feeding on a sucrose-rich diet determines metabolic and morphological changes in rat adipocytes. J Appl Physiol 91, 2109–2116. 24. Berger, J. J. and Barnard, R. J. (1999) Effect of diet on fat cell size and hormonesensitive lipase activity. J Appl Physiol 87, 227–232. 25. Schneider, B. S., Faust, I. M., Hemmes, R. and Hirsch, J. (1981) Effects of altered adipose tissue morphology on plasma insulin levels in the rat. Am J Physiol 240, E358–E362. 26. Craig, B. W., Garthwaite, S. M. and Holloszy, J. O. (1987) Adipocyte insulin resistance: effects of aging, obesity, exercise, and food restriction. J Appl Physiol 62, 95–100. 27. Olefsky, J. M. (1977) Mechanisms of decreased insulin responsiveness of large adipocytes. Endocrinology 100, 1169–1177. 28. Molina, J. M., Ciaraldi, T. P., Brady, D. and Olefsky, J. M. (1989) Decreased activation rate of insulin-stimulated glucose transport in adipocytes from obese subjects. Diabetes 38, 991–995. 29. Miles, P. D., Barak, Y., He, W., Evans, R. M. and Olefsky, J. M. (2000) Improved insulin-sensitivity in mice heterozygous for PPAR-gamma deficiency. J Clin Invest 105, 287–292. 30. Yamauchi, T., Waki, H., Kamon, J., Murakami, K., Motojima, K., Komeda, K., Miki, H., Kubota, N., Terauchi, Y., Tsuchida, A., Tsuboyama-Kasaoka, N., Yamauchi, N., Ide, T., Hori, W., Kato, S., Fukayama, M., Akanuma, Y., Ezaki, O., Itai, A., Nagai, R., Kimura, S., Tobe, K., Kagechika, H., Shudo, K. and Kadowaki, T. (2001) Inhibition of RXR and PPARgamma ameliorates diet-induced obesity and type 2 diabetes. J Clin Invest 108, 1001–1013. 31. Miles, P. D., Barak, Y., Evans, R. M. and Olefsky, J. M. (2003) Effect of heterozygous PPARgamma deficiency and TZD treatment on insulin resistance associated with age and high-fat feeding. Am J Physiol Endocrinol Metab 284, E618–E626. 32. Rangwala, S. M., Rhoades, B., Shapiro, J. S., Rich, A. S., Kim, J. K., Shulman, G. I., Kaestner, K. H. and Lazar, M. A. (2003) Genetic modulation of PPARgamma phosphorylation regulates insulin sensitivity. Dev Cell 5, 657–663. 33. Smith, U., Gogg, S., Johansson, A., Olausson, T., Rotter, V. and Svalstedt, B. (2001) Thiazolidinediones (PPARgamma agonists) but not PPARalpha agonists increase IRS-2 gene expression in 3T3-L1 and human adipocytes. FASEB J 15, 215–220. 34. Dana, S. L., Hoener, P. A., Bilakovics, J. M., Crombie, D. L., Ogilvie, K. M., Kauffman, R. F., Mukherjee, R. and Paterniti, J. R., Jr. (2001) Peroxisome proliferatoractivated receptor subtype-specific regulation of hepatic and peripheral gene expression in the Zucker diabetic fatty rat. Metabolism 50, 963–971. 35. Tamori, Y., Masugi, J., Nishino, N. and Kasuga, M. (2002) Role of peroxisome proliferator-activated receptor-gamma in maintenance of the characteristics of mature 3T3-L1 adipocytes. Diabetes 51, 2045–2055. 36. Chiang, S. H., Baumann, C. A., Kanzaki, M., Thurmond, D. C., Watson, R. T., Neudauer, C. L., Macara, I. G., Pessin, J. E. and Saltiel, A. R. (2001) Insulin-stimulated GLUT4 translocation requires the CAP-dependent activation of TC10. Nature 410, 944–948.

REFERENCES

259

37. Baumann, C. A., Brady, M. J. and Saltiel, A. R. (2001) Activation of glycogen synthase by insulin in 3T3-L1 adipocytes involves c-Cbl-associating protein (CAP)-dependent and CAP-independent signaling pathways. J Biol Chem 276, 6065–6068. 38. Baumann, C. A., Ribon, V., Kanzaki, M., Thurmond, D. C., Mora, S., Shigematsu, S., Bickel, P. E., Pessin, J. E. and Saltiel, A. R. (2000) CAP defines a second signalling pathway required for insulin-stimulated glucose transport. Nature 407, 202–207. 39. Ribon, V., Johnson, J. H., Camp, H. S. and Saltiel, A. R. (1998) Thiazolidinediones and insulin resistance: peroxisome proliferatoractivated receptor gamma activation stimulates expression of the CAP gene. Proc Natl Acad Sci USA 95, 14 751–14 756. 40. Baumann, C. A., Chokshi, N., Saltiel, A. R. and Ribon, V. (2000) Cloning and characterization of a functional peroxisome proliferator activator receptor-gamma-responsive element in the promoter of the CAP gene. J Biol Chem 275, 9131–9135. 41. Vidal-Puig, A., Jimenez-Linan, M., Lowell, B. B., Hamann, A., Hu, E., Spiegelman, B., Flier, J. S. and Moller, D. E. (1996) Regulation of PPAR gamma gene expression by nutrition and obesity in rodents. J Clin Invest 97, 2553–2561. 42. Schoonjans, K., Peinado-Onsurbe, J., Lefebvre, A. M., Heyman, R. A., Briggs, M., Deeb, S., Staels, B. and Auwerx, J. (1996) PPARalpha and PPARgamma activators direct a distinct tissue-specific transcriptional response via a PPRE in the lipoprotein lipase gene. EMBO J 15, 5336–5348. 43. Motojima, K., Passilly, P., Peters, J. M., Gonzalez, F. J. and Latruffe, N. (1998) Expression of putative fatty acid transporter genes are regulated by peroxisome proliferatoractivated receptor alpha and gamma activators in a tissue- and inducer-specific manner. J Biol Chem 273, 16 710–16 714. 44. Schoonjans, K., Watanabe, M., Suzuki, H., Mahfoudi, A., Krey, G., Wahli, W., Grimaldi, P., Staels, B., Yamamoto, T. and Auwerx, J. (1995) Induction of the acylcoenzyme A synthetase gene by fibrates and fatty acids is mediated by a peroxisome proliferator response element in the C promoter. J Biol Chem 270, 19 269–19 276. 45. Bakopanos, E. and Silva, J. E. (2000) Thiazolidinediones inhibit the expression of beta3-adrenergic receptors at a transcriptional level. Diabetes 49, 2108–2115. 46. De Vos, P., Lefebvre, A. M., Miller, S. G., Guerre-Millo, M., Wong, K., Saladin, R., Hamann, L. G., Staels, B., Briggs, M. R. and Auwerx, J. (1996) Thiazolidinediones repress ob gene expression in rodents via activation of peroxisome proliferator-activated receptor gamma. J Clin Invest 98, 1004–1009. 47. Kallen, C. B. and Lazar, M. A. (1996) Antidiabetic thiazolidinediones inhibit leptin (ob) gene expression in 3T3-L1 adipocytes. Proc Natl Acad Sci USA 93, 5793–5796. 48. Kishida, K., Shimomura, I., Nishizawa, H., Maeda, N., Kuriyama, H., Kondo, H., Matsuda, M., Nagaretani, H., Ouchi, N., Hotta, K., Kihara, S., Kadowaki, T., Funahashi, T. and Matsuzawa, Y. (2001) Enhancement of the aquaporin adipose gene expression by a peroxisome proliferator-activated receptor gamma. J Biol Chem 276, 48 572– 48 579. 49. Tordjman, J., Chauvet, G., Quette, J., Beale, E. G., Forest, C. and Antoine, B. (2003) Thiazolidinediones block fatty acid release by inducing glyceroneogenesis in fat cells. J Biol Chem 278, 18 785–18 790. 50. Olswang, Y., Cohen, H., Papo, O., Cassuto, H., Croniger, C. M., Hakimi, P., Tilghman, S. M., Hanson, R. W. and Reshef, L. (2002) A mutation in the peroxisome proliferator-activated receptor gamma-binding site in the gene for the cytosolic form of phosphoenolpyruvate carboxykinase reduces adipose tissue size and fat content in mice. Proc Natl Acad Sci USA 99, 625–630. 51. Glorian, M., Duplus, E., Beale, E. G., Scott, D. K., Granner, D. K. and Forest, C. (2001) A single element in the phosphoenolpyruvate carboxykinase gene mediates thiazolidinedione action specifically in adipocytes. Biochimie 83, 933–943.

260

PPARγ AND GLUCOSE HOMEOSTASIS

52. Tontonoz, P., Hu, E., Devine, J., Beale, E. G. and Spiegelman, B. M. (1995) PPAR gamma 2 regulates adipose expression of the phosphoenolpyruvate carboxykinase gene. Mol Cell Biol 15, 351–357. 53. Guan, H. P., Li, Y., Jensen, M. V., Newgard, C. B., Steppan, C. M. and Lazar, M. A. (2002) A futile metabolic cycle activated in adipocytes by antidiabetic agents. Nat Med 8, 1122–1128. 54. Tan, G. D., Debard, C., Tiraby, C., Humphreys, S. M., Frayn, K. N., Langin, D., Vidal, H. and Karpe, F. (2003) A ‘futile cycle’ induced by thiazolidinediones in human adipose tissue? Nat Med 9, 811–812; author reply 812. 55. Hegarty, B. D., Furler, S. M., Ye, J., Cooney, G. J. and Kraegen, E. W. (2003) The role of intramuscular lipid in insulin resistance. Acta Physiol Scand 178, 373–383. 56. Ye, J. M., Doyle, P. J., Iglesias, M. A., Watson, D. G., Cooney, G. J. and Kraegen, E. W. (2001) Peroxisome proliferator-activated receptor (PPAR)-alpha activation lowers muscle lipids and improves insulin sensitivity in high fat-fed rats: comparison with PPAR-gamma activation. Diabetes 50, 411–417. 57. Oakes, N. D., Thalen, P. G., Jacinto, S. M. and Ljung, B. (2001) Thiazolidinediones increase plasma–adipose tissue FFA exchange capacity and enhance insulin-mediated control of systemic FFA availability. Diabetes 50 (5), 1158–1165. 58. Zhang, Y., Proenca, R., Maffei, M., Barone, M., Leopold, L. and Friedman, J. M. (1994) Positional cloning of the mouse obese gene and its human homologue. Nature 372, 425–432. 59. Margetic, S., Gazzola, C., Pegg, G. G. and Hill, R. A. (2002) Leptin: a review of its peripheral actions and interactions. Int J Obes Relat Metab Disord 26, 1407–1433. 60. Kim, Y. B., Uotani, S., Pierroz, D. D., Flier, J. S., Kahn, B. B. (2000) In vivo administration of leptin activates signal transduction directly in insulin-sensitive tissues: overlapping but distinct pathways from insulin. Endocrinology 141, 2328–2339. 61. Minokoshi, Y., Kim, Y. B., Peroni, O. D., Fryer, L. G., Muller, C., Carling, D. and Kahn, B. B. (2002) Leptin stimulates fatty-acid oxidation by activating AMP-activated protein kinase. Nature 415, 339–343. 62. Shimomura, I., Hammer, R. E., Ikemoto, S., Brown, M. S. and Goldstein, J. L. (1999) Leptin reverses insulin resistance and diabetes mellitus in mice with congenital lipodystrophy. Nature 401, 73–76. 63. Ebihara, K., Ogawa, Y., Masuzaki, H., Shintani, M., Miyanaga, F., Aizawa-Abe, M., Hayashi, T., Hosoda, K., Inoue, G., Yoshimasa, Y., Gavrilova, O., Reitman, M. L. and Nakao, K. (2001) Transgenic overexpression of leptin rescues insulin resistance and diabetes in a mouse model of lipoatrophic diabetes. Diabetes 50, 1440–1448. 64. Colombo, C., Cutson, J. J., Yamauchi, T., Vinson, C., Kadowaki, T., Gavrilova, O. and Reitman, M. L. (2002) Transplantation of adipose tissue lacking leptin is unable to reverse the metabolic abnormalities associated with lipoatrophy. Diabetes 51, 2727–2733. 65. Yamauchi, T., Kamon, J., Waki, H., Terauchi, Y., Kubota, N., Hara, K., Mori, Y., Ide, T., Murakami, K., Tsuboyama-Kasaoka, N., Ezaki, O., Akanuma, Y., Gavrilova, O., Vinson, C., Reitman, M. L., Kagechika, H., Shudo, K., Yoda, M., Nakano, Y., Tobe, K., Nagai, R., Kimura, S., Tomita, M., Froguel, P. and Kadowaki, T. (2001) The fat-derived hormone adiponectin reverses insulin resistance associated with both lipoatrophy and obesity. Nat Med 7, 941–946. 66. Hu, E., Liang, P. and Spiegelman, B. M. (1996) AdipoQ is a novel adipose-specific gene dysregulated in obesity. J Biol Chem 271, 10 697–10 703. 67. Berg, A. H., Combs, T. P., Du, X., Brownlee, M. and Scherer, P. E. (2001) The adipocyte-secreted protein Acrp30 enhances hepatic insulin action. Nat Med 7, 947–953.

REFERENCES

261

68. Yamauchi, T., Kamon, J., Waki, H., Imai, Y., Shimozawa, N., Hioki, K., Uchida, S., Ito, Y., Takakuwa, K., Matsui, J., Takata, M., Eto, K., Terauchi, Y., Komeda, K., Tsunoda, M., Murakami, K., Ohnishi, Y., Naitoh, T., Yamamura, K., Ueyama, Y., Froguel, P., Kimura, S., Nagai, R. and Kadowaki, T. (2003) Globular adiponectin protected ob/ob mice from diabetes and ApoE-deficient mice from atherosclerosis. J Biol Chem 278, 2461–2468. 69. Fruebis, J., Tsao, T. S., Javorschi, S., Ebbets-Reed, D., Erickson, M. R., Yen, F. T., Bihain, B. E. and Lodish, H. F. (2001) Proteolytic cleavage product of 30-kDa adipocyte complement-related protein increases fatty acid oxidation in muscle and causes weight loss in mice. Proc Natl Acad Sci USA 98, 2005–2010. 70. Yamauchi, T., Kamon, J., Minokoshi, Y., Ito, Y., Waki, H., Uchida, S., Yamashita, S., Noda, M., Kita, S., Ueki, K., Eto, K., Akanuma, Y., Froguel, P., Foufelle, F., Ferre, P., Carling, D., Kimura, S., Nagai, R., Kahn, B. B. and Kadowaki, T. (2002) Adiponectin stimulates glucose utilization and fatty-acid oxidation by activating AMP-activated protein kinase. Nat Med 8, 1288–1295. 71. Zhou, G., Myers, R., Li, Y., Chen, Y., Shen, X., Fenyk-Melody, J., Wu, M., Ventre, J., Doebber, T., Fujii, N., Musi, N., Hirshman, M. F., Goodyear, L. J. and Moller, D. E. (2001) Role of AMP-activated protein kinase in mechanism of metformin action. J Clin Invest 108, 1167–1174. 72. Kubota, N., Terauchi, Y., Yamauchi, T., Kubota, T., Moroi, M., Matsui, J., Eto, K., Yamashita, T., Kamon, J., Satoh, H., Yano, W., Froguel, P., Nagai, R., Kimura, S., Kadowaki, T. and Noda, T. (2002) Disruption of adiponectin causes insulin resistance and neointimal formation. J Biol Chem 277, 25 863–25 866. 73. Ma, K., Cabrero, A., Saha, P. K., Kojima, H., Li, L., Chang, B. H., Paul, A. and Chan, L. (2002) Increased beta -oxidation but no insulin resistance or glucose intolerance in mice lacking adiponectin. J Biol Chem 277, 34 658–34 661. 74. Matsuda, M., Shimomura, I., Sata, M., Arita, Y., Nishida, M., Maeda, N., Kumada, M., Okamoto, Y., Nagaretani, H., Nishizawa, H., Kishida, K., Komuro, R., Ouchi, N., Kihara, S., Nagai, R., Funahashi, T. and Matsuzawa, Y. (2002) Role of adiponectin in preventing vascular stenosis. The missing link of adipo-vascular axis. J Biol Chem 277, 37 487–37 491. 75. Hotamisligil, G. S., Shargill, N. S. and Spiegelman, B. M. (1993) Adipose expression of tumor necrosis factor-alpha: direct role in obesity-linked insulin resistance. Science 259, 87–91. 76. Zinman, B., Hanley, A. J., Harris, S. B., Kwan, J. and Fantus, I. G. (1999) Circulating tumor necrosis factor-alpha concentrations in a native Canadian population with high rates of type 2 diabetes mellitus. J Clin Endocrinol Metab 84, 272–278. 77. Gonzalez, F., Thusu, K., Abdel-Rahman, E., Prabhala, A., Tomani, M. and Dandona, P. (1999) Elevated serum levels of tumor necrosis factor alpha in normal-weight women with polycystic ovary syndrome. Metabolism 48, 437–441. 78. Singh Ahuja, H., Liu, S., Crombie, D. L., Boehm, M., Leibowitz, M. D., Heyman, R. A., Depre, C., Nagy, L., Tontonoz, P. and Davies, P. J. (2001) Differential effects of rexinoids and thiazolidinediones on metabolic gene expression in diabetic rodents. Mol Pharmacol 59, 765–773. 79. Uysal, K. T., Wiesbrock, S. M., Marino, M. W. and Hotamisligil, G. S. (1997) Protection from obesity-induced insulin resistance in mice lacking TNF-alpha function. Nature 389, 610–614. 80. Ventre, J., Doebber, T., Wu, M., MacNaul, K., Stevens, K., Pasparakis, M., Kollias, G. and Moller, D. E. (1997) Targeted disruption of the tumor necrosis factor-alpha gene: metabolic consequences in obese and nonobese mice. Diabetes 46, 1526–1531.

262

PPARγ AND GLUCOSE HOMEOSTASIS

81. Schreyer, S. A., Chua, S. C., Jr. and LeBoeuf, R. C. (1998) Obesity and diabetes in TNF-alpha receptor- deficient mice. J Clin Invest 102, 402–411. 82. Steppan, C. M., Bailey, S. T., Bhat, S., Brown, E. J., Banerjee, R. R., Wright, C. M., Patel, H. R., Ahima, R. S. and Lazar, M. A. (2001) The hormone resistin links obesity to diabetes. Nature 409, 307–312. 83. Rajala, M. W., Obici, S., Scherer, P. E. and Rossetti, L. (2003) Adipose-derived resistin and gut-derived resistin-like molecule-beta selectively impair insulin action on glucose production. J Clin Invest 111, 225–230. 84. Way, J. M., Gorgun, C. Z., Tong, Q., Uysal, K. T., Brown, K. K., Harrington, W. W., Oliver, W. R., Jr., Willson, T. M., Kliewer, S. A. and Hotamisligil, G. S. (2001) Adipose tissue resistin expression is severely suppressed in obesity and stimulated by peroxisome proliferator-activated receptor gamma agonists. J Biol Chem 276, 25 651–25 653. 85. Pilon, G., Penfornis, P. and Marette, A. (2000) Nitric oxide production by adipocytes: a role in the pathogenesis of insulin resistance? Horm Metab Res 32, 480–484. 86. Perreault, M. and Marette, A. (2001) Targeted disruption of inducible nitric oxide synthase protects against obesity-linked insulin resistance in muscle. Nat Med 7, 1138–1143. 87. Picard, F., Kapur, S., Perreault, M., Marette, A. and Deshaies, Y. (2001) Nitric oxide mediates endotoxin-induced hypertriglyceridemia through its action on skeletal muscle lipoprotein lipase. FASEB J 15, 1828–1830. 88. Chao, L., Marcus-Samuels, B., Mason, M. M., Moitra, J., Vinson, C., Arioglu, E., Gavrilova, O. and Reitman, M. L. (2000) Adipose tissue is required for the antidiabetic, but not for the hypolipidemic, effect of thiazolidinediones. J Clin Invest 106, 1221–1228. 89. Arakawa, K., Ishihara, T., Aoto, M., Inamasu, M., Saito, A. and Ikezawa, K. (1998) Actions of novel antidiabetic thiazolidinedione, T-174, in animal models of non-insulindependent diabetes mellitus (NIDDM) and in cultured muscle cells. Br J Pharmacol 125, 429–436. 90. Yonemitsu, S., Nishimura, H., Shintani, M., Inoue, R., Yamamoto, Y., Masuzaki, H., Ogawa, Y., Hosoda, K., Inoue, G., Hayashi, T. and Nakao, K. (2001) Troglitazone induces GLUT4 translocation in L6 myotubes. Diabetes 50, 1093–1101. 91. Ciaraldi, T. P., Gilmore, A., Olefsky, J. M., Goldberg, M. and Heidenreich, K. A. (1990) In vitro studies on the action of CS-045, a new antidiabetic agent. Metabolism 39, 1056–1062. 92. Zhang, B., Szalkowski, D., Diaz, E., Hayes, N., Smith, R. and Berger, J. (1994) Potentiation of insulin stimulation of phosphatidylinositol 3-kinase by thiazolidinedionederived antidiabetic agents in Chinese hamster ovary cells expressing human insulin receptors and L6 myotubes. J Biol Chem 269, 25 735–25 741. 93. Cha, B. S., Ciaraldi, T. P., Carter, L., Nikoulina, S. E., Mudaliar, S., Mukherjee, R., Paterniti, J. R., Jr. and Henry, R. R. (2001) Peroxisome proliferator-activated receptor (PPAR) gamma and retinoid X receptor (RXR) agonists have complementary effects on glucose and lipid metabolism in human skeletal muscle. Diabetologia 44, 444–452. 94. Kausch, C., Krutzfeldt, J., Witke, A., Rettig, A., Bachmann, O., Rett, K., Matthaei, S., Machicao, F., Haring, H. U. and Stumvoll, M. (2001) Effects of troglitazone on cellular differentiation, insulin signaling, and glucose metabolism in cultured human skeletal muscle cells. Biochem Biophys Res Commun 280, 664–674. 95. Norris, A. W., Chen, L., Fisher, S. J., Szanto, I., Ristow, M., Jozsi, A. C., Hirshman, M. F., Rosen, E. D., Goodyear, L. J., Gonzalez, F. J., Spiegelman, B. M. and Kahn, C. R. (2003) Muscle-specific PPARgamma-deficient mice develop increased adiposity and insulin resistance but respond to thiazolidinediones. J Clin Invest 112, 608–618. 96. Gavrilova, O., Haluzik, M., Matsusue, K., Cutson, J. J., Johnson, L., Dietz, K. R., Nicol, C. J., Vinson, C., Gonzalez, F. J. and Reitman, M. L. (2003) Liver peroxisome

REFERENCES

97.

98.

99.

100.

101.

102.

103.

104.

105.

106.

107.

108.

109.

110.

263

proliferator-activated receptor gamma contributes to hepatic steatosis, triglyceride clearance, and regulation of body fat mass. J Biol Chem 278, 34 268–34 276. Way, J. M., Harrington, W. W., Brown, K. K., Gottschalk, W. K., Sundseth, S. S., Mansfield, T. A., Ramachandran, R. K., Willson, T. M. and Kliewer, S. A. (2001) Comprehensive messenger ribonucleic acid profiling reveals that peroxisome proliferator-activated receptor gamma activation has coordinate effects on gene expression in multiple insulin-sensitive tissues. Endocrinology 142, 1269–1277. Dubois, M., Pattou, F., Kerr-Conte, J., Gmyr, V., Vandewalle, B., Desreumaux, P., Auwerx, J., Schoonjans, K. and Lefebvre, J. (2000) Expression of peroxisome proliferator-activated receptor gamma (PPARgamma) in normal human pancreatic islet cells. Diabetologia 43, 1165–1169. Higa, M., Zhou, Y. T., Ravazzola, M., Baetens, D., Orci, L. and Unger, R. H. (1999) Troglitazone prevents mitochondrial alterations, beta cell destruction, and diabetes in obese prediabetic rats. Proc Natl Acad Sci USA 96, 11 513–11 518. Ogawa, J., Takahashi, S., Fujiwara, T., Fukushige, J., Hosokawa, T., Izumi, T., Kurakata, S. and Horikoshi, H. (1999) Troglitazone can prevent development of type 1 diabetes induced by multiple low-dose streptozotocin in mice. Life Sci 65, 1287–1296. Kim, H. I., Kim, J. W., Kim, S. H., Cha, J. Y., Kim, K. S. and Ahn, Y. H. (2000) Identification and functional characterization of the peroxisomal proliferator response element in rat GLUT2 promoter. Diabetes 49, 1517–1524. Sironi, A. M., Vichi, S., Gastaldelli, A., Pecori, N., Anichini, R., Foot, E., Seghieri, G. and Ferrannini, E. (1997) Effects of troglitazone on insulin action and cardiovascular risk factors in patients with non-insulin-dependent diabetes. Clin Pharmacol Ther 62, 194–202. Suter, S. L., Nolan, J. J., Wallace, P., Gumbiner, B. and Olefsky, J. M. (1992) Metabolic effects of new oral hypoglycemic agent CS-045 in NIDDM subjects. Diabetes Care 15, 193–203. Inzucchi, S. E., Maggs, D. G., Spollett, G. R., Page, S. L., Rife, F. S., Walton, V. and Shulman, G. I. (1998) Efficacy and metabolic effects of metformin and troglitazone in type II diabetes mellitus. N Engl J Med 338, 867–872. Edvardsson, U., Bergstrom, M., Alexandersson, M., Bamberg, K., Ljung, B. and Dahllof, B. (1999) Rosiglitazone (BRL49653), a PPARgamma-selective agonist, causes peroxisome proliferator-like liver effects in obese mice. J Lipid Res 40, 1177–1184. Memon, R. A., Tecott, L. H., Nonogaki, K., Beigneux, A., Moser, A. H., Grunfeld, C. and Feingold, K. R. (2000) Up-regulation of peroxisome proliferator-activated receptors (PPAR-alpha) and PPAR-gamma messenger ribonucleic acid expression in the liver in murine obesity: troglitazone induces expression of PPAR-gamma-responsive adipose tissue-specific genes in the liver of obese diabetic mice. Endocrinology 141, 4021–4031. Bedoucha, M., Atzpodien, E. and Boelsterli, U. A. (2001) Diabetic KKAy mice exhibit increased hepatic PPARgamma1 gene expression and develop hepatic steatosis upon chronic treatment with antidiabetic thiazolidinediones. J Hepatol 35, 17–23. Rahimian, R., Masih-Khan, E., Lo, M., van Breemen, C., McManus, B. M. and Dube, G. P. (2001) Hepatic over-expression of peroxisome proliferator activated receptor gamma2 in the ob/ob mouse model of non-insulin dependent diabetes mellitus. Mol Cell Biochem 224, 29–37. Yu, S., Matsusue, K., Kashireddy, P., Cao, W. Q., Yeldandi, V., Yeldandi, A. V., Rao, M. S., Gonzalez, F. J. and Reddy, J. K. (2003) Adipocyte-specific gene expression and adipogenic steatosis in the mouse liver due to peroxisome proliferator-activated receptor gamma1 (PPARgamma1) overexpression. J Biol Chem 278, 498–505. Kim, J. K., Fillmore, J. J., Gavrilova, O., Chao, L., Higashimori, T., Choi, H., Kim, H. J., Yu, C., Chen, Y., Qu, X., Haluzik, M., Reitman, M. L. and Shulman, G. I. (2003)

264

111.

112.

113.

114.

115.

116.

117.

118.

119.

120.

121.

122.

123.

124.

PPARγ AND GLUCOSE HOMEOSTASIS

Differential effects of rosiglitazone on skeletal muscle and liver insulin resistance in A-ZIP/F-1 fatless mice. Diabetes 52, 1311–1318. Matsusue, K., Haluzik, M., Lambert, G., Yim, S. H., Gavrilova, O., Ward, J. M., Brewer, B., Jr., Reitman, M. L. and Gonzalez, F. J. (2003) Liver-specific disruption of PPARgamma in leptin-deficient mice improves fatty liver but aggravates diabetic phenotypes. J Clin Invest 111, 737–747. Fonseca, V. A., Valiquett, T. R., Huang, S. M., Ghazzi, M. N. and Whitcomb, R. W. (1998) Troglitazone monotherapy improves glycemic control in patients with type 2 diabetes mellitus: a randomized, controlled study. The Troglitazone Study Group. J Clin Endocrinol Metab 83, 3169–3176. Maggs, D. G., Buchanan, T. A., Burant, C. F., Cline, G., Gumbiner, B., Hsueh, W. A., Inzucchi, S., Kelley, D., Nolan, J., Olefsky, J. M., Polonsky, K. S., Silver, D., Valiquett, T. R. and Shulman, G. I. (1998) Metabolic effects of troglitazone monotherapy in type 2 diabetes mellitus. A randomized, double-blind, placebo-controlled trial. Ann Intern Med 128, 176–185. Frias, J. P., Yu, J. G., Kruszynska, Y. T. and Olefsky, J. M. (2000) Metabolic effects of troglitazone therapy in type 2 diabetic, obese, and lean normal subjects. Diabetes Care 23, 64–69. Patel, J., Anderson, R. J. and Rappaport, E. B. (1999) Rosiglitazone monotherapy improves glycaemic control in patients with type 2 diabetes: a twelve-week, randomized, placebo-controlled study. Diabetes Obes Metab 1, 165–172. Raskin, P., Rappaport, E. B., Cole, S. T., Yan, Y., Patwardhan, R. and Freed, M. I. (2000) Rosiglitazone short-term monotherapy lowers fasting and post-prandial glucose in patients with type II diabetes. Diabetologia 43, 278–284. Miyazaki, Y., Mahankali, A., Matsuda, M., Mahankali, S., Hardies, J., Cusi, K., Mandarino, L. J. and DeFronzo, R. A. (2002) Effect of pioglitazone on abdominal fat distribution and insulin sensitivity in type 2 diabetic patients. J Clin Endocrinol Metab 87, 2784–2791. Miyazaki, Y., Mahankali, A., Matsuda, M., Glass, L., Mahankali, S., Ferrannini, E., Cusi, K., Mandarino, L. J. and DeFronzo, R. A. (2001) Improved glycemic control and enhanced insulin sensitivity in type 2 diabetic subjects treated with pioglitazone. Diabetes Care 24, 710–729. Wolffenbuttel, B. H., Gomis, R., Squatrito, S., Jones, N. P. and Patwardhan, R. N. (2000) Addition of low-dose rosiglitazone to sulphonylurea therapy improves glycaemic control in Type 2 diabetic patients. Diabet Med 17, 40–47. Horton, E. S., Whitehouse, F., Ghazzi, M. N., Venable, T. C. and Whitcomb, R. W. (1998) Troglitazone in combination with sulfonylurea restores glycemic control in patients with type 2 diabetes. The Troglitazone Study Group. Diabetes Care 21, 1462–1469. Fonseca, V., Rosenstock, J., Patwardhan, R. and Salzman, A. (2000) Effect of metformin and rosiglitazone combination therapy in patients with type 2 diabetes mellitus: a randomized controlled trial. JAMA 283, 1695–1702. Raskin, P., Rendell, M., Riddle, M. C., Dole, J. F., Freed, M. I. and Rosenstock, J. (2001) A randomized trial of rosiglitazone therapy in patients with inadequately controlled insulin-treated type 2 diabetes. Diabetes Care 24, 1226–1232. Schwartz, S., Raskin, P., Fonseca, V. and Graveline, J. F. (1998) Effect of troglitazone in insulin-treated patients with type II diabetes mellitus. Troglitazone and Exogenous Insulin Study Group. N Engl J Med 338, 861–866. Nolan, J. J., Ludvik, B., Beerdsen, P., Joyce, M. and Olefsky, J. (1994) Improvement in glucose tolerance and insulin resistance in obese subjects treated with troglitazone. N Engl J Med 331, 1188–1193.

REFERENCES

265

125. Vidal-Puig, A. J., Considine, R. V., Jimenez-Linan, M., Werman, A., Pories, W. J., Caro, J. F. and Flier, J. S. (1997) Peroxisome proliferator-activated receptor gene expression in human tissues. Effects of obesity, weight loss, and regulation by insulin and glucocorticoids. J Clin Invest 99, 2416–2422. 126. Adams, M., Montague, C. T., Prins, J. B., Holder, J. C., Smith, S. A., Sanders, L., Digby, J. E., Sewter, C. P., Lazar, M. A., Chatterjee, V. K. and O’Rahilly, S. (1997) Activators of peroxisome proliferator-activated receptor gamma have depot-specific effects on human preadipocyte differentiation. J Clin Invest 100, 3149–3153. 127. Gurnell, M., Wentworth, J. M., Agostini, M., Adams, M., Collingwood, T. N., Provenzano, C., Browne, P. O., Rajanayagam, O., Burris, T. P., Schwabe, J. W., Lazar, M. A. and Chatterjee, V. K. (2000) A dominant-negative peroxisome proliferator-activated receptor gamma (PPARgamma) mutant is a constitutive repressor and inhibits PPARgamma-mediated adipogenesis. J Biol Chem 275, 5754–5759. 128. Larsen, T. M., Toubro, S. and Astrup, A. (2003) PPARgamma agonists in the treatment of type II diabetes: is increased fatness commensurate with long-term efficacy? Int J Obes Relat Metab Disord 27, 147–161. 129. Sewter, C. P., Blows, F., Vidal-Puig, A. and O’Rahilly, S. (2002) Regional differences in the response of human pre-adipocytes to PPARgamma and RXRalpha agonists. Diabetes 51, 718–723. 130. Jensen, M. D. (1997) Lipolysis: contribution from regional fat. Annu Rev Nutr 17, 127–139. 131. Weyer, C., Funahashi, T., Tanaka, S., Hotta, K., Matsuzawa, Y., Pratley, R. E. and Tataranni, P. A. (2001) Hypoadiponectinemia in obesity and type 2 diabetes: close association with insulin resistance and hyperinsulinemia. J Clin Endocrinol Metab 86, 1930–1935. 132. Yamamoto, Y., Hirose, H., Saito, I., Tomita, M., Taniyama, M., Matsubara, K., Okazaki, Y., Ishii, T., Nishikai, K. and Saruta, T. (2002) Correlation of the adipocytederived protein adiponectin with insulin resistance index and serum high-density lipoprotein-cholesterol, independent of body mass index, in the Japanese population. Clin Sci (Lond) 103, 137–142. 133. Yu, J. G., Javorschi, S., Hevener, A. L., Kruszynska, Y. T., Norman, R. A., Sinha, M. and Olefsky, J. M. (2002) The effect of thiazolidinediones on plasma adiponectin levels in normal, obese, and type 2 diabetic subjects. Diabetes 51, 2968–2974. 134. Yang, W. S., Lee, W. J., Funahashi, T., Tanaka, S., Matsuzawa, Y., Chao, C. L., Chen, C. L., Tai, T. Y. and Chuang, L. M. (2002) Plasma adiponectin levels in overweight and obese Asians. Obes Res 10, 1104–1110. 135. Kern, P. A., Di Gregorio, G. B., Lu, T., Rassouli, N. and Ranganathan, G. (2003) Adiponectin expression from human adipose tissue: relation to obesity, insulin resistance, and tumor necrosis factor-alpha expression. Diabetes 52, 1779–1785. 136. Maeda, N., Takahashi, M., Funahashi, T., Kihara, S., Nishizawa, H., Kishida, K., Nagaretani, H., Matsuda, M., Komuro, R., Ouchi, N., Kuriyama, H., Hotta, K., Nakamura, T., Shimomura, I. and Matsuzawa, Y. (2001) PPARgamma ligands increase expression and plasma concentrations of adiponectin, an adipose-derived protein. Diabetes 50, 2094–2099. 137. Yang, W. S., Jeng, C. Y., Wu, T. J., Tanaka, S., Funahashi, T., Matsuzawa, Y., Wang, J. P., Chen, C. L., Tai, T. Y. and Chuang, L. M. (2002) Synthetic peroxisome proliferator-activated receptor-gamma agonist, rosiglitazone, increases plasma levels of adiponectin in type 2 diabetic patients. Diabetes Care 25, 376–380. 138. Combs, T. P., Wagner, J. A., Berger, J., Doebber, T., Wang, W. J., Zhang, B. B., Tanen, M., Berg, A. H., O’Rahilly, S., Savage, D. B., Chatterjee, K., Weiss, S., Larson, P. J., Gottesdiener, K. M., Gertz, B. J., Charron, M. J., Scherer, P. E. and

266

139.

140.

141.

142.

143.

144.

145.

146. 147.

148.

149.

150. 151.

152.

PPARγ AND GLUCOSE HOMEOSTASIS

Moller, D. E. (2002) Induction of adipocyte complement-related protein of 30 kilodaltons by PPARgamma agonists: a potential mechanism of insulin sensitization. Endocrinology 143, 998–1007. Savage, D. B., Sewter, C. P., Klenk, E. S., Segal, D. G., Vidal-Puig, A., Considine, R. V. and O’Rahilly, S. (2001) Resistin/Fizz3 expression in relation to obesity and peroxisome proliferator-activated receptor-gamma action in humans. Diabetes 50, 2199–2202. Janke, J., Engeli, S., Gorzelniak, K., Luft, F. C. and Sharma, A. M. (2002) Resistin gene expression in human adipocytes is not related to insulin resistance. Obes Res 10, 1–5. McTernan, P. G., McTernan, C. L., Chetty, R., Jenner, K., Fisher, F. M., Lauer, M. N., Crocker, J., Barnett, A. H. and Kumar, S. (2002) Increased resistin gene and protein expression in human abdominal adipose tissue. J Clin Endocrinol Metab 87, 2407. Barroso, I., Gurnell, M., Crowley, V. E., Agostini, M., Schwabe, J. W., Soos, M. A., Maslen, G. L., Williams, T. D., Lewis, H., Schafer, A. J., Chatterjee, V. K. and O’Rahilly, S. (1999) Dominant negative mutations in human PPARgamma associated with severe insulin resistance, diabetes mellitus and hypertension. Nature 402, 880–883. Agarwal, A. K. and Garg, A. (2002) A novel heterozygous mutation in peroxisome proliferator-activated receptor-gamma gene in a patient with familial partial lipodystrophy. J Clin Endocrinol Metab 87, 408–411. Hegele, R. A., Cao, H., Frankowski, C., Mathews, S. T. and Leff, T. (2002) PPARG F388L, a transactivation-deficient mutant, in familial partial lipodystrophy. Diabetes 51, 3586–3590. Savage, D. B., Tan, G. D., Acerini, C. L., Jebb, S. A., Agostini, M., Gurnell, M., Williams, R. L., Umpleby, A. M., Thomas, E. L., Bell, J. D., Dixon, A. K., Dunne, F., Boiani, R., Cinti, S., Vidal-Puig, A., Karpe, F., Chatterjee, V. K. and O’Rahilly, S. (2003) Human metabolic syndrome resulting from dominant-negative mutations in the nuclear receptor peroxisome proliferator-activated receptor-gamma. Diabetes 52, 910–917. Reitman, M. L., Arioglu, E., Gavrilova, O. and Taylor, S. I. (2000) Lipoatrophy revisited. Trends Endocrinol Metab 11, 410–416. Savage, D. B., Agostini, M., Barroso, I., Gurnell, M., Luan, J., Meirhaeghe, A., Harding, A. H., Ihrke, G., Rajanayagam, O., Soos, M. A., George, S., Berger, D., Thomas, E. L., Bell, J. D., Meeran, K., Ross, R. J., Vidal-Puig, A., Wareham, N. J., O’Rahilly, S., Chatterjee, V. K. and Schafer, A. J. (2002) Digenic inheritance of severe insulin resistance in a human pedigree. Nat Genet 31, 379–384. Ristow, M., Muller-Wieland, D., Pfeiffer, A., Krone, W. and Kahn, C. R. (1998) Obesity associated with a mutation in a genetic regulator of adipocyte differentiation. N Engl J Med 339, 953–959. Altshuler, D., Hirschhorn, J. N., Klannemark, M., Lindgren, C. M., Vohl, M. C., Nemesh, J., Lane, C. R., Schaffner, S. F., Bolk, S., Brewer, C., Tuomi, T., Gaudet, D., Hudson, T. J., Daly, M., Groop, L. and Lander, E. S. (2000) The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nat Genet 26, 76–80. Stumvoll, M. and Haring, H. (2002) The peroxisome proliferator-activated receptorgamma2 Pro12Ala polymorphism. Diabetes 51, 2341–2347. Ren, D., Collingwood, T. N., Rebar, E. J., Wolffe, A. P. and Camp, H. S. (2002) PPARgamma knockdown by engineered transcription factors: exogenous PPARgamma2 but not PPARgamma1 reactivates adipogenesis. Genes Dev 16, 27–32. Deeb, S. S., Fajas, L., Nemoto, M., Pihlajamaki, J., Mykkanen, L., Kuusisto, J., Laakso, M., Fujimoto, W. and Auwerx, J. (1998) A Pro12Ala substitution in

REFERENCES

153.

154.

155.

156.

157.

158.

159.

160.

161.

162.

163.

267

PPARgamma2 associated with decreased receptor activity, lower body mass index and improved insulin sensitivity. Nat Genet 20, 284–287. Hara, K., Okada, T., Tobe, K., Yasuda, K., Mori, Y., Kadowaki, H., Hagura, R., Akanuma, Y., Kimura, S., Ito, C. and Kadowaki, T. (2000) The Pro12Ala polymorphism in PPAR gamma2 may confer resistance to type 2 diabetes. Biochem Biophys Res Commun 271, 212–216. Mancini, F. P., Vaccaro, O., Sabatino, L., Tufano, A., Rivellese, A. A., Riccardi, G. and Colantuoni, V. (1999) Pro12Ala substitution in the peroxisome proliferator-activated receptor-gamma2 is not associated with type 2 diabetes. Diabetes 48, 1466–1468. Meirhaeghe, A., Fajas, L., Helbecque, N., Cottel, D., Auwerx, J., Deeb, S. S. and Amouyel, P. (2000) Impact of the peroxisome proliferator activated receptor gamma2 Pro12Ala polymorphism on adiposity, lipids and non-insulin-dependent diabetes mellitus. Int J Obes Relat Metab Disord 24, 195–199. Ringel, J., Engeli, S., Distler, A. and Sharma, A. M. (1999) Pro12Ala missense mutation of the peroxisome proliferator activated receptor gamma and diabetes mellitus. Biochem Biophys Res Commun 254, 450–453. Clement, K., Hercberg, S., Passinge, B., Galan, P., Varroud-Vial, M., Shuldiner, A. R., Beamer, B. A., Charpentier, G., Guy-Grand, B., Froguel, P. and Vaisse, C. (2000) The Pro115Gln and Pro12Ala PPAR gamma gene mutations in obesity and type 2 diabetes. Int J Obes Relat Metab Disord 24, 391–393. Poulsen, P., Andersen, G., Fenger, M., Hansen, T., Echwald, S. M., Volund, A., BeckNielsen, H., Pedersen, O. and Vaag, A. (2003) Impact of two common polymorphisms in the PPARgamma gene on glucose tolerance and plasma insulin profiles in monozygotic and dizygotic twins: thrifty genotype, thrifty phenotype, or both? Diabetes 52, 194–198. Li, S., Chen, W., Srinivasan, S. R., Boerwinkle, E. and Berenson, G. S. (2003) The peroxisome proliferator-activated receptor-gamma2 gene polymorphism (Pro12Ala) beneficially influences insulin resistance and its tracking from childhood to adulthood: the Bogalusa Heart Study. Diabetes 52, 1265–1269. Cole, S. A., Mitchell, B. D., Hsueh, W. C., Pineda, P., Beamer, B. A., Shuldiner, A. R., Comuzzie, A. G., Blangero, J. and Hixson, J. E. (2000) The Pro12Ala variant of peroxisome proliferator-activated receptor-gamma2 (PPAR-gamma2) is associated with measures of obesity in Mexican Americans. Int J Obes Relat Metab Disord 24, 522–524. Beamer, B. A., Yen, C. J., Andersen, R. E., Muller, D., Elahi, D., Cheskin, L. J., Andres, R., Roth, J. and Shuldiner, A. R. (1998) Association of the Pro12Ala variant in the peroxisome proliferator-activated receptor-gamma2 gene with obesity in two Caucasian populations. Diabetes 47, 1806–1808. Valve, R., Sivenius, K., Miettinen, R., Pihlajamaki, J., Rissanen, A., Deeb, S. S., Auwerx, J., Uusitupa, M. and Laakso, M. (1999) Two polymorphisms in the peroxisome proliferator-activated receptor-gamma gene are associated with severe overweight among obese women. J Clin Endocrinol Metab 84, 3708–3712. Luan, J., Browne, P. O., Harding, A. H., Halsall, D. J., O’Rahilly, S., Chatterjee, V. K., Wareham, N. J. (2001) Evidence for gene–nutrient interaction at the PPARgamma locus. Diabetes 50, 686–689.

10 Adipokines and Insulin Resistance Daniel K. Clarke and Vidya Mohamed-Ali The adipose tissue is now regarded as a major endocrine organ and a variety of factors released by adipose cells potentially mediate insulin resistance.1 Evidence suggests that one or more of these adipokines could impair insulin signalling and cause insulin resistance early in the pre-diabetic state.2 – 4 These factors include tumour necrosis factor (TNF)-α, leptin, interleukin-6 (IL-6) and more recently resistin and adiponectin (Figure 10.1): HSL, hormone-sensitive lipase;

Insulin

Catecholamines LPL

Chylomicron & VLDL-TAG

Resistin

Adiponectin

Adipose tissue HSL Leptin

NEFA

IL-6 TNFα sR-II

IL-6 sR TNFα TNFα sR-I

Figure 10.1 Major adipokines (and receptors) released from adipocytes (adapted from reference 1) Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

270

ADIPOKINES AND INSULIN RESISTANCE

IL-6, interleukin 6; LPL, lipoprotein lipase; NEFA, non-esterified fatty acids; PAI-1, plasminogen activator–inhibitor-1; sR, soluble receptor; TNF-α, tumour necrosis factor-α; VLDL-TG, very low density lipoprotein–triglyceride. However, the precise role of these factors and the molecular mechanisms whereby they generate insulin resistance has remained elusive. This chapter aims to critically review the current research on adipokines and insulin resistance, including known correlations and experimental data on their possible mechanisms.

10.1

Obesity and insulin resistance

The prevalence of obesity in England has tripled over the last 20 years and continues to rise, along with an increasing incidence of type II diabetes in younger age groups.5 Both of these clinical conditions are largely due to behavioural and lifestyle changes, with increased intake of high fat foods and low levels of physical exercise.6 Numerous cross-sectional studies have shown an association between obesity and type 2 diabetes, and this association is, in part, due to increased insulin resistance: a clear predisposing factor for the development of type 2 diabetes.7 In insulin resistance there is diminished response to insulin in a range of tissues. These actions include impairment of glucose uptake in skeletal muscle, inhibition of glucose release in the liver and reduced fat oxidation in adipose tissue.8, 9 In obesity an increased amount of adipose tissue is found in the subcutaneous layers between the muscle and dermis as well as fat deposits around the heart, liver, kidneys and other visceral organs. It has been clearly demonstrated that both an increase in total body fat and a preferential upper body accumulation of fat are independently related to insulin resistance.10 – 12 Obese women with a greater proportion of upper body fat are more insulin resistant than those with predominantly lower body fat.11 Visceral adipose tissue (VAT), as assessed by CT and MRI, was found to be specifically associated with hyperinsulinaemia, glucose intolerance, dyslipidaemia and insulin resistance in obese subjects.13 These observations, along with Randle’s hypothesis, led to the portal hypothesis. This states that complications of obesity are attributable to increases in VAT with an associated rise in portal vein NEFA concentrations, as the VAT, unlike the subcutaneous adipose tissue (SAT), drains directly into the portal vein.14 – 16 However, in obese subjects and those with type 2 diabetes, associations between total body fat, as well as abdominal SAT, and insulin resistance have been shown, independent of VAT.10, 17, 18 Furthermore, there is also growing experimental evidence that does not support the portal/Randle hypothesis. Therefore, mechanisms involving altered adipose conversion, inappropriate deposition of lipid in tissues other than adipose depots and the role of signals derived from adipose tissue now suggest additional explanations for the link between obesity and insulin resistance.

OBESITY AND INSULIN RESISTANCE

271

Increase in adipose tissue in non-morbid obesity is largely due to adipocyte hypertrophy, rather than hyperplasia.11, 19 – 21 Recent evidence shows that adipocyte hypertrophy correlates better with insulin resistance than any other measures of adiposity. These enlarged adipocytes are resistant to insulin-stimulated glucose uptake; however, this is unlikely to directly cause systemic insulin resistance. In obesity excess lipid is stored as triglyceride in liver and skeletal muscle, despite large stores of adipose tissue. As might appear paradoxical, in transgenic animal models in which adipose tissue development has been blocked, as well as in patients with lipodystrophy, who have insufficient adipose tissue mass, there are increased levels of lipid in muscle and liver. Thus, the consequence of either having no adipose tissue, or adipocytes that are unable to store further lipid in the face of excess energy intake, is ectopic storage of triglyceride, and this leads to severe insulin resistance.22 – 25 Adipocyte hypertrophy may be indicative of diminished adipocyte proliferation and differentiation. The regulation of adipocyte differentiation involves growth arrest and the coordinate regulation of nuclear transcription factors (CCAAT/enhancer binding proteins (C/EBPs) and peroxisome proliferator activated receptors (PPARs)), which activate a variety of genes necessary for lipid storage and insulin sensitivity (Figure 10.2). These transcription factors are in turn regulated by adipose signals. The increased fat cell size may also be a consequence of impaired fat oxidation. In rodents, it has been shown that inhibition of fat oxidation leads to increased intracellular lipid and insulin resistance in vivo. In humans, decreased fasting fat oxidation predicts weight gain and is associated with insulin resistance.22, 26 Fat oxidation in both muscle and adipose tissue is regulated by a number of factors, including endocrine factors secreted from the adipocyte, such as TNFα, adiponectin and leptin.27, 28

Figure 10.2 Transcription factors regulating adipogenesis

272

ADIPOKINES AND INSULIN RESISTANCE

10.2

Adipokines implicated in insulin resistance

In the early to mid-1990s a renaissance occurred in the study of the adipocyte and adipose tissue, where the understanding of its function developed from a storage tissue to a fully performing endocrine organ. Much of this knowledge derived from the discovery of three molecules expressed or secreted by adipose tissue. Two of these, TNFα and IL-6, were previously known pluripotent cytokines, and the third, leptin, was the product of the ob gene, secreted almost uniquely by adipose tissue. More recently two more adipokines with implications in insulin resistance, resistin and adiponectin, have been identified. These five adipokines, to varying extents, have been implicated in insulin resistance. This chapter will discuss the background and evidence for involvement of these adipokines in insulin resistance, both alone and in relation to other adipocyte products. Much of the data presented is based on in vitro experiments assessing insulin resistance in the adipocytes, muscle and liver, and to a lesser extent from in vivo studies.

Tumour necrosis factor-α The first adipokine to be directly associated with insulin resistance was TNFα,29 prior to the identification and naming of the molecule itself. Subsequently, associations between the expression of TNFα in adipose tissue and obesity and insulin resistance were reported in both humans and animals.30, 31 TNFα was first described as a pro-inflammatory cytokine released from monocytes and macrophages in response to injury or infection.32 – 35 The gene encodes a 26 kDa protein as a biologically active uncleaved transmembrane isotype, which after proteolytic cleavage is secreted as a 51 kDa homotrimer.36 – 38 TNFα functions via two dedicated receptors, TNFR1 (p55) and TNFR2 (p75), found on the cell surface of most cells. The ligand-binding, extracellular domains of these receptors share more homology than the intracellular portion, perhaps suggesting they initiate different signalling pathways and have distinct biological functions.39 While the expression and release of TNFα from adipocytes was discovered in the early 1990s,30, 31, 40, 41 prior to this it had long been known that a macrophagederived factor was able to induce insulin resistance in adipocytes.29, 42 Pertinently, the expression of TNFα and its receptors is raised considerably in both rodent and human obesity and insulin resistance.43 Soluble forms of the TNFα receptors also exist and are released by adipose tissue, perhaps to inhibit and localize the activity of the ligand.31, 44 Of all the adipokines, the relationship between TNFα and insulin resistance is by far the best understood. There is considerable data showing its ability to modulate components of the insulin signalling cascade, its effects on fat oxidation and adipocyte apoptosis and the expression and activity of other adipokines.

ADIPOKINES IMPLICATED IN INSULIN RESISTANCE

273

In the healthy individual insulin is a potent stimulator of glucose uptake in the adipocyte, muscle and liver. Insulin binds to its receptor, the insulin receptor (IR), on the cell surface and triggers a phosphorylation cascade that results in translocation of the insulin-dependent glucose transporter, GLUT4, from intracellular pools to the plasma membrane. TNFα reduces the availability of GLUT4 in the adipocyte by reducing expression of the GLUT4 gene, reducing protein levels or both.42, 45 – 47 With little glucose transporter available, the effect of insulin binding its receptor is significantly inhibited. TNFα also attenuates the signal further upstream from the transporter. Normal insulin binding causes tyrosine autophosphorylation of the intracellular part of the IR, and subsequent tyrosine phosphorylation of insulin receptor substrate-1 (IRS1). Incubation of cells with TNFα results in a serine phosphorylation of these molecules, thus preventing the tyrosine phosphorylation cascade.48 – 52 Other data has suggested that down-regulation of the expression of IRS-1 in the presence of TNFα may contribute to the reduced effectiveness of insulin signalling.47 From these studies it is clear that TNFα plays a central role in the inhibition of normal insulin signalling. The discovery of the class of anti-diabetic compounds known as thiazolidinediones (TZDs) has greatly increased the understanding of the mechanisms of insulin resistance, especially those related to TNFα.53 TZDs are activators of the transcription factor PPARγ, which is a powerful inducer of adipogenesis and controls the expression of a vast number of adipocyte genes. One of the benefits of TZD administration appears to be a significant decrease in TNFα expression in adipocytes, thus reducing the potential autocrine/paracrine effects of TNFα.54 Furthermore, TZDs and other PPARγ agonists appear to directly antagonize the inhibition of insulin signalling by TNFα. TZD treatment of adipocytes prevents TNFα-mediated reduction in GLUT4 expression,45 and is able to re-sensitize IR and IRS-1 to tyrosine phosphorylation.55 – 58 This outcome appears to be mediated by the downstream effects of PPARγ, returning the adipocyte to its normal function. Indirect TNFα effects on insulin resistance, such as increased circulating free fatty acids (FFAs) and a reduction in lipoprotein lipase (LPL) expression, were also reversed58 – 60 by TZDs. The use of these compounds has also led to the discovery of the intracellular signalling molecules affected by TNFα, notably NF-κB, which is activated by TNFα and mediates the downregulation in expression of a number of adipocyte genes.61, 62 TNFα is also equally adept at reducing insulin action on muscles following chronic exposure.63 – 67 Undoubtedly, part of this effect is due to autocrine/paracrine effects of TNFα released from skeletal muscle, but the considerable amounts of the cytokine released from adipocytes in obesity imply that muscle may be an endocrine target of adipocyte-derived TNFα. Again the mechanism is based upon the prevention of tyrosine phosphorylation of IR and IRS-1.50, 68 Similarly, liver cells are susceptible to insulin resistance induced by TNFα by the same

274

ADIPOKINES AND INSULIN RESISTANCE

mechanisms.50, 57, 63, 69 Therefore, the three major insulin-sensitive metabolic tissues in the body are targeted and affected by TNFα, inducing insulin resistance. In addition TNFα significantly increases the expression of IL-6,70, 71 reduces the expression of resistin72 – 74 and adiponectin,75 – 77 and correlates with increased expression of leptin.78, 79 It is possible that this leptin effect is a consequence of increased expression of both adipokines in the adipose tissue of the obese, as reports have suggested that incubation of TNFα with adipocytes reduces leptin expression,80 and that weight loss can considerably affect the relationship between the two.81 TNFα may also affect the deposition of lipid in adipose tissue by causing inappropriate apoptosis and dedifferentiation of adipocytes and preadipocytes.82, 83 This limits the available stores for excess lipid, resulting in the overloading of existing adipocytes as well as the sequestering of fat in other tissues, notably skeletal muscle and liver. Although the precise mechanism causing apoptosis is not known, TNFα increases expression of the apoptotic mediators bcl-2 and IL1β-converting enzyme (ICE). Furthermore, incubation with TZDs, which oppose TNFα action in adipocytes, increases the number of small adipocytes, reducing the volume of large adipocytes without affecting total adipose tissue mass.54 In vivo data supporting a direct role for TNFα in insulin resistance comes mainly from rodent models of obesity and insulin resistance, where antibodymediated neutralization of TNFα resulted in improvement of insulin sensitivity and a return to glycaemic control.50, 84 However, in one study of obese patients with type II diabetes the same strategy had no effect on insulin sensitivity, despite a decrease in TNFα levels in all subjects.85

Interleukin-6 IL-6, like TNFα, was originally described as a monocyte- or macrophagederived pro-inflammatory cytokine, and, again like TNFα, was later discovered to also be an adipocyte-derived molecule.86 – 88 IL-6 has a receptor complex consisting of a ligand binding domain (IL-6R) and a membrane-bound signaltransducing receptor (gp130), which upon ligand binding dimerizes and initiates signal transduction.89 – 92 The IL-6R also exists systemically in a soluble form, sIL-6R, where it binds and enhances signal transduction by polymerizing with gp130 on cell surfaces without the need for involvement of the membranebound component. Circulating IL-6 levels are significantly higher in obese individuals, such that they correlate closely with BMI, waist circumference and body fat.93 – 95 Also, in obese subjects there is greater expression of IL-6 in the visceral, compared with subcutaneous, adipose tissue.54 Much of the evidence implicating IL-6 in insulin action is based upon correlations between plasma levels of the adipokine and various indices of insulin resistance, first reported in cancer patients with reduced glucose metabolism.96 Subsequent studies have shown

ADIPOKINES IMPLICATED IN INSULIN RESISTANCE

275

similar correlations in insulin-resistant subjects following weight loss94, 97 and in healthy individuals.98 In children, IL-6 levels are associated with fat mass but not fasting insulin levels.99 Interestingly, in non-diabetic Pima Indians, during a hyperinsulinaemic, euglycaemic clamp circulating IL-6 levels did not correlate with glucose clearance rate.100 However, in another clamp study of obese and type II subjects there was a strong correlation between the inhibition of insulin action and adipose-tissue-derived IL-6.101 Furthermore, a gene polymorphism in the IL-6 promoter that results in increased IL-6 expression in peripheral blood cells was associated with abnormal circulating lipids and higher levels of diabetes, and the allele with lower IL-6 levels corresponded to increased insulin sensitivity.102 – 104 Other studies have also found a correlation between IL-6 and type 2 diabetes.105 Despite these studies showing associations of circulating IL-6 and insulin resistance, there is relatively little molecular evidence for any direct effect on tissue responses to insulin.94, 100, 101, 106 One recent study reports a reduction in adipocyte IRS-1 expression and tyrosine phosphorylation (without a related increase in serine phosphorylation) and lowered expression of GLUT4 in response to IL-6 treatment,107 though a number of previous studies have recorded an increase, or no change, in glucose uptake in adipocytes.108, 109 This increase in glucose uptake, additive to that of insulin, was however, attributed to an up-regulation in the intrinsic activity of the insulin-independent glucose transporter GLUT1. Furthermore, IL-6 does not appear to initiate insulin resistance in muscle,110 and the same study reported no effect of IL-6 on whole body glucose disposal. In the liver IL-6 may cause insulin resistance by inhibiting tyrosine phosphorylation of IRS-1, as well as inhibiting interactions between other downstream mediators of insulin signalling such as Akt and phosphatidylinositol 3-kinase.111 The ability of IL-6 to induce insulin resistance may be indirect, via modulation of the production and secretion of other adipokines. IL-6 increases the expression of resistin from human peripheral blood mononuclear cells.112 Conversely, circulating and adipocyte mRNA levels of adiponectin, the endogenous insulin sensitizer, were inversely correlated to plasma IL-6 levels,113 and exposure of adipocytes to IL-6 directly reduces transcription and release of adiponectin.76, 114 There are reports suggesting that IL-6 may stimulate fat oxidation in adipocytes,115, 116 thus leading to increased circulating NEFAs. However, this may only occur in specific adipose tissue depots (mammary), as other studies failed to show IL-6-induced increases in fat oxidation.117 In a study looking at the effect of food intake, sympathetic activation and lipolysis, it was reported that, while TNFα correlated with fat oxidation, IL-6 did not.118 However, previous reports have shown that IL-6 reduces lipoprotein lipase activity in adipose tissue and increases basal lipolysis.119 Part of the reason for the apparently contradictory results in terms of the role of IL-6 in insulin resistance may be that many different cell types, including

276

ADIPOKINES AND INSULIN RESISTANCE

macrophages, endothelial cells and smooth and skeletal muscle cells, as well as adipocytes, release IL-6. Clearly the regulation of IL-6 production differs depending on cellular origin, and this may have a bearing on the effects of the cytokine. For example, in response to exercise, circulating levels of IL-6, mainly of skeletal muscle origin, increase to several times higher than those in the basal state. Levels remain elevated for a few hours prior to dropping back to those seen prior to exercise.120 Such acute elevation in IL-6 levels is also seen after intravenous administration of the cytokine and is associated with increased plasma glucose clearance rate, in the absence of any change in insulin concentration, indicating that IL-6 stimulates glucose uptake in vivo.121 This is supported by in vitro data showing increases in basal and insulin stimulated glucose uptake by 3T3.L1 adipocytes. Stouthard et al. showed infusion of IL-6 to cause elevated serum NEFA concentrations.108 Furthermore, mice bearing an IL-6-secreting tumour were hypertriglyceridaemic as a result of increased hepatic triglyceride secretion, independent of endogenous catecholamines, implying elevation in basal fat oxidation.122 Subcutaneous injection of IL-6 in normal subjects also stimulates glucose oxidation.123 IL-6 release from contracting skeletal muscle increases when muscle glycogen availability is reduced and increases glucose uptake.124 Also during exercise, IL-6 inhibits the expression of TNFα in skeletal muscle.125 Thus, acute elevation in IL-6 increases lipolysis and glucose availability. In rodents, evidence suggests that central, but not peripheral, administration of IL-6 stimulates oxygen consumption, decreased body weight and fat mass, probably by stimulating energy expenditure at the CNS level.126, 127 Furthermore mice lacking IL-6 had a tendency to weight gain with age.128 In obesity there is a chronic (years) low level elevation (30–70 per cent compared with those in lean subjects) in circulating IL-6, probably due to constitutive release from adipose tissue. The consequences of this are less well understood.

Leptin Leptin was the third member of the triumvirate of adipokines discovered during the mid-1990s. It was initially investigated as the product of the ob gene, the absence of which resulted in grossly overweight animals, and its cloning was hailed as a new dawn in the fight against obesity.129 – 131 Although the effects of leptin on weight loss are not as profound in diet-induced obesity as in genetic models,132 it is nonetheless an important adipose signal with a range of endocrine functions. Leptin is a 16 kDa protein released primarily from adipocytes and its expression is directly related to the lipid content of the cells,78, 133 with greater levels being expressed in the subcutaneous compared with the visceral adipose tissue.134 – 136 Leptin increases with obesity136, 137 and its circulating levels are closely associated with all indices of adiposity.

ADIPOKINES IMPLICATED IN INSULIN RESISTANCE

277

The leptin receptor (Ob-R) shares homology with gp130, the signal-transducing component of class I cytokines. It is expressed both centrally and peripherally as membrane-bound (long) and soluble (short) forms, and has a range of target tissues.138 – 140 The adipokine is a mediator of energy status and metabolism. It interacts with other hormones, such as insulin, glucagon, the insulin-like growth factors, growth hormone and glucocorticoids, to regulate hepatic insulin action, peripheral glucose utilization, food intake and thermogenesis.141, 142 It is also a permissive factor for puberty, signalling to the hypothalamus when sufficient energy has been stored to embark on the energy-expensive reproductive cycle. Furthermore, In pregnancy leptin signals between maternal and foetal metabolic states.143 Insulin, both in vivo and in vitro, has been shown to increase systemic and adipocyte leptin release.144 – 146 Leptin concentrations are closely associated with fasting and fed insulin levels,137, 147, 148 as well as measures of insulin resistance.149 – 151 Treatment with TZDs to prevent insulin resistance also inhibits the expression and release of leptin.152 – 155 In both adipocytes and myocytes, basal and insulin stimulated glucose uptake remains unaffected in some studies. However, other reports suggest a decrease in insulin-stimulated glucose uptake in both cells.27, 156 – 168 Leptin may also reduce insulin-stimulated glycogen synthesis in muscle cells.168 – 170 In liver prefusates, leptin inhibits insulin-mediated gluconeogenesis, noradrenaline-mediated glucose release and glucagon-regulated glycogen lysis.171 – 173 In pancreatic β-cells it increases basal insulin production and secretion, but inhibits glucose-stimulated insulin release.174 – 180 Additionally, there appears to be no acute effect of leptin on insulin resistance in vivo.181 Recent evidence has shown that leptin may activate AMP-activated protein kinase (AMPK), a key regulator of cellular signalling and gene transcription,182 in skeletal muscle, liver and pancreas.183, 184 Activation of this protein results in the phosphorylation of various cytoplasmic enzymes involved in metabolism.185, 186 The consequence of AMPK activation by leptin is phosphorylation and inactivation of acetyl-CoA carboxylase (Figure 10.3). Acetyl-CoA carboxylase plays a critical role in fatty acid metabolism and catalyses the carboxylation of

Figure 10.3 Disruption of AMPK activity by leptin or adiponectin

278

ADIPOKINES AND INSULIN RESISTANCE

acetyl-CoA to malonyl-CoA. Malonyl-CoA is a precursor for fatty acid synthesis187 and a crucial regulator of mitochondrial fatty acid β-oxidation through its inhibition of carnitine palmitoyltransferase-1 (CPT-1).188, 189 Thus leptin-induced activation of AMPK leads to increased muscle glucose utilization by increasing fat oxidation and reduces intramyocellular lipid accumulation.190, 191 AMPK also regulates nuclear gene transcription and has been shown to repress PPARγ-mediated transcription activity.192, 193 Additionally, it may also affect the secretory function of adipocytes through SREBP1 (AMPK-sensitive transcription factor) regulation of leptin and resistin gene expression.194, 195 Both leptin deficiency and hyperleptinaemia are associated with insulin resistance.196 This apparent contradiction may be explained by the effect of leptin on lipid accumulation, probably through AMPK. In lipodystrophy and in ob/ob animals there is an accumulation of lipid in skeletal muscle and liver, leading to the inability of these tissues to respond adequately to insulin. Administration of leptin to these subjects leads to improvement in insulin sensitivity.197 – 199 Obese subjects, in addition to increased adipose tissue mass, also have fatty livers and muscle, leading to insulin resistance. However, in these subjects there is no deficiency in leptin per se, but an inability to respond adequately to this hormone: leptin resistance.200, 201 Any direct acute role for leptin mediating insulin action remains undetermined. However, the association of leptin with insulin resistance in type 2 diabetes and obesity may be through its regulation of the deposition of fat in insulin responsive tissues, rather than through effects on insulin signalling.

Resistin At the turn of the 21st century a novel cysteine rich adipokine was discovered that was claimed to be the link between obesity and insulin resistance.202, 203 In the first study to describe resistin, rodents treated with this molecule developed glucose intolerance and impaired insulin function. Neutralizing antibodies to resistin improved insulin sensitivity. Furthermore, they also reported elevated resistin concentrations in diet-induced and genetic obesity. Treatment with TZDs reduced resistin levels in obesity.209 The resistin mRNA encodes a 114-amino-acid polypeptide containing a 20-amino-acid signal sequence. The secreted protein, resistin, is a 94-amino-acid disulfide-linked dimer.204 These data suggest that the raised circulating resistin levels might contribute to the hyperglycaemia and insulin resistance seen in this model.203 Resistin expression in 3T3-L1 adipocytes was significantly up-regulated by high glucose concentrations and suppressed by insulin.205 Also in these cells treatment with TNFα reduced resistin expression, but a similar reduction was also apparent after exposure to troglitazone, a thiazolidinedione hypoglycaemic agent.73 However, other data suggests that resistin expression is inhibited in obesity and insulin resistance, and PPARγ agonists (including the TZDs) increase its expression.206 – 209

ADIPOKINES IMPLICATED IN INSULIN RESISTANCE

279

Studies of resistin expression, secretion and regulation in human adipose tissue are highly variable and levels are significantly lower than those reported in rodents.210 Also, the homology between the murine and human forms of the molecule is relatively low, at 56 per cent.4 Low levels of expression have been shown in isolated human adipocytes (preadipocytes express higher mRNA levels211 ).212 However, this expression is not always altered in relation to weight, BMI213, 214 or insulin sensitivity.215 – 217 Circulating levels are higher in women than men, but were unaltered in response to fasting or leptin administration.217 Nevertheless, others have found a correlation between serum resistin and parameters of insulin resistance.214, 218 Recent data report resistin mRNA or protein expression in a number of other tissues, including macrophages, pancreatic islets219 and the placenta.220, 221 However, its physiological significance, and any potential roles in insulin resistance, have yet to be determined.

Adiponectin Adiponectin was cloned and sequenced in 1995 and was termed ACRP30 (adipocyte complement-related protein of 30 kDa).222 It has also been referred to as AdipoQ, but the current settled nomenclature is adiponectin. It is an adipocyte-specific homologue of the complement factor C1q, and has evolutionary homology to TNFα.223 It signals through two recently cloned and sequenced receptors, AdipoR1 and AdipoR2, which are expressed predominantly in skeletal muscle and liver respectively.224 Activation of these receptors induces AMPK and PPARα activity and increases fatty acid oxidation and glucose uptake. Adiponectin expression was found to be reduced in obese mice and humans.77, 225 – 229 In addition to this, PPARγ agonists are potent stimulators of adiponectin expression, both in vivo and in vitro.75, 230 – 233 Infusion or injection of adiponectin is able to improve insulin sensitivity and reduce adiposity in mice.234 – 236 The inverse relationship between plasma adiponectin levels and obesity, and the fact that levels are also correlated to insulin sensitivity in healthy humans,237 suggests a strong probable role for adiponectin in alleviating insulin resistance. Data on molecular mechanisms adds further weight to the central role of adiponectin in insulin action. It lowers circulating glucose levels in mice by reducing glucose production,238 and increases fatty acid oxidation239, 240 as well as glucose uptake239 in muscle, all contributing to weight loss. Fatty acid oxidation in the liver is also enhanced by adiponectin,241 as is hepatic insulin action.242 Adiponectin, like leptin, activates AMPK and therefore mediates several metabolic pathways improving glucose utilization, without increasing insulin secretion. It has also been shown to decrease circulating NEFAs.243 In both human and animal studies adiponectin is reduced in obesity and inversely correlated to diabetes and insulin resistance in the obese, and administering adiponectin restores insulin sensitivity and assists weight reduction.

280

ADIPOKINES AND INSULIN RESISTANCE

Treatment of diabetes with TZDs significantly raises circulating adiponectin, and it is entirely plausible that adiponectin itself is contributing to the alleviation of the pathology. While the discovery of the molecule and its receptors is still relatively recent, the data on its effect on insulin resistance is consistent. It appears to work in concert with other adipokines, such as leptin, as an endogenous insulin sensitizer.

10.3

Conclusions

It is apparent that proteins produced by adipose tissue, both intracellular and secreted, function directly in the coordination of insulin resistance. In obesity tissue resistance to leptin and IL-6, combined with adiponectin, and perhaps resistin deficiency, may lead to decreased fat oxidation, and increased fat deposition within skeletal muscle, macrophages and liver. There is also increased expression of TNFα in fat and muscle, which causes insulin resistance directly through its effects on insulin signalling molecules, and indirectly by inhibiting adipogenesis and inducing apoptosis. Diet, exercise and genetic background as well as pharmacological agents may regulate the expression and secretion of these adipokines. However, to date most of these data are from in vitro studies or from rodent genetic models of insulin resistance and their significance in human disease is yet to be fully realized. A more complete understanding of the pathways regulating the biosynthesis of these hormones and their precise mechanisms of action is likely to lead to new approaches for managing obesity and diabetes.

References 1. Mohamed-Ali, V., Pinkney, J. H. and Coppack, S. W. (1998) Adipose tissue as an endocrine and paracrine organ. Int J Obes Relat Metab Disord 22 (12), 1145–1158. 2. Mooradian, A. D. (2001) Obesity: a rational target for managing diabetes mellitus. Growth Horm IGF Res 11 (Suppl. A), S79–83. 3. Poirier, P. and Eckel, R. H. (2002) Obesity and cardiovascular disease. Curr Atheroscler Rep 4 (6), 448–453. 4. Jazet, I. M., Pijl, H. and Meinders, A. E. (2003) Adipose tissue as an endocrine organ: impact on insulin resistance. Neth J Med 61 (6), 194–212. 5. Lobstein, T. J., James, W. P. and Cole, T. J. (2003) Increasing levels of excess weight among children in England. Int J Obes Relat Metab Disord 27 (9), 1136–1138. 6. Zimmet, P. and Thomas, C. R. (2003) Genotype, obesity and cardiovascular disease – has technical and social advancement outstripped evolution? J Intern Med 254 (2), 114–125. 7. Olefsky, J. M. and Kolterman, O. G. (1981) Mechanisms of insulin resistance in obesity and noninsulin-dependent (type II) diabetes. Am J Med 70 (1), 151–168. 8. Miller, J. L. (2003) Insulin resistance syndrome. Description, pathogenesis, and management. Postgrad Med Spec. No., 27–34.

REFERENCES

281

9. Shuldiner, A. R., Yang, R. and Gong, D. W. (2001) Resistin, obesity and insulin resistance – the emerging role of the adipocyte as an endocrine organ. N Engl J Med 345 (18), 1345–1346. 10. Frayn, K. N. (2000) Visceral fat and insulin resistance – causative or correlative? Br J Nutr 83 (Suppl. 1), S71–S77. 11. Kissebah, A. H., Vydelingum, N., Murray, R., Evans, D. J., Hartz, A. J., Kalkhoff, R. K. and Adams, P. W. (1982) Relation of body fat distribution to metabolic complications of obesity. J Clin Endocrinol Metab 54 (2), 254–260. 12. Bjorntorp, P. (1997) Body fat distribution, insulin resistance, and metabolic diseases. Nutrition 13 (9), 795–803. 13. Macor, C., Ruggeri, A., Mazzonetto, P., Federspil, G., Cobelli, C. and Vettor, R. (1997) Visceral adipose tissue impairs insulin secretion and insulin sensitivity but not energy expenditure in obesity. Metabolism 46 (2), 123–129. 14. Randle, P. J., Garland, P. B., Hales, C. N. and Newsholme, E. A. (1963) The glucose fatty-acid cycle. Its role in insulin sensitivity and the metabolic disturbances of diabetes mellitus. Lancet 1, 785–789. 15. Randle, P. J., Garland, P. B., Newsholme, E. A. and Hales, C. N. (1965) The glucose fatty acid cycle in obesity and maturity onset diabetes mellitus. Ann NY Acad Sci 131 (1), 324–333. 16. Felber, J. P. (1990) Significance of the Randle-mechanism in the etiology of diabetes type II. Horm Metab Res Suppl 22, 11–17. 17. Bjorntorp, P. (1991) Metabolic implications of body fat distribution. Diabetes Care 14 (12), 1132–1143. 18. Tai, E. S., Lau, T. N., Ho, S. C., Fok, A. C. and Tan, C. E. (2000) Body fat distribution and cardiovascular risk in normal weight women. Associations with insulin resistance, lipids and plasma leptin. Int J Obes Relat Metab Disord 24 (6), 751–757. 19. Crandall, D. L., Goldstein, B. M., Huggins, F. and Cervoni, P. (1984) Adipocyte blood flow: influence of age, anatomic location, and dietary manipulation. Am J Physiol 247 (1 Pt. 2), R46–R51. 20. Weyer, C., Foley, J. E., Bogardus, C., Tataranni, P. A. and Pratley, R. E. (2000) Enlarged subcutaneous abdominal adipocyte size, but not obesity itself, predicts type II diabetes independent of insulin resistance. Diabetologia 43 (12), 1498–1506. 21. Li, J., Yu, X., Pan, W. and Unger, R. H. (2002) Gene expression profile of rat adipose tissue at the onset of high-fat-diet obesity. Am J Physiol Endocrinol Metab 282 (6), E1334–E1341. 22. Ravussin, E. and Smith, S. R. (2002) Increased fat intake, impaired fat oxidation, and failure of fat cell proliferation result in ectopic fat storage, insulin resistance, and type 2 diabetes mellitus. Ann NY Acad Sci 967, 363–378. 23. Farnier, C., Krief, S., Blache, M., Diot-Dupuy, F., Mory, G., Ferre, P. and Bazin, R. (2003) Adipocyte functions are modulated by cell size change: potential involvement of an integrin/ERK signalling pathway. Int J Obes Relat Metab Disord 27 (10), 1178–1186. 24. Petersen, K. F., Oral, E. A., Dufour, S., Befroy, D., Ariyan, C., Yu, C., Cline, G. W., DePaoli, A. M., Taylor, S. I., Gorden, P. and Shulman, G. I. (2002) Leptin reverses insulin resistance and hepatic steatosis in patients with severe lipodystrophy. J Clin Invest 109 (10), 1345–1350. 25. Colombo, C., Cutson, J. J., Yamauchi, T., Vinson, C., Kadowaki, T., Gavrilova, O. and Reitman, M. L. (2002) Transplantation of adipose tissue lacking leptin is unable to reverse the metabolic abnormalities associated with lipoatrophy. Diabetes 51 (9), 2727– 2733. 26. Jequier, E. (1998) Effect of lipid oxidation on glucose utilization in humans. Am J Clin Nutr 67 (Suppl. 3), 527S–530S.

282

ADIPOKINES AND INSULIN RESISTANCE

27. Muller, G., Ertl, J., Gerl, M. and Preibisch, G. (1997) Leptin impairs metabolic actions of insulin in isolated rat adipocytes. J Biol Chem 272 (16), 10 585–10 593. 28. Heilbronn, L. K., Smith, S. R. and Ravussin, E. (2003) The insulin-sensitizing role of the fat derived hormone adiponectin. Curr Pharm Des 9 (17), 1411–1418. 29. Pekala, P., Kawakami, M., Vine, W., Lane, M. D. and Cerami, A. (1983) Studies of insulin resistance in adipocytes induced by macrophage mediator. J Exp Med 157 (4), 1360–1365. 30. Hotamisligil, G. S., Shargill, N. S. and Spiegelman, B. M. (1993) Adipose expression of tumor necrosis factor-alpha: direct role in obesity-linked insulin resistance. Science 259 (5091), 87–91. 31. Hotamisligil, G. S., Arner, P., Caro, J. F., Atkinson, R. L. and Spiegelman, B. M. (1995) Increased adipose tissue expression of tumor necrosis factor-alpha in human obesity and insulin resistance. J Clin Invest 95 (5), 2409–2415. 32. Carswell, E. A., Old, L. J., Kassel, R. L., Green, S., Fiore, N. and Williamson, B. (1975) An endotoxin-induced serum factor that causes necrosis of tumors. Proc Natl Acad Sci USA 72 (9), 3666–3670. 33. Old, L. J. (1985) Tumor necrosis factor (TNF). Science 230 (4726), 630–632. 34. Beutler, B. A., Milsark, I. W. and Cerami, A. (1985) Cachectin/tumor necrosis factor: production, distribution, and metabolic fate in vivo. J Immunol 135 (6), 3972– 3977. 35. Beutler, B., Greenwald, D., Hulmes, J. D., Chang, M., Pan, Y. C., Mathison, J., Ulevitch, R. and Cerami, A. (1985) Identity of tumour necrosis factor and the macrophagesecreted factor cachectin. Nature 316 (6028), 552–554. 36. Kriegler, M., Perez, C., DeFay, K., Albert, I. and Lu, S. D. (1988) A novel form of TNF/cachectin is a cell surface cytotoxic transmembrane protein: ramifications for the complex physiology of TNF. Cell 53 (1), 45–53. 37. Beutler, B. (1995) TNF, immunity and inflammatory disease: lessons of the past decade. J Invest Med 43 (3), 227–235. 38. Xu, H., Sethi, J. K. and Hotamisligil, G. S. (1999) Transmembrane tumor necrosis factor (TNF)-alpha inhibits adipocyte differentiation by selectively activating TNF receptor 1. J Biol Chem 274 (37), 26 287–26 295. 39. Tartaglia, L. A., Weber, R. F., Figari, I. S., Reynolds, C., Palladino, M. A., Jr., and Goeddel, D. V. (1991) The two different receptors for tumor necrosis factor mediate distinct cellular responses. Proc Natl Acad Sci USA 88 (20), 9292–9296. 40. Kern, P. A., Saghizadeh, M., Ong, J. M., Bosch, R. J., Deem, R. and Simsolo, R. B. (1995) The expression of tumor necrosis factor in human adipose tissue. Regulation by obesity, weight loss, and relationship to lipoprotein lipase. J Clin Invest 95 (5), 2111–2119. 41. Yamakawa, T., Tanaka, S., Yamakawa, Y., Kiuchi, Y., Isoda, F., Kawamoto, S., Okuda, K. and Sekihara, H. (1995) Augmented production of tumor necrosis factor-alpha in obese mice. Clin Immunol Immunopathol 75 (1), 51–56. 42. Stephens, J. M. and Pekala, P. H. (1991) Transcriptional repression of the GLUT4 and C/EBP genes in 3T3-L1 adipocytes by tumor necrosis factor-alpha. J Biol Chem 266 (32), 21 839–21 845. 43. Hofmann, C., Lorenz, K., Braithwaite, S. S., Colca, J. R., Palazuk, B. J., Hotamisligil, G. S. and Spiegelman, B. M. (1994) Altered gene expression for tumor necrosis factoralpha and its receptors during drug and dietary modulation of insulin resistance. Endocrinology 134 (1), 264–270. 44. Mohamed-Ali, V., Goodrick, S., Bulmer, K., Holly, J. M. P., Yudkin, J. S. and Coppack, S. W. (1999) Production of soluble tumor necrosis factor receptors by human subcutaneous adipose tissue in vivo. Am J Physiol Endocrinol Metab 277 (6), E971–E975.

REFERENCES

283

45. Ohsumi, J., Sakakibara, S., Yamaguchi, J., Miyadai, K., Yoshioka, S., Fujiwara, T., Horikoshi, H. and Serizawa, N. (1994) Troglitazone prevents the inhibitory effects of inflammatory cytokines on insulin-induced adipocyte differentiation in 3T3-L1 cells. Endocrinology 135 (5), 2279–2282. 46. Hauner, H., Petruschke, T., Russ, M., Rohrig, K. and Eckel, J. (1995) Effects of tumour necrosis factor alpha (TNF alpha) on glucose transport and lipid metabolism of newlydifferentiated human fat cells in cell culture. Diabetologia 38 (7), 764–771. 47. Stephens, J. M., Lee, J. and Pilch, P. F. (1997) Tumor necrosis factor-alpha-induced insulin resistance in 3T3-L1 adipocytes is accompanied by a loss of insulin receptor substrate-1 and GLUT4 expression without a loss of insulin receptor-mediated signal transduction. J Biol Chem 272 (2), 971–976. 48. Feinstein, R., Kanety, H., Papa, M. Z., Lunenfeld, B. and Karasik, A. (1993) Tumor necrosis factor-alpha suppresses insulin-induced tyrosine phosphorylation of insulin receptor and its substrates. J Biol Chem 268 (35), 26 055–26 058. 49. Hotamisligil, G. S., Murray, D. L., Choy, L. N. and Spiegelman, B. M. (1994) Tumor necrosis factor alpha inhibits signaling from the insulin receptor. Proc Natl Acad Sci USA 91 (11), 4854–4858. 50. Hotamisligil, G. S., Budavari, A., Murray, D. and Spiegelman, B. M. (1994) Reduced tyrosine kinase activity of the insulin receptor in obesity-diabetes. Central role of tumor necrosis factor-alpha. J Clin Invest 94 (4), 1543–1549. 51. Kanety, H., Feinstein, R., Papa, M. Z., Hemi, R. and Karasik, A. (1995) Tumor necrosis factor alpha-induced phosphorylation of insulin receptor substrate-1 (IRS-1). Possible mechanism for suppression of insulin-stimulated tyrosine phosphorylation of IRS-1. J Biol Chem 270 (40), 23 780–23 784. 52. Ahmad, F. and Goldstein, B. J. (1997) Effect of tumor necrosis factor-alpha on the phosphorylation of tyrosine kinase receptors is associated with dynamic alterations in specific protein-tyrosine phosphatases. J Cell Biochem 64 (1), 117–127. 53. Komers, R. and Vrana, A. (1998) Thiazolidinediones – tools for the research of metabolic syndrome X. Physiol Res 47 (4), 215–225. 54. Okuno, A., Tamemoto, H., Tobe, K., Ueki, K., Mori, Y., Iwamoto, K., Umesono, K., Akanuma, Y., Fujiwara, T., Horikoshi, H., Yazaki, Y. and Kadowaki, T. (1998) Troglitazone increases the number of small adipocytes without the change of white adipose tissue mass in obese Zucker rats. J Clin Invest 101 (6), 1354–1361. 55. Peraldi, P., Xu, M. and Spiegelman, B. M. (1997) Thiazolidinediones block tumor necrosis factor-alpha-induced inhibition of insulin signaling. J Clin Invest 100 (7), 1863–1869. 56. Iwata, M., Haruta, T., Usui, I., Takata, Y., Takano, A., Uno, T., Kawahara, J., Ueno, E., Sasaoka, T., Ishibashi, O. and Kobayashi, M. (2001) Pioglitazone ameliorates tumor necrosis factor-alpha-induced insulin resistance by a mechanism independent of adipogenic activity of peroxisome proliferator-activated receptor-gamma. Diabetes 50 (5), 1083–1092. 57. Solomon, S. S., Usdan, L. S. and Palazzolo, M. R. (2001) Mechanisms involved in tumor necrosis factor-alpha induction of insulin resistance and its reversal by thiazolidinedione(s). Am J Med Sci 322 (2), 75–78. 58. Shibasaki, M., Takahashi, K., Itou, T., Bujo, H. and Saito, Y. (2003) A PPAR agonist improves TNF-alpha-induced insulin resistance of adipose tissue in mice. Biochem Biophys Res Commun 309 (2), 419–424. 59. Porat, O. (1989) The effect of tumor necrosis factor alpha on the activity of lipoprotein lipase in adipose tissue. Lymphokine Res 8 (4), 459–469. 60. Kroder, G., Bossenmaier, B., Kellerer, M., Capp, E., Stoyanov, B., Muhlhofer, A., Berti, L., Horikoshi, H., Ullrich, A. and Haring, H. (1996) Tumor necrosis factor-alpha-

284

61.

62.

63.

64.

65.

66.

67. 68.

69.

70.

71.

72.

73.

74.

75.

ADIPOKINES AND INSULIN RESISTANCE

and hyperglycemia-induced insulin resistance. Evidence for different mechanisms and different effects on insulin signaling. J Clin Invest 97 (6), 1471–1477. Ruan, H., Hacohen, N., Golub, T. R., Van Parijs, L. and Lodish, H. F. (2002) Tumor necrosis factor-alpha suppresses adipocyte-specific genes and activates expression of preadipocyte genes in 3T3-L1 adipocytes: nuclear factor-kappaB activation by TNFalpha is obligatory. Diabetes 51 (5), 1319–1336. Ruan, H., Pownall, H. J. and Lodish, H. F. (2003) Troglitazone antagonizes TNF-alphainduced reprogramming of adipocyte gene expression by inhibiting the transcriptional regulatory functions of NF-kB. J Biol Chem 278, 28 181–28 192. Lang, C. H., Dobrescu, C. and Bagby, G. J. (1992) Tumor necrosis factor impairs insulin action on peripheral glucose disposal and hepatic glucose output. Endocrinology 130 (1), 43–52. Nolte, L. A., Hansen, P. A., Chen, M. M., Schluter, J. M., Gulve, E. A. and Holloszy, J. O. (1998) Short-term exposure to tumor necrosis factor-alpha does not affect insulinstimulated glucose uptake in skeletal muscle. Diabetes 47 (5), 721–726. del Aguila, L. F., Claffey, K. P. and Kirwan, J. P. (1999) TNF-alpha impairs insulin signaling and insulin stimulation of glucose uptake in C2C12 muscle cells. Am J Physiol 276 (5 Pt. 1), E849–E855. Halse, R., Pearson, S. L., McCormack, J. G., Yeaman, S. J. and Taylor, R. (2001) Effects of tumor necrosis factor-alpha on insulin action in cultured human muscle cells. Diabetes 50 (5), 1102–1109. Li, Y. P. and Reid, M. B. (2001) Effect of tumor necrosis factor-alpha on skeletal muscle metabolism. Curr Opin Rheumatol 13 (6), 483–487. Yamaguchi, K., Higashiura, K., Ura, N., Murakami, H., Hyakukoku, M., Furuhashi, M. and Shimamoto, K. (2003) The effect of tumor necrosis factor-alpha on tissue specificity and selectivity to insulin signaling. Hypertens Res 26 (5), 389–396. Solomon, S. S., Mishra, S. K., Cwik, C., Rajanna, B. and Postlethwaite, A. E. (1997) Pioglitazone and metformin reverse insulin resistance induced by tumor necrosis factoralpha in liver cells. Horm Metab Res 29 (8), 379–382. Stephens, J. M., Butts, M. D. and Pekala, P. H. (1992) Regulation of transcription factor mRNA accumulation during 3T3-L1 preadipocyte differentiation by tumour necrosis factor-alpha. J Mol Endocrinol 9 (1), 61–72. Fasshauer, M., Klein, J., Lossner, U. and Paschke, R. (2003) Interleukin (IL)-6 mRNA expression is stimulated by insulin, isoproterenol, tumour necrosis factor alpha, growth hormone, and IL-6 in 3T3-L1 adipocytes. Horm Metab Res 35 (3), 147–152. Fasshauer, M., Klein, J., Neumann, S., Eszlinger, M. and Paschke, R. (2001) Tumor necrosis factor alpha is a negative regulator of resistin gene expression and secretion in 3T3-L1 adipocytes. Biochem Biophys Res Commun 288 (4), 1027–1031. Shojima, N., Sakoda, H., Ogihara, T., Fujishiro, M., Katagiri, H., Anai, M., Onishi, Y., Ono, H., Inukai, K., Abe, M., Fukushima, Y., Kikuchi, M., Oka, Y. and Asano, T. (2002) Humoral regulation of resistin expression in 3T3-L1 and mouse adipose cells. Diabetes 51 (6), 1737–1744. Li, Y., Totsune, K., Takeda, K., Furuyama, K., Shibahara, S. and Takahashi, K. (2003) Differential expression of adrenomedullin and resistin in 3T3-L1 adipocytes treated with tumor necrosis factor-alpha. Eur J Endocrinol 149 (3), 231–238. Maeda, N., Takahashi, M., Funahashi, T., Kihara, S., Nishizawa, H., Kishida, K., Nagaretani, H., Matsuda, M., Komuro, R., Ouchi, N., Kuriyama, H., Hotta, K., Nakamura, T., Shimomura, I. and Matsuzawa, Y. (2001) PPARgamma ligands increase expression and plasma concentrations of adiponectin, an adipose-derived protein. Diabetes 50 (9), 2094–2099.

REFERENCES

285

76. Bruun, J. M., Lihn, A. S., Verdich, C., Pedersen, S. B., Toubro, S., Astrup, A. and Richelsen, B. (2003) Regulation of adiponectin by adipose tissue-derived cytokines: in vivo and in vitro investigations in humans. Am J Physiol Endocrinol Metab 285, E527–E533. 77. Kern, P. A., Di Gregorio, G. B., Lu, T., Rassouli, N. and Ranganathan, G. (2003) Adiponectin expression from human adipose tissue: relation to obesity, insulin resistance, and tumor necrosis factor-alpha expression. Diabetes 52 (7), 1779–1785. 78. Zhang, Y., Guo, K. Y., Diaz, P. A., Heo, M. and Leibel, R. L. (2002) Determinants of leptin gene expression in fat depots of lean mice. Am J Physiol Regul Integr Comp Physiol 282 (1), R226–R234. 79. Bullo, M., Garcia-Lorda, P., Peinado-Onsurbe, J., Hernandez, M., Del Castillo, D., Argiles, J. M. and Salas-Salvado, J. (2002) TNFalpha expression of subcutaneous adipose tissue in obese and morbid obese females: relationship to adipocyte LPL activity and leptin synthesis. Int J Obes Relat Metab Disord 26 (5), 652–658. 80. Fawcett, R. L., Waechter, A. S., Williams, L. B., Zhang, P., Louie, R., Jones, R., Inman, M., Huse, J. and Considine, R. V. (2000) Tumor necrosis factor-alpha inhibits leptin production in subcutaneous and omental adipocytes from morbidly obese humans. J Clin Endocrinol Metab 85 (2), 530–535. 81. Molina, A., Vendrell, J., Gutierrez, C., Simon, I., Masdevall, C., Soler, J. and Gomez, J. M. (2003) Insulin resistance, leptin and TNF-alpha system in morbidly obese women after gastric bypass. Obes Surg 13 (4), 615–621. 82. Prins, J. B., Niesler, C. U., Winterford, C. M., Bright, N. A., Siddle, K., O’Rahilly, S., Walker, N. I. and Cameron, D. P. (1997) Tumor necrosis factor-alpha induces apoptosis of human adipose cells. Diabetes 46 (12), 1939–1944. 83. Niesler, C. U., Siddle, K. and Prins, J. B. (1998) Human preadipocytes display a depotspecific susceptibility to apoptosis. Diabetes 47 (8), 1365–1368. 84. Cheung, A. T., Ree, D., Kolls, J. K., Fuselier, J., Coy, D. H. and Bryer-Ash, M. (1998) An in vivo model for elucidation of the mechanism of tumor necrosis factor-alpha (TNF-alpha)-induced insulin resistance: evidence for differential regulation of insulin signaling by TNF-alpha. Endocrinology 139 (12), 4928–4935. 85. Ofei, F., Hurel, S., Newkirk, J., Sopwith, M. and Taylor, R. (1996) Effects of an engineered human anti-TNF-alpha antibody (CDP571) on insulin sensitivity and glycemic control in patients with NIDDM. Diabetes 45 (7), 881–885. 86. Van Snick, J. (1990) Interleukin-6: an overview. Annu Rev Immunol 8, 253–278. 87. Mohamed-Ali, V., Goodrick, S., Rawesh, A., Katz, D. R., Miles, J. M., Yudkin, J. S., Klein, S. and Coppack, S. W. (1997) Subcutaneous adipose tissue releases interleukin6, but not tumor necrosis factor-alpha, in vivo. J Clin Endocrinol Metab 82 (12), 4196–4200. 88. Fried, S. K., Bunkin, D. A. and Greenberg, A. S. (1998) Omental and subcutaneous adipose tissues of obese subjects release interleukin-6: depot difference and regulation by glucocorticoid. J Clin Endocrinol Metab 83 (3), 847–850. 89. Hirano, T., Taga, T., Yamasaki, K., Matsuda, T., Tang, B., Muraguchi, A., Horii, Y., Suematsu, S., Hirata, Y., Yawata, H. et al. (1989) A multifunctional cytokine (IL-6/ BSF-2) and its receptor. Int Arch Allergy Appl Immunol 88 (1–2), 29–33. 90. Taga, T., Hibi, M., Hirata, Y., Yamasaki, K., Yasukawa, K., Matsuda, T., Hirano, T. and Kishimoto, T. (1989) Interleukin-6 triggers the association of its receptor with a possible signal transducer, gp130. Cell 58 (3), 573–581. 91. Kishimoto, T., Hibi, M., Murakami, M., Narazaki, M., Saito, M. and Taga, T. (1992) The molecular biology of interleukin 6 and its receptor. Ciba Found Symp 167, 5–16; discussion 16–23. 92. Kishimoto, T., Akira, S. and Taga, T. (1992) IL-6 receptor and mechanism of signal transduction. Int J Immunopharmacol 14 (3), 431–438.

286

ADIPOKINES AND INSULIN RESISTANCE

93. Mohamed-Ali, V., Flower, L., Sethi, J., Hotamisligil, G., Gray, R., Humphries, S. E., York, D. A. and Pinkney, J. (2001) β-adrenergic regulation of IL-6 release from adipose tissue: in vivo and in vitro studies. J Clin Endocrinol Metab 86 (12), 5864–5869. 94. Bastard, J.-P., Jardel, C., Bruckert, E., Blondy, P., Capeau, J., Laville, M., Vidal, H. and Hainque, B. (2000) Elevated levels of interleukin 6 are reduced in serum and subcutaneous adipose tissue of obese women after weight loss. J Clin Endocrinol Metab 85 (9), 3338–3342. 95. Gallistl, S., Sudi, K. M., Aigner, R. and Borkenstein, M. (2001) Changes in serum interleukin-6 concentrations in obese children and adolescents during a weight reduction program. Int J Obes Relat Metab Disord 25 (11), 1640–1643. 96. Makino, T., Noguchi, Y., Yoshikawa, T., Doi, C. and Nomura, K. (1998) Circulating interleukin 6 concentrations and insulin resistance in patients with cancer. Br J Surg 85 (12), 1658–1662. 97. Monzillo, L. U., Hamdy, O., Horton, E. S., Ledbury, S., Mullooly, C., Jarema, C., Porter, S., Ovalle, K., Moussa, A. and Mantzoros, C. S. (2003) Effect of lifestyle modification on adipokine levels in obese subjects with insulin resistance. Obes Res 11 (9), 1048–1054. 98. Fernandez-Real, J. M., Vayreda, M., Richart, C., Gutierrez, C., Broch, M., Vendrell, J. and Ricart, W. (2001) Circulating interleukin 6 levels, blood pressure, and insulin sensitivity in apparently healthy men and women. J Clin Endocrinol Metab 86 (3), 1154–1159. 99. Nemet, D., Wang, P., Funahashi, T., Matsuzawa, Y., Tanaka, S., Engelman, L. and Cooper, D. M. (2003) Adipocytokines, body composition, and fitness in children. Pediatr Res 53 (1), 148–152. 100. Vozarova, B., Weyer, C., Hanson, K., Tataranni, P. A., Bogardus, C. and Pratley, R. E. (2001) Circulating interleukin-6 in relation to adiposity, insulin action, and insulin secretion. Obes Res 9 (7), 414–417. 101. Bastard, J. P., Maachi, M., Van Nhieu, J. T., Jardel, C., Bruckert, E., Grimaldi, A., Robert, J. J., Capeau, J. and Hainque, B. (2002) Adipose tissue IL-6 content correlates with resistance to insulin activation of glucose uptake both in vivo and in vitro. J Clin Endocrinol Metab 87 (5), 2084–2089. 102. Fernandez-Real, J. M., Broch, M., Vendrell, J., Richart, C. and Ricart, W. (2000) Interleukin-6 gene polymorphism and lipid abnormalities in healthy subjects. J Clin Endocrinol Metab 85 (3), 1334–1339. 103. Fernandez-Real, J. M., Broch, M., Vendrell, J., Gutierrez, C., Casamitjana, R., Pugeat, M., Richart, C. and Ricart, W. (2000) Interleukin-6 gene polymorphism and insulin sensitivity. Diabetes 49 (3), 517–520. 104. Vozarova, B., Fernandez-Real, J. M., Knowler, W. C., Gallart, L., Hanson, R. L., Gruber, J. D., Ricart, W., Vendrell, J., Richart, C., Tataranni, P. A. and Wolford, J. K. (2003) The interleukin-6 (-174) G/C promoter polymorphism is associated with type2 diabetes mellitus in Native Americans and Caucasians. Hum Genet 112 (4), 409–413. 105. Pickup, J., Chusney, G., Thomas, S. and Burt, D. (2000) Plasma interleukin-6, tumour necrosis factor alpha and blood cytokine production in type 2 diabetes. Life Sci 67 (3), 291–300. 106. Kern, P. A., Ranganathan, S., Li, C., Wood, L. and Ranganathan, G. (2001) Adipose tissue tumor necrosis factor and interleukin-6 expression in human obesity and insulin resistance. Am J Physiol Endocrinol Metab 280 (5), E745–E751. 107. Rotter, V., Nagaev, I. and Smith, U. (2003) Interleukin-6 (IL-6) induces insulin resistance in 3T3-L1 adipocytes and is, like IL-8 and TNFalpha, overexpressed in human fat cells from insulin-resistant subjects. J Biol Chem 278, 45 777–45 784.

REFERENCES

287

108. Stouthard, J. M., Oude Elferink, R. P. and Sauerwein, H. P. (1996) Interleukin-6 enhances glucose transport in 3T3-L1 adipocytes. Biochem Biophys Res Commun 220 (2), 241–245. 109. Huppertz, C., Schwartz, C., Becker, W., Horn, F., Heinrich, P. C. and Joost, H. G. (1996) Comparison of the effects of insulin, PDGF, interleukin-6, and interferon-gamma on glucose transport in 3T3-L1 cells: lack of cross-talk between tyrosine kinase receptors and JAK/STAT pathways. Diabetologia 39 (12), 1432–1439. 110. Steensberg, A., Fischer, C. P., Sacchetti, M., Keller, C., Osada, T., Schjerling, P., van Hall, G., Febbraio, M. A. and Pedersen, B. K. (2003) Acute interleukin-6 administration does not impair muscle glucose uptake or whole-body glucose disposal in healthy humans. J Physiol 548, 631–638. 111. Senn, J. J., Klover, P. J., Nowak, I. A. and Mooney, R. A. (2002) Interleukin-6 induces cellular insulin resistance in hepatocytes. Diabetes 51 (12), 3391–3399. 112. Kaser, S., Kaser, A., Sandhofer, A., Ebenbichler, C. F., Tilg, H. and Patsch, J. R. (2003) Resistin messenger-RNA expression is increased by proinflammatory cytokines in vitro. Biochem Biophys Res Commun 309 (2), 286–290. 113. Engeli, S., Feldpausch, M., Gorzelniak, K., Hartwig, F., Heintze, U., Janke, J., Mohlig, M., Pfeiffer, A. F., Luft, F. C. and Sharma, A. M. (2003) Association between adiponectin and mediators of inflammation in obese women. Diabetes 52 (4), 942– 947. 114. Fasshauer, M., Kralisch, S., Klier, M., Lossner, U., Bluher, M., Klein, J. and Paschke, R. (2003) Adiponectin gene expression and secretion is inhibited by interleukin-6 in 3T3-L1 adipocytes. Biochem Biophys Res Commun 301 (4), 1045–1050. 115. Path, G., Bornstein, S. R., Gurniak, M., Chrousos, G. P., Scherbaum, W. A. and Hauner, H. (2001) Human breast adipocytes express interleukin-6 (IL-6) and its receptor system: increased IL-6 production by beta-adrenergic activation and effects of IL-6 on adipocyte function. J Clin Endocrinol Metab 86 (5), 2281–2288. 116. Lyngso, D., Simonsen, L. and Bulow, J. (2002) Metabolic effects of interleukin-6 in human splanchnic and adipose tissue. J Physiol 543 (Pt. 1), 379–386. 117. Feingold, K. R., Doerrler, W., Dinarello, C. A., Fiers, W. and Grunfeld, C. (1992) Stimulation of lipolysis in cultured fat cells by tumor necrosis factor, interleukin-1, and the interferons is blocked by inhibition of prostaglandin synthesis. Endocrinology 130 (1), 10–16. 118. Orban, Z., Remaley, A. T., Sampson, M., Trajanoski, Z. and Chrousos, G. P. (1999) The differential effect of food intake and beta-adrenergic stimulation on adipose-derived hormones and cytokines in man. J Clin Endocrinol Metab 84 (6), 2126–2133. 119. Mattacks, C. A. and Pond, C. M. (1999) Interactions of noradrenalin and tumour necrosis factor alpha, interleukin 4 and interleukin 6 in the control of lipolysis from adipocytes around lymph nodes. Cytokine 11 (5), 334–346. 120. Pedersen, B. K., Osturwski, K., Rohde, T. and Brnunsgaard, H. (1998) The cytokine response to strenuous exercise. Can J Physiol Pharmacol 76, 505–511. 121. Stouthard, J. M., Romijn, J. A., Van der Poll, T., Endert, E., Klein, S., Bakker, P. J., Veenhof, C. H. and Sauerwein, H. P. (1995) Endocrinologic and metabolic effects of interleukin-6 in humans. Am J Physiol 268 (5 Pt. 1), E813–E819. 122. Metzger, S., Hassin, T., Barash, V., Pappo, O. and Chajek-Shaul, T. (2001) Reduced body fat and increased hepatic lipid synthesis in mice bearing interleukin-6-secreting tumor. Am J Physiol Endocrinol Metab 281 (5), E957–E965. 123. Tsigos, C., Papanicolaou, D. A., Kyrou, I., Defensor, R., Mitsiadis, C. S. and Chrousos, G. P. (1997) Dose-dependent effects of recombinant human interleukin-6 on glucose regulation. J Clin Endocrinol Metab 82 (12), 4167–4170.

288

ADIPOKINES AND INSULIN RESISTANCE

124. Steensberg, A., van Hall, G., Osada, T., Sacchetti, M., Saltin, B. and Klarlund Pedersen, B. (2000) Production of interleukin-6 in contracting human skeletal muscles can account for the exercise-induced increase in plasma interleukin-6. J Physiol 529 Pt 1, 237–242. 125. Pedersen, B. K., Steensberg, A., Keller, P., Keller, C., Fischer, C., Hiscock, N., Van Hall, G., Plomgaard, P. and Febbraio, M. A. (2003) Muscle-derived interleukin-6: lipolytic, anti-inflammatory and immune regulatory effects. Pflugers Arch 446 (1), 9–16. 126. Wallenius, K., Wallenius, V., Sunter, D., Dickson, S. L. and Jansson, J. O. (2002) Intracerebroventricular interleukin-6 treatment decreases body fat in rats. Biochem Biophys Res Commun 293 (1), 560–565. 127. Jansson, J. O., Wallenius, K., Wernstedt, I., Ohlsson, C., Dickson, S. L. and Wallenius, V. (2003) On the site and mechanism of action of the anti-obesity effects of interleukin-6. Growth Horm IGF Res 13 (Suppl.), S28–S32. 128. Wallenius, V., Wallenius, K., Ahren, B., Rudling, M., Carlsten, H., Dickson, S. L., Ohlsson, C. and Jansson, J. O. (2002) Interleukin-6-deficient mice develop mature-onset obesity. Nat Med 8 (1), 75–79. 129. Zhang, Y., Proenca, R., Maffei, M., Barone, M., Leopold, L. and Friedman, J. M. (1994) Positional cloning of the mouse obese gene and its human homologue. Nature 372 (6505), 425–432. 130. Altmann, S. W., Timans, J. C., Rock, F. L., Bazan, J. F. and Kastelein, R. A. (1995) Expression and purification of a synthetic human obese gene product. Protein Expr Purif 6 (6), 722–726. 131. Halaas, J. L., Gajiwala, K. S., Maffei, M., Cohen, S. L., Chait, B. T., Rabinowitz, D., Lallone, R. L., Burley, S. K. and Friedman, J. M. (1995) Weight-reducing effects of the plasma protein encoded by the obese gene. Science 269 (5223), 543–546. 132. Veniant, M. M. and LeBel, C. P. (2003) Leptin: from animals to humans. Curr Pharm Des 9 (10), 811–818. 133. Frederich, R. C., Hamann, A., Anderson, S., Lollmann, B., Lowell, B. B. and Flier, J. S. (1995) Leptin levels reflect body lipid content in mice: evidence for diet-induced resistance to leptin action. Nat Med 1 (12), 1311–1314. 134. Hube, F., Lietz, U., Igel, M., Jensen, P. B., Tornqvist, H., Joost, H. G. and Hauner, H. (1996) Difference in leptin mRNA levels between omental and subcutaneous abdominal adipose tissue from obese humans. Horm Metab Res 28 (12), 690–693. 135. Montague, C. T., Prins, J. B., Sanders, L., Digby, J. E. and O’Rahilly, S. (1997) Depotand sex-specific differences in human leptin mRNA expression: implications for the control of regional fat distribution. Diabetes 46 (3), 342–347. 136. Van Harmelen, V., Reynisdottir, S., Eriksson, P., Thorne, A., Hoffstedt, J., Lonnqvist, F. and Arner, P. (1998) Leptin secretion from subcutaneous and visceral adipose tissue in women. Diabetes 47 (6), 913–917. 137. Zimmet, P., Hodge, A., Nicolson, M., Staten, M., de Courten, M., Moore, J., Morawiecki, A., Lubina, J., Collier, G., Alberti, G. and Dowse, G. (1996) Serum leptin concentration, obesity, and insulin resistance in Western Samoans: cross sectional study. BMJ 313 (7063), 965–969. 138. Tartaglia, L. A., Dembski, M., Weng, X., Deng, N., Culpepper, J., Devos, R., Richards, G. J., Campfield, L. A., Clark, F. T., Deeds, J. and et al. (1995) Identification and expression cloning of a leptin receptor, OB-R. Cell 83 (7), 1263–1271. 139. Baumann, H., Morella, K. K., White, D. W., Dembski, M., Bailon, P. S., Kim, H., Lai, C. F. and Tartaglia, L. A. (1996) The full-length leptin receptor has signaling capabilities of interleukin 6-type cytokine receptors. Proc Natl Acad Sci USA 93 (16), 8374–8378.

REFERENCES

289

140. White, D. W. and Tartaglia, L. A. (1996) Leptin and OB-R: body weight regulation by a cytokine receptor. Cytokine Growth Factor Rev 7 (4), 303–309. 141. Leibel, R. L. (2002) The role of leptin in the control of body weight. Nutr Rev 60 (10 Pt. 2), S15–S19; discussion S68–S84, S85–S87. 142. Mistry, A. M., Swick, A. G. and Romsos, D. R. (1997) Leptin rapidly lowers food intake and elevates metabolic rates in lean and ob/ob mice. J Nutr 127 (10), 2065–2072. 143. Margetic, S., Gazzola, C., Pegg, G. G. and Hill, R. A. (2002) Leptin: a review of its peripheral actions and interactions. Int J Obes Relat Metab Disord 26 (11), 1407–1433. 144. MacDougald, O. A., Hwang, C. S., Fan, H. and Lane, M. D. (1995) Regulated expression of the obese gene product (leptin) in white adipose tissue and 3T3-L1 adipocytes. Proc Natl Acad Sci USA 92 (20), 9034–9037. 145. Rentsch, J. and Chiesi, M. (1996) Regulation of ob gene mRNA levels in cultured adipocytes. FEBS Lett 379 (1), 55–59. 146. Barr, V. A., Malide, D., Zarnowski, M. J., Taylor, S. I. and Cushman, S. W. (1997) Insulin stimulates both leptin secretion and production by rat white adipose tissue. Endocrinology 138 (10), 4463–4472. 147. Mohamed-Ali, V., Pinkney, J. H., Panahloo, A., Goodrick, S., Coppack, S. W. and Yudkin, J. S. (1997) Relationships between plasma leptin and insulin concentrations, but not insulin resistance, in non-insulin-dependent (type 2) diabetes mellitus. Diabet Med 14 (5), 376–380. 148. Haffner, S. M., Mykkanen, L., Rainwater, D. L., Karhapaa, P. and Laakso, M. (1999) Is leptin concentration associated with the insulin resistance syndrome in nondiabetic men? Obes Res 7 (2), 164–169. 149. Donahue, R. P., Prineas, R. J., Donahue, R. D., Zimmet, P., Bean, J. A., De Courten, M., Collier, G., Goldberg, R. B., Skyler, J. S. and Schneiderman, N. (1999) Is fasting leptin associated with insulin resistance among nondiabetic individuals? The Miami Community Health Study. Diabetes Care 22 (7), 1092–1096. 150. Chu, N. F., Wang, D. J., Shieh, S. M. and Rimm, E. B. (2000) Plasma leptin concentrations and obesity in relation to insulin resistance syndrome components among school children in Taiwan – The Taipei Children Heart Study. Int J Obes Relat Metab Disord 24 (10), 1265–1271. 151. Chu, N. F., Chang, J. B. and Shieh, S. M. (2003) Plasma leptin, fatty acids, and tumor necrosis factor-receptor and insulin resistance in children. Obes Res 11 (4), 532–540. 152. De Vos, P., Lefebvre, A. M., Miller, S. G., Guerre-Millo, M., Wong, K., Saladin, R., Hamann, L. G., Staels, B., Briggs, M. R. and Auwerx, J. (1996) Thiazolidinediones repress ob gene expression in rodents via activation of peroxisome proliferator-activated receptor gamma. J Clin Invest 98 (4), 1004–1009. 153. Kallen, C. B. and Lazar, M. A. (1996) Antidiabetic thiazolidinediones inhibit leptin (ob) gene expression in 3T3-L1 adipocytes. Proc Natl Acad Sci USA 93 (12), 5793–5796. 154. Nolan, J. J., Olefsky, J. M., Nyce, M. R., Considine, R. V. and Caro, J. F. (1996) Effect of troglitazone on leptin production. Studies in vitro and in human subjects. Diabetes 45 (9), 1276–1278. 155. Williams, L. B., Fawcett, R. L., Waechter, A. S., Zhang, P., Kogon, B. E., Jones, R., Inman, M., Huse, J. and Considine, R. V. (2000) Leptin production in adipocytes from morbidly obese subjects: stimulation by dexamethasone, inhibition with troglitazone, and influence of gender. J Clin Endocrinol Metab 85 (8), 2678–2684. 156. Walder, K., Filippis, A., Clark, S., Zimmet, P. and Collier, G. R. (1997) Leptin inhibits insulin binding in isolated rat adipocytes. J Endocrinol 155 (3), R5–R7. 157. Ceddia, R. B., William, W. N., Jr., Lima, F. B. and Curi, R. (1998) Leptin inhibits insulin-stimulated incorporation of glucose into lipids and stimulates glucose decarboxylation in isolated rat adipocytes. J Endocrinol 158 (3), R7–R9.

290

ADIPOKINES AND INSULIN RESISTANCE

158. Zhang, H. H., Kumar, S., Barnett, A. H. and Eggo, M. C. (1999) Intrinsic site-specific differences in the expression of leptin in human adipocytes and its autocrine effects on glucose uptake. J Clin Endocrinol Metab 84 (7), 2550–2556. 159. Ranganathan, S., Ciaraldi, T. P., Henry, R. R., Mudaliar, S. and Kern, P. A. (1998) Lack of effect of leptin on glucose transport, lipoprotein lipase, and insulin action in adipose and muscle cells. Endocrinology 139 (5), 2509–2513. 160. Zierath, J. R., Frevert, E. U., Ryder, J. W., Berggren, P. O. and Kahn, B. B. (1998) Evidence against a direct effect of leptin on glucose transport in skeletal muscle and adipocytes. Diabetes 47 (1), 1–4. 161. Aprath-Husmann, I., Rohrig, K., Gottschling-Zeller, H., Skurk, T., Scriba, D., Birgel, M. and Hauner, H. (2001) Effects of leptin on the differentiation and metabolism of human adipocytes. Int J Obes Relat Metab Disord 25 (10), 1465–1470. 162. Ceddia, R. B., William, W. N., Jr., and Curi, R. (1998) Leptin increases glucose transport and utilization in skeletal muscle in vitro. Gen Pharmacol 31 (5), 799–801. 163. Ceddia, R. B., William, W. N., Jr., and Curi, R. (1999) Comparing effects of leptin and insulin on glucose metabolism in skeletal muscle: evidence for an effect of leptin on glucose uptake and decarboxylation. Int J Obes Relat Metab Disord 23 (1), 75–82. 164. Harris, R. B. (1998) Acute and chronic effects of leptin on glucose utilization in lean mice. Biochem Biophys Res Commun 245 (2), 502–509. 165. Berti, L., Kellerer, M., Capp, E. and Haring, H. U. (1997) Leptin stimulates glucose transport and glycogen synthesis in C2C12 myotubes: evidence for a P13-kinase mediated effect. Diabetologia 40 (5), 606–609. 166. Furnsinn, C., Brunmair, B., Furtmuller, R., Roden, M., Englisch, R. and Waldhausl, W. (1998) Failure of leptin to affect basal and insulin-stimulated glucose metabolism of rat skeletal muscle in vitro. Diabetologia 41 (5), 524–529. 167. Ishizuka, T., Ernsberger, P., Liu, S., Bedol, D., Lehman, T. M., Koletsky, R. J. and Friedman, J. E. (1998) Phenotypic consequences of a nonsense mutation in the leptin receptor gene (fak) in obese spontaneously hypertensive Koletsky rats (SHROB). J Nutr 128 (12), 2299–2306. 168. Liu, Y. L., Emilsson, V. and Cawthorne, M. A. (1997) Leptin inhibits glycogen synthesis in the isolated soleus muscle of obese (ob/ob) mice. FEBS Lett 411 (2–3), 351–355. 169. Muoio, D. M., Dohm, G. L., Fiedorek, F. T., Jr., Tapscott, E. B., Coleman, R. A. and Dohn, G. L. (1997) Leptin directly alters lipid partitioning in skeletal muscle. Diabetes 46 (8), 1360–1363. 170. Muoio, D. M., Dohm, G. L., Tapscott, E. B. and Coleman, R. A. (1999) Leptin opposes insulin’s effects on fatty acid partitioning in muscles isolated from obese ob/ob mice. Am J Physiol 276 (5 Pt 1), E913–E921. 171. Nemecz, M., Preininger, K., Englisch, R., Furnsinn, C., Schneider, B., Waldhausl, W. and Roden, M. (1999) Acute effect of leptin on hepatic glycogenolysis and gluconeogenesis in perfused rat liver. Hepatology 29 (1), 166–172. 172. Ceddia, R. B., Lopes, G., Souza, H. M., Borba-Murad, G. R., William, W. N., Jr., Bazotte, R. B. and Curi, R. (1999) Acute effects of leptin on glucose metabolism of in situ rat perfused livers and isolated hepatocytes. Int J Obes Relat Metab Disord 23 (11), 1207–1212. 173. Cohen, S. M., Werrmann, J. G. and Tota, M. R. (1998) 13C NMR study of the effects of leptin treatment on kinetics of hepatic intermediary metabolism. Proc Natl Acad Sci USA 95 (13), 7385–7390. 174. Fehmann, H. C., Berghofer, P., Brandhorst, D., Brandhorst, H., Hering, B., Bretzel, R. G. and Goke, B. (1997) Leptin inhibition of insulin secretion from isolated human islets. Acta Diabetol 34 (4), 249–252.

REFERENCES

291

175. Fehmann, H. C., Peiser, C., Bode, H. P., Stamm, M., Staats, P., Hedetoft, C., Lang, R. E. and Goke, B. (1997) Leptin: a potent inhibitor of insulin secretion. Peptides 18 (8), 1267–1273. 176. Tanizawa, Y., Okuya, S., Ishihara, H., Asano, T., Yada, T. and Oka, Y. (1997) Direct stimulation of basal insulin secretion by physiological concentrations of leptin in pancreatic beta cells. Endocrinology 138 (10), 4513–4516. 177. Ookuma, M., Ookuma, K. and York, D. A. (1998) Effects of leptin on insulin secretion from isolated rat pancreatic islets. Diabetes 47 (2), 219–223. 178. Ceddia, R. B., William, W. N., Jr., Carpinelli, A. R. and Curi, R. (1999) Modulation of insulin secretion by leptin. Gen Pharmacol 32 (2), 233–237. 179. Seufert, J., Kieffer, T. J. and Habener, J. F. (1999) Leptin inhibits insulin gene transcription and reverses hyperinsulinemia in leptin-deficient ob/ob mice. Proc Natl Acad Sci USA 96 (2), 674–679. 180. Seufert, J., Kieffer, T. J., Leech, C. A., Holz, G. G., Moritz, W., Ricordi, C. and Habener, J. F. (1999) Leptin suppression of insulin secretion and gene expression in human pancreatic islets: implications for the development of adipogenic diabetes mellitus. J Clin Endocrinol Metab 84 (2), 670–676. 181. Widdowson, P. S., Upton, R., Pickavance, L., Buckingham, R., Tadayyon, M., Arch, J. and Williams, G. (1998) Acute hyperleptinemia does not modify insulin sensitivity in vivo in the rat. Horm Metab Res 30 (5), 259–262. 182. da Silva Xavier, G., Leclerc, I., Salt, I. P., Doiron, B., Hardie, D. G., Kahn, A. and Rutter, G. A. (2000) Role of AMP-activated protein kinase in the regulation by glucose of islet beta cell gene expression. Proc Natl Acad Sci USA 97 (8), 4023–4028. 183. Atkinson, L. L., Fischer, M. A. and Lopaschuk, G. D. (2002) Leptin activates cardiac fatty acid oxidation independent of changes in the AMP-activated protein kinase-acetylCoA carboxylase-malonyl-CoA axis. J Biol Chem 277 (33), 29 424–29 430. 184. Minokoshi, Y., Kim, Y. B., Peroni, O. D., Fryer, L. G., Muller, C., Carling, D. and Kahn, B. B. (2002) Leptin stimulates fatty-acid oxidation by activating AMP-activated protein kinase. Nature 415 (6869), 339–343. 185. Hardie, D. G. and Pan, D. A. (2002) Regulation of fatty acid synthesis and oxidation by the AMP-activated protein kinase. Biochem Soc Trans 30 (Pt. 6), 1064–1070. 186. Foretz, M., Carling, D., Guichard, C., Ferre, P. and Foufelle, F. (1998) AMP-activated protein kinase inhibits the glucose-activated expression of fatty acid synthase gene in rat hepatocytes. J Biol Chem 273 (24), 14 767–14 771. 187. Hardie, D. G. (1989) Regulation of fatty acid synthesis via phosphorylation of acetylCoA carboxylase. Prog Lipid Res 28 (2), 117–146. 188. McGarry, J. D. and Brown, N. F. (1997) The mitochondrial carnitine palmitoyltransferase system. From concept to molecular analysis. Eur J Biochem 244 (1), 1–14. 189. Park, H., Kaushik, V. K., Constant, S., Prentki, M., Przybytkowski, E., Ruderman, N. B. and Saha, A. K. (2002) Coordinate regulation of malonyl-CoA decarboxylase, sn-glycerol-3-phosphate acyltransferase, and acetyl-CoA carboxylase by AMP-activated protein kinase in rat tissues in response to exercise. J Biol Chem 277 (36), 32 571–32 577. 190. Jeukendrup, A. E. (2002) Regulation of fat metabolism in skeletal muscle. Ann NY Acad Sci 967, 217–235. 191. Winder, W. W. (2001) Energy-sensing and signaling by AMP-activated protein kinase in skeletal muscle. J Appl Physiol 91 (3), 1017–1028. 192. Vo, N. and Goodman, R. H. (2001) CREB-binding protein and p300 in transcriptional regulation. J Biol Chem 276 (17), 13 505–13 508. 193. Gelman, L., Zhou, G., Fajas, L., Raspe, E., Fruchart, J. C. and Auwerx, J. (1999) p300 interacts with the N- and C-terminal part of PPARgamma2 in a ligand-independent and -dependent manner, respectively. J Biol Chem 274 (12), 7681–7688.

292

ADIPOKINES AND INSULIN RESISTANCE

194. Kim, J. B., Sarraf, P., Wright, M., Yao, K. M., Mueller, E., Solanes, G., Lowell, B. B. and Spiegelman, B. M. (1998) Nutritional and insulin regulation of fatty acid synthetase and leptin gene expression through ADD1/SREBP1. J Clin Invest 101 (1), 1–9. 195. Seo, J. B., Noh, M. J., Yoo, E. J., Park, S. Y., Park, J., Lee, I. K., Park, S. D. and Kim, J. B. (2003) Functional characterization of the human resistin promoter with adipocyte determination- and differentiation-dependent factor 1/sterol regulatory element binding protein 1c and CCAAT enhancer binding protein-alpha. Mol Endocrinol 17 (8), 1522–1533. 196. Ceddia, R. B., Koistinen, H. A., Zierath, J. R. and Sweeney, G. (2002) Analysis of paradoxical observations on the association between leptin and insulin resistance. FASEB J 16 (10), 1163–1176. 197. Batt, R. and Mialhe, P. (1966) Insulin resistance of the inherently obese mouse – obob. Nature 212 (59), 289–290. 198. Weigle, D. S., Bukowski, T. R., Foster, D. C., Holderman, S., Kramer, J. M., Lasser, G., Lofton-Day, C. E., Prunkard, D. E., Raymond, C. and Kuijper, J. L. (1995) Recombinant ob protein reduces feeding and body weight in the ob/ob mouse. J Clin Invest 96 (4), 2065–2070. 199. Shimomura, I., Hammer, R. E., Ikemoto, S., Brown, M. S. and Goldstein, J. L. (1999) Leptin reverses insulin resistance and diabetes mellitus in mice with congenital lipodystrophy. Nature 401 (6748), 73–76. 200. Wang, J., Obici, S., Morgan, K., Barzilai, N., Feng, Z. and Rossetti, L. (2001) Overfeeding rapidly induces leptin and insulin resistance. Diabetes 50 (12), 2786–2791. 201. Cupples, W. A. (2003) Addressing leptin resistance. Am J Physiol Regul Integr Comp Physiol 284 (1), R86. 202. Steppan, C. M., Bailey, S. T., Bhat, S., Brown, E. J., Banerjee, R. R., Wright, C. M., Patel, H. R., Ahima, R. S. and Lazar, M. A. (2001) The hormone resistin links obesity to diabetes. Nature 409 (6818), 307–312. 203. Vidal-Puig, A. and O’Rahilly, S. (2001) Resistin: a new link between obesity and insulin resistance? Clin Endocrinol (Oxf) 55 (4), 437–438. 204. Steppan, C. M., Brown, E. J., Wright, C. M., Bhat, S., Banerjee, R. R., Dai, C. Y., Enders, G. H., Silberg, D. G., Wen, X., Wu, G. D. and Lazar, M. A. (2001) A family of tissue-specific resistin-like molecules. Proc Natl Acad Sci USA 98 (2), 502–506. 205. Haugen, F., Jorgensen, A., Drevon, C. A. and Trayhurn, P. (2001) Inhibition by insulin of resistin gene expression in 3T3-L1 adipocytes. FEBS Lett 507 (1), 105–108. 206. Juan, C. C., Au, L. C., Fang, V. S., Kang, S. F., Ko, Y. H., Kuo, S. F., Hsu, Y. P., Kwok, C. F. and Ho, L. T. (2001) Suppressed gene expression of adipocyte resistin in an insulin-resistant rat model probably by elevated free fatty acids. Biochem Biophys Res Commun 289 (5), 1328–1333. 207. Way, J. M., Gorgun, C. Z., Tong, Q., Uysal, K. T., Brown, K. K., Harrington, W. W., Oliver, W. R., Jr., Willson, T. M., Kliewer, S. A. and Hotamisligil, G. S. (2001) Adipose tissue resistin expression is severely suppressed in obesity and stimulated by peroxisome proliferator-activated receptor gamma agonists. J Biol Chem 276 (28), 25 651–25 653. 208. Fukui, Y. and Motojima, K. (2002) Expression of resistin in the adipose tissue is modulated by various factors including peroxisome proliferator-activated receptor alpha. Diabetes Obes Metab 4 (5), 342–345. 209. Maebuchi, M., Machidori, M., Urade, R., Ogawa, T. and Moriyama, T. (2003) Low resistin levels in adipose tissues and serum in high-fat fed mice and genetically obese mice: development of an ELISA system for quantification of resistin. Arch Biochem Biophys 416 (2), 164–170.

REFERENCES

293

210. Yang, R. Z., Huang, Q., Xu, A., McLenithan, J. C., Eison, J. A., Shuldiner, A. R., Alkan, S. and Gong da, W. (2003) Comparative studies of resistin expression and phylogenomics in human and mouse. Biochem Biophys Res Commun 310 (3), 927–935. 211. Fain, J. N., Cheema, P. S., Bahouth, S. W. and Lloyd Hiler, M. (2003) Resistin release by human adipose tissue explants in primary culture. Biochem Biophys Res Commun 300 (3), 674–678. 212. McTernan, P. G., McTernan, C. L., Chetty, R., Jenner, K., Fisher, F. M., Lauer, M. N., Crocker, J., Barnett, A. H. and Kumar, S. (2002) Increased resistin gene and protein expression in human abdominal adipose tissue. J Clin Endocrinol Metab 87 (5), 2407. 213. Savage, D. B., Sewter, C. P., Klenk, E. S., Segal, D. G., Vidal-Puig, A., Considine, R. V. and S. O. R. (2001) Resistin/Fizz3 expression in relation to obesity and peroxisome proliferator-activated receptor-gamma action in humans. Diabetes 50 (10), 2199–2202. 214. Silha, J. V., Krsek, M., Skrha, J. V., Sucharda, P., Nyomba, B. L. and Murphy, L. J. (2003) Plasma resistin, adiponectin and leptin levels in lean and obese subjects: correlations with insulin resistance. Eur J Endocrinol 149 (4), 331–335. 215. Janke, J., Engeli, S., Gorzelniak, K., Luft, F. C. and Sharma, A. M. (2002) Resistin gene expression in human adipocytes is not related to insulin resistance. Obes Res 10 (1), 1–5. 216. Furuhashi, M., Ura, N., Higashiura, K., Murakami, H. and Shimamoto, K. (2003) Circulating resistin levels in essential hypertension. Clin Endocrinol (Oxf) 59 (4), 507–510. 217. Lee, J. H., Chan, J. L., Yiannakouris, N., Kontogianni, M., Estrada, E., Seip, R., Orlova, C. and Mantzoros, C. S. (2003) Circulating resistin levels are not associated with obesity or insulin resistance in humans and are not regulated by fasting or leptin administration: cross-sectional and interventional studies in normal, insulin-resistant, and diabetic subjects. J Clin Endocrinol Metab 88 (10), 4848–4856. 218. Azuma, K., Katsukawa, F., Oguchi, S., Murata, M., Yamazaki, H., Shimada, A. and Saruta, T. (2003) Correlation between serum resistin level and adiposity in obese individuals. Obes Res 11 (8), 997–1001. 219. Minn, A. H., Patterson, N. B., Pack, S., Hoffmann, S. C., Gavrilova, O., Vinson, C., Harlan, D. M. and Shalev, A. (2003) Resistin is expressed in pancreatic islets. Biochem Biophys Res Commun 310 (2), 641–645. 220. Patel, L., Buckels, A. C., Kinghorn, I. J., Murdock, P. R., Holbrook, J. D., Plumpton, C., Macphee, C. H. and Smith, S. A. (2003) Resistin is expressed in human macrophages and directly regulated by PPARgamma activators. Biochem Biophys Res Commun 300 (2), 472–476. 221. Yura, S., Sagawa, N., Itoh, H., Kakui, K., Nuamah, M. A., Korita, D., Takemura, M. and Fujii, S. (2003) Resistin is expressed in the human placenta. J Clin Endocrinol Metab 88 (3), 1394–1397. 222. Scherer, P. E., Williams, S., Fogliano, M., Baldini, G. and Lodish, H. F. (1995) A novel serum protein similar to C1q, produced exclusively in adipocytes. J Biol Chem 270 (45), 26 746–26 749. 223. Shapiro, L. and Scherer, P. E. (1998) The crystal structure of a complement-1q family protein suggests an evolutionary link to tumor necrosis factor. Curr Biol 8 (6), 335–338. 224. Yamauchi, T., Kamon, J., Ito, Y., Tsuchida, A., Yokomizo, T., Kita, S., Sugiyama, T., Miyagishi, M., Hara, K., Tsunoda, M., Murakami, K., Ohteki, T., Uchida, S., Takekawa, S., Waki, H., Tsuno, N. H., Shibata, Y., Terauchi, Y., Froguel, P., Tobe, K., Koyasu, S., Taira, K., Kitamura, T., Shimizu, T., Nagai, R. and Kadowaki, T. (2003) Cloning of adiponectin receptors that mediate antidiabetic metabolic effects. Nature 423 (6941), 762–769.

294

ADIPOKINES AND INSULIN RESISTANCE

225. Hu, E., Liang, P. and Spiegelman, B. M. (1996) AdipoQ is a novel adipose-specific gene dysregulated in obesity. J Biol Chem 271 (18), 10 697–10 703. 226. Matsubara, M., Maruoka, S. and Katayose, S. (2002) Inverse relationship between plasma adiponectin and leptin concentrations in normal-weight and obese women. Eur J Endocrinol 147 (2), 173–180. 227. Milan, G., Granzotto, M., Scarda, A., Calcagno, A., Pagano, C., Federspil, G. and Vettor, R. (2002) Resistin and adiponectin expression in visceral fat of obese rats: effect of weight loss. Obes Res 10 (11), 1095–1103. 228. Stefan, N., Bunt, J. C., Salbe, A. D., Funahashi, T., Matsuzawa, Y. and Tataranni, P. A. (2002) Plasma adiponectin concentrations in children: relationships with obesity and insulinemia. J Clin Endocrinol Metab 87 (10), 4652–4656. 229. Yang, W. S., Lee, W. J., Funahashi, T., Tanaka, S., Matsuzawa, Y., Chao, C. L., Chen, C. L., Tai, T. Y. and Chuang, L. M. (2002) Plasma adiponectin levels in overweight and obese Asians. Obes Res 10 (11), 1104–1110. 230. Yamauchi, T., Kamon, J., Waki, H., Murakami, K., Motojima, K., Komeda, K., Ide, T., Kubota, N., Terauchi, Y., Tobe, K., Miki, H., Tsuchida, A., Akanuma, Y., Nagai, R., Kimura, S. and Kadowaki, T. (2001) The mechanisms by which both heterozygous peroxisome proliferator-activated receptor gamma (PPARgamma) deficiency and PPARgamma agonist improve insulin resistance. J Biol Chem 276 (44), 41 245–41 254. 231. Combs, T. P., Wagner, J. A., Berger, J., Doebber, T., Wang, W. J., Zhang, B. B., Tanen, M., Berg, A. H., O’Rahilly, S., Savage, D. B., Chatterjee, K., Weiss, S., Larson, P. J., Gottesdiener, K. M., Gertz, B. J., Charron, M. J., Scherer, P. E. and Moller, D. E. (2002) Induction of adipocyte complement-related protein of 30 kilodaltons by PPARgamma agonists: a potential mechanism of insulin sensitization. Endocrinology 143 (3), 998–1007. 232. Hirose, H., Kawai, T., Yamamoto, Y., Taniyama, M., Tomita, M., Matsubara, K., Okazaki, Y., Ishii, T., Oguma, Y., Takei, I. and Saruta, T. (2002) Effects of pioglitazone on metabolic parameters, body fat distribution, and serum adiponectin levels in Japanese male patients with type 2 diabetes. Metabolism 51 (3), 314–317. 233. Gustafson, B., Jack, M. M., Cushman, S. W. and Smith, U. (2003) Adiponectin gene activation by thiazolidinediones requires PPARgamma2, but not C/EBPalpha-evidence for differential regulation of the aP2 and adiponectin genes. Biochem Biophys Res Commun 308 (4), 933–939. 234. Maeda, N., Shimomura, I., Kishida, K., Nishizawa, H., Matsuda, M., Nagaretani, H., Furuyama, N., Kondo, H., Takahashi, M., Arita, Y., Komuro, R., Ouchi, N., Kihara, S., Tochino, Y., Okutomi, K., Horie, M., Takeda, S., Aoyama, T., Funahashi, T. and Matsuzawa, Y. (2002) Diet-induced insulin resistance in mice lacking adiponectin/ACRP30. Nat Med 8 (7), 731–737. 235. Pajvani, U. B. and Scherer, P. E. (2003) Adiponectin: systemic contributor to insulin sensitivity. Curr Diab Rep 3 (3), 207–213. 236. Masaki, T., Chiba, S., Yasuda, T., Tsubone, T., Kakuma, T., Shimomura, I., Funahashi, T., Matsuzawa, Y. and Yoshimatsu, H. (2003) Peripheral, but not central, administration of adiponectin reduces visceral adiposity and upregulates the expression of uncoupling protein in Agouti yellow (A(y)/a) obese mice. Diabetes 52 (9), 2266–2273. 237. Tschritter, O., Fritsche, A., Thamer, C., Haap, M., Shirkavand, F., Rahe, S., Staiger, H., Maerker, E., Haring, H. and Stumvoll, M. (2003) Plasma adiponectin concentrations predict insulin sensitivity of both glucose and lipid metabolism. Diabetes 52 (2), 239–243. 238. Combs, T. P., Berg, A. H., Obici, S., Scherer, P. E. and Rossetti, L. (2001) Endogenous glucose production is inhibited by the adipose-derived protein Acrp30. J Clin Invest 108 (12), 1875–1881.

REFERENCES

295

239. Fruebis, J., Tsao, T. S., Javorschi, S., Ebbets-Reed, D., Erickson, M. R., Yen, F. T., Bihain, B. E. and Lodish, H. F. (2001) Proteolytic cleavage product of 30-kDa adipocyte complement-related protein increases fatty acid oxidation in muscle and causes weight loss in mice. Proc Natl Acad Sci USA 98 (4), 2005–2010. 240. Yamauchi, T., Kamon, J., Waki, H., Imai, Y., Shimozawa, N., Hioki, K., Uchida, S., Ito, Y., Matsui, J., Eto, K., Komeda, K., Tsunoda, M., Murakami, K., Ohnishi, Y., Yamamura, K., Ueyama, Y., Froguel, P., Kimura, S., Nagai, R. and Kadowaki, T. (2002) Globular adiponectin protected ob/ob mice from diabetes and apoE deficient mice from atherosclerosis. J Biol Chem. 241. Xu, A., Wang, Y., Keshaw, H., Xu, L. Y., Lam, K. S. and Cooper, G. J. (2003) The fat-derived hormone adiponectin alleviates alcoholic and nonalcoholic fatty liver diseases in mice. J Clin Invest 112 (1), 91–100. 242. Berg, A. H., Combs, T. P., Du, X., Brownlee, M. and Scherer, P. E. (2001) The adipocyte-secreted protein Acrp30 enhances hepatic insulin action. Nat Med 7 (8), 947–953. 243. Yamauchi, T., Kamon, J., Minokoshi, Y., Ito, Y., Waki, H., Uchida, S., Yamashita, S., Noda, M., Kita, S., Ueki, K., Eto, K., Akanuma, Y., Froguel, P., Foufelle, F., Ferre, P., Carling, D., Kimura, S., Nagai, R., Kahn, B. B. and Kadowaki, T. (2002) Adiponectin stimulates glucose utilization and fatty-acid oxidation by activating AMP-activated protein kinase. Nat Med 8 (11), 1288–1295.

11 Dietary Factors and Insulin Resistance Jeremy Krebs and Susan Jebb

11.1 Introduction Diet is a critical determinant of the risk of many metabolic diseases. However, while the role of dietary factors in the aetiology of cardiovascular disease and cancer has been extensively explored, less consideration has been given to the development of insulin resistance and diabetes. Recently the global epidemic of type 2 diabetes, following in the wake of the increase in obesity, has focussed attention in this area. There is renewed interest in both the role of dietary factors as a contributor to obesity and the impact of specific dietary constituents on insulin resistance, independent of weight. Putative candidates include each of the macronutrients together with specific micronutrients. However, progress in understanding the relationship between diet and insulin resistance is hampered by the complexity of the relationship, which is difficult to isolate from factors such as genetic background, or other environmental factors such as physical activity. Indeed, there are likely to be complex inter-relationships between these factors, including gene–nutrient–environment interactions. Epidemiological analyses of the problem are hampered by the difficulties in making accurate measurements of exposure (dietary intake) and outcome (insulin resistance). Assessment of habitual diet is notoriously flawed, with a bias towards under-reporting, that is unlikely to apply equally across all foods or nutrients.1, 2 A variety of methods are used to assess insulin resistance, each offering a slightly different perspective on this metabolic disturbance, including fasting insulin concentration, combinations of fasting insulin and glucose such as the homeostasis model assessment (HOMA) and area under the insulin curve Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

298

DIETARY FACTORS AND INSULIN RESISTANCE

during an OGTT. In some cases the occurrence of impaired glucose tolerance may be used as a surrogate, albeit very loose, marker of insulin resistance. More sophisticated methods of determining insulin sensitivity such as the intravenous glucose tolerance test with minimal modelling or the hyperinsulinaemic euglycaemic clamp are the ‘gold standards’ but are invasive, costly and largely confined to experimental studies. Together the measurement errors in diet and insulin resistance incurred in most epidemiological studies make the interpretation of cross-sectional associations particularly challenging. Testing epidemiological hypotheses in controlled intervention studies has also proved difficult because habitual background diet, physical activity and body composition have important modulating effects on the impact of specific dietary factors on insulin resistance. It is difficult to alter one dietary factor independent of other components of the diet, and short term interventions may not appropriately reflect a lifetime’s exposure. Thus in many situations it is necessary to study the precise mechanism of action of a nutrient at a cellular or tissue level in order to shed light on its potential role in whole body insulin resistance. This chapter draws on evidence from diverse sources to consider the role of dietary factors in the aetiology of insulin resistance and thus offers a foundation for the development of dietary strategies to prevent or reduce insulin resistance.

11.2 The importance of body fatness Body mass index (BMI) is a strong predictor of the risk of developing type 2 diabetes.3, 4 The association is particularly marked for more specific measures of body fatness, especially abdominal fat.5 Adult weight gain increases the risk further (Figure 11.1). More detailed experimental studies using a euglycaemic clamp have confirmed that weight gain is associated with a deterioration in insulin sensitivity in overweight and obese individuals with either normal or impaired glucose tolerance.6 The exact mechanism for the link between

20 15

ta

t2

1

22–23

5

ye

ar

>24

10

ei

>11 5–10 <5 Weight gain since 21 year

gh

<22

0

W

Relative risk

25

Figure 11.1 Impact of BMI and weight change on the risk of developing diabetes in men (data from reference 3)

THE IMPORTANCE OF BODY FATNESS

299

increased fatness and insulin resistance remains unclear, but there is growing evidence of signalling between adipose tissue and insulin-sensitive organs – particularly liver and skeletal muscle – which in part regulates the insulin sensitivity of these organs. Potential candidates for this signal include circulating free fatty acids, adipokines such as Acrp30, IL-6, TNFα, leptin or resistin or some other as yet unidentified agent.7 These are discussed in detail in Chapter 10. However, it is apparent that normally functioning adipose tissue is required for normal whole body insulin sensitivity. This is highlighted by syndromes of lipodystrophy where the relative absence of adipose tissue is also associated with insulin resistance.8 Body weight is the integrated product of a lifetime’s dietary intake, offset by energy needs. An excess of energy intake over expenditure over a prolonged period of time leads to increases in body fat and ultimately, if unchecked, in obesity. Although this fundamental principle of energy balance lies at the heart of the aetiology of obesity, it oversimplifies the complex inter-relationships between genetic factors, lifestyle, cultural issues and behavioural patterns that all contribute to the risk of an individual becoming overweight.9, 10 Whilst a detailed discussion of the aetiology of obesity is beyond the scope of this chapter, it is important to remember that dietary factors that impact upon the risk of obesity will, in turn, increase the risk of developing insulin resistance. Epidemiological analyses of the relationship between fat intake and obesity are inconsistent, although the trend suggests that a high fat diet is linked to an increased risk of excess weight.11, 12 However, such studies are confounded by errors in dietary reporting and post hoc changes in consumption among obese individuals. More detailed experimental studies demonstrate that subjects allowed to eat ad libitum from diets of varying fat content consume more energy on high fat foods.13 However, this high fat hyperphagia is abolished when the energy density is equalized.14 Low fat, low energy-dense diets that are associated with a reduction in total energy intake lead to modest weight losses and associated improvements in insulin sensitivity.15 Fruit and vegetables can help to reduce the energy density of the diet, although specific evidence of a protective role for these foods in the aetiology of obesity is lacking. Data from diverse sources implies an adverse effect of sugar rich soft drinks. Consumption of soft drinks among children and young people has increased markedly over the last 20 years, coinciding with the rapid rise in obesity in developed countries. These have a low energy density, due to their high water content, but their low viscosity reduces their impact on innate satiety signals.16 Thus consumption of these drinks tends to supplement rather than substitute for food energy, increasing the risk of excessive energy intakes.17 A 10 week intervention study showed consumption of sugar rich beverages was associated with significant weight gain relative to artificially sweetened varieties.18 The role of other specific carbohydrate sources in the aetiology of obesity is less clear, although evidence favours a protective role of foods with a low glycaemic index.19

300

DIETARY FACTORS AND INSULIN RESISTANCE

Recently research has turned towards the investigation of broader eating habits rather than specific foods or nutrients. Issues such as the impact of fast food,20 snacking,21 portion size,22 food consumed in conjunction with TV viewing23 and family or cultural influences24 may all be important determinants of the risk of obesity. Finally, it is important to note the impact of physical activity, both as a determinant of energy needs, but also as an element in innate appetite control systems.25 These issues have been recently reviewed.26 The importance of obesity as a determinant of insulin resistance is confirmed by the striking improvements that can be seen in insulin resistance with weight loss.27 Even modest weight losses of 5–10 per cent of initial body weight achieved through diet and lifestyle modification in overweight and obese subjects are related to improved insulin sensitivity.28 The magnitude of the improvement in insulin resistance is largely related to the extent of weight loss. For example, very low calorie diets (VLCD), providing <800 kcal/day, are able to facilitate greater weight loss, at least in the short term, than more conservative dietary approaches, and a corresponding greater improvement in insulin sensitivity. In obese sedentary subjects those using a VLCD achieved a 15 per cent weight loss over 4 months with a 24 per cent improvement in insulin sensitivity measured by the euglycaemic clamp.29 In a group of 40 obese subjects with type 2 diabetes the initial use of a VLCD for eight weeks resulted in a mean weight loss of more than 10 per cent body weight with associated improvements in fructosamine, and reductions in insulin requirements. This benefit was maintained at 12 months after ongoing standard weight management advice.30 The adjunctive use of pharmacotherapy, such as sibutramine or orlistat, to achieve greater reductions in energy intake or absorption over and above diet and lifestyle modification alone is associated with greater weight loss compared with placebo. This translates into greater improvements in insulin sensitivity in obese individuals31, 32 and those with the metabolic syndrome33 and also improvements in glycaemic control in those with type 2 diabetes.34 Bariatric surgery, such as gastric bypass or gastric banding, leading to marked decreases in energy intake, results in weight losses of up to 50 per cent body weight. This is considerably greater than that achieved with other methods, leading to major improvements in insulin sensitivity and reduced progression to diabetes in obese individuals.35, 36 It should be noted that changes in total energy intake have important effects on insulin sensitivity independent of the effect of changes in body weight or fat mass. In highly controlled experimental studies, short term periods of energy restriction in individuals who are insulin resistant are associated with rapid improvements in insulin sensitivity, even in the absence of weight loss.37 The exact mechanism for this sudden change is not clear, but is likely to be related to changes in nutrient flux or possibly to gut-related hormones. In particular, a reduction in circulating free fatty acids is achieved with acute energy restriction due to reduced dietary fat intake and reduced adipocyte lipolysis. High levels of

THE IMPORTANCE OF BODY FATNESS

301

circulating free fatty acids have been linked to insulin resistance via impairment of insulin-mediated glucose uptake and reductions in free fatty acid levels with acute energy restriction reversing this effect.8, 38 Thus, in the acute phase of weight loss, the improvement in metabolic risk factors is largely related to the energy deficit and extent of weight lost and there is little evidence to support a specific benefit of any one dietary regimen over another. However, in the phase of weight-loss maintenance, diet composition may become more important. Weight loss achieved with diet and lifestyle modification, pharmacotherapy or surgery is often followed by some weight regain, which is frequently accompanied by deterioration in insulin sensitivity. In otherwise healthy obese individuals, a minimum of five per cent long term reduction in body weight appears to be required to maintain improvements in insulin sensitivity.39 However, recent data suggests that there may be residual benefits that reduce, or at least delay, the development of diabetes in obese subjects with impaired glucose tolerance. Two large prospective randomized controlled trials of diet and lifestyle intervention to promote weight loss in individuals at high risk of developing diabetes have shown a significantly reduced risk with very modest initial weight loss and even smaller long term weight loss. In the Finnish diabetes prevention study40 intensive dietary and lifestyle advice achieved a mean weight loss of 4.7 per cent over 12 months in 522 obese individuals with impaired glucose tolerance, and significant reduction in 2 hour post-glucose-load insulin concentration but not fasting insulin. This was followed by variable weight regain over the mean 3.2 year follow-up, resulting in a mean 3.5 ± 5.5 kg decrease in weight from baseline. This small long term sustained weight loss was associated with a 58 per cent reduced risk of progression to diabetes. An identical risk reduction was observed in the Diabetes Prevention Program,41 in a similar group of 3234 obese individuals with impaired glucose tolerance, and a mean weight loss of less than five per cent body weight after 4 years. This implies a longer term metabolic benefit of even small weight losses, which may encompass benefits on insulin release from pancreatic β-cells as well as those of improved insulin sensitivity. However, as might be expected, greater long term weight losses are associated with a greater reduction in risk. The Xendos trial42 was a randomized, placebocontrolled trial comparing the adjunctive use of orlistat with intensive diet and lifestyle modification in 4193 obese subjects. Subjects randomized to orlistat lost a mean of 6.9 kg compared with 4.1 kg in those on placebo after 4 years. This translated to a 37 per cent reduction (9.0 per cent compared with 6.2 per cent) in the rate of progression to diabetes over the 4 years of the study. In a subset of those with impaired glucose tolerance, those in the intensive lifestyle alone group had similar rates of progression to diabetes to those in the intensive lifestyle group of the Diabetes Prevention Program.41 In these subjects, the additional weight loss achieved with orlistat further reduced the rate of developing diabetes by an additional 52 per cent.

302

DIETARY FACTORS AND INSULIN RESISTANCE

The impact of lifestyle changes, independent of body weight, are unclear, but the improvement in insulin sensitivity is probably greater than may be anticipated from the small overall weight loss. Increases in physical activity are known to offer a decreased risk of diabetes but certain dietary components may also be significant. In each of these studies the dietary recommendations were based around a low fat, calorie-controlled diet, rich in fruits and vegetables and with an emphasis on unrefined carbohydrates, which is consistent with international dietary recommendations for the prevention of cardiovascular disease. At present, no comparable long term data showing improvements in the hard clinical endpoint of incident diabetes is available for other, less orthodox, dietary regimens.

11.3

Specific dietary factors

Epidemiological investigations into the role of dietary factors and insulin resistance generally focus on specific nutrients, notably macronutrients (fat, carbohydrate, protein and, to a lesser extent, alcohol) or micronutrients (vitamins and minerals). In addition there is growing interest in the role of a range of other plant-based compounds that are not classical nutrients but that may exert specific health benefits, such as flavanoids and phytoestrogens.43 This makes it difficult to disentangle the health effects of specific nutrients. Similar difficulties exist in the interpretation of many dietary intervention studies. Changes in absolute macronutrient intake have implications for total energy intake, while changes in the proportion of energy-providing substrates result in changes in more than one macronutrient. Food represents a complex mixture of nutrients and foods are rarely eaten in isolation, so it may be more appropriate, although more complex, to analyse broader dietary patterns. However suitable statistical techniques are only just being employed to analyse nutritional data.

Fat Fat is the most energy dense of the macronutrients, containing 9 kcal/g (37 kJ/g) compared with 4 kcal/g (16 kJ/g) for carbohydrate or protein, and has been implicated in the aetiology of obesity. However independent of the effect on body weight, both the amount and type of fat have an impact on insulin sensitivity. Diets high in fat are associated with impairments in insulin sensitivity and animal studies consistently demonstrate that high fat diets promote insulin resistance compared with diets high in carbohydrate.44 Although less consistent, studies in humans show that high fat diets are associated with higher fasting insulin concentration and reduced insulin sensitivity,45, 46 and in longitudinal studies a higher rate of development of impaired glucose tolerance47 and progression to type 2 diabetes.48

SPECIFIC DIETARY FACTORS

303

However, it is important to distinguish between different types of fat. The negative association between fat and insulin sensitivity is predominately driven by saturated fat. In epidemiological studies, a high saturated fat intake has been associated with higher fasting insulin and glucose levels45 and greater rates of glucose intolerance.47 Specific fatty acid analysis of serum and muscle membrane phospholipids reveals an association between high levels of saturated fatty acid content and higher fasting insulin, reduced insulin sensitivity and higher risk of developing type 2 diabetes.49, 50 Monounsaturated fatty acids (MUFAs) are usually considered to have a neutral impact on insulin sensitivity. However, a recent large intervention study replacing saturated fat with monounsaturated fat and with detailed measures of insulin sensitivity using an IVGTT showed improvements in insulin sensitivity in healthy subjects after 3 months.51 However, a post hoc analysis suggested that this benefit was only apparent among individuals where the intake of fat was less than 37 per cent of total energy – highlighting the importance of total fat content. In epidemiological studies, increases in the proportion of PUFAs in the diet are associated with lower insulin levels, enhanced insulin sensitivity52, 53 and reduced risk of developing type 2 diabetes.54 In the Nurses’ Health Study, after 14 years follow-up, the adjusted relative risk for developing type 2 diabetes was 0.75 (95 per cent CI, 0.65–0.88) for the highest versus lowest quintile of PUFA intake.54 Polyunsaturated fatty acids are classified as essential fatty acids since they must be obtained from the diet and cannot be synthesised in vivo. Linoleic acid (n − 6) and α-linolenic acid (n − 3) classes of PUFA may be elongated and further desaturated to form long chain fatty acids. This occurs to some extent in vivo, but the majority of these long chain n − 3 PUFAs are obtained from the diet in the form of the so-called fish oils, eicosapentanoic acid (EPA) and decosahexanoic acid (DHA). In the average western diet, intake of n − 6 PUFA is considerably greater than that of n − 3 PUFA, and quantitatively small changes in n − 3 can have a considerable effect on the n − 6:n − 3 ratio. There is some debate about the relative importance of n − 3 intake and the n − 6:n − 3 ratio as a determinant of insulin sensitivity. A study in rats fed a high fat diet resulting in insulin resistance showed that replacing saturated fat with a combination of short chain (18:2 n − 6) and short chain (18:3 n − 3) PUFA had no effect on insulin resistance measured by the euglycaemic clamp.55 However, if saturated fat was replaced with long chain n − 3 PUFA, insulin resistance was significantly improved. Moreover, if the rats were fed a diet of saturated fat combined with short chain n − 3 but not short chain n − 6 PUFA, insulin resistance was similarly improved (Figure 11.2). These results suggest an important role for long chain n − 3 PUFAs in improving insulin sensitivity, but further indicate that the competition for enzymes to further elongate and desaturate shorter chain n − 3 PUFAs prevents this conversion when combined with a diet rich in short chain n − 6

304

DIETARY FACTORS AND INSULIN RESISTANCE

GIR (mg/kg min)

20 15 10 5

Figure 11.2 ence 55)

Sat + short(n – 3)

Poly + short (n – 3)

Poly + long(n – 3)

Poly

Mono

Sat

0

Impact of dietary fat composition on insulin sensitivity (data from refer-

PUFAs. From this it may be concluded that n − 3 PUFAs are important dietary determinants of insulin sensitivity, and that the ratio of n − 6:n − 3 PUFAs and the chain length of n − 3 PUFAs are also important. Epidemiological evidence supports a beneficial impact of high dietary intakes of the long chain n − 3 PUFAs eicosapentanoic acid (EPA) and decosahexanoic acid (DHA) in reducing insulin resistance and rates of impaired glucose tolerance and type 2 diabetes.47, 56 Intervention studies have shown mixed results, which may reflect differences in habitual diets of participants, doses of n − 3 PUFAs used, other dietary components, methodologies used for measuring insulin sensitivity or other population characteristics. Further research is required to resolve this uncertainty. Although long chain n − 3 PUFAs represent a small proportion of the total dietary intake fat, they have specific metabolic functions, which may explain their positive effect on insulin sensitivity. These fatty acids are preferentially incorporated into cell membranes, altering membrane fluidity and receptor function.57 They have anti-inflammatory properties, by virtue of being substrates for less proinflammatory ecosanoids than equivalent n − 6 fatty acids.58 They have a potent lipid modifying effect with consistent reductions in fasting triglycerides of 25–30 per cent in a wide range of patient groups.59 They are also natural ligands for PPARγ, and via this or other nuclear receptors may impact on gene expression of adipocytokines.60 Any or all of these features may explain the potentially important role for dietary long chain n − 3 PUFAs on insulin sensitivity.

Carbohydrate Changes in the proportion of dietary fat frequently lead to reciprocal changes in carbohydrate, since protein intake tends to remain broadly constant in most

SPECIFIC DIETARY FACTORS

305

Western diets. Diets proportionally higher in carbohydrate tend to be associated with a reduced risk of obesity and hence decreased risk of diabetes,61 but it is not easy to ascertain whether this reflects the disadvantageous effects of high fat diets or a specific positive benefit of carbohydrate. Recently, the concept that low carbohydrate diets may be linked to enhanced weight loss has received much public attention, but there is little scientific evidence for any novel effect. A systematic review of low carbohydrate diets concluded that weight loss was related to the energy deficit and diet duration rather than to the carbohydrate content per se.62 A 1 year trial of a low carbohydrate diet versus a low fat diet found that although initial weight losses were greater in the low carbohydrate group this was not sustained and after 1 year there was no significant difference between the two groups.63 In practice, a low carbohydrate diet reduces energy intake since it is difficult to replace calories from carbohydrate from other sources. Indeed, low carbohydrate diets can also reduce fat intake since the two co-exist in many foods such as cakes and biscuits, or carbohydrate may act as a vehicle for added fat, e.g. bread and butter. However, over and above these putative effects on body weight there is growing interest in the possibility that different types of carbohydrate may be associated with specific effects on insulin resistance, independent of body weight. These metabolic properties are particularly associated with specific features of certain carbohydrate foods, such as their chemical structure, e.g. fibre content, the degree of processing, e.g. wholegrain, or the metabolic effects, e.g. glycaemic index. 1. Fibre. Epidemiological studies suggest that high fibre diets are associated with a reduced risk of type 2 diabetes.64 The mechanism of action is not clear, although fibre may attenuate the glycaemic response to ingested carbohydrate, possibly by its physical effect in the gut, where it tends to slow the absorption of nutrients, thus reducing the demand for insulin. Alternatively, fibre and indigestible carbohydrate may be fermented by the colonic bacteria, producing short chain fatty acids. These may enter the portal circulation, increase hepatic glucose oxidation, decrease FFA release and increase insulin clearance.65 The relative effects of soluble and insoluble fibre remain unclear. In a crossover study in 14 subjects with type 2 diabetes, increased cereal fibre reduced mean glucose concentration with no effect on insulin levels, suggesting an improvement in insulin sensitivity.66 In contrast, in 22 healthy postmenopausal women insulin sensitivity measured by an IVGTT was no different whether subjects were taking high fibre rye bread or white wheat bread.67 However, insulin secretion measured from the IVGTT was increased with the high fibre rye bread, suggesting an effect of fibre on β-cell function. Another study comparing whole kernel rye bread, wholemeal rye bread (high in soluble fibre), dark durum wheat pasta and white wheat bread in a test meal with equivalent total

306

DIETARY FACTORS AND INSULIN RESISTANCE

carbohydrate content demonstrated no difference in rate of gastric emptying or glucose response, but lower insulin responses to each of the higher fibre products compared with white wheat bread. The total fibre content of each was different, but resulted in similar effects on insulin response. The authors concluded that the structural and compositional properties of the fibre are more important that the total quantity.68 2. Whole grains. In western countries the majority of grain products consumed are refined, with average consumption of wholegrain foods as low as one serving per day in the United States.69 Epidemiological studies show a protective effect of diets rich in wholegrain foods on insulin sensitivity70 and risk for type 2 diabetes.71 In the Framingham offspring study cohort, there was an inverse relationship between wholegrain consumption and fasting insulin concentration, which remained significant after adjustment for BMI.70 In the Health Professionals Follow-Up Study, the adjusted relative risk of developing type 2 diabetes over 12 years was 0.58 comparing the highest and lowest quintiles of wholegrain intakes.71 Experimental studies have also demonstrated benefits of whole grains on insulin sensitivity. In a cross-over study in 11 obese subjects insulin sensitivity, measured by the euglycaemic clamp, improved after six weeks on a diet rich in whole grains compared with refined grains. This effect was deserved in the absence of any change in body weight.72 The mechanism for any protective effect of whole grains remains uncertain. The refining process modifies the nutritional composition of grains, reducing magnesium, vitamin E and fibre content. In the Framingham study and the Health Professionals Follow-Up Study, individual adjustment for intake of magnesium and insoluble fibre attenuated the inverse relationship with fasting insulin and risk for developing type 2 diabetes respectively, suggesting that these components may be important,70, 71 although they did not appear to explain the full association. Of further interest is the observation that, when stratified for BMI, the protective effect of whole grains on fasting insulin may be limited to those with a BMI greater than 30 kg/m2 .70 This may be related to higher fasting insulin levels in the more obese individuals, but also raises the intriguing possibility of an interaction between dietary factors and phenotype, where low wholegrain consumption may be particularly disadvantageous in the obese. 3. Glycaemic index (GI). There is increasing interest in the concept of glycaemic index (GI) – a physiological classification that describes the impact of a known quantity of available carbohydrate on blood glucose following ingestion. This is of particular relevance to the consideration of insulin resistance since there is a high correlation between the glycaemic response and the insulin response (with just a few exceptions, notably dairy products, which induce a disproportionately high insulin response).

SPECIFIC DIETARY FACTORS

307

There is concern that a high carbohydrate intake increases insulin secretion to maintain glucose homeostasis, resulting in higher postprandial insulin levels.73 However, the glycaemic index of the carbohydrate, or other components of the meal, will modulate the effect on insulin release. The possibility of effects of glycaemic index on both insulin secretion and uptake highlights the complexities of this theory. The glycaemic index measures and ranks the impact of carbohydrates on postprandial plasma glucose. The GI depends largely on the rate of digestion and absorption of carbohydrates. From this it can by shown that many ‘complex’ carbohydrates induce a glycaemic response nearly as high as that of pure glucose. This suggests that the traditional classification of simple versus complex carbohydrate based on chemical composition may not be especially useful. In epidemiological studies, low dietary glycaemic load (GI/total carbohydrate) has been associated with reduced rates of developing type 2 diabetes. In a cohort of 65 173 women in the Nurses’ Health Study over a six year period the relative risk was 1.37 of developing diabetes in the highest quintile of glycaemic load compared with the lowest quintile after adjusting for intake of cereal fibre64 (Figure 11.3). Wolever and Bolognesi examined the effect of both the amount and source of carbohydrate consumed on postprandial glucose and insulin responses to mixed meals of varying total energy, fat, protein and carbohydrate content, in eight subjects without diabetes.74 The amount of carbohydrate alone was not significantly related to the mean glucose and insulin responses. However, amount of carbohydrate combined with glycaemic index explained approximately 90 per cent of the variability of the glucose and insulin responses. This apparent effect on insulin sensitivity may depend on the underlying individual level of insulin resistance. In a small study of seven healthy, lean, insulin-sensitive young men, no improvements were seen with a low GI diet compared with a high GI diet in a 30

Relative risk

2.5 2 1.5 1 0.5 0 High (>165)

Medium

Low (<143)

Glycaemic load

Hi gh

Lo w (< M 2. ed 5g ium ) (> 5. 8g )

re

ib

f al

re

Ce

Figure 11.3 Impact of carbohydrate composition on the risk of type 2 diabetes (data from reference 64)

308

DIETARY FACTORS AND INSULIN RESISTANCE

day randomized crossover study.75 However, in a group of 30 patients with advanced cardiovascular disease those randomized to a low GI dietary intervention over 4 weeks had improvements in insulin sensitivity compared with those on a high GI diet.76 However, these classification systems are not mutually exclusive and there is no comprehensive definition that neatly accounts for the health effect of carbohydrates. In epidemiological analyses it may be more useful to focus on certain foods or on overall eating patterns, using techniques such as or principal component analysis. Meanwhile, intervention studies need to use well defined dietary prescriptions, which if successful can be translated into public health recommendations.

Protein Across diverse diets the proportion of protein in the diet remains relatively stable, with a reciprocal relationship between fat and carbohydrate dominating most changes in dietary intake. There is relatively little data on the effects of protein on insulin sensitivity. In a group of overweight insulin-resistant subjects, replacing carbohydrate with protein from meat, poultry and dairy food in a calorie reduced diet (high protein diet, 27 per cent energy protein, 44 per cent carbohydrate and 29 per cent fat, versus low protein diet, 16 per cent protein, 57 per cent carbohydrate, 27 per cent fat) had no effect on overall weight loss but had a beneficial effect on glycaemic response, suggesting improved insulin sensitivity.77 There is evidence from studies in rats that the source of dietary protein may have differential effects on insulin sensitivity. In rats fed a high fat diet, in which the protein source was casein, fish (cod) protein or soy protein, the high fat feeding led to severe insulin resistance, which was prevented by fish protein, and to a lesser degree by soy protein compared with casein.78 However, highly controlled intervention studies testing the impact of differing dietary protein content or source employing euglycaemic clamp or IVGTT methods of measuring insulin sensitivity in humans are lacking. This therefore remains an area requiring additional research.

Alcohol Epidemiological studies remain equivocal on the relationship between alcohol consumption and type 2 diabetes, with the impact being dose related. The Nurses Health Study79 and US Male Health Professionals Study80 both suggest a protective role for modest alcohol intake (less than 21 standard drinks per week), but the Atherosclerosis Risk in Communities Study (ARIC) suggest that men consuming over 21 standard drinks per week have an increased risk.81 Data

SPECIFIC DIETARY FACTORS

309

from the British Regional Heart Study suggests a U-shaped relationship between alcohol consumption and risk of type 2 diabetes.82 Thus the effects of alcohol may be different according to level of consumption and are confounded by differences in body weight, body fatness and blood lipids. Intervention studies specifically examining the impact of alcohol on insulin sensitivity are limited. One crossover study in overweight women showed no effect of 10 weeks of modest red wine intake on insulin sensitivity, measured by an IVGTT, or glucose homeostasis.83

Micronutrients There has been relatively little systematic investigation into the effects of specific vitamins and minerals on insulin sensitivity. Epidemiological analysis reveals several candidates, but in each case the evidence for specific physiological effects is limited. Vitamin E

Vitamin E is a fat-soluble vitamin with antioxidant properties. Increased oxidative stress has been linked with insulin resistance, raising the possibility that dietary antioxidants may have beneficial effects. Two cohort studies have examined the relationship between vitamin E status and risk of type 2 diabetes. One study showed that low levels of vitamin E were associated with a 3.9fold increased risk of developing type 2 diabetes over four years.84 The other, a nested case control study, showed that subjects with high levels of vitamin E had a 39 per cent lower risk of type 2 diabetes compared with those with low levels.85 However, this association was lost when adjusted for cholesterol, smoking, BMI and hypertension. In healthy non-diabetic individuals, insulin sensitivity measured by an IVGTT was positively related to plasma vitamin E concentration and inversely related to lipid hyperoxide concentrations, suggesting a role in insulin sensitivity.86 However, this relationship was not seen in a similar study after adjustment for other factors known to affect insulin sensitivity such as degree of obesity and level of physical activity.87 Together this data suggests that vitamin E intake and status may reflect a generally healthy lifestyle rather than independent metabolic effects. Magnesium

Large epidemiological studies have shown an association between low magnesium intake and the risk of type 2 diabetes in both men and women with a risk ratio for those in the upper quintile compared with the lower quintile of magnesium intake of about 0.7 after adjustment for BMI, smoking and physical activity.64, 69, 88 Cereal fibre is an important dietary source of magnesium and adjustment for fibre intake attenuates this relationship.

310

DIETARY FACTORS AND INSULIN RESISTANCE

Chromium

Chromium appears to have an important role in tissue whole body insulin sensitivity. In subjects with impaired glucose tolerance and raised insulin levels, chromium supplementation improves both insulin levels and glucose tolerance in patients with low intakes of chromium.89 Similar improvements in glycaemic control are seen with chromium supplements in those with established type 2 diabetes,90 although there is no apparent effect on insulin sensitivity in those with normal glucose tolerance. Although the role of chromium supplements is not firmly established there is at least a plausible mechanism of action for increased insulin action via increased insulin receptor expression and increased activation of insulin receptor kinase.91

11.4

Summary

Whole body insulin sensitivity is the product of a complex interaction between genotype, physical characteristics such as body weight and environmental and behavioural factors such as diet and physical activity. Obesity is strongly linked to impaired insulin sensitivity, but acute changes in total energy intake influence insulin sensitivity independently of changes in body weight or fat mass. Specific dietary components may also have independent effects on insulin sensitivity. The balance of evidence suggests that a high intake of saturated fat reduces insulin sensitivity, but that monounsaturated and polyunsaturated fat are neutral or beneficial, at least in the setting of moderate total fat intake. The effects of carbohydrate are less clear; however, unrefined carbohydrate, with a low glycaemic index, wholegrain and high fibre foods appear to have beneficial effects on insulin sensitivity compared with more refined carbohydrates. There may also be an influence of specific micronutrients such as magnesium, chromium and vitamin E; however, the evidence is limited. The evidence relating to dietary factors and insulin resistance is mostly drawn from epidemiological analyses with limited evidence from intervention studies and supplemented in some cases by biochemical mechanisms. However, more research is needed, especially to identify interrelationships with specific genotypes as have been elucidated with ApoE and hyperlipidaemia.92 Nonetheless there is a rational framework to make dietary recommendations to reduce the risk of insulin resistance and type 2 diabetes. Specifically, diets low in fat, especially saturated fat, with further substitutions of MUFAs or n − 3 PUFAs for n − 6 PUFAs and increases in unrefined carbohydrate, fruits and vegetables. This dietary prescription is consistent with strategies to reduce the risk of other non-communicable diseases.

REFERENCES

311

References 1. Goris, H. C., Westerterp-Plantenga, M. S. and Westerperp, K. R. (2000) Undereating and underrecording of habitual food intake in obese men: selective underreporting of fat intake. Am J Clin Nutr 71, 130–134. 2. Prentice, A. M., Black, A. E., Coward, W. A., Davies, H. L., Goldberg, G. R. and Murgatroyd, P. R. et al. (1986) High levels of energy expenditure in obese women. BMJ 292, 983–987. 3. Chan, J. M., Rimm, E. B., Colditz, G. A., Stampfer, M. J. and Willett, W. C. (1994) Obesity, fat distribution and weight gain as risk factors for clinical diabetes in men. Diabetes Care 17, 961–969. 4. Colditz, G. A., Willett, W. C., Rotnitzky, A. and Manson, J. E. (1995) Weight gain as a risk factor for clinical diabetes mellitus in women. Ann Intern Med 122 (7), 481–486. 5. Carey, D. G., Jenkins, A. B., Campbell, L. V., Freund, J. and Chisholm, D. J. (1996) Abdominal fat and insulin resistance in normal and overweight women. Diabetes 45, 633–638. 6. Weyer, C., Hanson, K., Bogardus, C. and Pratley, R. E. (2000) Long-term changes in insulin action and insulin secretion associated with gain, loss, regain and maintenance of body weight. Diabetologia 43 (1), 36–46. 7. Fruhbeck, G., Gomez-Ambrosi, J., Muruzabal, F. R. and Burrell, M. A. (2001) The adipocyte: a model for integration of endocrine and metabolic signaling in energy metabolism regulation. Am J Physiol Endocrinol Metab 280, E827–E847. 8. Frayn, K. N. (2001) Adipose tissue and the insulin resistance syndrome. Proc Nutr Soc 60 (3), 375–380. 9. Jebb, S. A. (1997) Aetiology of obesity. Br Med Bull 53, 264–285. 10. Egger, G. and Swinburn, B. A. (1997) An ecological approach to the obesity epidemic. BMJ 315, 477–480. 11. Bolton-Smith, C. and Woodward, M. (1994) Dietary composition and fat to sugar ratios in relation to obesity. Int J Obes Relat Metab Disorders 18 (12), 820–828. 12. Seidell, J. C. (1998) Dietary fat and obesity: an epidemiological perspective. Am J Nutr 67 (Suppl. 3), 546S–550S. 13. Stubbs, R. J., Ritz, P., Coward, W. A. and Prentice, A. M. (1995) Covert manipulation of the ratio of dietary fat to carbohydrate and energy density: effect on food intake and energy balance in free-living men eating ad libitum. Am J Clin Nutr 62 (2), 330–337. 14. Stubbs, R. J., Harbon, C. G. and Prentice, A. M. (1996) Covert manipulation of the dietary fat to carbohydrate ratio of isoenergetically dense diets: effects on food intake in feeding men ad libitum. Int J Obes 20, 651–660. 15. NHLBI Obesity Education Initiative Expert Panel. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults; the evidence report: National Institutes of Health; 1998 September 1998. Report No. 98-4083. 16. Mattes, R. D. and Rothacker, D. (2001) Beverage viscosity is inversely related to postprandial hunger in humans. Physiol Behav 74, 551–557. 17. Ludwig, D. S., Peterson, K. E. and Gortmaker, S. L. (2001) Relation between consumption of sugar-sweetened drinks and childhood obesity: a prospective, observational analysis. Lancet 357 (9255), 505–508. 18. Raben, A., Vasilaras, T. H., Moller, A. C. and Astrup, A. (2002) Sucrose compared with artificial sweeteners: different effects on ad libitum food intake and body weight after 10 weeks of supplementation in overweight subjects. Am J Clin Nutr 76, 721–729.

312

DIETARY FACTORS AND INSULIN RESISTANCE

19. Ludwig, D. S., Majzoub, J. A., Al-Zahrani, A., Dallal, G. E., Blanco, I. and Roberts, S. B. (1999) High glycaemic index foods, overeating, and obesity. Pediatrics 103 (3), E26. 20. Prentice, A. M. and Jebb, S. A. (2003) Fast foods, energy density and obesity – a possible mechanistic link. Obes Rev 4 (4), 187–194. 21. Green, S. M. and Blundell, J. E. (1996) Effect of fat and sucrose-containing foods on the size of eating episodes and energy intake in lean dietary restrained and unrestrained females: potential for causing over-consumption. Eur J Clin Nutr 50, 625–635. 22. Rolls, B. J., Morris, E. L. and Roe, L. S. (2002) Portion size of food affects energy intake in normal-weight and overweight men and women. Am J Clin Nutr 76, 1207–1213. 23. Rennie, K. and Jebb, S. A. (2004) Sedentary lifestyles are associated with being overweight and consumption of savoury snacks in young people (4–18 years). Proc Nutr Soc (in press). 24. Campbell, K. and Crawford, D. (2001) Family food environments as determinants of preschool-aged children’s eating behaviours: implications for obesity prevention policy. A review. Aust J Nutr Dietet 58, 19–25. 25. Saris, W. H. (1998) Fit, fat and fat free: the metabolic aspects of weight control. [Review; 50 refs]. Int J Obes 22 (Suppl. 2), S15–S21. 26. Jebb, S. A. and Krebs, J. D. Lifestyle determinants of obesity. In: Kumar, S. and Barnett, A. H., eds. Obesity and Diabetes. New York: Wiley (in press). 27. Pi-Sunyer, F. X. (1993) Short-term medical benefits and adverse effects of weight loss. Ann Intern Med 119 (7), 722–726. 28. Goldstein, D. J. (1992) Beneficial health effects of modest weight loss. Int J Obes 16, 397–415. 29. Goodpaster, B. H., Kelley, D. E., Wing, R. R., Meier, A. and Thaete, F. L. (1999) Effects of weight loss on regional fat distribution and insulin sensitivity in obesity. Diabetes 48, 839–847. 30. Dhindsa, P., Scott, A. R. and Donnelly, R. (2003) Metabolic and cardiovascular effects of very-low-calorie diet therapy in obese patients with type 2 diabetes in secondary failure: outcomes after 1 year. Diabet Med 20, 319–324. 31. Davidson, M. H., Hauptman, J., DiGirolamo, M., Foreyt, J. P., Halsted, C. H. and Heber, D. et al. (1999) Weight control and risk factor reduction in obese subjects treated for 2 years with orlistat: a randomized controlled trial. JAMA 281 (3), 235–242. 32. James, W. P., Astrup, A., Finer, N., Hilsted, J., Kopelman, P. and Rossner, S. et al. (2000) Effect of sibutramine on weight maintenance after weight loss: a randomised trial. STORM Study Group. Sibutramine Trial of Obesity Reduction and Maintenance. Lancet 356 (9248), 2119–2125. 33. Reaven, G., Segal, K., Hauptman, J., Boldrin, M. and Lucas, C. (2001) Effect of orlistatassisted weight loss in decreasing coronary heart disease risk in patients with syndrome X. Am J Cardiol 87 (7), 827–831. 34. Finer, N., Bloom, S. R., Frost, G. S., Banks, L. M. and Griffiths, J. (2000) Sibutramine is effective for weight loss and diabetic control in obesity with type 2 diabetes: a randomised, double-blind, placebo-controlled study. Diabetes Obes Metab 2 (2), 105–112. 35. Sjostrom, C. D., Lissner, L., Wedel, H. and Sjostrom, L. (1999) Reduction in incidence of diabetes, hypertension and lipid disturbances after intentional weight loss induced by bariatric surgery: the SOS intervention study. Obes Res 7 (5), 477–484. 36. Friedman, J. E., Dohm, G. L., Leggett-Frazier, N., Elton, C. W., Tapscott, E. B. and Pories, W. P. et al. (1992) Restoration of insulin responsiveness in skeletal muscle of morbidly obese patients after weight loss. Effect on muscle glucose transport and glucose transporter GLUT4. J Clin Invest 89 (2), 701–705.

REFERENCES

313

37. Weinsier, R. L., James, L. D. and Darnell, B. E. (1992) Lipid and insulin concentrations in obese postmenopausal women: seperate effects of energy restriction and weight loss. Am J Clin Nutr 56, 44–49. 38. Shulman, G. I. (2000) Cellular mechanisms of insulin resistance. J Clin Invest 106 (2), 171–176. 39. Krebs, J. D., Evans, S., Cooney, L., Mishra, G. D., Finer, N. and Jebb, S. A. (2002) Changes in risk factors for cardiovascular disease with body fat loss in obese women. Diabetes Obes Metab 4 (6), 379–387. 40. Tuomilehto, J., Lindstrom, J., Eriksson, J. G., Valle, T. T., Hamalainen, H. and IlanneParikka, P. et al. (2001) Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 344, 1343–1350. 41. Diabetes Prevention Program Research Group. (2002) Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 346, 393–403. 42. Torgerson, J. S. et al. (2004) XENDOS: a randomised study of orlistat as an adjunct to lifestyle changes for the prevention of type 2 diabetes in obese patients. Diabetes Care 27 (1), 155–161. 43. Goldberg, G., ed. (2003) Plants: Diet and Health, British Nutrition Foundation. Oxford: Blackwell. 44. Storlien, L. H., Pan, D. A., Kriketos, A. D. and Baur, L. A. (1993) High fat diet-induced insulin resistance. Lessons and implications from animal studies. Ann NY Acad Sci 683, 82–90. 45. Marshall, J. A., Bessesen, D. H. and Hamman, R. F. (1997) High saturated fat and low starch and fibre are associated with hyperinsulinaemia in a non-diabetic population: the San Luis Valley Diabetes Study. Diabetologia 40 (4), 430–438. 46. Lovejoy, J. and DiGirolamo, M. (1992) Habitual dietary intake and insulin sensitivity in lean and obese adults. Am J Clin Nutr 55 (6), 1174–1179. 47. Feskens, E. J., Virtanen, S. M., Rasanen, L., Tuomilehto, J., Stengard, J. and Pekkanen, J. et al. (1995) Dietary factors determining diabetes and impaired glucose tolerance. A 20-year follow-up of the Finnish and Dutch cohorts of the Seven Countries Study. Diabetes Care 18 (8), 1104–1112. 48. Marshall, J. A., Hoag, S., Shetterly, S. and Hamman, R. F. (1994) Dietary fat predicts conversion from impaired glucose tolerance to NIDDM. The San Luis Valley Diabetes Study. Diabetes Care 17 (1), 50–56. 49. Storlien, L. H., Pan, D. A., Kriketos, A. D., O’Connor, J., Caterson, I. D. and Cooney, G. J. et al. (1996) Skeletal muscle membrane lipids and insulin resistance. Lipids 31 (Suppl.), S261–S265. 50. Vessby, B., Aro, A., Skarfors, E., Berglund, L., Salminen, I. and Lithell, H. (1994) The risk to develop NIDDM is related to the fatty acid composition of the serum cholesterol esters. Diabetes 43, 1353–1357. 51. Vessby, B., Unsitupa, M., Hermansen, K., Riccardi, G., Rivellese, A. A. and Tapsell, L. C. et al. (2001) Substituting dietary saturated for monounsaturated fat impairs insulin sensitivity in healthy men and women: the KANWU Study. Diabetologia 44 (3), 312–319. 52. Feskens, E. J., Loeber, J. G. and Kromhout, D. (1994) Diet and physical activity as determinants of hyperinsulinemia: the Zutphen Elderly Study. Am J Epidemiol 140 (4), 350–360. 53. Mayer-Davis, E. J., Monaco, J. H., Hoen, H. M., Carmichael, S., Vitolins, M. Z. and Rewers, M. J. et al. (1997) Dietary fat and insulin sensitivity in a triethnic population: the role of obesity. The Insulin Resistance Atherosclerosis Study (IRAS). Am J Clin Nutr 65 (1), 79–87.

314

DIETARY FACTORS AND INSULIN RESISTANCE

54. Salmeron, J., Hu, F. B., Manson, J. E., Stampfer, M. J., Colditz, G. A. and Rimm, E. B. et al. (2001) Dietary fat intake and risk of type 2 diabetes in women. Am J Clin Nutr 73 (6), 1019–1026. 55. Storlien, L. H., Jenkins, A. B., Chisholm, D. J., Pascoe, W. S., Khouri, S. and Kraegen, E. W. (1991) Influence of dietary fat composition on development of insulin resistance in rats. Relationship to muscle triglyceride and omega-3 fatty acids in muscle phospholipid. Diabetes 40 (2), 280–289. 56. Adler, A. I., Boyko, E. J., Schraer, C. D. and Murphy, N. J. (1994) Lower prevalence of impaired glucose tolerance and diabetes associated with daily seal oil or salmon consumption among Alaska Natives. Diabetes Care 17 (12), 1498–1501. 57. Simopoulos, A. P. (1999) Essential fatty acids in health and chronic disease. Am J Clin Nutr 70 (Suppl. 3), 560S–569S. 58. Grimble, R. F. (1998) Dietary lipids and the inflammatory response. Proc Nutr Soc 57 (4), 535–542. 59. Harris, W. S. (1996) n-3 fatty acids and lipoproteins: comparison of results from human and animal studies. Lipids 31 (3), 243–252. 60. Chambrier, C., Bastard, J. P., Rieusset, J., Chevillotte, E., Bonnefont-Rousselot, D. and Therond, P. et al. (2002) Eicosapentaenoic acid induces mRNA expression of peroxisome proliferator-activated receptor γ. Obes Res 10 (6), 518–525. 61. Hill, J. O. and Prentice, A. M. (1995) Sugar and body weight regulation. Am J Clin Nutr 62 (Suppl. 1), 264S–274S. 62. Bravata, D. M., Sanders, L., Huang, J., Krumholz, H. M., Olkin, I. and Gardner, C. D. et al. (2003) Efficacy and safety of low-carbohydrate diets. A systematic review. JAMA 289, 1837–1850. 63. Foster, G. D., Wyatt, H. R., Hill, J. O., McGuckin, B. G., Brill, C. and Mohammed, B. S. et al. (2003) A randomised trial of a low-carbohydrate diet for obesity. N Engl J Med 348, 2082–2090. 64. Salmeron, J., Manson, J. E., Stampfer, M. J., Colditz, G. A., Wing, A. L. and Willett, W. C. (1997) Dietary fiber, glycemic load, and risk of non-insulin-dependent diabetes mellitus in women. JAMA 277 (6), 472–477. 65. Thorburn, A., Muir, J. and Proietto, J. (1993) Carbohydrate fermentation decreases hepatic glucose output in healthy subjects. Metabolism 42, 780–785. 66. Karlstrom, B., Vessby, B., Asp, N. G., Boberg, M., Gustafsson, I. B. and Lithell, H. et al. (1984) Effects of an increased content of cereal fibre in the diet of type 2 (noninsulin-dependent) diabetic patients. Diabetologia 26, 272–277. 67. Juntunen, K. S., Laaksonen, D. E., Poutanen, K. S., Niskanen, L. K. and Mykkanen, H. M. (2003) High-fibre rye bread and insulin secretion and sensitivity in healthy postmenopausal women. Am J Clin Nutr 77, 385–391. 68. Juntunen, K. S., Niskanen, L. K., Liukkonen, K. H., Poutanen, K. S., Holst, J. J. and Mykkanen, H. M. (2002) Postprandial glucose, insulin and incretin responses to grain products in healthy subjects. Am J Clin Nutr 75, 254–262. 69. Meyer, K. A., Kushi, L. H., Jacobs, D. R., Slavin, J., Sellers, T. A. and Folsom, A. R. (2000) Carbohydrates, dietary fiber, and incident type 2 diabetes in older women. Am J Clin Nutr 71 (4), 921–930. 70. McKeown, N. M., Meigs, J. B., Liu, S., Wilson, P. W. F. and Jacques, P. F. (2002) Whole-grain intake is favourably associated with metabolic risk factors for type 2 diabetes and cardiovascular disease in the Framingham Offspring Study. Am J Clin Nutr 76, 390–398. 71. Fung, T. T., Hu, F. B., Pereira, M. A., Liu, S., Stampfer, M. J. and Colditz, G. A. et al. (2002) Whole-grain intake and the risk of type 2 diabetes: a prospective study in men. Am J Clin Nutr 76, 535–540.

REFERENCES

315

72. Pereira, M. A., Jacobs, D. R., Jr., Pins, J. J., Raatz, S. K., Gross, M. D. and Slavin, J. L. et al. (2002) Effect of whole grains on insulin sensitivity in overweight hyperinsulinemic adults. Am J Clin Nutr 75 (5), 848–855. 73. Reaven, G. M. (1997) Do high carbohydrate diets prevent the development or attenuate the manifestations (or both) of syndrome X? A viewpoint strongly against. Curr Opin Lipidol 8 (1), 23–27. 74. Wolever, T. M. and Bolognesi, C. (1996) Prediction of glucose and insulin responses of normal subjects after consuming mixed meals varying in energy, protein, fat, carbohydrate and glycemic index. J Nutr 126 (11), 2807–2812. 75. Kiens, B. and Richter, E. A. (1996) Types of carbohydrate in an ordinary diet affect insulin action and muscle substrates in humans. Am J Clin Nutr 63, 47–53. 76. Frost, G. (1996) The effect of low-glycaemic carbohydrate on insulin and glucose response in vivo and in vitro in patients with coronary heart disease. Metabolism 45 (6), 669–672. 77. Farnsworth, E., Luscombe, N. D., Noakes, M., Wittert, G., Argyiou, E. and Clifton, P. M. (2003) Effect of a high-protein, energy-restricted diet on body composition, glycaemic control, and lipid concentration in overweight and obese hyperinsulinaemic men and women. Am J Clin Nutr 78, 31–39. 78. Lavigne, C., Tremblay, F., Asselin, G., Jacques, H. and Marette, A. (2001) Prevention of skeletal muscle insulin resistance by dietary cod protein in high fat-fed rats. Am J Physiol Endocrinol Metab 281 (1), E62–E71. 79. Stampfer, M. J., Colditz, G. A. and Willett, W. C. (1988) A prospective study of moderate alcohol drinking and risk of diabetes in women. Am J Epidemiol 128, 549–558. 80. Ajani, U. A., Hennekens, C. H. and Spelsberg, A. (2000) Alcohol consumption and risk of type diabetes mellitus among US male physicians. Arch Intern Med 160, 1025–1030. 81. Kao, W. H., Puddey, I. B. and Boland, L. L. (2001) Alcohol consumption and the risk of type 2 diabetes mellitus: atherosclerosis risk in communities study. Am J Epidemiol 154, 748–757. 82. Perry, I. J., Wannamethee, S. G., Walker, M. K., Thompson, A. G., Whincup, P. H. and Shaper, A. G. (1995) Prospective study of risk factors for development of non-insulin dependent diabetes in middle-aged British men. BMJ 310, 560–564. 83. Cordain, L., Melby, C. L., Hamamoto, A. E., O’Neill, D. S., Cornier, M. A. and Barakat, H. A. et al. (2000) Influence of moderate chronic wine consumption on insulin sensitivity and other correlates of syndrome X in moderately obese women. Metab: Clin Exp 49 (11), 1473–1480. 84. Salonen, J. T., Nyyssonen, K., Tuomainen, T. P., Maenpaa, P. H., Korpela, H. and Kaplan, G. A. et al. (1995) Increased risk of non-insulin dependent diabetes mellitus at low plasma vitamin E concentrations: a four year follow up study in men. BMJ 311 (7013), 1124–1127. 85. Reunanen, A., Knekt, P., Aaran, R. K. and Aromaa, A. (1998) Serum antioxidants and risk of non-insulin dependent diabetes mellitus. Eur J Clin Nutr 52 (2), 89–93. 86. Facchini, F. S., Humphreys, M. H., DoNascimento, C. A., Abbasi, F. and Reaven, G. M. (2000) Relation between insulin resistance and plasma concentrations of lipid hydroperoxides, carenoids and tocopherols. Am J Clin Nutr 72 (3), 776–779. 87. Facchini, F., Coulston, A. M. and Reaven, G. M. (1996) Relationship between dietary vitamin intake and resistance to insulin-mediated glucose disposal in healthy volunteers. Am J Clin Nutr 63 (6), 946–949. 88. Salmeron, J., Ascherio, A., Rimm, E. B., Colditz, G. A., Spiegelman, D. and Jenkins, D. J. et al. (1997) Dietary fiber, glycemic load, and risk of NIDDM in men. Diabetes Care 20 (4), 545–550.

316

DIETARY FACTORS AND INSULIN RESISTANCE

89. Anderson, R. A., Polansky, M. M., Bryden, N. A. and Canary, J. J. (1991) Supplemental-chromium effects on glucose, insulin, glucagon and urinary chromium losses in subjects consuming controlled low-chromium diets. Am J Clin Nutr 54, 909–916. 90. Anderson, R. A., Cheng, N., Bryden, N. A., Polansky, M. M., Chi, J. and Feng, J. (1997) Elevated intakes of supplemental chromium improve glucose and insulin variables in individuals with type 2 diabetes. Diabetes 46, 1786–1791. 91. Vincent, J. B. (2000) The biochemistry of chromium. J Nutr 130, 715–718. 92. Boer, J. M., Feskens, E. J., Schouten, E. G., Havekes, L. M., Seidell, J. C. and Kromhout, D. (1998) Lipid profiles reflecting high and low risk for coronary heart disease: contribution of apolipoprotein E polymorphism and lifestyle. Atherosclerosis 136 (2), 395–402.

12 Physical Activity and Insulin Resistance Nicholas J. Wareham, Søren Brage, Paul W. Franks and Rebecca A. Abbott

12.1 Introduction The past 20 years has seen an explosion of interest in the relationship between physical activity and insulin resistance. These studies have addressed not only whether there is an association and how strong it is, but also the mechanisms that may underlie it. This chapter takes a predominantly epidemiological approach to describing this association, and our concentration is on a systematic review of studies that have quantified the relationship between activity and/or fitness and insulin resistance. The level of causal inference from these studies varies and, as in all other areas of epidemiological enquiry, can be assessed by reference to the classic Bradford Hill criteria.1 These include assessment of the strength and consistency of the association, the degree of dose–response effect and biological plausibility. The demonstration of reversibility in a clinical trial contributes massively to causal inference and also points the way for preventive efforts. A key question in the context of the design of preventive strategies is whether the association of inactivity with insulin resistance is similar in all individuals. If it is, then a population-wide preventive strategy would be most appropriate. However, if sub-populations were demonstrably more at risk of the metabolic consequences of sedentary living, then targeted prevention would be a logical strategy. Thus in this chapter we consider the evidence for heterogeneity of association between different sub-groups in the population. The chapter concludes with a discussion of major unresolved uncertainties and areas of future enquiry. Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

318

PHYSICAL ACTIVITY AND INSULIN RESISTANCE

12.2

Evidence from observational studies of the association between physical activity and insulin resistance

Rather than only present data from papers that support the theory that physical activity is protective against the development of insulin resistance, we have elected to undertake a more systematic summary. In describing the studies, we have separated studies in adults (Table 12.1) from those in children and adolescents (Table 12.2). We excluded studies with fewer than 50 adult participants. We have only included those studies that have a measure of insulin resistance, either from a euglycaemic hyperinsulinaemic clamp or more indirectly from insulin measurement at fasting or in an intravenous or oral glucose tolerance test. This focus on insulin measurement excludes those studies where the outcome of interest is related to insulin resistance such as measures of glucose homeostasis or the metabolic syndrome.

12.3 Summary of findings from observational studies in adults Table 12.1 shows that a total of 39 cross-sectional studies relating an assessment of physical activity or fitness to a measure of insulin sensitivity were identified. Thirty-four of these studies demonstrated that some dimension of physical activity was inversely associated with fasting insulin or other proxy measures of insulin resistance. None of the studies found the association to be in the opposite direction and four of the five inconclusive studies were either small (Ross2 (n = 50), Palaniappan et al.3 (n = 207), Parker et al.4 (n = 358)) or used a global assessment of activity,5 which may have resulted in non-differential misclassification and attenuation of the true association. Thus, overall the data suggests that the finding of an inverse association between activity and insulin resistance is strong and consistent between studies. In 30 of these cross-sectional studies self-reported or interviewer administered physical activity questionnaires were used as the main measure of activity. This concentration on self-report assessment introduces the possibility of recall bias. This is less likely to be a direct phenomenon than it would be in a study where individuals with a diagnostic label were being compared with those without, since people with insulin resistance would tend to be unaware of their condition. Direct bias of this nature would be much more likely if people with and without diabetes were being compared, for example. However, it is more likely in this context that self-report is biased with respect to obesity, which would in turn create a bias with respect to the outcome of insulin resistance since the relationship between obesity and insulin sensitivity is so strong. Adjustment for obesity whilst removing its effect as a confounder would not deal with the issue of associated recall bias.

Nested case–control study in a longitudinal study To assess the association between incident hyperinsulinemia and sports-related physical activity

To determine differences in fasting insulin between inactive and active groups of lean and obese people

124

125

Reference

Objective of study

N (m/f): 115/0 Age: 47–49 years BMI: Nationality: Swedish

Cases: N (m/f): 380/469 BMI (SD): 29.4 (4.8) Age: 53.6 (5.7) years Ethnicity: 28.2% Black Controls: N (m/f): 3268/4457 BMI: 26.3 (4.4) Age: 53.7 (5.7) Ethnicity: 17.0% Black

Participant characteristics

Measure of insulin resistance

Fasting insulin Case definition: insulin >19.08 µU/ml

Saltin Questionnaire

Fasting insulin

Cross-sectional studies

Leisure-time PA by Baecke Questionnaire Coded into 5 levels

Case–control studies

Measure of physical activity

Stratified by obesity Separate analysis on work activity and leisure-time activity

BMI

Confounders adjusted for

(continues overleaf )

Lean groups: no difference between active and inactive individuals Obese groups: significantly lower fasting insulin in active compared to inactive individuals

OR = 0.98 (NS)

Direction and magnitude of effect

Table 12.1 Observational studies of the relationship between physical activity and insulin resistance in adults SUMMARY OF FINDINGS FROM OBSERVATIONAL STUDIES IN ADULTS

319

To assess whether higher level of METh/week was associated with lower fasting insulin level

To assess the association between LTPA and insulin

126

127

Reference

Objective of study

Subjective assessment of leisure-time and occupational activity (Stanford 7d PA recall)

Questionnaire on past 2 week LTPA

N (m/f): 0/641 Age: 50–89 years BMI: 24 Ethnicity: Caucasians

Measure of physical activity

N (m/f): 442/489 Age: 21–75 years BMI: 25 Ethnicity: Hispanic and non-Hispanic Caucasians

Participant characteristics

Fasting and 2 h insulin during an OGTT

Fasting insulin

Measure of insulin resistance

Table 12.1 (continued )

Age, fasting glucose, BMI, WHR, sum of skin fold, ethnicity, MABP, smoking, angina

Confounders adjusted for

Inverse relationship between insulin and activity during leisure time (p < 0.05) but not during work Men: β = −0.0008; p = 0.0027, for METh/week on insulin Women: β = −0.0003; p = 0.6027, for METhr/wk on insulin Inverse association between PA level and fasting (p < 0.002) and 2 h insulin (p < 0.001)

Direction and magnitude of effect

320 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

To assess the association between PA and fitness and insulin

To assess the association between PA and insulin

128

129

Modified Minnesota Questionnaire LTPA Fitness by duration on a graded treadmill test

Questionnaire on past 4 week PA Coded into four levels and also into two (doing regular heavy exercise or not)

N (m/f): 2058/2533 Age: 25 (18–30) years BMI: 24.4 Ethnicity: Caucasians and Blacks

N (m/f): 283/499 Age: 77.5 (5.5) years BMI: 25.7 (4.3) Ethnicity: Caucasians (New Zealand)

2 h insulin after standard meal (containing 100 g CHO, 30 g fat and 30 g protein)

Fasting insulin

Stratified by sex Participants taking insulin and hypoglycemic drugs excluded

Adjusted for age and BMI Stratified by sex and ethnicity

(continues overleaf )

Inverse association between self-reported heavy PA and insulin in men only (p < 0.05) Inverse association between fitness and insulin in all strata (p < 0.01) except black women 22% lower insulin levels in women doing regular heavy exercise (p < 0.005) but no difference in men

SUMMARY OF FINDINGS FROM OBSERVATIONAL STUDIES IN ADULTS

321

To assess the association between METhrs/wk and insulin level

To assess the association between PA and CHD risk factors

To assess the association between PA and insulin

130

131

132

Reference

Objective of study Leisure-time and occupational activity measured by Stanford 7d PA recall

Questionnaire Coded into binary variable: active = participation in PA ≥ once a week

Subjective assessment of leisure-time and occupational activity (Stanford 7d PA recall)

N (m/f): 551/669 Age: 15–24 years Mean BMI (SD): 21.4 (3.0) Nationality: Finnish

N (m/f): 819/1159 Age: 35–64 years BMI: Ethnicity: Mexican Hispanics

Measure of physical activity

N (m/f): 219 Age: 31–76 years BMI: 28.1 Ethnicity: Hispanics and non-Hispanic Caucasians

Participant characteristics

OGTT–fasting and post-challenge insulin

Fasting insulin

OGTT–fasting and post-challenge insulin

Measure of insulin resistance

Table 12.1 (continued )

Age, fasting glucose, BMI, WHR, sum of skin fold, ethnicity, hypertension, smoking, angina, oestrogen therapy Stratified by gender Adjusted for butter use, alcohol use, smoking status, oral contraceptive use (all binary) and BMI (continuous) Stratified by sex

Confounders adjusted for

No uni-variate relationship in men (fasting and 2 h insulin) Adjustment for confounders not performed in men

Inverse relationship in males: insulin 1.53 mU lower in active vs inactive (p < 0.001) No association in females

β = −0.0034; p = 0.0001, for METh/week on insulin

Direction and magnitude of effect

322 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

To assess the association between cardiovascular risk factors To evaluate the relationship between physical fitness and early and late insulin response as predictors of type 2 diabetes mellitus

134

135

To assess the association between central obesity, PA, and insulin

133

Questionnaire on leisure and occupational PA Coded into four levels

Questionnaire about leisure time PA Coded into four levels Subjective (PA index)

N (m/f): 80/72 Age: 26–65 years BMI: 22 (3) Ethnicity: Asian Indian (Urban North India)

N (m/f): 504/548 Age: 40 years BMI: Nationality: Danish

N (m/f): 4637/0 Age: 48–54 years BMI: Ethnicity: Caucasian

OGTT–fasting and post-challenge insulin

OGTT–fasting and post-challenge insulin

Fasting and post-challenge plasma insulin

None

Stratified by sex

Analysis presented for quintiles of waist–hip girth ratio (W/H)

(continues overleaf )

Inverse relationship in women (r = −.07, p < 0.05 for fasting insulin and r = −0.10, p < 0.0001 for 2 h insulin) Inverse association between PA and W/H ratio Direct association between insulin levels and W/H ratio Inverse association in men (p = 0.01) No significant association in women Inverse correlation between PA and late insulin response (r = −0.42; p < 0.0001)

SUMMARY OF FINDINGS FROM OBSERVATIONAL STUDIES IN ADULTS

323

To assess the association between insulin sensitivity and fitness

To assess the likelihood of being NGT, IGT and T2DM, based on level of PA

To assess the relationship between CV fitness and insulin level in coronary patients and healthy subjects

136

5

137

Reference

Objective of study

Questionnaire assessment of occupational and leisure-time PA (divided into sedentary, light, moderate, heavy categories) VO2 max

N (m/f): 1020 (∼50% m/f) Age: 40 (12) years BMI: 22.3 (4.3) Ethnicity: Urban Asian Southern Indians

Coronary patients: N (m/f): 0/20 Age: 66 (6) years BMI: 28.8 (4.7) Healthy subjects: N (m/f): 0/50 Age: 68 (6) years BMI: 24.9 (3.7)

Submaximal bicycle test

Measure of physical activity

N (m/f): 186/194 Age: 25.2 (3.5) years BMI: 23.6 (3.7) Nationality: Danish

Participant characteristics

Age, sex, BMI, WHR, family history (of DM), interaction terms where appropriate

Weight, height, waist, WHR, %body fat, %lean body mass, BMI Analyses also stratified by group

Fasting serum insulin

Stratified by sex

Confounders adjusted for

OGTT–fasting and post-challenge insulin

IVGTT

Measure of insulin resistance

Table 12.1 (continued )

No significant association in the patients, the healthy subjects or when combined

Positive relationship between insulin sensitivity and fitness in men (r = 0.44, p < 0.001) and women (r = 0.32, p < 0.001) No association between level of PA and risk of insulin resistance status

Direction and magnitude of effect

324 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

To assess the association between exercise training (METs) and SI

To assess the relative relationships of cardiorespiratory fitness and PAEE on fasting insulin and other factors To assess the association between PA and fasting insulin

139

140

141

To assess the association between vigorous PA and hyper-insulinaemia

138

N (m/f): 515/0 Age: 40–49 years BMI: Ethnicity:

Subjective assessment of leisure-time and occupational activity

N (m/f): 660/807 Age: 55.6 (8.4) years BMI: 29.3 (5.8) Ethnicity: African-Americans, Hispanics, Non-Hispanic Caucasians N (m/f): 53/63 Age: 67 (8) years BMI: 24.8 (3) Ethnicity: Caucasians

Questionnaire – usual pattern of recreational activity (with some reference made to occupational activity) Divided into 5 categories of activity level

Doubly labelled water and indirect calorimetry

Subjective assessment of leisure-time and occupational activity

N (m/f): 632/719 Age: 51.8 (12.1) years BMI: 25.5 (4.2) Ethnicity: Hispanics and Non-Hispanic Caucasians

Fasting insulin

Fasting insulin

IVGTT

Fasting insulin

Age, BMI, SES, smoking, heavy drinking, existing CHD

Three-way analysis of covariance adjusted for age

Age, sex, ethnicity, clinic, alcohol intake, smoking, energy intake from fat, hypertension

(continues overleaf )

Inverse association between PA and fasting insulin from 94 to 79 pmol/l p < 0.001 (for trend)

Inverse association between CV fitness and insulin (p < 0.01) but not PAEE (p = 0.081)

Absence of self-report vigorous activity was associated with hyper-insulinaemia (p = 0.002) Positive correlation for TEE with SI (r = 0.14; p < 0.001) and log fasting insulin (r = −0.07; p < 0.01)

SUMMARY OF FINDINGS FROM OBSERVATIONAL STUDIES IN ADULTS

325

To assess the association between physical activity and insulin sensitivity in postmenopausal women

To assess the association between PA and fasting insulin

9

142

Reference

Objective of study Subjects were classified as either sedentary (n = 18), physically active (n = 19) or athletic (n = 23) Fitness (VO2 max ) by maximal treadmill test

The Modifiable Physical Activity Questionnaire (the Pima Indian Questionnaire) Interviewer administered assessment of current and past PA

N (m/f): 231/299 Age: 18–79 years BMI: 28 Ethnicity: Native Canadian Indians

Measure of physical activity

N (m/f): 0/60 Age: 64 (5) years BMI: 23.3 (3) Nationality: American

Participant characteristics

Fasting insulin

IVGTT

Measure of insulin resistance

Table 12.1 (continued )

Stratified by sex Adjusted for age, BMI (or BF%) and waist circumference

Body composition (DXA) and BMI

Confounders adjusted for

Positive relationship between PA and IS (p = 0.06) and an inverse association between PA and fasting insulin (p = 0.036) Both these relationships were unaltered by adjustment The relationship between fitness and IS was also positive (r = 0.35, p = 0.007) Inverse association between total PA (METhrs/wk) and fasting insulin (mmol/l) Men: −0.039; p = 0.014 Women: 0.015; p = 0.288

Direction and magnitude of effect

326 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

To assess the association between PA and fasting insulin in high risk (of DM) populations

To assess the association between PAL and fasting plasma insulin level

143

144

The Modifiable Physical Activity Questionnaire (the Pima Indian Questionnaire) Interviewer administered assessment of current and past PA

PA by flex HR method (4 days)

N (m/f): 2277/2750 Age: 15–59 years BMI: Ethnicity: Pima Indians and Mauritian Islanders

N (m/f): 375/440 Age: 31–71 years BMI: 28.1 Ethnicity: UK Caucasians Fasting insulin

Fasting insulin

Adjusted for total dietary fat, total energy intake, BMI, waist-to-hip ratio, age, sex, family history of diabetes, smoking status, alcohol intake

Stratified by sex and ethnicity Adjusted for age, BMI, waist/thigh ratio, mean plasma glucose

(continues overleaf )

Inverse association between total PA (METh/week) and fasting insulin (pmol/l) Pima: men (n = 1007) −0.017; p =< 0.001, women (n = 1314): −0.01; p = 0.018 Mauritian: men (n = 1270) −0.019; p =< 0.001, women (n = 1446): −0.011; p < 0.001 Inverse association (β = −0.13; p = 0.007)

SUMMARY OF FINDINGS FROM OBSERVATIONAL STUDIES IN ADULTS

327

145

Reference

To assess relationship between PA and insulin in civil servants

Objective of study

N (m/f): 498/301 Age: 41 (8) years BMI: 22.9 (4) Ethnicity: Black (Nigeria)

Participant characteristics Interviewer administered questionnaire (Kriska) for past year leisure and occupational activity, including time spent walking or biking to work

Measure of physical activity Fasting insulin

Measure of insulin resistance

Table 12.1 (continued )

Stratified by sex Univariate analysis for all activity components. Analysis of time spent walking or biking to work adjusted for age, BMI and waist girth

Confounders adjusted for

In both men and women, there were no significant associations between insulin and occupational, leisure time or total activity In men, there was an inverse association between insulin and time spent walking or biking to work (r = −0.21, p < 0.001) but this was attenuated by adjustment (standardized β = −0.07, p = 0.133) In women, this relationship was non-significant in either analysis

Direction and magnitude of effect

328 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

To assess relationship between PA and insulin sensitivity among people with normal and impaired GT

To examine the association between different intensities of PA with metabolic syndrome in 3 female ethnic groups

146

147, 148

Interviewer administered 1 year recall of PA

PA records detailing past 4 consecutive days of activity, completed twice at 1 month interval

N (m/f): 456/551 Age: 55 years BMI: 28.5 Ethnicity: Hispanics, non-Hispanic Whites, African-Americans

N (m/f): 0/142 Age: 40–83 years BMI: Ethnicity: African-American (n = 47), Native American (n = 46), White (n = 49) Fasting insulin

IVGTT

Age, ethnicity, menopause, HRT, study centre

Stratified by NGT and IGT groups Adjusted for age, sex, ethnicity, clinical centre, total energy intake

(continues overleaf )

Acute insulin response (AIR) and disposition index (DI) Inconsistent directions of association across groups and outcome variables All associations NS, except for % change in DI in IGT group: β = 4.04; p ≤ 0.05 An increase of 30 min moderate intensity PA was associated with a decrease in insulin of 6.6% (p < 0.05)

SUMMARY OF FINDINGS FROM OBSERVATIONAL STUDIES IN ADULTS

329

To assess the association between insulin sensitivity and heart rate recovery after exercise

To assess the association between PA and fasting serum insulin

149

150

Reference

Objective of study

N (m/f): 515/115 Age: 42 (SD 2.0) years BMI: Ethnicity: 71.6% Caucasians

N (m/f): 70/0 Age: 70 years BMI: Nationality: Swedish

Participant characteristics Fitness by heart rate recovery (HRR) after maximal symptom-limited bike test. HRR was positively related to maximal workload (r = 0.37) and inversely related to mean HR during the test (r = −0.33) and resting HR (r = −0.27) Questionnaire (Baecke) – sports, leisure and occupational

Measure of physical activity

Fasting insulin

Hyperinsulinemic euglycemic clamp

Measure of insulin resistance

Table 12.1 (continued )

Unadjusted

Unadjusted

Confounders adjusted for

Inverse correlation between PA and insulin (sports r = −0.16, p < 0.01; leisure r = −0.075 (NS); work r = .053 (NS) Difference of 2.1 µU/ml between highest PA quartile and lower 3 Q (p = 0.046) in men only

Positive relationship between HRR and insulin sensitivity (r = 0.29, p < 0.05) HRR and BMI were inversely associated (r = −0.31, p < 0.01)

Direction and magnitude of effect

330 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

To assess whether exercise modulates age-related decline in insulin sensitivity

To assess the relationship between PA and multiple risk factors of the insulin resistance syndrome

151

152

Self-report activity level

Four questions relating to OPA, LTPA, TV viewing, computer useage.

N (m/f): 65/61 Sedentary Young: 21–35 (m/f: 13/12) Older: 50–80 (m/f: 20/23) BMI: Endurance trained Young: 21–35 (m/f: 12/13) Older: 50–80 (m/f: 20/13) BMI: Ethnicity:

N (m/f): 554/866 Age: 20–38 years BMI: Ethnicity: Afro-American (35%) and Caucasian (65%)

Non-fasting HOMA

IVGTT

Age, ethnicity, sex

Age, sex

(continues overleaf )

ISI values were lower in the older vs young adults in both sedentary (−53%; 3.9 + / − 0.3 vs 7.0 + / − 0.7 × 10−4 /min/µU/ml; p < 0.01) and endurance-trained (−36%; 7.9 + / − 0.6 vs 12.4 + / − 1.0 × 10−4 /min/µU/ml; p < 0.01) groups, but the value was 72–102% higher in the trained subjects at either age (p < 0.01) IRI was inversely related with leisure-time activity (p < 0.01) and positively related with hours of inactivity (p < 0.01)

SUMMARY OF FINDINGS FROM OBSERVATIONAL STUDIES IN ADULTS

331

To assess the association between PA patterns and 2 hour insulin in different ethnic cohorts

To assess the association between LTPA and insulin sensitivity

To assess CVD risk factors in young women, and to make cross cultural comparisons

153

63

3

Reference

Objective of study PA index

Four question self-report

Lifestyle questionnaire

N (m/f): 475/0 Age: BMI: Ethnicity:

N (m/f): 0/207 Age: 20 (2) years BMI: Ethnicity: African-American (n = 69), Asian Indian-American (n = 70), Caucasian (n = 68)

Measure of physical activity

N (m/f): 699/699 Age: 25–75 years BMI: Ethnicity: Caucasians (n = 749), South-East Asian (SEA) (n = 659)

Participant characteristics

Fasting insulin

ISI by euglycaemic hyperinsulinaemic clamp

2 h insulin

Measure of insulin resistance

Table 12.1 (continued )

BMI, W:H ratio, waist circ., IGT, BP, drug treatment, smoking) None

Age Stratified by sex and ethnicity

Confounders adjusted for

Inverse correlations between insulin and PA: male/Caucasian (r = −0.08, p = NS), SEA (r = −0.15, p = 0.01); female/Caucasian (r = −0.1, p = 0.05), SEA (r = −0.2, p = 0.001) Inverse association between PA and ISI (M/I) (β = −0.08; p = 0.02) No assessment of association between PA and insulin level

Direction and magnitude of effect

332 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

156

155

154

To investigate the association between LPTA and insulin resistance, and to explore whether twinship modifies this effect To explore the relative importance of diet and PA in cardiovascular risk To examine the potential for effect modification by fitness and LTPA of the relationship between birth weight/length and metabolic syndrome Allied Dunbar LTPA questionnaire

Doubly labelled H2 O (n = 73) and CSA/MTI actigraph Kuopio LTPA questionnaire

N (m/f): 0/798 twins Age: 44.6 (12.6) years BMI: Ethnicity:

N (m/f): 63/67 Age: 35–49 years BMI: Ethnicity: Chinese

N (m/f) 462/0 Age: 51 (6.4) years BMI: Ethnicity: Finnish Caucasian QUICKI

Fasting insulin

HOMA

Interaction between birth weight and LPTA (above/below median) adjusted for age

Diet, body composition, sex, smoking, alcohol intake

Age

(continues overleaf )

PAL was inversely associated with fasting insulin level (β = 0.62; p < 0.05) In active men no association between ponderal index and metabolic syndrome was observed, whereas in inactive men a significant (p = 0.033) and inverse association was observed

LTPA was associated with lower fasting insulin (5.5; 95% CI 5.2–5.9 vs 6.2 95% CI 6.0–6.5 mIU/l) (p = 0.002)

SUMMARY OF FINDINGS FROM OBSERVATIONAL STUDIES IN ADULTS

333

To assess the association between PA and insulin

158

4

To investigate the relationship between different types and levels of PA and insulin resistance, in a healthy female population in China To investigate the determinants of the insulin resistance/metabolic syndrome

157

Reference

Objective of study MOSPA questionnaire

Health and Lifestyle Questionnaire

Questionnaire on past year LTPA Coded into METhrs/wk

N (m/f): 154/204 Age: 49–51 years BMI: Ethnicity: Caucasian

N (m/f): 405/454 Age: 25–75 years BMI: 24.7 Nationality: American

Measure of physical activity

N (m/f): 0/761 Age: 35–65 years BMI: Ethnicity: Chinese (Guangdong Province)

Participant characteristics

Fasting plasma insulin measured on a sub-set of 695 individuals

Fasting and 2 h insulin

Fasting serum insulin (Fasting insulin resistance index: ‘a multiplication value of fasting insulin and fasting glucose by 25’)

Measure of insulin resistance

Table 12.1 (continued )

Age, sex, BMI, smoking status, alcohol intake, NSAID use, dietary fat intake, television watching and interaction with sex for all listed

Age, sex, smoking, alcohol use

Age, menopause, tea, BMI, dietary energy, cholesterol intake, dietary fatty acid composition, dietary antioxidants

Confounders adjusted for

PA was not significantly associated with metabolic syndrome in men or women Inverse relationship between PA and insulin (β = −0.317 µU/ml for every 20 MET-hrs/wk increase, p = 0.04)

Mean (SD) fasting insulin resistance index in low, moderate and high total PA groups: 2.43 (0.07), 2.00 (0.04), 2.26 (0.03); p < 0.001

Direction and magnitude of effect

334 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

To assess whether the association between PA and insulin was modified by P:S ratio and PPARγ genotype

To assess the association between changes in insulin and PA during 11 year follow-up

112

159

N (m/f): 425/0 Baseline age: 45 years Mean BMI: Nationality: Danish

N (m/f): 226/280 Age: 31–71 years BMI: 27 (5) Ethnicity: UK Caucasians Fasting plasma insulin

Questionnaire LTPA coded into three levels

Fasting serum insulin

Longitudinal cohort studies

PA by flex HR method (4 days)

Unclear

Adjusted for age, sex, BMI, and P:S ratio Analysis also stratified by genotype (Pro12Ala SNP)

(continues overleaf )

Change in PA was not related to change in insulin (p = 0.32 for univariate, p = 0.64 for multivariate) At both time points, there was an inverse association between PA and insulin (p ≤ 0.02)

Inverse association between PA and insulin (β = −0.13; p = 0.005) No interaction between PA and P:S ratio in Pro/Pro but significant interaction in Ala carriers (p = 0.038)

SUMMARY OF FINDINGS FROM OBSERVATIONAL STUDIES IN ADULTS

335

To characterize 7 year changes in fasting serum insulin, and to assess the effects of PA on insulin resistance

To assess the association between physical activity and fasting insulin at age 50 and age 70

160

161

Reference

Objective of study

At age 50 years: N (m/f): 1860/0 BMI: 24.9 (3.2) At age 70 years: N (m/f): 898/0 BMI: 26.1 (3.3) Ethnicity: Swedish

N (m/f): 1486/1609** Age: 18–30 years** BMI: 24.4* Ethnicity: Afro-Americans and Caucasians *Baseline; **follow-up

Participant characteristics

Questionnaire about leisure time PA (four levels)

Short version Minnesota PA history

Measure of physical activity

Fasting specific insulin

Fasting insulin

Measure of insulin resistance

Table 12.1 (continued )

Weight change

Stratified by sex and ethnicity Adjusted for age, BMI, WHR, family history DM

Confounders adjusted for

β coefficients (µU/ml/100 unit of PA) Black male = −0.20; p < 0.05 Black female = −0.25; p < 0.05 White male = −0.30; p < 0.05 White female = −0.13; p < 0.05 Borderline significant inverse association between change in insulin and change in PA (−7.7%/PA level change, p = 0.072, n = 405)

Direction and magnitude of effect

336 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

162

To assess the association between LTPA and CV fitness with metabolic syndrome

N (m/f): 612/0 Age: 51 (6.4) years BMI: Ethnicity: Finnish Caucasian Kuopio LTPA questionnaire

Fasting insulin

Adjusted for age, smoking, socio-economic status, BMI, alcohol)

This association disappeared after adjustment for weight change At both time points, there was an inverse association between PA and insulin (r = −0.07 and r = −0.09, respectively, both p < 0.05) after adjustment for age and BMI Men engaging in > 3 h/week moderate or vigorous LTPA had half the risk of developing metabolic syndrome (p = 0.058)

SUMMARY OF FINDINGS FROM OBSERVATIONAL STUDIES IN ADULTS

337

338

PHYSICAL ACTIVITY AND INSULIN RESISTANCE

Only nine studies used objective measurement; in five studies measures of cardio-respiratory fitness were made, including two studies that also reported the use of a physical activity questionnaire. Four studies assessed energy expenditure objectively: two using doubly labelled water and the others individually calibrated heart rate monitoring. This focus on subjective measurement is in keeping with much of the literature relating physical activity to other health endpoints. Although self-report measures are sufficient to demonstrate a crude association, they do not allow the sub-dimensions of activity to be disentangled, nor do they allow quantification of the relationship between activity and insulin resistance.

How large is the effect of activity on insulin resistance? A key question from these observational studies is how much difference in insulin resistance is associated with a given difference in physical activity. Such a question would normally be addressed by a meta-analysis of the measures of association from observational studies or clinical trials. In the context of the effect of physical activity on glucose tolerance, Boule and colleagues6 have produced such an analysis, suggesting that the equivalent of 30 minutes of activity two or three times per week is associated with a difference of 0.66% in HbA1c. Although this type of analysis gives a sense of the magnitude of the overall effect, it is probably inaccurate since there is considerable difference between studies in how physical activity is assessed. Therefore, on the exposure side one runs the risk of adding together apples and pears. The issue with a meta-analysis of physical activity on insulin resistance is that there is not only a problem with differences in how the exposure is measured, but also in how the outcome is assessed with little consistency between studies in how insulin resistance is quantified.

Which dimension of physical activity is most closely associated with insulin resistance? Physical activity, like nutrition, is not a simple uni-dimensional exposure, but is complex, multi-dimensional and, perhaps most importantly, difficult to measure.7 Thirty of the 39 studies in Table 12.1 only used simple estimates of physical activity from self-report questionnaires. These are usually focused on recreational or leisure-time activity since this is easier to recall and in some studies may be the element of activity that is most different between individuals, especially when cohorts are socially homogeneous or occupationally defined. This focus on self-reported recreational activity leaves many questions unanswered. It is uncertain, for example, whether the associations observed are a reflection

SUMMARY OF FINDINGS FROM OBSERVATIONAL STUDIES IN ADULTS

339

of a true relationship between differing levels of vigorous activity or energy expenditure with insulin resistance. This uncertainty is problematic as it creates difficulties in translating epidemiological observations into preventive action. If the association is truly closer with energy expenditure, then the appropriate preventive strategy would be aimed at increasing that dimension of activity by encouraging increases in any form of activity. If however, the association is closest with vigorous activity, then the public health response would be different since the goal would be to increase participation in more intensive activities. Leaving aside issues of the ease with which these alternative goals can be achieved, it is important that this question is resolved since focusing on the wrong dimension of activity could have counter-intuitive consequences. This would be especially true if there were evidence to suggest that interventions aimed at increasing vigorous activity did not result in increased energy expenditure, an issue sometimes referred to as compensation.8

Can the association of different sub-dimensions of activity with insulin resistance be disentangled in an observational study? The possibility of different associations of vigorous activity and overall energy expenditure raises the question as to whether this issue can be resolved in an observational study. Is it possible, for example, to use observational data to simulate the situation in a trial where overall activity remains constant whilst the amount of vigorous activity or cardio-respiratory fitness is increased, or vice versa? To address such a question a study would need not only to incorporate a measure of both exposures, but also to have an understanding of the relative precision with which both are assessed. Only three of the studies reported in Table 12.1 reported measures of both total activity and cardio-respiratory fitness. In one of these,9 the measure of fitness was objective and relatively precise (VO2 max assessment during a treadmill test) compared with that of activity, which was by simple global assessment. In general, poorly measured exposures result in attenuation of the true effect, so one would anticipate that a difficult to measure but important exposure would appear to be less strongly associated with the outcome than an easily quantified but truly less strongly associated exposure. Without knowing the relative precision of exposure measurement, one would come to the wrong conclusion as to which was more important from an aetiological perspective. This problem would not be resolved by multivariate analysis, since the more precisely measured exposure would dominate and appear to contribute to a greater extent to the shared variance in the outcome. The appropriate epidemiological resolution to this issue is to undertake studies in which objective assessments of both exposures are made with a simultaneous estimation of their precision10 and complex modeling to remove the effects of bivariate measurement error.11

340

PHYSICAL ACTIVITY AND INSULIN RESISTANCE

Which comes first, inactivity or insulin resistance? The usual criticism of cross-sectional studies is that they shed no light on the direction of causality, as it is unclear whether the putative exposure, in this case physical activity, preceded the outcome, insulin resistance. From the crosssectional data alone, one would need to question whether it is possible that insulin resistance might, either directly or indirectly, lead to a decrease in physical activity. Although this may be unlikely, it is possible to postulate reasons why this may be the case. Thus, it would be preferable to have evidence from longitudinal cohort studies in which it was clear that the measurement of activity preceded that of insulin resistance. Compared with the number of cross-sectional studies, the literature relating activity and insulin resistance in cohort studies is much smaller, with a total of only four studies being identified. All of these studies used self-report measures of activity and change in fasting insulin as the outcome measured on at least two occasions over 6–20 years of follow-up. This literature is similar to that concerning the question of the links between activity and weight change, in which it has been extremely difficult to identify temporal sequence for two factors that probably change together. Those studies that have measured both factors over prolonged periods of time have been unable to disentangle which came first, particularly when they have considered the differences in precision of measurement of the two factors. In the case of insulin resistance and activity, the problem is even greater, since none of these studies employed repeated measures of activity and adjustments were made for change in obesity, which may constitute over-adjustment if changing body mass is part of the causal pathway leading from activity to insulin sensitivity. Thus, although the cohort study approach is held up as the methodological pinnacle of observational epidemiological study designs, its contribution to resolving issues of temporal sequence in the context of variables such as activity, weight and insulin resistance is probably rather limited, having much similarity to the issue of the chicken and the egg.

12.4 Summary of findings from observational studies in children and adolescents Table 12.2 describes the results of the systematic search for studies relating insulin resistance to exercise in children and adolescents. Fifteen cross-sectional studies were identified, seven of which reported a significant association of a measure of activity with insulin resistance. Another six reported significant associations of measures of fitness with insulin resistance and only two negative studies were published. Among the studies of activity and insulin sensitivity, only two reported the association in the opposite direction to that which was expected. In the first of these studies, Craig et al.12 showed that, although there was an overall positive relationship between activity and fasting

To describe the differences in mean fitness and IS in black compared with white children

To assess the difference in metabolic parameters between adolescent boys who attend sport clubs and those who do not

163

164

Reference

Objective of study

12 black prepubertal children (M/F 6/6) compared with 11 whites (M/F 7/4). Age 10.3 (0.2) years Mean BMI 17.7 Ethnicity: African-Americans and Whites N (m/f): 264/0 Age: 17–18 years Mean BMI: 20.7 (2.3) and 21.7 (2.6) in exercise and non-exercising groups respectively Nationality: Asian

Participant characteristics

Attendance in sports clubs during the past two years

VO2 max by graded bike test

Ecological studies

Measure of physical activity/fitness

HOMA

AIR/IS by 2 h hyperglycaemic clamp.

Measure of insulin resistance

Unadjusted

Sex distribution, age and BMI not significantly different between ethnic groups

Confounders adjusted for

(continues overleaf )

No difference in mean HOMA between population who reported attendance at sports clubs and those who did not

VO2 max lower in Blacks Fasting and first phase insulin higher in Blacks

Direction and magnitude of effect

Table 12.2 Observational studies of the relationship between physical activity and insulin resistance in children and adolescents

FINDINGS FROM OBSERVATIONAL STUDIES IN CHILDREN

341

To assess the difference in fitness between hyperinsulinemic cases and two control groups, one weight matched and one normal weight

To describe the association between PA and eating behaviour and adolescent T2DM

165

166

Reference

Objective of study

Cases: Adolescents with T2DM and presumed insulin resistance (N = 11), mean age (SD) 14.5 (1.7) Controls: non-diabetic siblings (N = 9), mean age (SD) 14.0 (10.2) Ethnicity: African American and White

Ethnicity: Hungarian

Normal weight controls: 43 (25m, 18f) Age: 11.6 (0.1) years % Body fat: 11.9 (0.8)

Obese controls: 14 (7m, 7f) Age: 11.2 (0.5) years % Body fat: 37.0 (0.8)

Cases: 11 (7m, 4f) Age: 10.4 (0.7) years % Body fat: 37.2 (1.1)

Participant characteristics

Measure of insulin resistance

Open ended unstructured interview concerning leisure-time activity

Treadmill test (Bruce)

Fasting insulin This was not significantly different between cases and controls

Fasting insulin

Case–control studies

Measure of physical activity/fitness

Table 12.2 (continued )

Cases matched with controls for family history

Obese controls matched for body weight, body composition, physical activity and plasma lipid values Normal weight controls matched for age

Confounders adjusted for

Cases reported higher participation in sedentary activities (5.0 (2.7) h/day TV viewing, computer games) compared with sibling controls (3.0 (2.4) h/day) Difference non-significant

Lower fitness in cases than in controls (p < .05) Furthermore, there was an inverse relationship between insulin and exercise duration in the obese groups

Direction and magnitude of effect

342 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

To assess the association between work capacity and adolescent metabolic syndrome

To examine association between risk factors for the metabolic syndrome in obese children

167

168

Cases: obese adolescent boys with MS (N = 22), mean age (SD) 14.2 (1.9) Controls: 1. Age matched obese group (N = 17), mean age (SD) 14.2 (2.6) 2. Age but non-obesity matched group (N = 29), mean age (SD) 15.3 (1.0) Nationality of subjects: Hungarian Cases: obese children with features of the metabolic syndrome (N (m/f) 53), mean BMI 27.3 (4.0) Controls: obese children without features of the metabolic syndrome (N (m/f) 30) Physical activity assessed by questionnaire (PAQ-C) a self-administered 7 day activity recall VO2 max by cycle ergometer

Resting HR exercise duration, physical work capacity (PWC-170), VO2 peak , and lactate threshold

Fasting serum insulin This was significantly higher in the cases than controls (p < 0.05)

Fasting insulin This was significantly elevated in cases compared to obese and non-obese controls

Both groups of controls matched for age. Obese control group poorly matched for BMI to cases (BMI significantly lower, but no significant difference in % body fat)

(continues overleaf )

No significant association of cardiovascular fitness or physical activity with the metabolic syndrome

No formal presentation of measure of association All performance parameters were reduced (p < 0.05) in cases compared with obese and non-obese controls.

FINDINGS FROM OBSERVATIONAL STUDIES IN CHILDREN

343

To assess the association between PA and IR

To assess the association between fitness and IS within a population of individuals with T1DM and a separate population of non-diabetic adolescents

169

170

Reference

Objective of study

27 adolescents with T1DM and 10 non-diabetic individuals BMI 22.4 (range 18–27) in T1DM and 22.9 in non-diabetic population (17–28) Ethnicity: no information provided

Mean BMI 26.1 (3.9) Age: 6–12 years Ethnicity: 73 Caucasian, 10 non-Caucasian N (m/f): 68/99 Age: 15.7 (1) years BMI: 22.1 (3.6) Nationality: Venezuelan

Participant characteristics

Fasting insulin Case definition: insulin > 84 pmol/l−1

Measure of insulin resistance

VO2 max by bike test

IS by hyperinsulinaemic euglycaemic clamp

Cross-sectional studies

PA (min/week) from medical records

Measure of physical activity/fitness

Table 12.2 (continued )

Analysis stratified by T1DM status

Stratified by BMI above or below 25

Confounders adjusted for

Positive correlation between VO2 max and IS in non-diabetic adolescents (r = 0.81, p < 0.05) and T1DM patients (r = 0.83, p < 0.05)

Lean group: 32% lower PA in cases (p < 0.05) Obese group: no difference in PA No difference in PA between lean controls and obese cases PA was 34% higher in obese than in lean cases (p < 0.05)

Direction and magnitude of effect

344 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

To assess the association between fitness and fasting insulin

To assess the association between physical activity and CHD risk factors

171

12

Cohort of 42 girls (age 8–11 years) Mean BMI (SD) 16.4 (2.0) Ethnicity: 78% White, 10% Black, 4% Hispanic, 8% unclassified

Volunteer sample of 46 boys and girls (age 9–11 years) Mean % body fat 24.6 (SD 10.4) Ethnicity: African-Americans and Whites Total energy expenditure (TEE) by doubly labelled water Resting metabolic rate (RMR) by ventilated hood Non-resting energy expenditure = TEE − RMR Physical activity also assessed by questionnaire

Sub-maximal heart rate during exercise

Fasting insulin

Fasting insulin

Unadjusted

Adjustment in analysis for resting heart rate

(continues overleaf )

Positive association between sub-maximal heart rate and fasting insulin (F value 14.4, p < 0.001) after adjustment for resting heart rate Positive correlation between insulin level and non-resting energy expenditure (r = 0.48, p = 0.002) Self-reported PA positively correlated with insulin (r = 0.47, p = 0.003).

FINDINGS FROM OBSERVATIONAL STUDIES IN CHILDREN

345

To assess the association between physical activity and CHD risk factors

To assess the association between PA and CHD risk factors

172

13

Reference

Objective of study Leisure-time physical activity score computed from questionnaire

Physical activity score from parental questionnaire on outdoor play, hours TV viewing, weekly sports participation frequency and perceived physical activity level

N (m/f): 1330 Age: 6–13 years Mean BMI: 17.2 (2.5) Ethnicity: Asian

Measure of physical activity/fitness

N (m/f): 1114/1244 Mean age: 16.4 (5.0) years Mean BMI (SD): 20.0 (3.6) Nationality: Finnish

Participant characteristics

Fasting insulin

Fasting insulin

Measure of insulin resistance

Table 12.2 (continued )

Stratified by age group (6–7 years, 9–10 years, 12–13 years)

Stratified analysis by gender and adjusted for puberty stage

Confounders adjusted for

In boys and girls separately, inverse relationship between activity and fasting insulin after adjustment for puberty stage (test for trend in boys p = 0.0027 and p = 0.025 in girls) In age groups 9–10 years and 12–13 years there was a positive correlation of the activity score with fasting insulin This association was not significant in those aged 6–7 years However, in age group 12–13 years the proportion of children with low activity was greater in those with high fasting insulin

Direction and magnitude of effect

346 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

To assess the association between fitness and IS in children with and without a family history of T2DM

To assess the cross-sectional association between fitness and fasting insulin This study was an analysis of the baseline measurement for a trial (see Table 12.4)

110

173

VO2 max by incremental treadmill test

Leisure time PA by questionnaire. VO2 max predicted from sub-maximal bike test

13 children without a family history and 9 with a family history of T2DM Mean age (SD) 10 (0.9) years Mean BMI 18.7 (4.8) Ethnicity: African-American

N (m/f): 139/125 Age: 11–14 years Mean BMI (SD): 22.4 (5) Ethnicity: not stated Fasting insulin

IS by 3 h hyperinsulinaemic euglycaemic clamp

VO2 max scaled for body size by adjusting for body mass to the power of 0.8

Stratified by family history of T2DM

(continues overleaf )

Positive correlation between VO2 max and IS in those without a family history (r = 0.47, p < 0.05) but not in those with a family history (r = −0.20, p = 0.6) Inverse correlation between fasting insulin and VO2 max in boys (r = −0.33, p < 0.01) and girls (r = −0.20, p < 0.01) after adjustment for body size No significant association between LTPA and IS

FINDINGS FROM OBSERVATIONAL STUDIES IN CHILDREN

347

To assess the association between fitness, physical activity and insulin sensitivity

To assess the cross-sectional association between fitness and markers of IR

To assess the association between PA and fasting insulin

106

174

175

Reference

Objective of study PA by questionnaire. VO2 max by all-out treadmill test

N (m/f): 33/35 Age: 5–11 years Mean BMI: 21 (5)

Incremental bicycle test

Stanford 7 day questionnaire expressed as kcal/day

N (m/f): 18/17 Mean age: 13.2 (2.9) years Mean BMI: 30.0 (5.3) Nationality: Austrian

N (m/f): 114/238 Mean age: 16.6 (1.2) Median BMI: 21.5 Nationality: Mexican

Ethnicity: African-Americans and Whites

Measure of physical activity/fitness

Participant characteristics

Fasting insulin

Fasting insulin

AIR and IS by IVGTT

Measure of insulin resistance

Table 12.2 (continued )

BMI, waist circumference, smoking, age group, energy intake, family history of T2DM

Age

Analysis adjusted for ethnicity, fat mass, fat-free mass and IGF-1

Confounders adjusted for

Positive correlation between insulin sensitivity and PA (p < 0.01) Difference between black and white children is independent of activity Positive correlation between IS and VO2 max (p < 0.05) Inverse correlation between log insulin and power output per kg body weight (r = −0.6, p = 0.001) 1.1 pmol/l decrease in fasting insulin level for each 250 kcal/d increase in estimated energy expenditure (p = 0.0001)

Direction and magnitude of effect

348 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

To assess the association between fitness and fasting insulin in obese and non-obese adolescent boys

To assess the association between physical activity and insulin sensitivity in non-diabetic, normal weight children

To assess the association between fitness and clustering of metabolic risk factors in two age groups of children

176

177

178, 179

N (m/f) 279/310 Age: 9.6 years BMI: 17.3 (2.5) N (m/f) 206/225 Age: 15.5 BMI: 20.9 (2.7) Ethnicity: 94% Caucasian (Danish)

N (m/f): 40/0 Mean age: 13.7 (0.6) years Mean BMI in obese group 27.7 (2.9) and 22.8 (3.0) in non-obese group Nationality: Chinese-Singaporean N (m/f): 266/89 Mean age: 13.0 (1.2) years Mean BMI: 22 (4.5) Ethnicity: Black, White and Hispanic

Wattmax estimated from maximal bike test

Paffenbarger physical activity questionnaire

Maximal treadmill walking test

Fasting serum insulin and glucose

Euglycaemic hyperinsulinaemic clamp + fasting insulin

Fasting insulin

Age and stratified by sex

Age, sex, ethnicity and Tanner stage Additionally BMI, %BF, waist circumference and lipids

Fat mass

(continues overleaf )

Positive correlation of physical activity score with IS (r = 0.18, p = 0.001) and negative relationship with fasting insulin (r = −0.12, p = 0.03) Partial correlations of Wattmax with fasting insulin were r = −0.31 and r = −0.28 in boys and girls respectively (p < 0.001) after adjustment for age

No relationship between VO2 peak and fasting insulin in either group

FINDINGS FROM OBSERVATIONAL STUDIES IN CHILDREN

349

To assess the relationship between physical activity and fitness and insulin sensitivity in overweight Hispanic children with a positive family history of T2DM

To assess the association of 6 year changes in PA and fasting insulin levels

180

14

Reference

Objective of study

N (m/f): 174/223 Baseline age: 12, 15 and 18 years Mean BMI at 6 year follow-up: 22.1 (2.8) Nationality: Finnish

N (m/f): 55/40 Age: 11.1 (1.7) years Mean BMI: 28.2 (6.4) Ethnicity: Hispanic

Participant characteristics Frequently sampled IVGTT

Measure of insulin resistance

Combined index of leisure time activity assessed by questionnaire 1 PA unit = 6 min intense exercise per week 15 PA units = 1 h light aerobic exercise per week

Fasting insulin (mU/l)

Longitudinal cohort studies

Fitness assessed in maximal walking treadmill test Recreational activity assessed by Modifiable Activity Questionnaire

Measure of physical activity/fitness

Table 12.2 (continued )

Stratified by gender Adjusted for change in sub-scapular skinfold thickness

Sex, Tanner stage, fat mass and soft lean tissue mass

Confounders adjusted for

Inverse correlation between change in log insulin and change in physical activity in boys (p < 0.001) after adjustment for change in skinfold thickness No effect in girls

No correlation between VO2 max or activity with insulin sensitivity

Direction and magnitude of effect

350 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

BIOLOGICAL MECHANISMS

351

insulin, this association was highly susceptible to outlying data and was nonsignificant (r = 0.1, p = 0.56) when two extreme outliers (> 2 SD from mean) were excluded. In the second study Matsui et al.13 showed a positive relationship of activity and insulin in one age stratum of their large study of children, but this study did not control for obesity or puberty status (a key issue in studies of older children) and only included a third party classification of activity based on a parental questionnaire on outdoor play, hours TV viewing, weekly sports participation frequency and perceived physical activity level. Thus overall the data from these observational studies suggests that both physical activity and fitness are associated with insulin resistance, but, as described in relation to the studies in adults, there are no reports of studies in which both fitness and physical activity are measured with known precision. Thus it is uncertain from these studies which factor is more closely related to insulin sensitivity in children. As in the studies in adults, the number of longitudinal studies in children is small and indeed our search identified only a single study.14

12.5

Mechanisms underlying the association between physical activity and insulin resistance

The strength of the inference about the causal relationship between physical activity and insulin resistance is raised considerably by evidence concerning the biological mechanisms that may explain this effect. The basic mechanisms of insulin signalling have been reviewed by Siddle elsewhere in this book and will not be repeated here. However, there are various points in this process where physical activity may have its effect. One of the major difficulties at the tissue, cellular and molecular level, however, is in distinguishing between the acute and chronic effects of activity. Acute muscle contraction allocates GLUT4 to the cell membrane through an insulin-independent mechanism,15 – 23 possibly working though rising adenosine monophosphate (AMP) and calcium ion (Ca2+ ) levels (calcium/calmodulin-dependent protein kinase IV), and most likely from different intracellular pools of GLUT4.24 – 27 This acute effect makes it difficult to investigate the effect of physical activity on insulin sensitivity or glucose transport since observations could be attributable to the most recent bout of activity rather than a chronic effect. However, it would be inappropriate to rest individuals to get around this problem, since this might diminish the differences between individuals in the effects of habitual activity on insulin resistance if the chronic effects of activity are an accumulation of the acute ones.28, 29 It is likely that physical activity stimulates insulin action and glycaemic control by more than one mechanism. One simple hypothesis is that physical activity leads to an up-regulation of the enzymes hexokinase (HK), citrate synthase (CS) and glycogen synthase (GS), which are the rate-limiting enzymes in glycolysis, in the Krebs cycle and in glycogen synthesis, respectively. This would ensure maintenance of the concentration gradient during the time when the GluT4s

352

PHYSICAL ACTIVITY AND INSULIN RESISTANCE

are incorporated in the membrane because glucose is more rapidly being either metabolized or stored as glycogen. Another mechanism is that exercise has been shown to induce hyperexpression of GLUT protein and mRNA,30 – 35 making more GLUTs available for translocation. This transcription is possibly regulated via mitogen-activated protein kinase (MAPK), which is increased after exercise.36 – 40 Such transcriptional regulation may also occur at the IRS and the PI3-K levels.31, 41 – 43 A separate pathway by which chronic exercise could influence insulin sensitivity is through the lowering of triglyceride (TG) and non-esterified fatty acid (NEFA or free fatty acid, FFA) levels by activity. These lipids could impair the function of the proteins in the insulin cascade44 – 50 or change membrane fluidity, due to a preferential incorporation of saturated fatty acids into the plasma membrane when fat utilization is low. The rate of the fatty acid synthesis is increased by physical activity and decreases with age.51 Exercise training increases HDL levels via LPL and by upregulation of hepatic lipase (HL), cholesterol ester transfer protein (CETP) and lecithin–cholesterol acyl transferase (LCAT).52, 53 Increased lipoprotein lipase-mediated TG clearance and reduced hepatic TG secretion are both likely to contribute to the exerciseinduced TG reductions.54 LPL is also activated by apoprotein (contained in chylomicrons and lipoproteins), which is associated with higher levels of physical activity.55 Exercise improves the anti-lipolytic response of insulin56 – 58 and endurance training induces an increased contribution from fat to energy needs. This may result from increased muscle capillary and fat transporter density, enhanced activity of LPL and of the enzymes controlling β-oxidation.59 – 70 During the recovery phase after physical activity, oxygen consumption is increased (excess post-exercise consumption) to replenish ATP, CP and glycogen stores. Physical activity may also influence insulin action through haemodynamic mechanisms. Potassium ion (K+ ) release, increased plasma osmolality, increase in blood pH and CO2 , hypoxaemia and histamine release all occur during exercise and cause vasodilatation to increase blood flow to exercising muscles, whereas blood vessels of other tissues are constricted. These factors also stimulate endothelial release of nitric oxide (NO), which has a stimulatory effect on glucose transport.71 – 75 The release of NO is chronically increased with regular exercise, possibly modified by genotypic differences in the endothelial NO synthase (eNOS) and/or neuronal NO synthase (nNOS) genes. This may modulate changes in arterial compliance. Indeed, aerobic training increases the large artery compliance, contributing to a reduction in systolic blood pressure and an attenuation of the cardiac afterload, which may be explained by the NO pathway.76 Emerging evidence also suggests that when noradrenaline binds to its β1 -adrenoceptor, nNOS can regulate Ca2+ flux to minimize the effect of excessive sympathetic stimulation.77 Physical activity also interacts with energy intake (EI) to impact on obesity and hence could have indirect effects on insulin resistance. Appetite is

TRIALS OF THE EFFECT OF PHYSICAL ACTIVITY ON INSULIN SENSITIVITY

353

influenced via a feedback mechanism involving leptin and there is considerable between-individual variation in the level of leptin relative to body mass, indicating that some people may be less sensitive to the modifying effects of leptin on adiposity.78 There is evidence to indicate that the function of leptin is modulated by the habitual physical activity level, in that sedentary individuals are leptin resistant and thus require higher circulating levels of leptin to regulate appetite in an optimal manner, which may thus impact on insulin resistance.79 – 85 Physical activity energy expenditure is dependent not only on the amount of external work performed but also on the efficiency with which it is performed. The latter is possibly modulated by certain genes, e.g. the UCP family or the PPARGC-1, which may therefore interact with the effect of physical activity to predict metabolic outcomes.86 – 92

12.6

Trials of the effect of physical activity on insulin sensitivity in adults

A major question that the observational data cannot resolve is whether the association between inactivity and insulin resistance is reversible. The highest form of evidence of reversibility comes from experimental trials. These studies not only shed light on the question of the direction of causality, which is left unresolved by the observational studies, but also provide information about how much change is achievable and about whether overall activity is more effective than concentration on vigorous activity, issues that are difficult to resolve from observational data. Table 12.3 summarizes the results of 32 reports of clinical trials in adults. We excluded trials with fewer than 25 participants. 18 of these reports were of randomized controlled trials, but three reports were from the same study. In 12 of these reports, the RCT demonstrated a significant positive effect of the physical activity intervention on insulin resistance. In one of the studies, an effect was only demonstrable in the group who also undertook a dietary intervention93 and in another the effect of activity was restricted to those who also lost weight either through diet or physical activity.94 The four other trials that did not find an effect included one preliminary report from a trial that later showed a positive effect when more individuals were included,95 two small studies (Fairey et al.96 (n = 52); Bunout et al.97 (n = 108)) and one study that compared different approaches to low intensity activity.98 In general, these null studies also tended to have a shorter duration of intervention than the positive studies, which all, with the exception of a single study, intervened for longer than 6 months. The one positive short duration study involved relatively intense activity at 70% of maximum heart rate for three 20 minute sessions increasing to four bouts at 80% of maximum heart rate four times a week.99 This study by Short et al. was able to demonstrate a positive effect at 16 weeks. An additional factor that may have improved the capacity to detect a true effect in this study may have been the use of an intravenous glucose tolerance test

Randomized controlled trial To assess the effect of 9 months training on insulin in MI survivors

Un-controlled trial To assess the effect of 12 weeks training on insulin

181

182

Reference

Objective of study

N (m/f): 50/0 Age: 33–69 years BMI: Ethnicity:

9 months physical training, tailored to each patient’s work capacity. The intervention consisted of cycling, running, and calisthenics for half an hour, three times a week Subjects were randomized to one of five treadmill walking groups (no control group), varying by intensity (50–70% HR reserve), frequency (2–4 sessions/week) and session duration (30–60 min)

Trials

Nature of intervention

Plasma insulin levels at 0, 30, 60, 90 and 120 min during OGTT measured at baseline, 4, 8, 12 weeks and post-training

OGTT – fasting and post-challenge insulin

Measure of insulin resistance

Combined analysis + stratified by training group

Analysis stratified by controls, insufficiently and sufficiently trained

Confounders adjusted for

Trials of physical activity on insulin resistance in adults

N (m/f): 104/0 Age: 55 years BMI: Nationality: Swedish

Participant characteristics

Table 12.3

No differences from baseline values were observed in any group or across group at any time point

Insulin was reduced in all groups but was more pronounced in the sufficiently trained group

Direction and magnitude of effect

354 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

Non-randomized controlled trial To assess the effect of 3 months training on insulin in obese women and in type 2 diabetics

Un-controlled trial To assess the effect of exercise training on insulin in cardiac rehabilitation patients

183

184

Obese group: N (m/f): 0/55 Age: 38.5 (15) years Normal weight controls: Age: 37.1 (4) years Diabetic (n = 33) and glucose tolerant individuals (n = 13): N (m/f): 12/34 Age: 49.8 (12) years N (m/f): 49 Age: 56 (10) years BMI: Nationality: American 12 months training Three sessions/week for the first 3 months; five sessions/week thereafter Session duration was increased from 40–45 min to 50–60 min Intensity was increased from 60–70% VO2 max to 70–90% VO2 max (HR and VO2 monitored periodically)

3 months training of the obese and the diabetic groups Normal weight controls and glucose tolerant individuals were not trained

(continues overleaf )

T2DM: Significantly lower insulin values at 30, 60 and 120 min but no change in fasting and 180 min values

Insulin at 0, 30, 60, 120 and 180 min during OGTT Follow-up OGTT performed 18 h after last exercise bout

Stratified by initial glucose tolerance status (T2DM, IGT or NGT)

No significant effect of training in the obese group or in the diabetics

OGTT – fasting and post-challenge insulin

TRIALS OF THE EFFECT OF PHYSICAL ACTIVITY ON INSULIN SENSITIVITY

355

Non-randomized controlled trial The study was a prospective study to test the feasibility aspect of long term intervention with an emphasis on life-style changes

Randomized controlled trial To assess the effect of lifestyle modification on insulin in newly diagnosed type 2 diabetics

185

186

Reference

Objective of study

Nature of intervention A 5 year protocol, including an initial 6 month (randomized) pilot study, consisting of dietary treatment and/or increase of PA or training with annual check-ups

After 3 months of routine care, groups were randomized to either conventional care or diet and exercise for 12 months

Participant characteristics

N (m/f): 222 Age: 48.1 (SD 0.7) BMI: 25.7 years Ethnicity: Swedish Caucasians

N (m/f): 86 Age: 40–64 years BMI: Nationality: Finnish

OGTT – fasting and post-challenge insulin

OGTT – fasting and post-challenge insulin

Measure of insulin resistance

Table 12.3 (continued ) Confounders adjusted for

Reduction in 0, 40 min increment, and 2 h insulin during intervention (p < 0.0001) in intervention groups, but not in control groups. Reduction in 2 h insulin from baseline to 5 year follow-up (p for trend in intervention groups (p = 0.02) Insulin significantly reduced in the intervention group

Direction and magnitude of effect

356 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

93

81

Un-controlled trial 20 week endurance exercise training trial aimed at modifying metabolic parameters in sedentary individuals Randomized controlled trial To assess the combined effects of diet and exercise on insulin resistance

N (m/f): 219 Age: >40 years Ethnicity: Caucasian

N (m/f): 51/46 Age: 24.4 (5.8) years BMI: Ethnicity: Caucasian

1 year intervention trial involving supervised endurance exercise training 3/week

The intervention was diet and exercise recommendations (specific instructions) 3/week for 20 week supervised aerobic exercise training programme

HOMA

Fasting insulin

Stratified by sex

(continues overleaf )

Significant reduction in insulin resistance with diet and exercise, but not with exercise alone.

No effect of exercise training on insulin levels

TRIALS OF THE EFFECT OF PHYSICAL ACTIVITY ON INSULIN SENSITIVITY

357

Non-randomized controlled trial To assess the effects of lifestyle intervention vs ‘usual care’ on CV risk factors including fasting insulin in IGT and/or obese people

Un-controlled trial To determine the effect of dietand exercise-induced weight loss on serum insulin levels in obese type 2 diabetic patients

187

188

Reference

Objective of study The programme was implemented during a one-month stay with full board at two local council ‘wellness’ centres. Programme included 140 h of scheduled aerobic-based activities and weighed and measured diet Participants were followed up at 12 months 4 week intervention, exercise (2200 kcal/week) and diet (1000 kcal/day, 50% CHO/25% prot./25% fat with PS ratio of 1.0)

N (m/f): 69/123 Age: 55.5 (0.9) years BMI: 30.6 (0.33) Nationality: Swedish

N (m/f): 34 Age: 49 (9) years BMI: 33.1 (5.1) Nationality: German Non-random sample

Nature of intervention

Participant characteristics

Fasting insulin

OGTT – fasting and post-challenge insulin

Measure of insulin resistance

Table 12.3 (continued )

Unadjusted

Confounders adjusted for

Fasting insulin decreased (p < 0.001)

Intervention group had significantly lower fasting insulin at baseline compared with controls (p = 0.0001). No difference in delta fasting insulin during follow-up

Direction and magnitude of effect

358 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

95

189

Un-controlled trial To determine the effect of dietand exercise-induced weight loss on serum insulin levels in obese type 2 diabetic patients Randomized controlled trial To assess the effectiveness of intervention with diet and PA to reduce fasting and 2 h serum insulin levels at 1 year 4 week intervention, exercise (2200 kcal/week) and diet (1000 kcal/day, 50% CHO/25% prot./25% fat with PS ratio of 1.0)

Within the intervention group, individual guidance was given relating to improving one’s aerobic activity levels, and supervised, tailored, circuit-type activities were also offered Dietary advice was also given

N (m/f): 20/0 Age: 48 (8) years BMI: 32.1 (3.9) Nationality: German Non-random sample

N (m/f): 77/135 Age: 53 (7.0) years BMI: 31.2 (4.8) Ethnicity: Finnish OGTT – fasting and post-challenge insulin

Fasting insulin

Participants stratified (by intervention/control groups) by study centre, sex and 2 h glucose Success scores based on staff’s judgment of whether predefined goals were achieved

Unadjusted

(continues overleaf )

No difference in delta fasting or 2 h insulin between groups

Fasting insulin changed from 12.8 to 9.2 µU/l (p = 0.012) Insulin µIU/ml = 6.945 pmol/l

TRIALS OF THE EFFECT OF PHYSICAL ACTIVITY ON INSULIN SENSITIVITY

359

Non-randomized controlled trial To assess the affect of communitybased healthy lifestyle programme on factors including insulin resistance

Randomized controlled trial To determine the effects of dietor exercise-induced weight loss and exercise without weight loss on factors including insulin sensitivity

190

94

Reference

Objective of study Community-based programme of education and promotion of PA and diet in high risk (of DM) overweight people PA was assessed through questionnaire 12 week intervention, randomly assigned to 1 of 4 study groups: diet-induced weight loss; exercise-induced weight loss; exercise without weight loss; control

N (m/f): 43 (at 2 year follow-up) Age: 49 (3) years BMI: 28.6 (0.6) Ethnicity: Australian Aborigines

N (m/f): 52/0 Age: 42.6 (9.7) and 46.0 (10.9) years BMI: 31.3 (2.0) Ethnicity:

Nature of intervention

Participant characteristics

Hyperinsulinaemic– euglycaemic clamp + fasting and AUC insulin during an OGTT

Fasting insulin

Measure of insulin resistance

Table 12.3 (continued )

Not intention to treat analysis (one-way ANOVA with repeated measures (group × time interaction))

Not intention to treat analysis Unadjusted

Confounders adjusted for

Insulin sensitivity improved in the exercise-induced weight-loss group as compared with the controls (p = 0.01) but only borderline in the exercise group without weight loss (p = 0.09)

Significant reduction (ptime = 0.002) in fasting insulin, but no change in obesity or prevalence of diabetes

Direction and magnitude of effect

360 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

192

191

Randomized controlled trial To determine the effects of an endurance and resistance exercise training intervention on insulin sensitivity in healthy younger women Un-controlled trial To assess the effect of exercise training on coronary risk factors in coronary patients 6 month intervention, randomly assigned to endurance training (ET) group (n = 14), resistance training (RT) group (n = 17) or control group (n = 20)

36 exercise sessions over 12 weeks

N (m/f): 0/51 Age: 29 (SD 5), 28 (SD 3), 28 (SD 4) years BMI: 22 (SD 2) Ethnicity: Caucasians

N (m/f): 59/23 Age: 61.2 (12.2) years BMI: 27.9 (4.7) Nationality: American Fasting insulin

Hyperinsulinaemic– euglycaemic clamp

ANOVA repeated measures Analysis also stratified by sex

A 2 × 3 repeated measures ANOVA was used to assess changes over time and between groups

(continues overleaf )

No significant change in insulin, despite favourable changes in fitness and obesity measures Similar findings in each sex

Fasting and AUC insulin change only borderline (p = 0.10) more in the intervention groups, compared with the controls Insulin sensitivity improved with training in ET group (p < 0.05) and RT group (p = 0.06), but not in control group No coefficients given

TRIALS OF THE EFFECT OF PHYSICAL ACTIVITY ON INSULIN SENSITIVITY

361

193

Reference

Non-randomized controlled trial To assess the effect of lifestyle intervention (diet and exercise) on insulin

Objective of study

N (m/f): 69 Age: 30–70 years BMI: Ethnicity: African-Americans

Participant characteristics Each session consisted of 5–10 min warm-up, 40–45 min aerobic exercise (treadmill, bike, arm crank, rowing), 20 min resistance training and 10 min cool-down Intervention (n = 45) was lifestyle education (monthly telephone calls, bimonthly news letters and ad libitum individual meetings). It aimed at increasing PA with 125 kcal/day through daily or aerobic PA and reducing dietary fat by 14 g/day (125 kcal/day) for 12 months

Nature of intervention

Fasting insulin and AUC during an OGTT, measured at baseline, 4 months and 12 months in both groups + at 1 week and 8 months in the intervention group

Measure of insulin resistance

Table 12.3 (continued )

Not intention to treat analysis 12 months follow-up data was available in 19 and 17 from intervention and control groups, respectively

Confounders adjusted for

Fasting insulin and AUC lower than baseline after 1 week but only fasting insulin lower than baseline after 4 months (p < 0.05) At 8 and 12 months there were no differences from baseline Intervention group did not differ from control group at any time point

Direction and magnitude of effect

362 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

Randomized controlled trial To assess the effect of a 6 month behavioral intervention on cardiovascular risk in IGT individuals

Un-controlled trial To assess the effect of 20 week exercise training on insulin in previously sedentary subjects

194

195

N (m/f): 250/252 Age: 34.1 (13.3) years BMI: 25.9 (4.7) Ethnicity: 72% Caucasian, 28% Black

Controls (n = 32) BMI: 29.9 (4.9)

Intervention (n = 35) BMI: 30.4 (5.6)

N (m/f): 38/29 Age: 24–75 years Ethnicity: Caucasian (European origin) Intervention group received a tailored physical activity programme from a physiotherapist aimed at engaging in aerobic activity 2–3 times per week for 20–30 min per session They also received up to 80% discount to local exercise facilities Advice on activity and diet was given again after 2, 4, 6, 10, 14 and 18 weeks Bike training 3 days/week for 20 weeks The training load was increased from 55% VO2 max for 30 min per session to 75% VO2 max for 50 min per session, which was then maintained for the last 6 weeks VO2 max was measured pre- and post-training by maximal bike test IVGGT

OGTT + short insulin tolerance test (ITT) Not intent to treat analysis Originally, 78 were randomized but 8 (5 controls) withdrew and 3 (2 controls) had incomplete data

(continues overleaf )

Fasting insulin decreased by 11.2% (p < 0.001) The change was not significantly related to change in fitness, although the quartile of least VO2 max improvement showed a significantly greater decrease than the other quartiles

Fasting insulin decreased by 18% in the intervention group, which was significantly more than the change (positive) in the controls (p = 0.005). 2 h insulin also decreased but there was no change in insulin sensitivity by the ITT

TRIALS OF THE EFFECT OF PHYSICAL ACTIVITY ON INSULIN SENSITIVITY

363

Randomized controlled trial To assess the effectiveness of intervention with diet and PA to reduce fasting and 2 h serum insulin levels at 1 year

Un-controlled trial To assess the effect of 6 weeks diet and exercise on insulin sensitivity and resistance in type 2 diabetic patients

196 This paper is related to that published by Eriksson et al. 95

197

Reference

Objective of study Within the intervention group, individual guidance was given relating to improving one’s aerobic activity levels, and supervised, tailored, circuit-type activities were also offered Dietary advice was also given Patients were admitted to hospital and instructed to accumulate 10 000 steps daily The diet consisted of 1440–1720 kcal/day (20% protein, 25% fat, 55% CHO)

N (m/f): 172/350 Age: 55 (7.0) years BMI: 31.2 (4.6) Nationality: Finnish

N (m/f): 45/15 Age: 54.4 (11.3) years BMI: 23.7 (3.2) Ethnicity: Asian (Japanese)

Nature of intervention

Participant characteristics

Hyperinsulinaemic euglycaemic clamp + QUICKI

OGTT

Measure of insulin resistance

Table 12.3 (continued ) Confounders adjusted for

38% increase in insulin sensitivity and 8% decrease in QUICKI (p < 0.001) Decrease (21%) in fasting insulin was not significant

The intervention group achieved a significantly greater reduction in 2 h serum insulin (p < 0.001), but not fasting insulin (p = 0.14) compared with the control group

Direction and magnitude of effect

364 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

Randomized controlled trial To evaluate the effect of 12 months lifestyle intervention (diet and exercise) on insulin

Randomized controlled trial To assess the effect of exercise training on insulin in post-menopausal breast cancer survivors

198

96

N (m/f): 0/52 Age: 59 (6) years BMI: 29.2 (6.6) Nationality: Canadian

N (m/f): 58/44 Age: 57 (7) years BMI: 29 (4) Nationality: Dutch Intervention was dietary advice after 1, 3, 6 and 9 months including advice to stop smoking and reduce alcohol intake if necessary Advice was also given to increase PA to at least 30 min/day for at least 5 day/week Subjects were encouraged to take part in exercise training programme (free) at least 1 h/week 15 week exercise intervention, three sessions/week at respiratory exchange ratio of 1 (60–70% VO2 max ) for 15 min at weeks 1–3, then increased by 5 min every 3 weeks to 35 min for weeks 13–15 Fasting plasma insulin and HOMA Follow-up blood sample > 48 h after last exercise bout

Fasting and 2 h insulin during OGTT

Intention to treat analysis

(continues overleaf )

No differences between groups in delta-insulin (p = 0.941) or
-HOMA (p = 0.247)

Fasting and 2 h insulin decreased 2.5 µU/ml and 6.7 µU/ml in intervention group but only change in fasting was different from control group (p < 0.01)

TRIALS OF THE EFFECT OF PHYSICAL ACTIVITY ON INSULIN SENSITIVITY

365

101

Reference

Randomized controlled trial To determine the effect of 6+ months training on insulin sensitivity

Objective of study

Nature of intervention Subjects were randomized to one of four groups 1. Low volume–moderate intensity (171 min/week, 3.3 times/week, 10.3 mile equivalents/ week) 2. Low volume–high intensity (114 min/week, 2.9 times/week, 10.5 mile equivalents/ week) 3. High volume–high intensity (167 min/ week, 3.6 times/ week, 15.9 mile equivalents/week) 4. Control group Training groups received 6 months of training after 2–3 months ramp-up

Participant characteristics

N (m/f): 85/69 Age: 52 (8) years BMI: 30 (3) Ethnicity: 79% Caucasian, 18% Black, 3% other IVGTT

Measure of insulin resistance

Table 12.3 (continued )

Not intention to treat analysis (30% drop-out)

Confounders adjusted for

Insulin sensitivity increased significantly in all training groups, and decreased in the control group (p < 0.05). Groups 2 and 3 increased IS by 85%, whereas group 1 only increased by 40%

Direction and magnitude of effect

366 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

199

Randomized controlled trial To assess the long term effect of exercise intervention on insulin in individuals with IGT

N (m/f): 87 Age: 56 (7) years BMI: 30.4 (4) Nationality: Finnish Intervention group received individual advice on exercise (>30 min of moderate PA per day) and diet (decrease fat and energy intake, increase fruit and vegetable, red meat, vegetable oils rich in unsaturated fat and whole-grain products intake), aiming at weight loss Diet advice was given 7 times the first year, then every 3 months Endurance exercise was recommended and circuit-type resistance training was offered Control group received general advice on diet and exercise

Fasting and 2 h insulin, and insulin sensitivity from IVGTT

Not intention to treat analysis (n = 52) Drop-out due to progression to T2DM, unwillingness to participate in IVGTT and technical error

(continues overleaf )

Fasting insulin decreased in intervention group (p = 0.001) but also borderline significantly in control group (p = 0.086). No changes were observed for 2 h insulin (p = 0.152) or insulin sensitivity (p = 0.227)

TRIALS OF THE EFFECT OF PHYSICAL ACTIVITY ON INSULIN SENSITIVITY

367

Randomized controlled trial To assess the effect of exercise on insulin

Randomized controlled trial To assess the effect of exercise with or without weight loss on insulin

200

201

Reference

Objective of study

Nature of intervention Exercise intervention was 4 sessions/week and progressed from 20 min @ 60% of HR reserve at baseline to 45 min @ 75% of HR reserve at 6 months This was then maintained for 10 months Subjects were assigned to either exercise only (n = 21), exercise + weight loss (n = 21) or waiting-list control group (n = 11) for 6 months

Participant characteristics

N (m/f): 131 Age: 17–35 years BMI: 25–34.9 Nationality: American

N (m/f): 53 Age: > 29 years BMI: > 25 Nationality: American

Fasting and 2 h insulin during OGTT

Fasting, 2 h insulin and AUC during OGTT at baseline, 9 months and 16 months

Measure of insulin resistance

Table 12.3 (continued )

Not intention to treat analysis (n = 41 with complete adherence, 67% in exercise group, 76% in exercise + weight loss and 100% in control group)

Stratified by sex Not intention to treat analysis Complete data in n = 66 (28 males/38 females)

Confounders adjusted for

Men: Fasting and 2 h insulin decreased about 20% and 39%, respectively, after 9 months, with no further improvement at 16 months (p < 0.05) Women: No change in fasting or 2 h insulin Fasting insulin decreased by 12–14% in both exercise groups (p < 0.05 for comparison with control group) 2 h insulin decreased by 27 and 50% in exercise and exercise + weightloss groups, respectively (both p < 0.05 for comparison with control group)

Direction and magnitude of effect

368 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

98

Randomized controlled trial To assess the effect of different walking exercise regimens on insulin

N (m/f): 0/255 Age: 57 (4) years BMI: Nationality: Finnish

Exercise intervention consisted of walking/jogging/cycling 3–4 times/week @ 70–85% HR reserve for 35 min, with 10 min warm-up and 10 min cool-down. Weight-loss group received weight-management advice, aiming at decreasing fat and energy intake for 0.5–1.0 kg weight loss/week This study was comprised of two sub-studies (I & II) Fasting insulin Study I also included 2 h insulin during OGTT

(continues overleaf )

No changes in fasting (or 2 h) insulin in any of the intervention groups (W1–6) as compared with the control groups (C1–2)

TRIALS OF THE EFFECT OF PHYSICAL ACTIVITY ON INSULIN SENSITIVITY

369

Reference

Objective of study

Participant characteristics Study I had three parallel groups; control (C1) or daily walking @ 65% VO2 max once (W1) or twice (W2) for 5 days/week for 15 weeks total PAEE per session was 300 kcal Study II had five parallel groups; control (C2), or walking once daily @ 55% VO2 max , 300 kcal (W3), @ 45% VO2 max , 300 kcal (W4), @ 55% VO2 max , 200 kcal (W5) or @ 45% VO2 max , 200 kcal (W6) for 5 days/week for 24 weeks total

Nature of intervention

Measure of insulin resistance

Table 12.3 (continued ) Confounders adjusted for

Direction and magnitude of effect

370 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

Randomized controlled trial To assess the modulation of seasonal variation in insulin sensitivity by exercise and/or nutritional supplementation

Un-controlled trial Investigated whether PPARγ gene polymorphism affects exercise response of insulin resistance

97

113

Genotype: (Pro/Pro n = 117, Pro/Ala n = 6)

N (m/f): 123/0 Age: 21–69 years BMI: Ethnicity: Japanese

N (m/f): 42/66 Age: 74.4 (3.8) years Nutr. supp.+training: n = 31 Nutr. supp. only: n = 28 Training only: n = 16 No intervention: n = 33

2 × 1 h/week Leg and arm aerobic conditioning ex. Respiratory muscle training using a threshold inspiratory muscle trainer 15 min walking periods before and after training Attendance was recorded to assess compliance with the exercise programme 3 month intervention of 50% max HR 20–60 min/day, 2–3/week = 700 kcal/week (mainly brisk walking). No control group Fasting insulin

Fasting HOMA and postprandial insulin (meal: standard breakfast containing 75 g carbohydrates)

Unadjusted

Not intention to treat analysis Unadjusted

(continues overleaf )

No change in insulin level when genotypes were combined Genotype modified change in insulin level (p = 0.02). Insulin increased in Pro12Pro group and decreased in Pro12Ala group.

No differences between groups in delta-insulin or delta-HOMA

TRIALS OF THE EFFECT OF PHYSICAL ACTIVITY ON INSULIN SENSITIVITY

371

202

Reference

Randomized controlled trial To determine effect of lifestyle intervention on features of insulin resistance

Objective of study 24 month intervention involved education on Mediterranean-style step I diet (1300 kcal/d for year 1, 1500 kcal/d year 2), goal setting and use of food diaries, through a series of monthly small-group sessions Guidance on ↑ PA (walking, swimming or aerobic ball games) Monthly sessions with nutritionist and exercise trainer for year 1; bimonthly sessions for year 2

N (m/f): 0/120 Age: 20–46 years BMI: Ethnicity:

Exercise: n = 60 Control: n = 60

Nature of intervention

Participant characteristics HOMA and fasting insulin

Measure of insulin resistance

Table 12.3 (continued )

Intention to treat analysis MLR to test association of BMI, WHR, FFA, physical activity and plasma cytokine concentrations on
-HOMA and
-fasting insulin

Confounders adjusted for

At 2 years both groups had significant reduction in HOMA (intervention group −5 and −1.3 µU/ml for fasting insulin and HOMA, respectively p = 0.02 for both Control group −2 and −0.4 µU/ml for fasting insulin and HOMA, respectively p < 0.01 for both)

Direction and magnitude of effect

372 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

99

Randomized controlled trial Effect of 16 week aerobic exercise intervention on insulin sensitivity

Exercise: n = 65 Control: n = 37

N (m/f): 41/49 Age: 21–87 years BMI: Ethnicity:

From 3 × 20 min bicycle ergometery @ 70% MaxHR, to 4 × 40 min @ 80% MaxHR Control group undertook home-based flexibility exercises IVGTT

Unpaired and paired t-tests for between-sex and pre- and post-testing within groups comparisons, respectively MLR to assess relationship between age, body comp etc and Si

Increased Si with exercise (∼26%) Si response inversely related to age When age-stratified, post-training Si + 72% in young (5.77 ± 0.73 vs 9.92 ± 1.36; p < 0.001), +20% for middle aged (5.42 ± 0.68 vs 6.52 ± 0.82; p = 0.11) and −5% for older (3.90 ± 0.44 vs 3.71 ± 0.53; p = 0.42) people. Si response unrelated to delta VO2 peak , body composition, muscle metabolic parameters etc, besides age

TRIALS OF THE EFFECT OF PHYSICAL ACTIVITY ON INSULIN SENSITIVITY

373

374

PHYSICAL ACTIVITY AND INSULIN RESISTANCE

as outcome rather than insulin measurement at fasting or during an OGTT. By contrast, the studies that were null tended to be short in duration (e.g. the Ross et al. study,100 which intervened for only 12 weeks) or both short and of lower intensity, such as the Fairey et al. trial,96 which initially encouraged brief 15 minute bouts of activity at 60–70 per cent VO2 max and only lasted a total of 15 weeks. As with the observational studies, one would ideally wish to pool the trials to give a summary estimate of the overall effect of activity intervention on insulin resistance. However, the heterogeneity of the trials in terms of the duration and intensity of the intervention and the nature of the outcome assessment make this unrealistic. It is clear from these trials that the overwhelming majority of studies confirm that activity has beneficial effects on insulin resistance, with the null studies tending to have certain methodological characteristics that might explain their failure to demonstrate an effect. That the trials of lower intensity activity tended to be null does not, in itself, suggest that such an intervention is ineffective, merely that the effect is harder to demonstrate. This is a paradox, since the real life application of these trial data is likely to involve individuals who are less willing to undertake activity, particularly when activity is more intensive. Thus the question of the benefits of lower intensity activity on insulin sensitivity remains to be demonstrated. In the one trial that included lower intensity activity and had sufficiently long duration of intervention,101 there was a significant difference in change in insulin sensitivity by comparison with a control group of individuals who were randomized to low volume, moderate intensity activity. However, the magnitude of the effect on insulin sensitivity (40 per cent reduction) was not as great as that seen in either the group of individuals who were randomized to low volume, high intensity activity or high volume, high intensity activity, in whom an 85 per cent reduction was observed. However, this study did not undertake an intention to treat analysis and even within the context of an experimental study the drop-out rate was high at 30 per cent. If such an intervention were generalized to a real-life context, the dropout rate would be likely to be much greater, and thus the difference between the overall effect of the intensive intervention compared with the less intensive would be diminished.

12.7

Trials of the effect of physical activity on insulin sensitivity in children and adolescents

A total of 14 trials were identified in children and adolescents as described in Table 12.4. Only four of these were classical randomized controlled trials, with a further five being uncontrolled and four not involving randomization. The final trial was ecological in design. Among the RCTs, two found a positive result, suggesting that markers of insulin resistance were improved following exercise intervention. However, one of these studies102 compared a dietary programme

EVIDENCE OF HETEROGENEITY OF EFFECT

375

with and without exercise against control, and as such does not shed any light on the effect of exercise alone on insulin resistance. Thus the strongest evidence comes from a single study103 in which 79 obese children (mean age 9.5 years) were randomized in a cross-over design to a 4 month exercise intervention programme aimed at adding 40 minutes a day of exercise for 5 days a week. This study demonstrated a significant decrease of 25.4 pmol/l (p < 0.05) in fasting insulin following the training period compared to an increase after cessation of training. As in many of the other trials, the magnitude of the change in insulin concentration was closely correlated with the change in percentage body fat, raising the issue of separating the effects of activity, weight change and alteration in body composition. This issue is almost impossible to resolve in experimental studies since changes in weight and physical activity are highly likely to be collinear. Attempts to adjust for differences in body composition in trials or observational studies may result in over-adjustment if at least part of the effect of changing activity is mediated through alteration in total level of obesity or its regional distribution. As in the adult studies, the issue of trials informing causal inference about the relationship between activity and insulin resistance as opposed to assessing the magnitude of achievable change in insulin sensitivity are evident in the studies of children and adolescents. For example, Kang et al.104 demonstrated that children who achieved at least a 40 per cent attendance rate in a training programme had a 17 pmol/l decrease in fasting insulin compared with a 23 pmol/l increase in those in a comparison group (p = 0.085). However, there was no difference in the intention to treat analysis, suggesting that the issue of non-compliance with the intervention is a major factor. The inference from such ‘per protocol’ analyses is stronger when they are pre-specified. It is unclear whether the restriction to the sub-group of children who attended at least 40 per cent of the time was a pre-planned analysis or one that was data driven.

12.8

Evidence of heterogeneity of the effect of physical inactivity on insulin resistance in sub-groups of the population

The currently available observational and experimental trials have concentrated on assessing the magnitude and direction of effect of physical activity on insulin sensitivity. They have thus tended to describe the overall effect and have not, to date, reported whether these effects are comparable in all population sub-groups. These questions of interaction are of interest not only in providing aetiological information, but also in a much more pragmatic sense, since the demonstration of a sizeable impact of activity on insulin resistance in a population sub-group could lead to targeted preventive interventions. None of the trials reported to date have formally assessed effect modification by age. As Tables 12.3 and 12.4 demonstrate, the effects of activity on insulin resistance have been demonstrated

Un-controlled trial Diet and physical activity intervention in obese adolescent girls

204

102

Un-controlled trial To assess the effect of an exercise programme (with diet restrictions) on insulin response in obese children RCT To assess the effect of diet and exercise on insulin resistance in obese adolescents

203

Reference

Type and objective of trial Nature of intervention Exercise 3 days/week for 5 months Intensity approx. 70% of age-predicted max. heart rate

20 week of either diet and behaviour change (DB group), diet, behaviour change and exercise (DBE group), or control group 6 week diet and exercise intervention (1–2 h per day, mainly swimming or jogging)

Participant characteristics

N 13 obese Mean age: 11.5 (8.3–13.6) years Mean weight: 74.3 kg (7.7) Ethnicity: not stated

N (m/f): 50 Age: adolescents Mean BMI: obese Nationality: Italian

N (m/f) 0/116 Mean age: 15.2 (0.4) years Mean BMI: 31.3 (4.6) Ethnicity: Caucasian

Fasting insulin

Fasting insulin

Insulin level 30 and 60 min after a mixed meal

Measure of insulin resistance

Unadjusted

Confounders adjusted for

Table 12.4 Trials of physical activity on insulin resistance in children and adolescents

Fasting insulin and sum of insulins decreased significantly in both DB and DBE, when compared with controls (p < 0.01) Significant decline in fasting insulin (3.4 mU/l, p < 0.001) Weight loss following intervention 8.5 kg (2.4) p < 0.01

Insulin level lower at 30 min and 60 min (p < 0.05) after intervention

Direction and magnitude of effect

376 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

206

205

Non-randomized controlled trial Exercise versus lifestyle education on cardiovascular risk factors in obese girls Un-controlled trial To assess the impact of a mild routine exercise programme on insulin dynamics and glucose homeostasis in obese male adolescents

N (m/f): 7/0 Mean age (SD): 13.3 (1.4) years Mean BMI: 38.8 (1.4) Ethnicity: Black and White

N (m/f): 0/24 Mean age: 9.2 years Mean BMI: not given (% fat (SD): 43.1 (1.7)) Ethnicity: Black Assignment to either a 10 week aerobic training program for 5 days/week or to lifestyle education weekly discussions 15 weeks supervised mild (60–70% of max. heart rate) routine exercise 3 days/week Post-prandial peak insulin response

Fasting insulin

Body weight, body fat

Unadjusted

(continues overleaf )

Significant decrease in peak insulin response from 819 pmol/l to 397 pmol/l (p = 0.014). AUC decreased by 50% (p = 0.017)

No significant changes observed in fasting insulin between the groups

EVIDENCE OF HETEROGENEITY OF EFFECT

377

Un-controlled trial To explore the influence of body fat distribution on atherogenic risk profile after a weight-loss programme, consisting of diet and exercise

Non-randomized controlled trial To compare the effects of diet or exercise in obese children with pre-existing hyperlipidaemia

207

208

Reference

Type and objective of trial Nature of intervention 6 week programme of a reduced calorie diet (ave. 1050 kcal/day) and an exercise component of 1–2 h aerobic exercise per day

Children self-selected to enrol into one of three groups: control, exercise or diet, over 6 weeks Exercise equated to 1 h of aerobic exercise (at 75–80% max. HR) 3 times/week

Participant characteristics

N (m/f): 0/73 Mean age (SD): 15.0 (1.1) years Mean BMI (SD): 31.1 (3.8) Ethnicity: Caucasian

N (m/f): 19/17 Mean age (SD): 9–12 years Mean BMI (SD): 28.3 (1.4) Ethnicity: Hispanic

Fasting insulin

Fasting insulin

Measure of insulin resistance

Table 12.4 (continued )

Body weight, BMI

Baseline insulin, age, baseline WHR, WHR change, body weight, body weight change

Confounders adjusted for

Reduction in fasting insulin from 14.5 mU/l to 11.6 mU/l (unadjusted p < 0.001) Baseline insulin (p < 0.01) and baseline body weight (p < 0.05) were the only significant predictors of insulin change Mean weight loss 8.1 kg (2.0) Significant reductions (p < 0.05) observed in fasting insulin (decrease of approx. 80%) in both interventions compared with control

Direction and magnitude of effect

378 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

103

209

Non-randomized controlled trial To compare difference in metabolic rate at rest and after OGTT in trained and untrained girls over a 4 year period Randomized cross-over trial To determine the effect of exercise training and its cessation on components of the insulin resistance syndrome in obese children

Training group: N (m/f): 0/12 Age: 11.7 (0.2) years Control group year 1 N (m/f): 0/13 Age: 11.5 (0.3) years Control group year 4 N (m/f): 0/18 Age: 14.4 (0.3) years Nationality: Polish N (m/f): 26/53 Mean age (SD): 9.5 (1.0) years Mean BMI: not given (% fat range: 27–61%) Ethnicity: Black, White and Asian 4 months exercise intervention (5 days/week, 40 min/day) in random cross-over trial design Mean attendance: 4 days/week

Participation in rowing practice

Fasting insulin

Biannual measurement of 2 h plasma insulin after OGTT

Gender, ethnicity

Unadjusted Age at menarche was similar for all groups

(continues overleaf )

Significant decrease (p < 0.05) in fasting insulin following training period Average decrease of 25.4 pmol/l but increase in insulin level 4 months after cessation of training Changes in insulin corresponded to changes in percentage body fat

Trained girls had lower 2 h plasma insulin after OGTT, compared with controls

EVIDENCE OF HETEROGENEITY OF EFFECT

379

Un-controlled trial To evaluate the effect of a diet and exercise programme on insulin level and hepatic insulin clearance in obese children and adolescents

Cluster randomized trial To assess the influence of exercise on plasma insulin and glucose

210

173

Reference

Type and objective of trial Nature of intervention All subjects enrolled into a 10 week programme comprising a protein-sparing modified fast diet, a moderate progressive exercise programme and a behaviourmodification intervention 8 week standard state-mandated physical activity programme (3 days/week) compared to aerobic exercise programme (20 min per session, 3 days/week)

Participant characteristics

N (m/f): 4/11 Mean age (SD): 12.3 (2.7) years Mean BMI (SD): 35.3 (7.8) Ethnicity: Black

N (m/f): 139/125 Age: 11–14 years Mean BMI: 22.4 (5) Nationality: US

Fasting insulin and glucose

Fasting insulin

Measure of insulin resistance

Table 12.4 (continued )

Body fat, gender, pubertal status and leisure-time PA (LTPA) levels (assessed by questionnaire)

Age

Confounders adjusted for

A significant reduction in fasting insulin was observed post-intervention (from 29.2 ± 13.2 µU/ml to 15.98 ± 6.55 µU/ml, p < 0.05) Significant weight loss 7.8 kg following intervention No significant improvement in VO2 max in either group Children whose VO2 max improved (n = 60) had a greater decrease in insulin: 16 vs 1 pmol/l (p = 0.028) compared with all others (n = 204)

Direction and magnitude of effect

380 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

104

211

Non-randomized trial To assess the effect of a weight loss programme involving exercise and diet on metabolic parameters in obese children Randomized controlled trial To assess the effect of physical training, especially at high intensity, on components of the insulin resistance syndrome in obese adolescents

N (m/f): 26/54 Mean age (SD): 12.0 (1.8) years Mean BMI (SD): 26.5 (5.2) Ethnicity: Black and White

N (m/f): 20/40 Mean age (SD): 12.0 (1.8) years Mean BMI (SD): 26.5 (5.2) Nationality: Austrian 3 week programme low calorie diet (1000–1200 kcals/day) and 3 exercise sessions/day (cycling, swimming, brisk jogging and football) Random assignment into one of three groups: lifestyle education (LSE), LSE with moderate PA training and LSE with intense PA training Training lasted 8 months and took place on 5 days/week Each session aimed at energy expenditure of 250 kcal Fasting insulin

Fasting insulin

Gender, ethnicity, group assignment

Body fat

(continues overleaf )

No significant difference in change in fasting insulin between intervention groups (p = 0.25) despite group differences in change in fitness (p < 0.001)

Fasting insulin was significantly reduced by 4.1 µIU/ml (p < 0.001) Mean weight loss 3.8 kg (1.2)

EVIDENCE OF HETEROGENEITY OF EFFECT

381

212

Reference

Ecological trial To assess the temporal effect of a school-based lifestyle intervention programme (exercise, diet and diabetes education) on metabolic parameters in three cohorts of Native American youth

Type and objective of trial

Baseline (m/f): 29/41 Mean BMI (m/f): 26.7/25.6 Year 1.5 (m/f): 39/25 Mean BMI (m/f): 24.2/22.7 Year 3 (m/f): 32/33 Mean BMI (m/f): 27.0/23.9 All three groups: Ethnicity: Native American (Zuni) Age: 16–19

Participant characteristics School-based intervention with no individual follow-up. Establishment of youth fitness centre in school with instructors, organization of aerobics classes, basketball tournaments, hiking, rock climbing, running, mountain biking and dances Replacement of snacks with healthy foods Diabetes prevention information

Nature of intervention Modified OGTT (fasting and 30 min) Trend test of the median and 75th percentile values of the three cohorts

Measure of insulin resistance

Table 12.4 (continued )

Stratified by gender

Confounders adjusted for

Median fasting insulin decreased by 12 pmol/l per 1.5 years (p = 0.03) in girls and 18 pmol/l per 1.5 years (p < 0.001) in boys

Direction and magnitude of effect

382 PHYSICAL ACTIVITY AND INSULIN RESISTANCE

EVIDENCE OF HETEROGENEITY OF EFFECT

383

in individuals of diverse ages, but few of the studies included individuals older than 65 years, a group rarely included in trials. Demonstration of the effects of activity on insulin resistance in older individuals is important, as this group constitutes the most sizeable sub-group in the entire population who are at risk from the effects of insulin resistance. It is also the sub-group in which the balance between the benefits of activity and its possible dis-benefits is most critical. The demonstration in observational studies of a greater propensity to insulin resistance among individuals of different ethnic origins raises the possibility that the association of activity and insulin resistance may differ between ethnic groups. This is certainly true of the relationship between measures of adiposity, ethnic origin and measures of insulin resistance,105 but remains uncertain for physical activity. Although some studies, such as that by Ku et al.,106 have begun to examine this issue, it remains unproven, largely because few observational studies have recruited sufficient numbers of individuals from different ethnic groups to undertake pre-specified sub-analyses. An additional issue in studies comparing individuals from different ethnic groups is the use of subjective selfreport as the means of assessing physical activity. As the responses to such questionnaires may be culturally specific, it would be more appropriate to utilize objective quantitative measures of activity in studies comparing the relationship of activity and insulin resistance between ethnic groups. To date, no such studies have been undertaken. The thrifty phenotype hypothesis, as described elsewhere in this book, defines a group of individuals who are at increased risk of insulin resistance through early programmed risk. Recent studies have demonstrated that there is an interaction of that risk with adult physical activity patterns. In analyses from the Kuopio Ischaemic Heart Disease Risk Factor Study, Laaksonen and colleagues reported that men in the lowest tertile for ponderal index at birth were twice as likely to have the metabolic syndrome than those in the remainder of the population distribution, an association unaffected by adjustment for socioeconomic status or adult BMI. However, there was an interaction with activity and fitness, such that thinness at birth was even more clearly associated with hyperinsulinaemia and the metabolic syndrome in inactive men (<25 minutes per week of vigorous activity) and in unfit men with a VO2 max less than 28.6 ml/kg/min. There was no association in active or fit men. Not only does this study raise the possibility of targeted exercise intervention as one response to modifying the risk associated with early development, but it also raises intriguing questions about the mechanisms underlying that risk, particularly through programming of muscle enzyme107 or genes that are associated with both obesity and metabolic disorder.108 Individuals with a family history of diabetes are more at risk of the metabolic consequences of adiposity and physical inactivity than individuals who do not have a family history.109 This has been demonstrated in cohort studies with type 2 diabetes as the outcome of interest, but there have been no reports with insulin

384

PHYSICAL ACTIVITY AND INSULIN RESISTANCE

resistance as the outcome, probably as a consequence of the paucity of longitudinal cohort study data. However, given the clear links between insulin resistance and type 2 diabetes, it is likely that such an interaction would exist. Attempts to study effect modification by family history of metabolic disease in childhood have produced negative results,110 but this may be a reflection of the limited power of such studies to date. The possibility of interaction creates opportunities for targeted prevention and indeed, at least one trial (MRC ProActive Trial) is now underway to examine the effectiveness of lifestyle approaches to promoting physical activity in individuals who are at risk of the metabolic consequences of sedentary living by virtue of having a parental history of type 2 diabetes. Using family history as an entry point for such a trial is logical as the offspring are at increased risk and that risk is tangible since a close relation is already affected by the disorder. Whether such logic could be transferred to a situation in which risk is less tangible is unclear. Family history of a disorder also implies shared risk, be that from inherited risk factors or from shared environmental influences. Although the former is fixed, it is possible to demonstrate to individuals with a family history of metabolic disease that they have a considerable amount to gain by avoidance of inactivity and weight gain. The sharing of risk through common environments also points to part of the solution, as families need to support or at the very least not obstruct each other as they attempt to increase everyday activity. A high risk targeted prevention strategy based on family history is a model for how intervention based on a high risk genotype could operate. This is, of course, a distant strategy, but the development of theoretically sound, effective and feasible interventions that could be applied in this situation needs to be undertaken simultaneously with the analysis of which genotypic information best identifies individuals at high risk. To date there are relatively few examples of gene–physical activity interaction on insulin resistance. Candidate gene association studies in observational studies provide additional information about plausible sites for gene–physical activity interaction on insulin resistance phenotypes including the β-adrenoceptor (βAR-2)111 and PPARγ.112 – 114 The ability to detect such interaction in observational studies is a function of the allele frequency, the size of the association between the exposure and the outcome and the strength of the interaction term.115 A major issue is the precision with which physical activity is quantified. In a study designed to detect gene–physical activity interaction on insulin sensitivity, more than 150 000 people would be required to detect a doubling of effect size for those with the minor allele of population frequency of 20 per cent if proxy measures of the exposure (physical activity) and outcome (insulin resistance) were used. Even if individuals were better phenotyped, perhaps by repeated measures of fasting insulin, then the study would still need between 30 000 and 50 000 individuals. However, if a study employed both a better measure of outcome and exposure, such as an objective quantitative measure of overall activity, then the same interaction could be detected in 5000 individuals.116

CONCLUSIONS

385

The Heritage Study in Canada has been at the forefront of the description of potential targets for gene–physical activity interaction. In this study, sedentary individuals aged 17–40 years were recruited to a 20 week exercise training programme. A total of 507 white subjects from 99 nuclear families were recruited, together with 283 black individuals from 105 nuclear families. The response to training data was available on 459 whites and 211 blacks, providing a total of 372 sib pairs for analysis of exercise training response phenotypes.117 There is considerable variation in the response to training, with familial aggregation of training response phenotypes.118 Following on from this, the Heritage study has formed the basis of genome wide scans for a range of different response phenotypes. In whites the strongest evidence of linkage for fasting insulin response to exercise training was in the leptin gene at 7q31, with other areas of linkage at 1q21, 2q31, 7q21–q22 and 11q13. In the blacks, the strongest linkage was at 15p11.119 The 7q21–q31 region is a particularly interesting area for genes that may plausibly interact with physical activity on insulin resistance. Not only does it include the leptin gene, but also the protein phosphatase 1 regulatory subunit 3 (PPP1R3) gene, which plays a major role in glycogen metabolism and glucose disposal in skeletal muscle. The focus on PPP1R3 is supported by growing evidence of familial resemblance in skeletal muscle histology and biochemical phenotypes.120 Common variants in this gene have been associated with insulin resistance and type 2 diabetes,121, 122 as has an uncommon frameshift mutation.123 This frameshift mutation is neither necessary nor sufficient to cause disease, but in the presence of a second apparently unrelated mutation in PPARγ gives rise to diabetes. However, studying the metabolic effects of an interaction between a mutation that is present in one per cent of the population and physical activity is a major challenge and one that would require exercise training studies with individuals selected on the basis of genotype rather than a post hoc analysis of existing trials unselected by genotype.

12.9

Conclusions

The observational epidemiological data reviewed in this chapter demonstrates that the relationship between physical activity and insulin sensitivity is strong, consistent between studies and supported by evidence of biological plausibility. The relative paucity of longitudinal studies means that the strength of evidence concerning temporal sequence from observational data is weak. However, this is more than compensated for by the abundance of clinical trial information which provides conclusive evidence that insulin sensitivity improves following increased physical activity. Although the certainty of this conclusion is greater in adults, where the number of randomized controlled trials is larger, there is a growing body of evidence in children. Heterogeneity in clinical trial methodology does not allow simple quantification of a summary effect size, but in general the larger RCTs with more intensive intervention over a prolonged

386

PHYSICAL ACTIVITY AND INSULIN RESISTANCE

period of time produce comparable results. The translation of these clinical trial results into practice is hampered by patient adherence. A major area of future research will be in the quantification of the benefits on insulin sensitivity of less intensive physical activity interventions, which are likely to be more easily implemented in everyday life. Although such interventions to increase activity need to be aimed at everyone since declining physical activity is a collective problem fundamentally determined by societal influences, there is a strong case for targeting individual-level physical activity interventions at those who are most likely to take them up and who are most likely to have major metabolic advantages to being more active. Whether one defines these high risk groupings on current metabolic phenotype such as impaired glucose tolerance, or on other characteristics such as ethnic origin, early life development, family history or genetic factors, remains to be determined. The study of these interactions will provide pragmatic information concerning who to target and also considerable insights into the mechanisms by which physical activity has its effect on insulin sensitivity.

References 1. Bradford Hill, A. (1965) Environment and disease: association or causation? J R Soc Med 58, 295–300. 2. Ross, R. (1997) Effects of diet- and exercise-induced weight loss on visceral adipose tissue in men and women. Sports Med 24, 55–64. 3. Palaniappan, L., Anthony, M. N., Mahesh, C., Elliott, M., Killeen, A., Giacherio, D. and Rubenfire, M. (2002) Cardiovascular risk factors in ethnic minority women aged < or = 30 years. Am J Cardiol 89, 524–529. 4. Parker, L., Lamont, D. W., Unwin, N., Pearce, M. S., Bennett, S. M., Dickinson, H. O., White, M., Mathers, J. C., Alberti, K. G. and Craft, A. W. (2003) A lifecourse study of risk for hyperinsulinaemia, dyslipidaemia and obesity (the central metabolic syndrome) at age 49–51 years. Diabet Med 20, 406–415. 5. Ramachandran, A., Snehalatha, C., Latha, E., Vijay, V. and Viswanathan, M. (1997) Rising prevalence of NIDDM in an urban population in India. Diabetologia 40, 232–237. 6. Boule, N. G., Haddad, E., Kenny, G. P., Wells, G. A. and Sigal, R. J. (2001) Effects of exercise on glycemic control and body mass in type 2 diabetes mellitus: A meta-analysis of controlled clinical trials. JAMA 286, 1218–1227. 7. Wareham, N. J. and Rennie, K. L. (1998) The assessment of physical activity in individuals and populations: why try to be more precise about how physical activity is assessed? Int J Obes Relat Metab Disord 22 (Suppl. 2), S30–S38. 8. Goran, M. I. and Poehlman, E. T. (1992) Endurance training does not enhance total energy expenditure in healthy elderly persons. Am J Physiol Endocrinol Metab 263, E950–E957. 9. Brown, M. D., Korytkowski, M. T., Zmuda, J. M., McCole, S. D., Moore, G. E. and Hagberg, J. M. (2000) Insulin sensitivity in postmenopausal women: independent and combined associations with hormone replacement, cardiovascular fitness, and body composition. Diabetes Care 23, 1731–1736.

REFERENCES

387

10. Wareham, N. J., Wong, M. Y. and Day, N. E. (2000) Glucose intolerance and physical inactivity: the relative importance of low habitual energy expenditure and cardiorespiratory fitness. Am J Epidemiol 152, 132–139. 11. Wong, M. Y., Day, N. E. and Wareham, N. J. (1999) Measurement error in epidemiology: the design of validation studies II: bivariate situation. Stat Med 18, 2831–2845. 12. Craig, S. B., Bandini, L. G., Lichtenstein, A. H., Schaefer, E. J. and Dietz, W. H. (1996) The impact of physical activity on lipids, lipoproteins, and blood pressure in preadolescent girls. Pediatrics 98, 389–395. 13. Matsui, I., Nambu, S. and Baba, S. (1998) Evaluation of fasting serum insulin levels among Japanese school-age children. J Nutr Sci Vitaminol (Tokyo) 44, 819–828. 14. Raitakari, O. T., Porkka, K. V., Taimela, S., Telama, R., Rasanen, L. and Viikari, J. S. (1994) Effects of persistent physical activity and inactivity on coronary risk factors in children and young adults. The Cardiovascular Risk in Young Finns Study. Am J Epidemiol 140, 195–205. 15. Ploug, T. and Ralston, E. (1998) Anatomy of glucose transporters in skeletal muscle. Effects of insulin and contractions. Adv Exp Med Biol 441, 17–26. 16. Ploug, T., Wojtaszewski, J., Kristiansen, S., Hespel, P., Galbo, H. and Richter, E. A. (1993) Glucose transport and transporters in muscle giant vesicles: differential effects of insulin and contractions. Am J Physiol 264, E270–E278. 17. Richter, E. A., Ploug, T. and Galbo, H. (1985) Increased muscle glucose uptake after exercise. No need for insulin during exercise. Diabetes 34, 1041–1048. 18. Ploug, T., Galbo, H. and Richter, E. A. (1984) Increased muscle glucose uptake during contractions: no need for insulin. Am J Physiol 247, E726–E731. 19. Ploug, T., Galbo, H., Vinten, J., Jorgensen, M. and Richter, E. A. (1987) Kinetics of glucose transport in rat muscle: effects of insulin and contractions. Am J Physiol 253, E12–E20. 20. Ploug, T., Galbo, H., Ohkuwa, T., Tranum-Jensen, J. and Vinten, J. (1992) Kinetics of glucose transport in rat skeletal muscle membrane vesicles: effects of insulin and contractions. Am J Physiol 262, E700–E711. 21. Cushman, S. W., Goodyear, L. J., Pilch, P. F., Ralston, E., Galbo, H., Ploug, T., Kristiansen, S. and Klip, A. (1998) Molecular mechanisms involved in GLUT4 translocation in muscle during insulin and contraction stimulation. Adv Exp Med Biol 441, 63–71. 22. Thorell, A., Hirshman, M. F., Nygren, J., Jorfeldt, L., Wojtaszewski, J. F., Dufresne, S. D., Horton, E. S., Ljungqvist, O. and Goodyear, L. J. (1999) Exercise and insulin cause GLUT-4 translocation in human skeletal muscle. Am J Physiol 277, E733–E741. 23. Lemieux, K., Han, X. X., Dombrowski, L., Bonen, A. and Marette, A. (2000) The transferrin receptor defines two distinct contraction-responsive GLUT4 vesicle populations in skeletal muscle. Diabetes 49, 183–189. 24. Ploug, T., van Deurs, B., Ai, H., Cushman, S. W. and Ralston, E. (1998) Analysis of GLUT4 distribution in whole skeletal muscle fibers: identification of distinct storage compartments that are recruited by insulin and muscle contractions. J Cell Biol 142, 1429–1446. 25. Ploug, T. and Ralston, E. (2002) Exploring the whereabouts of GLUT4 in skeletal muscle [review]. Mol Membr Biol 19, 39–49. 26. Sevilla, L., Tomas, E., Munoz, P., Guma, A., Fischer, Y., Thomas, J., RuizMontasell, B., Testar, X., Palacin, M., Blasi, J. and Zorzano, A. (1997) Characterization of two distinct intracellular GLUT4 membrane populations in muscle fiber. Differential protein composition and sensitivity to insulin. Endocrinology 138, 3006–3015.

388

PHYSICAL ACTIVITY AND INSULIN RESISTANCE

27. Tomas, E., Sevilla, L., Palacin, M. and Zorzano, A. (2001) The insulin-sensitive GLUT4 storage compartment is a postendocytic and heterogeneous population recruited by acute exercise. Biochem Biophys Res Commun 284, 490–495. 28. Zierath, J. R. (2002) Invited review: Exercise training-induced changes in insulin signaling in skeletal muscle. J Appl Physiol 93, 773–781. 29. Tomas, E., Zorzano, A. and Ruderman, N. B. (2002) Exercise and insulin signaling: a historical perspective. J Appl Physiol 93, 765–772. 30. Yu, M., Blomstrand, E., Chibalin, A. V., Wallberg-Henriksson, H., Zierath, J. R. and Krook, A. (2001) Exercise-associated differences in an array of proteins involved in signal transduction and glucose transport. J Appl Physiol 90, 29–34. 31. Chibalin, A. V., Yu, M., Ryder, J. W., Song, X. M., Galuska, D., Krook, A., WallbergHenriksson, H. and Zierath, J. R. (2000) Exercise-induced changes in expression and activity of proteins involved in insulin signal transduction in skeletal muscle: differential effects on insulin-receptor substrates 1 and 2. Proc Natl Acad Sci USA 97, 38–43. 32. Tsao, T. S., Li, J., Chang, K. S., Stenbit, A. E., Galuska, D., Anderson, J. E., Zierath, J. R., McCarter, R. J. and Charron, M. J. (2001) Metabolic adaptations in skeletal muscle overexpressing GLUT4: effects on muscle and physical activity. FASEB J 15, 958–969. 33. Charron, M. J., Katz, E. B. and Zierath, J. R. (1997) Metabolic and molecular consequences of modifying GLUT4 expression in skeletal muscle. Biochem Soc Trans 25, 963–968. 34. Ren, J. M., Semenkovich, C. F., Gulve, E. A., Gao, J. and Holloszy, J. O. (1994) Exercise induces rapid increases in GLUT4 expression, glucose transport capacity, and insulin-stimulated glycogen storage in muscle. J Biol Chem 269, 14 396–14 401. 35. Derave, W., Eijnde, B. O., Verbessem, P., Ramaekers, M., Van Leemputte, M., Richter, E. A. and Hespel, P. (2003) Combined creatine and protein supplementation in conjunction with resistance training promotes muscle GLUT-4 content and glucose tolerance in humans. J Appl Physiol 94, 1910–1916. 36. Widegren, U., Jiang, X. J., Krook, A., Chibalin, A. V., Bjornholm, M., Tally, M., Roth, R. A., Henriksson, J., Wallberg-Henriksson, H. and Zierath, J. R. (1998) Divergent effects of exercise on metabolic and mitogenic signaling pathways in human skeletal muscle. FASEB J 12, 1379–1389. 37. Ryder, J. W., Fahlman, R., Wallberg-Henriksson, H., Alessi, D. R., Krook, A. and Zierath, J. R. (2000) Effect of contraction on mitogen-activated protein kinase signal transduction in skeletal muscle. Involvement of the mitogen- and stress-activated protein kinase 1. J Biol Chem 275, 1457–1462. 38. Krook, A., Widegren, U., Jiang, X. J., Henriksson, J., Wallberg-Henriksson, H., Alessi, D. and Zierath, J. R. (2000) Effects of exercise on mitogen- and stress-activated kinase signal transduction in human skeletal muscle. Am J Physiol Regul Integr Comp Physiol 279, R1716–R1721. 39. Widegren, U., Ryder, J. W. and Zierath, J. R. (2001) Mitogen-activated protein kinase signal transduction in skeletal muscle: effects of exercise and muscle contraction. Acta Physiol Scand 172, 227–238. 40. Yu, M., Blomstrand, E., Chibalin, A. V., Krook, A. and Zierath, J. R. (2001) Marathon running increases ERK1/2 and p38 MAP kinase signalling to downstream targets in human skeletal muscle. J Physiol 536, 273–282. 41. Wadley, G. D., Tunstall, R. J., Sanigorski, A., Collier, G. R., Hargreaves, M. and Cameron-Smith, D. (2001) Differential effects of exercise on insulin-signaling gene expression in human skeletal muscle. J Appl Physiol 90, 436–440.

REFERENCES

389

42. Houmard, J. A., Shaw, C. D., Hickey, M. S. and Tanner, C. J. (1999) Effect of shortterm exercise training on insulin-stimulated PI 3-kinase activity in human skeletal muscle. Am J Physiol 277, E1055–E1060. 43. Tanner, C. J., Koves, T. R., Cortright, R. L., Pories, W. J., Kim, Y. B., Kahn, B. B., Dohm, G. L. and Houmard, J. A. (2002) Effect of short-term exercise training on insulin-stimulated PI 3-kinase activity in middle-aged men. Am J Physiol Endocrinol Metab 282, E147–E153. 44. Zierath, J. R., Houseknecht, K. L., Gnudi, L. and Kahn, B. B. (1997) High-fat feeding impairs insulin-stimulated GLUT4 recruitment via an early insulin-signaling defect. Diabetes 46, 215–223. 45. Greco, A. V., Mingrone, G., Giancaterini, A., Manco, M., Morroni, M., Cinti, S., Granzotto, M., Vettor, R., Camastra, S. and Ferrannini, E. (2002) Insulin resistance in morbid obesity: reversal with intramyocellular fat depletion. Diabetes 51, 144–151. 46. Ashley, M. A., Buckley, A. J., Criss, A. L., Ward, J. A., Kemp, A., Garnett, S., Cowell, C. T., Baur, L. A. and Thompson, C. H. (2002) Familial, anthropometric, and metabolic associations of intramyocellular lipid levels in prepubertal males. Pediatr Res 51, 81–86. 47. Boden, G. (1999) Free fatty acids, insulin resistance, and type 2 diabetes mellitus. Proc Assoc Am Physicians 111, 241–248. 48. Boden, G. and Shulman, G. I. (2002) Free fatty acids in obesity and type 2 diabetes: defining their role in the development of insulin resistance and beta-cell dysfunction. Eur J Clin Invest 32 (Suppl. 3), 14–23. 49. Boden, G. (2002) Interaction between free fatty acids and glucose metabolism. Curr Opin Clin Nutr Metab Care 5, 545–549. 50. Boden, G. (2003) Effects of free fatty acids (FFA) on glucose metabolism: significance for insulin resistance and type 2 diabetes. Exp Clin Endocrinol Diabetes 111, 121–124. 51. Hamilton, M. T., Areiqat, E., Hamilton, D. G. and Bey, L. (2001) Plasma triglyceride metabolism in humans and rats during aging and physical inactivity. Int J Sport Nutr Exerc Metab 11 (Suppl.), S97–S104. 52. Lehmann, R., Engler, H., Honegger, R., Riesen, W. and Spinas, G. A. (2001) Alterations of lipolytic enzymes and high-density lipoprotein subfractions induced by physical activity in type 2 diabetes mellitus. Eur J Clin Invest 31, 37–44. 53. Sviridov, D., Kingwell, B., Hoang, A., Dart, A. and Nestel, P. (2003) Single session exercise stimulates formation of pre beta 1-HDL in leg muscle. J Lipid Res 44, 522–526. 54. Gill, J. M. and Hardman, A. E. (2003) Exercise and postprandial lipid metabolism: an update on potential mechanisms and interactions with high-carbohydrate diets [review]. J Nutr Biochem 14, 122–132. 55. MacAuley, D., McCrum, E. E., Stott, G., Evans, A. E., Duly, E., Trinick, T., Sweeney, K. and Boreham, C. A. (1996) Physical activity, lipids, apolipoproteins, and Lp(a) in the Northern Ireland Health and Activity Survey. Med Sci Sports Exerc 28, 720–736. 56. Hickner, R. C., Racette, S. B., Binder, E. F., Fisher, J. S. and Kohrt, W. M. (2000) Effects of 10 days of endurance exercise training on the suppression of whole body and regional lipolysis by insulin. J Clin Endocrinol Metab 85, 1498–1504. 57. Hickner, R. C., Racette, S. B., Binder, E. F., Fisher, J. S. and Kohrt, W. M. (1999) Suppression of whole body and regional lipolysis by insulin: effects of obesity and exercise. J Clin Endocrinol Metab 84, 3886–3895. 58. Franks, P. W., Wong, M. Y., Luan, J., Mitchell, J., Hennings, S. and Wareham, N. J. (2002) Non-esterified fatty acid levels and physical inactivity: the relative importance of low habitual energy expenditure and cardio-respiratory fitness. Br J Nutr 88, 307–313.

390

PHYSICAL ACTIVITY AND INSULIN RESISTANCE

59. Kiens, B., Lithell, H., Mikines, K. J. and Richter, E. A. (1989) Effects of insulin and exercise on muscle lipoprotein lipase activity in man and its relation to insulin action. J Clin Invest 84, 1124–1129. 60. Tunstall, R. J., Mehan, K. A., Wadley, G. D., Collier, G. R., Bonen, A., Hargreaves, M. and Cameron-Smith, D. (2002) Exercise training increases lipid metabolism gene expression in human skeletal muscle. Am J Physiol Endocrinol Metab 283, E66–E72. 61. Kraus, W. E., Houmard, J. A., Duscha, B. D., Knetzger, K. J., Wharton, M. B., McCartney, J. S., Bales, C. W., Henes, S., Samsa, G. P., Otvos, J. D., Kulkarni, K. R. and Slentz, C. A. (2002) Effects of the amount and intensity of exercise on plasma lipoproteins. N Engl J Med 347, 1483–1492. 62. Israel, R. G., Davidson, P. C., Albrink, M. J. and Krall, J. M. (1981) Exercise effects on fitness, lipids, glucose tolerance and insulin levels in young adults. Arch Phys Med Rehabil 62, 336–341. 63. Hedman, A., Byberg, L., Reneland, R. and Lithell, H. O. (2002) Muscle morphology, self-reported physical activity and insulin resistance syndrome. Acta Physiol Scand 175, 325–332. 64. Utriainen, T., Makimattila, S., Virkamaki, A., Lindholm, H., Sovijarvi, A. and YkiJarvinen, H. (1996) Physical fitness and endothelial function (nitric oxide synthesis) are independent determinants of insulin-stimulated blood flow in normal subjects. J Clin Endocrinol Metab 81, 4258–4263. 65. Utriainen, T., Holmang, A., Bjorntorp, P., Makimattila, S., Sovijarvi, A., Lindholm, H. and Yki-Jarvinen, H. (1996) Physical fitness, muscle morphology, and insulinstimulated limb blood flow in normal subjects. Am J Physiol 270, E905–E911. 66. Turcotte, L. P., Petry, C., Kiens, B. and Richter, E. A. (1998) Contraction-induced increase in Vmax of palmitate uptake and oxidation in perfused skeletal muscle. J Appl Physiol 84, 1788–1794. 67. Turcotte, L. P., Richter, E. A. and Kiens, B. (1992) Increased plasma FFA uptake and oxidation during prolonged exercise in trained vs. untrained humans. Am J Physiol 262, E791–E799. 68. Dumortier, M., Perez-Martin, A., Pierrisnard, E., Mercier, J. and Brun, J. F. (2002) Regular exercise (3×45 min/wk) decreases plasma viscosity in sedentary obese, insulin resistant patients parallel to an improvement in fitness and a shift in substrate oxidation balance. Clin Hemorheol Microcirc 26, 219–229. 69. Glatz, J. F., Bonen, A. and Luiken, J. J. (2002) Exercise and insulin increase muscle fatty acid uptake by recruiting putative fatty acid transporters to the sarcolemma. Curr Opin Clin Nutr Metab Care 5, 365–370. 70. Kiens, B., Kristiansen, S., Jensen, P., Richter, E. A. and Turcotte, L. P. (1997) Membrane associated fatty acid binding protein (FABPpm) in human skeletal muscle is increased by endurance training. Biochem Biophys Res Commun 231, 463–465. 71. Durham, W. J., Yeckel, C. W., Miller, S. L., Gore, D. C. and Wolfe, R. R. (2003) Exogenous nitric oxide increases basal leg glucose uptake in humans. Metabolism 52, 662–665. 72. Richter, E. A., Derave, W. and Wojtaszewski, J. F. (2001) Glucose, exercise and insulin: emerging concepts. J Physiol 535, 313–322. 73. Stuhlinger, M. C., Abbasi, F., Chu, J. W., Lamendola, C., McLaughlin, T. L., Cooke, J. P., Reaven, G. M. and Tsao, P. S. (2002) Relationship between insulin resistance and an endogenous nitric oxide synthase inhibitor. JAMA 287, 1420–1426. 74. Tooke, J. E. and Hannemann, M. M. (2000) Adverse endothelial function and the insulin resistance syndrome. J Intern Med 247, 425–431.

REFERENCES

391

75. Kingwell, B. A., Formosa, M., Muhlmann, M., Bradley, S. J. and McConell, G. K. (2002) Nitric oxide synthase inhibition reduces glucose uptake during exercise in individuals with type 2 diabetes more than in control subjects. Diabetes 51, 2572–2580. 76. Kingwell, B. A. and Jennings, G. L. (1997) The exercise prescription: focus on vascular mechanisms. Blood Press Monit 2, 139–145. 77. Paton, J. F., Kasparov, S. and Paterson, D. J. (2002) Nitric oxide and autonomic control of heart rate: a question of specificity. Trends Neurosci 25, 626–631. 78. El Haschimi, K. and Lehnert, H. (2003) Leptin resistance – or why leptin fails to work in obesity. Exp Clin Endocrinol Diabetes 111, 2–7. 79. Wauters, M., Considine, R. V., Chagnon, M., Mertens, I., Rankinen, T., Bouchard, C. and Van Gaal, L. F. (2002) Leptin levels, leptin receptor gene polymorphisms, and energy metabolism in women. Obes Res 10, 394–400. 80. Ruige, J. B., Dekker, J. M., Blum, W. F., Stehouwer, C. D., Nijpels, G., Mooy, J., Kostense, P. J., Bouter, L. M. and Heine, R. J. (1999) Leptin and variables of body adiposity, energy balance, and insulin resistance in a population-based study. The Hoorn Study. Diabetes Care 22, 1097–1104. 81. Perusse, L., Collier, G., Gagnon, J., Leon, A. S., Rao, D. C., Skinner, J. S., Wilmore, J. H., Nadeau, A., Zimmet, P. Z. and Bouchard, C. (1997) Acute and chronic effects of exercise on leptin levels in humans. J Appl Physiol 83, 5–10. 82. Wauters, M., Mertens, I., Rankinen, T., Chagnon, M., Bouchard, C. and Van Gaal, L. (2001) Leptin receptor gene polymorphisms are associated with insulin in obese women with impaired glucose tolerance. J Clin Endocrinol Metab 86, 3227–3232. 83. Wauters, M., Considine, R. V., Yudkin, J. S., Peiffer, F., De, L. I. and Van Gaal, L. F. (2003) Leptin levels in type 2 diabetes: associations with measures of insulin resistance and insulin secretion. Horm Metab Res 35, 92–96. 84. Wauters, M., Considine, R. V. and Van Gaal, L. F. (2000) Human leptin: from an adipocyte hormone to an endocrine mediator. Eur J Endocrinol 143, 293–311. 85. Franks, P. W., Farooqi, I. S., Luan, J., Wong, M. Y., Halsall, I., O’Rahilly, S. and Wareham, N. J. (2003) Does physical activity energy expenditure explain the betweenindividual variation in plasma leptin concentrations after adjusting for differences in body composition? J Clin Endocrinol Metab 88, 3258–3263. 86. Perusse, L., Rankinen, T., Rauramaa, R., Rivera, M. A., Wolfarth, B. and Bouchard, C. (2003) The human gene map for performance and health-related fitness phenotypes: the 2002 update. Med Sci Sports Exerc 35, 1248–1264. 87. Booth, F. W., Chakravarthy, M. V. and Spangenburg, E. E. (2002) Exercise and gene expression: physiological regulation of the human genome through physical activity. J Physiol 543, 399–411. 88. Attie, A. D. and Kendziorski, C. M. (2003) PGC-1alpha at the crossroads of type 2 diabetes. Nat Genet 34, 244–245. 89. Mootha, V. K., Lindgren, C. M., Eriksson, K. F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstrale, M., Laurila, E., Houstis, N., Daly, M. J., Patterson, N., Mesirov, J. P., Golub, T. R., Tamayo, P., Spiegelman, B., Lander, E. S., Hirschhorn, J. N., Altshuler, D. and Groop, L. C. (2003) PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet 34, 267–273. 90. Franks, P. W., Barroso, I., Luan, J., Ekelund, U., Crowley, V. E. F., Brage, S., Sandhu, M. S., Jakes, R. W., Middelberg, R. P. S., Harding, A. H., Brage, S., Schafer, A. J., O’Rahilly, S. and Wareham, N. (2003) PGC-1a genotype modifies the relationship between volitional energy expenditure and VO2 max . Med Sci Sports Exerc 35.

392

PHYSICAL ACTIVITY AND INSULIN RESISTANCE

91. Chung, W. K., Luke, A., Cooper, R. S., Rotini, C., Vidal-Puig, A., Rosenbaum, M., Chua, M., Solanes, G., Zheng, M., Zhao, L., LeDuc, C., Eisberg, A., Chu, F., Murphy, E., Schreier, M., Aronne, L., Caprio, S., Kahle, B., Gordon, D., Leal, S. M., Goldsmith, R., Andreu, A. L., Bruno, C., DiMauro, S. and Leibel, R. L. (1999) Genetic and physiologic analysis of the role of uncoupling protein 3 in human energy homeostasis. Diabetes 48, 1890–1895. 92. Chung, W. K., Luke, A., Cooper, R. S., Rotini, C., Vidal-Puig, A., Rosenbaum, M., Gordon, D., Leal, S. M., Caprio, S., Goldsmith, R., Andreu, A. L., Bruno, C., DiMauro, S., Heo, M., Lowe, W. L., Jr., Lowell, B. B., Allison, D. B. and Leibel, R. L. (1999) The long isoform uncoupling protein-3 (UCP3L) in human energy homeostasis. Int J Obes Relat Metab Disord 23 (Suppl 6), S49–S50. 93. Torjesen, P. A., Birkeland, K. I., Anderssen, S. A., Hjermann, I., Holme, I. and Urdal, P. (1997) Lifestyle changes may reverse development of the insulin resistance syndrome. The Oslo Diet and Exercise Study: a randomized trial. Diabetes Care 20, 26–31. 94. Ross, R., Dagnone, D., Jones, P. J., Smith, H., Paddags, A., Hudson, R. and Janssen, I. (2000) Reduction in obesity and related comorbid conditions after diet-induced weight loss or exercise-induced weight loss in men. A randomized, controlled trial. Ann Intern Med 133, 92–103. 95. Eriksson, J., Lindstrom, J., Valle, T., Aunola, S., Hamalainen, H., Ilanne-Parikka, P., Keinanen-Kiukaanniemi, S., Laakso, M., Lauhkonen, M., Lehto, P., Lehtonen, A., Louheranta, A., Mannelin, M., Martikkala, V., Rastas, M., Sundvall, J., Turpeinen, A., Viljanen, T., Uusitupa, M. and Tuomilehto, J. (1999) Prevention of type II diabetes in subjects with impaired glucose tolerance: the Diabetes Prevention Study (DPS) in Finland. Study design and 1-year interim report on the feasibility of the lifestyle intervention programme. Diabetologia 42, 793–801. 96. Fairey, A. S., Courneya, K. S., Field, C. J., Bell, G. J., Jones, L. W. and Mackey, J. R. (2003) Effects of exercise training on fasting insulin, insulin resistance, insulin-like growth factors, and insulin-like growth factor binding proteins in postmenopausal breast cancer survivors: a randomized controlled trial. Cancer Epidemiol Biomarkers Prev 12, 721–727. 97. Bunout, D., Barrera, G., de la Maza, P., Gattas, V. and Hirsch, S. (2003) Seasonal variation in insulin sensitivity in healthy elderly people. Nutrition 19, 310–316. 98. Asikainen, T. M., Miilunpalo, S., Kukkonen-Harjula, K., Nenonen, A., Pasanen, M., Rinne, M., Uusi-Rasi, K., Oja, P. and Vuori, I. (2003) Walking trials in postmenopausal women: effect of low doses of exercise and exercise fractionization on coronary risk factors. Scand J Med Sci Sports 13, 284–292. 99. Short, K. R., Vittone, J. L., Bigelow, M. L., Proctor, D. N., Rizza, R. A., CoenenSchimke, J. M. and Nair, K. S. (2003) Impact of aerobic exercise training on agerelated changes in insulin sensitivity and muscle oxidative capacity. Diabetes 52, 1888–1896. 100. Ross, R., Dagnone, D., Jones, P. J., Smith, H., Paddags, A., Hudson, R. and Janssen, I. (2000) Reduction in obesity and related comorbid conditions after diet-induced weight loss or exercise-induced weight loss in men. A randomized, controlled trial. Ann Intern Med 133, 92–103. 101. Houmard, J. A., Tanner, C. J., Slentz, C. A., Duscha, B. D., McCartney, J. S. and Kraus, W. E. (2003) The effect of the volume and intensity of exercise training on insulin sensitivity. J Appl Physiol. 102. Rocchini, A. P., Katch, V., Schork, A. and Kelch, R. P. (1987) Insulin and blood pressure during weight loss in obese adolescents. Hypertension 10, 267–273.

REFERENCES

393

103. Ferguson, M. A., Gutin, B., Le, N. A., Karp, W., Litaker, M., Humphries, M., Okuyama, T., Riggs, S. and Owens, S. (1999) Effects of exercise training and its cessation on components of the insulin resistance syndrome in obese children. Int J Obes Relat Metab Disord 23, 889–895. 104. Kang, H. S., Gutin, B., Barbeau, P., Owens, S., Lemmon, C. R., Allison, J., Litaker, M. S. and Le, N. A. (2002) Physical training improves insulin resistance syndrome markers in obese adolescents. Med Sci Sports Exerc 34, 1920–1927. 105. Whincup, P. H., Gilg, J. A., Papacosta, O., Seymour, C., Miller, G. J., Alberti, K. G. and Cook, D. G. (2002) Early evidence of ethnic difference in cardiovascular risk: cross sectional comparison of British South Asian and white children. BMJ 324, 1–6. 106. Ku, C. Y., Gower, B. A., Hunter, G. R. and Goran, M. I. (2000) Racial differences in insulin secretion and sensitivity in prepubertal children: role of physical fitness and physical activity. Obes Res 8, 506–515. 107. Ozanne, S. E., Olsen, G. S., Hansen, L. L., Tingey, K. J., Nave, B. T., Wang, C. L., Hartil, K., Petry, C. J., Buckley, A. J. and Mosthaf-Seedorf, L. (2003) Early growth restriction leads to down regulation of protein kinase C zeta and insulin resistance in skeletal muscle. J Endocrinol 177, 235–241. 108. Lindsay, R. S., Dabelea, D., Roumain, J., Hanson, R. L., Bennett, P. H. and Knowler, W. C. (2000) Type 2 diabetes and low birth weight: the role of paternal inheritance in the association of low birth weight and diabetes. Diabetes 49, 445–449. 109. Sargeant, L. A., Wareham, N. J. and Khaw, K. T. (2000) Family history of diabetes identifies a group at increased risk for the metabolic consequences of obesity and physical inactivity in EPIC-Norfolk: a population-based study. The European Prospective Investigation into Cancer. Int J Obes Relat Metab Disord 24, 1333–1339. 110. Danadian, K., Balasekaran, G., Lewy, V., Meza, M. P., Robertson, R. and Arslanian, S. A. (1999) Insulin sensitivity in African-American children with and without family history of type 2 diabetes. Diabetes Care 22, 1325–1329. 111. Meirhaeghe, A., Luan, J., Selberg-Franks, P., Hennings, S., Mitchell, J., Halsall, D., O’Rahilly, S. and Wareham, N. J. (2001) The effect of the Gly16Arg polymorphism of the beta(2)-adrenergic receptor gene on plasma free fatty acid levels is modulated by physical activity. J Clin Endocrinol Metab 86, 5881–5887. 112. Franks, P. W., Luan, J., Browne, P. O., Harding, A.-H., O’Rahilly, S., Chatterjee, V. K. K. and Wareham, N. J. (2004) Does peroxisome proliferator-activated receptor [gamma] genotype (Pro12ala) modify the association of physical activity and dietary fat with fasting insulin level? Metabolism 53, 11–16. 113. Kahara, T., Takamura, T., Hayakawa, T., Nagai, Y., Yamaguchi, H., Katsuki, T., Katsuki, K., Katsuki, M. and Kobayashi, K. (2003) PPARgamma gene polymorphism is associated with exercise-mediated changes of insulin resistance in healthy men. Metabolism 52, 209–212. 114. Lindi, V. I., Uusitupa, M. I., Lindstrom, J., Louheranta, A., Eriksson, J. G., Valle, T. T., Hamalainen, H., Ilanne-Parikka, P., Keinanen-Kiukaanniemi, S., Laakso, M. and Tuomilehto, J. (2002) Association of the Pro12Ala polymorphism in the PPAR-gamma2 gene with 3-year incidence of type 2 diabetes and body weight change in the Finnish Diabetes Prevention Study. Diabetes 51, 2581–2586. 115. Luan, J. A., Wong, M. Y., Day, N. E. and Wareham, N. J. (2001) Sample size determination for studies of gene–environment interaction. Int J Epidemiol 30, 1035–1040. 116. Wong, M. Y., Day, N. E., Luan, J. A., Chan, K. P. and Wareham, N. J. (2003) The detection of gene–environment interaction for continuous traits: should we deal with measurement error by bigger studies or better measurement? Int J Epidemiol 32, 51–57.

394

PHYSICAL ACTIVITY AND INSULIN RESISTANCE

117. Bouchard, C., Leon, A. S., Rao, D. C., Skinner, J. S., Wilmore, J. H. and Gagnon, J. (1995) The HERITAGE family study. Aims, design, and measurement protocol. Med Sci Sports Exerc 27, 721–729. 118. Bouchard, C. and Rankinen, T. (2001) Individual differences in response to regular physical activity. Med Sci Sports Exerc 33, S446–S451. 119. Lakka, T. A., Rankinen, T., Weisnagel, S. J., Chagnon, Y. C., Rice, T., Leon, A. S., Skinner, J. S., Wilmore, J. H., Rao, D. C. and Bouchard, C. (2003) A quantitative trait locus on 7q31 for the changes in plasma insulin in response to exercise training: the HERITAGE Family Study. Diabetes 52, 1583–1587. 120. Rico-Sanz, J., Rankinen, T., Joanisse, D. R., Leon, A. S., Skinner, J. S., Wilmore, J. H., Rao, D. C. and Bouchard, C. (2003) Familial resemblance for muscle phenotypes in the HERITAGE Family Study. Med Sci Sports Exerc 35, 1360–1366. 121. Xia, J., Scherer, S. W., Cohen, P. T., Majer, M., Xi, T., Norman, R. A., Knowler, W. C., Bogardus, C. and Prochazka, M. (1998) A common variant in PPP1R3 associated with insulin resistance and type 2 diabetes. Diabetes 47, 1519–1524. 122. Hansen, L. (2003) Candidate genes and late-onset type 2 diabetes mellitus. Susceptibility genes or common polymorphisms? Dan Med Bull 50, 320–346. 123. Savage, D. B., Agostini, M., Barroso, I., Gurnell, M., Luan, J., Meirhaeghe, A., Harding, A. H., Ihrke, G., Rajanayagam, O., Soos, M. A., George, S., Berger, D., Thomas, E. L., Bell, J. D., Meeran, K., Ross, R. J., Vidal-Puig, A., Wareham, N. J., O’Rahilly, S., Chatterjee, V. K. and Schafer, A. J. (2002) Digenic inheritance of severe insulin resistance in a human pedigree. Nat Genet 31, 379–384. 124. Carnethon, M. R., Fortmann, S. P., Palaniappan, L., Duncan, B. B., Schmidt, M. I. and Chambless, L. E. (2003) Risk factors for progression to incident hyperinsulinemia: the Atherosclerosis Risk in Communities Study, 1987–1998. Am J Epidemiol 158, 1058–1067. 125. Lindgarde, F. and Saltin, B. (1981) Daily physical activity, work capacity and glucose tolerance in lean and obese normoglycaemic middle-aged men. Diabetologia 20, 134–138. 126. Regensteiner, J. G., Mayer, E. J., Shetterly, S. M., Eckel, R. H., Haskell, W. L., Marshall, J. A., Baxter, J. and Hamman, R. F. (1991) Relationship between habitual physical activity and insulin levels among nondiabetic men and women. San Luis Valley Diabetes Study. Diabetes Care 14, 1066–1074. 127. Reaven, P. D., Barrett-Connor, E. and Edelstein, S. (1991) Relation between leisuretime physical activity and blood pressure in older women. Circulation 83, 559–565. 128. Manolio, T. A., Savage, P. J., Burke, G. L., Hilner, J. E., Liu, K., Orchard, T. J., Sidney, S. and Oberman, A. (1991) Correlates of fasting insulin levels in young adults: the CARDIA study. J Clin Epidemiol 44, 571–578. 129. Campbell, A. J., Busby, W. J., Horwath, C. C. and Robertson, M. C. (1993) Relation of age, exercise, anthropometric measurements, and diet with glucose and insulin levels in a population aged 70 years and over. Am J Epidemiol 138, 688–696. 130. Regensteiner, J. G., Shetterly, S. M., Mayer, E. J., Eckel, R. H., Haskell, W. L., Baxter, J. and Hamman, R. F. (1995) Relationship between habitual physical activity and insulin area among individuals with impaired glucose tolerance. The San Luis Valley Diabetes Study. Diabetes Care 18, 490–497. 131. Raitakari, O. T., Porkka, K. V., Rasanen, L. and Viikari, J. S. (1994) Relations of lifestyle with lipids, blood pressure and insulin in adolescents and young adults. The Cardiovascular Risk in Young Finns Study. Atherosclerosis 111, 237–246. 132. Sowers, M., Gonzalez, V. C., Stern, M. P., Fox, C. and Mitchell, B. D. (1995) Relationships between physical activity, insulin levels and lipids in non-diabetic low

REFERENCES

133.

134. 135.

136.

137.

138.

139.

140.

141.

142.

143.

144.

145.

146.

147.

395

income residents of Mexico City: the Mexico City Diabetes Study. Arch Med Res 26, 133–140. Singh, R. B., Niaz, M. A., Agarwal, P., Beegum, R., Rastogi, S. S. and Singh, N. K. (1995) Epidemiologic study of central obesity, insulin resistance and associated disturbances in the urban population of North India. Acta Cardiol 50, 215–225. Moller, L. F. and Jespersen, J. (1995) Fasting serum insulin levels and coronary heart disease in a Danish cohort: 17-year follow-up. J Cardiovasc Risk 2, 235–240. Eriksson, K. F. and Lindgarde, F. (1996) Poor physical fitness, and impaired early insulin response but late hyperinsulinaemia, as predictors of NIDDM in middle-aged Swedish men. Diabetologia 39, 573–579. Clausen, J. O., Borch-Johnsen, K., Ibsen, H., Bergman, R. N., Hougaard, P., Winther, K. and Pedersen, O. (1996) Insulin sensitivity index, acute insulin response, and glucose effectiveness in a population-based sample of 380 young healthy Caucasians. Analysis of the impact of gender, body fat, physical fitness, and life-style factors. J Clin Invest 98, 1195–1209. Ross, S. J., Poehlman, E. T., Johnson, R. K. and Ades, P. A. (1997) Body fat distribution predicts cardiac risk factors in older female coronary patients. J Cardiopulm Rehabil 17, 419–427. Marshall, J. A., Bessesen, D. H. and Hamman, R. F. (1997) High saturated fat and low starch and fibre are associated with hyperinsulinaemia in a non-diabetic population: the San Luis Valley Diabetes Study. Diabetologia 40, 430–438. Mayer-Davis, E. J., D’Agostino, R., Jr., Karter, A. J., Haffner, S. M., Rewers, M. J., Saad, M. and Bergman, R. N. (1998) Intensity and amount of physical activity in relation to insulin sensitivity: the Insulin Resistance Atherosclerosis Study. JAMA 279, 669–674. Dvorak, R. V., Tchernof, A., Starling, R. D., Ades, P. A., DiPietro, L. and Poehlman, E. T. (2000) Respiratory fitness, free living physical activity, and cardiovascular disease risk in older individuals: a doubly labeled water study. J Clin Endocrinol Metab 85, 957–963. Wannamethee, S. G., Shaper, A. G. and Alberti, K. G. (2000) Physical activity, metabolic factors, and the incidence of coronary heart disease and type 2 diabetes. Arch Intern Med 160, 2108–2116. Kriska, A. M., Hanley, A. J., Harris, S. B. and Zinman, B. (2001) Physical activity, physical fitness, and insulin and glucose concentrations in an isolated Native Canadian population experiencing rapid lifestyle change. Diabetes Care 24, 1787–1792. Kriska, A. M., Pereira, M. A., Hanson, R. L., de Court, Zimmet, P. Z., Alberti, K. G., Chitson, P., Bennett, P. H., Narayan, K. M. and Knowler, W. C. (2001) Association of physical activity and serum insulin concentrations in two populations at high risk for type 2 diabetes but differing by BMI. Diabetes Care 24, 1175–1180. Harding, A. H., Williams, D. E., Hennings, S. H., Mitchell, J. and Wareham, N. J. (2001) Is the association between dietary fat intake and insulin resistance modified by physical activity? Metabolism 50, 1186–1192. Forrest, K. Y., Bunker, C. H., Kriska, A. M., Ukoli, F. A., Huston, S. L. and Markovic, N. (2001) Physical activity and cardiovascular risk factors in a developing population. Med Sci Sports Exerc 33, 1598–1604. Mayer-Davis, E. J., Levin, S., Bergman, R. N., D’Agostino, R. B., Jr., Karter, A. J. and Saad, M. F. (2001) Insulin secretion, obesity, and potential behavioral influences: results from the Insulin Resistance Atherosclerosis Study (IRAS). Diabetes Metab Res Rev 17, 137–145. Irwin, M. L., Mayer-Davis, E. J., Addy, C. L., Pate, R. R., Durstine, J. L., Stolarczyk, L. M. and Ainsworth, B. E. (2000) Moderate-intensity physical activity and

396

148.

149.

150.

151.

152.

153.

154.

155.

156.

157. 158.

159. 160.

161.

PHYSICAL ACTIVITY AND INSULIN RESISTANCE

fasting insulin levels in women: the Cross-Cultural Activity Participation Study. Diabetes Care 23, 449–454. Irwin, M. L., Ainsworth, B. E., Mayer-Davis, E. J., Addy, C. L., Pate, R. R. and Durstine, J. L. (2002) Physical activity and the metabolic syndrome in a tri-ethnic sample of women. Obes Res 10, 1030–1037. Lind, L. and Andren, B. (2002) Heart rate recovery after exercise is related to the insulin resistance syndrome and heart rate variability in elderly men. Am Heart J 144, 666–672. Taylor, A. J., Watkins, T., Bell, D., Carrow, J., Bindeman, J., Scherr, D., Feuerstein, I., Wong, H., Bhattarai, S., Vaitkus, M. and O’Malley, P. G. (2002) Physical activity and the presence and extent of calcified coronary atherosclerosis. Med Sci Sports Exerc 34, 228–233. Clevenger, C. M., Parker, J. P., Tanaka, H., Seals, D. R. and DeSouza, C. A. (2002) Decline in insulin action with age in endurance-trained humans. J Appl Physiol 93, 2105–2111. Gustat, J., Srinivasan, S. R., Elkasabany, A. and Berenson, G. S. (2002) Relation of self-rated measures of physical activity to multiple risk factors of insulin resistance syndrome in young adults: the Bogalusa Heart Study. J Clin Epidemiol 55, 997–1006. Hayes, L., White, M., Unwin, N., Bhopal, R., Fischbacher, C., Harland, J. and Alberti, K. G. (2002) Patterns of physical activity and relationship with risk markers for cardiovascular disease and diabetes in Indian, Pakistani, Bangladeshi and European adults in a UK population. J Public Health Med 24, 170–178. Greenfield, J. R., Samaras, K., Jenkins, A. B., Kelly, P. J., Spector, T. D. and Campbell, L. V. (2003) Moderate alcohol consumption, estrogen replacement therapy, and physical activity are associated with increased insulin sensitivity: is abdominal adiposity the mediator? Diabetes Care 26, 2734–2740. Yao, M., Lichtenstein, A. H., Roberts, S. B., Ma, G., Gao, S., Tucker, K. L. and McCrory, M. A. (2003) Relative influence of diet and physical activity on cardiovascular risk factors in urban Chinese adults. Int J Obes Relat Metab Disord 27, 920–932. Laaksonen, D. E., Lakka, H. M., Lynch, J., Lakka, T. A., Niskanen, L., Rauramaa, R., Salonen, J. T. and Kauhanen, J. (2003) Cardiorespiratory fitness and vigorous leisuretime physical activity modify the association of small size at birth with the metabolic syndrome. Diabetes Care 26, 2156–2164. Ma, J., Liu, Z. and Ling, W. (2003) Physical activity, diet and cardiovascular disease risks in Chinese women. Public Health Nutr 6, 139–146. Pischon, T., Hankinson, S. E., Hotamisligil, G. S., Rifai, N. and Rimm, E. B. (2003) Leisure-time physical activity and reduced plasma levels of obesity-related inflammatory markers. Obes Res 11, 1055–1064. Moller, L. F. and Jespersen, J. (1995) Elevated insulin levels in men: an 11-year followup study. J Cardiovasc Risk 2, 339–343. Folsom, A. R., Jacobs, D. R., Jr., Wagenknecht, L. E., Winkhart, S. P., Yunis, C., Hilner, J. E., Savage, P. J., Smith, D. E. and Flack, J. M. (1996) Increase in fasting insulin and glucose over seven years with increasing weight and inactivity of young adults. The CARDIA Study. Coronary Artery Risk Development in Young Adults. Am J Epidemiol 144, 235–246. Byberg, L., Zethelius, B., McKeigue, P. M. and Lithell, H. O. (2001) Changes in physical activity are associated with changes in metabolic cardiovascular risk factors. Diabetologia 44, 2134–2139.

REFERENCES

397

162. Laaksonen, D. E., Lakka, H. M., Salonen, J. T., Niskanen, L. K., Rauramaa, R. and Lakka, T. A. (2002) Low levels of leisure-time physical activity and cardiorespiratory fitness predict development of the metabolic syndrome. Diabetes Care 25, 1612–1618. 163. Arslanian, S., Suprasongsin, C. and Janosky, J. E. (1997) Insulin secretion and sensitivity in black versus white prepubertal healthy children. J Clin Endocrinol Metab 82, 1923–1927. 164. Kawabe, H., Murata, K., Shibata, H., Hirose, H., Tsujioka, M., Saito, I. and Saruta, T. (2000) Participation in school sports clubs and related effects on cardiovascular risk factors in young males. Hypertens Res 23, 227–232. 165. Molnar, D. and Porszasz, J. (1990) The effect of fasting hyperinsulinaemia on physical fitness in obese children. Eur J Pediatr 149, 570–573. 166. Pinhas-Hamiel, O., Standiford, D., Hamiel, D., Dolan, L. M., Cohen, R. and Zeitler, P. S. (1999) The type 2 family: a setting for development and treatment of adolescent type 2 diabetes mellitus. Arch Pediatr Adolesc Med 153, 1063–1067. 167. T¨or¨ok, K., Szelenyi, Z., Porszasz, J. and Molnar, D. (2001) Low physical performance in obese adolescent boys with metabolic syndrome. Int J Obes Relat Metab Disord 25, 966–970. 168. Ball, G. D., Marshall, J. D. and McCargar, L. J. (2003) Fatness and fitness in obese children at low and high health risk. Ped Exerc Sci 15. 169. Molero-Conejo, E., Morales, L. M., Fernandez, V., Raleigh, X., Gomez, M. E., Semprun-Fereira, M., Campos, G. and Ryder, E. (2003) Lean adolescents with increased risk for metabolic syndrome. Arch Latinoam Nutr 53, 39–46. 170. Arslanian, S., Nixon, P. A., Becker, D. and Drash, A. L. (1990) Impact of physical fitness and glycemic control on in vivo insulin action in adolescents with IDDM. Diabetes Care 13, 9–15. 171. Gutin, B., Islam, S., Treiber, F., Smith, C. and Manos, T. (1995) Fasting insulin concentration is related to cardiovascular reactivity to exercise in children. Pediatrics 96, 1123–1125. 172. Raitakari, O. T., Taimela, S., Porkka, K. V., Telama, R., Valimaki, I., Akerblom, H. K. and Viikari, J. S. (1997) Associations between physical activity and risk factors for coronary heart disease: the Cardiovascular Risk in Young Finns Study. Med Sci Sports Exerc 29, 1055–1061. 173. McMurray, R. G., Bauman, M. J., Harrell, J. S., Brown, S. and Bangdiwala, S. I. (2000) Effects of improvement in aerobic power on resting insulin and glucose concentrations in children. Eur J Appl Physiol 81, 132–139. 174. Gallistl, S., Sudi, K. M., Borkenstein, M., Trobinger, M., Weinhandl, G. and Muntean, W. (2000) Determinants of haemostatic risk factors for coronary heart disease in obese children and adolescents. Int J Obes Relat Metab Disord 24, 1459–1464. 175. Ramirez-Lopez, G., Gonzalez-Villalpando, C., Sanchez-Corona, J., Salmeron-Castro, J., Gonzalez-Ortiz, M., Celis-de la Rosa, A. and Valles-Sanchez, V. (2001) Weight, physical activity, and smoking as determinants of insulinemia in adolescents. Arch Med Res 32, 208–213. 176. Stensel, D. J., Lin, F. P., Ho, T. F. and Aw, T. C. (2001) Serum lipids, serum insulin, plasma fibrinogen and aerobic capacity in obese and non-obese Singaporean boys. Int J Obes Relat Metab Disord 25, 984–989. 177. Schmitz, K. H., Jacobs, D. R., Jr., Hong, C. P., Steinberger, J., Moran, A. and Sinaiko, A. R. (2002) Association of physical activity with insulin sensitivity in children. Int J Obes Relat Metab Disord 26, 1310–1316. 178. Wedderkopp, N., Froberg, K., Hansen, H. S., Riddoch, C. and Andersen, L. B. (2003) Cardiovascular risk factors cluster in children and adolescents with low physical fitness: the European Youth Heart Study. Ped Exerc Sci 15, 419–427.

398

PHYSICAL ACTIVITY AND INSULIN RESISTANCE

179. Andersen, L. B., Wedderkopp, N., Hansen, H. S., Cooper, A. R. and Froberg, K. (2003) Biological cardiovascular risk factors cluster in Danish children and adolescents: the European Youth Heart Study. Prev Med 37, 363–367. 180. Ball, G. D., Shaibi, G. Q., Cruz, M. L., Watkins, M. P., Weigensberg, M. J. and Goran, M. I. (2004) Insulin sensitivity, cardiorespiratory fitness, and physical activity in overweight Hispanic youth with a family history of type 2 diabetes. Obes Res 12, 77–85. 181. Bjorntorp, P., Berchtold, P., Grimby, G., Lindholm, B., Sanne, H., Tibblin, G. and Wilhelmsen, L. (1972) Effects of physical training on glucose tolerance, plasma insulin and lipids and on body composition in men after myocardial infarction. Acta Med Scand 192, 439–443. 182. Leon, A. S., Conrad, J., Casal, D., Serfass, R., Bonnard, R., Goetz, F. C. and Blackburn, H. (1984) Exercise for diabetics: effects of conditioning at constant body weight. J Cardiac Rehabil 4, 278–286. 183. Krotkiewski, M., Lonnroth, P., Mandroukas, K., Wroblewski, Z., Rebuffe-Scrive, M., Holm, G., Smith, U. and Bjorntorp, P. (1985) The effects of physical training on insulin secretion and effectiveness and on glucose metabolism in obesity and type 2 (noninsulin-dependent) diabetes mellitus. Diabetologia 28, 881–890. 184. Holloszy, J. O., Schultz, J., Kusnierkiewicz, J., Hagberg, J. M. and Ehsani, A. A. (1986) Effects of exercise on glucose tolerance and insulin resistance. Brief review and some preliminary results. Acta Med Scand Suppl 711, 55–65. 185. Eriksson, K. F. and Lindgarde, F. (1991) Prevention of type 2 (non-insulin-dependent) diabetes mellitus by diet and physical exercise. The 6-year Malmo feasibility study. Diabetologia 34, 891–898. 186. Uusitupa, M. I. (1996) Early lifestyle intervention in patients with non-insulindependent diabetes mellitus and impaired glucose tolerance. Ann Med 28, 445–449. 187. Lindahl, B., Nilsson, T. K., Jansson, J. H., Asplund, K. and Hallmans, G. (1999) Improved fibrinolysis by intense lifestyle intervention. A randomized trial in subjects with impaired glucose tolerance. J Intern Med 246, 105–112. 188. Halle, M., Berg, A., Garwers, U., Baumstark, M. W., Knisel, W., Grathwohl, D., Konig, D. and Keul, J. (1999) Influence of 4 weeks’ intervention by exercise and diet on low-density lipoprotein subfractions in obese men with type 2 diabetes. Metabolism 48, 641–644. 189. Halle, M., Berg, A., Garwers, U., Grathwohl, D., Knisel, W. and Keul, J. (1999) Concurrent reductions of serum leptin and lipids during weight loss in obese men with type II diabetes. Am J Physiol 277, E277–E282. 190. Rowley, K. G., Daniel, M., Skinner, K., Skinner, M., White, G. A. and O’Dea, K. (2000) Effectiveness of a community-directed ‘healthy lifestyle’ program in a remote Australian aboriginal community. Aust NZ J Public Health 24, 136–144. 191. Poehlman, E. T., Dvorak, R. V., DeNino, W. F., Brochu, M. and Ades, P. A. (2000) Effects of resistance training and endurance training on insulin sensitivity in nonobese, young women: a controlled randomized trial. J Clin Endocrinol Metab 85, 2463–2468. 192. Brochu, M., Poehlman, E. T., Savage, P., Fragnoli-Munn, K., Ross, S. and Ades, P. A. (2000) Modest effects of exercise training alone on coronary risk factors and body composition in coronary patients. J Cardiopulm Rehabil 20, 180–188. 193. Racette, S. B., Weiss, E. P., Obert, K. A., Kohrt, W. M. and Holloszy, J. O. (2001) Modest lifestyle intervention and glucose tolerance in obese African Americans. Obes Res 9, 348–355. 194. Oldroyd, J. C., Unwin, N. C., White, M., Imrie, K., Mathers, J. C. and Alberti, K. G. (2001) Randomised controlled trial evaluating the effectiveness of behavioural

REFERENCES

195.

196.

197.

198.

199.

200.

201.

202.

203.

204.

205.

206.

207.

399

interventions to modify cardiovascular risk factors in men and women with impaired glucose tolerance: outcomes at 6 months. Diabetes Res Clin Pract 52, 29–43. Wilmore, J. H., Green, J. S., Stanforth, P. R., Gagnon, J., Rankinen, T., Leon, A. S., Rao, D. C., Skinner, J. S. and Bouchard, C. (2001) Relationship of changes in maximal and submaximal aerobic fitness to changes in cardiovascular disease and non-insulindependent diabetes mellitus risk factors with endurance training: the HERITAGE Family Study. Metabolism 50, 1255–1263. Tuomilehto, J., Lindstrom, J., Eriksson, J. G., Valle, T. T., Hamalainen, H., IlanneParikka, P., Keinanen-Kiukaanniemi, S., Laakso, M., Louheranta, A., Rastas, M., Salminen, V. and Uusitupa, M. (2001) Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 344, 1343–1350. Katsuki, A., Sumida, Y., Gabazza, E. C., Murashima, S., Urakawa, H., Morioka, K., Kitagawa, N., Tanaka, T., Araki-Sasaki, R., Hori, Y., Nakatani, K., Yano, Y. and Adachi, Y. (2002) QUICKI is useful for following improvements in insulin sensitivity after therapy in patients with type 2 diabetes mellitus. J Clin Endocrinol Metab 87, 2906–2908. Mensink, M., Feskens, E. J., Saris, W. H., De Bruin, T. W. and Blaak, E. E. (2003) Study on Lifestyle Intervention and Impaired Glucose Tolerance Maastricht (SLIM): preliminary results after one year. Int J Obes Relat Metab Disord 27, 377–384. Uusitupa, M., Lindi, V., Louheranta, A., Salopuro, T., Lindstrom, J. and Tuomilehto, J. (2003) Long-term improvement in insulin sensitivity by changing lifestyles of people with impaired glucose tolerance: 4-year results from the Finnish Diabetes Prevention Study. Diabetes 52, 2532–2538. Potteiger, J. A., Jacobsen, D. J., Donnelly, J. E. and Hill, J. O. (2003) Glucose and insulin responses following 16 months of exercise training in overweight adults: the Midwest Exercise Trial. Metabolism 52, 1175–1181. Watkins, L. L., Sherwood, A., Feinglos, M., Hinderliter, A., Babyak, M., Gullette, E., Waugh, R. and Blumenthal, J. A. (2003) Effects of exercise and weight loss on cardiac risk factors associated with syndrome X. Arch Intern Med 163, 1889–1895. Esposito, K., Pontillo, A., Di Palo, C., Giugliano, G., Masella, M., Marfella, R. and Giugliano, D. (2003) Effect of weight loss and lifestyle changes on vascular inflammatory markers in obese women: a randomized trial. JAMA 289, 1799–1804. Kahle, E. B., O’Dorisio, T. M., Walker, R. B., Eisenman, P. A., Reiser, S., Cataland, S. and Zipf, W. B. (1986) Exercise adaptation responses for gastric inhibitory polypeptide (GIP) and insulin in obese children. Possible extra-pancreatic effects. Diabetes 35, 579–582. Wabitsch, M., Hauner, H., Heinze, E., Muche, R., Bockmann, A., Parthon, W., Mayer, H. and Teller, W. (1994) Body-fat distribution and changes in the atherogenic riskfactor profile in obese adolescent girls during weight reduction. Am J Clin Nutr 60, 54–60. Gutin, B., Cucuzzo, N., Islam, S., Smith, C. and Stachura, M. E. (1996) Physical training, lifestyle education, and coronary risk factors in obese girls. Med Sci Sports Exerc 28, 19–23. Kahle, E. B., Zipf, W. B., Lamb, D. R., Horswill, C. A. and Ward, K. M. (1996) Association between mild, routine exercise and improved insulin dynamics and glucose control in obese adolescents. Int J Sports Med 17, 1–6. Wabitsch, M., Blum, W. F., Muche, R., Heinze, E., Haug, C., Mayer, H. and Teller, W. (1996) Insulin-like growth factors and their binding proteins before and after weight loss and their associations with hormonal and metabolic parameters in obese adolescent girls. Int J Obes Relat Metab Disord 20, 1073–1080.

400

PHYSICAL ACTIVITY AND INSULIN RESISTANCE

208. Hardin, D. S., Hebert, J. D., Bayden, T., Dehart, M. and Mazur, L. (1997) Treatment of childhood syndrome X. Pediatrics 100, E5. 209. Burkhard-Jagodzinska, K., Nazar, K., Ladyga, M., Starczewska-Czapowska, J. and Borkowski, L. (1999) Resting metabolic rate and thermogenic effect of glucose in trained and untrained girls age 11–15 years. Int J Sport Nutr 9, 378–390. 210. Escobar, O., Mizuma, H., Sothern, M. S., Blecker, U., Udall, J. N., Jr., Suskind, R. M., Hilton, C. and Vargas, A. (1999) Hepatic insulin clearance increases after weight loss in obese children and adolescents. Am J Med Sci 317, 282–286. 211. Sudi, K. M., Gallistl, S., Trobinger, M., Payerl, D., Weinhandl, G., Muntean, W., Aigner, R. and Borkenstein, M. H. (2001) The influence of weight loss on fibrinolytic and metabolic parameters in obese children and adolescents. J Pediatr Endocrinol Metab 14, 85–94. 212. Ritenbaugh, C., Teufel-Shone, N. I., Aickin, M. G., Joe, J. R., Poirier, S., Dillingham, D. C., Johnson, D., Henning, S., Cole, S. M. and Cockerham, D. (2003) A lifestyle intervention improves plasma insulin levels among Native American high school youth. Prev Med 36, 309–319.

13 Genetics of the Metabolic Syndrome George Argyropoulos, Steven Smith and Claude Bouchard

13.1

Historical perspective

Multiple metabolic abnormalities, including obesity, impaired glucose tolerance, insulin resistance and hyperinsulinaemia, dyslipidaemia, hypertension, endothelial dysfunctions and other anomalies tend to occur together in the same subjects more frequently than expected by chance alone. Gries and his colleagues (1969) were among the first to recognize that a syndrome, which they referred to as ‘a special metabolic syndrome in certain human beings’, included some of these features.1 Subsequently, the late Roger Williams and his colleagues described a syndrome in which hypertension was associated with mixed lipid abnormalities in Utah families.2 Then Gerald Reaven published a landmark paper emphasizing the magnitude of the metabolic anomalies associated with insulin resistance and hyperinsulinaemia.3 This clustering of cardiovascular disease and diabetes risk factors has been referred to variously as the metabolic syndrome,4 insulin resistance syndrome,5 syndrome X,3 deadly quartet,6 and plurimetabolic syndrome.7 Since the seminal proposal by Reaven,3 the definition of the syndrome has been expanded, and additional factors have been recognized. Thus, microalbuminuria, a high rate of sodium–lithium countertransport, hyperuricaemia, abnormalities in the fibrinolytic system and increased accumulation of abdominal fat, particularly visceral fat, have been added to the clustering, although obesity and hyperinsulinaemia remain the most common clinical conditions of the syndrome. Interestingly, in his 1988 paper,3 Reaven did not recognize obesity Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

402

GENETICS OF THE METABOLIC SYNDROME

as a feature of this syndrome despite the fact that it is by far the most prevalent feature of the cluster. A significant proportion of middle-aged individuals of both sexes are characterized by the presence of some of the manifestations of the metabolic syndrome. For instance, Reaven3 has estimated that about 25 per cent of middle-aged adults were insulin resistant or had hyperinsulinaemia, which suggests that the prevalence of those affected by the metabolic syndrome is quite high. Perhaps even more importantly, the prevalence of overweight and obesity has now reached epidemic proportions. Sixty-four per cent of the United States adult population is now characterized by a BMI in the overweight and obese range, i.e. a BMI greater than or equal to 25.8 The age-adjusted prevalence of obesity, defined as a BMI greater than or equal to 30, is now 30.5 per cent of all adults in the US.8 Using the definition of the metabolic syndrome provided in the Third Report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (ATP III), Ford et al. estimated the prevalence of the syndrome among US adults based on the data of the Third National Health and Nutrition Examination Survey.9 The presence of the metabolic syndrome was defined by three or more abnormalities as specified in ATP III. The prevalence increased from 6.75 per cent among 20–29-year-old adults to about 42 per cent for those 60 years of age and older. The prevalence of the metabolic syndrome was identical in men and women but it was highest among Mexican Americans and African American women. The reasons for the joint occurrence of several abnormalities are only partially understood. Undoubtedly, the development of a metabolic syndrome involves multiple and interactive effects of genes and environmental factors, including physical inactivity and poor diet.10 It is quite clear, however that excessive adiposity and android fat deposition are strongly correlated with the risk factor profile typically seen in the metabolic syndrome.11 For the purpose of the present review, the metabolic syndrome is defined as the cluster of risk factors for cardiovascular disease and type 2 diabetes mellitus (T2DM) resulting from excess adipose tissue mass, abnormal adipose tissue metabolism or ectopic fat deposition. An ectopic fat deposition phenotype is characterized by a number of central features such as elevated hepatic fat deposition, increased skeletal muscle fat content and perhaps abnormal pancreatic fat infiltration. It remains to be seen whether these key features are correlated with abdominal visceral fat levels, a phenotype that has often been proposed as a strong determinant of the metabolic syndrome.3 These disorders in adipose tissue morphology and biology are typically accompanied by insulin resistance and hyperinsulinaemia. Figure 13.1 illustrates the definition of the metabolic syndrome upon which the present review is based. The cardinal features of obesity–abnormal adipose tissue metabolism and/or ectopic fat deposition in the presence of a genetic predisposition and adverse environmental factors such as a sedentary lifestyle–will result over time in a

HISTORICAL PERSPECTIVE

Excess adipose tissue mass Abnormal adipose tissue metabolism Ectopic fat deposition

. , etc

Adip

Insulin resistance

Genes

FFA

okin es, etc.

Environment

403

Hyperinsulinaemia

Endothelium dysfunction

Hypertension

IN MEN Low DHEA Low androgens Low growth hormone

Coagulation anomalies

High cortisol levels or abnormal secretion patterns

Dyslipidemia

IN WOMEN Low DHEA High androgens Low growth hormone

Figure 13.1 Schematic representation of the hierarchical relations among the genetic and non-genetic components of the metabolic syndrome

greater risk of developing insulin resistance and hyperinsulinaemia. Abnormal adipose tissue metabolism, mass or distribution is also known to be often associated with elevated free fatty acid (FFA) levels. Although poorly defined at this time, excess adipose tissue mass, abnormal adipose tissue metabolism and/or ectopic fat deposition could be accompanied by altered adipose tissue hormone and cytokine secretion patterns. The metabolic syndrome as defined herein posits that the above adipose tissue and insulin derangements may result in a cluster of cardiovascular and T2DM risk factors in the presence of the relevant genetic predisposition combined with a high fat and high sugar diet and a physically inactive lifestyle.

404

GENETICS OF THE METABOLIC SYNDROME

13.2 Pathophysiology Several hypotheses have been invoked to explain the relationships between fatness, diabetes and cardiovascular disease as important sequelae of the metabolic syndrome. Herein, we briefly review the prevailing hypotheses concerning the physiopathology of the syndrome and the supporting data. These hypotheses serve to guide us toward candidate pathways/genes for the metabolic syndrome. Given that the metabolic syndrome is most common in individuals with a central pattern of adipose tissue, the earliest hypotheses centred around the intraperitoneal adipose tissue depots, the omental and mesenteric depots, which are collectively known as visceral adipose tissue.12 An increase in total body fatness and a preferential upper body accumulation of fat are independently related to insulin resistance. Obese women with a greater proportion of upper body fat (measured by body circumferences) tend to be more insulin resistant, hyperinsulinaemic, glucose intolerant and dyslipidaemic than obese women with a greater proportion of lower body fat.13 Later, when imaging techniques such as magnetic resonance imaging and computed tomography were used, visceral fat accumulation was found to be specifically associated with the metabolic alterations of obesity, in both men and women.14 – 17 Combined with Randle’s hypothesis,18 – 20 the above observations led to the portal hypothesis, which states that the complications of obesity are attributable to increases in visceral adipose tissue with an associated rise in portal vein plasma FFA concentrations. Bjorntorp noted that abdominal and visceral adipose tissue depots have higher rates of lipid turnover. He suggested that the release of FFA into the portal vein resulted in alterations in hepatic function, specifically insulin clearance, increased hepatic glucose and VLDL production, and low HDL cholesterol.21 How this translates into an increase in skeletal muscle insulin resistance was never specified and remains unclear. In the intervening years since the ‘portal’ hypothesis was proposed, a large body of observational evidence has accumulated in support of the key observation that increased visceral adipose tissue mass is associated with increased risk for developing the metabolic syndrome and the downstream sequelae of diabetes and cardiovascular disease. Given the difficulty in sampling portal vein FFA levels in humans, several investigators have sought to test the portal hypothesis in animal models. For example, elegant studies by Bergman and Ader, using a canine model, support the dominant role of visceral adipose tissue in the development of insulin resistance.20 However, discordant data have been reported.22 For example, Frayn et al. point out that when portal vein FFA levels have been measured, there are no major differences when compared with concentrations in the inferior vena cava. Similarly, several studies have shown that subcutaneous abdominal adipose tissue mass is a strong contributor to the metabolic syndrome.23, 24 As such, the portal hypothesis has not been proven and should be considered in the light of other advances in the field of adipocyte biology and endocrinology.

PATHOPHYSIOLOGY

405

Given the lack of conclusive evidence that portal FFAs are increased and the lack of compelling data linking all of the features of the metabolic syndrome to the portal system, several alternative hypotheses have been suggested.24 They are summarized in Figure 13.2. Adipose tissue is now considered an endocrine organ, secreting a wide variety of hormones and metabolically active substances. A central feature of these endocrine hypotheses is that as the adipose organ increases in size,

Adrenal ↓DHEA

Liver • Steatosis • ↑ VLDL secretion

Adipose tissue (esp. visceral) • ↑ PAI-1, IL-8, TNF-α, resistin, leptin • ↓ Adiponectin • Local activation of cortisol by 11- βHSD • ↓ PPAR-γ

Sex steroids • ↓ Testosterone (men) • ↑ Testosterone (women)

CNS • Altered hypothalamic peptides • Activation of HPA axis • Growth hormone deficiency • Altered sympathetic tone

Pancreas ↑ Insulin secretion Gut Altered gut peptide secretion (Ghrelin, GLP-1, PYY, etc.) Vasculature • Endothelial dysfunction • Hypertension • Pro-coagulant state Muscle • Insulin resistance • ↑ Intramyocellularlipid • ↓ Fat oxidation Intracellular function Activation of energy sensing pathways: • Glucosamine • Long-chain CoA

Figure 13.2 This figure illustrates a selected subset of the hormones, organs, tissues and cellular pathways that are dysregulated in the metabolic syndrome or in obesity. The latter regulatory systems are candidate pathways for the underlying pathophysiology of the metabolic syndrome

406

GENETICS OF THE METABOLIC SYNDROME

there is a change in the circulating concentrations of these endocrine signals. Many adipose tissue hormones have been identified and linked with components of the metabolic syndrome. For example, plasminogen activator inhibitor-1 (PAI-1),25 interleukin-826, 27 and angiotensinogen28 are produced in adipose tissue, providing partial linkage between increases in adipose tissue mass and cardiovascular disease. Several adipose tissue hormones serve as putative links to insulin resistance. For example, resistin,29 leptin30 – 32 and adiponectin33 are secreted proteins that influence peripheral insulin action and fat oxidation. Adiponectin may also impact the development of atheroma through regulation of inflammatory cytokines in the arterial wall.34 The endocrine hypothesis is also consistent with the observations of a dominant role of abdominal obesity in the metabolic syndrome, as many of these hormones are secreted to a greater or lesser degree in abdominal versus gluteal–femoral adipose tissue. It is also possible that the origins of the metabolic syndrome lie not in adipose tissue, but in the dysregulation of insulin action in skeletal muscle, the β-cell and/or the liver. For example, PC-1 is a membrane-bound protein present in skeletal muscle and adipose tissue that directly binds to and inhibits the insulin receptor tyrosine kinase autophosphorylation, a key early step in insulin signalling.35 PC-1 is elevated in obese insulin-resistant individuals and in the insulin resistance and diabetes of pregnancy.36 The relative degree of insulin sensitivity across different tissues is also important. Mice with insulin resistance due to a reduction of the insulin receptor content in skeletal muscle have a completely different phenotype when compared with mice in which the insulin receptor is knocked out in the β-cell.37, 38 Nevertheless, reductions in skeletal muscle insulin sensitivity and glycogen synthase activity are hallmarks of the metabolic syndrome in humans.39 Given the problems with the portal hypothesis and the neglected role of insulin as a lipotrophic hormone,40 several investigators have focused on the storage of lipid in peripheral tissues other than adipose tissue as a cause of insulin resistance. An increase in skeletal muscle intramyocellular lipid content or liver triglyceride content is an excellent correlate of insulin resistance.41 This observation led to the hypothesis that a spillover of lipid, due to insufficient adipose tissue storage,42 leads to ‘ectopic’ fat storage in liver, skeletal muscle and the pancreatic β-cell.43 Consistent with these observations, impairments in lipid oxidation are associated with the metabolic syndrome.44 Blockade of fat oxidation increases intracellular fat and is associated with insulin resistance in vitro,45 possibly through the activation of protein kinase C.46 Given the similarities between Cushing’s disease and the metabolic syndrome, several groups have investigated the role of the hypothalamic–pituitary–adrenal (HPA) axis. Pasquali,47 Bjorntorp48 and, more recently, Rosmond49 have provided suggestive observational evidence for a link between chronic activation of the HPA axis and the metabolic syndrome. Furthermore, recent investigations suggest that local production of cortisol in abdominal adipose tissue (by

GENETIC EPIDEMIOLOGY

407

the cortisone activating enzyme 11βHSD1) contributes to a clinical phenotype similar to Cushing’s disease and the metabolic syndrome.50 This phenotype is recapitulated in transgenic mice over-expressing the 11βHSD1 gene.51 Several investigators have noted that in the animal models of obesity, sympathetic activity is low. This led to the MONA-LISA hypothesis, which states that a low sympathetic outflow is a cause of obesity (and thence the metabolic syndrome).52, 53 Concordant with this model, treatment with specific or nonspecific β-agonists reduces body weight,54, 55 improves components of the metabolic syndrome and increases fat oxidation.56 Although this section of the review focuses on the mechanisms by which alterations in peripheral metabolism might lead to the metabolic syndrome, the CNS must also be considered. As the master regulator of energy homeostasis, the hypothalamus, the brainstem and the spinal cord play a key role in the regulation of peripheral metabolism. The CNS receives inputs from the periphery via nutrient-sensing mechanisms including the vagus nerve, integrates these signals in the hypothalamus and sends efferent signals to the periphery via the SNS, PNS and endocrine effectors (growth hormone secretion, HPA etc.). As such, the diverse CNS signalling systems, i.e. neurotransmitters and neuropeptides, are candidate systems for the control of peripheral metabolisms and therefore the metabolic syndrome.57 Another system that is dysregulated in the metabolic syndrome is the capillary bed and the endothelium. Defects in transcapillary transport of insulin may account for up to one-third of the observed insulin resistance.58, 59 Similarly, endothelial dysfunction, in terms of alterations in responses to vasoactive substances, has been proposed as a cardinal feature of the metabolic syndrome.60 Lastly, it is possible that the etiology of the metabolic syndrome is simply due to the degree of energy excess acting through one of several key signalling pathways. For example, AMP kinase,61 – 66 GFAT/glucosamine67, 68 and longchain CoAs69 have all been described as components of energy-sensing pathways leading to insulin resistance, increased PAI-1 secretion and increased insulin secretion, respectively.

13.3 Genetic epidemiology No study on familial aggregation, genetic heritability or other genetic epidemiology characteristics of the metabolic syndrome, as defined in the present chapter, has been reported thus far. Thus no data are available on the familial clustering of excess adipose mass, abnormal adipose tissue metabolism, ectopic fat deposition, insulin resistance and hyperinsulinaemia together with a panel of risk factors. However, subsets of this larger cluster as well as genetic epidemiology features of individual components have been considered in some reports. They are briefly reviewed here.

408

GENETICS OF THE METABOLIC SYNDROME

Table 13.1 Common manifestations of the metabolic syndrome: trends in genetic epidemiology findings

Total adiposity Abdominal fat Fasting insulin Triglycerides Total cholesterol HDL-cholesterol Dense LDL Systolic BP Diastolic BP Hypertension Androgen levels Cortisol level Type 2 diabetes

Heritability (%)

Major gene

<50 50 20–55 25–45 50–60 30–55 30–50 30 20–30 50 25 50 90

Yes Yes Yes No Yes Yes Yes Mixed results Mixed results Yes NA NA Yes

In Table 13.1, we have summarized the trends emerging from a large number of studies that have dealt with individual components of the metabolic syndrome. The common features of the metabolic syndrome are all individually characterized by familial resemblance that may differ in some cases between sexes.70, 71 Heritability levels ranging from 25 to 40 per cent for total body fatness, the most common feature of the metabolic syndrome, have been reported, although higher and lower heritability values are not uncommon. For abdominal obesity, the familial effect is just as high even when total adiposity is taken into account.70 The heritability estimates for fasting insulin levels vary from 20 to 55 per cent.72 – 74 Other components of the metabolic syndrome such as lipoprotein abnormalities, hypertension and glucose intolerance exhibit individually strong genetic components. For instance, heritability levels in the ranges 25–45 per cent for triglycerides, 50–60 per cent for total cholesterol, 30–55 per cent for HDL-cholesterol, 30 per cent for systolic blood pressure, 20–30 per cent for diastolic blood pressure, 50 per cent for hypertension and 90 per cent for T2DM have been reported.70 In spite of the remaining uncertainties concerning the genetic epidemiology of the individual traits of the metabolic syndrome, the general picture emerging is one in which the genes have pervasive effects. Heritability levels are statistically significant, evidence for major gene effects is commonly reported and the presence of complex genotype–nutrient, genotype–overfeeding, genotype–exercise and genotype–drug interactions is a regular finding.75 Several studies suggest that clustering of the components of the metabolic syndrome may have familial determinants. For instance, data on 2508 adult male twins suggested the presence of a common underlying factor mediating the clustering of hypertension, diabetes and obesity.76 This latent common factor was influenced by both genetic and environmental effects (59 per cent genetic, 41

GENETIC EPIDEMIOLOGY

409

per cent environmental). Furthermore, the concordance rate for the clustering of all three conditions in the same individuals was five times higher in monozygotic compared with dizygotic twin pairs.77 Similar results for dyslipidaemic hypertension in male twins were reported by Selby et al.78 In the San Antonio Family Heart Study, a common set of genes influenced insulin levels together with other insulin-resistance-syndrome-related traits, with one exception: absence of pleiotropy between insulin and blood pressure.79 Results of another twin study, the Swedish Adoption/Twin Study of Aging,80 showed that five principal components computed from the measurements of BMI, insulin levels, triglycerides, HDL-cholesterol and systolic blood pressure were influenced by a single latent genetic factor. In contrast, only three of the components (triglycerides, insulin level and HDL-cholesterol) were associated through a single non-familial environmental factor.80 A common genetic factor influenced BMI and insulin levels. Other components of the syndrome were affected by the same latent genetic factor but to a lesser degree.80 An individual-specific environmental factor had common effects on triglycerides and HDL-cholesterol and, to a lesser degree, on insulin levels. Using the Framingham Heart Study algorithm, the familial aggregation of the Coronary Heart Disease Risk Index was estimated in 113 families of Blacks and 99 families of Whites who participated in the HERITAGE Family Study.81 There was approximately twice as much variance between families than among family members for the index in Blacks or Whites. The maximal heritability for the risk index ranged from 34 to 53 per cent. There were strong indications that the risk of coronary heart disease runs along family lines. In another study, based on principal components analysis of a panel of six risk factors measured in males and females, 8–18 years of age, of the Quebec Family Study and then re-measured 12 years later, it was found that composites of risk factors are moderately stable from childhood to young adulthood.82 It is clearly recognized that a positive family history of T2DM is a risk factor for the development of the disease in other family members related by descent. Thus, in one study conducted with 766 male 54-year-old subjects from G¨oteborg, Sweden, individuals with a positive family history of diabetes had a 2.4 times higher risk of developing the disease than those without such a history.83 More recently, it was shown that the development of T2DM was preceded by depressed values of insulin-dependent glucose uptake and insulinindependent glucose uptake in 155 subjects from 86 families followed for periods ranging from 6 to 25 years.84 In most cases, these predictive low values could be observed more than 10 years before T2DM was diagnosed. Along these lines, the San Antonio Heart Study data also support the notion that prediabetic individuals with hyperinsulinaemia are more numerous in families with a stronger history of T2DM.85 These studies indicate that insulin-mediated glucose disposal and other markers of insulin sensitivity or insulin resistance precede the advent of T2DM and that both cluster in families.

410

GENETICS OF THE METABOLIC SYNDROME

Hypertension is a common manifestation of the metabolic disturbances associated with insulin resistance and hyperinsulinaemia. In the G¨oteborg study of men born in 1913, 185 were hypertensive at 67 years of age while 459 were not.86 A metabolic syndrome defined by the presence of impaired glucose tolerance or T2DM, hyperinsulinaemia and hypertriglyceridaemia was present in six per cent of all hypertensives but in only three per cent of the normotensive group. Williams and collaborators87 have reported that about 12 per cent of hypertensive patients also exhibit high plasma triglycerides and low high density lipoprotein cholesterol levels. These are prominent features of what they have described as familial dyslipidaemic hypertension.2 The association of a parental history of diabetes and hypertension with the metabolic syndrome was evaluated in the Atherosclerosis Risk in Communities (ARIC) Study among middle-aged adults.88 Marked associations between a parental history of some components of the metabolic syndrome and the clustering of these metabolic disorders in the offspring generation were observed. The greatest increase in the occurrence of the metabolic syndrome as defined was related to a parental history of both diabetes and hypertension.88 Hyperinsulinaemia and/or insulin resistance increase the prevalence of dyslipoproteinaemia, as has been shown in several studies.89 – 91 In a study of 682 female twins aged 30–91 years, Selby et al.91 showed that the prevalence of the small, dense LDL particle phenotype rose from about six per cent in women with no common manifestation of the metabolic syndrome to 100 per cent in women who had four features of the syndrome. In the San Antonio Heart Study, 549 non-diabetic persons with a parental history of diabetes were compared with 1167 non-diabetic individuals without such a history.92 Those with a parental history of T2DM had a more atherogenic pattern of risk factors, including higher triglycerides and lower high density lipoprotein cholesterol. However, the differences in blood lipids and lipoproteins between the two groups became non-significant when the data were adjusted for BMI, waist-to-hip circumference ratio (WHR) and fasting insulin levels. In the CARDIA study, parental myocardial infarction was associated with higher fasting insulin levels in their adult children, 18–30 years of age, of Black or White ancestry.72 As revealed by several studies, evidence for insulin resistance, hyperinsulinaemia or parental or familial history of diabetes or impaired glucose tolerance is associated with an augmented probability of exhibiting a more atherogenic risk profile or experiencing myocardial infarction.72, 74, 87, 89 This was further emphasized in the eight-year follow-up of the Nurses Health Study73 and the 12-year follow-up of the Multiple Risk Factor Intervention Trial Study.88 In the Nurses Health Study, the risk for non-fatal or fatal myocardial infarction or stroke was four to seven times greater over an eight-year period in 1483 diabetic patients versus 114 694 non-diabetics, with 20 per cent of the diabetic cases having a parental history of myocardial infarction while the corresponding value was 14 per cent in the non-diabetic women.73

MONOGENIC DISORDERS

411

Cross-trait familial studies between indicators of body fat or fat distribution and other components of the metabolic syndrome have suggested the presence of some degree of genetic pleiotropism. Data of the Quebec Family Study suggested a moderate common familial basis, genetic and/or common environment, in the covariation between body fat and blood pressure93 as well as between body fat and fasting plasma insulin.94 In the same cohort, the covariation between plasma lipids and body fat was associated more strongly with a shared environmental than a genetic hypothesis.95 Moreover, genes and/or familial non-genetic factors with pleiotropic effects were reported to influence, at least to a certain degree, both abdominal visceral fat and plasma fasting insulin levels in the HERITAGE Family Study.96 However, there was no evidence of pleiotropy between measures of resting blood pressure and body composition in another study.97 Thus manifestations of the metabolic syndrome tend to cluster in the same people and there are families at a greater risk than others of exhibiting the syndrome features. Studies with families, siblings and twins generally suggest that genetic factors are involved in the commonly observed familial aggregation of the typical features of the syndrome. However, it is also quite clear that lifestyle characteristics and environmental factors contribute to the clustering and the familial resemblance.72, 91 Support for the latter notion comes from a variety of sources, including studies of discordant monozygotic twins.72 Results of the Kaiser Permanente Women Twins Study showed that, in addition to significant genetic influences on fasting insulin, environmental factors were important determinants of fasting insulin and the insulin resistance syndrome.98 Evidence comes also from the comparison of wives of coronary high risk men with agematched married women of the general population in the Tromso Heart Study.99 The conclusion from that study was that spouses of individuals at increased risk for coronary heart disease are themselves at increased risk, probably as a result of shared lifestyle characteristics, including dietary habits, and a lower level of education with its impact on a variety of health behaviours. In spite of the fact that the genetic determinants of the metabolic syndrome manifestations may not be dramatically high, they are nonetheless sufficient to cause a susceptibility for the syndrome in the presence of adverse lifestyle and environmental characteristics.

13.4 Monogenic disorders The monogenic obesities and lipodystrophies are instructive not only in the pathophysiology of the metabolic syndrome, but also illuminate candidate pathways and genes for the metabolic syndrome. Online Mendelian Inheritance in Man (OMIM) serves to coordinate the classification and diagnostic criteria of the inherited monogenic disorders.100 OMIM can be accessed on-line (http://www.ncbi.nlm.nih.gov/Entrez).

412

GENETICS OF THE METABOLIC SYNDROME

Prader–Willi Of the rare syndromic obesities, Prader–Willi is the most common. Prader–Willi (OMIM No. 176270) is an inherited autosomal dominant disorder with a syndromic constellation of physical and mental abnormalities that include hyperphagia, muscular hypotonia, mental retardation, short stature, small hands and feet and increased cardiovascular disease.101 Angelman syndrome (OMIM No. 105830) is a similar syndrome except that it is maternally inherited and only the neurological abnormality, not obesity, is apparent. Hypogonadism and GH deficiency may contribute to the increased cardiovascular risk.102 Most patients have deletions of the end of paternal chromosome 15 (15q11–q13), although other abnormalities have been reported.103 Recent studies suggest that deletions, mutations and/or translocations in the C/D box small nucleolar RNAs are the critical ‘loss of function’ genes for the development of the syndrome.104 Plasma levels of the gut peptide ghrelin are increased in PWS105 and, given the orexigenic role of ghrelin,106 this may be an important component of the intense hyperphagia seen in these patients.

Other rare monogenic syndromic obesities Many of the rare syndromic obesities develop diabetes or other manifestations of the metabolic syndrome. The reader is referred to OMIM and the excellent chapter by Bray101 for a more detailed description and discussion of the following syndromes: • Alstrom syndrome (mutated gene is ALMS1; Chr 2p13; OMIM No. 203800), • Bardet–Biedl syndrome (Chr 20p12, 16q21, 15q22.3–q23, 11q13, 3p13–p12, 2q31; OMIM No. 209900), • Carpenter syndrome (acrocephalopolysyndactyly type II; OMIM No. 201000) and • Cohen syndrome (Chr 8q22–23; OMIM No. 216550).

Lipodystrophy–lipoatrophy Lipodystrophy can be defined as an absolute or relative decrease in adipose tissue mass that leads to ectopic fat storage in liver, muscle and the pancreatic β-cell. This ectopic fat leads to increased triglycerides, insulin resistance and diabetes, as well as premature coronary artery disease and hypertension. Lipodystrophy can be due to either genetic or acquired causes107 and is reviewed in greater detail elsewhere in this volume. Syndromes described in Table 13.2 are included in this chapter to highlight the fact that too little adipose tissue can cause T2DM just like too much adipose tissue. Furthermore, these monogenic disorders generate genetic hypotheses (candidate genes and cellular pathways), which guide clinical investigation and therapy.

151660

269700

acquired

Congenital generalized lipodystrophy (CGL), also known as Berardinelli–Seip syndrome

HIV-associated lipodystrophy325

OMIM No.

Familial partial lipodystrophy (FPL), also known as K¨obberling–Dunnigan syndrome

Disease

Phenotype

Peripheral fat loss with central fat gain

Multiple alterations in adipose tissue transcription factors (PPAR-γ and SREBP1/ADD) and an increase in mRNA for TNF-α; in addition, the metabolic alterations are highly correlated with the blood levels of the soluble TNF receptor (sTNF-RII)326

(2) Lipid synthesis and/or LPA signalling324

(2) 1-acyl glycerol-3-phosphate O-acetyltransferase 2323 Unknown

Lamin A interacts with SREBP1a and 1c,320 which are important in adipocyte differentiation. Lamin A/C may directly bind SREBP321

Mechanisms

(1) Unknown

317 – 319

(1) Guanine nucleotide-binding protein, gamma3-linked gene, a.k.a Seipin322

Lamin A/C (LMNA)

Genes

Selected lipodystrophic syndromes

FPL manifests during or after puberty and results in the near absence of fat in the extremities. A hallmark of this syndrome is an increase in fat around the neck, face and/or viscera. Most patients are severely insulin resistant, have dyslipidaemia with elevated triglycerides and a low HDL and often develop overt diabetes at an early age CGL manifests at birth as a complete absence of adipose tissue, hepatomegaly and severe non-ketotic insulin-resistant diabetes

Table 13.2

MONOGENIC DISORDERS

413

414

GENETICS OF THE METABOLIC SYNDROME

13.5 Candidate genes In this section we discuss a few select candidate genes that have been associated with the development of the metabolic syndrome. A comprehensive list of candidate genes would be much longer and will continue to increase as our knowledge of the functional roles of many genes becomes elucidated.

Adiponectin Adiponectin (or ACRP30 – adipocyte complement-related protein-30) is a 30 kDa secretory and collagen-like plasma protein that is synthesized in adipose tissue.108 Full length versions of ACRP30 or its proteolytic fragments decrease postprandial rise in plasma FFA and improve post-absorptive insulin-mediated suppression of hepatic glucose output.109 – 111 Its secretion is enhanced by insulin, which makes it a significant candidate factor that may participate in the delicate balancing of energy homeostasis, food intake and energy metabolism.108 Mice lacking adiponectin (knockouts) have reduced fatty acid transport protein-1 (FATP-1) mRNA and insulin-receptor substrate-1 (IRS-1) mediated insulin signalling, resulting in severe diet-induced insulin resistance.112 Adiponectin has a protease-generated globular segment that enhances fatty acid oxidation in muscles, thereby modulating lipid and glucose metabolism.113 Globular and full-length adiponectin in skeletal muscle stimulate the phosphorylation and activation of the 5
-AMPactivated protein kinase (AMPK), thereby directly regulating glucose metabolism and insulin sensitivity in vivo.114 Using monoclonal and polyclonal antibodies, adiponectin plasma levels were found to be significantly lower in obese individuals versus lean controls.115 Adiponectin was negatively correlated in a female Japanese population with serum triglycerides, an atherogenic index, (total cholesterol – HDL-C)/HDL-C, APO B and APO E, and positively correlated with serum HDL-C.116 In another study involving the Pima Indians and other populations, plasma adiponectin concentrations were positively associated with insulin-stimulated glucose disposal and an increase in insulin receptor tyrosine phosphorylation, and negatively associated with percentage body fat.117 Adiponectin has also been shown to suppress lipid accumulation and class A scavenger receptor expression in human monocyte-derived macrophages,118 while low plasma levels of adiponectin in obesity and T2DM are in close association with insulin resistance and hyperinsulinaemia.119 At the genetic level, adiponectin maps on chromosome 3q27 and consists of three exons and two introns. Common single-nucleotide polymorphisms (SNPs) in the gene have been reported to be associated with various phenotypes of T2DM. Specifically, a silent polymorphism in exon 2 at position 94, T94G, and a missense mutation in exon 3, Arg112Cys, were associated with low plasma levels and obesity120 – 123 (Table 13.3). In another study, three missense mutations (Ile164Thr, Arg221Ser, His241Pro) were identified in the globular domain

CANDIDATE GENES

415

Table 13.3 Genes and sequence variants potentially involved in the metabolic syndrome Gene name

Genetic variation

Location

References

ACRP30 ACRP30 ACRP30 ACRP30 ACRP30 ACRP30 Leptin Leptin Leptin Leptin Leptin Resistin Resistin Resistin Resistin Resistin PC-1 PC-1 PPARγ β3-AR 11β-HSD-2 11β-HSD-2 11β-HSD-2 11β-HSD-2 11β-HSD-2 11β-HSD-2 TNF-α TNF-α TNF-α GR GR GR GR GR GR GR MC4R MC4R AgRP AgRP NPY CART CART CART POMC

T94G Arg112Cys Ile164Thr Arg221Ser His241Pro −11 391/−11 377 A19G 25(CAA/CAG) −2548G → A Tetra-nt repeat
G133 −394C → G IVS2 + 181G → A −537A → C −420C → G ATG-triplet repeat Lys121Gln G2897A, G2906C, C2948T Pro12Ala Trp64Arg CA-repeat Ala328Val Pro227Leu Arg213Cys Lys179Arg Arg208His −308G → A Linkage −857C → T Bcl I RFLP Tth 111I RFLP Val571Ala Asn363Ser Arg477His Gly679Ser Glu22Arg/Glu23Lys Del211* Ins732* −38C → T Ala67Thr Leu7Pro −156A → G −929G → C A1475G Arg236Gly

Coding region, silent Coding region Coding region Coding region Coding region 5
haplotype 5
non-coding exon Coding region, silent 5
UTR 3
UTR Coding region 5
UTR Intronic 5
UTR 5
UTR 3
UTR Coding region 3
UTR haplogroup Coding region Coding region 1st intron Coding region Coding region Coding region Coding region Coding region Promoter 6p21.3 locus Promoter 4.5/2.3 kb RFLP 3.8/3.4 kb RFLP Coding region Coding region Coding region Coding region Coding region Coding region Coding region Promoter Coding region Coding region 5
UTR 5
UTR 3
UTR Coding region

120–123 120–123 113 113 113 124 137 138 139, 140 141 142, 143 170 171 172 172 173 179 182 189, 190 200 212, 213 214 215 216 217 217 236–242 243 244, 245 251–255 256 327 257 261 261 262 271 272 281, 284 285 293–298 306 306 307 311

416

GENETICS OF THE METABOLIC SYNDROME

with the Ile164Thr SNP having a higher frequency in diabetic patients than in controls, and carriers of the SNP showed features of metabolic syndrome including hypertension, hyperlipidaemia, diabetes and atherosclerosis.113 Two other SNPs forming a haplotype at positions −11391 and −11377 were also associated with adiponectin levels.124 Taking together the physiological properties and the genetic association studies, adiponectin could be envisioned to play a role in human insulin resistance as well as obesity. This could take place mostly by an indirect action of the gene that may result in increased insulin resistance. Additional functional studies are, however, needed to establish the various reported SNPs as functional operators.

Leptin A search in PubMed on October 2002 for ‘leptin’ yielded 5601 publications. This is an ischaemic number in comparison with the 190 526 publications for ‘insulin’ but there are few other hormones that have caused as much excitement in the scientific community as leptin did when it was discovered in 1994.125 The human OB (leptin or LEP ) gene maps on chromosome 7q31.1126 and consists of one 5
non-coding and two coding exons and two introns altogether spanning over 33 Mb of genomic sequence and encoding a 16 kDa protein.127 Northern blot analyses show that leptin is expressed at high levels in adipose tissue, at much lower levels in placenta and heart, but not expressed in many other tissues.126 Reverse transcriptase and the polymerase chain reaction (RT-PCR) have also identified expression of the two isoforms of its receptor in the umbilical cord and foetal membrane, suggesting a potential autocrine and paracrine role for leptin in these tissues.128 Leptin is not expressed in the 3T3-F442A preadipocyte clonal line but it is expressed robustly in the fully differentiated state, while insulin has been shown to regulate its transcription.129 In ob/ob mice (i.e. mice lacking mature leptin protein due a mutation in the coding region), intraperitoneal injections of either the mouse or human recombinant leptin protein reduced body weight by 30 per cent after two weeks of treatment.130 Leptin has been reported to be involved in signal transduction by the selective activation of its receptor and the signal transducer and activator of transcription-3 (STAT3) in the mouse hypothalamus131 and the human foetal pituitary.132 Signalling pathways utilized by leptin include JAK/STAT, MAPK and SOCS3, while in the hypothalamus the cocaine- and amphetamine-related transcript (CART) may potentially be involved as a downstream mediator of leptin effects, especially with regard to control of GnRH.133, 134 Low plasma levels of leptin concentration have also been proposed to play a role in the development of obesity in Pima Indians, which is a population prone to obesity.135 The literature is mixed with regard to mutations in leptin and obesity or other phenotypes of the metabolic syndrome. Three SNPs, A19G, A144G and G328A (Ala110Met), were not associated with obesity in a Finnish population.127

CANDIDATE GENES

417

Similarly, SNPs in the coding and promoter regions were not associated with eating disorders or extreme early onset obesity.136 In another study, however, obese individuals who were G/G homozygous for the A19G SNP had significantly lower leptin concentrations than allozygotes137 (Table 13.3). In a Japanese population, a silent mutation in codon 25 (CAA/CAG) was linked to morbid obesity,138 while in another population a promoter SNP (−2548G → A) was associated with lower leptin concentrations adjusted for fat mass139 and possibly adipose tissue secretion levels of the hormone140 (Table 13.3). A tetranucleotide repeat (class I versus class II) in the 3
UTR region of the leptin gene was associated with hypertension independent of obesity.141 Individuals with a deletion of a single guanine nucleotide in codon 133 (that leads to the introduction of 14 aberrant amino acids after Gly132 and insertion of a stop codon (
G133)) were severely obese as homozygotes or had high BMI and adiposity as heterozygotes142, 143 (Table 13.3). With regard to the leptin receptor, there have been several SNPs identified but the reports are conflicting regarding associations with phenotypes of the metabolic syndrome.144 – 157 Although a body of compelling physiological data indicates that leptin might play a significant role in the development of the metabolic syndrome, only a handful of mutations/SNPs appear to be functionally associated with the syndrome.

Resistin The hormone resistin is a member of a novel family of cysteine-rich secreted proteins associated with pulmonary inflammation and expressed in the murine small bowel and adipose tissue.158 Resistin was downregulated in the mouse by thiazolidinediones (TZDs), which are agonists for the antidiabetic peroxisome proliferator-activated receptor-gamma (PPAR-γ), and was proposed to link obesity to diabetes.29 The latter findings were contradicted in rodent models of obesity where PPAR-γ agonists augmented expression of resistin.159 Resistin expression in humans has been reported at low levels in the adipose tissue of some but not all humans,160, 161 and its reduced expression has also been proposed as a hallmark of obesity.162 In another study, resistin mRNA was not related to insulin resistance when using RNA isolated from cultured adipocytes163 but was upregulated by acute hyperglycaemia in various mouse adipose depots.164 Using 32 adipose tissues and quantitative PCR, increased amounts of resistin mRNA were found in human abdominal depots compared with thigh depots, suggesting an increased risk for T2DM due to central obesity and higher resistin.165 Resistin was also reported as cysteine-rich adipose tissue specific secretory factor that blocks adipocyte differentiation.166 This finding provides an appealing functional role for resistin by promoting ectopic fat accumulation as a result of its effects on adipose tissue differentiation and impaired lipid storage in adipocytes. Indeed, failure of adipocyte differentiation has been

418

GENETICS OF THE METABOLIC SYNDROME

proposed as a cause of T2DM42 possibly through an ectopic overload of fatty acids and lipotoxicity of non-adipose tissues.167 A role for resistin could therefore be envisioned in the prediabetic syndrome of insulin resistance by virtue of its ability to block adipocyte differentiation. At the genic level, SNPS in non-coding regions of the human resistin gene were either not significantly associated with insulin resistance (G1326C in 3
UTR; −167C → T, 157C → T, 299G → A in introns)168, 169 or associated with an insulin sensitivity index in the case of a promoter SNP (−394C → G)170 (Table 13.3). A genetic variant in intron 2, IVS2 + 181G → A, was significantly involved in a possible interaction between obesity and the association between T2DM and the SNP.171 A study that combined population data from the Quebec Family Study and the Saguenay-Lac-St-Jean region of Quebec found two promoter SNPs (−537A → C and −420C → G) to be associated with increased risk for BMI, but this result was not replicated in a population from Scandinavia.172 A trinucleotide (ATG) repeat at the 3
UTR of the gene was, on the other hand, associated with a decreased risk of insulin resistance.173 It is too early at this point to draw any definitive conclusions regarding the role of resistin in the aetiology of the metabolic syndrome but its proposed physiological role and early genetic studies suggest a link between resistin and the metabolic syndrome. However, its effects may be mediated by intermediate factors such as oxidative stress or population-specific environmental factors.

PC-1 Plasma cell membrane glycoprotein-1 (PC-1) inhibits insulin receptor (IR) tyrosine kinase activity and subsequent cellular signalling, possibly by inhibiting the IR by directly interacting with a specific region in the IR α-subunit.174 IR kinase activity is impaired in muscle, fibroblasts and other tissues of many patients with T2DM but abnormalities in the insulin receptor gene are not the cause of this decreased kinase activity. Skin fibroblasts, however, from certain insulin-resistant patients show increased enzymatic activity by PC-1, while overexpression of PC-1 in transfected cultured cells reduces insulin-stimulated tyrosine kinase activity.175 Using an assay to determine concentrations of circulating PC-1, it was shown that plasma PC-1 of 19 ng/ml or less identified a cluster of insulin-resistance-related alterations with 75 per cent accuracy, indicating that circulating PC-1 is related to insulin sensitivity.176, 177 In addition, women with gestational diabetes mellitus and T2DM have an increased PC-1 content, which could contribute to lower phosphorylation levels of IRS-1. These post-receptor defects in the insulin signalling pathway are greater in these two groups of women than in women with normal pregnancy.178 At the genic level, an SNP (transversion A → C in codon 121) that resulted in an amino-acid substitution, Lys121Gln, was strongly associated with insulin resistance179 (Table 13.3). The same SNP was associated with higher fasting

CANDIDATE GENES

419

Table 13.4 Genome scans and linkages for metabolic syndrome phenotypes Locus or gene 2p21 (D2S1788) 3q27 17p12 APO E CEPT 16p13–pter 3q27 8q23 6q22–q23 ∗

Phenotype(s) Leptin levels, fat mass Several indicators Several indicators Weight/fat factor in IR∗ Lipid factor in IR∗ CHD CHD T2DM, HBP Insulin resistance, obesity

LOD score or p-value LOD = 4.95 LOD = 2.4–3.5 LOD = 5.0 p-value = 0.01 p-value = 0.002 LOD = 3.06 LOD = 2.13 LOD = 2.55 LOD = 3.5

Reference 312 314 314 315 315 316 316 316 183

Insulin resistance.

plasma glucose, higher systolic blood pressure and higher fasting insulin levels in diabetic patients as well as normal individuals and, therefore, it may not be enough to increase susceptibility to T2DM.180 The same SNP (Lys121Gly), however, was not associated with T2DM among Danish Caucasians.181 A haplotype of three SNPs in the 3
UTR of PC-1 (G2897A, G2906C and C2948T) was associated with increased PC-1 protein content and insulin resistance in Caucasians from Sicily182 (Table 13.3). Furthermore, PC-1 maps to a region on chromosome 6q22–q23 that has been strongly linked to several insulin-resistance-related phenotypes in Mexican Americans183 (Table 13.4), which further suggests a potential role for PC-1 in the aetiology of the metabolic syndrome, possibly in interaction with genes that contribute to the aetiology of obesity and/or hypertension, using a rather direct pathway of action to inhibit insulin signalling.

PPARγ Recently, several pedigrees have been described with severe insulin resistance, diabetes, and peripheral fat wasting. The manifestation of this inherited partial lipodystrophy syndrome is quite similar to the metabolic syndrome-X, with the exception that these patients do not respond to the anti-diabetic thiazolidinediones (TZDs). These families were found to have mutations in the PPAR-γ nuclear transcription factor gene at the ligand binding pocket.184 This results in impaired activation of gene transcription by the TZDs. PPAR-γ is a ligandactivated nuclear receptor that regulates adipocyte differentiation and possibly lipid metabolism and insulin sensitivity.185 Predominantly expressed in the intestine and adipose tissue, it triggers adipocyte differentiation and promotes lipid storage.186 It could therefore play a significant role in the development of the metabolic syndrome through its ability to stimulate adipocyte differentiation and prevent lipid spillage to the liver and the muscle (i.e. prevent ectopic lipotoxicity). PPAR-γ and its agonists are subjects of intense investigation as therapeutic agents for insulin resistance and the metabolic syndrome.187 Using a gain-offunction approach, Wang et al. showed that constitutive activation of PPAR-γ

420

GENETICS OF THE METABOLIC SYNDROME

was sufficient to prevent endothelial cells (ECs) from converting into a proinflammatory phenotype, suggesting that genetic modification of the PPAR-γ activity in ECs may be a potential method for therapeutic intervention in inflammatory disorders including the metabolic syndrome.188 A common polymorphism, Pro12Ala, was associated with adiposity and insulin resistance189 and decreased risk of the insulin resistance syndrome190 (Table 13.3). Newer PPAR-γ ligands with a different structural backbone have been shown to bypass CGL mutations in vitro.191 Agarwal and Garg describe a C to T heterozygous mutation at nucleotide 1273 in exon 6 of the PPAR-γ gene with a phenotype of lipodystrophy.192 Although rare, these mutations are instructive in the sense that the metabolic sequelae are almost identical to the ‘garden-variety’ obesity and illustrate the utility of PPAR-γ agonists in the treatment of the metabolic syndrome. PPAR-γ is therefore a strong candidate gene for the metabolic syndrome with effects on adipocyte differentiation, as well as the development of obesity, dyslipidaemia and insulin resistance. Its mode of action may be indirect by means of regulating the transcriptional activation of several adipose tissue-specific genes, thus altering adipose tissue mass and leading to insulin resistance.

β3-adrenoreceptor Five adrenoreceptors are involved in the adrenergic regulation of fat cell functions: beta1- (β1-), β2-, β3-, alpha1- (α1-) and α2-adrenergic receptors (ADRs). cAMP production and cAMP-related cellular responses are mediated through the control of adenyl cyclase activity that is stimulated by β1-, β2-, and β3adrenoreceptors while activation of α1-adrenoreceptors stimulates phosphoinositidase C activity so that a balance among adrenoreceptor subtypes determines the final effects of physiological amines in adipocytes.193 The cloning of the human β3-adrenoreceptor (β3-ADR) produced new excitement in the field of obesity because of its thermogenic, anti-obesity and antidiabetic activities in animal models.194 Structurally, the human β3-adrenoreceptor consists of two coding exons, and the pharmacological properties of the full length cDNA differ somewhat from those of the truncated receptor.195 The human β3-ADR gene is expressed predominantly in infant peripheral brown adipose tissue (which also expresses the thermogenic mitochondrial uncoupling protein UCP1), and in adults it is expressed at low levels in deep fat, such as perirenal and omental, but at much lower levels in subcutaneous fat.196 It is also highly expressed in the gallbladder but to a lower extent in the colon, suggesting a potential role in the control of lipid metabolism and triglyceride storage and mobilization in adipose tissues.196, 197 However, doubts about its therapeutic effects were raised when it was found that β3-ADR is also expressed in human heart, where agonists for this receptor induce a negative inotropic effect, while in blood vessels stimulation of β3-ADR produces a vasodilation.198

CANDIDATE GENES

421

Transcriptionally, β3-ADR is regulated by C/EBP-α through a binding site in an enhancer cis-acting element at position −3306.199 Mutational analysis of the human β3-ADR identified a missense polymorphism that resulted in an aminoacid substitution, Trp64Arg, that was associated with early onset of T2DM in the Pima Indians200 (Table 13.3). The Trp64Arg SNP was also found to contribute significantly to the accumulation of multiple risk factors in male subjects with hyperuricaemia,201 modulate the effects of β-blockers on triglyceride and HDL cholesterol concentrations in an Indo-Mauritian population,202 predict a greater tendency to develop abdominal adiposity and high blood pressure,203 be associated with visceral obesity but lower serum triglyceride204 and confer increased sensitivity to the pressor effect of noradrenaline.205 On the other hand, the Trp64Arg SNP was not associated with obesity phenotypes in the Quebec Family Study and Swedish Obese Subjects cohorts,206 T2DM and features of the insulin resistance syndrome in a Finnish population207 or components of the metabolic syndrome in Chinese subjects.208 Taken together, the data show inconsistent associations of this SNP with the metabolic syndrome. The end result may depend on population-specific characteristics such as ethnic origin, diet, exercise and environmental factors, i.e. gene–gene or gene–environment interactions, that require further investigation.

11β-HSD The 11beta-hydroxysteroid dehydrogenase (11β-HSD) enzymes convert cortisol into inactive cortisone and vice versa. There are two isoforms of 11β-HSD: 11β-HSD-1 (mainly localized in the liver), which acts bidirectionally potentially restoring cortisone into active cortisol, and 11β-HSD-2 (mainly localized in the kidney), which inactivates cortisol unidirectionally.209 The renal 11β-HSD-2 inactivates 11-hydroxysteroids in the kidney, thus protecting the non-selective mineralocorticoid receptor from occupation by glucocorticoids.210 Hepatic transcription of 11β-HSD-1 is regulated by members of the C/EBP family of transcription factors providing a mechanism of cross-talk between C/EBP and the glucocorticoid signalling pathway.211 11β-HSD is highly expressed in all sodium-transporting epithelia, and mutations in the gene cause a rare monogenic juvenile hypertensive syndrome called apparent mineralocorticoid excess (AME).210 Recent studies have shown a prolonged half-life of cortisol and an increased ratio of urinary cortisol to cortisone metabolites in some patients with essential hypertension, similar to the effects of a CA-repeat polymorphism in the first intron, although there was no correlation between this marker and blood pressure.210 The same CA-repeat, however, was associated with a mean arterial pressure difference between the sodium-loaded and the sodium-depleted states212, 213 (Table 13.3). In another study, a proband with AME was homozygous for a mutation (Ala328Val) resulting in a protein devoid of activity,214 while a different individual with AME was homozygous for a Pro227Leu mutation215

422

GENETICS OF THE METABOLIC SYNDROME

(Table 13.3). In other cases, the polymorphism Arg213Cys was strongly associated with AME,216 while two other mutations (Lys179Arg, Arg208His) resulted again in protein devoid of activity.217 Other polymorphisms in 11β-HSD-2 have also been associated with essential hypertension.218 – 220 From these data, we conclude that 11β-HSD-2 plays a significant role in essential hypertension and is therefore an important candidate gene that may contribute to the development of the metabolic syndrome. Its mode of action may be independent of abnormal adipose tissue biology or the insulin signalling pathways, but it may exert its effects directly on the development of hypertension.

TNF-α TNF-α is a cytokine that is produced by macrophages, monocytes, endothelial cells, neutrophils, smooth muscle cells, activated lymphocytes, astrocytes and adipocytes.221 TNF-α is a transmembrane glycoprotein and a cytotoxin with a variety of functions, such as mediating expression of genes for growth factors, cytokines, transcription factors and receptors. TNF-α suppresses adipocytespecific genes and activates expression of preadipocyte genes in 3T3-L1 cells, with NF-κB being an obligatory mediator.222 TNF-α has been termed an adipostat because its adipose tissue expression is, like leptin, more or less proportional to the degree of adiposity. TNF-α is synthesized as a 26 kDa transmembrane protein found on the surface or processed to release the 17 kDa soluble form.223 The ways in which TNF-α may be involved in the aetiology of obesity include its inhibitory effect on lipoprotein lipase (LPL) activity, its effects on glucose homeostasis and its effects on leptin. There are significant positive relationships between TNFα expression, BMI and leptin, and a negative significant correlation between TNF-α and LPL activity, suggesting that TNF-α may be a homeostatic mechanism that may prevent further fat deposition by regulating LPL activity and leptin production.224 Higher plasma levels of TNF-α are also associated with insulin resistance, higher BMI, higher fasting glucose levels and higher LDL-C levels.225 Using confirmatory factor analysis and structural equation modelling, it was shown that obesity, dyslipidaemia and cytokines such as TNF-α were the principal explanatory variables for the various components of the metabolic syndrome.226 Human obesity and T2DM are associated with alterations in the sterol regulatory element binding protein (SREBP)-1 transcription factor that is downregulated at the transcriptional level by TNF-α.227 TNF-α has also been proposed to link obesity with insulin resistance, with serine phosphorylation of the insulin receptor substrate-1 being a prominent mechanism for TNF-α-induced insulin resistance.228 Physiologically, TNF-α could affect several metabolic functions (probably involving the adipose tissue) but its mode of action could be indirect, possibly requiring the development of insulin resistance for its effects to become evident (Figure 13.1).

CANDIDATE GENES

423

In terms of genetic variants in TNF-α, there have been numerous publications, centred mostly on two promoter variants: −308G → A and −238G → A. There are data that do not support an involvement of these two SNPs in the development of the metabolic syndrome229 – 235 but also a body of data that supports an involvement of the two promoter variants in the aetiology of insulin resistance, obesity or T2DM236 – 242 (Table 13.3). A linkage between obesity and a marker (dinucleotide repeat) near the TNF-α locus in the Pima Indians has also been reported.243 Another promoter SNP (−857C → T) was present at higher frequencies in obese patients with diabetes (T/T homozygotes) than in lean subjects244, 245 (Table 13.3). Taking together the physiological functions of TNF-α and the genetic variants, TNF-α may play a role in the development of the metabolic syndrome but the association studies are somewhat inconclusive.

Glucocorticoid receptor The glucocorticoid receptor (GR) is the essential receptor by which glucocorticoids exert their regulatory effects on gene expression. GR is a member of the steroid family of nuclear receptors, and in the absence of its cognate ligand it is transcriptionally inactive.246 There are two isoforms of GR (GR-α and GR-β), which are products of alternative splicing, but only GR-α has functional properties.246 Inside the DNA-binding domain of the receptor molecule, there are two zinc-finger structures, each containing four cysteines that are stabilized by bonds of Zn2+ ions.247 These zinc fingers enable GR homodimers to bind to palindromic DNA sequences and GR response elements found in the promoters of GR-regulated genes.248 The receptor then communicates with the basal transcriptional machinery to either enhance or repress transcription.246 Mutations in GR have often been associated with the metabolic syndrome in association with hyperactivity or abnormal regulation of the HPA axis.249, 250 A restriction fragment length polymorphism (RFLP), Bcl I, has been studied extensively by several groups and appears to be associated with several subphenotypes of the metabolic syndrome. Specifically, in a study regarding the effects of GR in response to overfeeding, 2.3/2.3 kb homozygotes for the GR Bcl I RFLP experience greater increases in body weight, blood pressure, cholesterol levels and visceral fat than 4.5/2.3 kb subjects251 (Table 13.3). In another study involving the Quebec Family Study, the 4.5 kb allele of the GR Bcl I RFLP was associated with a higher amount of abdominal visceral fat (AVF) depot independent of the levels of total body fat.252 The 4.5 kb allele of the GR Bcl I RFLP was also associated with elevated BMI, WHR, abdominal sagittal diameter, leptin and associated borderline with elevated systolic blood pressure.253 In a separate study, the 4.5 kb allele was again associated with higher AVF independently of total body fat, suggesting that the GR Bcl I RFLP or a locus in linkage disequilibrium with it may contribute to the accumulation of AVF.254 The Bcl I RFLP in GR has also been associated with indices of glucose metabolism in obesity,

424

GENETICS OF THE METABOLIC SYNDROME

where 4.5 kb homozygotes had elevated both fasting insulin and an index of insulin resistance.255 Another RFLP in the 5
flanking region of the GR gene (3.8/3.4 kb) was associated (the 3.8 kb homozygotes) with elevated total and evening cortisol levels in a cohort of randomly selected middle-aged men.256 Heterozygotes for another SNP resulting in an amino-acid substitution, Asn363Ser, had higher BMI but normal blood pressure,257 but two other studies did not find an association between the Asn363Ser SNP and altered sensitivity to glucocorticoids or obesity258, 259 (Table 13.3). Yet a recent study reports an association of the Asn363Ser SNP with increased WHR in males for the 363Ser allele but no association with blood pressure, BMI, serum cholesterol, triglycerides, LDL or glucose tolerance status.260 Other mutations in patients with primary cortisol resistance have been reported for GR due to complete lack or reduction of transactivation capacity (Arg477His and Gly679Ser, respectively)261 (Table 13.3). Additional evidence for involvement of GR in the metabolic syndrome comes from a study for a haplogroup of the Glu22Arg/Glu23Lys SNPs where carriers of the less frequent alleles had lower fasting insulin, HOMA-IR index and total LDL cholesterol concentrations.262 Other mutations in the promoter (−22C → A) and 3
UTR exon 9β (A → G in a AUUUA motif) have been reported263, 264 in GR, but they were not associated with phenotypes of the metabolic syndrome. Taking together the functional properties of the GR and the various SNPs and RFLPs that have been associated with the metabolic syndrome, we conclude that DNA sequence variations in the GR gene play a significant role in the aetiology of the syndrome.

Hypothalamic genes The role of the hypothalamus in the metabolic syndrome has been discussed before in terms of cortisol and the glucocorticoid receptors,265, 266 as well as in terms of hypothalamic arousal and its effects on the development of endocrine abnormalities, insulin resistance, central obesity, dyslipidaemia and hypertension.266 The melanocortin receptor 4 (MC4R) is involved in satiation and is antagonized by the agouti protein in the paraventricular nucleus as well as in other tissues.267, 268 Null mutations in MC4R in mice result in hyperphagia, obesity and longitudinal growth while MC3R knockout mice exhibit 50–60 per cent increase in adipose mass and 50 per cent reduction in locomotory activity.269 A missense variant of the porcine MC4R gene was associated with backfat, growth rate and food intake,270 while frameshift mutations in humans were associated with dominantly inherited obesity271 – 275 (Table 13.3). There are in addition four other neuropeptides that have been shown to play significant roles in the regulation of food intake and energy balance: agouti-related protein (AgRP), neuropeptide Y (NPY), cocaine- and amphetamine-regulated transcript (CART) and pro-opiomelanocortin (POMC).

CANDIDATE GENES

425

AgRP binds competitively to the melanocortin receptors and is a potent appetite effector276 and therefore represents a strong case as a candidate gene for obesity and consequently the metabolic syndrome. The murine and human AgRP orthologs stimulate hyperphagia when administered intracerebroventricularly277 – 279 or when overexpressed in transgenic mice.280 The minimal promoter of the gene has been characterized and a functional polymorphism in the promoter (−38C → T) was associated with decreased obesity in Blacks281 (Table 13.3). AgRP plasma levels were elevated in obese individuals282 or increased by 75 per cent after a two-hour fast.283 Further studies in another cohort showed that the T allele of the −38C → T SNP in the promoter of AgRP was linked with reduced visceral adiposity, percentage body fat and T2DM.281, 284 A structural polymorphism (Ala67Thr) has been strongly associated with resistance to late-onset obesity285 (Table 13.3). The same SNP was also reported to be associated with anorexia nervosa.286 This SNP represents a rare example for a common polymorphism that was found in Caucasians only and was associated with resistance to obesity in the parental population but not in the offspring.285 This parallels the syndromic characteristics of the metabolic syndrome, which is also a late onset disease, with components of its complex phenotype expressing gradually in the range of 35–55 years of age. NPY is also a strong orexigenic gene287, 288 regulated by leptin and other peripheral signals.289 There have been numerous studies linking NPY with feeding behaviour in several mammalian systems. NPY knockout mice have an attenuated obese phenotype,289 while its receptors have important physiological functions.290 – 292 A polymorphism in the signal peptide (Leu7Pro) resulted in altered intracellular processing and release of NPY293 (Table 13.3). The same SNP has been associated with phenotypes of the metabolic syndrome including nephropathy in T2DM,294 enhanced carotid atherosclerosis in elderly patients with T2DM,294 carotid atherosclerosis, blood pressure, serum lipids in Finnish men295 and serum lipids in patients with coronary heart disease,296 as well as alcohol consumption and alcohol dependence.297, 298 CART is a hypothalamic anorectic peptide that is upregulated by leptin299, 300 and is also a candidate gene for the metabolic syndrome by virtue of its ability to regulate food intake. CART blocks the feeding response induced by NPY and its C-terminus is the active part of the protein.301 It has been shown to modulate the voltage-gated Ca2+ signalling in the hippocampal neurons,302 and expression studies in the brain further suggest a role for CART in the regulation of energy homeostasis.303, 304 CART is a drug target for obesity therapy, and polymorphisms in its promoter region have been associated with obesity in humans.305, 306 Specifically, SNP −156A → G in the promoter of the gene was associated with high BMI and was found at higher frequencies in obese individuals, while a neighbouring SNP (−929G → C) was in linkage disequilibrium with the −156A → G SNP306 (Table 13.3). A mutation in the 3
UTR of the gene, A1475G, was significantly associated with WHR in heterozygous males,

426

GENETICS OF THE METABOLIC SYNDROME

thus suggesting a role by CART in fat distribution and variables related to the metabolic syndrome307 (Table 13.3). POMC is the precursor of α-MSH, a strong anorectic peptide activated by leptin308 and therefore a candidate gene for the metabolic syndrome. Posttranslational processing of POMC results in five distinct proteins with different physiological functions: adrenocorticotropin, β-lipotropin, α-MSH, β-MSH and β-endorphin. Mice lacking POMC have obesity and defective adrenal development and, when treated with α-MSH agonists, they lose weight.309, 310 A missense mutation disrupting a dibasic prohormone processing site in hPOMC was associated with early onset obesity311 (Table 13.3). A role for several hypothalamic neuropeptides can therefore be envisioned in the development of the metabolic syndrome either as a result of elevated or diminished arousal of the hypothalamus or due to genetic alterations that may affect the expression levels or the activities of the protein products of these genes. It must be noted that these neuropeptides are also expressed in peripheral tissues and, therefore, their mode of action is quite complex. Hence, there are several routes by which these genes could influence the development of the metabolic syndrome (Figure 13.1).

13.6 Genomic scans There is abundant literature on linkage analyses and genome scans for the main subphenotypes of the metabolic syndrome (Figure 13.1) considered individually. In contrast, very few scans have been performed using a single integrated metabolic syndrome phenotype. This is probably due to the complexity of the syndrome and the lack of comprehensive physiological and clinical data in family cohorts that would allow an adequate definition of the syndrome phenotype. Yet there are reports providing suggestive linkages that may apply to the metabolic syndrome as a whole. Comuzzie and colleagues have reported a significant LOD score on 2p21 (LOD = 4.95) for microsatellite D2S1788 that may determine serum leptin levels and fat mass in Mexican-Americans312 (Table 13.4). Indeed, this locus accounted for 47 per cent of the variation in serum leptin levels and contains several potential candidate genes including the glucokinase regulatory protein and POMC. However, it was not significantly linked to hypertension in African-Americans.313 In a study that directly scanned the genome for QTLs for the metabolic syndrome, Kissebah and colleagues reported two QTLs with significant LOD scores.314 Specifically, using a 10 cM map in 2209 individuals distributed over 507 nuclear Caucasian families, a QTL on 3q27 was strongly linked with six traits characteristic of the metabolic syndrome, and this QTL was in possible epistatic interaction with a second QTL on 17p12314 (Table 13.4). Another study used sib-pair linkage analysis with women twins in an effort to identify lipoprotein candidate genes for multivariate factors of the insulin

REFERENCES

427

resistance syndrome. Specifically, quantitative sib-pair analysis based on factor scores with markers for nine candidate genes was carried out using 126 dizygotic women twins.315 There was suggestive evidence for linkage for the weight/fat factor and the APO E gene (0.01) and stronger evidence for linkage with the lipid factor and the cholesterol ester transfer protein (p − value = 0.002)315 (Table 13.4). A genome-wide scan in Indo-Mauritians for coronary heart disease (CHD) identified a susceptibility locus on chromosome 16p13–pter and was able to replicate the previously reported linkage314 with the metabolic syndrome on 3q27316 (Table 13.4). A suggestive linkage was also identified for T2DM and high blood pressure on 8q23 (LOD = 2.55).316 A significant LOD score (LOD = 3.5) was identified on chromosome 6q22–q23 (D6S403, D6S264) for fasting glucose, specific insulin values and other insulin resistance-related phenotypes with strong pleiotropic effects with obesity-related phenotypes in nondiabetic Mexican-Americans183 (Table 13.4). It would therefore appear that there are suggestive linkages and candidate QTLs for the metabolic syndrome, but no single locus stands out as of yet. Additional linkage studies are required to determine whether there are any compelling QTLs for the metabolic syndrome. In this regard, it may be useful to revisit previous genomic scan studies and re-analyse data from cohorts in which linkages with single phenotypes were reported, with the aim of testing more comprehensive metabolic syndrome phenotypes.

13.7

Conclusions

The metabolic syndrome in humans is a multi-component disease whose cardinal features include obesity, abnormal adipose tissue metabolism, ectopic fat deposition, insulin resistance, hyperinsulinaemia, dyslipidaemia and hypertension. The genetic causes for each of the components of the syndrome are under intense investigation. A number of genes have emerged as possible regulators but no genetic master switch has been identified yet for the syndrome as a whole. At this point the genetic data are not particularly robust, and intense work lies ahead in order to define the genetic aetiology of the disease. The present review of epidemiological, Mendelian and syndromic data; candidate genes and polymorphisms; and linkage studies highlights several features and genetic hypotheses that deserve further research. The field would benefit greatly from concertation among informative cohorts already assembled and from new collections of longitudinal data on large populations over an extended period of time. Innovative genomic scan studies are also needed to identify key loci and QTLs for the syndrome defined as a single integrated phenotype. Until then, the candidate gene approach appears to be the best way to identify functional SNPs that may contribute to the development of the metabolic syndrome.

References 1. Jahnke, K., Daweke, H., Liebermeister, H., Thamer, G., Preiss, H. and Gries, F. A. (1969) Hormonal and metabolic aspects of obesity in humans. In: Milner, R. D. G., ed.

428

2.

3. 4. 5.

6. 7. 8. 9.

10. 11.

12. 13. 14.

15.

16.

17. 18.

19. 20.

GENETICS OF THE METABOLIC SYNDROME

Proceedings of the Sixth Congress of the International Diabetes Federation. Amsterdam: Excerpta Medica Foundation, 533–539. Williams, R. R., Hunt, S. C., Hopkins, P. N., Stults, B. M., Wu, L. L., Hasstedt, S. J., Barlow, G. K., Stephenson, S. H., Lalouel, J. M. and Kuida, H. (1988) Familial dyslipidemic hypertension. Evidence from 58 Utah families for a syndrome present in approximately 12% of patients with essential hypertension. JAMA 259, 3579–3586. Reaven, G. M. (1988) Banting Lecture 1988. Role of insulin resistance in human disease. Diabetes 37, 1595–1607. Bjorntorp, P. (1992) Abdominal obesity and the metabolic syndrome. Ann Med 24, 465–468. DeFronzo, R. A. and Ferrannini, E. (1991) Insulin resistance. A multifaceted syndrome responsible for NIDDM, obesity, hypertension, dyslipidemia, and atherosclerotic cardiovascular disease. Diabetes Care 14, 173–194. Kaplan, N. M. (1989) The deadly quartet. Upper-body obesity, glucose intolerance, hypertriglyceridemia, and hypertension. Arch Intern Med 149, 1514–1520. Crepaldi, G., Tiengo, A. and Manzato, E. (1993) Diabetes, Obesity and Hyperlipidemias: V: the Plurimetabolic Syndrome. Amsterdam: Excerpta Medica. Flegal, K. M., Carroll, M. D., Ogden, C. L. and Johnson, C. L. (2002) Prevalence and trends in obesity among US adults, 1999–2000. JAMA 288, 1723–1727. Ford, E. S., Giles, W. H. and Dietz, W. H. (2002) Prevalence of the metabolic syndrome among US adults: findings from the third National Health and Nutrition Examination Survey. JAMA 287, 356–359. Bouchard, C. (1995) Genetics and the metabolic syndrome. Int J Obes Relat Metab Disord 19 (Suppl. 1), S52–59. Han, T. S., Williams, K., Sattar, N., Hunt, K. J., Lean, M. E. and Haffner, S. M. (2002) Analysis of obesity and hyperinsulinemia in the development of metabolic syndrome: San Antonio Heart Study. Obes Res 10, 923–931. Smith, S. R. (1999) Regional fat distribution. In: Ryan, D. H., ed. Nutrition Genetic and Obesity. Baton Rouge, LA: LSU Press, 433–458. Kissebah, A. H. and Peiris, A. N. (1989) Biology of regional body fat distribution: relationship to non-insulin-dependent diabetes mellitus. Diabetes Metab Rev 5, 83–109. Despres, J. P., Lemieux, S., Lamarche, B., Prud’homme, D., Moorjani, S., Brun, L. D., Gagne, C. and Lupien, P. J. (1995) The insulin resistance–dyslipidemic syndrome: contribution of visceral obesity and therapeutic implications. Int J Obes Relat Metab Disord 19 (Suppl. 1), S76–86. Banerji, M. A., Chaiken, R. L., Gordon, D., Kral, J. G. and Lebovitz, H. E. (1995) Does intra-abdominal adipose tissue in black men determine whether NIDDM is insulinresistant or insulin-sensitive? Diabetes 44, 141–146. Albu, J. B., Murphy, L., Frager, D. H., Johnson, J. A. and Pi-Sunyer, F. X. (1997) Visceral fat and race-dependent health risks in obese nondiabetic premenopausal women. Diabetes 46, 456–462. Albu, J. B., Kovera, A. J. and Johnson, J. A. (2000) Fat distribution and health in obesity. Ann NY Acad Sci 904, 491–501. Randle, P. J., Garland, P. B., Hales, C. N. and Newsholme, E. A. (1963) The glucose fatty acid cycle: its role in insulin sensitivity and metabolic disturbances of diabetes mellitus. Lancet i, 7285–7289. Kelley, D. E. and Mandarino, L. J. (2000) Fuel selection in human skeletal muscle in insulin resistance: a reexamination. Diabetes 49, 677–683. Bergman, R. N. and Ader, M. (2000) Free fatty acids and pathogenesis of type 2 diabetes mellitus. Trends Endocrinol Metab 11, 351–356.

REFERENCES

429

21. Bjorntorp, P. (1990) ‘Portal’ adipose tissue as a generator of risk factors for cardiovascular disease and diabetes. Arteriosclerosis 10, 493–496. 22. Frayn, K. N., Samra, J. S. and Summers, L. K. (1997) Visceral fat in relation to health: is it a major culprit or simply an innocent bystander? [letter]. Int J Obes Relat Metab Disord 21, 1191–1192. 23. Kelley, D. E., Thaete, F. L., Troost, F., Huwe, T. and Goodpaster, B. H. (2000) Subdivisions of subcutaneous abdominal adipose tissue and insulin resistance. Am J Physiol 278, E941. 24. Smith, S. R., Lovejoy, J. C., Greenway, F., Ryan, D., deJonge, L., de la Bretonne, J., Volafova, J. and Bray, G. A. (2001) Contributions of total body fat, abdominal subcutaneous adipose tissue compartments, and visceral adipose tissue to the metabolic complications of obesity. Metabolism 50, 425–435. 25. Lundgren, C. H., Brown, S. L., Nordt, T. K., Sobel, B. E. and Fujii, S. (1996) Elaboration of type-1 plasminogen activator inhibitor from adipocytes. A potential pathogenetic link between obesity and cardiovascular disease. Circulation 93, 106–110. 26. Bruun, J. M., Pedersen, S. B. and Richelsen, B. (2000) Interleukin-8 production in human adipose tissue. inhibitory effects of anti-diabetic compounds, the thiazolidinedione ciglitazone and the biguanide metformin. Horm Metab Res 32, 537–541. 27. Straczkowski, M., Dzienis-Straczkowska, S., Stepien, A., Kowalska, I., Szelachowska, M. and Kinalska, I. (2002) Plasma interleukin-8 concentrations are increased in obese subjects and related to fat mass and tumor necrosis factor-alpha system. J Clin Endocrinol Metab 87, 4602–4606. 28. Engeli, S., Negrel, R. and Sharma, A. M. (2000) Physiology and pathophysiology of the adipose tissue renin–angiotensin system. Hypertension 35, 1270–1277. 29. Steppan, C. M., Bailey, S. T., Bhat, S., Brown, E. J., Banerjee, R. R., Wright, C. M., Patel, H. R., Ahima, R. S. and Lazar, M. A. (2001) The hormone resistin links obesity to diabetes. Nature 409, 307–312. 30. Harris, R. B. (1998) Acute and chronic effects of leptin on glucose utilization in lean mice. Biochem Biophys Res Commun 245, 502–509. 31. Muoio, D. M., Dohm, G. L., Fiedorek, F. T., Jr., Tapscott, E. B., Coleman, R. A. and Dohn, G. L. (1997) Leptin directly alters lipid partitioning in skeletal muscle [published erratum appears in Diabetes 1997 46 (10), 1663]. Diabetes 46, 1360–1363. 32. Muoio, D. M., Dohm, G. L., Tapscott, E. B. and Coleman, R. A. (1999) Leptin opposes insulin’s effects on fatty acid partitioning in muscles isolated from obese ob/ob mice. Am J Physiol 276, E913–921. 33. Yamauchi, T., Kamon, J., Waki, H., Terauchi, Y., Kubota, N., Hara, K., Mori, Y., Ide, T., Murakami, K., Tsuboyama-Kasaoka, N., Ezaki, O., Akanuma, Y., Gavrilova, O., Vinson, C., Reitman, M. L., Kagechika, H., Shudo, K., Yoda, M., Nakano, Y., Tobe, K., Nagai, R., Kimura, S., Tomita, M., Froguel, P. and Kadowaki, T. (2001) The fat-derived hormone adiponectin reverses insulin resistance associated with both lipoatrophy and obesity. Nat Med 7, 941–946. 34. Ouchi, N., Kihara, S., Arita, Y., Maeda, K., Kuriyama, H., Okamoto, Y., Hotta, K., Nishida, M., Takahashi, M., Nakamura, T., Yamashita, S., Funahashi, T. and Matsuzawa, Y. (1999) Novel modulator for endothelial adhesion molecules: adipocytederived plasma protein adiponectin. Circulation 100, 2473–2476. 35. Goldfine, I. D., Maddux, B. A., Youngren, J. F., Frittitta, L., Trischitta, V. and Dohm, G. L. (1998) Membrane glycoprotein PC-1 and insulin resistance. Mol Cell Biochem 182, 177–184. 36. Shao, J., Catalano, P. M., Yamashita, H., Ruyter, I., Smith, S., Youngren, J. and Friedman, J. E. (2000) Decreased insulin receptor tyrosine kinase activity and plasma

430

37.

38.

39.

40. 41.

42. 43.

44.

45.

46.

47.

48.

49.

50. 51.

52.

GENETICS OF THE METABOLIC SYNDROME

cell membrane glycoprotein-1 overexpression in skeletal muscle from obese women with gestational diabetes mellitus (GDM): evidence for increased serine/threonine phosphorylation in pregnancy and GDM. Diabetes 49, 603–610. Kahn, C. R., Bruning, J. C., Michael, M. D. and Kulkarni, R. N. (2000) Knockout mice challenge our concepts of glucose homeostasis and the pathogenesis of diabetes mellitus. J Pediatr Endocrinol Metab 13 (Suppl. 6), 1377–1384. Mauvais-Jarvis, F., Kulkarni, R. N. and Kahn, C. R. (2002) Knockout models are useful tools to dissect the pathophysiology and genetics of insulin resistance. Clin Endocrinol (Oxf) 57, 1–9. Bogardus, C., Lillioja, S., Stone, K. and Mott, D. (1984) Correlation between muscle glycogen synthase activity and in vivo insulin action in man. J Clin Invest 73, 1185–1190. McGarry, J. D. (1992) What if Minkowski had been ageusic? An alternative angle on diabetes. Science 258, 766–770. Sinha, R., Dufour, S., Petersen, K. F., LeBon, V., Enoksson, S., Ma, Y. Z., Savoye, M., Rothman, D. L., Shulman, G. I. and Caprio, S. (2002) Assessment of skeletal muscle triglyceride content by (1)H nuclear magnetic resonance spectroscopy in lean and obese adolescents: relationships to insulin sensitivity, total body fat, and central adiposity. Diabetes 51, 1022–1027. Danforth, E., Jr. (2000) Failure of adipocyte differentiation causes type II diabetes mellitus? Nat Genet 26, 13. Smith, S. R. and Ravussin, E. (2002) Increased fat intake, impaired fat oxidation, and failure of fat cell proliferation result in ectopic fat storage, insulin resistance, and type 2 diabetes mellitus. Ann NY Acad Sci 967, 363–378. Colberg, S. R., Simoneau, J. A., Thaete, F. L. and Kelley, D. E. (1995) Skeletal muscle utilization of free fatty acids in women with visceral obesity. J Clin Invest 95, 1846–1853. Dobbins, R. L., Szczepaniak, L. S., Bentley, B., Esser, V., Myhill, J. and McGarry, J. D. (2001) Prolonged inhibition of muscle carnitine palmitoyltransferase-1 promotes intramyocellular lipid accumulation and insulin resistance in rats. Diabetes 50, 123–130. Kim, Y. B., Shulman, G. I. and Kahn, B. B. (2002) Fatty acid infusion selectively impairs insulin action on Akt1 and PKC lambda/zeta but not on glycogen synthase kinase-3. J Biol Chem 277, 32 915–32 922. Pasquali, R., Cantobelli, S., Casimirri, F., Capelli, M., Bortoluzzi, L., Flamia, R., Labate, A. M. and Barbara, L. (1993) The hypothalamic–pituitary–adrenal axis in obese women with different patterns of body fat distribution. J Clin Endocrinol Metab 77, 341–346. Marin, P., Darin, N., Amemiya, T., Andersson, B., Jern, S. and Bjorntorp, P. (1992) Cortisol secretion in relation to body fat distribution in obese premenopausal women. Metabolism 41, 882–886. Rosmond, R., Holm, G. and Bjorntorp, P. (2000) Food-induced cortisol secretion in relation to anthropometric, metabolic and haemodynamic variables in men. Int J Obes Relat Metab Disord 24, 416–422. Bujalska, I. J., Kumar, S. and Stewart, P. M. (1997) Does central obesity reflect ‘Cushing’s disease of the omentum’? Lancet 349, 1210–1213. Masuzaki, H., Paterson, J., Shinyama, H., Morton, N. M., Mullins, J. J., Seckl, J. R. and Flier, J. S. (2001) A transgenic model of visceral obesity and the metabolic syndrome. Science 294, 2166–2170. Tataranni, P. A., Young, J. B., Bogardus, C. and Ravussin, E. (1997) A low sympathoadrenal activity is associated with body weight gain and development of central adiposity in Pima Indian men. Obes Res 5, 341–347.

REFERENCES

431

53. Bray, G. A. (1991) Obesity, a disorder of nutrient partitioning: the MONA LISA hypothesis. J Nutr 121, 1146–1162. 54. Astrup, A., Buemann, B., Christensen, N. J., Toubro, S., Thorbek, G., Victor, O. J. and Quaade, F. (1992) The effect of ephedrine/caffeine mixture on energy expenditure and body composition in obese women. Metabolism 41, 686–688. 55. Toubro, S., Astrup, A. V., Breum, L. and Quaade, F. (1993) Safety and efficacy of long-term treatment with ephedrine, caffeine and an ephedrine/caffeine mixture. Int J Obes Relat Metab Disord 17 (Suppl. 1), S69–72. 56. Weyer, C., Tataranni, P., Snitker, S., Danforth, E. and Ravussin, E. (1998) Increase in insulin action and fat oxidation after treatment with CL 316,243, a highly selective beta3-adrenoceptor agonist in humans. Diabetes 47, 1555–1561. 57. Berthoud, H. R. (2002) Multiple neural systems controlling food intake and body weight. Neurosci Biobehav Rev 26, 393–428. 58. Miles, P. D. G., Li, S., Hart, M., Romeo, O., Cheng, J., Cohen, A., Raafat, K., Moossa, A. R. and Olefsky, J. M. (1998) Mechanisms of insulin resistance in experimental hyperinsulinemic dogs. J Clin Invest 101, 202–211. 59. Hamilton-Wessler, M., Ader, M., Dea, M. K., Moore, D., Loftager, M., Markussen, J. and Bergman, R. N. (2002) Mode of transcapillary transport of insulin and insulin analog NN304 in dog hindlimb: evidence for passive diffusion. Diabetes 51, 574–582. 60. Pinkney, J. H., Stehouwer, C. D., Coppack, S. W. and Yudkin, J. S. (1997) Endothelial dysfunction: cause of the insulin resistance syndrome. Diabetes 46 (Suppl. 2), S9–13. 61. Minokoshi, Y., Kim, Y. B., Peroni, O. D., Fryer, L. G., Muller, C., Carling, D. and Kahn, B. B. (2002) Leptin stimulates fatty-acid oxidation by activating AMP-activated protein kinase. Nature 415, 339–343. 62. Fryer, L. G., Parbu-Patel, A. and Carling, D. (2002) The anti-diabetic drugs rosiglitazone and metformin stimulate AMP-activated protein kinase through distinct signaling pathways. J Biol Chem 277, 25 226–25 232. 63. Aschenbach, W. G., Hirshman, M. F., Fujii, N., Sakamoto, K., Howlett, K. F. and Goodyear, L. J. (2002) Effect of AICAR treatment on glycogen metabolism in skeletal muscle. Diabetes 51, 567–573. 64. Hardie, D. G. and Carling, D. (1997) The AMP-activated protein kinase – fuel gauge of the mammalian cell? Eur J Biochem 246, 259–273. 65. Muoio, D. M., Seefeld, K., Witters, L. A. and Coleman, R. A. (1999) AMP-activated kinase reciprocally regulates triacylglycerol synthesis and fatty acid oxidation in liver and muscle: evidence that sn-glycerol-3-phosphate acyltransferase is a novel target. Biochem J 338, 783–791. 66. Hutber, C. A., Hardie, D. G. and Winder, W. W. (1997) Electrical stimulation inactivates muscle acetyl-CoA carboxylase and increases AMP-activated protein kinase. Am J Physiol 272, E262–266. 67. Du, X. L., Edelstein, D., Rossetti, L., Fantus, I. G., Goldberg, H., Ziyadeh, F., Wu, J. and Brownlee, M. (2000) Hyperglycemia-induced mitochondrial superoxide overproduction activates the hexosamine pathway and induces plasminogen activator inhibitor-1 expression by increasing Sp1 glycosylation. Proc Natl Acad Sci USA 97, 12 222–12 226. 68. Hawkins, M., Barzilai, N., Liu, R., Hu, M., Chen, W. and Rossetti, L. (1997) Role of the glucosamine pathway in fat-induced insulin resistance. J Clin Invest 99, 2173–2182. 69. Prentki, M., Tornheim, K. and Corkey, B. E. (1997) Signal transduction mechanisms in nutrient-induced insulin secretion. Diabetologia 40 (Suppl. 2), S32–41. 70. Bouchard, C. and Perusse, L. (1994) Genetics of causes and manifestations of the metabolic syndrome. In: Crepaldi, G., ed. 6th European Symposium on Metabolism: the Plurimetabolic Syndrome. Amsterdam: Elsevier, 67–74.

432

GENETICS OF THE METABOLIC SYNDROME

71. Nelson, T. L., Vogler, G. P., Pedersen, N. L., Hong, Y. and Miles, T. P. (2000) Genetic and environmental influences on body fat distribution, fasting insulin levels and CVD: are the influences shared? Twin Res 3, 43–50. 72. Burke, G. L., Savage, P. J., Sprafka, J. M., Selby, J. V., Jacobs, D. R., Jr., Perkins, L. L., Roseman, J. M., Hughes, G. H. and Fabsitz, R. R. (1991) Relation of risk factor levels in young adulthood to parental history of disease. The CARDIA study. Circulation 84, 1176–1187. 73. Manson, J. E., Colditz, G. A., Stampfer, M. J., Willett, W. C., Krolewski, A. S., Rosner, B., Arky, R. A., Speizer, F. E. and Hennekens, C. H. (1991) A prospective study of maturity-onset diabetes mellitus and risk of coronary heart disease and stroke in women. Arch Intern Med 151, 1141–1147. 74. Sarlund, H., Pyorala, K., Penttila, I. and Laakso, M. (1992) Early abnormalities in coronary heart disease risk factors in relatives of subjects with non-insulin-dependent diabetes. Arterioscler Thromb 12, 657–663. 75. Ukkola, O. and Bouchard, C. (2001) Clustering of metabolic abnormalities in obese individuals: the role of genetic factors. Ann Med 33, 79–90. 76. Carmelli, D., Cardon, L. R. and Fabsitz, R. (1994) Clustering of hypertension, diabetes, and obesity in adult male twins: same genes or same environments? Am J Hum Genet 55, 566–573. 77. Liese, A. D., Mayer-Davis, E. J., Tyroler, H. A., Davis, C. E., Keil, U., Schmidt, M. I., Brancati, F. L. and Heiss, G. (1997) Familial components of the multiple metabolic syndrome: the ARIC study. Diabetologia 40, 963–970. 78. Selby, J. V., Newman, B., Quiroga, J., Christian, J. C., Austin, M. A. and Fabsitz, R. R. (1991) Concordance for dyslipidemic hypertension in male twins. JAMA 265, 2079–2084. 79. Mitchell, B. D., Kammerer, C. M., Mahaney, M. C., Blangero, J., Comuzzie, A. G., Atwood, L. D., Haffner, S. M., Stern, M. P. and MacCluer, J. W. (1996) Genetic analysis of the IRS. Pleiotropic effects of genes influencing insulin levels on lipoprotein and obesity measures. Arterioscler Thromb Vasc Biol 16, 281–288. 80. Hong, Y., Pedersen, N. L., Brismar, K. and de Faire, U. (1997) Genetic and environmental architecture of the features of the insulin-resistance syndrome. Am J Hum Genet 60, 143–152. 81. Katzmarzyk, P. T., Perusse, L., Rice, T., Gagnon, J., Skinner, J. S., Wilmore, J. H., Leon, A. S., Rao, D. C. and Bouchard, C. (2000) Familial resemblance for coronary heart disease risk: the HERITAGE Family Study. Ethn Dis 10, 138–147. 82. Katzmarzyk, P. T., Perusse, L., Malina, R. M., Bergeron, J., Despres, J. P. and Bouchard, C. (2001) Stability of indicators of the metabolic syndrome from childhood and adolescence to young adulthood: the Quebec Family Study. J Clin Epidemiol 54, 190–195. 83. Ohlson, L. O., Larsson, B., Bjorntorp, P., Eriksson, H., Svardsudd, K., Welin, L., Tibblin, G. and Wilhelmsen, L. (1988) Risk factors for type 2 (non-insulin-dependent) diabetes mellitus. Thirteen and one-half years of follow-up of the participants in a study of Swedish men born in 1913. Diabetologia 31, 798–805. 84. Martin, B. C., Warram, J. H., Krolewski, A. S., Bergman, R. N., Soeldner, J. S. and Kahn, C. R. (1992) Role of glucose and insulin resistance in development of type 2 diabetes mellitus: results of a 25-year follow-up study. Lancet 340, 925–929. 85. Haffner, S. M., Stern, M. P., Hazuda, H. P., Mitchell, B. D. and Patterson, J. K. (1988) Increased insulin concentrations in nondiabetic offspring of diabetic parents. N Engl J Med 319, 1297–1301.

REFERENCES

433

86. Eriksson, H., Welin, L., Wilhelmsen, L., Larsson, B., Ohlson, L. O., Svardsudd, K. and Tibblin, G. (1992) Metabolic disturbances in hypertension: results from the population study ‘men born in 1913’. J Intern Med 232, 389–395. 87. Williams, R. R., Hunt, S. C., Hasstedt, S. J., Hopkins, P. N., Wu, L. L., Berry, T. D., Stults, B. M., Barlow, G. K., Schumacher, M. C. and Lifton, R. P. et al. (1991) Are there interactions and relations between genetic and environmental factors predisposing to high blood pressure? Hypertension 18, I29–37. 88. Stamler, J., Vaccaro, O., Neaton, J. D. and Wentworth, D. (1993) Diabetes, other risk factors, and 12-yr cardiovascular mortality for men screened in the Multiple Risk Factor Intervention Trial. Diabetes Care 16, 434–444. 89. Schumacher, M. C., Maxwell, T. M., Wu, L. L., Hunt, S. C., Williams, R. R. and Elbein, S. C. (1992) Dyslipidemias among normoglycemic members of familial NIDDM pedigrees. Diabetes Care 15, 1285–1289. 90. Laws, A., Stefanick, M. L. and Reaven, G. M. (1989) Insulin resistance and hypertriglyceridemia in nondiabetic relatives of patients with noninsulin-dependent diabetes mellitus. J Clin Endocrinol Metab 69, 343–347. 91. Selby, J. V., Austin, M. A., Newman, B., Zhang, D., Quesenberry, C. P., Jr., Mayer, E. J. and Krauss, R. M. (1993) LDL subclass phenotypes and the insulin resistance syndrome in women. Circulation 88, 381–387. 92. Haffner, S. M., Stern, M. P., Hazuda, H. P., Mitchell, B. D., Patterson, J. K. and Ferrannini, E. (1989) Parental history of diabetes is associated with increased cardiovascular risk factors. Arteriosclerosis 9, 928–933. 93. Rice, T., Province, M., Perusse, L., Bouchard, C. and Rao, D. C. (1994) Cross-trait familial resemblance for body fat and blood pressure: familial correlations in the Quebec Family Study. Am J Hum Genet 55, 1019–1029. 94. Rice, T., Nadeau, A., Perusse, L., Bouchard, C. and Rao, D. C. (1996) Familial correlations in the Quebec Family Study: cross-trait familial resemblance for body fat with plasma glucose and insulin. Diabetologia 39, 1357–1364. 95. Perusse, L., Rice, T., Despres, J. P., Rao, D. C. and Bouchard, C. (1997) Cross-trait familial resemblance for body fat and blood lipids: familial correlations in the Quebec Family Study. Arterioscler Thromb Vasc Biol 17, 3270–3277. 96. Hong, Y., Rice, T., Gagnon, J., Despres, J. P., Nadeau, A., Perusse, L., Bouchard, C., Leon, A. S., Skinner, J. S., Wilmore, J. H. and Rao, D. C. (1998) Familial clustering of insulin and abdominal visceral fat: the HERITAGE Family Study. J Clin Endocrinol Metab 83, 4239–4245. 97. An, P., Rice, T., Gagnon, J., Leon, A. S., Skinner, J. S., Wilmore, J. H., Bouchard, C. and Rao, D. C. (2000) Cross-trait familial resemblance for resting blood pressure and body composition and fat distribution: the HERITAGE family study. Am J Human Biol 12, 32–41. 98. Mayer, E. J., Newman, B., Austin, M. A., Zhang, D., Quesenberry, C. P., Jr., Edwards, K. and Selby, J. V. (1996) Genetic and environmental influences on insulin levels and the insulin resistance syndrome: an analysis of women twins. Am J Epidemiol 143, 323–332. 99. Knutsen, S. F. and Knutsen, R. (1990) Wives of coronary high-risk men – are they also at higher risk? The Tromso Heart Study. J Intern Med 228, 333–337. 100. Hamosh, A., Scott, A. F., Amberger, J., Valle, D. and McKusick, V. A. (2000) Online Mendelian Inheritance in Man (OMIM). Hum Mutat 15, 57–61. 101. Bray, G. (1998) Contemporary Diagnosis and Management of Obesity. 1st edn. Newtown, PA: Handbooks in Healthcare, 289.

434

GENETICS OF THE METABOLIC SYNDROME

102. Hoybye, C., Hilding, A., Jacobsson, H. and Thoren, M. (2002) Metabolic profile and body composition in adults with Prader–Willi syndrome and severe obesity. J Clin Endocrinol Metab 87, 3590–3597. 103. Nicholls, R. D. and Knepper, J. L. (2001) Genome organization, function, and imprinting in Prader–Willi and Angelman syndromes. Annu Rev Genomics Hum Genet 2, 153–175. 104. Gallagher, R. C., Pils, B., Albalwi, M. and Francke, U. (2002) Evidence for the role of PWCR1/HBII-85 C/D box small nucleolar RNAs in Prader–Willi syndrome. Am J Hum Genet 71, 669–678. 105. Cummings, D. E., Clement, K., Purnell, J. Q., Vaisse, C., Foster, K. E., Frayo, R. S., Schwartz, M. W., Basdevant, A. and Weigle, D. S. (2002) Elevated plasma ghrelin levels in Prader Willi syndrome. Nat Med 8, 643–644. 106. Wren, A. M., Seal, L. J., Cohen, M. A., Brynes, A. E., Frost, G. S., Murphy, K. G., Dhillo, W. S., Ghatei, M. A. and Bloom, S. R. (2001) Ghrelin enhances appetite and increases food intake in humans. J Clin Endocrinol Metab 86, 5992. 107. Garg, A. (2000) Lipodystrophies. Am J Med 108, 143–152. 108. Scherer, P. E., Williams, S., Fogliano, M., Baldini, G. and Lodish, H. F. (1995) A novel serum protein similar to C1q, produced exclusively in adipocytes. J Biol Chem 270, 26 746–26 749. 109. Fruebis, J., Tsao, T. S., Javorschi, S., Ebbets-Reed, D., Erickson, M. R., Yen, F. T., Bihain, B. E. and Lodish, H. F. (2001) Proteolytic cleavage product of 30-kDa adipocyte complement-related protein increases fatty acid oxidation in muscle and causes weight loss in mice. Proc Natl Acad Sci USA 98, 2005–2010. 110. Berg, A. H., Combs, T. P., Du, X., Brownlee, M. and Scherer, P. E. (2001) The adipocyte-secreted protein Acrp30 enhances hepatic insulin action. Nat Med 7, 947–953. 111. Berg, A. H., Combs, T. P. and Scherer, P. E. (2002) ACRP30/adiponectin: an adipokine regulating glucose and lipid metabolism. Trends Endocrinol Metab 13, 84–89. 112. Maeda, N., Shimomura, I., Kishida, K., Nishizawa, H., Matsuda, M., Nagaretani, H., Furuyama, N., Kondo, H., Takahashi, M., Arita, Y., Komuro, R., Ouchi, N., Kihara, S., Tochino, Y., Okutomi, K., Horie, M., Takeda, S., Aoyama, T., Funahashi, T. and Matsuzawa, Y. (2002) Diet-induced insulin resistance in mice lacking adiponectin/ACRP30. Nat Med 8, 731–737. 113. Kondo, H., Shimomura, I., Matsukawa, Y., Kumada, M., Takahashi, M., Matsuda, M., Ouchi, N., Kihara, S., Kawamoto, T., Sumitsuji, S., Funahashi, T. and Matsuzawa, Y. (2002) Association of adiponectin mutation with type 2 diabetes: a candidate gene for the insulin resistance syndrome. Diabetes 51, 2325–2328. 114. Yamauchi, T., Kamon, J., Minokoshi, Y., Ito, Y., Waki, H., Uchida, S., Yamashita, S., Noda, M., Kita, S., Ueki, K., Eto, K., Akanuma, Y., Froguel, P., Foufelle, F., Ferre, P., Carling, D., Kimura, S., Nagai, R., Kahn, B. B. and Kadowaki, T. (2002) Adiponectin stimulates glucose utilization and fatty-acid oxidation by activating AMP-activated protein kinase. Nat Med 8, 1288–1295. 115. Arita, Y., Kihara, S., Ouchi, N., Takahashi, M., Maeda, K., Miyagawa, J., Hotta, K., Shimomura, I., Nakamura, T., Miyaoka, K., Kuriyama, H., Nishida, M., Yamashita, S., Okubo, K., Matsubara, K., Muraguchi, M., Ohmoto, Y., Funahashi, T. and Matsuzawa, Y. (1999) Paradoxical decrease of an adipose-specific protein, adiponectin, in obesity. Biochem Biophys Res Commun 257, 79–83. 116. Matsubara, M., Maruoka, S. and Katayose, S. (2002) Decreased plasma adiponectin concentrations in women with dyslipidemia. J Clin Endocrinol Metab 87, 2764–2769. 117. Stefan, N., Vozarova, B., Funahashi, T., Matsuzawa, Y., Weyer, C., Lindsay, R. S., Youngren, J. F., Havel, P. J., Pratley, R. E., Bogardus, C. and Tataranni, P. A. (2002)

REFERENCES

118.

119.

120.

121.

122.

123.

124.

125.

126.

127.

128.

435

Plasma adiponectin concentration is associated with skeletal muscle insulin receptor tyrosine phosphorylation, and low plasma concentration precedes a decrease in wholebody insulin sensitivity in humans. Diabetes 51, 1884–1888. Ouchi, N., Kihara, S., Arita, Y., Nishida, M., Matsuyama, A., Okamoto, Y., Ishigami, M., Kuriyama, H., Kishida, K., Nishizawa, H., Hotta, K., Muraguchi, M., Ohmoto, Y., Yamashita, S., Funahashi, T. and Matsuzawa, Y. (2001) Adipocyte-derived plasma protein, adiponectin, suppresses lipid accumulation and class A scavenger receptor expression in human monocyte-derived macrophages. Circulation 103, 1057–1063. Weyer, C., Funahashi, T., Tanaka, S., Hotta, K., Matsuzawa, Y., Pratley, R. E. and Tataranni, P. A. (2001) Hypoadiponectinemia in obesity and type 2 diabetes: close association with insulin resistance and hyperinsulinemia. J Clin Endocrinol Metab 86, 1930–1935. Takahashi, M., Arita, Y., Yamagata, K., Matsukawa, Y., Okutomi, K., Horie, M., Shimomura, I., Hotta, K., Kuriyama, H., Kihara, S., Nakamura, T., Yamashita, S., Funahashi, T. and Matsuzawa, Y. (2000) Genomic structure and mutations in adiposespecific gene, adiponectin. Int J Obes Relat Metab Disord 24, 861–868. Menzaghi, C., Ercolino, T., Di Paola, R., Berg, A. H., Warram, J. H., Scherer, P. E., Trischitta, V. and Doria, A. (2002) A haplotype at the adiponectin locus is associated with obesity and other features of the insulin resistance syndrome. Diabetes 51, 2306–2312. Stumvoll, M., Tschritter, O., Fritsche, A., Staiger, H., Renn, W., Weisser, M., Machicao, F. and Haring, H. (2002) Association of the T-G polymorphism in adiponectin (exon 2) with obesity and insulin sensitivity: interaction with family history of type 2 diabetes. Diabetes 51, 37–41. Hara, K., Boutin, P., Mori, Y., Tobe, K., Dina, C., Yasuda, K., Yamauchi, T., Otabe, S., Okada, T., Eto, K., Kadowaki, H., Hagura, R., Akanuma, Y., Yazaki, Y., Nagai, R., Taniyama, M., Matsubara, K., Yoda, M., Nakano, Y., Tomita, M., Kimura, S., Ito, C., Froguel, P. and Kadowaki, T. (2002) Genetic variation in the gene encoding adiponectin is associated with an increased risk of type 2 diabetes in the Japanese population. Diabetes 51, 536–540. Vasseur, F., Helbecque, N., Dina, C., Lobbens, S., Delannoy, V., Gaget, S., Boutin, P., Vaxillaire, M., Lepretre, F., Dupont, S., Hara, K., Clement, K., Bihain, B., Kadowaki, T. and Froguel, P. (2002) Single-nucleotide polymorphism haplotypes in the both proximal promoter and exon 3 of the APM1 gene modulate adipocyte-secreted adiponectin hormone levels and contribute to the genetic risk for type 2 diabetes in French Caucasians. Hum Mol Genet 11, 2607–2614. Zhang, Y., Proenca, R., Maffei, M., Barone, M., Leopold, L. and Friedman, J. M. (1994) Positional cloning of the mouse obese gene and its human homologue [published erratum appears in Nature 1995 374 (6521), 479] [see comments]. Nature 372, 425–432. Green, E. D., Maffei, M., Braden, V. V., Proenca, R., DeSilva, U., Zhang, Y., Chua, S. C., Jr., Leibel, R. L., Weissenbach, J. and Friedman, J. M. (1995) The human obese (OB) gene: RNA expression pattern and mapping on the physical, cytogenetic, and genetic maps of chromosome 7. Genome Res 5, 5–12. Karvonen, M. K., Pesonen, U., Heinonen, P., Laakso, M., Rissanen, A., Naukkarinen, H., Valve, R., Uusitupa, M. I. and Koulu, M. (1998) Identification of new sequence variants in the leptin gene. J Clin Endocrinol Metab 83, 3239–3242. Akerman, F., Lei, Z. M. and Rao, C. V. (2002) Human umbilical cord and fetal membranes co-express leptin and its receptor genes. Gynecol Endocrinol 16, 299–306.

436

GENETICS OF THE METABOLIC SYNDROME

129. Leroy, P., Dessolin, S., Villageois, P., Moon, B. C., Friedman, J. M., Ailhaud, G. and Dani, C. (1996) Expression of ob gene in adipose cells. Regulation by insulin. J Biol Chem 271, 2365–2368. 130. Halaas, J. L., Gajiwala, K. S., Maffei, M., Cohen, S. L., Chait, B. T., Rabinowitz, D., Lallone, R. L., Burley, S. K. and Friedman, J. M. (1995) Weight-reducing effects of the plasma protein encoded by the obese gene [see comments]. Science 269, 543–546. 131. Vaisse, C., Halaas, J. L., Horvath, C. M., Darnell, J. E., Jr., Stoffel, M. and Friedman, J. M. (1996) Leptin activation of Stat3 in the hypothalamus of wild-type and ob/ob mice but not db/db mice. Nat Genet 14, 95–97. 132. Shimon, I., Yan, X., Magoffin, D. A., Friedman, T. C. and Melmed, S. (1998) Intact leptin receptor is selectively expressed in human fetal pituitary and pituitary adenomas and signals human fetal pituitary growth hormone secretion. J Clin Endocrinol Metab 83, 4059–4064. 133. Spicer, L. J. (2001) Leptin: a possible metabolic signal affecting reproduction. Domest Anim Endocrinol 21, 251–270. 134. Brann, D. W., Wade, M. F., Dhandapani, K. M., Mahesh, V. B. and Buchanan, C. D. (2002) Leptin and reproduction. Steroids 67, 95–104. 135. Ravussin, E., Pratley, R. E., Maffei, M., Wang, H., Friedman, J. M., Bennett, P. H. and Bogardus, C. (1997) Relatively low plasma leptin concentrations precede weight gain in Pima Indians. Nat Med 3, 238–240. 136. Hinney, A., Bornscheuer, A., Depenbusch, M., Mierke, B., Tolle, A., Middeke, K., Ziegler, A., Roth, H., Gerber, G., Zamzow, K., Ballauff, A., Hamann, A., Mayer, H., Siegfried, W., Lehmkuhl, G., Poustka, F., Schmidt, M. H., Hermann, H., HerpertzDahlmann, B. M., Fichter, M., Remschmidt, H. and Hebebrand, J. (1998) No evidence for involvement of the leptin gene in anorexia nervosa, bulimia nervosa, underweight or early onset extreme obesity: identification of two novel mutations in the coding sequence and a novel polymorphism in the leptin gene linked upstream region. Mol Psychiatry 3, 539–543. 137. Hager, J., Clement, K., Francke, S., Dina, C., Raison, J., Lahlou, N., Rich, N., Pelloux, V., Basdevant, A., Guy-Grand, B., North, M. and Froguel, P. (1998) A polymorphism in the 5
untranslated region of the human ob gene is associated with low leptin levels. Int J Obes Relat Metab Disord 22, 200–205. 138. Ohshiro, Y., Ueda, K., Nishi, M., Ishigame, M., Wakasaki, H., Kawashima, H., Furuta, H., Sasaki, H., Sanke, T., Takasu, N. and Nanjo, K. (2000) A polymorphic marker in the leptin gene associated with Japanese morbid obesity. J Mol Med 78, 516–520. 139. Mammes, O., Betoulle, D., Aubert, R., Herbeth, B., Siest, G. and Fumeron, F. (2000) Association of the G-2548A polymorphism in the 5
region of the LEP gene with overweight. Ann Hum Genet 64, 391–394. 140. Hoffstedt, J., Eriksson, P., Mottagui-Tabar, S. and Arner, P. (2002) A polymorphism in the leptin promoter region (−2548 g/a) influences gene expression and adipose tissue secretion of leptin. Horm Metab Res 34, 355–359. 141. Shintani, M., Ikegami, H., Fujisawa, T., Kawaguchi, Y., Ohishi, M., Katsuya, T., Higaki, J., Shimamoto, K. and Ogihara, T. (2002) Leptin gene polymorphism is associated with hypertension independent of obesity. J Clin Endocrinol Metab 87, 2909–2912. 142. Montague, C. T., Farooqi, I. S., Whitehead, J. P., Soos, M. A., Rau, H., Wareham, N. J., Sewter, C. P., Digby, J. E., Mohammed, S. N., Hurst, J. A., Cheetham, C. H., Earley, A. R., Barnett, A. H., Prins, J. B. and O’Rahilly, S. (1997) Congenital leptin deficiency is associated with severe early-onset obesity in humans. Nature 387, 903–908.

REFERENCES

437

143. Farooqi, I. S., Keogh, J. M., Kamath, S., Jones, S., Gibson, W. T., Trussell, R., Jebb, S. A., Lip, G. Y. and O’Rahilly, S. (2001) Partial leptin deficiency and human adiposity. Nature 414, 34–35. 144. Thompson, D. B., Ravussin, E., Bennett, P. H. and Bogardus, C. (1997) Structure and sequence variation at the human leptin receptor gene in lean and obese Pima Indians. Hum Mol Genet 6, 675–679. 145. Clement, K., Vaisse, C., Lahlou, N., Cabrol, S., Pelloux, V., Cassuto, D., Gourmelen, M., Dina, C., Chambaz, J., Lacorte, J. M., Basdevant, A., Bougneres, P., Lebouc, Y., Froguel, P. and Guy-Grand, B. (1998) A mutation in the human leptin receptor gene causes obesity and pituitary dysfunction. Nature 392, 398–401. 146. Chagnon, Y. C., Chung, W. K., Perusse, L., Chagnon, M., Leibel, R. L. and Bouchard, C. (1999) Linkages and associations between the leptin receptor (LEPR) gene and human body composition in the Quebec Family Study. Int J Obes Relat Metab Disord 23, 278–286. 147. Lakka, H. M., Oksanen, L., Tuomainen, T. P., Kontula, K. and Salonen, J. T. (2000) The common pentanucleotide polymorphism of the 3
-untranslated region of the leptin receptor gene is associated with serum insulin levels and the risk of type 2 diabetes in non-diabetic men: a prospective case–control study. J Intern Med 248, 77–83. 148. Chagnon, Y. C., Wilmore, J. H., Borecki, I. B., Gagnon, J., Perusse, L., Chagnon, M., Collier, G. R., Leon, A. S., Skinner, J. S., Rao, D. C. and Bouchard, C. (2000) Associations between the leptin receptor gene and adiposity in middle-aged Caucasian males from the HERITAGE family study. J Clin Endocrinol Metab 85, 29–34. 149. de Silva, A. M., Walder, K. R., Aitman, T. J., Gotoda, T., Goldstone, A. P., Hodge, A. M., de Courten, M. P., Zimmet, P. Z. and Collier, G. R. (1999) Combination of polymorphisms in OB-R and the OB gene associated with insulin resistance in Nauruan males. Int J Obes Relat Metab Disord 23, 816–822. 150. Quinton, N. D., Lee, A. J., Ross, R. J., Eastell, R. and Blakemore, A. I. (2001) A single nucleotide polymorphism (SNP) in the leptin receptor is associated with BMI, fat mass and leptin levels in postmenopausal Caucasian women. Hum Genet 108, 233–236. 151. Wauters, M., Mertens, I., Chagnon, M., Rankinen, T., Considine, R. V., Chagnon, Y. C., Van Gaal, L. F. and Bouchard, C. (2001) Polymorphisms in the leptin receptor gene, body composition and fat distribution in overweight and obese women. Int J Obes Relat Metab Disord 25, 714–720. 152. Wauters, M., Mertens, I., Rankinen, T., Chagnon, M., Bouchard, C. and Van Gaal, L. (2001) Leptin receptor gene polymorphisms are associated with insulin in obese women with impaired glucose tolerance. J Clin Endocrinol Metab 86, 3227–3232. 153. Mammes, O., Aubert, R., Betoulle, D., Pean, F., Herbeth, B., Visvikis, S., Siest, G. and Fumeron, F. (2001) LEPR gene polymorphisms: associations with overweight, fat mass and response to diet in women. Eur J Clin Invest 31, 398–404. 154. Gotoda, T., Manning, B. S., Goldstone, A. P., Imrie, H., Evans, A. L., Strosberg, A. D., McKeigue, P. M., Scott, J. and Aitman, T. J. (1997) Leptin receptor gene variation and obesity: lack of association in a white British male population. Hum Mol Genet 6, 869–876. 155. Silver, K., Walston, J., Chung, W. K., Yao, F., Parikh, V. V., Andersen, R., Cheskin, L. J., Elahi, D., Muller, D., Leibel, R. L. and Shuldiner, A. R. (1997) The Gln223Arg and Lys656Asn polymorphisms in the human leptin receptor do not associate with traits related to obesity. Diabetes 46, 1898–1900. 156. Rand, L., Winchester, E. C., Millwood, I. Y., Penny, M. A. and Kessling, A. M. (2001) Maternal leptin receptor gene variant Gln223Arg is not associated with variation in birth weight or maternal body mass index in UK and South Asian populations. Int J Obes Relat Metab Disord 25, 753–755.

438

GENETICS OF THE METABOLIC SYNDROME

157. Heo, M., Leibel, R. L., Fontaine, K. R., Boyer, B. B., Chung, W. K., Koulu, M., Karvonen, M. K., Pesonen, U., Rissanen, A., Laakso, M., Uusitupa, M. I., Chagnon, Y., Bouchard, C., Donohoue, P. A., Burns, T. L., Shuldiner, A. R., Silver, K., Andersen, R. E., Pedersen, O., Echwald, S., Sorensen, T. I., Behn, P., Permutt, M. A., Jacobs, K. B., Elston, R. C., Hoffman, D. J., Gropp, E. and Allison, D. B. (2002) A meta-analytic investigation of linkage and association of common leptin receptor (LEPR) polymorphisms with body mass index and waist circumference. Int J Obes Relat Metab Disord 26, 640–646. 158. Holcomb, I. N., Kabakoff, R. C., Chan, B., Baker, T. W., Gurney, A., Henzel, W., Nelson, C., Lowman, H. B., Wright, B. D., Skelton, N. J., Frantz, G. D., Tumas, D. B., Peale, F. V., Jr., Shelton, D. L. and Hebert, C. C. (2000) FIZZ1, a novel cysteine-rich secreted protein associated with pulmonary inflammation, defines a new gene family. EMBO J 19, 4046–4055. 159. Way, J. M., Gorgun, C. Z., Tong, Q., Uysal, K. T., Brown, K. K., Harrington, W. W., Oliver, W. R., Jr., Willson, T. M., Kliewer, S. A. and Hotamisligil, G. S. (2001) Adipose tissue resistin expression is severely suppressed in obesity and stimulated by peroxisome proliferator-activated receptor gamma agonists. J Biol Chem 276, 25 651–25 653. 160. Savage, D. B., Sewter, C. P., Klenk, E. S., Segal, D. G., Vidal-Puig, A., Considine, R. V. and O’Rahilly, S. (2001) Resistin/Fizz3 expression in relation to obesity and peroxisome proliferator-activated receptor-gamma action in humans. Diabetes 50, 2199–2202. 161. Nagaev, I. and Smith, U. (2001) Insulin resistance and type 2 diabetes are not related to resistin expression in human fat cells or skeletal muscle. Biochem Biophys Res Commun 285, 561–564. 162. Lay, S. L., Boucher, J., Rey, A., Castan-Laurell, I., Krief, S., Ferre, P., Valet, P. and Dugail, I. (2001) Decreased resistin expression in mice with different sensitivities to a high-fat diet. Biochem Biophys Res Commun 289, 564–567. 163. Janke, J., Engeli, S., Gorzelniak, K., Luft, F. C. and Sharma, A. M. (2002) Resistin gene expression in human adipocytes is not related to insulin resistance. Obes Res 10, 1–5. 164. Rajala, M. W., Lin, Y., Ranalletta, M., Yang, X. M., Qian, H., Gingerich, R., Barzilai, N. and Scherer, P. E. (2002) Cell type-specific expression and coregulation of murine resistin and resistin-like molecule-alpha in adipose tissue. Mol Endocrinol 16, 1920–1930. 165. McTernan, C. L., McTernan, P. G., Harte, A. L., Levick, P. L., Barnett, A. H. and Kumar, S. (2002) Resistin, central obesity, and type 2 diabetes. Lancet 359, 46–47. 166. Kim, K. H., Lee, K., Moon, Y. S. and Sul, H. S. (2001) A cysteine-rich adipose tissue-specific secretory factor inhibits adipocyte differentiation. J Biol Chem 276, 11 252–11 256. 167. Unger, R. H. and Orci, L. (2000) Lipotoxic diseases of nonadipose tissues in obesity. Int J Obes Relat Metab Disord 24 (Suppl. 4), S28–32. 168. Sentinelli, F., Romeo, S., Arca, M., Filippi, E., Leonetti, F., Banchieri, M., Di Mario, U. and Baroni, M. G. (2002) Human resistin gene, obesity, and type 2 diabetes: mutation analysis and population study. Diabetes 51, 860–862. 169. Osawa, H., Onuma, H., Murakami, A., Ochi, M., Nishimiya, T., Kato, K., Shimizu, I., Fujii, Y., Ohashi, J. and Makino, H. (2002) Systematic search for single nucleotide polymorphisms in the resistin gene: the absence of evidence for the association of three identified single nucleotide polymorphisms with Japanese type 2 diabetes. Diabetes 51, 863–866.

REFERENCES

439

170. Wang, H., Chu, W. S., Hemphill, C. and Elbein, S. C. (2002) Human resistin gene: molecular scanning and evaluation of association with insulin sensitivity and type 2 diabetes in Caucasians. J Clin Endocrinol Metab 87, 2520–2524. 171. Ma, X., Warram, J. H., Trischitta, V. and Doria, A. (2002) Genetic variants at the resistin locus and risk of type 2 diabetes in Caucasians. J Clin Endocrinol Metab 87, 4407–4410. 172. Engert, J. C., Vohl, M. C., Williams, S. M., Lepage, P., Loredo-Osti, J. C., Faith, J., Dore, C., Renaud, Y., Burtt, N. P., Villeneuve, A., Hirschhorn, J. N., Altshuler, D., Groop, L. C., Despres, J. P., Gaudet, D. and Hudson, T. J. (2002) 5
flanking variants of resistin are associated with obesity. Diabetes 51, 1629–1634. 173. Pizzuti, A., Argiolas, A., Di Paola, R., Baratta, R., Rauseo, A., Bozzali, M., Vigneri, R., Dallapiccola, B., Trischitta, V. and Frittitta, L. (2002) An ATG repeat in the 3
-untranslated region of the human resistin gene is associated with a decreased risk of insulin resistance. J Clin Endocrinol Metab 87, 4403–4406. 174. Maddux, B. A. and Goldfine, I. D. (2000) Membrane glycoprotein PC-1 inhibition of insulin receptor function occurs via direct interaction with the receptor alpha-subunit. Diabetes 49, 13–19. 175. Maddux, B. A., Sbraccia, P., Kumakura, S., Sasson, S., Youngren, J., Fisher, A., Spencer, S., Grupe, A., Henzel, W. and Stewart, T. A. et al. (1995) Membrane glycoprotein PC-1 and insulin resistance in non-insulin-dependent diabetes mellitus [see comments]. Nature 373, 448–451. 176. Frittitta, L., Spampinato, D., Solini, A., Nosadini, R., Goldfine, I. D., Vigneri, R. and Trischitta, V. (1998) Elevated PC-1 content in cultured skin fibroblasts correlates with decreased in vivo and in vitro insulin action in nondiabetic subjects: evidence that PC-1 may be an intrinsic factor in impaired insulin receptor signaling. Diabetes 47, 1095–1100. 177. Frittitta, L., Camastra, S., Baratta, R., Costanzo, B. V., D’Adamo, M., Graci, S., Spampinato, D., Maddux, B. A., Vigneri, R., Ferrannini, E. and Trischitta, V. (1999) A soluble PC-1 circulates in human plasma: relationship with insulin resistance and associated abnormalities. J Clin Endocrinol Metab 84, 3620–3625. 178. Tomazic, M., Janez, A., Sketelj, A., Kocijancic, A., Eckel, J. and Sharma, P. M. (2002) Comparison of alterations in insulin signalling pathway in adipocytes from Type II diabetic pregnant women and women with gestational diabetes mellitus. Diabetologia 45, 502–508. 179. Pizzuti, A., Frittitta, L., Argiolas, A., Baratta, R., Goldfine, I. D., Bozzali, M., Ercolino, T., Scarlato, G., Iacoviello, L., Vigneri, R., Tassi, V. and Trischitta, V. (1999) A polymorphism (K121Q) of the human glycoprotein PC-1 gene coding region is strongly associated with insulin resistance. Diabetes 48, 1881–1884. 180. Gu, H. F., Almgren, P., Lindholm, E., Frittitta, L., Pizzuti, A., Trischitta, V. and Groop, L. C. (2000) Association between the human glycoprotein PC-1 gene and elevated glucose and insulin levels in a paired-sibling analysis. Diabetes 49, 1601–1603. 181. Rasmussen, S. K., Urhammer, S. A., Pizzuti, A., Echwald, S. M., Ekstrom, C. T., Hansen, L., Hansen, T., Borch-Johnsen, K., Frittitta, L., Trischitta, V. and Pedersen, O. (2000) The K121Q variant of the human PC-1 gene is not associated with insulin resistance or type 2 diabetes among Danish Caucasians. Diabetes 49, 1608–1611. 182. Frittitta, L., Ercolino, T., Bozzali, M., Argiolas, A., Graci, S., Santagati, M. G., Spampinato, D., Di Paola, R., Cisternino, C., Tassi, V., Vigneri, R., Pizzuti, A. and Trischitta, V. (2001) A cluster of three single nucleotide polymorphisms in the 3
-untranslated region of human glycoprotein PC-1 gene stabilizes PC-1 mRNA and is associated with increased PC-1 protein content and insulin resistance-related abnormalities. Diabetes 50, 1952–1955.

440

GENETICS OF THE METABOLIC SYNDROME

183. Duggirala, R., Blangero, J., Almasy, L., Arya, R., Dyer, T. D., Williams, K. L., Leach, R. J., O’Connell, P. and Stern, M. P. (2001) A major locus for fasting insulin concentrations and insulin resistance on chromosome 6q with strong pleiotropic effects on obesity-related phenotypes in nondiabetic Mexican Americans. Am J Hum Genet 68, 1149–1164. 184. Barroso, I., Gurnell, M., Crowley, V. E., Agostini, M., Schwabe, J. W., Soos, M. A., Maslen, G. L., Williams, T. D., Lewis, H., Schafer, A. J., Chatterjee, V. K. and O’Rahilly, S. (1999) Dominant negative mutations in human PPARgamma associated with severe insulin resistance, diabetes mellitus and hypertension. Nature 402, 880–883. 185. Yen, C. J., Beamer, B. A., Negri, C., Silver, K., Brown, K. A., Yarnall, D. P., Burns, D. K., Roth, J. and Shuldiner, A. R. (1997) Molecular scanning of the human peroxisome proliferator activated receptor gamma (hPPAR gamma) gene in diabetic Caucasians: identification of a Pro12Ala PPAR gamma 2 missense mutation. Biochem Biophys Res Commun 241, 270–274. 186. Bocher, V., Chinetti, G., Fruchart, J. C. and Staels, B. (2002) Role of the peroxisome proliferator-activated receptors (PPARS) in the regulation of lipids and inflammation control. J Soc Biol 196, 47–52. 187. Olefsky, J. M. and Saltiel, A. R. (2000) PPAR gamma and the treatment of insulin resistance. Trends Endocrinol Metab 11, 362–368. 188. Wang, N., Verna, L., Chen, N. G., Chen, J., Li, H., Forman, B. M. and Stemerman, M. B. (2002) Constitutive activation of peroxisome proliferator-activated receptorgamma suppresses pro-inflammatory adhesion molecules in human vascular endothelial cells. J Biol Chem 277, 34176–34181. 189. Gonzalez Sanchez, J. L., Serrano Rios, M., Fernandez Perez, C., Laakso, M. and Martinez Larrad, M. T. Effect of the Pro12Ala polymorphism of the peroxisome proliferator-activated receptor gamma-2 gene on adiposity, insulin sensitivity and lipid profile in the Spanish population. Eur J Endocrinol 147, 495–501. 190. Frederiksen, L., Brodbaek, K., Fenger, M., Jorgensen, T., Borch-Johnsen, K., Madsbad, S. and Urhammer, S. A. (2002) Comment: studies of the Pro12Ala polymorphism of the PPAR-gamma gene in the Danish MONICA cohort: homozygosity of the Ala allele confers a decreased risk of the insulin resistance syndrome. J Clin Endocrinol Metab 87, 3989–3992. 191. Fischer, P., Moller, P., Bindl, L., Melzner, I., Tornqvist, H., Debatin, K. M. and Wabitsch, M. (2002) Induction of adipocyte differentiation by a thiazolidinedione in cultured, subepidermal, fibroblast-like cells of an infant with congenital generalized lipodystrophy. J Clin Endocrinol Metab 87, 2384–2390. 192. Agarwal, A. K. and Garg, A. (2002) A novel heterozygous mutation in peroxisome proliferator-activated receptor-gamma gene in a patient with familial partial lipodystrophy. J Clin Endocrinol Metab 87, 408–411. 193. Lafontan, M. and Berlan, M. (1993) Fat cell adrenergic receptors and the control of white and brown fat cell function. J Lipid Res 34, 1057–1091. 194. Emorine, L. J., Marullo, S., Briend-Sutren, M. M., Patey, G., Tate, K., DelavierKlutchko, C. and Strosberg, A. D. (1989) Molecular characterization of the human beta 3-adrenergic receptor. Science 245, 1118–1121. 195. Granneman, J. G., Lahners, K. N. and Chaudhry, A. (1993) Characterization of the human beta 3-adrenergic receptor gene. Mol Pharmacol 44, 264–270. 196. Krief, S., Lonnqvist, F., Raimbault, S., Baude, B., Van Spronsen, A., Arner, P., Strosberg, A. D., Ricquier, D. and Emorine, L. J. (1993) Tissue distribution of beta 3-adrenergic receptor mRNA in man. J Clin Invest 91, 344–349.

REFERENCES

441

197. Lafontan, M. (1994) Differential recruitment and differential regulation by physiological amines of fat cell beta-1, beta-2 and beta-3 adrenergic receptors expressed in native fat cells and in transfected cell lines. Cell Signal 6, 363–392. 198. Balligand, J. L. (2000) Beta 3 adrenergic receptor: physiologic role and potential therapeutic applications. Bull Mem Acad R Med Belg 155, 311–317; discussion 317–319. 199. Dixon, T. M., Daniel, K. W., Farmer, S. R. and Collins, S. (2001) CCAAT/enhancerbinding protein alpha is required for transcription of the beta 3-adrenergic receptor gene during adipogenesis. J Biol Chem 276, 722–728. 200. Walston, J., Silver, K., Bogardus, C., Knowler, W. C., Celi, F. S., Austin, S., Manning, B., Strosberg, A. D., Stern, M. P. and Raben, N. et al. (1995) Time of onset of non-insulin-dependent diabetes mellitus and genetic variation in the beta 3-adrenergicreceptor gene. N Engl J Med 333, 343–347. 201. Hayashi, H., Nagasaka, S., Ishikawa, S., Kawakami, A., Rokkaku, K., Nakamura, T., Saito, T., Kusaka, I., Higashiyama, M., Kubota, K. and Murakami, T. (1998) Contribution of a missense mutation (Trp64Arg) in beta3-adrenergic receptor gene to multiple risk factors in Japanese men with hyperuricemia. Endocr J 45, 779–784. 202. Manraj, M., Francke, S., Hebe, A., Ramjuttun, U. S. and Froguel, P. (2001) Genetic and environmental nature of the insulin resistance syndrome in Indo-Mauritian subjects with premature coronary heart disease: contribution of beta3-adrenoreceptor gene polymorphism and beta blockers on triglyceride and HDL concentrations. Diabetologia 44, 115–122. 203. Strazzullo, P., Iacone, R., Siani, A., Cappuccio, F. P., Russo, O., Barba, G., Barbato, A., D’Elia, L., Trevisan, M. and Farinaro, E. (2001) Relationship of the Trp64Arg polymorphism of the beta3-adrenoceptor gene to central adiposity and high blood pressure: interaction with age. Cross-sectional and longitudinal findings of the Olivetti Prospective Heart Study. J Hypertens 19, 399–406. 204. Kim-Motoyama, H., Yasuda, K., Yamaguchi, T., Yamada, N., Katakura, T., Shuldiner, A. R., Akanuma, Y., Ohashi, Y., Yazaki, Y. and Kadowaki, T. (1997) A mutation of the beta 3-adrenergic receptor is associated with visceral obesity but decreased serum triglyceride. Diabetologia 40, 469–472. 205. Melis, M. G., Secchi, G., Brizzi, P., Severino, C., Maioli, M. and Tonolo, G. (2002) The Trp64Arg beta3-adrenergic receptor amino acid variant confers increased sensitivity to the pressor effects of noradrenaline in Sardinian subjects. Clin Sci (Lond) 103, 397–402. 206. Gagnon, J., Mauriege, P., Roy, S., Sjostrom, D., Chagnon, Y. C., Dionne, F. T., Oppert, J. M., Perusse, L., Sjostrom, L. and Bouchard, C. (1996) The Trp64Arg mutation of the beta3 adrenergic receptor gene has no effect on obesity phenotypes in the Quebec Family Study and Swedish Obese Subjects cohorts. J Clin Invest 98, 2086–2093. 207. Rissanen, J., Kuopusjarvi, J., Pihlajamaki, J., Sipilainen, R., Heikkinen, S., Vanhala, M., Kekalainen, P., Kuusisto, J. and Laakso, M. (1997) The Trp64Arg polymorphism of the beta 3-adrenergic receptor gene. Lack of association with NIDDM and features of insulin resistance syndrome. Diabetes Care 20, 1319–1323. 208. Thomas, G. N., Tomlinson, B., Chan, J. C., Young, R. P. and Critchley, J. A. (2000) The Trp64Arg polymorphism of the beta3-adrenergic receptor gene and obesity in Chinese subjects with components of the metabolic syndrome. Int J Obes Relat Metab Disord 24, 545–551. 209. Vogeser, M., Zachoval, R., Felbinger, T. W. and Jacob, K. (2002) Increased ratio of serum cortisol to cortisone in acute-phase response. Horm Res 58, 172–175.

442

GENETICS OF THE METABOLIC SYNDROME

210. Ferrari, P. and Krozowski, Z. (2000) Role of the 11beta-hydroxysteroid dehydrogenase type 2 in blood pressure regulation. Kidney Int 57, 1374–1381. 211. Williams, L. J., Lyons, V., MacLeod, I., Rajan, V., Darlington, G. J., Poli, V., Seckl, J. R. and Chapman, K. E. (2000) C/EBP regulates hepatic transcription of 11beta-hydroxysteroid dehydrogenase type 1. A novel mechanism for cross-talk between the C/EBP and glucocorticoid signaling pathways. J Biol Chem 275, 30 232–30 239. 212. White, P. C., Agarwal, A. K., Nunez, B. S., Giacchetti, G., Mantero, F. and Stewart, P. M. (2000) Genotype–phenotype correlations of mutations and polymorphisms in HSD11B2, the gene encoding the kidney isozyme of 11beta-hydroxysteroid dehydrogenase. Endocr Res 26, 771–780. 213. Agarwal, A. K., Giacchetti, G., Lavery, G., Nikkila, H., Palermo, M., Ricketts, M., McTernan, C., Bianchi, G., Manunta, P., Strazzullo, P., Mantero, F., White, P. C. and Stewart, P. M. (2000) CA-repeat polymorphism in intron 1 of HSD11B2: effects on gene expression and salt sensitivity. Hypertension 36, 187–194. 214. Li, A., Li, K. X., Marui, S., Krozowski, Z. S., Batista, M. C., Whorwood, C. B., Arnhold, I. J., Shackleton, C. H., Mendonca, B. B. and Stewart, P. M. (1997) Apparent mineralocorticoid excess in a Brazilian kindred: hypertension in the heterozygote state. J Hypertens 15, 1397–1402. 215. Wilson, R. C., Dave-Sharma, S., Wei, J. Q., Obeyesekere, V. R., Li, K., Ferrari, P., Krozowski, Z. S., Shackleton, C. H., Bradlow, L., Wiens, T. and New, M. I. (1998) A genetic defect resulting in mild low-renin hypertension. Proc Natl Acad Sci USA 95, 10 200–10 205. 216. Rogoff, D., Smolenicka, Z., Bergada, I., Vallejo, G., Barontini, M., Heinrich, J. J. and Ferrari, P. (1998) The codon 213 of the 11beta-hydroxysteroid dehydrogenase type 2 gene is a hot spot for mutations in apparent mineralocorticoid excess. J Clin Endocrinol Metab 83, 4391–4393. 217. Nunez, B. S., Rogerson, F. M., Mune, T., Igarashi, Y., Nakagawa, Y., Phillipov, G., Moudgil, A., Travis, L. B., Palermo, M., Shackleton, C. and White, P. C. (1999) Mutants of 11beta-hydroxysteroid dehydrogenase (11-HSD2) with partial activity: improved correlations between genotype and biochemical phenotype in apparent mineralocorticoid excess. Hypertension 34, 638–642. 218. Odermatt, A., Dick, B., Arnold, P., Zaehner, T., Plueschke, V., Deregibus, M. N., Repetto, H., Frey, B. M., Frey, F. J. and Ferrari, P. (2001) A mutation in the cofactor-binding domain of 11beta-hydroxysteroid dehydrogenase type 2 associated with mineralocorticoid hypertension. J Clin Endocrinol Metab 86, 1247– 1252. 219. Sugiyama, T., Kato, N., Ishinaga, Y., Yamori, Y. and Yazaki, Y. (2001) Evaluation of selected polymorphisms of the Mendelian hypertensive disease genes in the Japanese population. Hypertens Res 24, 515–521. 220. Poch, E., Gonzalez, D., Giner, V., Bragulat, E., Coca, A. and de La Sierra, A. (2001) Molecular basis of salt sensitivity in human hypertension. Evaluation of renin–angiotensin–aldosterone system gene polymorphisms. Hypertension 38, 1204–1209. 221. Smith, A. D., (2000) Oxford Dictionary of Biochemistry and Molecular Biology. Revised edn. Oxford: Oxford University Press. 222. Ruan, H., Hacohen, N., Golub, T. R., Van Parijs, L. and Lodish, H. F. (2002) Tumor necrosis factor-alpha suppresses adipocyte-specific genes and activates expression of preadipocyte genes in 3T3-L1 adipocytes: nuclear factor-kappaB activation by TNFalpha is obligatory. Diabetes 51, 1319–1336.

REFERENCES

443

223. Xu, H., Uysal, K. T., Becherer, J. D., Arner, P. and Hotamisligil, G. S. (2002) Altered tumor necrosis factor-alpha (TNF-alpha) processing in adipocytes and increased expression of transmembrane TNF-alpha in obesity. Diabetes 51, 1876–1883. 224. Bullo, M., Garcia-Lorda, P., Peinado-Onsurbe, J., Hernandez, M., Del Castillo, D., Argiles, J. M. and Salas-Salvado, J. (2002) TNFalpha expression of subcutaneous adipose tissue in obese and morbid obese females: relationship to adipocyte LPL activity and leptin synthesis. Int J Obes Relat Metab Disord 26, 652–658. 225. Nilsson, J., Jovinge, S., Niemann, A., Reneland, R. and Lithell, H. (1998) Relation between plasma tumor necrosis factor-alpha and insulin sensitivity in elderly men with non-insulin-dependent diabetes mellitus. Arterioscler Thromb Vasc Biol 18, 1199–1202. 226. Chan, J. C., Cheung, J. C., Stehouwer, C. D., Emeis, J. J., Tong, P. C., Ko, G. T. and Yudkin, J. S. (2002) The central roles of obesity-associated dyslipidaemia, endothelial activation and cytokines in the Metabolic Syndrome – an analysis by structural equation modelling. Int J Obes Relat Metab Disord 26, 994–1008. 227. Sewter, C., Berger, D., Considine, R. V., Medina, G., Rochford, J., Ciaraldi, T., Henry, R., Dohm, L., Flier, J. S., O’Rahilly, S. and Vidal-Puig, A. J. (2002) Human obesity and type 2 diabetes are associated with alterations in SREBP1 isoform expression that are reproduced ex vivo by tumor necrosis factor-alpha. Diabetes 51, 1035–1041. 228. Sykiotis, G. P. and Papavassiliou, A. G. (2001) Serine phosphorylation of insulin receptor substrate-1: a novel target for the reversal of insulin resistance. Mol Endocrinol 15, 1864–1869. 229. Day, C. P., Grove, J., Daly, A. K., Stewart, M. W., Avery, P. J. and Walker, M. (1998) Tumour necrosis factor-alpha gene promoter polymorphism and decreased insulin resistance. Diabetologia 41, 430–434. 230. Rasmussen, S. K., Urhammer, S. A., Jensen, J. N., Hansen, T., Borch-Johnsen, K. and Pedersen, O. (2000) The −238 and −308G → A polymorphisms of the tumor necrosis factor alpha gene promoter are not associated with features of the insulin resistance syndrome or altered birth weight in Danish Caucasians. J Clin Endocrinol Metab 85, 1731–1734. 231. da Sliva, B., Gapstur, S. M., Achenbach, Y. H., Schuh, T. S., Kotlar, T. J., Liu, K. and Lowe, W. L., Jr. (2000) Lack of association between the −308 polymorphism of the tumor necrosis factor-alpha gene and the insulin resistance syndrome. J Investig Med 48, 236–244. 232. Lee, S. C., Pu, Y. B., Thomas, G. N., Lee, Z. S., Tomlinson, B., Cockram, C. S., Critchley, J. A. and Chan, J. C. (2000) Tumor necrosis factor alpha gene G − 308A polymorphism in the metabolic syndrome. Metabolism 49, 1021–1024. 233. Romeo, S., Sentinelli, F., Capici, F., Arca, M., Berni, A., Vecci, E., Mario, U. D. and Baroni, M. G. (2001) The G − 308A variant of the Tumor Necrosis Factor-alpha (TNFalpha) gene is not associated with obesity, insulin resistance and body fat distribution. BMC Med Genet 2, 10. 234. Valenti, L., Fracanzani, A. L., Dongiovanni, P., Santorelli, G., Branchi, A., Taioli, E., Fiorelli, G. and Fargion, S. (2002) Tumor necrosis factor alpha promoter polymorphisms and insulin resistance in nonalcoholic fatty liver disease. Gastroenterology 122, 274–280. 235. Furuta, M., Yano, Y., Ito, K., Gabazza, E. C., Katsuki, A., Tanaka, T., Ohtake, K., Hirata, N., Hori, Y., Araki-Sasaki, R., Sumida, Y. and Adachi, Y. (2002) Relationship of the tumor necrosis factor-alpha −308 A/G promoter polymorphism with insulin sensitivity and abdominal fat distribution in Japanese patients with type 2 diabetes mellitus. Diabetes Res Clin Pract 56, 141–145.

444

GENETICS OF THE METABOLIC SYNDROME

236. Fernandez-Real, J. M., Gutierrez, C., Ricart, W., Casamitjana, R., Fernandez-Castaner, M., Vendrell, J., Richart, C. and Soler, J. (1997) The TNF-alpha gene Nco I polymorphism influences the relationship among insulin resistance, percent body fat, and increased serum leptin levels. Diabetes 46, 1468–1472. 237. Herrmann, S. M., Ricard, S., Nicaud, V., Mallet, C., Arveiler, D., Evans, A., Ruidavets, J. B., Luc, G., Bara, L., Parra, H. J., Poirier, O. and Cambien, F. (1998) Polymorphisms of the tumour necrosis factor-alpha gene, coronary heart disease and obesity. Eur J Clin Invest 28, 59–66. 238. Hoffstedt, J., Eriksson, P., Hellstrom, L., Rossner, S., Ryden, M. and Arner, P. (2000) Excessive fat accumulation is associated with the TNF alpha −308 G/A promoter polymorphism in women but not in men. Diabetologia 43, 117–120. 239. Padovani, J. C., Pazin-Filho, A., Simoes, M. V., Marin-Neto, J. A., Zago, M. A. and Franco, R. F. (2000) Gene polymorphisms in the TNF locus and the risk of myocardial infarction. Thromb Res 100, 263–269. 240. Brand, E., Schorr, U., Kunz, I., Kertmen, E., Ringel, J., Distler, A. and Sharma, A. M. (2001) Tumor necrosis factor-alpha −308 G/A polymorphism in obese Caucasians. Int J Obes Relat Metab Disord 25, 581–585. 241. Nicaud, V., Raoux, S., Poirier, O., Cambien, F., O’Reilly, D. S. and Tiret, L. (2002) The TNF alpha/G − 308A polymorphism influences insulin sensitivity in offspring of patients with coronary heart disease: the European Atherosclerosis Research Study II. Atherosclerosis 161, 317–325. 242. Dalziel, B., Gosby, A. K., Richman, R. M., Bryson, J. M. and Caterson, I. D. (2002) Association of the TNF-alpha −308 G/A promoter polymorphism with insulin resistance in obesity. Obes Res 10, 401–407. 243. Norman, R. A., Bogardus, C. and Ravussin, E. (1995) Linkage between obesity and a marker near the tumor necrosis factor-alpha locus in Pima Indians. J Clin Invest 96, 158–162. 244. Kamizono, S., Yamada, K., Seki, N., Higuchi, T., Kimura, A., Nonaka, K. and Itoh, K. (2000) Susceptible locus for obese type 2 diabetes mellitus in the 5
-flanking region of the tumor necrosis factor-alpha gene. Tissue Antigens 55, 449–452. 245. Skoog, T., Eriksson, P., Hoffstedt, J., Ryden, M., Hamsten, A. and Arner, P. (2001) Tumour necrosis factor-alpha (TNF-alpha) polymorphisms −857 C/A and −863 C/A are associated with TNF-alpha secretion from human adipose tissue. Diabetologia 44, 654–655. 246. Rosmond, R. (2002) The glucocorticoid receptor gene and its association to metabolic syndrome. Obes Res 10, 1078–1086. 247. Beato, M., Herrlich, P. and Schutz, G. (1995) Steroid hormone receptors: many actors in search of a plot. Cell 83, 851–857. 248. Beato, M., Chavez, S. and Truss, M. (1996) Transcriptional regulation by steroid hormones. Steroids 61, 240–251. 249. DeRijk, R. H., Schaaf, M. and de Kloet, E. R. (2002) Glucocorticoid receptor variants: clinical implications. J Steroid Biochem Mol Biol 81, 103–122. 250. Bjorntorp, P. and Rosmond, R. (2000) The metabolic syndrome – a neuroendocrine disorder? Br J Nutr 83 (Suppl. 1), S49–57. 251. Ukkola, O., Rosmond, R., Tremblay, A. and Bouchard, C. (2001) Glucocorticoid receptor Bcl I variant is associated with an increased atherogenic profile in response to long-term overfeeding. Atherosclerosis 157, 221–224. 252. Ukkola, O., Perusse, L., Chagnon, Y. C., Despres, J. P. and Bouchard, C. (2001) Interactions among the glucocorticoid receptor, lipoprotein lipase and adrenergic receptor genes and abdominal fat in the Quebec Family Study. Int J Obes Relat Metab Disord 25, 1332–1339.

REFERENCES

445

253. Rosmond, R., Chagnon, Y. C., Holm, G., Chagnon, M., Perusse, L., Lindell, K., Carlsson, B., Bouchard, C. and Bjorntorp, P. (2000) A glucocorticoid receptor gene marker is associated with abdominal obesity, leptin, and dysregulation of the hypothalamic–pituitary–adrenal axis. Obes Res 8, 211–218. 254. Buemann, B., Vohl, M. C., Chagnon, M., Chagnon, Y. C., Gagnon, J., Perusse, L., Dionne, F., Despres, J. P., Tremblay, A., Nadeau, A. and Bouchard, C. (1997) Abdominal visceral fat is associated with a BclI restriction fragment length polymorphism at the glucocorticoid receptor gene locus. Obes Res 5, 186–192. 255. Weaver, J. U., Hitman, G. A. and Kopelman, P. G. (1992) An association between a BclI restriction fragment length polymorphism of the glucocorticoid receptor locus and hyperinsulinaemia in obese women. J Mol Endocrinol 9, 295–300. 256. Rosmond, R., Chagnon, Y. C., Chagnon, M., Perusse, L., Bouchard, C. and Bjorntorp, P. (2000) A polymorphism of the 5
-flanking region of the glucocorticoid receptor gene locus is associated with basal cortisol secretion in men. Metabolism 49, 1197–1199. 257. Huizenga, N. A., Koper, J. W., De Lange, P., Pols, H. A., Stolk, R. P., Burger, H., Grobbee, D. E., Brinkmann, A. O., De Jong, F. H. and Lamberts, S. W. (1998) A polymorphism in the glucocorticoid receptor gene may be associated with an increased sensitivity to glucocorticoids in vivo. J Clin Endocrinol Metab 83, 144–151. 258. Lin, R. C., Wang, W. Y. and Morris, B. J. (1999) Association and linkage analyses of glucocorticoid receptor gene markers in essential hypertension. Hypertension 34, 1186–1192. 259. Rosmond, R., Bouchard, C. and Bjorntorp, P. (2001) Tsp509I polymorphism in exon 2 of the glucocorticoid receptor gene in relation to obesity and cortisol secretion: cohort study. BMJ 322, 652–653. 260. Dobson, M. G., Redfern, C. P., Unwin, N. and Weaver, J. U. (2001) The N363S polymorphism of the glucocorticoid receptor: potential contribution to central obesity in men and lack of association with other risk factors for coronary heart disease and diabetes mellitus. J Clin Endocrinol Metab 86, 2270–2274. 261. Ruiz, M., Lind, U., Gafvels, M., Eggertsen, G., Carlstedt-Duke, J., Nilsson, L., Holtmann, M., Stierna, P., Wikstrom, A. C. and Werner, S. (2001) Characterization of two novel mutations in the glucocorticoid receptor gene in patients with primary cortisol resistance. Clin Endocrinol (Oxf) 55, 363–371. 262. van Rossum, E. F., Koper, J. W., Huizenga, N. A., Uitterlinden, A. G., Janssen, J. A., Brinkmann, A. O., Grobbee, D. E., de Jong, F. H., van Duyn, C. M., Pols, H. A. and Lamberts, S. W. (2002) A polymorphism in the glucocorticoid receptor gene, which decreases sensitivity to glucocorticoids in vivo, is associated with low insulin and cholesterol levels. Diabetes 51, 3128–3134. 263. Ikeda, Y., Suehiro, T., Tsuzura, S., Shiinoki, T., Kaneda, T., Kumon, Y. and Hashimoto, K. (2001) A polymorphism in the promoter region of the glucocorticoid receptor gene is associated with its transcriptional activity. Endocr J 48, 723–726. 264. Schaaf, M. J. and Cidlowski, J. A. (2002) AUUUA motifs in the 3
UTR of human glucocorticoid receptor alpha and beta mRNA destabilize mRNA and decrease receptor protein expression. Steroids 67, 627–636. 265. Bjorntorp, P. and Rosmond, R. (1999) Hypothalamic origin of the metabolic syndrome X. Ann NY Acad Sci 892, 297–307. 266. Bjorntorp, P., Holm, G. and Rosmond, R. (1999) Hypothalamic arousal, insulin resistance and Type 2 diabetes mellitus. Diabet Med 16, 373–383. 267. Hagan, M. M., Rushing, P. A., Schwartz, M. W., Yagaloff, K. A., Burn, P., Woods, S. C. and Seeley, R. J. (1999) Role of the CNS melanocortin system in the response to overfeeding. J Neurosci 19, 2362–2367.

446

GENETICS OF THE METABOLIC SYNDROME

268. Marks, D. L. and Cone, R. D. (2001) Central melanocortins and the regulation of weight during acute and chronic disease. Recent Prog Horm Res 56, 359–375. 269. Butler, A. A., Kesterson, R. A., Khong, K., Cullen, M. J., Pelleymounter, M. A., Dekoning, J., Baetscher, M. and Cone, R. D. (2000) A unique metabolic syndrome causes obesity in the melanocortin-3 receptor-deficient mouse. Endocrinology 141, 3518–3521. 270. Kim, K. S., Larsen, N., Short, T., Plastow, G. and Rothschild, M. F. (2000) A missense variant of the porcine melanocortin-4 receptor (MC4R) gene is associated with fatness, growth, and feed intake traits. Mamm Genome 11, 131–135. 271. Yeo, G. S., Farooqi, I. S., Aminian, S., Halsall, D. J., Stanhope, R. G. and O’Rahilly, S. (1998) A frameshift mutation in MC4R associated with dominantly inherited human obesity. Nat Genet 20, 111–112. 272. Vaisse, C., Clement, K., Guy-Grand, B. and Froguel, P. (1998) A frameshift mutation in human MC4R is associated with a dominant form of obesity. Nat Genet 20, 113–114. 273. Yeo, G. S., Farooqi, I. S., Challis, B. G., Jackson, R. S. and O’Rahilly, S. (2000) The role of melanocortin signalling in the control of body weight: evidence from human and murine genetic models. QJM 93, 7–14. 274. Vaisse, C., Clement, K., Durand, E., Hercberg, S., Guy-Grand, B. and Froguel, P. (2000) Melanocortin-4 receptor mutations are a frequent and heterogeneous cause of morbid obesity. J Clin Invest 106, 253–262. 275. Ho, G. and MacKenzie, R. G. (1999) Functional characterization of mutations in melanocortin-4 receptor associated with human obesity. J Biol Chem 274, 35 816–35 822. 276. Schwartz, M. W., Woods, S. C., Porte, D., Jr., Seeley, R. J. and Baskin, D. G. (2000) Central nervous system control of food intake. Nature 404, 661–671. 277. Rossi, M., Kim, M. S., Morgan, D. G., Small, C. J., Edwards, C. M., Sunter, D., Abusnana, S., Goldstone, A. P., Russell, S. H., Stanley, S. A., Smith, D. M., Yagaloff, K., Ghatei, M. A. and Bloom, S. R. (1998) A C-terminal fragment of Agouti-related protein increases feeding and antagonizes the effect of alpha-melanocyte stimulating hormone in vivo. Endocrinology 139, 4428–4431. 278. Hagan, M. M., Rushing, P. A., Pritchard, L. M., Schwartz, M. W., Strack, A. M., Van Der Ploeg, L. H., Woods, S. C. and Seeley, R. J. (2000) Long-term orexigenic effects of AgRP-(83–132) involve mechanisms other than melanocortin receptor blockade. Am J Physiol Regul Integr Comp Physiol 279, R47–52. 279. Rosenfeld, R. D., Zeni, L., Welcher, A. A., Narhi, L. O., Hale, C., Marasco, J., Delaney, J., Gleason, T., Philo, J. S., Katta, V., Hui, J., Baumgartner, J., Graham, M., Stark, K. L. and Karbon, W. (1998) Biochemical, biophysical, and pharmacological characterization of bacterially expressed human agouti-related protein. Biochemistry 37, 16 041–16 052. 280. Graham, M., Shutter, J. R., Sarmiento, U., Sarosi, I. and Stark, K. L. (1997) Overexpression of Agrt leads to obesity in transgenic mice. Nat Genet 17, 273–274. 281. Mayfield, D. K., Brown, A. M., Page, G. P., Garvey, W. T., Shriver, M. D. and Argyropoulos, G. (2001) A role for the agouti related protein promoter in obesity and type 2 diabetes. Biochem Biophys Res Commun 287, 568–573. 282. Katsuki, A., Sumida, Y., Gabazza, E. C., Murashima, S., Tanaka, T., Furuta, M., Araki-Sasaki, R., Hori, Y., Nakatani, K., Yano, Y. and Adachi, Y. (2001) Plasma levels of agouti-related protein are increased in obese men. J Clin Endocrinol Metab 86, 1921–1924. 283. Shen, C. P., Wu, K. K., Shearman, L. P., Camacho, R., Tota, M. R., Fong, T. M. and Van Der Ploeg, L. H. (2002) Plasma agouti-related protein level: a possible correlation with fasted and fed states in humans and rats. J Neuroendocrinol 14, 607–610.

REFERENCES

447

284. Argyropoulos, G., Rankinen, T., Bai, F., Rice, T., Province, M., Leon, A., Skinner, J., Wilmore, J., Rao, D. and Bouchard, B. (2003) The agouti related protein promoter and body fatness in humans. Int J Obes Relat Metab Disord 27, 276–280. 285. Argyropoulos, G., Rankinen, T., Neufeld, D. R., Rice, T., Province, M. A., Leon, A. S., Skinner, J. S., Wilmore, J. H., Rao, D. C. and Bouchard, C. (2002) A polymorphism in the human agouti-related protein is associated with late-onset obesity. J Clin Endocrinol Metab 87, 4198–4202. 286. Vink, T., Hinney, A., van Elburg, A. A., van Goozen, S. H., Sandkuijl, L. A., Sinke, R. J., Herpertz-Dahlmann, B. M., Hebebrand, J., Remschmidt, H., van Engeland, H. and Adan, R. A. (2001) Association between an agouti-related protein gene polymorphism and anorexia nervosa. Mol Psychiatry 6, 325–328. 287. Raposinho, P. D., Pierroz, D. D., Broqua, P., White, R. B., Pedrazzini, T. and Aubert, M. L. (2001) Chronic administration of neuropeptide Y into the lateral ventricle of C57BL/6J male mice produces an obesity syndrome including hyperphagia, hyperleptinemia, insulin resistance, and hypogonadism. Mol Cell Endocrinol 185, 195–204. 288. Halford, J. C. (2001) Pharmacology of appetite suppression: implication for the treatment of obesity. Curr Drug Targets 2, 353–370. 289. Erickson, J. C., Hollopeter, G. and Palmiter, R. D. (1996) Attenuation of the obesity syndrome of ob/ob mice by the loss of neuropeptide Y. Science 274, 1704–1707. 290. Naveilhan, P., Canals, J. M., Arenas, E. and Ernfors, P. (2001) Distinct roles of the Y1 and Y2 receptors on neuropeptide Y-induced sensitization to sedation. J Neurochem 78, 1201–1207. 291. Chamorro, S., Della-Zuana, O., Fauchere, J. L., Feletou, M., Galizzi, J. P. and Levens, N. (2002) Appetite suppression based on selective inhibition of NPY receptors. Int J Obes Relat Metab Disord 26, 281–298. 292. Sainsbury, A., Schwarzer, C., Couzens, M., Fetissov, S., Furtinger, S., Jenkins, A., Cox, H. M., Sperk, G., Hokfelt, T. and Herzog, H. (2002) Important role of hypothalamic Y2 receptors in body weight regulation revealed in conditional knockout mice. Proc Natl Acad Sci USA 99, 8938–8943. 293. Kallio, J., Pesonen, U., Kaipio, K., Karvonen, M. K., Jaakkola, U., Heinonen, O. J., Uusitupa, M. I. and Koulu, M. (2001) Altered intracellular processing and release of neuropeptide Y due to leucine 7 to proline 7 polymorphism in the signal peptide of preproneuropeptide Y in humans. FASEB J 15, 1242–1244. 294. Niskanen, L., Voutilainen-Kaunisto, R., Terasvirta, M., Karvonen, M. K., Valve, R., Pesonen, U., Laakso, M., Uusitupa, M. I. and Koulu, M. (2000) Leucine 7 to proline 7 polymorphism in the neuropeptide y gene is associated with retinopathy in type 2 diabetes. Exp Clin Endocrinol Diabetes 108, 235–236. 295. Karvonen, M. K., Valkonen, V. P., Lakka, T. A., Salonen, R., Koulu, M., Pesonen, U., Tuomainen, T. P., Kauhanen, J., Nyyssonen, K., Lakka, H. M., Uusitupa, M. I. and Salonen, J. T. (2001) Leucine7 to proline7 polymorphism in the preproneuropeptide Y is associated with the progression of carotid atherosclerosis, blood pressure and serum lipids in Finnish men. Atherosclerosis 159, 145–151. 296. Erkkila, A. T., Lindi, V., Lehto, S., Laakso, M. and Uusitupa, M. I. (2002) Association of leucine 7 to proline 7 polymorphism in the preproneuropeptide Y with serum lipids in patients with coronary heart disease. Mol Genet Metab 75, 260–264. 297. Kauhanen, J., Karvonen, M. K., Pesonen, U., Koulu, M., Tuomainen, T. P., Uusitupa, M. I. and Salonen, J. T. (2000) Neuropeptide Y polymorphism and alcohol consumption in middle-aged men. Am J Med Genet 93, 117–121. 298. Lappalainen, J., Kranzler, H. R., Malison, R., Price, L. H., Van Dyck, C., Rosenheck, R. A., Cramer, J., Southwick, S., Charney, D., Krystal, J. and Gelernter, J. (2002)

448

299. 300. 301.

302.

303.

304.

305. 306.

307.

308.

309. 310.

311.

312.

313.

314.

GENETICS OF THE METABOLIC SYNDROME

A functional neuropeptide Y Leu7Pro polymorphism associated with alcohol dependence in a large population sample from the United States. Arch Gen Psychiatry 59, 825–831. Jequier, E. (2002) Leptin signaling, adiposity, and energy balance. Ann NY Acad Sci 967, 379–388. Elmquist, J. K. (2001) Hypothalamic pathways underlying the endocrine, autonomic, and behavioral effects of leptin. Physiol Behav 74, 703–708. Ludvigsen, S., Thim, L., Blom, A. M. and Wulff, B. S. (2001) Solution structure of the satiety factor, CART, reveals new functionality of a well-known fold. Biochemistry 40, 9082–9088. Yermolaieva, O., Chen, J., Couceyro, P. R. and Hoshi, T. (2001) Cocaine- and amphetamine-regulated transcript peptide modulation of voltage-gated Ca2+ signaling in hippocampal neurons. J Neurosci 21, 7474–7480. Elias, C. F., Lee, C. E., Kelly, J. F., Ahima, R. S., Kuhar, M., Saper, C. B. and Elmquist, J. K. (2001) Characterization of CART neurons in the rat and human hypothalamus. J Comp Neurol 432, 1–19. Elias, C. F., Lee, C., Kelly, J., Aschkenasi, C., Ahima, R. S., Couceyro, P. R., Kuhar, M. J., Saper, C. B. and Elmquist, J. K. (1998) Leptin activates hypothalamic CART neurons projecting to the spinal cord. Neuron 21, 1375–1385. Dhillo, W. S. and Bloom, S. R. (2001) Hypothalamic peptides as drug targets for obesity. Curr Opin Pharmacol 1, 651–655. Yamada, K., Yuan, X., Otabe, S., Koyanagi, A., Koyama, W. and Makita, Z. (2002) Sequencing of the putative promoter region of the cocaine- and amphetamine-regulatedtranscript gene and identification of polymorphic sites associated with obesity. Int J Obes Relat Metab Disord 26, 132–136. Challis, B. G., Yeo, G. S., Farooqi, I. S., Luan, J., Aminian, S., Halsall, D. J., Keogh, J. M., Wareham, N. J. and O’Rahilly, S. (2000) The CART gene and human obesity: mutational analysis and population genetics. Diabetes 49, 872–875. Cowley, M. A., Smart, J. L., Rubinstein, M., Cerdan, M. G., Diano, S., Horvath, T. L., Cone, R. D. and Low, M. J. (2001) Leptin activates anorexigenic POMC neurons through a neural network in the arcuate nucleus. Nature 411, 480–484. Butler, A. A. and Cone, R. D. (2001) Knockout models resulting in the development of obesity. Trends Genet 17, S50–54. Yaswen, L., Diehl, N., Brennan, M. B. and Hochgeschwender, U. (1999) Obesity in the mouse model of pro-opiomelanocortin deficiency responds to peripheral melanocortin. Nat Med 5, 1066–1070. Challis, B. G., Pritchard, L. E., Creemers, J. W., Delplanque, J., Keogh, J. M., Luan, J., Wareham, N. J., Yeo, G. S., Bhattacharyya, S., Froguel, P., White, A., Farooqi, I. S. and O’Rahilly, S. (2002) A missense mutation disrupting a dibasic prohormone processing site in pro-opiomelanocortin (POMC) increases susceptibility to early-onset obesity through a novel molecular mechanism. Hum Mol Genet 11, 1997–2004. Comuzzie, A. G., Hixson, J. E., Almasy, L., Mitchell, B. D., Mahaney, M. C., Dyer, T. D., Stern, M. P., MacCluer, J. W. and Blangero, J. (1997) A major quantitative trait locus determining serum leptin levels and fat mass is located on human chromosome 2. Nat Genet 15, 273–276. Rutkowski, M. P., Klanke, C. A., Su, Y. R., Reif, M. and Menon, A. G. (1998) Genetic markers at the leptin (OB) locus are not significantly linked to hypertension in African Americans. Hypertension 31, 1230–1234. Kissebah, A. H., Sonnenberg, G. E., Myklebust, J., Goldstein, M., Broman, K., James, R. G., Marks, J. A., Krakower, G. R., Jacob, H. J., Weber, J., Martin, L.,

REFERENCES

315.

316.

317.

318. 319.

320.

321. 322.

323.

324.

325.

326.

449

Blangero, J. and Comuzzie, A. G. (2000) Quantitative trait loci on chromosomes 3 and 17 influence phenotypes of the metabolic syndrome. Proc Natl Acad Sci USA 97, 14 478–14 483. Edwards, K. L., Talmud, P. J., Newman, B., Krauss, R. M. and Austin, M. A. (2001) Lipoprotein candidate genes for multivariate factors of the insulin resistance syndrome: a sib-pair linkage analysis in women twins. Twin Res 4, 41–47. Francke, S., Manraj, M., Lacquemant, C., Lecoeur, C., Lepretre, F., Passa, P., Hebe, A., Corset, L., Yan, S. L., Lahmidi, S., Jankee, S., Gunness, T. K., Ramjuttun, U. S., Balgobin, V., Dina, C. and Froguel, P. (2001) A genome-wide scan for coronary heart disease suggests in Indo-Mauritians a susceptibility locus on chromosome 16p13 and replicates linkage with the metabolic syndrome on 3q27. Hum Mol Genet 10, 2751–2765. Speckman, R. A., Garg, A., Du, F., Bennett, L., Veile, R., Arioglu, E., Taylor, S. I., Lovett, M. and Bowcock, A. M. (2000) Mutational and haplotype analyses of families with familial partial lipodystrophy (Dunnigan variety) reveal recurrent missense mutations in the globular C-terminal domain of lamin A/C. Am J Hum Genet 66, 1192–1198. Genschel, J. and Schmidt, H. H. (2000) Mutations in the LMNA gene encoding lamin A/C. Hum Mutat 16, 451–459. Cao, H. and Hegele, R. A. (2000) Nuclear lamin A/C R482Q mutation in Canadian kindreds with Dunnigan-type familial partial lipodystrophy. Hum Mol Genet 9, 109–112. Lloyd, D. J., Trembath, R. C. and Shackleton, S. (2002) A novel interaction between lamin A and SREBP1: implications for partial lipodystrophy and other laminopathies. Hum Mol Genet 11, 769–777. Dhe-Paganon, S., Werner, E. D., Chi, Y. I. and Shoelson, S. E. (2002) Structure of the globular tail of nuclear lamin. J Biol Chem 277, 17 381–17 384. Magre, J., Delepine, M., Khallouf, E., Gedde-Dahl, T., Jr., Van Maldergem, L., Sobel, E., Papp, J., Meier, M., Megarbane, A., Bachy, A., Verloes, A., d’Abronzo, F. H., Seemanova, E., Assan, R., Baudic, N., Bourut, C., Czernichow, P., Huet, F., Grigorescu, F., de Kerdanet, M., Lacombe, D., Labrune, P., Lanza, M., Loret, H., Matsuda, F., Navarro, J., Nivelon-Chevalier, A., Polak, M., Robert, J. J., Tric, P., Tubiana-Rufi, N., Vigouroux, C., Weissenbach, J., Savasta, S., Maassen, J. A., Trygstad, O., Bogalho, P., Freitas, P., Medina, J. L., Bonnicci, F., Joffe, B. I., Loyson, G., Panz, V. R., Raal, F. J., O’Rahilly, S., Stephenson, T., Kahn, C. R., Lathrop, M. and Capeau, J. (2001) Identification of the gene altered in Berardinelli–Seip congenital lipodystrophy on chromosome 11q13. Nat Genet 28, 365–370. Agarwal, A. K., Arioglu, E., De Almeida, S., Akkoc, N., Taylor, S. I., Bowcock, A. M., Barnes, R. I. and Garg, A. (2002) AGPAT2 is mutated in congenital generalized lipodystrophy linked to chromosome 9q34. Nat Genet 31, 21–23. Pages, C., Daviaud, D., An, S., Krief, S., Lafontan, M., Valet, P. and SaulnierBlache, J. S. (2001) Endothelial differentiation gene-2 receptor is involved in lysophosphatidic acid-dependent control of 3T3F442A preadipocyte proliferation and spreading. J Biol Chem 276, 11 599–11 605. Carr, A., Samaras, K., Thorisdottir, A., Kaufmann, G. R., Chisholm, D. J. and Cooper, D. A. (1999) Diagnosis, prediction, and natural course of HIV-1 proteaseinhibitor-associated lipodystrophy, hyperlipidaemia, and diabetes mellitus: a cohort study [see comments]. Lancet 353, 2093–2099. Mynarcik, D. C., McNurlan, M. A., Steigbigel, R. T., Fuhrer, J. and Gelato, M. C. (2000) Association of severe insulin resistance with both loss of limb fat and elevated

450

GENETICS OF THE METABOLIC SYNDROME

serum tumor necrosis factor receptor levels in HIV lipodystrophy [in process citation]. J Acquir Immune Defic Syndr 25, 312–321. 327. Mendonca, B. B., Leite, M. V., de Castro, M., Kino, T., Elias, L. L., Bachega, T. A., Arnhold, I. J., Chrousos, G. P. and Latronico, A. C. (2002) Female pseudohermaphroditism caused by a novel homozygous missense mutation of the GR gene. J Clin Endocrinol Metab 87, 1805–1809.

14 Insulin Resistance and Dyslipidaemia Benoˆıt Lamarche and Jean-Fran¸cois Mauger

14.1 Introduction The rising epidemic of obesity in industrialized countries has forced scientists and clinicians as well as public health instances to intensify their research efforts to achieve a more in-depth understanding of the grounds underlying this undesirable trend. Among other findings, it is being increasingly acknowledged that obesity, particularly abdominal obesity, and insulin resistance share common disturbances that are unequivocally associated with an elevated risk of cardiovascular disease. As indicated in this brief overview, abdominal obesity and insulin resistance are common grounds for a typical atherogenic dyslipidaemia that includes increased plasma triglyceride (triglyceride) levels as well as reduced high density lipoprotein (HDL) cholesterol concentrations. The presence of smaller, denser low density lipoprotein (LDL) particles is also frequently observed in insulin-resistant and abdominally obese subjects, despite the fact that many of these individuals will display relatively normal LDL cholesterol levels. This chapter will describe some of the mechanisms that underlie the appearance of these typical dyslipidaemic features in insulin resistance states. The evidence that hypertriglyceridaemia plays a key role in these processes will also be reviewed. Finally, the risk of cardiovascular disease associated with this dyslipidaemia will also be briefly discussed.

14.2

Historical notes

It was in 1988, at the Banting Lecture of the American Diabetes Association Annual Meeting, that Dr. Gerald Reaven first proposed the concept that Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

452

INSULIN RESISTANCE AND DYSLIPIDAEMIA

insulin resistance and compensatory hyperinsulinaemia were the cornerstone of a plurimetabolic syndrome that included hypertriglyceridaemia, reduced plasma HDL cholesterol levels, essential hypertension and some degree of glucose intolerance.1 This concept, which was first referred to as syndrome X, implied that the insulin resistance syndrome might be associated with significant elevation in the risk of cardiovascular disease, although there were no data at that time to support this thesis. It was also suggested that a significant proportion of non-diabetic individuals in the general population, perhaps as many as 25 per cent, might display some features of the syndrome,1 but again data had yet to be provided to support this hypothesis. Since 1988, the syndrome has been the topic of intense research leading to major advances in our understanding of its molecular basis, clinical characteristics and associated cardiovascular risk. As a result, the National Cholesterol Education Panel (NCEP) has recently recognized the importance of insulin resistance in furthering the risk of cardiovascular disease and the Adult Treatment Panel III (ATP-III) has followed by providing a clinical definition of the insulin resistance syndrome, which they defined as the ‘metabolic syndrome’.2 Studies have also shown that approximately 25 per cent of the adult American population may be characterized as having the metabolic syndrome as defined by NCEP-APT III.3 The determination of the most appropriate term to designate the metabolic syndrome remains a matter of intense debate and it is beyond the scope of this brief chapter to address this issue. Nevertheless, and as shown in Figure 14.1, one has to recognize that the interest from the research community in investigating various aspects of the ‘insulin resistance syndrome’, ‘metabolic syndrome’ or ‘syndrome X’ has exploded over

Number of yearly appearances

400

Metabolic syndrome

350

Syndrome X

300

Insulin resistance syndrome

250 200 150 100 50 0 1988

1990

1992

1994

1996

1998

2000

2002

Publication year

Figure 14.1 Interest in the insulin resistance syndrome in the scientific community, as depicted by the number of yearly appearances of the terminologies ‘insulin resistance syndrome’, ‘syndrome X’ and ‘metabolic syndrome’ in any part of any scientific publications between 1988 and 2002. This is an informal analysis of all publications found in PubMed (http://www.ncbi.nlm.nih.gov) during that period

HYPERTRIGLYCERIDAEMIA

453

the last few years. Interestingly, the terminology ‘metabolic syndrome’ to define and designate this complex array of metabolic and physiological abnormalities appears to have become more popular since the NCEP-ATP III report recognized the syndrome as an important clinical entity. For the purpose of the present review, the insulin resistance syndrome and metabolic syndrome terminologies will be used interchangeably and will reflect the same concept.

14.3

Obesity versus the insulin resistance syndrome

Whether obesity precedes the onset of insulin resistance, whether obesity is simply an innocent bystander in the series of abnormalities associated with insulin resistance states or whether it is actually the insulin resistance state that favours the accumulation of body fat remains a controversial issue as all of these hypotheses have been supported to some degree by scientific evidence.4 – 6 It is beyond the scope of this chapter to add to this debate. However, while it is recognized that obese individuals do not necessarily all show signs of insulin resistance, and that insulin-resistant individuals are not necessarily all obese, it is generally agreed that obesity, particularly abdominal obesity, and insulin resistance are most frequently related and that they share most of the metabolic disturbances associated with one or the other.7, 8 Consequently, when reviewing the mechanisms underlying the typical dyslipidaemia of the insulin resistance syndrome, one may plead that similar mechanisms will relate this dyslipidaemia to abdominal obesity. In that context, data that have related lipoprotein physiology and kinetics to insulin resistance states or to obesity essentially provide interchangeable information. This explains why we have chosen to present and review physiological mechanisms that were derived from models either based on abdominal obesity or on insulin resistance states.

14.4

Hypertriglyceridaemia

Elevated plasma triglyceride concentrations have been identified as one of the primary components of the insulin resistance syndrome proposed by Reaven in the late 1980s.1 Subsequent research on mechanistic pathways relating plasma triglyceride levels to insulin resistance has demonstrated that moderate hypertriglyceridaemia should definitely be considered as one of the key components of the metabolic syndrome.9 Triglycerides in blood circulation are primarily transported by two main subclasses of lipoproteins, chylomicrons and chylomicron remnants in the fed state, and very low density lipoproteins (VLDLs) in the fasted state. The concept that plasma triglyceride levels should be considered as an important risk factor for cardiovascular disease has been a topic of an interesting debate over the last two decades.10 – 12 Thus, for many years, scientists had recognized elevated

454

INSULIN RESISTANCE AND DYSLIPIDAEMIA

plasma triglyceride concentrations as a risk factor for cardiovascular disease in univariate analyses but not multivariate analyses, particularly when the contribution of the strongly correlated plasma HDL cholesterol levels to cardiovascular disease risk was taken into account.13 However, the publication in 1996 of a powerful meta-analysis of 17 prospective studies comprising approximately 50 000 males and 10 000 females revived this debate by showing that every 1 mmol/l increase in plasma triglyceride levels was associated with a 14 per cent increase in the risk of cardiovascular disease in men and 37 per cent increase in women even after adjustment for plasma HDL cholesterol levels.14 Since then, other studies have contributed to support the concept that marginally elevated plasma triglyceride levels should be considered as a key component of the cardiovascular risk associated with the insulin resistance syndrome.15, 16 The definition of the metabolic syndrome by NCEP ATP-III, which includes the presence of moderate hypertriglyceridaemia, will also contribute to the renewed interest in plasma triglyceride levels, in addition to LDL cholesterol concentrations, as part of the clinical routine to identify individuals at high risk for cardiovascular disease. Beyond these clinical considerations, there is evidence to support the thesis that insulin resistance and obesity both contribute to a disturbed metabolism of triglyceride-rich lipoproteins17 (Table 14.1). It has been shown that the LDL receptor and the LDL-receptor-related proteins (LRPs) play a key role in the removal of chylomicron remnants from the circulation.18 There are data suggesting that the LDL receptor activity is suppressed in insulin-resistant individuals, thereby contributing to a delayed clearance of chylomicrons and their remnants.19 Using a novel test that estimates chylomicron remnant metabolism based on the injection of a labelled remnant-like emulsion and on measurement Table 14.1 Lipid abnormalities associated with insulin resistance states and potential mechanisms underlying these associations Abnormality Moderate hypertriglyceridaemia Fasting state (↑ VLDL and VLDL remnants) Fed state (↑ chylomicrons and chylomicron remnants) Reduced HDL cholesterol Reduced LDL particle size Moderately increased particle number (hyperapoB) Relatively normal LDL cholesterol concentrations HyperTG: hypertriglyceridaemia.

Main underlying causes Reduced catabolism, increased production Reduced catabolism, increased production (?) Moderate hyperTG in synergy with increased intravascular lipase activities Moderate hyperTG in synergy with increased intravascular lipase activities Increased production and reduced catabolism of apolipoprotein B-containing lipoproteins –

REDUCED HDL CHOLESTEROL CONCENTRATIONS

455

of C13 O2 in the breath,20 Chan et al. have shown that obesity and insulin resistance are associated with increased plasma concentrations of remnant-likeparticle cholesterol and apoB-48 mainly due to a decreased catabolism of these particles.21 However, it remains possible that the increased concentration of chylomicron remnants in insulin-resistant individuals may be attributable to an increased secretion of apoB-48-containing lipoproteins.17 VLDL metabolism has also been shown to be perturbed in insulin-resistant states and visceral obesity. First, obese and insulin-resistant individuals have been shown to have a reduced intravascular LPL activity, thus contributing to a delayed clearance of triglyceride rich lipoproteins, including VLDL.22 Insulin resistance and visceral obesity have both been associated with an increased portal flux of free fatty acids, thus stimulating synthesis of cholesteryl esters and triglycerides, thereby contributing to an increased hepatic output of VLDL.23 Insulin is also known to have direct inhibitory effects on apoB secretion by hepatocytes.24 It is therefore reasonable to expect that insulin resistance will be associated with a reduced inhibitory effect of insulin on the secretion of VLDL apoB. The increased output of apoB-containing lipoproteins from the gut in the fed state and from the liver in the fasted state, together with a reduced catabolism of triglyceride rich lipoproteins due to the lowered LPL activity, is therefore most likely to represent the key mechanisms underlying the hypertriglyceridaemic state associated with insulin resistance and abdominal obesity. In summary, high plasma triglyceride levels have been almost systematically associated with insulin resistance states, and there is accumulating evidence linking increased plasma triglyceride concentrations and insulin resistance mechanistically. As indicated in the following sections, it is believed that the hypertriglyceridaemic state associated with insulin resistance may in turn be a key determinant of the other dyslipidaemias that are typical of the metabolic syndrome.

14.5

Reduced HDL cholesterol concentrations

It had been known for a number of years that increased plasma triglyceride levels and reduced HDL cholesterol concentrations were strongly and inversely interrelated.25 It was therefore not surprising that reduced plasma HDL cholesterol concentrations were identified as one of the primary components of the metabolic syndrome by Reaven in 1988, along with hypertriglyceridaemia.1 Early studies by Schaefer et al.26 had indicated that plasma apoA-I residence time (apoA-I being the protein moiety of HDL) was inversely correlated with plasma triglyceride concentrations. Subsequent studies indicated that individuals with elevated plasma triglyceride levels and reduced HDL cholesterol concentrations had increased apoA-I fractional catabolic rate (FCR) compared with individuals with normal triglyceride and HDL cholesterol levels.27 On the other hand, the FCR of apoA-I measured in a subgroup of subjects with low HDL

456

INSULIN RESISTANCE AND DYSLIPIDAEMIA

cholesterol levels, but with normal triglyceride concentrations, was not different from that observed in controls.27 Subsequent studies indicated that abdominal obesity, insulin resistance, post-heparin plasma lipase activity and plasma triglyceride concentrations were key determinants of HDL particle size, which in turn was the primary determinant of apoA-I FCR.28 The kinetics of HDL apoA-I have also been investigated more recently in insulin-resistant and diabetic patients. Generally, studies have shown that the reduced HDL cholesterol and apoA-I levels in insulin-resistant subjects or patients with type 2 diabetes were primarily due to an increased apoA-I catabolism and not to a reduced production rate compared with normal subjects.29 – 31 Based on these observations, it has been postulated that variation in plasma triglyceride concentrations is an important determinant of the metabolic fate of HDL.32 However, the extent to which interrelated factors such as HDL particle size and intravascular lipolytic activity contributed to this process had to be determined. Recent research from our group as well as from others has provided further insights into our understanding of the dynamic interactions between triglyceride rich lipoproteins and HDL in vivo.32 Reduced plasma HDL cholesterol concentrations are recognized as a very potent risk factor for cardiovascular disease,33 – 36 thus suggesting that HDL may have cardioprotective properties. Several mechanisms have been suggested to explain the cardioprotection that has been associated with increased plasma HDL cholesterol levels. One of these hypotheses pertains to the role of HDL in the process referred to as the reverse cholesterol transport,37 – 39 according to which an increased concentration of HDL in the intravascular compartment promotes the net movement of cholesterol from extrahepatic tissues to the liver. This process ultimately contributes to a lessened accumulation of cholesterol in peripheral tissues, thereby slowing down the atherosclerotic process.40 The concept of the reverse cholesterol transport involves a number of cellular as well as intravascular enzymes. One of these enzymes, the cholesteryl ester transfer protein (CETP), promotes the hetero-exchange of triglycerides and cholesterol between triglyceride rich lipoproteins and HDL.41, 42 Because it relays cholesterol from HDL to apoB-containing lipoproteins, which are subsequently taken up by the liver, CETP is considered as a key factor contributing to the reverse cholesterol transport pathway, i.e. the trafficking of cholesterol from peripheral tissues back to the liver.37, 43 Although there is no evidence to suggest that CETP activity may be increased in the insulin-resistant state,44 there is data supporting the concept that the CETP-mediated process is largely dependent upon the concentration of substrates to which it is exposed.45 Thus, in the hypertriglyceridaemic state, HDLs become more susceptible to being enriched with triglycerides through an accelerated transfer process.32, 46 It is believed that one of the key elements responsible for the lowering of HDL in the hypertriglyceridaemic/insulin resistance state is the enrichment of HDL with triglycerides.

SMALL, DENSE LDL PARTICLES

457

One of the most convincing studies that support this hypothesis in humans was undertaken by our group to investigate the impact of triglyceride enrichment of HDL per se on the metabolic clearance of the particle in normal individuals.47 We have shown that HDLs endogenously enriched with triglycerides were cleared approximately 25 per cent faster than normal, triglyceride poor HDLs.47 Recent data from experiments undertaken in rabbits by Rashid et al.48 has suggested that triglyceride enrichment of HDL results in an enhanced HDL clearance only when lipolytically active hepatic lipase is expressed in vivo, demonstrating the important interaction between HDL triglyceride enrichment and hepatic lipase activity in the pathogenesis of HDL lowering in hypertriglyceridemic states.49 – 52 The contribution of hepatic lipase in this process is an important aspect since it has been shown that subjects with visceral obesity are more likely to have increased intravascular hepatic lipase activity.53 In summary, it is obvious that the hypertriglyceridaemic state associated with insulin resistance plays a key role in the modulation of HDL cholesterol levels in individuals with the metabolic syndrome. Other factors such as variation in adenosine triphosphate-binding cassette protein A1 (ABC A-I) activity, a key element in the pathway through which HDL ‘scavenges’ cholesterol from peripheral cells,54 or variation in the newly discovered endothelial lipase,55 – 57 may also contribute to the reduced HDL cholesterol concentrations frequently associated with insulin resistance. Further research will need to be undertaken to investigate these possibilities. Nevertheless, it is postulated that hypertriglyceridaemia, even at moderate levels, is the key determinant of the HDL levels observed in insulin-resistant individuals.

14.6

Small, dense LDL particles

It is now well accepted that LDL particles are heterogeneous in size, density and composition.58, 59 There is now a wealth of data supporting the concept that small dense LDL particles are associated with increased risk of cardiovascular disease.60 – 62 Interestingly, the small dense LDL phenotype has also been recognized as one of the typical features associated with the insulin resistance syndrome.5 Indeed, it has been shown that individuals with evidence of insulin resistance as measured by the hyperinsulinaemic–euglycaemic clamp have smaller and denser LDL particles compared with insulin-sensitive individuals.63 There is also evidence indicating that non-diabetic individuals who accumulate several features of the insulin resistance syndrome are more likely to be characterized as having small, dense LDL particles.60 Although it is recognized that a proportion of individuals with small dense LDL particles may not present with other features of the insulin resistance syndrome, it is postulated that the majority of individuals with small, dense LDL particles are more likely to display other features of the syndrome concurrently. The mechanisms linking the small dense LDL phenotype to insulin resistance are very similar to those relating reduced HDL cholesterol levels to insulin

458

INSULIN RESISTANCE AND DYSLIPIDAEMIA

Proportion of LDL <255 Å (%)

120

R = 0.42 P < 0.001 N = 2072

100 80 60 40 20 0 0

1

2 3 Plasma TG levels (mmol/l)

4

5

Figure 14.2 Correlation between plasma triglyceride concentrations and the proportion of ˚ in a sample of 2072 men without cardiovassmall dense LDL particles (LDL size <255 A) cular disease from the Quebec Cardiovascular Study (unpublished data)

resistance states. Indeed, the presence of moderate hypertriglyceridaemia appears as one of the primary factors responsible for the reduction in LDL particle size and the concomitant increase in LDL density among the general population.64, 65 This is best exemplified in Figure 14.2, which depicts the relationship between plasma triglyceride levels and the proportion of small LDL particles in a sample of approximately 2000 men from the Quebec Cardiovascular Study. Thus, hypertriglyceridaemia will increase the propensity of LDL to become enriched with triglyceride through the CETP pathway, and the hydrolysis of those triglycerideenriched LDL particles is likely to yield smaller and denser LDL particles.60 Hepatic lipase and perhaps other lipases such as endothelial lipase are likely to be involved in this process. However, human models of hepatic lipase deficiency have indicated that even in the presence of massive triglyceride enrichment LDL remained large and buoyant, suggesting that triglyceride enrichment may be only a contributing factor leading to the small dense LDL phenotype.66 Further evidence supporting the close inter-relationship between plasma triglyceride levels and the LDL particle size phenotype include dietary and pharmacological interventions, which have shown that any intervention known to have an impact on plasma triglyceride levels is also most likely to modulate the LDL particle size phenotype.60 It has been postulated that the secretion of large triglyceride rich VLDL (VLDL1 ) as opposed to smaller VLDL (VLDL2 ), as is frequently observed in hypertriglyceridaemic states, may represent one of the key mechanisms promoting the accumulation of small dense LDL particles in insulin-resistant individuals.67 In summary, evidence was provided to support the concept that the hypertriglyceridaemic state most frequently associated with insulin resistance and abdominal obesity may be considered as one of the key elements responsible for other typical dyslipidaemic features associated with the insulin resistance

LDL CHOLESTEROL LEVELS VERSUS LDL PARTICLE NUMBER

459

syndrome. Obviously, other factors such as gene variants in key regulating enzymes, diet, physical activity and smoking may modulate these associations. However, it is postulated that moderate hypertriglyceridaemia may be the primary requirement in the general population to induce further changes in other characteristics of the lipid profile, including HDL and LDL particles.

14.7

LDL cholesterol levels versus LDL particle number

Insulin resistance and abdominal obesity have not been systematically associated with increased plasma LDL cholesterol levels,61, 68 a strong risk factor for cardiovascular disease and the primary target for therapy in primary and secondary prevention. This has led many scientists to suggest that insulin resistance was a clinical feature of the metabolic syndrome mostly related to VLDL and HDL rather than to LDL. However, and as indicated in the previous paragraphs, insulin resistance and abdominal obesity are strongly related to the preferential accumulation of small dense LDL particles. While much attention has been directed towards the study of LDL particle size, the importance of considering LDL particle number has been much less emphasized.69 While the concentration of cholesterol within each LDL in the plasma may vary considerably from one individual to another, each LDL contains only one apolipoprotein B (apoB).70 This particular feature of LDL has interesting clinical implications since measuring apoB concentration is essentially equivalent to measuring the number of particles in circulation.71, 72 The concept of LDL particle number as an important component of the insulin resistance syndrome and related cardiovascular risk has been emphasized by our own studies, which have shown that the combination of elevated plasma apoB (hyperapoB) and hypertriglyceridaemia was the most common dyslipidemic phenotype among individuals who developed cardiovascular disease in the Quebec Cardiovascular Study.73 The presence versus absence of hyperapoB was also an important determinant of the risk associated with hypertriglyceridaemia. Indeed, hypertriglyceridaemia was associated with an increased risk of cardiovascular disease only when hyperapoB was concurrently present.73 We also showed that there was a relatively strong synergy between LDL particle size and LDL particle number in determining the risk of cardiovascular disease in men. Thus, while men with small dense LDL particles were at increased risk of cardiovascular disease even in the presence of a relatively reduced number of LDL particles (low apoB concentrations), the combination of small dense LDL with increased number of LDL particles was associated with the greatest risk (Figure 14.3).62 This is an important issue since the insulin resistance syndrome is more likely to be associated with both an increase in LDL particle number and a reduction in LDL particle size. In this context, it is proposed that the insulin resistance syndrome should really be considered as an LDL phenotype problem, not in terms of the traditional phenotype related to cholesterol, but rather in terms of LDL particle number and size.

460

INSULIN RESISTANCE AND DYSLIPIDAEMIA Relative risk of CVD 6

5.9

5

3.9

4 3 2

2.0 1.0

1 0 Proportion of small dense LDL

Low

Low

High

High

LDL particle number

Low

High

Low

High

Figure 14.3 Synergy between LDL particle number as estimated by plasma apolipoprotein B concentrations and LDL particle size phenotype measured by non-denaturing gradient gel electrophoresis in modulating the risk of cardiovascular disease (CVD) in men of the Quebec Cardiovascular Study (adapted from reference 62)

14.8

Insulin resistance, dyslipidaemia and the risk of cardiovascular disease

The relationship between each of the individual dyslipidaemias of the insulin resistance syndrome and the risk of cardiovascular disease has been discussed briefly in the previous sections. It is generally accepted that hypertriglyceridaemia, primarily due to the accumulation of remnants from chylomicrons or VLDL, reduced HDL cholesterol levels, and small dense LDL particles with moderate increase in LDL particle number will all individually be associated with an increased risk of cardiovascular disease. However, accumulating data suggests that the combined contribution of these risk factors may be more important than their individual contribution to cardiovascular risk. This is an important issue because the majority of individuals with the insulin resistance syndrome are most likely to display several rather than just one or two features of the syndrome.74 The relative risk of cardiovascular disease associated with the insulin resistance syndrome or metabolic syndrome as defined by the NCEP ATP III or by other organizations has been shown to increase two- to fivefold in both men and women and in various populations.75 – 77 We have shown, using data from the Quebec Cardiovascular Study, that individuals who accumulated several risk factors associated with the insulin resistance syndrome were characterized by a tremendous increase in the relative risk of cardiovascular disease compared with those who had only one or none of these risk factors. For example, we have demonstrated that non-diabetic men characterized as having hyperapoB, small dense LDL and hyperinsulinaemia simultaneously had a 20-fold increase in the risk of cardiovascular disease over five years compared with men who

REFERENCES

461

had none of these metabolic perturbations.78 We have also shown that the risk associated with hypertriglyceridaemia was modulated to a significant extent by the presence or absence of other components of the insulin resistance syndrome. For example, men with marginally increased plasma triglyceride levels (above 1.6 mmol/l) but with no other features of the insulin resistance syndrome had a threefold increase in the risk of cardiovascular disease compared with men with normal plasma triglyceride concentrations.79 On the other hand, the risk of cardiovascular disease was increased 13-fold in subjects with moderate hypertriglyceridaemia who also displayed hyperapoB, reduced HDL cholesterol levels and increased insulin concentrations.79 These data clearly indicate that the insulin resistance syndrome, irrespective of its definition, may be associated with significant elevations in risk of cardiovascular disease. Each of the typical dyslipidaemic features of the insulin resistance syndrome may contribute, through different mechanisms, to this increased risk of cardiovascular disease.

14.9

Conclusions

With the increasing rate of obesity in industrialized countries such as North America and Canada, and because obesity is such an important component of the insulin resistance syndrome and its accompanying metabolic perturbations, it is urgent that clinicians and public health instances recognize the importance of considering this syndrome and its treatment as key elements in primary and secondary prevention of cardiovascular disease. As emphasized in other chapters of this book, each feature of the insulin resistance syndrome can be treated and modified through non-pharmacological and pharmacological approaches. Because the insulin resistance syndrome may be present in a relatively large proportion of the population, any intervention that is successful in reducing its prevalence will have a tremendous impact on the rate of cardiovascular disease and related socioeconomic costs.

References 1. Reaven, G. M. (1988) Role of insulin resistance in human disease. Diabetes 37, 1495–1507. 2. Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). (2002) Final report. Circulation 106, 3143. 3. Ford, E. S., Giles, W. H. and Dietz, W. H. (2002) Prevalence of the metabolic syndrome among US adults – findings from the Third National Health and Nutrition Examination Survey. JAMA 287, 356–359. 4. Reaven, G. M. (1999) Insulin resistance: a chicken that has come to roost. Ann NY Acad Sci 892, 45. 5. Reaven, G. (2002) Metabolic Syndrome: pathophysiology and implications for management of cardiovascular disease. Circulation 106, 286–288.

462

INSULIN RESISTANCE AND DYSLIPIDAEMIA

6. Despres, J. P. and Marette, A. (1994) Relation of components of insulin resistance syndrome to coronary disease risk. Curr Opin Lipidol 5, 274–289. 7. Despres, J. P. (2001) Health consequences of visceral obesity. Ann Med 33, 534–541. 8. Lamarche, B. (1998) Abdominal obesity and its metabolic complications. Implications for the risk of ischaemic heart disease. Coronary Artery Dis 9, 473–481. 9. Avramoglu, R. K., Qiu, W. and Adeli, K. (2003) Mechanisms of metabolic dyslipidemia in insulin resistant states: deregulation of hepatic and intestinal lipoprotein secretion. Front Biosci 8, d464–d476. 10. Austin, M. A. (1991) Plasma triglyceride and coronary heart disease. Arterioscler Thromb Vasc Biol 11, 2–14. 11. Davignon, J. and Cohn, J. S. (1996) Triglycerides: a risk factor for coronary heart disease. Atherosclerosis 124, S57–S64. 12. Gotto, A. M., Jr. (1992) Hypertriglyceridemia: risks and perspectives. Am J Cardiol 70, 19h–25h. 13. Austin, M. A. (2000) Triglyceride, small, dense low-density lipoprotein, and the atherogenic lipoprotein phenotype. Curr Atheroscler Rep 2, 200–207. 14. Hokanson, J. E. and Austin, M. A. (1996) Plasma triglyceride level is a risk factor for cardiovascular disease independent of high-density lipoprotein cholesterol level: a metaanalysis of population-based prospective studies. J Cardiovasc Risk 3, 213–219. 15. Jeppesen, J., Hein, H. O., Suadicani, P. and Gyntelberg, F. (1998) Triglyceride concentration and ischemic heart disease: an eight-year follow-up in the Copenhagen Male Study. Circulation 97, 1029–1036. 16. Hokanson, J. E. (2002) Hypertriglyceridemia and risk of coronary heart disease. Curr Cardiol Rep 4, 488–493. 17. Ginsberg, H. N. and Illingworth, D. R. (2001) Postprandial dyslipidemia: an atherogenic disorder common in patients with diabetes mellitus. Am J Cardiol 20, 9H–15H. 18. Cooper, A. D. (1997) Hepatic uptake of chylomicron remnants. J Lipid Res 38, 2173–2192. 19. Mamo, J. C., Watts, G. F., Barrett, P. H., Smith, D., James, A. P. and Pal, S. (2001) Postprandial dyslipidemia in men with visceral obesity: an effect of reduced LDL receptor expression? Am J Physiol Endocrinol Metab 281, E626–E632. 20. Dane-Stewart, C. A., Watts, G. F., Barrett, P. H., Stuckey, B. G., Mamo, J. C., Martins, I. J. and Redgrave, T. G. (2003) Chylomicron remnant metabolism studied with a new breath test in postmenopausal women with and without type 2 diabetes mellitus. Clin Endocrinol (Oxf) 58, 415–420. 21. Chan, D. C., Watts, G. F., Barrett, P. H., Mamo, J. C. and Redgrave, T. G. (2002) Markers of triglyceride-rich lipoprotein remnant metabolism in visceral obesity. Clin Chem 48, 278–283. 22. Eckel, R. (1989) Lipoprotein lipase: a multifunctional enzyme relevant to common metabolic diseases. N Engl J Med 320, 1060–1068. 23. Lewis, G. F. (1997) Fatty acid regulation of very low density lipoprotein (VLDL) production. Curr Opin Lipidol 8, 146–153. 24. Ginsberg, H. N. and Huang, L. S. (2000) The insulin resistance syndrome: impact on lipoprotein metabolism and atherothrombosis. J Cardiovasc Risk 7, 325–331. 25. Despres, J. P., Lemieux, I., Dagenais, G. R., Cantin, B. and Lamarche, B. (2000) HDLcholesterol as a marker of coronary heart disease risk: the Quebec cardiovascular study. Atherosclerosis 153, 263–272. 26. Schaefer, E. J., Zech, L. A., Jenkins, L. L., Bronzert, T. J., Rubalcaba, E. A., Lindgren, F. T., Aamodt, R. L. and Brewer, H. B., Jr. (1982) Human apolipoprotein A-I and A-II metabolism. J Lipid Res 23, 850–862.

REFERENCES

463

27. Le, N. A. and Ginsberg, H. N. (1988) Heterogeneity of apoprotein A-I turnover in subjects with reduced concentrations of plasma high density lipoprotein cholesterol. Metabolism 37, 614–617. 28. Brinton, E. A., Eisenberg, S. and Breslow, J. L. (1994) Human HDL cholesterol levels are determined by apoA-I fractional catabolic rate, which correlates inversely with estimates of HDL particle size. Effects of gender, hepatic and lipoprotein lipases, triglyceride and insulin levels, and body fat distribution. Arterioscler Thromb 14, 707–720. 29. Frenais, R., Ouguerram, K., Maugeais, C., Mahot, P., Maugere, P., Krempf, M. and Magot, T. (1997) High density lipoprotein apolipoprotein AI kinetics in NIDDM: a stable isotope study. Diabetologia 40, 578–583. 30. Barrett, P. H. and Watts, G. F. (2003) Kinetic studies of lipoprotein metabolism in the metabolic syndrome including effects of nutritional interventions. Curr Opin Lipidol 14, 61–68. 31. Pont, F., Duvillard, L., Florentin, E., Gambert, P. and Verges, B. (2002) High-density lipoprotein apolipoprotein A-I kinetics in obese insulin resistant patients. An in vivo stable isotope study. Int J Obes Relat Metab Disord 26, 1151–1158. 32. Lamarche, B., Rashid, S. and Lewis, G. F. (1999) HDL metabolism in hypertriglyceridemic states: an overview. Clin Chim Acta 286, 145–161. 33. Gordon, D. J. and Rifkind, B. M. (1989) High density lipoprotein: the clinical implications of recent studies. N Engl J Med 321, 1311–1316. 34. Gordon, D. J., Probstfield, J. L., Garrison, R. J., Neaton, J. D., Castelli, W. P., Knoke, J., Jacobs, D. R., Jr., Bangdiwala, S. and Tyroler, H. A. (1989) High-density lipoprotein cholesterol and cardiovascular disease. Four prospective American Studies. Circulation 79, 8–15. 35. Gordon, D. J., Knoke, J., Probstfield, J. L., Superko, R. and Tyroler, H. A. (1986) High density lipoprotein cholesterol and coronary heart disease in hypercholesterolemic men: the Lipid Research Clinics Coronary Primary Prevention Trial. Circulation 74, 1217–1225. 36. Gordon, T., Castelli, W. P., Hjortland, M. C., Kannel, W. B. and Dawber, T. R. (1977) High density lipoprotein as a protective factor against coronary heart disease: the Framingham study. Am J Med 62, 707–714. 37. Tall, A. R. (1993) Plasma cholesteryl ester transfer protein. J Lipid Res 34, 1255–1274. 38. Tall, A. R. (1986) Mechanisms of enhanced cholesteryl ester transfer from high density lipoproteins to apolipoprotein B-containing lipoproteins during alimentary lipemia. J Clin Invest 77, 1163–1172. 39. Tall, A. R. (1990) Plasma high density lipoproteins. Metabolism and relationship to atherogenesis. J Clin Invest 68, 379–384. 40. Quintao, E. C. R. (1995) Is reverse cholesterol transport a misnomer for suggesting its role in the prevention of atheroma formation? Atherosclerosis 116, 1–14. 41. Agellon, L. B., Quinet, E., Gillette, T., Drayna, D., Brown, M. and Tall, A. R. (1990) Organization of the human cholesteryl ester transfer protein gene. Biochemistry 29, 1372–1376. 42. Collet, X., Tall, A. R., Serajuddin, H., Guendouzi, K., Royer, L., Oliveira, H., Barbaras, R., Jiang, X. C. and Francone, O. L. (1999) Remodeling of HDL by CETP in vivo and by CETP and hepatic lipase in vitro results in enhanced uptake of HDL CE by cells expressing scavenger receptor B-I. J Lipid Res 40, 1185–1193. 43. Tall, A. R. (1995) Plasma cholesteryl ester transfer protein and high-density lipoproteins: new insights from molecular genetic studies. J Intern Med 237, 5–12.

464

INSULIN RESISTANCE AND DYSLIPIDAEMIA

44. Maclean, P. S., Tanner, C. J., Houmard, J. A. and Barakat, H. A. (2001) Plasma cholesteryl ester transfer protein activity is not linked to insulin sensitivity. Metabolism 50, 783–788. 45. Mann, C. J., Yen, F. T., Grant, A. M. and Bihain, B. E. (1991) Mechanism of plasma cholesteryl ester transfer in hypertriglyceridemia. J Clin Invest 88, 2059–2066. 46. Lewis, G. F., Rashid, S., Uffelman, K. D. and Lamarche, B. (2001) Mechanism of HDL lowering in insulin resistant states. Diabetes Cardiovasc Dis Etiol Treatment Outcomes 498, 273–277. 47. Lamarche, B., Uffelman, K. D., Carpentier, A., Cohn, J. S., Steiner, G., Barrett, P. H. and Lewis, G. F. (1999) Triglyceride enrichment of HDL enhances in vivo metabolic clearance of HDL apo A-I in healthy men. J Clin Invest 103, 1191–1199. 48. Rashid, S., Trinh, D. K., Uffelman, K. D., Cohn, J. S., Rader, D. J. and Lewis, G. F. (2003) Expression of human hepatic lipase in the rabbit model preferentially enhances the clearance of triglyceride-enriched versus native high-density lipoprotein apolipoprotein A-I. Circulation 107, 3066–3072. 49. Lamarche, B., Uffelman, K. D., Barrett, H. R., Steiner, G. and Lewis, G. F. (1998) Analysis of particle size and lipid composition as determinants of the metabolic clearance of human high density lipoproteins in a rabbit model. J Lipid Res 39, 1162–1172. 50. Lewis, G. F., Lamarche, B., Uffelman, K. D., Heatherington, A. C., Honing, M. A., Szeto, L. W. and Barrett, H. R. (1997) Clearance of post-prandial and lipolytically modified human HDL in rabbits and rats. J Lipid Res 38, 1771–1781. 51. Rashid, S., Watanabe, T., Sakaue, T. and Lewis, G. F. (2003) Mechanisms of HDL lowering in insulin resistant, hypertriglyceridemic states: the combined effect of HDL triglyceride enrichment and elevated hepatic lipase activity. Clin Biochem 36, 421–429. 52. Rashid, S., Barrett, P. H., Uffelman, K. D., Watanabe, T., Adeli, K. and Lewis, G. F. (2002) Lipolytically modified triglyceride-enriched HDLs are rapidly cleared from the circulation. Arterioscler Thromb Vasc Biol 22, 483–487. 53. Despr´es, J. P., Ferland, M., Moorjani, S., Nadeau, A., Tremblay, A. and Lupien, P. J. (1989) Role of hepatic-triglyceride lipase activity in the association between intraabdominal fat and plasma HDL cholesterol in obese women. Arterioscler Thromb Vasc Biol 9, 485–492. 54. Brewer, H. B. and Santamarina-Fojo, S. (2003) Clinical significance of high-density lipoproteins and the development of atherosclerosis: focus on the role of the adenosine triphosphate-binding cassette protein A1 transporter. Am J Cardiol 92, 10–16. 55. Cohen, J. C. (2003) Endothelial lipase: direct evidence for a role in HDL metabolism. J Clin Invest 111, 318–321. 56. Ishida, T., Choi, S., Kundu, R. K., Hirata, Ki, Rubin, E. M., Cooper, A. D. and Quertermous, T. (2003) Endothelial lipase is a major determinant of HDL level. J Clin Invest 111, 347–355. 57. Jaye, M., Lynch, K. J., Krawiec, J., Marchadier, D., Maugeais, C., Doan, K., South, V., Amin, D., Perrone, M. and Rader, D. J. (1999) A novel endothelial-derived lipase that modulates HDL metabolism. Nat Genet 21, 424–428. 58. Krauss, R. M. and Burke, D. J. (1982) Identification of multiple subclasses of plasma low density lipoproteins in normal humans. J Lipid Res 23, 97–104. 59. Fisher, W. R. (1983) Heterogeneity of plasma low density lipoproteins: manifestations of the physiologic phenomenon in man. Metabolism 32, 283–291. 60. Lamarche, B., Lemieux, I. and Despr´es, J. P. (1999) The small, dense LDL phenotype and the risk of coronary heart disease. Epidemiology, pathophysiology and therapeutic considerations. Diabetes Metab 25, 199–211.

REFERENCES

465

61. Lamarche, B., Tchernof, A., Moorjani, S., Cantin, B., Dagenais, G. R., Lupien, P. J. and Despres, J. P. (1997) Small, dense low-density lipoprotein particles as a predictor of the risk of ischemic heart disease in men. Prospective results from the Quebec Cardiovascular Study. Circulation 95, 69–75. 62. St-Pierre, A. C., Ruel, I. L., Cantin, B., Dagenais, G. R., Bernard, P. M., Despres, J. P. and Lamarche, B. (2001) Comparison of various electrophoretic characteristics of LDL particles and their relationship to the risk of ischemic heart disease. Circulation 104, 2295–2299. 63. Fagerberg, B., Hulthe, J., Bokemark, L. and Wikstrand, J. (2001) Low-density lipoprotein particle size, insulin resistance, and proinsulin in a population sample of 58-year-old men. Metabolism 50, 120–124. 64. Campos, H., Blijlevens, E., McNamara, J. R., Ordovas, J. M., Posner, B. M. and Wilson, P. W. F. (1992) LDL particle size distribution. Results from the Framingham Offspring Study. Arterioscler Thromb Vasc Biol 12, 1410–1419. 65. McNamara, J. R., Campos, H., Ordovas, J. M., Peterson, J., Wilson, P. W. F. and Schaefer, E. J. (1987) Effect of gender, age, and lipid status on low density lipoprotein subfraction distribution: results from the Framingham Offspring Study. Arterioscler Thromb Vasc Biol 7, 483–490. 66. Ruel, I. L., Couture, P., Gagne, C., Deshaies, Y., Simard, J., Hegele, R. A. and Lamarche, B. (2003) Characterization of a novel mutation causing hepatic lipase deficiency among French Canadians. J Lipid Res 44, 1508–1514. 67. Berneis, K. K. and Krauss, R. M. (2002) Metabolic origins and clinical significance of LDL heterogeneity. J Lipid Res 43, 1363–1379. 68. Despr´es, J. P. (1998) The insulin resistance–dyslipidemic syndrome of visceral obesity: effects on patients’ risk. Obes Res 6 (Suppl. 1), 8S–17S. 69. Sniderman, A. D., Pedersen, T. and Kjekshus, J. (1997) Putting low-density lipoproteins at center stage in atherogenesis. Am J Cardiol 79, 64–67. 70. Sniderman, A. D. and Genest, J. J. (1992) The measurement of apolipoprotein B should replace the conventional lipid profile in screening for cardiovascular risk. Can J Cardiol 8, 133–140. 71. Sniderman, A. D. and Silberberg, J. (1990) Is it time to measure apolipoprotein B? Arterioscler Thromb Vasc Biol 10, 665–667. 72. Sniderman, A. D. and Cianflone, K. (1996) Measurement of apoproteins: time to improve the diagnosis and treatment of the atherogenic dyslipoproteinemias. Clin Chem 42, 489–491. 73. Lamarche, B., Despr´es, J. P., Moorjani, S., Cantin, B., Dagenais, G. R. and Lupien, P. J. (1995) Prevalence of dyslipidemic phenotypes in ischemic heart disease (prospective results from the Qu´ebec Cardiovascular Study). Am J Cardiol 75, 1189–1195. 74. Reaven, G. (2002) Metabolic syndrome: pathophysiology and implications for management of cardiovascular disease. Circulation 106, 286. 75. Isomaa, B., Almgren, P., Tuomi, T., Forsen, B., Lahti, K., Nissen, M., Taskinen, M. R. and Groop, L. (2001) Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care 24, 683. 76. Lakka, H. M., Laaksonen, D. E., Lakka, T. A., Niskanen, L. K., Kumpusalo, E., Tuomilehto, J. and Salonen, J. T. (2002) The metabolic syndrome and total and cardiovascular disease mortality in middle-aged men. JAMA 288, 2709–2716. 77. Ridker, P. M., Buring, J. E., Cook, N. R. and Rifai, N. (2003) C-reactive protein, the metabolic syndrome, and risk of incident cardiovascular events: an 8-year follow-up of 14 719 initially healthy American women. Circulation 107, 391–397.

466

INSULIN RESISTANCE AND DYSLIPIDAEMIA

78. Lamarche, B., Tchernof, A., Mauri`ege, P., Cantin, B., Dagenais, G. R., Lupien, P. J. and Despr´es, J. P. (1998) Fasting insulin and apolipoprotein B levels and low-density lipoprotein particle size as risk factors for ischemic heart disease. JAMA 279, 1955–1961. 79. Lamarche, B., Cantin, B., Mauri`ege, P., Dagenais, G. R. and Despr´es, J. P. (1999) Variability in the risk of IHD associated with moderate hypertriglyceridemia. The Qu´ebec Cardiovascular Study. Circulation 100 (18, Suppl. 1), abstract.

15 Insulin Resistance, Hypertension and Endothelial Dysfunction Stephen J. Cleland and John M. C. Connell

15.1 Introduction In 1966 Welborn et al. demonstrated that patients with essential hypertension had elevated insulin levels, highlighting the link between dysfunctional insulin action and risk of cardiovascular disease.1 By the 1970s, Reaven’s group had shown that type 2 diabetes was characterized by a reduction in insulin’s ability to stimulate whole body glucose uptake (insulin resistance),2 and subsequent studies by the same group characterized a similar metabolic association among obesity, dyslipidaemia and hypertension. Reaven coined the term ‘syndrome X’ to describe this overlap of metabolic and vascular abnormalities. Nevertheless, the direct association between hyperinsulinaemic insulin resistance and essential hypertension that could not be attributed to confounding obesity was most convincingly demonstrated by Ferrannini and colleagues in 1987.3 A number of cross-sectional epidemiological studies have also demonstrated an association between insulin levels and blood pressure.4 In this article we will review the potential mechanisms that might underlie this association, and consider how the presence of insulin resistance might signal a more general abnormality in cell signalling that is relevant to the development of vascular disease.

15.2

Hyperinsulinaemia, insulin resistance and hypertension

It is unlikely that hyperinsulinaemia directly causes hypertension, and the relationship between insulin resistance and vascular dysfunction is certainly not direct and Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

468

INSULIN RESISTANCE, HYPERTENSION AND ENDOTHELIAL DYSFUNCTION

simple. Thus, chronic artificial elevation of serum insulin concentrations increases BP in rats,5 has no effect in dogs6 and lowers BP in man.7 Patients with insulinomas do not tend to have hypertension.8 Nevertheless, prospective studies have shown that individuals with hyperinsulinaemia have a higher risk of developing both hypertension9 and coronary events.10 Studies using the hyperinsulinaemic–euglycaemic clamp technique have demonstrated that hyperinsulinaemia occurs in hypertension as a compensatory response to reduced insulin-stimulated glucose uptake by skeletal muscle.3, 11 Insulin resistance is absent in secondary hypertension but present in normotensive offspring of essential hypertensive patients,12 suggesting that it may precede the development of high blood pressure. It has been suggested that the relationship between insulin resistance and BP may be confounded by obesity, as body mass index (BMI) has a strong association with both insulin resistance and hypertension.13 However, pooled analysis of insulin sensitivity data from 333 subjects from various European centres has demonstrated that both systolic and diastolic BP have a negative relationship with insulin sensitivity even after adjustment for age, gender, BMI and fasting serum insulin concentration; i.e., the data is consistent with the hypothesis that the association between BMI and BP is mediated by insulin sensitivity.14

15.3 Possible mechanisms linking insulin with blood pressure Insulin has depressor peripheral vasodilator actions mainly in skeletal muscle vascular beds, probably by an endothelium-dependent mechanism, an action that will be discussed in more detail later. However, the hormone also has pressor effects mainly via stimulation of the sympathetic nervous system15 and enhancement of renal sodium absorption.16 The net physiological effect is a balance of pressor and depressor effects and maintenance of BP (Figure 15.1). In pathophysiological states such as obesity, the balance may be disrupted by enhanced sympathetic activation in response to hyperinsulinaemia17 together with ‘blunting’ of insulinmediated vasodilation (vascular insulin resistance).18 Indeed, there is positron emission tomography evidence to suggest that insulin-stimulated muscle blood flow is impaired in lean patients with mild essential hypertension.19 This result concurs with previous reports of a negative correlation between insulin-induced vasodilation and blood pressure using less sensitive techniques for measurement of flow.20, 21 However, some authors have debated these results22 and it remains unclear whether blunting of insulin-mediated vasodilation contributes to hypertension in insulin-resistant states via increased peripheral vascular resistance. Thus, while there is undoubtedly a link among insulin resistance, hyperinsulinaemia and hypertension, the association may not be causal: instead, it may reflect shared underlying pathophysiological abnormalities.

ENDOTHELIAL DYSFUNCTION AND ATHEROTHROMBOTIC DISEASE ‘depressor’

endothelium-dependent vasodilation

469

‘pressor’

sympathetic stimulation sodium reabsorption

BP

BP

insulin sensitive

insulin resistant

Figure 15.1 The balance of insulin’s pressor and depressor effects may influence BP

15.4

Atherosclerosis and insulin resistance

The risk of coronary artery disease is greatly increased in type 2 diabetes. In a study examining the seven-year incidence of myocardial infarction (MI), Haffner et al.23 reported that the 10-year risk for a non-diabetic subject without previous MI was 3.5 per cent; if a subject had previously had an MI, the risk of a further event was 18.8 per cent. In contrast, in diabetic subjects without previous MI, the risk was comparable to that for a non-diabetic post-MI subject (20.2 per cent), while the risk of a second MI in a diabetic subject was 45 per cent.23 Thus, diabetes that is characterized by insulin resistance and hyperinsulinaemia is associated with an accelerated risk of atherosclerosis. However, in patients without overt type 2 diabetes, the independent association between insulin resistance and atherosclerosis risk has been less easy to demonstrate. Nevertheless, there are now several good epidemiological studies that suggest that insulin resistance is an independent risk factor for cardiovascular disease. For example, surrogate measures of insulin resistance are associated with carotid artery intima–media thickness, a measure of atherosclerosis.24, 25 As yet, there are no prospective data on the predictive role of insulin resistance on cardiovascular event rate, although the European Group for the study of Insulin Resistance (EGIR) is currently conducting a large multi-centre study to address this issue.

15.5 Vascular endothelial dysfunction and mechanisms of atherothrombotic disease Our understanding of the link between diabetes and cardiovascular disease is evolving. It now appears likely that defective insulin action on vascular endothelial cells is a key intermediate mechanism of vascular dysfunction in insulin-resistant conditions.

470

INSULIN RESISTANCE, HYPERTENSION AND ENDOTHELIAL DYSFUNCTION

Overview of vascular endothelial function and role of nitric oxide (NO) Cells of the endothelial monolayer produce a variety of mediators in response to a wide range of agonists. Of these, nitric oxide (NO) is a key signalling molecule that causes vascular relaxation, inhibits vascular smooth muscle cell growth, and is anti-thrombotic (Figure 15.2). We will focus in this section on NO, and use the term ‘endothelial dysfunction’ specifically to refer to abnormal endothelial NO availability. This, in turn, can represent either abnormal NO synthesis (e.g. reduced activity of endothelial nitric oxide synthase – eNOS) or increased NO quenching (e.g. by superoxide or other cellular free radicals). While it is often assumed that defects in NO production equate with global dysfunction of other endothelial mechanisms, there is very little direct supporting evidence.

Measurement of NO availability in vivo Measurement of either stimulated or basal NO production is the ‘gold standard’ for assessment of vascular endothelial function. A useful surrogate measure is evaluation of endothelium-dependent limb blood flow. This can be assessed by a number of methods, the most commonly used being forearm venous-occlusion plethysmography. A number of different compounds have been infused via a limb artery to demonstrate local vasodilation via stimulation of endothelial NO production; these include acetylcholine, methacholine and bradykinin. In all such protocols, it is vital to study in parallel the effects of an endothelium-independent donor of NO (e.g. sodium nitroprusside), which is used as an experimental control to assess sensitivity of adjacent vascular smooth muscle to NO. An alternative approach is to assess basal endothelial NO production. The most commonly used method for this in man is measurement of the vasoconstrictor response to a local infusion of NG -monomethyl-L-arginine (L-NMMA), which is a stereospecific substrate inhibitor of eNOS. Vasoconstriction to L-NMMA in the human forearm is dose dependent with maximal reduction in blood flow in

VSMCs healthy endothelium

anti-proliferative

NO

vasodilator

anti-coagulant anti-oxidant anti-inflammatory Figure 15.2 Pluripotential role of nitric oxide (NO) produced by vascular endothelial cells in prevention of atherothrombosis (VSMCs: vascular smooth muscle cells)

DIRECT VASCULAR ACTION OF INSULIN

471

the order of 30–40 per cent.26 Therefore, basal production of endothelial NO contributes significantly to the determination of resting blood flow.

15.6

Direct vascular action of insulin

It is now accepted that insulin has a direct vasodilator action on peripheral arterioles, mainly in skeletal muscle vascular beds. However, there is debate as to the physiological relevance of this effect,27 since significant vasodilation only occurs after 40–50 minutes of systemic insulin infusion at high physiological levels.28 A more likely role for insulin in this context is as a chronically acting regulator of blood flow in metabolically active vascular beds. While this concept is controversial, it is teleologically attractive since it would be useful for insulin to direct fuel substrate to relevant tissues prior to stimulating cellular uptake, and it is supported by the demonstration of a positive association between insulin sensitivity and insulin-mediated vasodilation in man.29 The action of insulin to cause vasodilation is dependent on endothelial NO release. Thus, insulin infusion into the brachial artery of normal human subjects causes an increase in forearm blood flow. This effect can be abolished by pretreatment with the inhibitor of endothelial NO synthesis, L-NMMA, and enhanced by the co-infusion of the substrate for eNOS, L-arginine.30 The vasodilation is also likely to be an energy-dependent process, as we have shown that the action of insulin in this context is not seen when co-administered with L-glucose instead of D-glucose.28

Does insulin resistance cause endothelial dysfunction? There is accumulating evidence that insulin directly stimulates eNOS activity in vascular endothelial cells.31 – 33 Thus, we and others have been able to demonstrate that all of the components of the insulin signalling pathway, including IRS, PI3kinase and PKB/AKT, are expressed in cultured human aortic endothelial cells and are phosphorylated on the addition of insulin to the cells. These components are also necessary for the regulation of glucose uptake in insulin-sensitive tissues. Addition of insulin to endothelial cells results in a prompt increase in release of NO; this effect is abolished by inhibition of the inhibitor of PI3kinase, wortmannin. Insulin also stimulates the uptake of L-arginine by endothelial cells via its specific transporter.34 The action of insulin to release NO is seen at concentrations of the hormone that are physiologically relevant. Thus, it now seems likely that insulin contributes to the regulation of endothelial NO synthesis via a signalling pathway that is similar to that utilized in fat and skeletal muscle for the uptake of insulin (Figure 15.3.) This concordance of insulin signalling pathways in endothelium and adipose tissue identifies a possible mechanistic link between metabolic insulin resistance and endothelial dysfunction. We reported earlier that there was a direct relationship

472

INSULIN RESISTANCE, HYPERTENSION AND ENDOTHELIAL DYSFUNCTION (a) PDK1 PIP3 PKB/Akt

PI3-K insulin

IRS GSK3

adiopcyte / myocyte

GLUT4 glucose

(b) PDK1 PIP3 PI3-K insulin

PKB/Akt

IRS

eNOS NO

endothelial cell

Figure 15.3 Insulin signalling pathway for (a) glucose uptake in adipocytes and myocytes and (b) NO production in endothelial cells (IRS, insulin receptor substrate; PI3-K, phosphatidylinositol-3-kinase; PIP3, phosphatidylinositol phosphate-3; PDK1, 3-phosphoinositide-dependent kinase-1; PKB/Akt, protein kinase B; GSK3, glycogen synthase kinase-3; GLUT4, glucose transporter-4)

between insulin sensitivity and endothelial NO availability in normal males and in patients with hypertension or type 2 diabetes (Figure 15.4).35, 36 It is reasonable to speculate that this reflects variation in insulin sensitivity of endothelial tissue, resulting in altered NO synthesis. Furthermore, there was a direct association between insulin-stimulated glucose uptake and insulin-mediated vasodilation in these subjects.29 Data from two animal models support the idea that insulin action is essential for normal endothelial function and that common defects in insulin signalling can result in defective glucose uptake and an abnormal vascular endothelium. First, defective endothelium-dependent vasorelaxation has been demonstrated in mice lacking insulin receptor substrate-1.37 Second, multiple defects in components of the insulin signalling pathway have been reported in vascular tissue of the insulin-resistant obese Zucker rat,38 although it is of interest that the regulation of MAP kinase by insulin was not affected in this model. This data suggests that there is a specific abnormality in the insulin signalling pathway that utilizes IRS/PI3kinase in both metabolic tissues, such as fat, and

DIRECT VASCULAR ACTION OF INSULIN

473

L-NMMA

–60 –50 –40

% change FBF ratio

–30

r = 0.52 p < 0.01

–20 –10 –20

0

20

40

60

Norepinephrine –60

–40

–20

0

r = –0.15 p = NS

20 –20

0

20

40

60

Insulin/glucose-mediated % change FBF ratio Figure 15.4 Percentage change in forearm blood flow ratio in response to intra-arterial infusions of L-NMMA (assessment of basal NO synthesis) and noradrenaline (endothelium-independent control) plotted against local insulin/glucose-mediated vasodilation (percentage change in forearm blood flow ratio). Pooled correlation analysis in patients with type 2 diabetes, essential hypertension and controls (n = 27) (adapted from reference 36; reprinted from Cleland et al, 2000, with permission from Lippincott, Williams & Wilkins)

vascular endothelium.38 Thus, abnormal insulin signalling may be a key intermediate mechanism that links metabolic and vascular dysfunction.

Does endothelial dysfunction cause insulin resistance? The alternative view is that abnormal vascular endothelium might cause insulin resistance.39 For example, it is possible that reduced substrate delivery is rate limiting for insulin-stimulated glucose uptake,40 although this concept has been dismissed by a number of authors.41 – 43 A recent study demonstrating insulin resistance in eNOS ‘knockout’ mice has been interpreted as supporting the role of decreased blood flow to skeletal muscle resulting in diminished glucose uptake,44 but is also consistent with the alternative explanation that there is an interaction

474

INSULIN RESISTANCE, HYPERTENSION AND ENDOTHELIAL DYSFUNCTION

between NO and insulin signalling at the level of the skeletal myocytes, since there is increasing evidence that NO plays a key role in muscle metabolic control, especially in the context of exercise.45, 46 There is evidence of expression of eNOS in skeletal muscle, and it is possible that vascular endothelial dysfunction in insulin-resistant states may reflect more generalized dysfunction of NO pathways in insulin-sensitive tissues. Finally, evidence from spontaneously hypertensive rats suggests that isolated adipocytes show defective insulin-stimulated glucose uptake, consistent with the notion that there is a primary defect in transduction of the insulin signal in this circumstance.47

Endothelial dysfunction in type 2 diabetes – role of hyperglycaemia? Impairment of vascular endothelial function is a feature of type 2 diabetes.48 Despite the suggestion that this is secondary to obesity/insulin resistance rather than hyperglycaemia per se,49 significant endothelial dysfunction has been demonstrated in type 2 diabetic patients compared with age- and BMI-matched control subjects.50 Coronary artery endothelial function has been shown to be impaired in type 2 diabetes51 and LDL-cholesterol size has been shown to correlate with the degree of endothelial function in diabetes, supporting the notion that an atherogenic lipid profile might be a key intermediate mechanism.52 However, while hyperglycaemia may contribute independently to endothelial dysfunction, it is unlikely to be the primary underlying cause, since studies have shown that altered vascular function is present in insulin-resistant states with normoglycaemia.53, 54

15.7 What causes abnormal insulin signalling in metabolic and vascular tissues? If it is accepted that a common defect in insulin action in metabolically active tissues, such as skeletal muscle and fat, and vascular endothelium accounts for the association between insulin resistance and conditions characterized by endothelial dysfunction such as hypertension, type 2 diabetes and atherosclerosis, it is reasonable to speculate on potential mechanisms. It is possible that the shared abnormality reflects a primary (genetic) alteration in a component of insulin signalling or that external factors affect insulin action in a range of tissues. This latter idea may be more appealing; metabolic insulin sensitivity and vascular endothelial function both change in parallel in response to a range of interventions, such as weight loss, exercise and pharmacological intervention. This would be consistent with the idea that certain factors might directly influence insulin signalling in endothelium, adipose tissue and skeletal muscle. This concept is strengthened by the evidence that adipose tissue secretes a number of hormones and cytokines that can act in an autocrine, paracrine and endocrine manner to influence insulin sensitivity and endothelial function. For example, TNF-α has been shown not only to induce insulin resistance by disruption of the proximal insulin signalling pathway55 – 57 but also to lead to endothelial dysfunction.58

WHAT CAUSES ABNORMAL INSULIN SIGNALLING?

475

One potential mechanism to account for these effects of TNF-α is activation of nuclear factor-κB (NFkB).59 In this context, three recent studies are of particular interest. First, insulin has been shown to have a potent anti-inflammatory effect in vitro, via inhibition of NFkB and stimulation of IkB, an inhibitory regulator of NFkB.60 Second, the insulin-sensitizing drugs thiazolidinediones, which are known to inhibit NFkB, have been shown to block TNFα-mediated insulin resistance.61 Third, aspirin, which stimulates IkB, has been shown to reduce insulin resistance, supporting the notion that this pathway plays a key role in the link between insulin signalling, endothelial dysfunction and pro-inflammation62, 63 (Figure 15.5). The logical proposal that TNF-α might be a potential therapeutic target in metabolic and vascular disease has led to some conflicting results. (a)

TNF-α

aspirin

NFkB PDK1

IkB PIP3

PKB/Akt

PI3-K insulin

IRS GSK3 adiopcyte/ myocyte

GLUT4 glucose

(b)

TNF-α

aspirin

NFkB PDK1

IkB PIP3 PI3-K insulin

PKB/Akt

IRS

eNOS NO

endothelial cell

Figure 15.5 Proposed mechanism for TNF-α (tumour necrosis factor α)-induced (a) insulin resistance and (b) endothelial dysfunction, via NFkB (nuclear factor kappa B)-mediated inhibition of the proximal insulin signalling pathway. Aspirin may improve insulin sensitivity and endothelial NO production by stimulation of IkB (inhibitory kappa B), an inhibitory modulator of NFkB

476

INSULIN RESISTANCE, HYPERTENSION AND ENDOTHELIAL DYSFUNCTION

adiponectin

TNF-α IL-6 resistin

CRP

β-cell dysfunction

cytokines adiponectin procoagulation prothrombosis hypertension endothelial dysfunction atherogenesis

muscle insulin resistance

Figure 15.6 Proposed mechanism for adipocytokine effects on liver, pancreas, muscle, heart, arteries and platelets (IL-6, interleukin-6; CRP, C-reactive protein)

Initial data from mice were encouraging,64 but a study of anti-TNF-α antibodies in humans with type 2 diabetes yielded disappointing results.65 TNF-α is not the only adipocytokine that has been proposed as a mediator of metabolic and endothelial dysfunction66 – 68 (Figure 15.6). IL-6, a potent stimulator of hepatic CRP production, has been linked to diabetes and cardiovascular disease in prospective epidemiological studies,69 – 71 and there is good evidence of a direct link between IL-6 production and insulin resistance.72 Leptin has also been shown to have both metabolic and vascular effects,73, 74 and resistin may be an important adipocytokine, although initial work in animal models has not translated into human studies.75, 76 Finally, adiponectin appears to act at many distant sites including skeletal muscle and endothelium and is a promising candidate as mediator of metabolic and vascular effects.77 In particular, adiponectin levels appear to be predictive of the risk for development of type 2 diabetes, with low levels associated with an increased risk.78 In addition, reduced adiponectin levels are reportedly found in patients with essential hypertension (whose insulin status was not defined),79 and reduced levels are also predictive of the development of coronary disease.80 Thus, there is a growing body of evidence that reduced adiponectin levels are associated with insulin resistance, hypertension and coronary disease, but the causal nature of this association and the molecular mechanisms remain to be identified. FFAs secreted from visceral adipocytes may also be exerting a hormonal action (Figure 15.7). As well as adversely influencing insulin action, FFAs exert effects on vascular endothelial function. For example, FFA infusion caused blunting of

SUMMARY AND CONCLUSIONS

FFAs

477

β-cell dysfunction FFAs TG/VLDL sdLDL

procoagulation prothrombosis

glucose hypertension endothelial dysfunction atherogenesis

muscle insulin resistance

Figure 15.7 Proposed mechanism for free fatty acid (FFA) effects on liver, pancreas, muscle, heart, arteries and platelets (TG, triglyceride; VLDL, very low density lipoprotein; sdLDL, small dense low density lipoprotein cholesterol)

endothelium-dependent leg vasodilation during insulin suppression.81 Interestingly, this effect was reversed in the presence of insulin. This result has been confirmed by others82 and is supported by a study in which the free fatty acid oleic acid was shown to inhibit nitric oxide synthase in endothelial cell culture.83 Therefore, adipocytokines are potential candidates as mediators of insulin resistance, endothelial dysfunction and hypertension, and reflect the importance of visceral adiposity as a causal factor in metabolic and vascular disease. Elucidation of the mechanisms involved may facilitate the development of novel therapeutic targets.84

15.8 Summary and conclusions (Figure 15.8) The association between insulin action and blood pressure has been observed for nearly 40 years. Insulin has both pressor and depressor actions, the imbalance of which may lead to hypertension. Insulin resistance is the main intermediate mechanism linking obesity (especially visceral adiposity) with hypertension and atherosclerosis. A key site for interplay between metabolic and vascular control pathways is the endothelium. The insulin signalling pathway has been demonstrated in vascular endothelial cells and its integrity may be important in the production of endothelial nitric oxide. Thus, ‘vascular insulin resistance’ may cause blunting of NO production with subsequent promotion of hypertension

478

INSULIN RESISTANCE, HYPERTENSION AND ENDOTHELIAL DYSFUNCTION

Obesity Type 2 diabetes Hypertension CAD

FFAs Adipocytokines CRP Insulin resistance

Vascular endothelial dysfunction

Figure 15.8 Mechanisms linking insulin resistance, vascular endothelial dysfunction and conditions such as obesity, type 2 diabetes, hypertension and coronary artery disease may be direct at a cellular level or indirect, mediated by circulating factors, e.g. adipocytokines, FFAs and CRP

and atherosclerosis in the long term. In addition, circulating factors may influence endothelial function and lead to hypertension. For example, proinflammatory adipocytokines released from insulin-resistant visceral adipocytes may influence endothelial NO production, resulting in vascular dysfunction, and may promote inflammatory atherosclerotic lesions. Therefore, to prevent vascular damage in an insulin-resistant patient, a key therapeutic strategy is to preserve vascular endothelial function, either by promoting protective intracellular pathways or by reducing the load of adverse circulating factors.

References 1. Welborn, T. A., Breckenridge, A., Dollery, C. T., Rubenstein, A. H. and Russell Fraser, T. (1966) Serum insulin in essential hypertension and in peripheral vascular disease. Lancet 1, 1336–1337. 2. Ginsberg, H., Kimmerling, G., Olefsky, J. M. and Reaven, G. M. (1975) Demonstration of insulin resistance in untreated adult onset diabetic subjects with fasting hyperglycaemia. J Clin Invest 55, 454–461. 3. Feskens, E. J. M., Tuomilehto, J., Stengaard, J. H., Pekkanen, J., Nissinen, A. and Kromhout, D. (1995) Hypertension and overweight associated with hyperinsulinaemia and glucose tolerance: a longitudinal study of the Finnish and Dutch cohorts of the Seven Countries Study. Diabetologia 38, 839–847. 4. Brands, M. W., Hildebrandt, D. A., Mizelle, H. L. and Hall, J. E. (1991) Sustained hyperinsulinemia increases arterial pressure in conscious rats. Am J Physiol 260, R764–R768. 5. Brands, M. W., Mizelle, H. L., Gaillard, C. A., Hildebrandt, D. A. and Hall, J. E. (1991) The hemodynamic response to chronic hyperinsulinemia in conscious dogs. Am J Hypertens 4, 164–168.

REFERENCES

479

6. Heise, T., Magnusson, K., Heinemann, L. and Sawicki, P. T. (1998) Insulin resistance and the effect of insulin on blood pressure in essential hypertension. Hypertension 32, 243–248. 7. Fujita, N., Baba, T., Tomiyami, T., Kodama, T. and Kako, N. (1992) Hyperinsulinaemia and blood pressure in patients with insulinoma. BMJ 304, 1157–1157. 8. Haffner, S. M., Valdez, R. A., Hazuda, H. P., Mitchell, B. D., Morales, P. A. and Stern, M. P. (1992) Prospective analysis of the insulin-resistance syndrome (Syndrome X). Diabetes 41, 715–722. 9. Ferrannini, E., Buzzigoli, G. and Bonadonna, R. (1987) Insulin resistance in essential hypertension. N Engl J Med 317, 350–357. 10. Despres, J.-P., Lamarche, B. and Mauriege, P et al. (1996) Hyperinsulinemia as an independent risk factor for ischemic heart disease. N Engl J Med 334, 952–957. 11. Lind, L., Berne, C. and Lithell, H. (1995) Prevalence of insulin resistance in essential hypertension. J Hypertens 13, 1457–1462. 12. Beatty, O. L., Harper, R., Sheridan, B., Atkinson, A. B. and Bell, P. M. (1993) Insulin resistance in offspring of hypertensive parents. BMJ 307, 92–96. 13. Jarrett, R. J. (1992) In defence of insulin: A critique of syndrome X. Lancet 340, 469–471. 14. Ferrannini, E., Natali, A., Capaldo, B., Lehtovirta, M., Jacob, and Yki-Jarvinen, H. (1997) Insulin resistance, hyperinsulinemia, and blood pressure: Role of age and obesity. Hypertension 30, 1144–1149. 15. Anderson, E. A., Balon, T. W., Hoffman, R. P., Sinkey, C. A. and Mark, A. L. (1992) Insulin increases sympathetic activity but not blood pressure in borderline hypertensive humans. Hypertension 19, 621–627. 16. Ferrannini, E. and Natali, A. (1993) Insulin resistance and hypertension: Connections with sodium metabolism. Am J Kidney Dis 21, 37–42. 17. Scherrer, U., Randin, D., Tappy, L., Vollenweider, P., Jequier, and Nicod, P. (1994) Body fat and sympathetic nerve activity in healthy subjects. Circulation 89, 2634–2640. 18. Laakso, M., Edelman, S. V., Brechtel, G. and Baron, A. D. (1990) Decreased effect of insulin to stimulate skeletal muscle blood flow in obese man. A novel mechanism for insulin resistance. J Clin Invest 85, 1844–1852. 19. Laine, H., Knuuti, M. J., Ruotsalainen, U., Raitakari, M., Iida, H., Kapanen, J., Kirvela, O., Haaparanta, M. and Yki-Jarvinen, H. N. (1998) Insulin resistance in essential hypertension is characterized by impaired insulin stimulation of blood flow in skeletal muscle. J Hypertens 16, 211–219. 20. Baron, A. D. (1993) Cardiovascular actions of insulin in humans. Implications for insulin sensitivity and vascular tone. Baillieres Clin Endocrinol Metabol 7, 961–987. 21. Feldman, R. D. and Bierbrier, G. S. (1993) Insulin-mediated vasodilation: Impairment with increased blood pressure and body mass. Lancet 342, 707–709. 22. Hunter, S. J., Harper, R., Ennis, C. N., Sheridan, B., Atkinson, A. B. and Bell, P. M. (1997) Skeletal muscle blood flow is not a determinant of insulin resistance in essential hypertension. J Hypertens 15, 73–77. 23. Haffner, S. M., Lehto, S., Ronnemaa, T., Pyorala, K. and Laakso, M. (1998) Mortality from coronary heart disease in subjects with type 2 diabetes and in nondiabetic subjects with and without prior myocardial infarction. N Engl J Med 339, 229–234. 24. Bokemark, L., Wikstrand, J., Attvall, S., Hulthe, J., Wedel, H. and Fagerberg, B. (2001) Insulin resistance and intima–media thickness in the carotid and femoral arteries of clinically healthy 58-year-old men. The Atherosclerosis and Insulin Resistance Study (AIR). J Intern Med 249, 59–67. 25. Howard, G., O’Leary, D. H., Zaccaro, D., Haffner, S., Rewers, M., Hamman, R., Selby, J. V., Saad, M. F., Savage, P. and Bergman, R. (1996) Insulin sensitivity and atherosclerosis. Circulation 93, 1809–1817.

480

INSULIN RESISTANCE, HYPERTENSION AND ENDOTHELIAL DYSFUNCTION

26. Vallance, P., Collier, J. and Moncada, S. (1989) Effects of endothelium-derived nitric oxide on peripheral arteriolar tone in man. Lancet 2, 997–1000. 27. Yki-Jarvinen, H. and Utriainen, T. (1998) Insulin-induced vasodilatation: Physiology or pharmacology? Diabetologia 41, 369–379. 28. Ueda, S., Petrie, J. R., Cleland, S. J., Elliott, H. L. and Connell, J. M. C. (1998) The vasodilating effect of insulin is dependent on local glucose uptake: A double blind, placebo-controlled study. J Clin Endocrinol Metab 83, 2126–2131. 29. Cleland, S. J., Petrie, J. R., Ueda, S., Elliott, H. L. and Connell, J. M. C. (1999) Insulinmediated vasodilation and glucose uptake are functionally linked in humans. Hypertension 33, 554–558. 30. Ueda, S., Petrie, J. R., Cleland, S. J., Elliott, H. L. and Connell, J. M. C. (1998) Insulin vasodilatation and the ‘arginine paradox’. Lancet 351, 959–960. 31. Zeng, G. and Quon, M. J. (1996) Insulin-stimulated production of nitric oxide is inhibited by Wortmannin: Direct measurement in vascular endothelial cells. J Clin Invest 98, 894–898. 32. Aljada, A. and Dandona, P. (2000) Effect of insulin on human aortic endothelial nitric oxide synthase. Metab Clin Exp 49, 147–150. 33. Kuboki, K., Jiang, Z.-Y., Takahara, N., Ha, S.-W., Igarashi, M., Yamauchi, T., Feener, E. P., Herbert, T. P., Rhodes, C. J. and King, G. L. (2000) Regulation of constitutive nitric oxide synthase gene expression in endothelial cells and in vivo. A specific vascular action of insulin. Circulation 101, 676–681. 34. Sobrevia, L., Nadal, A., Yudilevich, D. L. and Mann, G. E. (1996) Activation of Larginine transport (system y+) and nitric oxide synthase by elevated glucose and insulin in human endothelial cells. J Physiol 490, 775–781. 35. Petrie, J. R., Ueda, S., Webb, D. J., Elliott, H. L. and Connell, J. M. C. (1996) Endothelial nitric oxide production and insulin sensitivity: A physiological link with implications for pathogenesis of cardiovascular disease. Circulation 93, 1331–1333. 36. Cleland, S. J., Petrie, J. R., Small, M., Elliott, H. L. and Connell, J. M. C. (2000) Insulin action is associated with endothelial function in hypertension and type 2 diabetes. Hypertension 35(1), 507–511. 37. Abe, H., Yamada, N., Kuwaki, T., Shimada, M., Osuga, J., Shionoiri, F., Yahagi, N., Kadowaki, T., Tamemoto, H., Ishibashi, S., Yazaki, Y. and Makuuchi, M. (1998) Hypertension, hypertriglyceridemia, and impaired endothelium-dependent vascular relaxation in mice lacking insulin receptor substrate-1. J Clin Invest 101, 1784–1788. 38. Jiang, Z. Y., Lin, Y.-W., Clemont, A., Feener, E. P., Hein, K. D., Igarashi, M., Yamauchi, T., White, M. F. and King, G. L. (1999) Characterization of selective resistance to insulin signaling in the vasculature of obese Zucker (fa/fa) rats. J Clin Invest 104, 447–457. 39. Pinkney, J. H., Stehouwer, C. D. A., Coppack, S. W. and Yudkin, J. S. (1997) Endothelial dysfunction: Cause of the insulin resistance syndrome. Diabetes 46, S9–S13. 40. Baron, A. D. (1994) Hemodynamic actions of insulin. Am J Physiol – Endocrinol Metab 267, E187–E202. 41. Utriainen, T., Nuutila, P., Takala, T., Vicini, P., Ruotsalainen, Ronnemaa, T., Tolvanen, T., Raitakari, M., Haaparanta, M., Kirvela, O., Cobelli, C. and Yki-Jarvinen, H. (1997) Intact insulin stimulation of skeletal muscle blood flow, its heterogeneity and redistribution, but not of glucose uptake in non-insulin-dependent diabetes mellitus. J Clin Invest 100, 777–785. 42. Natali, A., Bonadonna, R., Santoro, D., Galvan, A. Q., Baldi, S., Frascerra, S., Palombo, C., Ghione, S. and Ferrannini, E. (1994) Insulin resistance and vasodilation in essential hypertension. Studies with adenosine. J Clin Invest 94, 1570–1576.

REFERENCES

481

43. Nuutila, P., Raitakari, M., Laine, H., Kirvela, O., Takala, T., Utriainen, T., Makimattila, S., Pitkanen, O.-P., Ruotsalainen, U., Iida, H., Knuuti, J. and Yki-Jarvinen, H. (1996) Role of blood flow in regulating insulin-stimulated glucose uptake in humans: Studies using bradykinin, [15O]water, and [18F]fluoro-deoxy-glucose and positron emission tomography. J Clin Invest 97, 1741–1747. 44. Shankar, R. R., Wu, Y., Shen, H.-Q., Zhu, J.-S. and Baron, A. D. (2000) Mice with disruption of both endothelial and neuronal nitric oxide synthase exhibit insulin resistance. Diabetes 49, 684–687. 45. Hayashi, T., Wojtaszewski, J. F. P. and Goodyear, L. J. (1997) Exercise regulation of glucose transport in skeletal muscle. Am J Physiol – Endocrinol Metab 273, E1039–E1051. 46. Young, M. E., Radda, G. K. and Leighton, B. (1997) Nitric oxide stimulates glucose transport and metabolism in rat skeletal muscle in vitro. Biochem J 322, 223–228. 47. Collison, M., Glazier, A. M., Graham, D., Morton, J. J., Dominiczak, M. H., Aitman, T. J., Connell, J. M., Gould, G. W. and Dominiczak, A. F. (2000) Cd36 and molecular mechanisms of insulin resistance in the stroke-prone spontaneously hypertensive rat. Diabetes 49, 2222–2226. 48. Williams, S. B., Cusco, J. A., Roddy, M.-A., Johnstone, M. T. and Creager, M. A. (1996) Impaired nitric oxide-mediated vasodilation in patients with non-insulin-dependent diabetes mellitus. J Am Coll Cardiol 27, 567–574. 49. Steinberg, H. O., Chaker, H., Leaming, R., Johnson, A., Brechtel, and Baron, A. D. (1996) Obesity/insulin resistance is associated with endothelial dysfunction. Implications for the syndrome of insulin resistance. J Clin Invest 97, 2601–2610. 50. Hogikyan, R. V., Galecki, A. T., Pitt, B., Halter, J. B., Greene, D. A. and Supiano, M. A. (1998) Specific impairment of endothelium-dependent vasodilation in subjects with type 2 diabetes independent of obesity. J Clin Endocrinol Metab 83, 1946–1952. 51. Nitenberg, A., Paycha, F., Ledoux, S., Sachs, R., Attali, J.-R. and Valensi, P. (1998) Coronary artery responses to physiological stimuli are improved by deferoxamine but not by L-arginine in non-insulin-dependent diabetic patients with angiographically normal coronary arteries and no other risk factors. Circulation 97, 736–743. 52. Makimattila, B., Liu, M.-L., Vakkilainen, J., Schlenzka, A., Lahdenpera, S., Syvanne, M., Mantysaari, M., Summanen, P., Bergholm, R., Taskinen, M.-R. and Yki, Jarvinen, H. (1999) Impaired endothelium-dependent vasodilation in type 2 diabetes: Relation to LDL size, oxidized LDL, and antioxidants. Diabetes Care 22, 973–981. 53. Tooke, J. E. and Goh, K. L. (1999) Vascular function in Type 2 diabetes mellitus and pre-diabetes: The case for intrinsic endotheliopathy. Diabet Med 16, 710–715. 54. Caballero, A. E., Arora, S., Saouaf, R., Lim, S. C., Smakowski, P., Park, J. Y., King, G. L. L., Horton, E. S. and Veves, A. (1999) Microvascular and macrovascular reactivity is reduced in subjects at risk for type 2 diabetes. Diabetes 48, 1856– 1862. 55. Valverde, A. M., Teruel, T., Navarro, P., Benito, M. and Lorenzo, M. (1998) Tumor necrosis factor-alpha causes insulin receptor substrate-2-mediated insulin resistance and inhibits insulin-induced adipogenesis in fetal brown adipocytes. Endocrinology 139, 1229–1238. 56. Feinstein, R., Kanety, H., Papa, M. Z., Lunenfeld, B. and Karasik, A. (1993) Tumor necrosis factor-alpha supresses insulin-induced tyrosine phosphorylation of insulin receptor and its substrates. J Biol Chem 268, 26 055–26 058. 57. Halse, R., Pearson, S. L., McCormack, J. G., Yeaman, S. J. and Taylor, R. (2001) Effects of tumor necrosis factor-α on insulin action in cultured human muscle cells. Diabetes 50, 1102–1109.

482

INSULIN RESISTANCE, HYPERTENSION AND ENDOTHELIAL DYSFUNCTION

58. Wang, P., Ba, Z. E. and Chaudry, I. H. (1994) Administration of tumour necrosis factor-alpha in vivo depresses endothelium-dependent relaxation. Am J Physiol 266, H2535–H2541. 59. Ruan, H., Hacohen, N., Golub, T. R., Van Parijs, L. and Lodish, H. F. (2002) Tumor necrosis factor-α suppresses adipocyte-specific genes and activates expression of preadipocyte genes in 3T3-L1 adipocytes: nuclear factor-κB activation by TNF-α is obligatory. Diabetes 51, 1319–1336. 60. Dandona, P., Aljada, A., Mohanty, P., Ghanim, H., Hamouda, W., Assian, E. and Ahmad, S. (2001) Insulin inhibits intranuclear nuclear factor κB and stimulates IκB in mononuclear cells in obese subjects: evidence for an anti-inflammatory effect? J Clin Endocrinol Metab 86, 3257–3265. 61. Peraldi, P., Xu, M. and Spiegelman, B. M. (1997) Thiazolidinediones block tumor necrosis factor-alpha-induced inhibition of insulin signaling. J Clin Invest 100, 1863–1869. 62. Hundal, R. S., Petersen, K. F., Mayerson, A. B., Randhawa, P. S., Inzucchi, S., Shoelson, S. E. and Shulman, G. I. (2002) Mechanism by which high-dose aspirin improves glucose metabolism in type 2 diabetes. J Clin Invest 109, 1321–1326. 63. Yuan, M., Konstantopoulos, N., Lee, J., Hansen, L., Li, Z. W., Karin, M. and Shoelson, S. E. (2001) Reversal of obesity- and diet-induced insulin resistance with salicylates or targeted disruption of Ikkbeta. Science 293, 1673–1677. 64. Ventre, J., Doebber, T., Wu, M., MacNaul, K., Stevens, K., Pasparakis, M., Kollias, G. and Moller, D. E. (1997) Targeted disruption of the tumor necrosis factor-alpha gene: metabolic consequences in obese and nonobese mice. Diabetes 46, 1526–1531. 65. Ofei, F., Hurel, S., Newkirk, J., Sopwith, M. and Taylor, R. (1996) Effects of an engineered human anti-TNF-a antibody (CPD571) on insulin sensitivity and glycemic control in patients with NIDDM. Diabetes 45, 881–885. 66. Stears, A. J. and Byrne, C. D. (2001) Adipocyte metabolism and the metabolic syndrome. Diabetes Obes Metab 3, 129–142. 67. Saltiel, A. R. and Kahn, R. C. (2001) Insulin signalling and the regulation of glucose and lipid metabolism. Nature 414, 799–806. 68. Shulman, G. I. (2000) Cellular mechanisms of insulin resistance. J Clin Invest 106, 171–176. 69. Bermudez, E. A., Rifai, N., Buring, J., Manson, J. E. and Ridker, P. M. (2002) Interrelationships among circulating interleukin-6, C-reactive protein, and traditional cardiovascular risk factors in women. Arterioscleros Thrombos Vasc Biol 22, 1668–1673. 70. Han, T. S., Sattar, N., Williams, K., Gonzalez-Villalpando, C., Lean, M. E. J. and Haffner, S. M. (2002) Prospective study of C-reactive protein in relation to the development of diabetes and metabolic syndrome in the Mexico City Diabetes Study. Diabetes Care 25, 2016–2021. 71. Festa, A., D’Agostino, R., Tracy, R. P. and Haffner, S. M. (2002) Elevated levels of acute-phase proteins and plasminogen activator inhibitor-1 predict the development of type 2 diabetes: the Insulin Resistance Atherosclerosis Study. Diabetes 51, 1131–1137. 72. Bastard, J.-P., Maachi, J., Van Nhieu, J. T., Jardel, C., Brucker, E., Grimaldi, A., Robert, J.-J., Capeau, J. and Hainque, B. (2002) Adipose tissue IL-6 content correlates with resistance to insulin activation of glucose uptake both in vivo and in vitro. J Clin Endocrinol Metab 87, 2084–2089. 73. Mantzoros, C. S. (1999) The role of leptin in human obesity and disease: a review of current evidence. Ann Intern Med 130, 671–680. 74. Shimomura, I., Hammer, R. E., Ikemoto, S., Brown, M. S. and Goldstein, J. L. (1999) Leptin reverses insulin resistance and diabetes mellitus in mice with congenital lipodystrophy. Nature 401, 73–76.

REFERENCES

483

75. Steppan, C. M., Brown, E. J., Wright, C. M., Bhat, S., Banerjee, R. R., Dai, C. Y., Enders, G. H., Silberg, D. G., Wen, X., Wu, G. D. and Lazar, M. A. (2001) A family of tissue-specific resistin-like molecules. Proc Natl Acad Sci USA 98, 502–506. 76. Nagaev, I. and Smith, U. (2001) Insulin resistance and type 2 diabetes are not related to resistin expression in human fat cells or skeletal muscle. Biochem Biophys Res Commun 285, 561–564. 77. Yamauchi, T., Kamon, J., Waki, H., Terauchi, Y., Kubota, N., Hara, K., Mori, Y., Ide, T., Murakami, K., Tsuboyama-Kasaoka, N., Ezaki, O., Akanuma, Y., Gavrilova, O., Vinson, C., Reitman, M. L., Kagechika, H., Shudo, K., Yoda, M., Nakano, Y., Tobe, K., Nagai, R., Kimura, S., Tomita, M., Froguel, P. and Kadowaki, T. (2001) The fat-derived hormone adiponectin reverses insulin resistance associated with both lipoatrophy and obesity. Nature Med 7, 941–946. 78. Lindsay, R. S., Funahashi, T., Hanson, R. L., Matsuzawa, Y., Tanaka, S., Tataranni, P. A., Knowler, W. C. and Krakoff, J. (2002) Adiponectin and development of type 2 diabetes in the Pima Indian population. Lancet 360, 57–8. 79. Adamczak, M., Wiecek, A., Funahashi, T., Chudek, J., Kokot, F. and Matsuzawa, Y. (2003) Decreased plasma adiponectin concentration in patients with essential hypertension. Am J Hypertens 16, 72–75. 80. Kumada, M., Kihara, S., Sumitsuji, S., Kawamoto, T., Matsumoto, S., Ouchi, N., Arita, Y., Okamoto, Y., Shimomura, I., Hiraoka, H., Nakamura, T., Funahashi, T. and Matsuzawa, Y. (2003) Osaka CAD Study Group. Coronary artery disease. Association of hypoadiponectinemia with coronary artery disease in men. Arterioscleros Thrombos Vascr Biol 23, 85–9. 81. Steinberg, H. O., Tarshoby, M., Monestel, R., Hook, G., Cronin, J., Johnson, A., Bayazeed, B. and Baron, A. D. (1997) Elevated circulating free fatty acid levels impair endothelium-dependent vasodilation. J Clin Invest 100, 1230–1239. 82. deKreutzenberg, S. V., Crepaldi, C., Marchetto, S., Calo, L. and Tiengo, A. (2000) Plasma free fatty acids and endothelium-dependent vasodilation: Effect of chain-length and cyclooxygenase inhibition. J Clin Endocrinol Metab 85, 793–798. 83. Davda, R. K., Stepniakowski, K. T., Lu, G., Ullian, M. E., Goodfriend, T. L. and Egan, B. M. (1995) Oleic acid inhibits endothelial nitric oxide synthase by a protein kinase C-independent mechanism. Hypertension 26, 764–770. 84. Moller, D. E. (2001) New drug targets for type 2 diabetes and the metabolic syndrome. Nature 414, 821–827.

16 Insulin Resistance and Polycystic Ovary Syndrome Neus Potau

16.1 Introduction Polycystic ovary syndrome (PCOS) is a common endocrine condition that affects women of reproductive age. In a broad sense PCOS may be considered to be synonymous with chronic unexplained hyperandrogenaemia, which accounts for approximately 95 per cent of hyperandrogenism in women.1 The most frequent forms of hyperandrogenism are premature pubarche (defined as the appearance of pubic hair before 8 years) in the pre-pubertal period and PCOS in the post-pubertal period, which affects approximately 5–10 per cent of women of reproductive age.2 Insulin resistance and compensatory hyperinsulinaemia are prominent features of many women with PCOS. The aetiology of this condition is unknown, but recent evidence suggests that the principal underlying disorder is insulin resistance and that the resulting hyperinsulinaemia stimulates excess ovarian androgens.3 Associated with insulin resistance, these women exhibit hyperlipidaemia and have a high risk of type 2 diabetes and cardiovascular disease in later life.4, 5 The new concept arising from the link with insulin resistance introduces a concept that not only has major implications for the health of affected women but also offers a potential for new treatments. Nowadays, the current treatment mainly with antiandrogens has been associated with insulin sensitizers such as metformin or thiazolidinediones. The results obtained with these drugs seem to confirm their efficacy in reversing metabolic and ovarian abnormalities in these women and adolescent girls. Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

486

INSULIN RESISTANCE AND POLYCYSTIC OVARY SYNDROME

16.2 Definition of polycystic ovary syndrome (PCOS) and diagnostic criteria PCOS is probably the most common endocrine disorder in women. Although not universally accepted, the 1990 point Conference of the National Institute of Health/National Institute of Child Health and Human Development established the diagnostic criteria on PCOS. PCOS is defined as a metabolic condition characterized by hyperandrogenism (hirsutism, acne, androgenic alopecia) and chronic anovulation (irregular menses with menses every 6 weeks to 6 months or amenorrhea) with the exclusion of specific disorders, such as non-classical adrenal hyperplasia due to 21-hydroxylase deficiency, hyperprolactinaemia, androgen-secreting tumours and thyroid diseases. Thus, the most widely accepted definition of PCOS is the association of clinical and/or biochemical evidence of androgen excess with chronic anovulation (having excluded specific underlying disorders of the pituitary or adrenals).6 This syndrome as a form of functional ovarian hyperandrogenism is a prevalent disorder affecting approximately 5–10 per cent of reproductive women.2 The prevalence of polycystic ovaries increases throughout puberty, reaching about 26 per cent by the age of 15. The prevalence of PCOS among teenage girls is not known but is clearly common.7 Ethnic differences in the prevalence of PCOS have not been explored but not significant differences between white and black women in the USA have been observed.2 Similar prevalence (6.8 and 6.5 per cent) was reported in two European countries.8, 9 Insulin resistance, a common feature of PCOS, can be characterized as impaired action of insulin in the uptake and metabolism of glucose. Impaired insulin action leads to elevated insulin levels, which causes a decrease in the synthesis of two important binding proteins: insulin-like growth factor binding protein (IGFBP1) and sex hormone binding globulin (SHBG). IGFBP1 binds IGF I and IGF II and SHBG binds to sex steroids, especially androgens. Obesity, which is seen in 50–65 per cent of PCOS patients, may increase the insulin resistance and hyperinsulinaemia.3 Acanthosis nigricans, a dark and hyperpigmented hyperplasia of the skin typically found at the nape of the neck and axila, is a marker of insulin resistance. Acanthosis nigricans is usually found in about 30 per cent of hyperandrogenic women. The triad of hyperandrogenism, insulin resistance and acanthosis nigricans (HAIR-AN) syndrome appears in a subgroup of patients with PCOS.10 Chronically elevated luteinizing hormone (LH) and insulin resistance are two of the most common endocrine aberrations seen in PCOS. The genetic cause of high LH is not known. In vitro and in vivo evidence offers support that high LH and hyperinsulinemia work synergistically, causing ovarian growth, androgen production and ovarian cyst formation.1 Figure 16.1 shows the multiple factors that can contribute to the development of PCOS.

DEFINITION OF POLYCYSTIC OVARY SYNDROME (PCOS)

OBESITY

INSULIN RESISTANCE

487

PITUITARY LH

ACTH

ADRENAL GLANS P450c17

INSULIN

IGFI ANDROGENS DHEAS

Puberty

Premature pubarche PCOS

OTHER FACTORS Low birthweight

OVARY P450c17

Genes

ANDROGENS TESTOSTERONE ANDROSTENEDIONE

AND

FOLLICLE ARREST ANOVULATION

Figure 16.1 Development of PCOS and the multiple factors that affect steroid dysregulation. Synergic role of insulin, LH and IGFI in androgen production. Other factors such as genes or functional abnormalities in prenatal, childhood or pubertal periods must be considered

The diagnosis of polycystic ovary syndrome is usually made on the basis of a combination of clinical and biochemical criteria (Table 16.1). The degree of hirsutism can be assessed by the Ferriman–Gallwey score, a simple, semiquantitative method for recording the distribution and severity of excess body hair.11 The classic anatomical pattern of polycystic ovaries can be identified by ultrasound assessment as increased number of subcapsular follicular cysts and increased intervening stroma.12 These ultrasound features are consistent with, but not essential for, the diagnosis of the syndrome.13 Serum levels of testosterone and androstenedione are usually increased. DHEAS dehydroepiandrosterone sulfate levels are increased by up to 50 per cent in women with PCOS. Elevated free testosterone activity, defined by the free androgen index, represents the most sensitive biochemical marker supporting the diagnosis. Prolactin is usually

488

INSULIN RESISTANCE AND POLYCYSTIC OVARY SYNDROME

Table 16.1 Clinical and biochemical evaluation of PCOS

Clinical

Biochemical

Test

Menstrual disturbances Ferriman–Gallwey score Pelvic ultrasonography Obesity (BMI) Testosterone, androstenedione, DHEAS SHBG FSH, LH, prolactin Fasting glucose and insulin OGTT GnRH agonist (nafarelin, leuprolide acetate) Dexamethasona suppression

normal, although it has been reported that approximately 15 per cent of PCOS patients have mild elevations.14 No single test is diagnostic of the syndrome, but choice should be guided by clinical presentation. Serum LH levels are typically elevated in PCOS but up to 50 per cent of the young women with other clinical and biochemical features of the syndrome may have normal serum LH levels. Measurement of LH is therefore of limited diagnostic value; it is quite specific that raised LH and normal FSH essentially occur only in PCOS, but this is not very sensitive.1 To assess insulin resistance with compensatory hyperinsulinism, fasting blood glucose and insulin could be useful and simple to detect a primary abnormality. With a standard oral glucose tolerance test, a hyperinsulinaemic response, impaired glucose tolerance or type 2 diabetes could be documented. The abnormal response of 17 α-hydroxyprogesterone after an agonist analogue of gonadotrophin-releasing hormone (GnRH) challenge has been described in women and adolescents.15, 16 Short-term leuprolide acetate (500 µg sc) is a reliable tool for identification of the ovary source of hyperandrogenaemia. The response was considered supranormal if the peak plasma 17 α-hydroxyprogesterone 24 h postestimulation was greater than 4.75 nmol/l (160 ng/dl).16 Hyperandrogenism in PCOS may therefore represent an intrinsic abnormality of ovarian theca-interstitial cell function. This conclusion is supported by clinical studies suggesting that the ovary is the primary abnormality site. The response observed in women with PCOS in the above mentioned test (GnRH agonist) could not be explained on the basis of LH hyper-responsiveness. Women with PCOS given an hCG challenge test produce more androstenedione and 17 α-hydroxyprogesterone than normal subjects and this difference remains evident after suppression of endogenous LH secretion by GnRH.17, 18 As many hyperandrogenic anovulatory women have significantly increased ovarian steroidogenic responses to stimulation with GnRH analogues, Rosenfield and colleagues have coined the term ‘functional ovarian hyperandrogenism,’ as an alternative to PCOS.19

HYPERANDROGENISM AND HYPERINSULINISM

16.3

489

Hyperandrogenism and hyperinsulinism

The earliest description of ‘diabete des femmes a barbe’ pointed out the relationship between androgen excess in women and disturbances in carbohydrate metabolism.20 The coexistence of severe insulin resistance and acanthosis nigricans in three lean adolescent women confirmed the association between hyperandrogenism and hyperinsulinism.21 Insulin resistance associated with PCOS was also reported some years later by Chang and colleagues in 1983.22 This resistance, which is independent of obesity, causes hyperinsulinaemia23 and more than 50 per cent of the obese women with PCOS are insulin resistant compared with age and weight-matched controls.24 Hyperinsulinaemia is shown to be a characteristic finding in women with ovarian androgen excess, even in the absence of diabetes. Nowadays, it has become evident that insulin resistance is a cardinal feature of PCOS that could serve as the pathogenic link between hyperandrogenism and hyperinsulinism. Because insulin resistance is related to many manifestations of PCOS, there tends to be substantial overlap between the PCOS phenotype and the so-called ‘metabolic syndrome’ or ‘syndrome X’: obesity, glucose intolerance, hypertension, macrovascular disease and dyslipidaemia, which are seen in both syndromes. Figure 16.2 shows the metabolic and endocrine disorders associated with PCOS and insulin resistance. It is generally accepted that women with PCOS are predisposed to type 2 diabetes and that the development of diabetes cannot be attributed solely to the obesity that typically accompanies PCOS. The prevalence of impaired glucose tolerance in PCOS is between 30 and 40 per cent and that of type 2 diabetes is between 5 and 10 per cent.4, 5 These prevalences approximate those in Pima indians, who have one of the highest rates of diabetes in the world. In addition, suggesting some genetic risk factor in this process, most women and adolescents with PCOS have a family history of type 2 diabetes.25, 26 Elevated serum androgens may at times cause mild insulin resistance but it is unlikely that the insulin resistance of PCOS occurs as a result of hyperandrogenism.27 Insulin resistance persists in women with PCOS in whom both ovaries have been removed surgically or in women whose ovarian androgen production has been suppressed with the use of long-acting gonadotrophin-releasing hormone (GnRH) agonist.1 Pre-pubertal women with acanthosis nigricans are hyperinsulinaemic, yet elevated serum androgen levels do not appear until several years following the diagnosis of insulin resistance. In the same way, some women with point mutations in the insulin receptor gene causing hyperinsulinaemic insulin resistance have been shown to have PCOS. Collectively, the genetic syndromes of severe insulin resistance secondary to mutations in the insulin receptor gene (leprechaunism, Rabson–Mendenhall syndrome and type A insulin resistance syndrome) have a common phenotype characterized by hyperandrogenism, insulin resistance with hyperinsulinism and acanthosis nigricans. These observations support

490

INSULIN RESISTANCE AND POLYCYSTIC OVARY SYNDROME

PCOS Insulin resistance

Obesity

Endocrine disorders

Hyperinsulinaemia

Liver

Ovary

SHBG IGFBP1

Androgen production

Metabolic disorders

Glucose intolerance

Type 2 diabetes

Dyslipidaemia

Metabolic syndrome

Cardiovascular disorders

Figure 16.2

Endocrine and metabolism disorders in PCOS

the idea that the hyperinsulinaemia of PCOS is a causal factor in the accompanying hyperandrogenism.3 It has been suggested that insulin, as IGFI, is capable of enhancing a variety of steroidogenic pathways, not only in ovarian thecal cells, but in ovarian granulosa cells, adrenocortical cells and the periphery. Furthermore, insulin seems to be capable of exerting such effects directly, at elevations too modest to invoke such action via interaction with the IGFI receptor.28 Hyperinsulinaemia appears to be a major factor in the ovarian dysfunction of PCOS. Any treatment that lowers insulin levels produces a decrease in androgen levels and improves ovarian function. The increase in insulin levels common in PCOS may precipitate hyperandrogenaemia in genetically vulnerable individuals by acting through latent abnormalities in steroidogenesis regulation, although it probably has only a minimal effect on ovarian function in many individuals. Paradoxically, hyperinsulinaemia is capable of exerting systemic effects in patients moderately resistant to the effects of insulin on glucose metabolism. Thus, it is capable of lowering IGFBP1 and SHBG concentrations and stimulating ovarian steroidogenesis.

ASSESSMENT OF INSULIN RESISTANCE IN PCOS

491

One plausible hypothesis that tries to explain the relationships between hyperinsulinaemia and hyperandrogenaemia is the unified serine activity in both insulin receptors and cytochrome P450c17. Hormonally regulated serine phosphorylation of adrenal P450c17 by a c-AMP-dependent kinase accounts for a large increase in 17–20 lyase activity and has been proposed as the mechanism for normal adrenarche.29 Phosphorylation studies of the insulin receptors in fibroblasts from PCOS patients have shown that around half of the PCOS women have an increase in serine phosphorylation, which produces an inhibition of tyrosine phosphorylation and a reduction of insulin signal transduction.30 This means that abnormal serine phosphorylation, possibly associated with a single kinase, may be responsible for excessive serine phosphorylation of the insulin receptors and P450c17, leading to insulin resistance and adrenal/ovarian hyperandrogenism. Even though the responsible kinase has not been identified and the explained theory has not been confirmed, recent results suggest that a serine kinase-mediated pathway may be involved in the insulin resistance of PCOS patients.31 At the moment, there is no unified theory to explain a heterogeneous disease such as PCOS, but the key role of insulin in this process is not questioned (Figure 16.1). The onset may occur in late childhood since many of the metabolic and endocrine features of the disorder mimic puberty. Associated with this are increases in the pulse, an amplitude of luteinizing hormone (LH), increasing androgen concentrations, hyperinsulinism and irregular menses. Multiple, small ovarian cysts are seen on ultrasound examination and are a common and normal feature of puberty. It is therefore possible that women genetically predisposed to polycystic ovarian syndrome fail to resume normal insulin sensitivity and continue to express metabolic and endocrine features usually confined to puberty.32, 33

16.4

Assessment of insulin resistance in PCOS

The euglycaemic–hyperinsulinaemic clamp technique34 is the gold standard for assessing insulin sensitivity and it is often combined with the hyperglycaemic clamp to determine the adequacy of compensatory β-cell hypersecretion.35 Insulin resistance and β-cell responsiveness can also be assessed by the frequently sampled intravenous glucose tolerance test.36 However, they cannot be used on a routine clinical basis or epidemiological studies because they are too laborious, time consuming and invasive, especially in children and adolescents. Surrogates based on fasting glucose and insulin and on insulin and glucose responses to oral glucose have often been used. Although assessment of either fasting or peak insulinaemia after OGTT could provide sufficient data to classify individuals into normal, mild to moderate and severe insulin resistance, the results of this test must be interpreted in the context of plasma glucose levels, because the presence of any degree of hyperglycaemia

492

INSULIN RESISTANCE AND POLYCYSTIC OVARY SYNDROME

suggests the existence of defects in insulin secretion, which invalidates the degree of insulinaemia as an index of insulin resistance. Fasting insulin levels above 50–70 µU/ml or insulin peak in post-oral-glucose challenge above 350 µU/ml suggest severe insulin resistance, in contrast to the fasting insulin levels below 20 µU/ml or OGTT peak insulin below 150 µU/ml observed in normal individuals.37 Various indices have been derived from the basis data provided by the oral glucose tolerance test (OGTT) which allow quantitative estimation of β-cell function, such as mean serum insulin index (MSI).38, 39 Measures of insulin sensitivity based on fasting glucose and insulin include the homeostasis model assessment (HOMA),40 fasting insulin resistance index (FIRI),41 fasting glucose insulin ratio,24 and quantitative insulin sensitivity check index (QUICKI)42 and others. Determining the fasting glucose insulin ratio could be a good screening test in that it is simple, quick and relatively inexpensive to obtain a single blood sample, and it has been validated against ‘gold standard’ methodology.43, 44 However, the glucose insulin ratio is most useful in a purely insulin-resistant population, before overt β-cell dysfunction develops. A fasting glucose–insulin ratio of less than seven in girls with premature pubarche or obesity may be helpful in the early identification of those at risk for complications of insulin resistance43 and this finding was recently validated44 by a stepwise regression analysis showing that the fasting glucose–insulin ratio was significantly predictive of insulin sensitivity. A ratio of less than seven is a cut-off for diagnosis of insulin resistance in adolescents with PCOS, and in adult women with PCOS the ratio is less than 4.5.24 As mentioned, measures of insulin sensitivity can also be obtained from the OGTT. Fasting insulin sensitivity and post-oral-glucose compensatory hyperinsulinaemia are closely related, although they do reflect distinct aspects of glucose regulation. Fasting insulin levels reflect hepatic insulin sensitivity and the ability of insulin to suppress hepatic glucose production.45 Post-oral-glucose insulin excursions, on the other hand, in part reflect the need to suppress hepatic glucose production and also the requirement to increase peripheral glucose disposal.45 The high prevalence of impaired glucose tolerance and type 2 diabetes mellitus found in adult women with PCOS was also found in adolescents with PCOS by means of 2 h glucose levels after 75 g glucose challenge.46 To predict these abnormalities the OGTT would be the choice and it was finally recommended that adolescents with PCOS should undergo periodic screening for abnormal glucose tolerance using 2 h post-challenge plasma glucose levels.47

16.5 Gene studies on PCOS Several reports have stressed that PCOS is a familial disorder; however, the genetic basis of the syndrome remains controversial.48

GENE STUDIES ON PCOS

493

It is difficult to determine the mode of inheritance of this heterogeneous syndrome and there is an absence of an equivalent male phenotype. Some studies have revealed an autosomal dominant mode of inheritance considering premature balding in men as the primary male phenotype.49, 50 On the other hand, there are studies of families with high prevalence of PCOS in which the Mendelian autosomal dominant mode of inheritance cannot explain the mode of inheritance of the syndrome,51 while in another study an X-linked model was postulated.52 As a result, the mode of inheritance remains unclear and more than one gene defect seems to participate in the pathogenesis of the syndrome. Thus, PCOS appears to be an oligogenic disorder and several genes may be involved in its aetiology. The presence of insulin resistance and compensatory hyperinsulinaemia led to the assumption that genes involved in the secretion and action of insulin may play a role in the pathogenesis of PCOS. Molecular studies of the coding region of the insulin receptor gene in women with PCOS have shown a large number of silent polymorphisms, mainly in intronic regions. The majority of these polymorphisms have also been identified in normal subjects and are considered to be common polymorphisms, which do not lead to remarkable molecular disturbance in the insulin receptor gene.53 There is, however, evidence of a stable abnormality in insulin receptor phosphorylation in cells from women with PCOS. Increased insulin-dependent serine phosphorylation of the insulin receptor β-subunit in skin fibroblast and skeletal muscle from 50 per cent of the women with PCOS was found compared with controls.30 The serine-phosphorylated insulin receptor had reduced ability to phosphorylate tyrosine, suggesting that it may impair signal transduction. A single-nucleotide polymorphism in the exon 17 C/T of the insulin receptor was most frequently found in lean patients with PCOS compared with lean controls, but the role of this susceptibility needs to be determined.54 The minisatellite of the insulin gene INS VNTR (insulin gene variable number tandem repeats) has been investigated since this region is directly implicated in the regulation of insulin secretion. The INS VNTR is a functional polymorphism, so it regulates the transcription of the insulin gene and probably the expression of the IGF-II gene, which is adjacent to the insulin gene.55 An association between PCOS and allelic variation at the INS VNTR locus has been reported. It was shown that class III alleles and especially III/III genotypes are associated with PCOS and are most strongly associated with anovulatory PCOS. The group of women with one or two class III alleles had significantly higher fasting insulin levels and higher mean body mass index than women with the I/genotype.56 This finding was confirmed in another study.57 Conversely, in another European population of girls who presented with precocious pubarche, hyperinsulinaemia and dyslipidaemia were related to both birth weight and INS VNTR class I alleles.58

494

INSULIN RESISTANCE AND POLYCYSTIC OVARY SYNDROME

Other candidate genes in the pathogenesis of PCOS are the encoding genes of steroidogenic enzymes, such as CYP17, CYP11α and CYP19. Recent studies have shown that PCOS may be the result of overfunction of the enzyme that catalyses androgen production (cytochrome P450c17α). Cytochrome P450c17α is an enzyme with two functions, since it has both 17 α-hydroxylase and 17,20-lyase activities. In the thecal cells P450c17α converts progesterone to 17 α-hydroxyprogesterone through its 17 α-hydroxylase activity, and then it converts 17 α-hydroxyprogesterone to androstendione through its 17,20-lyase activity.15 Clinical studies have shown an abnormality in the regulation of 17 α-hydroxylase/17,20-lyase (the rate-limiting step in androgen biosynthesis in the ovaries and the adrenals) in women presenting with PCOS, as evidenced by increased 17 α-hydroxylase and to a lesser extent 17,20-lyase activity, since in these women there is an exaggerated serum 17α-hydroxyprogesterone to stimulation by gonadotrophin-releasing hormone agonists, as already mentioned.19 The other gene involved in the steroidogenic pathway is CYP11α, which encodes P450scc, the enzyme for cholesterol side chain cleavage that catalyses the conversion of cholesterol to pregnenolone, which is the initial and ratelimiting step at the start of the steroid hormone biosynthetic pathway. It has been hypothesized that up-regulation of this enzyme could lead to increased androgen production.59 After some contradictory results, no association was found between any of the alleles of the CYP11α and the presence of PCOS.60, 61 The enzyme aromatase encoded by CYP19 catalyses the conversion of androgens to oestrogens. It has been found that granulosa cells from anovulatory polycystic ovaries are hyper-responsive to follicle-stimulating hormone (FSH) in vitro, displaying significantly greater oestradiol production than granulosa cells from normal ovaries.62 So far, there is no evidence of any association of alleles of this gene with PCOS.63 The androgen receptor, through which all androgens act, has also been investigated, especially the polymorphic CAG repeat within exon 1, which encodes a polyglutamine chain in the N-terminal transactivation domain.64 The length of the polymorphic CAG repeat sequence is inversely correlated to the androgen receptor transcriptional activity. An association between increased hirsutism and decreased CAG repeat length has been demonstrated.65, 66 However, further studies need to be conducted to analyse the role of androgen receptors in the pathogenesis of PCOS. Another gene studied to analyse the possible genetic origin of PCOS is LH β-subunit gene; since about 50 per cent of women with PCOS have hypersecretion of LH associated with anovulation, an adverse role of LH gene may be suspected. One polymorphic variant seems to protect obese women from developing symptomatic PCOS,67 but another LH variant has been identified as a result of

PREMATURE PUBARCHE, HYPERINSULINISM AND PCOS

495

a single missense mutation in exon 3 of the LH β-subunit gene. This variant seems to play a role in female infertility but further studies are required to determine the pathological significance of this variant.68 Recent investigations have shown an association between PCOS and follistatin,60 but the contribution of follistatin gene in the development of PCOS has not been confirmed.69, 70

16.6 Premature pubarche, hyperinsulinism and PCOS Premature pubarche is defined as the early appearance of pubic hair, before 8 years in girls and 9 years in boys, independently of the appearance of axillary hair and apocrine secretion, and of pubertal development. The incidence of premature pubarche is almost tenfold higher in girls than in boys. In most cases, premature pubarche is due to an exaggerated variant of normal maturation of adrenal gland function being a most frequent form of hyperandrogenism in the pre-pubertal period.71 Enzymatic defects of steroidogenesis are pathological causes of premature pubarche, with a reported frequency around seven per cent in these girls.72 Genetic defects in the CYP21 gene, which encodes the 21 hydroxylase enzyme, have been investigated, and the incidences of molecular defects were comparable in the premature pubarche and control groups. There is no relationship between the presence of carrier status and endocrine–metabolic abnormalities.73 Prospective studies of larger cohorts of premature pubarche girls are needed to ascertain the long-term clinical relevance of CYP21 heterozygosity. In the absence of an adrenal enzymatic defect, premature pubarche has been associated with an acceleration of statural growth and bone maturation, without affecting the timing of the onset or the progression of puberty or the final height.74 Re-evaluation of adrenal function in young women with a history of premature pubarche revealed an increased incidence of so called ‘idiopathic functional adrenal hyperandrogenism’. A pattern of adrenal secretion that affects 50 per cent of these girls gives rise to a suprahormonal response to ACTH test. Idiopathic functional adrenal hyperandrogenism has been attributed to a dysregulation of adrenal cytochrome P450c17, prominently in the
5 pathway.75 Post-pubertal follow-up of girls with premature pubarche has documented more than tenfold prevalence of ‘functional ovarian hyperandrogenism’ (45 versus 3 per cent in the normal adolescent population), a form of PCOS at adolescence, which is usually associated with hyperinsulinaemia and dyslipidaemia.46, 76 This sequence seems to occur more frequently in girls with elevated DHEAS and or androstenedione at diagnosis of premature pubarche.77 Assessment of ovulatory function in girls with a history of precocious pubarche revealed that the fractions of ovulating girls and ovulatory cycles in late post-menarche were strikingly higher (P < 0.001) in the non-premature

496

INSULIN RESISTANCE AND POLYCYSTIC OVARY SYNDROME

pubarche than in the premature pubarche subgroup (91 versus 20 and 47 versus 12 per cent), with no differences in early post-menarche.78 It could be assumed that the development of ovarian hyperandrogenism after premature pubarche is preceded by an apparently normal phase, with regular cycles lasting for about 3–5 years after menarche. In general, puberty is associated with increasing fasting and glucosestimulated insulin concentrations and a decrease in insulin sensitivity.79, 33 The insulin resistance during puberty is restricted to peripheral glucose metabolism and is associated with concomitant increases in growth hormone and insulinlike growth factor (IGFI) secretion and a decrease in IGFBP1 and SHBG concentrations.80 The hyperinsulinaemia and increased IGFI activity during puberty have been proposed as inducing factors in the development of PCOS in susceptible subjects.32, 81 In girls with premature pubarche, hyperinsulinism is already detectable before puberty and throughout all states of pubertal development. It is often accompanied by an increased early insulin response to glucose, by an elevated free androgen index and by decreased IGFBP1 and SHBG concentrations.46 In addition to hyperinsulinaemia, girls with premature pubarche display supranormal triglyceride levels, very low density lipoprotein cholesterol, and very low density lipoprotein triglyceride concentrations.76 Both hyperinsulinaemia and altered lipid profile support the concept that the cluster of highly atherogenic abnormalities may already start by childhood, in agreement with other studies pointing towards an early development of the pathophysiological events leading to type 2 diabetes and cardiovascular disease.82 The frequent association of premature pubarche with functional ovarian hyperandrogenism and hyperinsulinism could have in common early origin rather than being the result of a direct inter-relationship later in life. Reduced foetal growth was first related to type 2 diabetes in older adults83 and also was found to be associated with insulin resistance in pre-pubertal and post-pubertal children born small for gestational age.84, 85 Girls with premature pubarche have lower birth-weight standard deviation (SD) scores than control girls.86 Those girls with premature pubarche who subsequently develop functional ovarian hyperandrogenism have even lower birth weights. Finally, the lowest birth weights were found in girls with – in addition – pronounced hyperinsulinism86 (Figure 16.3). The precise mechanism governing the aforementioned relationship is currently unknown, but the results seem to suggest that premature pubarche and hyperinsulinaemia may precede the development of ovarian hyperandrogenism, and possibly PCOS, and that this sequence may have a common early origin (low birth weight serving as a marker). These data support the early life hypothesis that disease in post-natal life may have its origin in the foetal environment, and that this process can be attributed to changes in the programming of foetal endocrine axes.83

TREATMENT APPROACH WITH ANTIANDROGENS

∗

∗

1 Birth-weight SDS

497

∗

0 −1 −2

∗

−3

p ≤ 0.01 ± Std. dev. ± Std. err. Mean

Precocious pubarche Ovarian hyperandrogenism Hyperinsulinism

– – – n = 31

+ – – n = 25

+ + – n = 12

+ + + n = 11

Figure 16.3 Birth-weight scores of post-menarcheal control girls (−, − and −) and postmenarcheal girls with a history of premature pubarche without ovarian hyperandrogenism and without hyperinsulinaemia (+, − and −), with ovarian hyperandrogenism and without hyperinsulinaemia (+, + and −) and with both ovarian hyperandrogenism and hyperinsulinaemia (+, + and +) (J Clin Endocrinol Metab 1998, 83, 3558–3562, (with permission)

The follow-up related findings in girls with premature pubarche suggest that this process should no longer be considered a normal variant of development but rather a clinical marker of endocrine–metabolic disorders associated with reduced foetal growth.

16.7 Treatment approach with antiandrogens Current treatments until now have been addressed to reduce the main presenting features such as irregular menses, hirsutism or infertility. Oral contraceptives are commonly used to regulate menses and decrease ovarian androgen production. Increasing levels of sex-hormone-binding globulin while decreasing ovarian androgen production reduces the circulating free testosterone and subsequently androgen activity; however, the combined pill exacerbates insulin resistance, mainly in obese patients, in whom this treatment may be unsuitable. Hirsutism may be addressed by the use of antiandrogens, cyproterone acetate or spironolactone. Their principal mode of action is the inhibition of the binding of dihydrotestosterone to its receptors at the hair follicle. Beneficial effects can be seen after some months of treatment, but excessive hair growth returns soon after cessation of treatment. Cyproterone acetate may exacerbate irregularity of the menstrual cycle, and both drugs are unsuitable for use in those trying to conceive. Another alternative approach to be used is finasteride, an inhibitor of the type 2 isoenzyme of 5α-reductase, the enzyme responsible for conversion of testosterone

498

INSULIN RESISTANCE AND POLYCYSTIC OVARY SYNDROME

to the active metabolite dihydrotestosterone. The other one is flutamide, the most common antiandrogen used as a therapeutic regime in the treatment of hirsutism. Flutamide is a non-steroidal compound that seems to act only at the receptor site and is therefore considered a pure antiandrogen. Liver toxicity is a rare but potentially severe side-effect of flutamide, which is dose dependent. Several recent papers have been published evaluating treatment results of PCOS with flutamide, spironolactone, cyproterone acetate, ketoconazole and finasteride.87 – 89 Those drugs employed currently constitute a satisfactory alternative therapeutic regime in the treatment of hyperandrogenism. However, a long treatment period is always required to improve hirsutism and prevent or delay its relapse.87 The reduction of androgen levels by flutamide restores normal ovarian regulation of GnRH secretion in PCOS and may have a place in the therapeutic regime aimed at establishing cyclic ovulation in women with PCOS.89 According to our results,88 flutamide treatment was accompanied by a marked decrease in hirsutism score, free androgen index, testosterone and androstenedione levels and by an increase in sex-hormone-binding globulin concentrations. However, there were no substantial changes in the pattern of menstrual cycles, gonadotropin, oestradiol or dehydroepiandrosterone sulfate concentrations, and there were no detectable effects on the 17-hydroxyprogesterone response to GnRH agonist. Serum triglycerides, total cholesterol and low-density lipoprotein cholesterol levels decreased markedly during flutamide therapy, whereas high-density lipoprotein cholesterol, fasting glycaemia–insulinaemia and the insulin response to a glucose load remained unchanged. In conclusion, low dose flutamide treatment was found to be an effective and safe approach to reduce hirsutism and circulating androgen, low-density lipoprotein cholesterol and triglyceride levels in girls with functional ovarian hyperandrogenism after premature pubarche.88 However, flutamide failed to increase high-density lipoprotein cholesterol levels or decrease hyperinsulinaemia, these being two major risk factors for subsequent cardiovascular disease.

16.8

Treatment approach with insulin sensitizers (metformin)

Taking into consideration the aforementioned, the administration of insulin sensitizer drugs such as metformin or thiazolidinediones could potentially reverse the metabolic process and restore the ovarian function. Several reports have been published in recent years addressing evaluation of the effect of insulin sensitizer agents in PCOS women, such as biguanides and thiazolidinediones (metformin and troglitazone). Most of the metabolic abnormalities of PCOS can be reversed by metformin, with the additional benefit of enough normalization of the endocrine milieu to allow regular menstrual cycles, reversal of infertility and spontaneous pregnancy. Thus, one report,90 despite the short treatment period (8 weeks), was able to show

TREATMENT APPROACH WITH INSULIN SENSITIZERS (METFORMIN)

499

an improvement in insulin sensitivity associated with decrease in serum LH and androgens. In contrast, it has been shown91 that the administration of metformin in 24 obese women, presenting with hirsutism according to the criteria of Ferriman and Gallwey had no additional benefit over the effect of low caloric diet in improving hyperinsulinaemia and hyperandrogenaemia. Moreover, in this study there was no control group for the weight loss intervention. Recently, a study has been published that supported the Vel´azquez et al. results, in which administration of metformin in obese women with PCOS reduces ovarian cytochrome P450c17 activity and ameliorates hyperandrogenism and hirsutism by decreasing insulin concentrations. In these women the exaggerated serum 17α-hydroxyprogesterone response to stimulation by gonadotropin-releasing hormone agonist was reduced after metformin treatment.92 On the other hand, contradictory results were obtained in a study with a limited number of PCOS women with moderate to extreme obesity. The study concluded that hyperinsulinaemia and androgen excess in obese non-diabetic women with PCOS were not improved by the administration of metformin.93 Subsequently, one further study has been published to assess menstrual cyclicity in 40 oligoamenorrheic women with PCOS. After a six-month course of metformin an improvement in menstrual cyclicity and fertility was seen.94 Another aspect that could be modified by metformin is the ovulatory response to clomiphene. The frequency of spontaneous ovulation and ovulation induced by clomiphene can be increased in obese women with PCOS by decreasing serum insulin concentration with metformin.95 An improvement in menstrual pattern after metformin treatment has also been described and confirmed that, by reducing hyperinsulinism, metformin determines a reduction in intraovarian androgens.96 This leads to a reduction in oestradiol levels and favours orderly follicular growth in response to exogenous gonadotropins.97 In PCOS women with abdominal obesity, long-term treatment induced reduction in body mass index associated with a significant improvement of hirsutism and menses abnormalities.98 Moreover, the 17-hydroxyprogesterone response to human chorionic gonadotropin was lower after metformin treatment,99 giving a direct demonstration that metformin leads to a reduction in stimulated ovarian cytochrome P450c17 activity, concomitantly with a reduction in basal insulin and testosterone levels and a significant increase in SHBG and IGFBP1.100 In conclusion, metformin reduced hyperinsulinaemia and hyperandrogenaemia, independently of changes in body weight. In a large number of subjects these changes were associated with striking sustained improvements in menstrual abnormalities and resumption of ovulation.101 Although not reported by all investigators, metformin seems to cause a decline in insulin levels and reverses metabolic and ovarian abnormalities. Many of these changes occur even in the absence of changes in body mass index. The action of metformin is not fully known. It inhibits hepatic glucose production and increases peripheral tissue sensitivity to insulin. In vitro

500

INSULIN RESISTANCE AND POLYCYSTIC OVARY SYNDROME

therapeutic concentrations of metformin have been shown to stimulate the tyrosine kinase activity of the intracellular portion of the β-subunit of the human insulin receptors.102 We reported the results of 10-month treatment with metformin (850 mg twice daily) in a lean girl aged 13 years and 6 months with severe hirsutism, acne, clitoral hypertrophy, acanthosis nigricans and primary amenorrhea. Hormonal assessment Glucose (mg/dL)

MSI (mU/L)

120 100 80 50 40

0 Metformin

–

NS

NS

+

–

0

Ferriman & Gallwey 20

Metformin

Free Androgen Index

0

**

*** +

–

75

100

50

50

25

–

*** +

*** +

–

HDL (mg/dL)

150

***

** –

LDL (mg/dL)

Metformin

–

5

–

0

*** +

10

10

0

*** –

0 –

**

**

–

+

–

Figure 16.4 Clinical, endocrine and metabolic values before metformin treatment (−) after 6 months of treatment (+) and 3 months after treatment (−) in adolescent girls with hirsutism, hyperandrogenism, oligomenorrhea, dyslipidaemia and hyperinsulinism after precocious pubarche. The top panel displays fasting glucose and mean serum insulin (MSI) during OGTT. The middle panel shows changes in hirsutism score and FAI. The bottom panel shows changes in serum LDL and HDL cholesterol (J Clin Endocrinol Metab 2000, 85, 3526–3530, with permission)

TREATMENT APPROACH WITH INSULIN SENSITIZERS

501

showed a severe insulin resistance with hyperinsulinaemia and hyperandrogenaemia. Molecular analysis of the insulin receptor gene showed a heterozygous missense mutation (Val 1028) in exon 17 of the insulin receptor, abolishing autophosphorylation of the insulin receptor β-subunit. Basal androgens and fasting insulin concentrations decreased significantly during treatment, whereas SHBG concentration increased. Breast development progressed and menarche occurred in the fifth month of therapy. No side-effects were documented.103 The results commented on above encourage the use of metformin in hyperinsulinaemic and hyperandrogenic women, but at present few studies have addressed the use of metformin in children as a treatment for either insulin resistance PCOS.104 In non-obese adolescent girls with hirsutism, hyperinsulinism, hyperandrogenism and dyslipidaemia, metformin therapy tends to normalize these abnormalities in concert.105 Thus, in non-obese girls with an adolescent variant of PCOS, insulinsensitizing treatment reduces hyperinsulinism, dyslipidaemia and hyperandrogenism and restores eumenorrhea and also induced ovulation106 (Figure 16.4). In conclusion, metformin was found to be an effective approach to reverse metabolic and ovarian abnormalities even in adolescent girls. Prolonged treatment with metformin has been proved to be safe in type 2 diabetes mellitus and in a pregnant hyperandrogenic woman.107 The most common morbidity associated with its use is gastrointestinal distress, specifically diarrhoea and abdominal pain, which is often transient and seems to be lessened if the dose is gradually increased.

16.9

Treatment approach with insulin sensitizers (thiazolidinediones)

Another class of insulin-sensitizing agents, the thiazolidinediones, have been used to improve PCOS abnormalities. These drugs require the presence of insulin, but they do not stimulate insulin secretion. They mainly activate a nuclear receptor called PPARγ (peroxisome proliferator-activated receptor gamma), which is most strongly expressed in adipose tissue. Activated PPARγ increases transcription of certain insulin-sensitive genes, including those that code for GLUT4 glucose transporters and enzymes for lipogenesis. The first thioglitazonedione, troglitazone, was introduced in Japan and the USA in 1997 and withdrawn in 2000 due to reports of fatal idiosyncratic hepatotoxicity.108 Other thiazolidinediones such as rosiglitazone and pioglitazone have little evidence of hepatotoxicity, except two non-fatal cases of hepatocellular damage observed with the initiation of rosiglitazone therapy. Thus, monitoring of serum alanine transaminase should be performed before starting and during therapy.109, 110 Dunaif et al.111 evaluated 21 PCOS subjects who received either 200 or 400 mg/day troglitazone for 12 weeks in a randomized, double-blind study. Treatment with troglitazone resulted in significant improvement in insulin action. Increases in insulin sensitivity were significant at both doses of troglitazone

502

INSULIN RESISTANCE AND POLYCYSTIC OVARY SYNDROME

but were more marked at 400 mg than at 200 mg. This was accompanied by decreases in circulating insulin levels, both basally and after glucose load, which were accounted for almost entirely by changes at 400 mg troglitazone dose. In this report, insulin sensitivity was improved independent of weight loss and hyperandrogenism was ameliorated. The author claimed111 that this observation is consistent with the hypothesis that hyperinsulinaemia contributes to hyperandrogenism in PCOS. However, the apparent dose-related effect suggests that these changes were troglitazone mediated. Recently it could also be demonstrated that troglitazone improves the ovulatory dysfunction, hirsutism, hyperandrogenemia and insulin resistance of PCOS in a dose-related fashion, with a minimum of adverse effects.112 It should be noted that none of the insulin-sensitizing drugs have Food and Drug Administration (FDA) approval for use in PCOS, hirsutism or hyperandrogenism with insulin resistance. Considering that women with PCOS may have insulin resistance secondary to a deficiency of D-chiro-inositol-containing phosphoglycans that mediate insulin action, the administration of this substance could improve insulin sensitivity. According to this hypothesis D-chiro-inositol increased insulin action in patients with PCOS, thereby improving ovulatory function and decreasing serum androgen concentrations, hirsutism, blood pressure and plasma triglyceride concentrations.113 The aforementioned results using insulin sensitizers give grounds for considering them a therapeutic approach for PCOS, alone or combined with antiandrogenic drugs or oral contraceptives.

16.10

Conclusion

The therapeutical interventions with insulin-sensitizing agents corroborate the idea that insulin resistance with hyperinsulinaemia may indeed be a prime factor underpinning the metabolic and hormonal disorders affecting anovulatory and ovarian hyperandrogenic women and adolescents. Randomized, controlled trials with safe insulin sensitizers will have to be conducted, especially in young women and adolescents with hyperinsulinism and anovulatory hyperandrogenism in an attempt to normalize insulin sensitivity and ovarian function. Considering that insulin sensitizers have less effect on hirsutism than antiandrogens, these drugs could be combined with an antiandrogen such as flutamide at low doses. Again, collaborative randomized trials in wide populations should be conducted to assess treatment results of the clinical and metabolic abnormalities in women and adolescents.

References 1. Franks, S. (1995) Medical progress article: polycystic ovary syndrome. N Engl J Med 333, 853–861.

REFERENCES

503

2. Knochenhauer, E. S., Key, T. J., Kahsar-Miller, M., Waggoner, W., Boots, L. R. and Azziz, R. (1998) Prevalence of the polycystic ovary syndrome in unselected Black and White women of the Southeastern United States: a prospective study. J Clin Endocrinol Metab 83, 3078–3082. 3. Dunaif, A. (1997) Insulin resistance and the polycystic ovary syndrome: mechanism and implications for pathogenesis. Endocr Rev 18, 774–800. 4. Ehrmann, D. A., Barnes, R. B., Rosenfield, R. L., Cavaghan, M. K. and Imperial, J. (1999) Prevalence of impaired glucose tolerance and diabetes in women with polycystic ovary syndrome. Diabetes Care 22, 141–146. 5. Legro, R. S., Kunselman, A. R., Dodson, W. C. and Dunaif, A. (1999) Prevalence and predictors of risk for type 2 diabetes mellitus and impaired glucose tolerance in polycystic ovary syndrome: a prospective, controlled study in 254 affected women. J Clin Endocrinol Metab 84, 165–169. 6. Zawadski, J. K. and Dunaif, A. (1992) Diagnostic criteria for polycystic ovary syndrome: towards a rational approach. In: Dunaif, A., Givens, J. R., Haseltine, F. and Merriman, G. R., eds. Polycystic Ovary Syndrome. Boston, MA: Blackwell, 377–384. 7. Bridges, N. A., Cooke, A., Healy, M. J. R., Hindmarsh, P. C. and Brook, C. G. (1993) Standard for ovarian volume in childhood and puberty. Fertil Steril 60, 456–460. 8. Diamanti-Kandarakis, E., Kouli, C. R., Bergiele, A. T., Filandra, F. A., Tsianateli, C., Spina, G. G., Zapanti, E. P. and Bartzis, M. I. (1999) A survey of the polycystic ovary syndrome in the Greek island of Lesbos: hormonal and metabolic profile. J Clin Endocrinol Metab 84, 4006–4011. 9. Asunci´on, M., Calvo, R. M., San Millan, J. L., Sancho, J., Avila, S. and EscobarMorreale, H. F. (2000) A prospective study of the prevalence of the polycystic ovary syndrome in unselected Caucasian women from Spain. J Clin Endocrinol Metab 85, 2434–2438. 10. Barbieri, R. L. (1994) Hyperandrogenism, insulin resistance and acanthosis nigricans: 10 years of progress. J Reprod Med 39, 327–336. 11. Ferriman, D. and Gallwey, J. D. (1961) Clinical assessment of body hair growth in women. J Clin Endocrinol Metab 21, 1440–1447. 12. Adams, J., Franks, S., Polson, D. W., Mason, H. D., Abdulwahid, N., Tucker, M., Morris, D. V., Price, J. and Jacobs, H. S. (1985) Multifollicular ovaries: clinical and endocrine features and response to pulsatile gonadotropin-releasing hormone. Lancet 2, 1375–1379. 13. Polson, D. W., Wadsworth, J., Adams, J. and Franks, S. (1988) Polycystic ovaries: a common finding in normal women. Lancet 1, 870–872. 14. Lucciano, A. A., Chapler, F. K. and Serman, B. M. (1984) Hyperprolactinemia in the polycystic ovary syndrome. Fertil Steril 41, 719–725. 15. Rosenfield, R. L., Barnes, R. B., Cara, J. F. and Lucky, A. W. (1990) Dysregulation of cytochrome P450c17α as the cause of polycystic ovarian syndrome. Fertil Steril 53, 785–791. 16. Ib´an˜ ez, L., Potau, N., Zampolli, M., Prat, N., Gussiny´e, M., Saenger, P., VicensCalvet, E. and Carrascosa, A. (1994) Source localization of androgen excess in adolescent girls. J Clin Endocrinol Metab 79, 1778–1784. 17. Ib´an˜ ez, L., Hall, J., Potau, N., Carrascosa, A., Prat, N. and Taylor, A. (1996) Ovarian 17hydroxyprogesterone hyperresponsiveness to gonadotropin-releasing hormone (GnRH) agonist challenge in women with polycystic ovary syndrome is not mediated by luteinizing hormone hypersecretion: evidence from GnRH agonist and human chorionic gonadotropin stimulation testing. J Clin Endocrinol Metab 81, 4103–4107.

504

INSULIN RESISTANCE AND POLYCYSTIC OVARY SYNDROME

18. Gilling-Smith, C., Story, H., Rogers, V. and Franks, S. (1997) Evidence for a primary abnormality of thecall cell steroidogenesis in the polycystic ovary syndrome. Clin Endocrinol 47, 93–99. 19. Rosenfield, R. L., Barnes, R. B. and Ehrmann, D. A. (1994) Studies of the nature of 17hydroxyprogesterone hyperresponsiveness to gonadotropin-releasing agonist challenge in functional ovarian hyperandrogenism. J Clin Endocrinol Metab 79, 1686–1692. 20. Archard, C. and Thiers, J. (1921) Le virilisme filaire et son association a l’insuffisance glycolytique (diabete des femmes a barbe). Bull Acad Natl Med 86, 51–64. 21. Kahn, C. R., Fliers, J. S., Bar, R. S., Archer, J. A., Gorden, P., Martin, M. M. and Roth, J. (1976) The syndromes of insulin resistance and acanthosis nigricans. N Engl J Med 294, 739–745. 22. Chang, R. J., Nakamura, R. M., Judd, H. L. and Kaplan, S. A. (1983) Insulin resistance in nonobese patients with polycystic ovarian disease. J Clin Endocrinol Metab 57, 356–359. 23. Dunaif, A., Segal, K. R., Futterweit, W. and Dobrjansky, A. (1989) Profound peripheral insulin resistance, independent of obesity, in polycystic ovary syndrome. Diabetes 38, 1165–1174. 24. Legro, R. S., Finegood, D. and Dunaif, A. (1998) A fasting glucose to insulin ratio is a useful measure of insulin sensitivity in women with polycystic ovary syndrome. J Clin Endocrinol Metab 83, 2694–2698. 25. Sir-Peterman, T., Angel, B., Maliqueo, M., Carvajal, F., Santos, L. and P´erez-Bravo, F. (2002) Prevalence of type II diabetes mellitus and insulin resistance in parents of women with polycystic ovary syndrome. Diabetologia 45, 959–964. 26. Ib´an˜ ez, L., Castell, C., Tresserras, R. and Potau, N. (1999) Increased prevalence of type 2 diabetes mellitus and impaired glucose tolerance in first-degree relatives of girls with a history of precocious pubarche. Clin Endocrinol 51, 395–401. 27. Speiser, P. W., Serrat, J., New, M. I. and Gertner, J. M. (1992) Insulin insensitivity in adrenal hyperplasia due to nonclassical steroid 21-hydroxylase deficiency. J Clin Endocrinol Metab 75, 1421–1424. 28. Rosenfield, R. L. (1999) Ovarian and adrenal function in polycystic ovary syndrome. Endocrinol Metab Clin North Am 28, 265–293. 29. Zhang, L. H., Rodriguez, H., Ohno, S. and Miller, W. L. (1995) Serine phosphorylation of human P450c17α increases 17,20-lyase activity: implications for adrenarche and polycystic ovary syndrome. PNAS 92, 10 619–10 623. 30. Dunaif, A., Xia, J., Book, C. B., Schenker, E. and Tang, Z. (1995) Excessive insulin receptor serine phosphorylation in cultured fibroblasts and in skeletal muscle. A potential mechanism for insulin resistance in the polycystic ovary syndrome. J Clin Invest 96, 801–810. 31. Li, M., Youngren, J. F., Dunaif, A., Goldfine, I. D., Maddux, B. A., Zhang, B. B. and Evans, J. (2002) Decreased insulin receptor (IR) autophosphorylation in fibroblast from patients with PCOS: Effects of serine kinase inhibitors and IR activators. J Clin Endocrinol Metab 87, 4088–4093. 32. Nobels, F. and Dewailley, D. (1992) Puberty and polycystic ovary syndrome: The insulin/insulin-like growth factor hypothesis. Fertil Steril 58, 655–663. 33. Potau, N., Ib´an˜ ez, L., Riqu´e, S. and Carrascosa, A. (1997) Pubertal changes in insulin secretion and peripheral insulin sensitivity. Horm Res 48, 219–226. 34. DeFronzo, R. A., Tobin, J. D. and Andres, R. (1979) Glucose clamp technique: a method for quantifying insulin secretion and resistance. Am J Physiol 237, E214–E223. 35. Polonsky, K. S., Given, B. D., Hirsch, L., Shapiro, E. T., Tillil, H., Beebe, C., Galloway, J. A., Frank, B. H., Karrison, T. and Van Cauter, E. (1988) Quantitative study of insulin secretion and clearance in normal and obese subjects. J Clin Invest 81, 435–441.

REFERENCES

505

36. Bergman, R. N., Prager, R., Volund, A. and Olefsky, J. M. (1987) Equivalence of the insulin sensitivity index in man derived by the minimal model method and the euglycemic glucose clamp. J Clin Invest 79, 790–800. 37. Tritos, N. A. and Mantzoros, C. S. (1998) Syndromes of severe insulin resistance. J Clin Endocrinol Metab 83, 3025–3030. 38. Cederholm, J. and Wibell, L. (1990) Insulin release and peripheral sensitivity at the oral glucose tolerance test. Diabetes Res Clin Pract 10, 167–175. 39. Matsuda, M. and DeFronzo, R. A. (1999) Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care 22, 1462–1470. 40. Matthews, D. R., Hosker, J. P., Rudenski, A. S., Naylor, B. A., Treacher, D. F. and Turner, R. C. (1985) Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28, 412–419. 41. Duncan, M. H., Singh, B. M., Wise, P. H., Carter, G. and Alaghband-Zadeh, J. (1995) A simple measure of insulin resistance. Lancet 346, 120–121. 42. Katz, A., Nambi, S. S., Mather, K., Baron, A. D., Follmann, D. A., Sullivan, G. and Quon, M. J. (2000) Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab 85, 2402–2410. 43. Silfen, M. E., Manibo, A. M., McMahon, D. J., Levine, L. S., Murphy, A. R. and Oberfield, S. E. (2001) Comparison of simple measures of insulin sensitivity in young girls with premature adrenarche: the fasting glucose to insulin ratio may be a simple and useful measure. J Clin Endocrinol Metab 86, 2863–2868. 44. Vuguin, P., Saenger, P. and DiMartino-Nardi, J. (2001) Fasting glucose insulin ratio: a useful measure of insulin resistance in girls with premature adrenarche. J Clin Endocrinol Metab 86, 4681–4621. 45. Kahn, S. E., Prigeon, R. L., McCulloch, D. K., Boyko, E. J., Bergman, R. N., Schwartz, M. W., Neifing, J. L., Ward, W. K., Beard, J. C., Palmer, J. P. and Porte, D. (1993) Quantification of the relationship between insulin sensitivity and beta-cell function in human subjects. Evidence for a hyperbolic function. Diabetes 42, 1663– 1672. 46. Ib´an˜ ez, L., Potau, N., Zampolli, M., Prat, N., Virdis, R., Vicens-Calvet, E. and Carrascosa, A. (1996) Hyperinsulinemia in postpubertal girls with a history of premature pubarche and functional ovarian hyperandrogenism. J Clin Endocrinol Metab 81, 1237–1243. 47. Palmert, M. R., Gordon, C. M., Kartashov, A. I., Legro, R. S., Emans, S. J. and Dunaif, A. (2002) Screening for abnormal glucose tolerance in adolescents with polycystic ovary syndrome. J Clin Endocrinol Metab 87, 1017–1023. 48. Franks, S., Gharani, N., Waterworth, D., Batty, S., White, D., Williamson, R. et al. (1997) The genetic basis of polycystic ovary syndrome. Hum Reprod 12, 2641–2648. 49. Ferriman, D. and Purdie, A. W. (1979) The inheritance of polycystic ovary syndrome and possible relationship to premature balding. Clin Endocrinol 11, 291–300. 50. Carey, A. H., Chan, K. L., Short, F., White, D., Williamson, R. and Franks, S. (1993) Evidence for a single gene effect causing polycystic ovaries and male pattern baldness. Clin Endocrinol 38, 653–658. 51. Hague, W. M., Adams, J., Reeders, S. T., Peto, T. E. and Jacobs, H. S. (1988) Familial polycystic ovaries: a genetic disease?. Clin Endocrinol 25, 593–605. 52. Givens, J. R. (1988) Familial polycystic ovarian disease. Endocrinol Metab Clin North Am 17, 771–783.

506

INSULIN RESISTANCE AND POLYCYSTIC OVARY SYNDROME

53. Talbot, J. A., Bicknell, E. J., Ranjhowa, M., Krook, A., O’Rahilly, S. and Clayton, R. N. (1996) Molecular scanning of the insulin receptor gene in women with polycystic ovarian syndrome. J Clin Endocrinol Metab 81, 1979–1983. 54. Siegel, S., Futterweit, W., Davies, T. F., Concepcion, E. S., Greenberg, D. A., Villanueva, R. and Tomer, Y. (2002) A C/T single nucleotide polymorphism at the tyrosine kinase domain of the insulin receptor gene is associated with polycystic ovary syndrome. Fertil Steril 78, 1240–1243. 55. Paquette, J., Giannoukakis, N., Polychronakos, C., Vafiadis, P. and Deal, C. (1998) The INS. 5
variable number of tandem repeats is associated with IGF-II expression in humans. J Biol Chem 273, 14 158–14 164. 56. Waterworth, D. M., Bennett, S. T., Gharani, N., McCarthy, M. I., Hague, S., Batty, S., Conway, G. S., White, P., Todd, J. A., Franks, S. and Williamson, R. (1997) Linkage and association of insulin gene VNTR regulatory polymorphism with ovary syndrome. Lancet 349, 986–990. 57. Michelmore, K., Ong, K., Mason, S., Bennett, S., Perry, L., Vessey, M., Balen, A. and Dunger, D. (2001) Clinical features in women with polycystic ovaries: relationships to insulin sensitivity, insulin gene VNTR and birth weight. Clin Endocrinol 55, 439–446. 58. Ib´an˜ ez, L., Ong, K., Potau, N., Marcos, M. V., De Zegher, F. and Dunger D (2001) Insulin gene variable number of tandem repeat genotype and the low birth weight, precocious pubarche and hyperinsulinism sequence. J Clin Endocrinol Metab 86, 5788–5793. 59. Miller, W. L. (1988) Molecular biology of steroid hormone synthesis. Endocr Rev 9, 295–318. 60. Urbanek, M., Legro, R. S., Driscoll, D. A., Azziz, R., Ehrmann, D. A., Norman, R. J., Strauss, J. F., Spielman, R. S. and Dunaif, A. (1999) Thirty-seven candidate genes for polycystic ovary syndrome: strongest evidence for linkage is with follistation. PNAS 96, 8573–8578. 61. San Millan, J. L., Sancho, J., Calvo, R. M. and Escobar-Morreale, H. F. (2001) Role of the pentanucleotide (tttta)n polymorphism in the promoter of the CYP11α gene in the pathogenesis of hirsutism. Fertil Steril 75, 797–802. 62. Mason, H. D., Willis, D. S., Beard, R. W., Winston, R. M. L., Margara, R. and Franks, S. (1994) Estradiol production by granulosa cells of normal and polycystic ovaries: relationship to menstrual cycle and concentration of gonadotropins and sex steroids in follicular fluid. J Clin Endocrinol Metab 79, 1355–1360. 63. Gharani, N., Waterworth, D. M., Batty, S., White, D., Gilling-Smith, C., Conway, G. S., McCarthy, M., Franks, S. and Williamson, R. (1997) Association of the steroid synthesis gene CYP11a with polycystic ovary syndrome and hyperandrogenism. Hum Mol Genet 6, 397–402. 64. Carson-Jurica, M. A., Schrader, W. T. and O’Malley, B. W. (1990) Steroid receptor family: structure and function. Endocr Rev 11, 201–218. 65. Legro, R. S., Shahbahrami, B., Lobo, R. A. and Kovacs, B. W. (1994) Size polymorphisms of the androgen receptor among female Hispanics and correlation with androgenic characteristics. Obstet Gynecol 83, 701–706. 66. Sawaya, M. E. and Shalita, A. R. (1998) Androgen receptor polymorphisms (CAG repeat lengths) in androgenic alopecia, hirsutism and acne. J Cutan Med Surg 3, 9–15. 67. Trapanainen, J. S., Koivunen, R., Fauser, B. C., Taylor, A. E., Clayton, R. N., Rajkowa, M. et al. (1999) A new contributing factor to polycystic ovary syndrome: the genetic variant of luteinizing hormone. J Clin Endocrinol Metab 84, 1711–1715. 68. Liao, W. X., Roy, A. C., Chan, C., Arulkumaran, S. and Ratnam, S. S. (1998) A new molecular variant of luteinizing hormone associated with female infertility. Fertil Steril 69, 102–106.

REFERENCES

507

69. Urbanek, M., Wu, X., Vickery, K. R., Kao, L. C., Christenson, L. K., Schneyer, A., Legro, R. S., Driscoll, D. A., Strauss, J. F., Dunaif, A. and Spielman, R. S. (2000) Allelic variants of the follistation gene in polycystic ovary syndrome. J Clin Endocrinol Metab 85, 4455–4461. 70. Calvo, R. M., Villuedas, G., Sancho, J., San Millan, J. L. and Escobar-Morreale, H. F. (2001) Role of the follistatin in women with polycystic ovary syndrome. Fertil Steril 75, 1020–1023. 71. Ib´an˜ ez, L., Dimartino-Nardi, J., Potau, N. and Saenger, P. (2000) Premature adrenarche normal variant or forerunner of adult disease? Endocrin Rev 21, 671–696. 72. Ib´an˜ ez, L., Bonnin, M. R., Zampolli, M., Prat, N., Alia, P. J. and Navarro, M. A. (1995) Usefulness of an ACTH test in the diagnosis of non-classical 21-hydroxylase deficiency among children presenting with premature pubarche. Horm Res 44, 51–56. 73. Potau, N., Riqu´e, S., Eduardo, I., Marcos, V. and Ib´an˜ ez, L. (2002) Molecular defects of the CYP21 gene in Spanish girls with isolated precocious pubarche. Eur J Endocrinol 147, 485–488. 74. Ib´an˜ ez, L., Virdis, R., Potau, N., Zampolli, M., Ghizonni, L., Albisu, M. A., Carrascosa, A., Bernasconi, S. and Vicens-Calvet, E. (1992) Natural history of premature pubarche: an auxological study. J Clin Endocrinol Metab 74, 254–257. 75. Rosenfield, R. L. (1996) Editorial: evidence that idiopathic functional adrenal hyperandrogenism is caused by disregulation of adrenal steroidogenesis and that hyperinsulinemia may be involved. J Clin Endocrinol Metab 81, 878–880. 76. Ib´an˜ ez, L., Potau, N., Chacon, P., Pascual, C. and Carrascosa, A. (1998) Hyperinsulinaemia, dyslipaemia and cardiovascular risk in girls with a history of premature pubarche. Diabetologia 41, 1057–1063. 77. Ib´an˜ ez, L., Potau, N., Virdis, R., Zampolli, M., Terzi, C., Gussiny´e, M., Carrascosa, A. and Vicens-Calvet, E. (1993) Postpubertal outcome in girls diagnosed of premature pubarche during childhood: increased frequency of functional ovarian hyperandrogenism. J Clin Endocrinol Metab 76, 1599–1603. 78. Ib´an˜ ez, L., De Zegher, F. and Potau, N. (1999) Anovulation after precocious pubarche: early markers and time course in adolescence. J Clin Endocrinol Metab 84, 2691–2695. 79. Amiel, S. A., Caprio, S., Sherwin, R. S., Plewe, G., Haymond, M. W. and Tamborlane, W. V. (1991) Insulin resistance of puberty: a defect restricted to peripheral glucose metabolism. J Clin Endocrinol Metab 72, 277–282. 80. Argente, J., Barrios, V., Pozo, J., Mu˜noz, M. T., Herv´as, F., Stene, M. and Hern´andez, M. (1993) Normative data for insulin-like growth factors (IGFs), IGF-binding proteins, and growth hormone-binding protein in healthy Spanish pediatric population: age and sex related changes. J Clin Endocrinol Metab 77, 1522–1528. 81. Ib´an˜ ez, L., Potau, N. and Carrascosa, A. (1998) Possible genesis of polycystic ovary syndrome in the periadolescent girl. Curr Opin Endocrinol Diab, 5, 19–26. 82. Arslanian, S. A., Lewy, V. D. and Danadian, K. (2001) Glucose intolerance in obese adolescents with polycystic ovary syndrome: roles of insulin resistance and β-cell dysfunction and risk of cardiovascular disease. J Clin Endocrinol Metab 86, 66–71. 83. Barker, D. J. P., Hales, C. H. D., Osmond, C. and Clark, P. M. S. (1993) Type 2 (noninsulin dependent) diabetes mellitus, hypertension and hyperlipidaemia (syndrome X): relation to reduced fetal growth. Diabetologia 36, 62–67. 84. Hofman, P. L., Cutfield, W. S., Robinson, E. M., Bergman, R. N., Menon, R. K., Sperling, M. A. and Gluckman, P. D. (1997) Insulin resistance in short children with intrauterine growth retardation. J Clin Endocrinol Metab 82, 402–406. 85. Potau, N., Gussiny´e, M., S´anchez-Ufarte, C., Riqu´e, S., Vicens-Calvet, E. and Carrascosa, A. (2001) Hyperinsulinemia in pre- and post-pubertal children born small for gestational age. Horm Res 56, 146–150.

508

INSULIN RESISTANCE AND POLYCYSTIC OVARY SYNDROME

86. Ib´an˜ ez, L., Potau, N., Francois, I. and De Zegher, F. (1998) Precocious pubarche, hyperinsulinism and ovarian hyperandrogenism in girls: relation to reduced fetal growth. J Clin Endocrinol Metab 83, 3558–3562. 87. Venturoli, S., Marescalchi, O., Colombo, F. M., Macrelli, S., Ravaioli, B., Bagnoli, A., Paradisi, R. and Flamigni, C. (1999) A prospective randomized trial comparing low dose flutamide, finasteride, kenoconazole, and cyproterone acetate–estrogen regimens in the treatment of hirsutism. J Clin Endocrinol Metab 44, 1304–1310. 88. Ib´an˜ ez, L., Potau, N., Marcos, M. V. and De Zegher, F. (2000) Treatment of hirsutism, hyperandrogenism, oligomenorrhea, dyslipidemia, and hyperinsulinism in non-obese, adolescents girls: Effect of flutamide. J Clin Endocrinol Metab 85, 3251–3255. 89. Eagleson, C. A., Gingrich, M. B., Pastor, C. L., Arora, T. K., Burt, C. M., Evans, W. S. and Marshall, J. C. (2000) Polycystic ovarian syndrome: evidence that flutamide restores sensitivity of the flutamide gonadotropin-releasing hormone pulse generator to inhibition by estradiol and progesterone. J Clin Endocrinol Metab 85, 4047–4052. 90. Vel´azquez, E. M., Mendoza, S., Hamer, T., Sosa, F. and Glueck, C. J. (1994) Metformin therapy in polycystic ovary syndrome reduces hyperinsulinemia, insulin resistance, hyperandrogenemia, and systolic blood pressure, while facilitating normal menses and pregnancy. Metabolism 43, 647–654. 91. Crave, J. C., Fimbel, S., Lejeune, H., Cugnardey, N., D´echaud, H. and Pugeat, M. (1995) Effect of diet and metformin administration on sex hormone-binding globulin, androgens, and insulin in hirsute and obese women. J Clin Endocrinol Metab 80, 2057–2062. 92. Nestler, J. E. and Jakubowicz, D. J. (1996) Decreases in ovarian cytochrome P450c17 activity and serum free testosterone after reduction of insulin secretion in polycystic ovary syndrome. N Engl J Med 335, 617–623. 93. Ehrmann, D. A., Cavaghan, M. K., Imperial, J., Sturis, J., Rosenfield, R. L. and Polonsky, K. S. (1997) Effect of metformin on insulin secretion, insulin action, and ovarian steroidogenesis in women with polycystic ovary syndrome. J Clin Endocrinol Metab 82, 524–530. 94. Vel´azquez, E., Acosta, A. and Mendoza, S. G. (1997) Menstrual cyclicity after metformin therapy in polycystic ovary syndrome. Obstet Gynecol 90, 392–395. 95. Nestler, J. E., Jakubowicz, D. L., Evans, W. S. and Pascuali, R. (1998) Effect of metformin on spontaneous and clomiphene-induced ovulation in the polycystic ovary syndrome. N Engl J Med 338, 1876–1880. 96. Morin-Papunen, L. C., Koivunen, R. M., Ruokonen, A. and Martikainen, H. K. (1998) Metformin therapy improves the menstrual pattern with minimal endocrine and metabolic effects in women with polycystic ovary syndrome. Fertil Steril 69, 691–696. 97. De Leo, V., la Marca, A., Ditto, A., Morgante, G. and Cianci, A. (1999) Effect of metformin on gonadotropin induced ovulation in women wih polycystic ovary syndrome. Fertil Steril 72, 282–285. 98. Pascuali, R., Gambineri, A., Biscotti, D., Vicennati, V., Gagliardi, L., Colitta, D., Fiorini, S., Cognigni, G. E., Filicori, M. and Morselli-labate, A. M. (2000) Effect of long-term treatment with metformin added to hypocaloric diet on body composition, fat distribution, and androgen and insulin levels in abdominally obese women with and without polycystic ovary syndrome. J Clin Endocrinol Metab 85, 2767–2774. 99. La Marca, A., Obinchemti Egbe, T., Morgante, G., Paglia, T., Ciani, A. and De Leo, V. (2000) Metformin treatment reduces ovarian cytochrome P450c17 response to human chorionic gonadotrophin in women with insulin resistance-related polycystic ovary syndrome. Hum Reprod 15, 21–23.

REFERENCES

509

100. De Leo, V., La Marca, A., Orvieto, R. and Morgante, G. (2000) Effect of metformin on insulin-like growth factor (IGF I) and IGF-binding protein I in polycystic ovary syndrome. J Clin Endocrinol Metab 85, 1598–1600. 101. Moghetti, P., Castello, R., Negri, C., Tosi, F., Perrone, F., Caputo, M., Zanolin, E. and Muggeo, M. (2000) Metformin effect on clinical features, endocrine and metabolic profiles, and insulin sensitivity in polycystic ovary syndrome: a randomized, doubleblind, placebo-controlled 6-month trial, followed by open, long-term clinical evaluation. J Clin Endocrinol Metab 85, 139–146. 102. Stith, B. J., Woronoff, K. and Wiernsperger, N. J. (1998) Stimulation of the intracellular portion of the human insulin receptor by the antidiabetic drug metformin. Biochem Pharmacol 55, 533–536. 103. Riqu´e, S., Iba˜nez, L., Marcos, M. V., Carrascosa, A. and Potau, N. (2000) Effect of metformin on androgens and insulin concentrations in type A insulin resistance syndrome. Diabetologia 43, 385–386. 104. Arslanian, S., Lewy, V., Danadian, K. and Saad, R. (2002) Metformin therapy in obese adolescents with polycystic ovary syndrome and impaired glucose tolerance: amelioration of exaggerated adrenal response to adrenocorticotropin with reduction of insulinemia/insulin resistance. J Clin Endocrinol Metab 87, 1555–1559. 105. Ib´an˜ ez, L., Valls, C., Potau, N., Marcos, M. V. and De Zegher, F. (2000) Sensitization to insulin in adolecent girls to normalize hirsutism, hyperandrogenism, oligomenorrhea, dyslipidemia, and hyperinsulinism after precocious pubarche. J Clin Endocrinol Metab 85, 3526–3530. 106. Ib´an˜ ez, L., Valls, C., Ferrer, A., Marcos, M. V., Rodriguez-Hierro, F. and De Zegher, F. (2001) Sensitization to insulin induces ovulation in non-obese adolescents with anovulatory hyperandrogenism. J Clin Endocrinol Metab 86, 3595–3598. 107. Sarlis, N. J., Weil, S. J. and Nelson, L. M. (1999) Administration of metformin to a diabetic woman with extreme hyperandrogenemia of nontumoral origin: management of infertility and prevention of inadvertent masculinization of a female fetus. J Clin Endocrinol Metab 84, 1510–1512. 108. Bailey, C. J. (2000) The rise and fall of troglitazone. Diabet Med 17, 414–415. 109. Forman, L. M., Simmons, D. A. and Diamond, R. H. (2000) Hepatic failure in a patient taking rosiglitazone. Ann Intern Med 132, 118–121. 110. Al-Salman, J., Arjomand, H., Kemp, D. G. and Mittal, M. (2000) Hepatocellular injury in a patient receiving rosiglitazone. A case report. Ann Intern Med 132, 121–124. 111. Dunaif, A., Scott, D., Finegood, D., Quintana, B. and Whitcomb, R. (1996) The insulinsensitizing agent troglitazone improves metabolic and reproductive abnormalities in the polycystic ovary syndrome. J Clin Endocrinol Metab 81, 3299–3306. 112. Azziz, R., Ehrmann, D., Legro, R. S., Whitcomb, R. W., Hanley, R., Fereshetian, A. G., O’Keefe, M. and Ghazzi, M. (2001) Troglitazone improves ovulation and hirsutism in the polycystic ovary syndrome: a multicenter, double blind, placebocontrolled trial. J Clin Endocrinol Metab 86, 1626–1632. 113. Nestler, J. E., Jakubowicz, D. J., Reamer, P., Gunn, R. D. and Allan, G. (1999) Ovulatory and metabolic effects of D-chiro-inositol in the polycystic ovary syndrome. N Engl J Med 340, 1314–1320.

17 Syndromes of Severe Insulin Resistance (SSIRs) David Savage and Stephen O’Rahilly

17.1 Introduction Insulin resistance is defined as a state in which a given concentration of insulin elicits a subnormal biological response. While insulin has several metabolic and mitogenic actions, insulin resistance is usually defined in terms of an impairment in insulin’s ability to lower plasma glucose, an action it performs through stimulating glucose uptake into muscle and fat and suppressing the hepatic production of glucose. Although insulin resistance is a key pathophysiological feature in most people with type 2 diabetes (T2DM), polycystic ovary syndrome (PCOS) and the metabolic syndrome, and is commonly seen in obesity, these common disorders will not be considered here. Instead this chapter will concentrate on inherited and acquired disorders where there is a profound impairment of insulin action. Somewhat simplistically, extreme insulin resistance can manifest itself in one of two ways. First, there are individuals with known diabetes mellitus who may require very large doses of insulin for the control of their glycaemia. Arbitrarily, a level of >200 U of exogenous insulin administered per day has been suggested to define severe insulin resistance in these circumstances. Second, there is a group of conditions that most frequently present, not with diabetes, but with other clinical manifestations of the underlying disorder such as the skin lesion acanthosis nigricans, ovarian hyperandrogenism, growth retardation or acral enlargement. In a patient who is suspected of having a SSIR but does not have insulin-treated diabetes, a useful and simple way of establishing the condition is to undertake an oral glucose tolerance test with measurements of Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

512

SYNDROMES OF SEVERE INSULIN RESISTANCE (SSIRs)

plasma insulin. While no formal criteria for severe insulin resistance are widely accepted, a fasting insulin level >150 pmol/l and/or a post-glucose-load insulin level of >1500 pmol/l indicate a marked degree of insulin resistance. However it should be noted that such levels are not infrequently seen in patients with morbid obesity, a condition not usually classified as a SSIR. The last 25 years have seen enormous advances in our understanding of the normal mechanism of insulin action.1 Progress in the elucidation of the molecular mechanisms underlying syndromes of extreme insulin resistance has been slower, but recently significant advances have been made. In this chapter we will first describe the general clinical features common to many syndromes of severe insulin resistance. We will then discuss the major hereditary and acquired syndromes of severe insulin resistance. Finally, we will consider therapeutic options in these conditions.

17.2

General biochemical and clinical features of severe insulin resistance

Compensatory hyperinsulinaemia and disturbed glucose metabolism Primary defects in insulin’s ability to exert its normal actions in muscle, liver and fat are associated with a compensatory increase in insulin secretion from the pancreatic β-cell. While small elevations in glucose may be involved in signalling the existence of peripheral resistance to the β-cell, signals other than glucose may be involved in maintaining this state of compensatory hyperinsulinaemia.2 Ultimately, the β-cell is unable to maintain this level of secretory activity and insulin levels fall, leading to the onset of frank diabetes, which is then difficult to control by conventional means. In the stages before the development of frank diabetes in SSIRs a number of glycaemia-related phenomena are worth noting. Quite frequently patients with SSIR have disproportionate post-prandial hyperglycaemia, with markedly elevated post-meal glucose levels in the face of normal fasting plasma glucose.3 Paradoxically, hypoglycaemic episodes can be a major feature of certain SSIRs at the early stages of the disease. Thus, children with Donohue’s syndrome almost inevitably have frequent fasting hypoglycaemia. Subjects with other, less extreme SSIRs frequently suffer from recurrent hypoglycaemic symptoms 3–4 h after a meal. These phenomena may occur because the normal accuracy of the physiological systems that control circulating insulin and glucose levels cannot be maintained at these extreme levels of insulin resistance, with this resulting in a period of ‘overcompensation’. The markedly delayed insulin clearance that occurs in some of the disorders may also contribute to reactive hypoglycaemic episodes. Even patients with complete congenital absence of insulin receptors develop hypoglycaemia, implying that the massively elevated

BIOCHEMICAL AND CLINICAL FEATURES OF SEVERE INSULIN RESISTANCE

513

levels of insulin are mediating glucose-lowering effects through other related receptors such as the IGF-1 receptor.

Acanthosis nigricans (Figure 17.1) This skin lesion is found in the great majority of patients with severe insulin resistance, whatever the underlying cause. It is a dark velvety hyperpigmented skin lesion, sometimes accompanied by multiple skin tags, occurring most strikingly in flexural locations such as the axillae, the back of the neck and the groin. It is also frequently seen over pressure points. In the most extreme cases it can be generalized but the palms and soles are usually spared. Histologically, it is a hyperkeratotic epidermal papillomatosis with some evidence for increased melanocyte number. Its absence in states of insulin deficiency, its presence in many different hyperinsulinaemic conditions and its rapid resolution in patients with type B insulin resistance in whom insulin receptor antibodies are removed suggest that it is likely to result from the hyperinsulinaemia. While it has been suggested that it might result from insulin’s actions on IGF-1 receptors in skin, acanthosis nigricans is not common in acromegaly, a condition where IGF-1 itself is raised. There have also been reports of its improvement when patients with SSIRs are treated with IGF-1.

Figure 17.1 Acanthosis nigricans in both axillae in a child with congenital generalized lipodystrophy

514

SYNDROMES OF SEVERE INSULIN RESISTANCE (SSIRs)

Ovarian hyperandrogenism Features of hyperandrogenism are very common in post-pubertal girls with SSIRs and are often the presenting feature of the condition. Amenorrhea/oligomenorrhoea, hirsutism, acne and ultrasonographically demonstrable polycystic ovaries are all common clinical manifestations. Plasma testosterone levels can reach the order of 10 mmol/l in some cases, often leading to a fruitless search for an adrenal or ovarian tumour if the association with severe insulin resistance is not recognized. In some of the more severe congenital SSIRs, clitoromegaly and precocious puberty can occur. The relationship between insulin resistance and PCOS was recently reviewed by Venkatesan et al.4

17.3

Classification of specific syndromes of insulin resistance

In the absence of firm knowledge of pathophysiological mechanisms, classification is somewhat arbitrary. However, we find it useful to place lipodystrophic disorders and those genetic disorders with complex phenotypic anomalies into separate categories (Table 17.1). This leaves a third category, which we refer to as ‘primary disorders of insulin action’. While this is certainly an accurate appellation for some of the diseases in this category, further research will lead to the need for finer distinctions to be made. Table 17.1 Classification of syndromes of severe insulin resistance Inherited

Acquired

Primary disorders of insulin action Donohue’s syndrome Rabson–Mendenhall syndrome Type A insulin resistance HAIR-AN syndrome Pseudoacromegaly

Type B insulin resistance

Lipodystrophies Congenital generalized lipodystrophy Familial partial lipodystrophy (LMNA mutations) Mandibulo-acral dysplasia PPARγ-dominant-negative mutations

Acquired generalized lipodystrophy Acquired partial lipodystrophy HIV-associated lipodystrophy

Other inherited disorders associated with severe insulin resistance Alstrom’s syndrome Myotonic dystrophy

PRIMARY DISORDERS OF INSULIN ACTION

17.4

515

Primary disorders of insulin action

Hereditary syndromes Donohue’s syndrome (also known as leprechaunism)

First described in 1954,5 this rare syndrome (∼1 in 4 million live births)6 occupies the most severe end of the insulin resistance spectrum. The distinguishing facial features of large ears, globular eyes and micrognathia led to use of the term ‘leprechaunism’ in this syndrome. Affected babies are severely growth retarded, have acanthosis nigricans, hirsutism, prominent rugae around body orifices, very little subcutaneous fat, cliteromegaly or penile enlargement and breast hyperplasia.7 Myocardial and pancreatic hypertrophy, dysmorphic lungs,8 rectal prolapse and renal disease with hypertension and albuminuria, and ovarian cysts have also been reported.9 These patients display extremely high insulin levels, often more than 10 000 pmol/l, alongside fasting hypoglycaemia and post-prandial hyperglycaemia. Subjects typically fail to survive beyond the first or second years of life. Donohue’s syndrome is invariably associated with the presence of mutations in both alleles of the insulin receptor gene. Several examples of the ‘null phenotype’ have now been reported, with these children being homozygotes or compound heterozygotes for nonsense mutations, leading to the complete absence of insulin receptors. In other cases, the missense or splice site mutations found result in severe receptor dysfunction. Rabson–Mendenhall syndrome

This was originally described by Mendenhall in 1950 and in 1956 three further cases were described by Rabson.10, 11 Its severity is intermediate between that of Donohue’s syndrome and type A insulin resistance (see below). Affected children typically have acanthosis nigricans, thick rapidly growing scalp hair, phallic enlargement and precocious pseudo-puberty. Characteristically they have abnormal dentition and thick fingernails. Generally it carries a poor prognosis but some patients survive beyond their teenage years. Children develop frank diabetes, which is often extremely difficult to control. If they survive they are susceptible to the full range of microvascular complications of diabetes. Although rare, ketoacidosis has been described in the context of this syndrome12 and is perhaps a feature of disease progression in patients surviving long enough for β-cell decompensation to occur.13 Most patients with Rabson–Mendenhall (RM) syndrome have mutations in both copies of their insulin receptor gene. However, in contrast to patients with Donohue’s syndrome, the mutant receptors found in RM subjects tend to retain a small amount of residual activity. Type A insulin resistance and variants

Type A insulin resistance syndrome was first described in 1976 by Kahn et al.14 They described several lean adolescent females with acanthosis nigricans,

516

SYNDROMES OF SEVERE INSULIN RESISTANCE (SSIRs)

hyperandrogenism and features of severe polycystic ovarian syndrome, who had extreme insulin resistance in the absence of lipodystrophy or obesity. The condition most commonly presents around puberty. Patients may present with oligo- or amenorrhoea and anovulation, hirsutism, acne and occasionally significant masculinization with male pattern baldness and muscle development.15 Acanthosis nigricans is a universal finding. Occasional patients manifest short stature and muscle cramps.16 Typically androgens are increased, sex hormone binding globulin is reduced17 and serum gonadotropins are elevated, with a raised LH/FSH ratio. Plasma insulin is markedly elevated but less so than in Donohue’s or RM syndrome. While diabetes is not a typical presenting feature, most patients develop impaired glucose tolerance and diabetes at some point. Mutations in the insulin receptor are responsible for some, but by no means all, subjects with type A insulin resistance syndrome. The prevalence of IR mutations is highly dependent on the selection criteria for the disease but may be up to 20–25 per cent. Typically, the mutations occur in only one copy of the insulin receptor gene and often affect the intracellular tyrosine kinase domain. As these mutant receptors can interfere with function of the co-expressed wild type receptor the condition can be inherited in an autosomal dominant manner. As originally defined, with hyperandrogenism as a key presenting feature, type A insulin resistance cannot strictly occur in males. However, there are several examples of male carriers of the insulin receptor mutations that lead to type A in their female relatives. Invariably these males are hyperinsulinaemic and often have acanthosis nigricans and glucose intolerance. These abnormalities frequently only come to light after family screening and/or after the development of diabetes in the fourth or fifth decade of life. Considering the typical insulin receptor mutations found in type A subjects versus those with Donohue’s or Rabson–Mendenhall syndrome a genotype/phenotype relationship is apparent. There is a broad correlation between the site and severity of the mutation in the insulin receptor and the age of onset, severity and pattern of inheritance of the clinical presentation. In fact the genetic ‘insulin receptor-opathies’ essentially represent a continuum of both receptor dysfunction and clinical severity, with the traditional division into three clinical syndromes being somewhat artificial. There are several variants of the type A syndrome. In addition to the typical findings of severe insulin resistance, some patients display features reminiscent of acromegaly, e.g. accelerated linear growth, large hands and feet, macroglossia, coarsened features and acromegaloid bone changes, but without any abnormality in growth hormone or IGF-1 levels.18, 19 To date all these patients have had normal insulin receptors. It has been suggested that these features might be due to the interaction of the high levels of insulin with the IGF-1 receptor but, if that were the explanation, one would expect all patients with severe hyperinsulinaemia to have features of acromegaly, which is not the case. Dib et al.20 reported that cultured fibroblasts from patients with this disorder show selective

PRIMARY DISORDERS OF INSULIN ACTION

517

defects in cellular metabolic signalling but normal growth signals. Thus, in these patients the defect in insulin’s metabolic signalling leads to compensatory hyperinsulinaemia, which stimulates tissue growth through the intact receptor and intact growth stimulating pathways downstream of the receptor. The HAIR-AN (hyperandrogenism–insulin resistance and acanthosis nigricans) syndrome is a rather nebulous term that has been used to describe patients with many of the features of type A insulin resistance but, unlike the classical description of type A, it does not exclude those who are obese. In reality it is difficult to be clear about the boundaries between type A insulin resistance, HAIR-AN syndrome and the more insulin resistant end of the PCOS spectrum. This is especially true in certain ethnic groups in which acanthosis nigricans is almost universal in obese women with PCOS.21

Acquired syndromes Type B insulin resistance

This is an acquired auto-immune syndrome, most often seen in women (the female:male ratio is 4:1), almost all of whom have additional manifestations of auto-immune disease or lymphoid malignancy. In fact as many as a third will meet the criteria for systemic lupus erythematosis (SLE), and vitiligo, alopecia areata, arthritis and nephritis are also frequently seen. The diagnostic hallmark of type B insulin resistance is the presence of polyclonal IgG autoantibodies to the insulin receptor.14 Antibody titres are proportional to the severity of the disease. The typical patient is a middle aged female with known autoimmune disease who develops diabetes that is very difficult to control despite the use of massive doses of insulin. In some patients severe hyperglycaemia results in significant caloric loss via glucose in the urine and marked weight loss (producing a cachectic appearance). Acanthosis nigricans is almost always present. The condition can be definitively diagnosed by demonstrating that the immunoglobulin fraction of the patient’s serum can inhibit binding of insulin to cloned insulin receptors. Occasionally patients exhibit fluctuating hyper- and hypoglycaemia as different subpopulations of antibodies can have an antagonistic or stimulatory effect on the receptor.22, 23 Type 2 and type 1 diabetes requiring high doses of exogenous insulin

Among diabetologists this is probably the commonest clinical scenario in which they will seek an explanation for severe insulin resistance. Unfortunately, it is one in which a clear explanation is seldom forthcoming. Excluding surreptitious manipulation of insulin therapy and the development of antibodies against injected insulin, possible explanations for such insulin resistance include (a) the patient having a previously unrecognized SSIR, which has now decompensated to diabetes (see comments above regarding males with type A insulin resistance);

518

SYNDROMES OF SEVERE INSULIN RESISTANCE (SSIRs)

(b) secondary impairment of insulin action due to the adverse effects of sustained hyperglycaemia, so-called ‘glucotoxicity’ or (c) a combination of the two. The presence of acanthosis nigricans or a strong family history of insulin resistance suggest the presence of an intrinsic defect in insulin action, whereas a reversibility over time of the insulin resistance after a period of strict metabolic control points towards an ‘acquired’ metabolic explanation.

17.5 Lipodystrophic syndromes and a lipocentric approach to diabetes The lipodystrophic syndromes encompass a heterogeneous group of conditions characterized by partial or complete absence of adipose tissue. The disorders may be genetic or acquired, and are further classified according to the anatomical distribution of the lipodystrophy. Insulin resistance is a feature of most, but not all, of these disorders, and may be severe. The recognition that insulin resistance can result from both obesity and lipodystrophy has fuelled interest in the so-called lipocentric approach to diabetes, an idea originally proposed by Dennis McGarry in 1992.24 This hypothesis holds that abnormal fatty acid metabolism may result in inappropriate accumulation of lipids in muscle, liver and β-cells.25 It is further proposed that ectopic fat accumulation is involved in the development of insulin resistance in muscle and liver as well as impairing β-cell function (so called ‘lipotoxicity’)26 (Figure 17.2). Proponents of this theory cite the following evidence. • Lipid accumulation within myocytes and hepatocytes is strongly associated with insulin resistance. This association is true of both diabetics and individuals with impaired glucose tolerance.27 In fact, nuclear magnetic resonance (NMR) measurements of intra-myocellular lipids (IMCLs) correlate more closely with insulin resistance than any other commonly measured indices including BMI, waist–hip ratios or total body fat.25 Non- alcoholic steatohepatitis (NASH) is also increasingly recognized as a component of the insulin resistance or metabolic syndrome.28, 29 • Infusion of free fatty acids (FFAs) during hyperinsulinaemic–euglycaemic clamps in both humans and rodents reduces glucose disposal. Furthermore, the fall in insulin sensitivity during such clamp procedures only occurs several hours after elevations in FFA concentrations, in keeping with the idea that FFA accumulation in skeletal muscle and liver is responsible for this phenomenon.27 Again in this paradigm, the presence of insulin resistance coincides with increasing intramuscular triglyceride levels as measured by NMR spectroscopy.27 • Lipid accumulation in myocytes is apparent in non-diabetic relatives of patients with type 2 diabetes, a cohort at high risk of developing diabetes.30

LIPODYSTROPHIC SYNDROMES Adipose tissue storage (‘buffer’) Lipodystrophy

Plasma TG/ FFAs

519

‘Ectopic lipid storage’

Hepatic steatosis

Healthy Skeletal muscle ( ↑IMTG)

Obesity Pancreatic steatosis

Figure 17.2 ‘Lipotoxicity’: healthy adipose tissue buffers ingestion of excess calories by storing energy as triglycerides. In obesity, excess energy intake overloads adipose tissue storage capacity, whilst in lipodystrophy the adipose storage capacity is significantly reduced. Excess energy accumulates as triglyceride in ‘ectopic’ sites where it is believed to impair insulin action (IMTG, intramyocellular triglyceride)

• Dietary restriction in obese insulin-resistant rodents leads to a significant reduction in IMCL levels and improvement in insulin sensitivity.31 Although triglyceride accumulation in non-adipose tissue is what is usually measured, it is widely believed that, rather than inducing insulin resistance themselves, triglycerides are a surrogate marker for another fatty-acid-derived entity. Candidates for the molecules directly responsible for inducing insulin resistance include long chain fatty acyl-coenzyme-A (acyl-CoA) molecules, diacylglycerol (DAG) and ceramides. Yu et al.32 attempted to resolve this question by infusing a lipid emulsion into healthy rats and then measuring intracellular levels of long chain acyl-CoA, ceramides, DAG and triglycerides. During this infusion there was no change in intracellular ceramide or triglyceride levels, whereas intracellular long chain acyl-CoA increased six-fold and DAG increased transiently after three hours. These changes were associated with protein kinase-C theta (PKC-θ) activation, serine phosphorylation of IRS-1, reduced insulin-stimulated tyrosine phosphorylation of IRS-1 and a fall in IRS-1-associated PI3-kinase activity, leading in turn to reduced glucose uptake. Yuan et al.33 hypothesized that IKK-β might be involved in mediating fattyacid-induced activation of a serine kinase. They then demonstrated that both pharmacological inhibition of IKK-β activity by high dose salicylates and heterozygous deletion of the IKK-β gene ameliorated insulin resistance in obese

520

SYNDROMES OF SEVERE INSULIN RESISTANCE (SSIRs)

rodents during high fat feeding or lipid infusion. This salicylate effect has also been observed in humans, although high dose salicylates remain a research tool only due to significant side-effects.34 In short, it would appear that inappropriate free fatty acid delivery to muscle leads to accumulation of esterified long chain fatty acids within myocytes. This accumulation triggers PKC and IKKβ-mediated serine phosphorylation of IRS-1, inhibiting insulin-induced tyrosine phosphorylation of IRS-1 and IRS-1-associated PI3-kinase activity, ultimately leading to a fall in insulin-stimulated GLUT-4 translocation to the cell membrane and reduced glucose uptake. Somewhat counter-intuitively, studies of lipodystrophic rodents and humans have provided several important pieces of information in the development of this hypothesis, the basic idea being that both lipodystrophy and obesity represent states of inadequate storage capacity for surplus energy.35 In obesity the adipose depot is ‘overloaded’ due to excess energy intake and reduced energy utilization, whereas in lipodystrophy a depleted adipose tissue depot cannot cope with normal energy intake (the problem is exacerbated by the tendency of people with lipodystrophy to ‘over-eat’ as a consequence of low plasma leptin levels). Lipodystrophic rodents and humans accumulate lipids in liver and muscle. One particularly compelling piece of evidence in support of the lipotoxicity theory of diabetes was recently provided by Reitman and co-workers, who successfully transplanted adipose tissue into lipodystrophic mice.36 Despite only partially restoring adipose tissue mass, they dramatically improved insulin sensitivity in the recipient mice as well as reducing intramuscular and intrahepatic triglyglycerides. Although adipose tissue transplantation has been considered in humans, to date this option remains theoretical. Other than lipodystrophy and obesity, one might expect genetic defects in fatty acid oxidation to lead to long chain acyl-CoA accumulation and insulin resistance. A single report describing physiological phenotyping in a patient with carnitine palmitoyltransferase II (CPT II) deficiency seems to support this notion.37 The patient initially presented with recurrent episodes of myalgia, rhabdomyolysis and myoglobinuria during adolescence. She was seen by neurologists, who identified a homozygous Ser113Leu CPT II mutation. At the age of 43 she was lean (BMI 24.9 kg/m2 ) and had normal glucose tolerance but an elevated fasting insulin level of 109 pmol/l. A hyperinsulinaemic–euglycaemic clamp confirmed the presence of severe insulin resistance. Interestingly, whole body lipolysis was partially suppressed in the basal state (presumably a consequence of the fasting hyperinsulinaemia) and responded appropriately to insulin infusion by suppressing even further, an observation in keeping with the expectation that although skeletal muscle was insulin resistant adipose tissue appeared to be insulin sensitive.∗ ∗ Very low plasma adiponectin levels have also been reported in lipodystrophic patients.91, 62 The possible mechanisms by which a lack of adiponectin may contribute to insulin resistance are discussed in Chapter 10.

LIPODYSTROPHIC SYNDROMES

521

Generalized lipodystrophy Congenital generalized lipodystrophy (CGL) (Figure 17.3)

CGL, also known as Berardinelli–Seip syndrome (BSCL),38, 39 is an autosomal recessive condition, characterized by a generalized absence of adipose tissue from birth. Children with the condition have increased appetites (due to leptin deficiency)40 accelerated growth and advanced bone age. Skeletal muscles, peripheral veins and the thyroid gland are particularly prominent due to the paucity of subcutaneous fat. Hyperinsulinaemia is present from early childhood and is believed to be the cause of extensive acanthosis nigricans, organomegaly and acromegaloid features. Diabetes tends to develop in the second decade. Hepatomegaly is principally due to excessive fat deposition and may progress to non-alcoholic steatohepatitis (NASH) and even cirrhosis (believed to be the most common cause of death). Affected women have more pronounced phenotypic abnormalities including features of PCOS and hyperandrogenism (hirsutism and clitoromegaly). Biochemical features include impaired glucose tolerance and dyslipidaemia, with severe hypertriglyceridaemia frequently resulting in eruptive xanthomata and pancreatitis. Serum leptin concentrations are extremely low due to the lack of adipose tissue.40 BSCL is genetically heterogenous, consisting of at least three different autosomal recessive conditions. The BSCL1 gene is on chromosome 9q.41 Agarwal et al.42 recently employed a positional cloning approach to identify homozygous or compound heterozygous mutations in 1-acylglycerol-3-phosphate Oacyltransferase 2 (AGPAT2) at this locus in 11 lipodystrophic kindreds of diverse ethnicity. AGPAT2 is an essential enzyme in glycerophospholipid and triacylglycerol synthesis. Following acylation of glycerol-3-phopshate at the first carbon (sn-1 position), AGPAT2 catalyses acylation at the second carbon (sn-2) to form phosphatidic acid, an essential precursor to diacylglycerol and ultimately triacylglycerol. One might expect loss of function mutations to lead to lipodystrophy by depleting adipocytes of triglyceride. BSCL2, which also occurs in multiple ethnic groups, is due to mutations in a gene of unknown function, termed siepin.43 This molecule is highly expressed in the brain and it is notable that there is a high prevalence of intellectual impairment in BSCL2 but not BSCL1 patients. The mechanism by which seipin mutations cause lipodystrophy remains poorly understood. A number of families with BSCL are unlinked to either of these loci, indicating the existence of additional genetic causes. Acquired generalized lipodystrophy (Lawrence)

First described by Lawrence,44 this syndrome is more frequent in women than men and typically develops in the second decade. Up to 50 per cent of cases follow viral infections and the aetiology is thought to be autoimmune in origin. Reports of an autoantibody against the adipocyte membrane exist, but the

522

SYNDROMES OF SEVERE INSULIN RESISTANCE (SSIRs)

Figure 17.3 Congenital generalized lipodystrophy in a 3-year-old girl

aetiopathogenesis remains poorly understood. The lipodystrophy is characterized by permanent, generalized loss of subcutaneous adipose tissue. Acanthosis nigricans, organomegaly and prominent superficial veins and muscles are present as seen in CGL. Similar metabolic complications also occur, with diabetes following several years after the onset of lipodystrophy.

Partial lipodystrophy Familial partial lipodystrophy (FPLD)

FPLD, also known as Dunnigan–Kobberling syndrome,45 is an autosomal dominant face-sparing form of lipodystrophy. Lipodystrophy was thought to develop during puberty in this condition but the use of genetic screening and consequent identification of carriers at an early age suggests that fat distribution may be abnormal during childhood. The lipodystrophy predominantly affects the limbs and gluteal fat depots with variable truncal involvement but with normal or excess fat on the face and neck.46 The phenotype is more severe in women, who may present with hirsutism and PCOS.47 Acanthosis nigricans is common. Metabolic abnormalities range from asymptomatic impaired glucose tolerance

LIPODYSTROPHIC SYNDROMES

523

and mild dyslipidaemia to severe insulin resistance with T2DM and severe dyslipidaemia potentially complicated by eruptive xanthomata and pancreatitis. As in the generalized forms of lipodystrophy, NASH is a common complication. Hypertension and accelerated atherosclerotic vascular disease have been reported in some kindreds.48 Recent work has identified mutations in the lamin A/C gene in families affected by FPLD.49, 50 Intriguingly mutations in the same gene, but at different sites, are responsible for a heterogeneous cluster of diseases (‘laminopathies’) including some cases of muscular dystrophy (Emery–Dreifuss variant), dilated cardiomyopathy, peripheral neuropathy (Charcot–Marie–Tooth IIB) and Hutchinson–Gilford progeria.51 – 53 Lamin is a structural nuclear envelope protein expressed in all cell types with putative roles in cell cycling and regulation of molecular traffic in and out of the nucleus.54 In keeping with the widespread expression of lamins, overlap syndromes in which carriers have a combination of lipodystrophy, myopathy and/or cardiomyopathy are now also recognized. A further recent development in our understanding of lamin pathology has been the recognition that certain lamin mutations produce a milder phenotype than others.55 In particular, the S583L mutation is located in exon 10, which is specific to lamin A, whereas most of the other mutations affect both lamin A and C (lamin C lacks a C-terminal region found in lamin A). The authors who described this mutant postulate that this might explain the milder phenotype. Mandibulo-acral dysplasia (MAD)

MAD is a very rare, autosomal recessive form of partial lipodystrophy associated with short stature, mandibular and clavicular hypoplasia, dental abnormalities, acro-osteolysis, stiff joints, skin atrophy, alopecia and mottled pigmentation.56 The lipodystrophy involves the limbs with excessive adipose tissue accumulation on the face, neck and trunk. Insulin resistance and dyslipidaemia have also been reported. A homozygous mutation (R527H) in lamin is responsible for some cases of mandibulo-acral dysplasia.57 Heterozygous members of these kindreds were reportedly entirely normal. Zinc metalloproteinase (ZEMPSTE24) is involved in post-translational proteolytic cleavage of carboxy-terminal residues of prelamin A. Its deficiency in mice causes accumulation of prelamin A and lipodystrophy.58 Compound heterozygous mutations in the ZEMPSTE24 gene have been identified in one kindred with a severe MAD phenotype, including generalized lipodystrophy and progeroid features.59 PPARγ deficiency

Peroxisome proliferator-activated receptor gamma (PPARγ) is a nuclear hormone receptor with a key role in adipogenesis60 and as such is an obvious candidate for lipodystrophy. Whilst the initial studies in cohorts with total lipodystrophy failed to identify any mutations in PPARγ, three groups have

524

SYNDROMES OF SEVERE INSULIN RESISTANCE (SSIRs)

recently found mutations in subjects with a stereotyped form of inherited partial lipodystrophy.61 – 64 These observations have provided compelling human genetic evidence for the role of PPARγ in adipogenesis as well as highlighting the broader involvement of this transcription factor (target of the novel class of insulin sensitizers, namely the thiazolidinediones) in insulin sensitivity and manifestations of syndrome X. Most of the affected subjects have severe insulin resistance (100 per cent), hypertension (75 per cent) and dyslipidaemia (100 per cent).65 The lipodystrophy is somewhat similar to that seen in FPLD and HIV-associated lipodystrophy with a paucity of limb and gluteal fat. However, in contrast to the latter syndromes, abdominal fat is normal and facial fat was variably reported as decreased, normal or increased. Whether the latter observation reflects molecular differences in the mutant proteins or is simply a feature of subjective assessment by different observers awaits clarification. Acquired partial lipodystrophy/Barraquer–Simons syndrome/lipodystrophy with mesangiocapillary glomerulonephritis type II (MCGN type II)

In acquired PLD, subcutaneous fat is lost from the face and upper body.66 This may occur acutely following a viral infection. Women are more commonly affected than men (3:1) and the onset is usually before 16 years of age. One in three patients also develop mesangiocapillary glomerulonephritis (MCGN type II) and less frequently other autoimmune conditions.67 The MCGN is associated with unregulated activation of the alternative complement pathway due to the presence of nephritic factor (NeF), an IgG autoantibody. NeF binds to and stabilizes C3 convertase (C3bBb), ultimately leading to reduced serum levels of C3 (a useful diagnostic marker). Metabolic complications are rare in this form of lipodystrophy. HIV-associated lipodystrophy

HIV-associated lipodystrophy is very rarely associated with severe insulin resistance, but is mentioned here on account of it being by far the most common cause of lipodystrophy. Whilst highly active antiretroviral therapy has undoubtedly provided hope to many HIV sufferers, side-effects are of increasing concern. Up to 53 per cent of patients using protease inhibitors may experience some degree of lipodystrophy within the first year of treatment, making this the most common form of lipodystrophy.68, 69 Typical features include fat wasting over the face, limbs and buttocks; with fat accumulation in the abdomen and/or dorso-cervical spine (‘buffalo hump’). This is associated with insulin resistance, which in some cases progresses to diabetes, and dyslipidaemia. Although the lipodystrophy is most commonly associated with the use of protease inhibitors, nucleoside analogues have also been implicated and some HIV sufferers have developed the syndrome in the absence of any therapy, making the precise aetiology unclear at present.70

COMPLEX GENETIC SYNDROMES

17.6

525

Complex genetic syndromes associated with severe insulin resistance

Alstrom’s syndrome This syndrome, first described in 1959, is an inherited disorder with multisystem dysfunction. Typical features include visual loss secondary to retinal pigment degeneration with cone and rod retinal dystrophy,71, 72 sensorineural hearing loss, childhood onset obesity, hyperlipidaemia, hypogonadism, dilated cardiomyopathy,73 hepatic dysfunction74 and severe insulin resistance with acanthosis nigricans. Renal dysfunction due to glomerulosclerosis is also a common feature. Glucose intolerance and diabetes are evident by the second decade. It is inherited in an autosomal recessive manner and was recently reported to be caused by mutations in ALMS1, a gene of unknown function.75

Other syndromes Although the inherited susceptibility to insulin resistance in humans is thought to involve the interplay of variants at multiple genetic loci, no clear examples of gene–gene interaction had been reported until very recently. We described a family in which five severely insulin resistant subjects and no unaffected family members were doubly heterozygous for frameshift/premature stop mutations in two unlinked genes, namely PPARγ and PPP1R3A, which encodes the muscle-specific regulatory subunit of protein phosphatase-1.76 The PPARγ mutant protein was truncated in the DNA-binding domain, rendering it unable to bind DNA and transcriptionally silent. In contrast to the ligand-binding domain mutations this mutant did not exhibit dominant-negative activity. Heterozygous PPARγ null mice retain insulin sensitivity and, interestingly, two of the seven carriers of this mutant did not appear to be insulin resistant, arguing against haploinsufficiency mediating this phenotype. Ongoing genetic studies later identified the second frameshift/premature stop mutation in a key regulator of skeletal muscle glycogen synthesis, PPP1R3A. Only the five doubly heterozygous subjects were severely insulin resistant, whereas single heterozygotes with either of the PPARγ or PPP1R3A mutations were normo-insulinaemic. This observation was of particular interest for three reasons. First, the finding that genetic defects in molecules primarily involved in either carbohydrate or lipid metabolism can combine to result in an extreme phenotype of insulin resistance provides a model for the type of gene–gene interaction that may underlie common human metabolic diseases such as type 2 diabetes. Second, the two proteins involved are predominantly expressed in different tissues, namely fat and muscle, suggesting that some form of metabolic cross-talk rather than protein–protein interaction is responsible for the insulin-resistant phenotype. Finally, singly heterozygous carriers of either mutation do not appear to be insulin resistant, suggesting that subtle defects can in combination produce a severe phenotype, a paradigm also seen in digenic insulin-resistant mouse models.

526

SYNDROMES OF SEVERE INSULIN RESISTANCE (SSIRs)

Other disorders in which severe insulin resistance is sometimes seen include myotonic dystrophy77 and Werner’s syndrome.78 A small number of subjects with what might be considered ‘atypical forms’ of Werner’s syndrome have heterozygous mutations in LMNA.79

17.7 Therapeutic options in the syndromes of severe insulin resistance Treatments designed to ameliorate the insulin resistance The SSIRs are uncommon and therefore few treatments have been subjected to the rigorous assessment demanded by ‘evidence-based medicine’. Type B insulin resistance can be successfully treated by a combination of plasmapheresis and immunosuppression.80, 81 In patients with SSIRs who have decompensated to develop frank diabetes the most compelling and difficult clinical problem is the achievement of acceptable glycaemic control. Some patients can be managed effectively by very high doses of insulin, most conveniently administered in a U500 format.82 Clearly this should be accompanied by the dietary and exercise recommendations provided to all patients with diabetes. Anecdotally, strict restriction of dietary fat from an early age may help to ameliorate the clinical course in congenital generalized lipodystrophy. Therapeutic trials of the available, orally active, insulin-sensitizing agents, including metformin and/or a thioazolidinedione, are usually justifiable. One condition in which there is some published evidence for the partial effectiveness of a thioazolidinedione is FPLD. Arioglu et al.83 demonstrated that troglitazone may improve insulin sensitivity and glycaemic status in these subjects. While troglitazone is no longer available, there is no reason to believe that these effects would not be seen with other drugs of this class. In our own experience thiazolidinediones have proved to be of little benefit. Reports describing worsening steatosis in the livers of lipodystrophic mice treated with rosiglitazone are also of concern and indicate the need for regular hepatic assessment if this option is employed.84 At least in patients with generalized lipodystrophy and very low circulating levels of leptin, early data suggests that recombinant leptin may be a better option.85 Recombinant leptin has been successfully used to ameliorate hyperphagia in leptin-deficient obese humans,86 and as generalized lipodystrophy also leads to extreme hypoleptinaemia and hyperphagia Oral et al.85 wondered whether this therapeutic approach might be of similar benefit in lipodystrophy. They treated nine patients with lipodystrophy and leptin levels below 4 µg/l with twice daily injections of recombinant leptin for four months. Glycaemic control, hypertriglyceridaemia and hepatic steatosis were strikingly improved, despite significant reductions in the use of oral hypoglycaemics and insulin therapy. As expected, self-reported caloric intake decreased and somewhat surprisingly,

REFERENCES

527

although consistent with previous reports on the use of leptin in humans,86 resting metabolic rate also fell significantly. Petersen et al.87 extended these observations in three of the patients, using hyperinsulinaemic–euglycaemic clamps to document improvements in both peripheral glucose disposal and hepatic glucose output. This improvement was associated with significant reductions in hepatic steatosis and intramyocellular triglycerides, providing a potential mechanism for the improved insulin sensitivity. This work is ongoing and long term results as well as data in subjects with partial lipodystrophy are awaited. There have been a number of reports of the use of human recombinant IGF-1 in the treatment of severe primary disorders of insulin action such as Donohue’s, RM and type A syndrome.88 – 90 This therapy undoubtedly lowers both glucose and insulin levels acutely in these subjects and has, in some, been shown to have long term beneficial effects. Difficulties in obtaining supplies of this protein for human use are considerable. A frequently asked question is ‘should insulin resistance per se be treated in subjects who have not yet developed diabetes?’. It is our opinion that advice on diet and exercise could reasonably be combined with a therapeutic trial of an oral insulin sensitizer. First this may help ameliorate the troublesome effects of severe hyperinsulinaemia on the skin and ovaries, and second, and only theoretically at present, it may help preserve the functional life of the pancreatic β-cells. If these drugs are used under these circumstances we recommend that objective evidence for improvement in hyperinsulinaemia be sought.

Managing the consequences of severe insulin resistance The principles behind the treatment of the ovarian hyperandrogenism in the SSIRs are similar to those that pertain in typical PCOS; however, women with SSIRs are more likely to be resistant to treatment. They frequently need potent antiandrogens to ameliorate severe hirsutism, acne and androgenic alopecia together with oestrogen/progestagen combinations to ensure regular menses, and assistance with fertility when appropriate. Acanthosis nigricans is a disfiguring skin lesion, which reduces quality of life for many patients. Other than treating the insulin resistance per se and using cosmetic measures to mask the skin lesion, there is little reliable specific therapy for acanthosis. There have been case reports of its improvement with etretinate and with calcipotriol. Dyslipidaemia is not infrequent, particularly in the lipodystrophic disorders, where it may be severe enough to result in xanthomata and pancreatitis. Fibrates are the first line therapy.

References 1. Saltiel, A. R. and Kahn, C. R. (2001) Insulin signalling and the regulation of glucose and lipid metabolism. Nature 414, 799–806.

528

SYNDROMES OF SEVERE INSULIN RESISTANCE (SSIRs)

2. Cavaghan, M. K., Ehrmann, D. A. and Polonsky, K. S. (2000) Interactions between insulin resistance and insulin secretion in the development of glucose intolerance. J Clin Invest 106, 329–333. 3. O’Rahilly, S., Hattersley, A., Vaag, A. and Gray, H. (1994) Insulin resistance as the major cause of impaired glucose tolerance: a self-fulfilling prophesy? Lancet 344, 585–589. 4. Venkatesan, A. M., Dunaif, A. and Corbould, A. (2001) Insulin resistance in polycystic ovary syndrome: progress and paradoxes. Recent Prog Horm Res 56, 295–308. 5. Donohue, W. and Uchida, I. (1954) Leprechaunism: a euphemism for a rare familial disorder. J Pediatr 45, 505–519. 6. Kosztolanyi, G. (1997) Leprechaunism/Donohue syndrome/insulin receptor gene mutations: a syndrome delineation story from clinicopathological description to molecular understanding. Eur J Pediatr 156, 253–255. 7. Longo, N., Langley, S. D., Griffin, L. D. and Elsas, L. J., II. (1992) Reduced mRNA and a nonsense mutation in the insulin-receptor gene produce heritable severe insulin resistance. Am J Hum Genet 50, 998–1007. 8. Thurlbeck, W. M. and Cooney, T. P. (1988) Dysmorphic lungs in a case of leprechaunism: case report and review of literature. Pediatr Pulmonol 5, 100–106. 9. Ellis, E. N., Kemp, S. F., Frindik, J. P. and Elders, M. J. (1991) Glomerulopathy in patient with Donohue syndrome (leprechaunism). Diabetes Care 14, 413–414. 10. Mendenhall, E. (1950) Tumor of the pineal body with high insulin resistance. J Indiana Med Assoc 43, 32–36. 11. Rabson, S. and Mendenhall, E. (1956) Familial hypertrophy of pineal body, hyperplasia of adrenal cortex and diabetes mellitus: report of 3 cases. Am J Clin Pathol 26, 283–290. 12. West, R. J., Lloyd, J. K. and Turner, W. M. (1975) Familial insulin-resistant diabetes, multiple somatic anomalies, and pineal hyperplasia. Arch Dis Child 50, 703–708. 13. Longo, N., Wang, Y. and Pasquali, M. (1999) Progressive decline in insulin levels in Rabson–Mendenhall syndrome. J Clin Endocrinol Metab 84, 2623–2629. 14. Kahn, C. R., Flier, J. S., Bar, R. S., Archer, J. A., Gorden, P., Martin, M. M. and Roth, J. (1976) The syndromes of insulin resistance and acanthosis nigricans. Insulinreceptor disorders in man. N Engl J Med 294, 739–745. 15. Barbieri, R. L. and Ryan, K. J. (1983) Hyperandrogenism, insulin resistance, and acanthosis nigricans syndrome: a common endocrinopathy with distinct pathophysiologic features. Am J Obstet Gynecol 147, 90–101. 16. Flier, J. S., Young, J. B. and Landsberg, L. (1980) Familial insulin resistance with acanthosis nigricans, acral hypertrophy, and muscle cramps. N Engl J Med 303, 970–973. 17. Dunaif, A., Hoffman, A. R., Scully, R. E., Flier, J. S., Longcope, C., Levy, L. J. and Crowley, W. F., Jr. (1985) Clinical, biochemical, and ovarian morphologic features in women with acanthosis nigricans and masculinization. Obstet Gynecol 66, 545–552. 18. Flier, J. S., Moller, D. E., Moses, A. C., O’Rahilly, S., Chaiken, R. L., Grigorescu, F., Elahi, D., Kahn, B. B., Weinreb, J. E. and Eastman, R. (1993) Insulin-mediated pseudoacromegaly: clinical and biochemical characterization of a syndrome of selective insulin resistance. J Clin Endocrinol Metab 76, 1533–1541. 19. Kausch, C., Bergemann, C., Hamann, A. and Matthaei, S. (1999) Insulin-mediated pseudoacromegaly in a patient with severe insulin resistance: association of defective insulin-stimulated glucose transport with impaired phosphatidylinositol 3-kinase activity in fibroblasts. Exp Clin Endocrinol Diabetes 107, 148–154. 20. Dib, K., Whitehead, J. P., Humphreys, P. J., Soos, M. A., Baynes, K. C., Kumar, S., Harvey, T. and O’Rahilly, S. (1998) Impaired activation of phosphoinositide 3-kinase by insulin in fibroblasts from patients with severe insulin resistance and pseudoacromegaly.

REFERENCES

21.

22.

23.

24. 25. 26. 27. 28.

29.

30.

31.

32.

33.

34.

35. 36.

37.

529

A disorder characterized by selective postreceptor insulin resistance. J Clin Invest 101, 1111–1120. Dunaif, A., Green, G., Phelps, R. G., Lebwohl, M., Futterweit, W. and Lewy, L. (1991) Acanthosis nigricans, insulin action, and hyperandrogenism: clinical, histological, and biochemical findings. J Clin Endocrinol Metab 73, 590–595. Flier, J. S., Kahn, C. R., Roth, J. and Bar, R. S. (1975) Antibodies that impair insulin receptor binding in an unusual diabetic syndrome with severe insulin resistance. Science 190, 63–65. Tsushima, T., Omori, Y., Murakami, H., Hirata, Y. and Shizume, K. (1989) Demonstration of heterogeneity of autoantibodies to insulin receptors in type B insulin resistance by isoelectric focusing. Diabetes 38, 1090–1096. McGarry, J. D. (1992) What if Minkowski had been ageusic? An alternative angle on diabetes. Science 258, 766–770. McGarry, J. D. (2002) Banting lecture 2001: dysregulation of fatty acid metabolism in the etiology of type 2 diabetes. Diabetes 51, 7–18. Unger, R. H. and Orci, L. (2000) Lipotoxic diseases of nonadipose tissues in obesity. Int J Obes Relat Metab Disord 24 (Suppl. 4), S28–S32. Boden, G. (2001) Pathogenesis of type 2 diabetes. Insulin resistance. Endocrinol Metab Clin North Am 30, 801–815, v. Marchesini, G., Brizi, M., Bianchi, G., Tomassetti, S., Bugianesi, E., Lenzi, M., McCullough, A. J., Natale, S., Forlani, G. and Melchionda, N. (2001) Nonalcoholic fatty liver disease: a feature of the metabolic syndrome. Diabetes 50, 1844–1850. Pagano, G., Pacini, G., Musso, G., Gambino, R., Mecca, F., Depetris, N., Cassader, M., David, E., Cavallo-Perin, P. and Rizzetto, M. (2002) Nonalcoholic steatohepatitis, insulin resistance, and metabolic syndrome: further evidence for an etiologic association. Hepatology 35, 367–372. Jacob, S., Machann, J., Rett, K., Brechtel, K., Volk, A., Renn, W., Maerker, E., Matthaei, S., Schick, F., Claussen, C. D. and Haring, H. U. (1999) Association of increased intramyocellular lipid content with insulin resistance in lean nondiabetic offspring of type 2 diabetic subjects. Diabetes 48, 1113–1139. Man, Z. W., Hirashima, T., Mori, S. and Kawano, K. (2000) Decrease in triglyceride accumulation in tissues by restricted diet and improvement of diabetes in Otsuka Long–Evans Tokushima fatty rats, a non-insulin-dependent diabetes model. Metabolism 49, 108–114. Yu, C., Chen, Y., Cline, G. W., Zhang, D., Zong, H., Wang, Y., Bergeron, R., Kim, J. K., Cushman, S. W., Cooney, G. J., Atcheson, B., White, M. F., Kraegen, E. W. and Shulman, G. I. (2002) Mechanism by which fatty acids inhibit insulin activation of insulin receptor substrate-1 (IRS-1)-associated phosphatidylinositol 3-kinase activity in muscle. J Biol Chem 277, 50 230–50 236. Yuan, M., Konstantopoulos, N., Lee, J., Hansen, L., Li, Z. W., Karin, M. and Shoelson, S. E. (2001) Reversal of obesity- and diet-induced insulin resistance with salicylates or targeted disruption of Ikkbeta. Science 293, 1673–1677. Hundal, R. S., Petersen, K. F., Mayerson, A. B., Randhawa, P. S., Inzucchi, S., Shoelson, S. E. and Shulman, G. I. (2002) Mechanism by which high-dose aspirin improves glucose metabolism in type 2 diabetes. J Clin Invest 109, 1321–1326. Friedman, J. (2002) Fat in all the wrong places. Nature 415, 268–269. Gavrilova, O., Marcus-Samuels, B., Graham, D., Kim, J. K., Shulman, G. I., Castle, A. L., Vinson, C., Eckhaus, M. and Reitman, M. L. (2000) Surgical implantation of adipose tissue reverses diabetes in lipoatrophic mice. J Clin Invest 105, 271–278. Haap, M., Thamer, C., Machann, J., Tschritter, O., Loblein, K., Kellerer, M., Schick, F., Jacob, S., Haring, H. U. and Stumvoll, M. (2002) Metabolic characterization of a woman

530

38. 39.

40.

41.

42.

43.

44. 45.

46.

47.

48. 49. 50.

51. 52.

53.

54.

SYNDROMES OF SEVERE INSULIN RESISTANCE (SSIRs)

homozygous for the Ser113Leu missense mutation in carnitine palmitoyl transferase II. J Clin Endocrinol Metab 87, 2139–2143. Seip, M. and Trygstad, O. (1996) Generalized lipodystrophy, congenital and acquired (lipoatrophy). Acta Paediatr Suppl 413, 2–28. Garg, A., Fleckenstein, J. L., Peshock, R. M. and Grundy, S. M. (1992) Peculiar distribution of adipose tissue in patients with congenital generalized lipodystrophy. J Clin Endocrinol Metab 75, 358–361. Pardini, V. C., Victoria, I. M., Rocha, S. M., Andrade, D. G., Rocha, A. M., Pieroni, F. B., Milagres, G., Purisch, S. and Velho, G. (1998) Leptin levels, beta-cell function, and insulin sensitivity in families with congenital and acquired generalized lipoatropic diabetes. J Clin Endocrinol Metab 83, 503–508. Garg, A., Wilson, R., Barnes, R., Arioglu, E., Zaidi, Z., Gurakan, F., Kocak, N., O’Rahilly, S., Taylor, S. I., Patel, S. B. and Bowcock, A. M. (1999) A gene for congenital generalized lipodystrophy maps to human chromosome 9q34. J Clin Endocrinol Metab 84, 3390–3394. Agarwal, A. K., Arioglu, E., De Almeida, S., Akkoc, N., Taylor, S. I., Bowcock, A. M., Barnes, R. I. and Garg, A. (2002) AGPAT2 is mutated in congenital generalized lipodystrophy linked to chromosome 9q34. Nat Genet 31, 21–23. Magre, J., Delepine, M., Khallouf, E., Gedde-Dahl, T., Jr., Van Maldergem, L., Sobel, E., Papp, J. et al. (2001) Identification of the gene altered in Berardinelli–Seip congenital lipodystrophy on chromosome 11q13. Nat Genet 28, 365–370. Lawrence, J. (1946) Lipodystrophy and hepatomegaly with diabetes, lipaemia and other metabolic disorders. Lancet 1, 724–741. Kobberling, J. and Dunnigan, M. G. (1986) Familial partial lipodystrophy: two types of an X linked dominant syndrome, lethal in the hemizygous state. J Med Genet 23, 120–127. Jackson, S. N., Howlett, T. A., McNally, P. G., O’Rahilly, S. and Trembath, R. C. (1997) Dunnigan–Kobberling syndrome: an autosomal dominant form of partial lipodystrophy. QJM 90, 27–36. Garg, A. (2000) Gender differences in the prevalence of metabolic complications in familial partial lipodystrophy (Dunnigan variety). J Clin Endocrinol Metab 85, 1776–1782. Hegele, R. A. (2001) Premature atherosclerosis associated with monogenic insulin resistance. Circulation 103, 2225–2229. Cao, H. and Hegele, R. A. (2000) Nuclear lamin A/C R482Q mutation in Canadian kindreds with Dunnigan-type familial partial lipodystrophy. Hum Mol Genet 9, 109–112. Shackleton, S., Lloyd, D. J., Jackson, S. N., Evans, R., Niermeijer, M. F., Singh, B. M., Schmidt, H., Brabant, G., Kumar, S., Durrington, P. N., Gregory, S., O’Rahilly, S. and Trembath, R. C. (2000) LMNA, encoding lamin A/C, is mutated in partial lipodystrophy. Nat Genet 24, 153–156. Hutchison, C. J. (2002) Lamins: building blocks or regulators of gene expression? Nat Rev Mol Cell Biol 3, 848–858. De Sandre-Giovannoli, A., Bernard, R., Cau, P., Navarro, C., Amiel, J., Boccaccio, I., Lyonnet, S., Stewart, C. L., Munnich, A., Le Merrer, M. and Levy, N. (2003) Lamin A truncation in Hutchinson–Gilford progeria. Science 300 (5628), 2055. Eriksson, M., Brown, W. T., Gordon, L. B., Glynn, M. W., Singer, J., Scott, L., Erdos, M. R., Robbins, C. M., Moses, T. Y., Berglund, P., Dutra, A., Pak, E., Durkin, S., Csoka, A. B., Boehnke, M., Glover, T. W. and Collins, F. S. (2003) Recurrent de novo point mutations in lamin A cause Hutchinson–Gilford progeria syndrome. Nature 423, 293–298. Flier, J. S. (2000) Pushing the envelope on lipodystrophy. Nat Genet 24, 103–104.

REFERENCES

531

55. Garg, A., Vinaitheerthan, M., Weatherall, P. T. and Bowcock, A. M. (2001) Phenotypic heterogeneity in patients with familial partial lipodystrophy (Dunnigan variety) related to the site of missense mutations in lamin a/c gene. J Clin Endocrinol Metab 86, 59–65. 56. Simha, V. and Garg, A. (2002) Body fat distribution and metabolic derangements in patients with familial partial lipodystrophy associated with mandibuloacral dysplasia. J Clin Endocrinol Metab 87, 776–785. 57. Novelli, G., Muchir, A., Sangiuolo, F., Helbling-Leclerc, A., D’Apice, M. R., Massart, C., Capon, F., Sbraccia, P., Federici, M., Lauro, R., Tudisco, C., Pallotta, R., Scarano, G., Dallapiccola, B., Merlini, L. and Bonne, G. (2002) Mandibuloacral dysplasia is caused by a mutation in LMNA-encoding lamin A/C. Am J Hum Genet 71, 426–431. 58. Pendas, A. M., Zhou, Z., Cadinanos, J., Freije, J. M., Wang, J., Hultenby, K., Astudillo, A., Wernerson, A., Rodriguez, F., Tryggvason, K. and Lopez-Otin, C. (2002) Defective prelamin A processing and muscular and adipocyte alterations in Zmpste24 metalloproteinase-deficient mice. Nat Genet 31 (1), 94–99. 59. Agarwal, A. K., Fryns, J. P., Auchus, R. J. and Garg, A. (2003) Zinc metalloproteinase, ZMPSTE24, is mutated in mandibuloacral dysplasia. Hum Mol Genet 12 (16), 1995–2001. 60. Rosen, E. D. and Spiegelman, B. M. (2001) PPARgamma: a nuclear regulator of metabolism, differentiation, and cell growth. J Biol Chem 276, 37 731–37 473. 61. Barroso, I., Gurnell, M., Crowley, V. E., Agostini, M., Schwabe, J. W., Soos, M. A., Maslen, G. L., Williams, T. D., Lewis, H., Schafer, A. J., Chatterjee, V. K. and O’Rahilly, S. (1999) Dominant negative mutations in human PPARgamma associated with severe insulin resistance, diabetes mellitus and hypertension. Nature 402, 880–883. 62. Savage, D. B., Tan, G. D., Acerini, C. L., Jebb, S. A., Agostini, M., Gurnell, M., Williams, R. L., Umpleby, A. M., Thomas, E. L., Bell, J. D., Dixon, A. K., Dunne, F., Boiani, R., Cinti, S., Vidal-Puig, A., Karpe, F., Chatterjee, V. K. and O’Rahilly, S. (2003) Human metabolic syndrome resulting from dominant-negative mutations in the nuclear receptor peroxisome proliferator-activated receptor-gamma. Diabetes 52, 910–917. 63. Agarwal, A. K. and Garg, A. (2002) A novel heterozygous mutation in peroxisome proliferator-activated receptor-gamma gene in a patient with familial partial lipodystrophy. J Clin Endocrinol Metab 87, 408–411. 64. Hegele, R. A., Cao, H., Frankowski, C., Mathews, S. T. and Leff, T. (2002) PPARG F388L, a transactivation-deficient mutant, in familial partial lipodystrophy. Diabetes 51, 3586–3590. 65. Gurnell, M., Savage, D. B., Chatterjee, V. K. and O’Rahilly, S. (2003) The metabolic syndrome: peroxisome proliferator-activated receptor gamma and its therapeutic modulation. J Clin Endocrinol Metab 88, 2412–2421. 66. Garg, A. (2000) Lipodystrophies. Am J Med 108, 143–152. 67. Mathieson, P. W. and Peters, D. K. (1997) Lipodystrophy in MCGN type II: the clue to links between the adipocyte and the complement system. Nephrol Dial Transplant 12, 1804–1806. 68. Carr, A., Samaras, K., Thorisdottir, A., Kaufmann, G. R., Chisholm, D. J. and Cooper, D. A. (1999) Diagnosis, prediction, and natural course of HIV-1 protease-inhibitorassociated lipodystrophy, hyperlipidaemia, and diabetes mellitus: a cohort study. Lancet 353, 2093–2099. 69. Carr, A. and Cooper, D. A. (2000) Adverse effects of antiretroviral therapy. Lancet 356, 1423–1430. 70. Grinspoon, S. (2001) Insulin resistance in the HIV–lipodystrophy syndrome. Trends Endocrinol Metab 12, 413–419.

532

SYNDROMES OF SEVERE INSULIN RESISTANCE (SSIRs)

71. Millay, R. H., Weleber, R. G. and Heckenlively, J. R. (1986) Ophthalmologic and systemic manifestations of Alstrom’s disease. Am J Ophthalmol 102, 482–490. 72. Russell-Eggitt, I. M., Clayton, P. T., Coffey, R., Kriss, A., Taylor, D. S. and Taylor, J. F. (1998) Alstrom syndrome. Report of 22 cases and literature review. Ophthalmology 105, 1274–1280. 73. Michaud, J. L., Heon, E., Guilbert, F., Weill, J., Puech, B., Benson, L., Smallhorn, J. F., Shuman, C. T., Buncic, J. R., Levin, A. V., Weksberg, R. and Breviere, G. M. (1996) Natural history of Alstrom syndrome in early childhood: onset with dilated cardiomyopathy. J Pediatr 128, 225–229. 74. Connolly, M. B., Jan, J. E., Couch, R. M., Wong, L. T., Dimmick, J. E. and Rigg, J. M. (1991) Hepatic dysfunction in Alstrom disease. Am J Med Genet 40, 421–424. 75. Hearn, T., Renforth, G. L., Spalluto, C., Hanley, N. A., Piper, K., Brickwood, S., White, C., Connolly, V., Taylor, J. F., Russell-Eggitt, I., Bonneau, D., Walker, M. and Wilson, D. I. (2002) Mutation of ALMS1, a large gene with a tandem repeat encoding 47 amino acids, causes Alstrom syndrome. Nat Genet 31, 79–83. 76. Savage, D. B., Agostini, M., Barroso, I., Gurnell, M., Luan, J., Meirhaeghe, A., Harding, A. H., Ihrke, G., Rajanayagam, O., Soos, M. A., George, S., Berger, D., Thomas, E. L., Bell, J. D., Meeran, K., Ross, R. J., Vidal-Puig, A., Wareham, N. J., O’Rahilly, S., Chatterjee, V. K. and Schafer, A. J. (2002) Digenic inheritance of severe insulin resistance in a human pedigree. Nat Genet 31, 379–384. 77. Savkur, R. S., Philips, A. V. and Cooper, T. A. (2001) Aberrant regulation of insulin receptor alternative splicing is associated with insulin resistance in myotonic dystrophy. Nat Genet 29, 40–47. 78. Vannini, P., Ciavarella, A., Forlani, G., Mustacchio, A., Patrono, D. and Capelli, M. (1987) Investigation of insulin resistance associated with Werner’s syndrome. Diabet Metab 13, 81–85. 79. Chen, L., Lee, L., Kudlow, B. A., Dos Santos, H. G., Sletvold, O., Shafeghati, Y., Botha, E. G., Garg, A., Hanson, N. B., Martin, G. M., Mian, I. S., Kennedy, B. K. and Oshima, J. (2003) LMNA mutations in atypical Werner’s syndrome. Lancet 362 (9382), 440–445. 80. Muggeo, M., Flier, J. S., Abrams, R. A., Harrison, L. C., Deisserroth, A. B. and Kahn, C. R. (1979) Treatment by plasma exchange of a patient with autoantibodies to the insulin receptor. N Engl J Med 300, 477–480. 81. Eriksson, J. W., Bremell, T., Eliasson, B., Fowelin, J., Fredriksson, L. and Yu, Z. W. (1998) Successful treatment with plasmapheresis, cyclophosphamide, and cyclosporin A in type B syndrome of insulin resistance. Case report. Diabetes Care 21, 1217–1220. 82. Baumann, G. and Drobny, E. C. (1984) Enhanced efficacy of U-500 insulin in the treatment of insulin resistance caused by target tissue insensitivity. Am J Med 76, 529–532. 83. Arioglu, E., Duncan-Morin, J., Sebring, N., Rother, K. I., Gottlieb, N., Lieberman, J., Herion, D., Kleiner, D. E., Reynolds, J., Premkumar, A., Sumner, A. E., Hoofnagle, J., Reitman, M. L. and Taylor, S. I. (2000) Efficacy and safety of troglitazone in the treatment of lipodystrophy syndromes. Ann Intern Med 133, 263–274. 84. Chao, L., Marcus-Samuels, B., Mason, M. M., Moitra, J., Vinson, C., Arioglu, E., Gavrilova, O. and Reitman, M. L. (2000) Adipose tissue is required for the antidiabetic, but not for the hypolipidemic, effect of thiazolidinediones. J Clin Invest 106, 1221–1228. 85. Oral, E. A., Simha, V., Ruiz, E., Andewelt, A., Premkumar, A., Snell, P., Wagner, A. J., DePaoli, A. M., Reitman, M. L., Taylor, S. I., Gorden, P. and Garg, A. (2002) Leptinreplacement therapy for lipodystrophy. N Engl J Med 346, 570–578.

REFERENCES

533

86. Farooqi, I. S., Jebb, S. A., Langmack, G., Lawrence, E., Cheetham, C. H., Prentice, A. M., Hughes, I. A., McCamish, M. A. and O’Rahilly, S. (1999) Effects of recombinant leptin therapy in a child with congenital leptin deficiency. N Engl J Med 341, 879–884. 87. Petersen, K. F., Oral, E. A., Dufour, S., Befroy, D., Ariyan, C., Yu, C., Cline, G. W., DePaoli, A. M., Taylor, S. I., Gorden, P. and Shulman, G. I. (2002) Leptin reverses insulin resistance and hepatic steatosis in patients with severe lipodystrophy. J Clin Invest 109, 1345–1350. 88. Nakae, J., Kato, M., Murashita, M., Shinohara, N., Tajima, T. and Fujieda, K. (1998) Long-term effect of recombinant human insulin-like growth factor I on metabolic and growth control in a patient with leprechaunism. J Clin Endocrinol Metab 83, 542–549. 89. Quin, J. D., Fisher, B. M., Paterson, K. R., Inoue, A., Beastall, G. H. and MacCuish, A. C. (1990) Acute response to recombinant insulin-like growth factor I in a patient with Mendenhall’s syndrome. N Engl J Med 323, 1425–1426. 90. Morrow, L. A., O’Brien, M. B., Moller, D. E., Flier, J. S. and Moses, A. C. (1994) Recombinant human insulin-like growth factor-I therapy improves glycemic control and insulin action in the type A syndrome of severe insulin resistance. J Clin Endocrinol Metab 79, 205–210. 91. Haque, W. A., Shimomura, I., Matsuzawa, Y. and Garg, A. (2002) Serum adiponectin and leptin levels in patients with lipodystrophies. J Clin Endocrinol Metab 87 (5), 2395.

18 Therapeutic Strategies for Insulin Resistance Harpal S. Randeva, Margaret Clarke and Sudhesh Kumar

18.1 Introduction Unlike the patients described in the previous chapter, who are insulin resistant due to major inherited defects in the insulin signalling pathway, in most patients with common type 2 diabetes obesity plays a key role in the development of insulin resistance. Until recently, there have been few options by way of pharmacological approaches to tackle the underlying problems of the metabolic syndrome. Approaches used have focussed on diet and lifestyle advice and treatment of secondary issues, for example tight control of hyperglycaemia and other cardiovascular risk factors. The advent of use of thiazolidinediones in type 2 diabetes has led to the possibility of newer pharmacological treatments for insulin resistance. Likewise, more intensive management of obesity using drugs and also surgery has provided the clinician with more treatment options for the obese, insulin-resistant type 2 diabetic patient. Here in, we will give an overview of possible benefits of pharmacological treatments and current strategies to manage obesity and insulin resistance. Treating the underlying pathogenic factors at an earlier phase of the disease is a more rational approach, and this involves managing obesity as a major predetermining factor of insulin resistance, and/or using ‘insulin-sensitizing’ drugs.

18.2

Obesity and insulin resistance

Although insulin resistance is associated with obesity, evidence suggests that insulin resistance is more closely related to the distribution of body fat rather Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

536

THERAPEUTIC STRATEGIES FOR INSULIN RESISTANCE

Table 18.1 Classification of the metabolic syndrome (A) National Cholesterol Education Program (NCEP)–2002 Risk factor

Defining level

Abdominal obesity

Waist circumference

Men Women Triglycerides

>102 cm (>40 inches) >88 cm (>35 inches) ≥150 mg/dl or 1.7 mmol/l

HDL cholesterol Men Women

<40 mg/dl or 1.04 mmol/l <50 mg/dl or 1.30 mmol/l

Blood pressure

≥130/≥85 mm Hg

Fasting glucose

≥110 mg/dl or 6.1 mmol/l

(B) World Health Organization (WHO) definition At least oneof: - glucose intolerance - IGT - type 2 diabetes - insulin resistance Plus At least two of: - impaired glucose regulation or diabetes - insulin resistance - central obesity waist:hip ratio >0.90 for men; >0.85 for women; and/or BMI > 30 kg/m2 - ↑blood pressure (≥140/90 mm Hg) - ↑plasma triglycerides (1.7 mmol/l or 150 mg/dl) and/or - ↓HDL cholesterol <0.9 mmol/L or 35 mg/dl for men; <1.0 mmol/L or 39 mg/dl for women - microalbuminuria urinary albumin excretion rate ≥ 20 µ g/min, or albumin to creatinine ratio ≥ 30 mg/g

than the overall fat mass.1 Intra-abdominal visceral fat (central obesity) is metabolically more active than subcutaneous fat, and with its direct access to the portal circulation there is an increased delivery to the liver of substances such as free fatty acids, augmenting hepatic gluconeogenesis, and impairing the regulation of glucose, insulin and lipid metabolism. Insulin resistance and compensatory hyperinsulinaemia not only contribute to hyperglycaemia, but also play a pathophysiologic role in a variety of other metabolic abnormalities including (a) dyslipidaemia (low levels of high-density lipoprotein (HDL) cholesterol and high levels of plasma triglycerides), (b) hypertension and (c) coronary artery

MANAGEMENT OF OBESITY

537

Table 18.2 Factors associated with developing insulin resistance Over age 40 years A sedentary lifestyle Non-Caucasian ethnicity A family history of type 2 diabetes, hypertension or cardiovascular disease (CVD) A history of glucose intolerance or gestational diabetes Body mass index (BMI) ≥ 25 kg/m2 A waist circumference of >40 inches for men, >35 inches for women A diagnosis of hypertension, elevated triglycerides/low HDL-cholesterol or CVD Acanthosis nigricans Polycystic ovary syndrome

disease, with abnormal fibrinolysis.2, 3 Individuals with the metabolic syndrome meet three or more of the criteria listed in Table 18.1. With the global epidemic of obesity, 20–30 percent of adults in western societies are obese and insulin resistant; most are able to produce enough insulin to maintain non-diabetic glucose levels. Over 80 per cent of the 16 million Americans who have type 2 diabetes are insulin resistant. The current epidemic of obesity among children and adolescents puts them at risk for insulin resistance and its complications. More recently, the WHO expert consultation has attempted to address the debate on whether Asian populations should have different body-mass index (BMI) cut-off points for determining overweight and obesity.4 This is in light of the fact that Asian populations have different associations between BMI, percentage of body fat and health risks than do European populations.4 Irrespective of race and geographical differences, individuals who are more likely to have or develop insulin resistance are listed in Table 18.2. The more factors (Table 18.2) an individual has, the greater the likelihood of having the insulin resistance syndrome. Insulin resistance and its metabolic dysfunction lead to a cluster of abnormalities, and the development of atherosclerosis through multiple risk factors (Figure 18.1), with serious clinical consequences, most importantly cardiovascular disease and/or type 2 diabetes. Both the National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III) and the World Health Organization (WHO) (Table 18.1) recently recognized the metabolic syndrome as a secondary therapeutic target for the prevention of cardiovascular diseases.5

18.3

Management of obesity

This includes lifestyle modification, including for example increasing physical exercise and reducing calorie intake, as well as more specialized diets looking at alterations in carbohydrate, fatty acid and protein intake. However, all lifestyle modifications are troubled by difficulties in maintaining levels of patient compliance. The metabolic abnormalities that are seen in obese individuals arise

538

THERAPEUTIC STRATEGIES FOR INSULIN RESISTANCE Genetic

Obesity

Lack of exercise

Hypercoagulability

Hyperinsulinaemia Insulin resistance

Microalbuminuria

Hyperglycaemia

Endothelial dysfunction

Hypertension Dyslipidaemia

Impaired fibrinolysis

ATHEROSCLEROSIS

Figure 18.1

Obesity, insulin resistance and the link with atherosclerosis

because of decreased sensitivity of peripheral tissues to insulin. In 1973, Sims et al.6 showed that normal young men who were overfed for six months and subsequently increased their weight by 21 per cent (of which 73 per cent was fat) had a significant increase in fasting serum insulin, glucose and cholesterol with a corresponding decrease in glucose tolerance. When the overfeeding was stopped they lost weight and the insulin insensitivity returned to normal. Similar observations have been seen in animal studies.7 Epidemiological evidence for the increasing problem of obesity and associated increases in morbidity and mortality is unequivocal and mounting.8 Data shows that for each increase in weight by 1 kg the risk of diabetes in the population increases by 4.5 per cent.9 The metabolic defects associated with increased weight and subsequent increased mortality are also reversible with weight loss (Table 18.3). In overweight diabetics, for example, the excess mortality risk is reversed by a 15–20 per cent weight loss in the first year after diagnosis.10 A deliberate weight loss of 0.5–9.0 kg is associated with a 30–40 per cent reduction in diabetes-related mortality.11 The lynch-pin of management of insulin resistance is sustained weight loss. Unfortunately this has not been achieved within our population. Indeed the prevalence of obesity is increasing at an exponential rate. Various approaches to dietary modification have been used to treat obesity and insulin resistance and these are discussed in Chapter 11. In addition to dietetic advice, patients benefit from a multidisciplinary approach and other professionals involved include psychologists, psychiatrists and bariatric surgeons.

DIETARY MANAGEMENT OF OBESITY

Table 18.3 Mortality

18.4

Benefits of 5–10 kg weight loss (from SIGN 1996) Diabetes

>20% reduction total mortality >30% reduction diabetes-related mortality >40% reduction obesity-related cancers

539

Blood pressure

50% reduction fasting 10 mm reduction plasma glucose systolic pressure 20 mm reduction diastolic pressure

Lipids 10% reduction total cholesterol 15% reduction LDL-C 8% rise HDL-C 30% reduction triglycerides

Dietary management of obesity

Obesity is a chronic condition, and therefore short term dietary programmes are unlikely to be effective in the long term but can motivate an individual as an initial boost to weight loss. The services of a dietician with experience of working with obese patients is invaluable. Initial assessment should be with a physician and dietician. A full history and examination should be performed and should include weight history and record previous attempts at weight loss. The conventional approach, i.e. telling an individual to ‘go on a diet’, may increase resistance to change, and an understanding of the process of change is helpful. Realistic goals should be set. It is unrealistic for an individual with extreme obesity to aim to lose the amount of weight necessary to achieve the targets set on standard weight tables. A weight loss of 5–10 per cent of the initial body weight is associated with clinically useful improvements in insulin resistance12 – 14 (Table 18.3). Therefore, a 600 kcal/day reduction in intake is both realistic and achievable. Nutrition therapy, which reduces caloric intake, should be designed not only to induce weight loss, but also to improve blood pressure, decrease plasma glucose and improve the lipid profile. Studies over five years show that although individuals can achieve a weight loss of on average 5–10 per cent initially, many regain the weight lost.15 Maintenance programmes can be used to improve the long term results; these often involve behaviour therapy and ongoing contact by phone and mail.16, 17 Dietary manipulation is effective. The Diabetes Prevention Programme Group showed a reduction in the incidence of diabetes in persons at high risk of 58 per cent in the lifestyle modification group compared with placebo, after a mean follow-up of 2.8 years.18 The Diabetes Prevention Study looked at the difference in outcome between patients given dietary advice and annual follow-up compared with an intensive lifestyle intervention programme. The ‘intensively’ treated group had significantly improved results with regard to weight loss.19 The findings are supported by other large trials, the FDPS,20 STOP-NIDDM21 and Da Qing,22 all highlighting that intensive treatment with

540

THERAPEUTIC STRATEGIES FOR INSULIN RESISTANCE

diet or exercise or both decreased the incidence of type 2 diabetes in subjects with impaired glucose tolerance compared with the control group.

18.5

Exercise and physical activity

Physical activity can have a positive effect on risk factors and diseases in the obese population, as discussed in Chapter 12. Though the exact mechanism is not known, exercise has many benefits for health and CVD risk factors, and reduces cardiovascular morbidity and mortality. For example, walking has been associated with substantial reduction in the incidence of type 2 diabetes mellitus23 and has also been shown to decrease significantly the risk of coronary heart disease.24 The type of exercise needs to be tailored, but regular brisk walking is a cheap and socially acceptable form of activity, which can be conducted frequently without requiring special equipment or facilities. Brisk walking carries a low risk of injury and has known health benefits. Exercise has a favourable action on modifying blood lipids, particularly HDL cholesterol in overweight individuals.25 Other studies have shown beneficial effects on blood pressure.26 Exercise has been shown to increase insulin sensitivity, GLUT-4 concentration and glucose disposal.27 Regular physical exercise improves endothelial function, by increasing vasculature shear stress and by increased production of nitric oxide.28 In overweight and insulin-resistant subjects, exercise has also been shown to reduce the non-traditional cardiovascular risk factor homocysteine.29 It is known that regular exercise, even in overweight individuals, leads to an improvement in the fibrinolytic system,30 though the precise mechanism is not clear. People who are overweight but also active are at much reduced overall risk for mortality and morbidity than those who are overweight and inactive.31, 32 Overweight and obese individuals should focus on three energy expenditure targets:33 (a) more weight-bearing movement as part of the daily routine, (b) less time spent in sedentary pursuits and (c) bouts of longer periods of aerobic exercise, sustained for 40 minutes or above. However, little is gained unless long term changes are established, and this is known to be difficult to achieve in the majority of individuals, although approaches involving behaviour modification, cognitive therapy and ongoing support from professionals/other patients can be helpful. Unfortunately, compliance with non-pharmacologic therapy, including diet and exercise, is generally poor, and pharmacological therapy eventually becomes necessary in most patients.

18.6 Anti-obesity drugs Therapeutic intervention can be helpful in cases where, despite the best efforts of patients and health care workers, weight loss has not been achieved or maintained. An ideal anti-obesity therapeutic agent is one that effectively lowers body weight, exerts beneficial effects on components of the metabolic syndrome,

ANTI-OBESITY DRUGS

541

including insulin resistance, and importantly is safe and well tolerated. Previous agents used to effect weight loss have included phentermine, a catecholaminergic drug with stimulant properties. It is only licensed for use for less than 8 weeks. Abuse and dependence can occur with this drug, and there is no good evidence to support its use in weight management. Two other centrally acting drugs – fenfluramine and dexfenfluramine – have both been withdrawn from use in the UK because of the risk of valvular heart disease. Currently, the two therapeutic agents licensed for use in weight management in the UK are orlistsat and sibutramine; both are approved by the National Institute of Clinical Excellence (NICE) for use in the National Health Service (NHS).

Orlistat Orlistat is a potent inhibitor of both gastric and pancreatic lipases. These are the two key enzymes required for the hydrolysis of dietary fat in the gastrointestinal tract. When administered with food, orlistat partially inhibits the hydrolysis of triglycerides, thus reducing the subsequent absorption of monoacylglycerides and free fatty acids.34 In total, 30 per cent of fat that would otherwise have been absorbed passes through the bowel and is excreted in the faeces. The pharmacokinetics of orlistat indicates minimal systemic absorption, with no evidence of accumulation after short term administration – 97 per cent is excreted in the faeces, 83 per cent as unchanged drug.35 Orlistat has been shown to aid weight loss in double-blind placebo-controlled trials.36, 37 The orlistat group lost 10.2 versus 6.1 per cent of body weight over one year,36, 37 and treatment with orlistat (120 mg t.i.d) for 12–104 weeks was associated with significant reductions in total cholesterol levels, low density lipoprotein cholesterol (LDL) and LDL to high density lipoprotein (HDL) ratio. Reductions in triglyceride were noted in three trials, but levels were unchanged in the others. HDL cholesterol did not change. Variable results have been shown on blood pressure. Orlistat has been shown to reduce fasting plasma glucose and fasting plasma insulin in patients with insulin resistance, notably those with type 2 diabetes. Orlistat should be taken before, during or up to one hour after each main meal. Patients should be on a nutritionally balanced, mildly hypocaloric diet that contains 30 per cent of calories from fat. Orlistat is licensed for a maximum duration of treatment of two years. Adverse effects are significant only on the gastrointestinal tract. These were usually mild to moderate and occurred early in treatment. They included oil spotting from the rectum (27 per cent), flatulence with discharge (24 per cent), faecal urgency (22 per cent), fatty/oily stools (20 per cent), oily evacuation (12 per cent), increased defaecation (11 per cent) and faecal incontinence (3 per cent). The incidence of side-effects increases if the diet is high in fat. No clinically relevant abnormalities in laboratory values were noted in clinical trials. In the majority of trials serum levels of the fat soluble vitamins (A, D and E) and β-carotene remained within the reference

542

THERAPEUTIC STRATEGIES FOR INSULIN RESISTANCE

range, although these levels were lower than those of placebo-treated patients in some trials. It is therefore recommended the diet should be rich in fruit and vegetables. In addition to this, NICE has recommended that the patient should have already lost 2.4 kg by diet and exercise prior to starting orlistat; their BMI should be above 30 kg/m2 or 28 kg/m2 if they have other co-morbidities. Patients should receive appropriate dietary advice from health professionals. Continuation of treatment beyond 3 months should be accompanied by a weight loss of five per cent from the initial body weight and beyond six months by a loss of 10 per cent.38, 39

Sibutramine Sibutramine is an orally administered, centrally acting weight management agent. It is apparently devoid of amphetamine-like abuse potential. The primary (BTS 54 505) and secondary (BTS 54 354) amine metabolites of sibutramine are pharmacologically active and are thought to induce the natural processes leading to the enhancement of satiety and thermogenesis by inhibiting serotonin and noradrenaline re-uptake. The pharmacological activity of sibutramine does not appear to be a result of increased serotonin release; this differentiates it from the action of dexfenfluramine, which predominantly causes the release of serotonin and dexamphetamine, which predominantly releases dopamine and noradrenaline. This may account for the lack of abuse potential with sibutramine.40 The drug undergoes first pass metabolism to form pharmacologically active primary (M1) and secondary (M2) metabolites. In trials steady state plasma metabolite concentrations were maintained throughout treatment.41 Plasma concentrations of sibutramine and its metabolites are unaffected by the presence of renal dysfunction.42 However, sibutramine is contraindicated in patients with significant hepatic dysfunction. In most trials sibutramine was administered with a reduced calorie diet and activity advice. Trial data has shown weight loss in up to 77 per cent of patients treated with sibutramine 10 mg/day and a 600 kcal/day deficit diet. There was also sustained weight loss in patients continuing therapy for 2 years.43 At higher doses (up to 30 mg/day), greater initial weight loss has been reported.44 Patients receiving 10–20 mg/day lost 5.0–7.5 kg of body weight over an 8–12 week period, compared with placebo recipients, who lost between 1.5 and 3.5 kg. In individuals with type 2 diabetes, weight loss of more than 10 per cent was achieved by a third of subjects on sibutramine, and this weight loss was associated with improvements in both metabolic control and quality of life.45 However, in the UK, the NICE guidelines state that sibutramine should only be prescribed as part of an overall treatment plan for the management of nutritional obesity in people aged 18–65 years who have either a BMI of >27.0 kg/m2 in the presence of co-morbidities or >30 kg/m2 without associated co-morbidities. The recommended starting dose of sibutramine is 10 mg o.d. with or without food. Sibutramine should be used in conjunction with a reduced calorie diet.

SURGICAL MANAGEMENT OF OBESITY

543

If a weight loss of 1.8 kg is not achieved within the first 4 weeks of therapy, either an increase in the dose to 15 mg o.d. or discontinuation of sibutramine should be considered. Dosages higher than 15 mg are not recommended. The most commonly reported adverse effects include headache, dry mouth, anorexia, insomnia and constipation. Statistically significant increases in blood pressure and heart rate (compared with placebo) were observed in obese patients without hypertension who received sibutramine. Blood pressure monitoring is therefore required before, and at regular intervals during, therapy. Treatment with sibutramine is not recommended for individuals whose blood pressure before the start of therapy is >145/90 mm Hg. It should be discontinued if it rises above this level or if the increase is greater than 10 mm Hg.38 Sibutramine should not be given to patients with poorly controlled hypertension, and it is also contraindicated for patients with coronary heart disease, congestive cardiac failure, arrhythmia, stroke or severe renal or hepatic impairment.40

18.7

Surgical management of obesity

Surgery as a treatment for obesity is not new. Techniques such as jaw wiring and stapled gastroplasty have been used for some time with variable results and complications. In some carefully selected patients newer surgical techniques (performed by a surgeon with experience in this field) can achieve a weight loss of up to 60 per cent. There are two approaches, either restrictive or malabsorptive surgical techniques. Many procedures involve a combination of these. Techniques to restrict intake include the stapled gastroplasty, an operation devised by Mason in 1982. It involves dividing the stomach by a line of staples into a small upper pouch with a capacity of about 15 ml, which communicates with the main body of the stomach via a stoma about 9 mm in diameter (Figure 18.2). When the patient eats or drinks, the pouch rapidly fills and stops further ingestion. This procedure is effective at limiting intake of solid food, but liquids can be taken fairly easily. Over time the pouch tends to stretch, thus allowing more intake. The procedure is relatively safe because the bowel is not cut open and food is normally digested and absorbed. The average weight loss at 1 year is 28.8 kg. More recently, extra-gastric banding has been used. Again this restricts the capacity of the stomach but it is achieved by wrapping an inextensible material around the outside. This can be done by either open or laproscopic techniques. In a multicentre study of 70 consecutive patients the excess weight loss in morbidly obese patients was 59 per cent (pre-op mean BMI = 45.2 kg/m2 ).46 This approach to weight loss has been shown to have associated improvement in insulin sensitivity and β-cell function. In a series of 254 patients who underwent adjustable gastric banding paired data from pre-operative and 1 year follow-up biochemistry showed marked improvement in insulin resistance.47 Malabsorptive procedures include the gastric bypass, bilio-pancreatic diversion and jejuno-ileal bypass. The current gold standard is the Roux en Y gastric

544

THERAPEUTIC STRATEGIES FOR INSULIN RESISTANCE

Figure 18.2 Cartoons show the principles of the bilio-pancreatic bypass and lap-band procedures for bariatric surgery (illustrations kindly supplied by Robert, E. Brolin, M. D., New Jersey Bariatrics, www.njbariatricspc.com)

bypass (Figure 18.2). This can have results of greater than 50 per cent weight loss in over 80 per cent of patients, corresponding to a fall of 15 BMI units in morbidly obese patients (BMI > 40 kg/m2 ) and 20 BMI units in super-obese patients (BMI > 50 kg/m2 ).48 An ongoing intervention study, the Swedish Obesity Study (SOS), enrolled over 2000 surgically treated patients and a similar number of matched controls. After 2 years follow-up the surgically treated patients had lost an average of 28 kg and the incidence of diabetes was reduced by 90 per cent.49 Complications from surgery in this high risk group include immediate cardiorespiratory complications with pulmonary embolus accounting for the majority of deaths. Abdominal wall complications occur in 6–10 per cent. Later complications include pouch dilation/erosion of the bands or staple line disruption, diarrhoea and the dumping syndrome. Nutritional complications are very common after bypass techniques and many patients require iron, folate and B12 supplementation.50

18.8

Pharmacological treatment of insulin resistance

Metformin Metformin is the only biguanide available for clinical use. Although metformin has a small effect as a peripheral insulin sensitizer, it primarily works by

PHARMACOLOGICAL TREATMENT OF INSULIN RESISTANCE

545

reducing hepatic gluconeogenesis and hepatic glycogenolysis, and by enhancing insulin-stimulated glucose uptake and glycogenesis by skeletal muscle.51 This effect may be mediated through stimulation of AMP-activated protein kinase.52 It does not cause hypoglycaemia or weight gain, which is extremely advantageous for many patients with associated obesity. Following the results of metformin in the United Kingdom Prospective Diabetes Study (UKPDS), it has become the first line pharmacological treatment for type 2 diabetes in overweight individuals in the United Kingdom.53 Beneficial effects for metformin in patients with insulin resistance but without type 2 diabetes have also been shown. Although not a true insulin sensitizer, metformin treatment lower plasma insulin levels and corrects many of the non-traditional cardiovascular risk factors associated with the insulin resistance syndrome. Various studies have used metformin in patients with polycystic ovarian syndrome with positive effects both on weight and sex-hormone-binding globulin, androgens and insulin resistance above that of diet alone.54, 55 Patients with acanthosis nigricans given metformin have also shown a reduction in hyperinsulinaemia, body weight and fat mass and improved insulin sensitivity.56 Patients with impaired glucose tolerance but not overt diabetes have been treated with metformin and diet in various studies. It has been shown that metformin also improves insulin resistance in these individuals and in some studies there appears to be an anti-obesity effect.57, 58 However, the use of metformin does not appear to alter the long term susceptibility of developing type 2 diabetes above the use of diet and lifestyle modifications alone.19 Side-effects in the gut include bloating, flatulence, diarrhoea and epigastric discomfort, which are common at the start of therapy. These can be minimized by starting at a low dose of 500 mg once or twice daily with meals. These side-effects resolve with time in many patients and the dose can be increased to a therapeutic level of 1 g twice daily. The drug is contraindicated in patients with renal impairment as it is excreted unchanged in the urine and excess accumulation causes hyperlactataemia and the risk of the rare complication of lactic acidosis. Other conditions leading to tissue hypoxia, for example severe heart failure or advanced liver disease, also exclude the use of metformin.

Thiazolidinediones Thiazolidinediones (TZDs) are novel compounds chemically and functionally unrelated to other oral blood-glucose-lowering agents. The antihyperglycaemic effects of TZDs were noticed by actions of ciglitazone on obese and diabetic animals in the early 1980s. Many agents in this class have followed, including troglitazone, pioglitazone and rosiglitazone. A thiazolidine-2-4-dione structure is common to all agents of this class, but they possess different side-chains that influence their pharmacological actions and potential for adverse effects. Troglitazone was introduced for clinical use in 1997 in Japan, the United States and United Kingdom, but its use was voluntarily suspended in the United Kingdom

546

THERAPEUTIC STRATEGIES FOR INSULIN RESISTANCE O CH3 H3C

N O

S

Troglitazone

O CH3

O

HO CH3 O Et N

Pioglitazone

S N

O O O CH3

N

N

N

Rosiglitazone

S O O

Figure 18.3 Structure of rosiglitazone and pioglitazone as distinct from troglitazone

in December 1997 following reports of side-effects on the liver and subsequently it was withdrawn worldwide due to problems with idiosyncratic hepatotoxicity. It is the α-tocopherol moiety on the side-chain of troglitazone that was thought to be implemented in hepatotoxicity (Figure 18.3). Thiazolidinediones (TZDs) have emerged as an important therapeutic drug class in the management of type 2 diabetes mellitus. Administration of a thiazolonedione results in increased insulin sensitivity in insulin-resistant mammals.59 – 61 This is thought to be associated with increased insulin gene expression in both skeletal muscle and adipose tissue and increased intrinsic activity of glucose transporters.62 The actions of the TZDs are mediated through binding and activation of the peroxisome proliferator-activated receptor (PPAR) γ, a nuclear receptor that has a regulatory role in the differentiation of cells, particularly adipocytes.63, 64 Since TZDs mediate their effects via gene transcription, the maximal therapeutic effect is seen 6–8 weeks after start of therapy. PPAR-γ is expressed mainly in white and brown adipocytes, where it is complexed to the retinoid X receptor (RXR) within the nucleus. Being lipophilic, TZDs enter the cells and bind to PPAR-γ with high affinity. This causes a conformational change in the PPAR-γ–RXR complex, which displaces a corepressor and allows activation of regulatory sequences of DNA, which in turn controls expression of specific genes. Thus, increased expression of insulinsensitive genes, through the activation of PPAR-γ, is perceived as the main mechanism by which TZDs reduce insulin resistance. At least some of these

PHARMACOLOGICAL TREATMENT OF INSULIN RESISTANCE

547

genes are also controlled by insulin, and TZDs amplify or mimic certain genomic effects of insulin on adipocytes. Activation of PPAR-γ is associated with control of the production, transport and utilization of glucose. The increased glucose transport has been attributed to increased production of the glucose transporter isoforms GLUT1 and GLUT4, and translocation of GLUT4 into the plasma membrane. Increased glucose transporter production and translocation into the plasma membrane in skeletal muscle and fat will contribute to improved glucose disposal and reduce glucose toxicity. Glucose toxicity will be further reduced by increased glucose disposal and decreased hepatic glucose production. The PPAR-γ receptor is also expressed in several other tissues, including vascular tissue. TZDs lower circulating triglyceride and non-esterified fatty acid concentrations, which may also contribute to improved insulin sensitivity65 via the glucose fatty acid (Randle) cycle. Because free fatty acids are involved in lipid metabolism and also have deleterious effects on the vasculature, this reduction in plasma free fatty acids may have a beneficial effect on cardiovascular disease. The lipid-lowering effect of TZDs appears to be independent of their glucose-lowering and their insulin-lowering effects,66 and this effect has been attributed to decreased hepatic very low density lipoprotein (VLDL) synthesis and increased peripheral clearance, together with reduced lipolysis. It is important to note that TZDs have effects on numerous other genes, which may also be related to the effects seen on glycaemic control and insulin resistance. For example, they reduce circulating TNF-α , which may be related to the development of obesity-linked insulin resistance. TZDs also reduce serum leptin, but increase the circulating levels of the antidiabetic, anti-inflammatory and anti-atherogenic agent adiponectin.

Rosiglitazone Rosiglitazone (Figure 18.3) is rapidly absorbed and food does not affect absorption significantly.67 It is highly bound to plasma proteins (99.8 per cent) and metabolized by the liver. It is given in doses of 4–8 mg as single or divided doses. There is virtually no unchanged drug secreted in the urine or faeces. In the UK it is licensed for use as monotherapy, or in combination with a sulfonylurea or metformin. Rosiglitazone is contraindicated for use in patients with heart failure, and with insulin therapy in the UK, but is used in combination with insulin in the USA. It is also contraindicated in patients with impaired liver function (ALT > 2.5 × normal). Monitoring of liver enzymes is recommended, every two months for the first year and periodically thereafter. Adverse effects related to rosiglitazone therapy include significant increase in body weight (see below) and a decrease in haemoglobin and haematocrit. In controlled clinical trials with rosiglitazone given as monotherapy, dosedependent reduction in fasting plasma glucose and glycated haemoglobin have

548

THERAPEUTIC STRATEGIES FOR INSULIN RESISTANCE

been reported;68 – 72 study duration varied in these studies from 8 to 52 weeks. Drug-na¨ıve patients show a better response to therapy than those previously treated with other oral agents.70 A study of combination treatment of sulfonylureas with either 2 or 4 mg of rosiglitazone has been published.73 In a study of 574 subjects, patients were randomized to continuing sulfonylurea therapy or the addition of either 2 or 4 mg of rosiglitazone to their therapy. Rosiglitazone, at both doses, in combination with sulfonylurea was associated with significant reduction in HbA1c from baseline. Furthermore, the percentage of patients who achieved HbA1c reduction of >0.7 per cent was 19 per cent in the control group versus 60 per cent in those receiving 4 mg of rosiglitazone with sulfonylurea. In addition to sulfonylureas, rosiglitazone has also been studied in combination with metformin. Fonseca et al., reported a mean reduction of 0.56–0.78 per cent in HbA1c from baseline after 26 weeks of rosiglitazone therapy in combination with metformin.74 During this period there was a 0.45 per cent increase in HbA1c from baseline in those receiving metformin alone. In addition to improving glycaemic parameters, rosiglitazone improves endogenous insulin secretion and significantly reduces NEFA levels.73, 74 Insulin resistance, measured using homeostasis model assessment (HOMA), was shown to be significantly reduced in patients with type 2 diabetes taking rosiglitazone 4–8 mg/day monotherapy over 12–52 weeks. There was no significant change in patients taking placebo or glibenclamide.75 Similarly, rosiglitazone 2–8 mg/day in combination with a sulfonulurea or metformin for 26 weeks resulted in significant reductions in insulin resistance (HOMA) versus no significant changes with sulfonylurea or metformin alone.76 Rosiglitazone may reduce insulin-resistance-related cardiovascular disease risk in type 2 diabetes patients.77 Euglycaemic clamp data substantiate these results: the insulin sensitivity index was significantly increased (by 78 per cent from baseline) in 33 patients with type 2 diabetes mellitus receiving rosiglitazone 8 mg/day.78 These effects appear to be sustained with continued treatment for at least 24 months.79 Indeed, rosiglitazone has also been shown to improve β-cell function by up to 94 per cent as assessed by mathematical modelling of fasting glucose and insulin data (HOMA).80 Furthermore, it is reported that open-label extension studies indicate no deterioration of glycaemic control in patients taking rosiglitazone during the 2 years of follow-up. If confirmed, this could prove to be a major advantage in the treatment of type 2 diabetes and insulin resistance as the progression of this disease is characterized by failing β-cell function.

Pioglitazone Pioglitazone (Figure 18.3), like rosiglitazone, mediates its effects through improved peripheral glucose disposal and reduced hepatic glucose production.81 Pioglitazone absorption from the gut is delayed when taken with food but without alteration of its clinical efficacy.73 Pioglitazone undergoes extensive hepatic

PHARMACOLOGICAL TREATMENT OF INSULIN RESISTANCE

549

metabolism via the CYP2C8 system. Secondary pathways include CYP3A4, CYP2C9 and CYP1A1/2.74, 80 Time to peak plasma concentration is 2.5 h for 15 mg/day and 3 h for 30 mg/day, with an elimination half-life of 3.3 and 4.9 h, respectively. Pioglitazone can be administered once daily at a dose of 15–45 mg. Clinical trials have examined its effects during monotherapy and in combination. Clinical efficacy in terms of reducing HbA1c levels was shown in a doubleblind dose-ranging study in which 399 patients were randomized to receive pioglitazone (7.5, 15, 30 or 45 mg/day) or placebo for 26 weeks. Mean HbA1c levels decreased significantly (p < 0.05 versus placebo) with pioglitazone 15, 30 or 45 mg/day in both previously treated and untreated patients.81 In another randomized double-blind study, involving 197 patients with type 2 diabetes mellitus, pioglitazone 30 mg/day for 16 weeks significantly reduced mean HbA1c (adjusted change versus placebo = −1.37 per cent; p < 0.05), and fasting plasma glucose and triglyceride levels.82 Similar effects on glycaemic control using pioglitazone as monotherapy have been reported by others.83 In a double-blind study of 560 patients with poorly controlled type II diabetes mellitus on sulfonylurea therapy,84 addition of pioglitazone therapy (15 or 30 mg/day) for 16 weeks significantly decreased HbA1c levels (by 0.9 and 1.3 per cent, respectively; p < 0.05) and fasting blood glucose levels (by 2.2 and 3.2 mmol/l respectively; p < 0.05), relative to sulfonylurea plus placebo. Furthermore, combination treatment of pioglitazone (30 mg/day) and metformin (>2 g/day in 40 per cent of patients) for 16 weeks significantly decreased HbA1c and fasting glucose levels in a double-blind study in 328 patients with type 2 diabetes.85 Administration of pioglitazone 30 mg/day has no significant affects on the pharmacodynamic characteristics of warfarin, glipizide, metformin or digoxin.74 Lack of induction or inhibition of hepatic enzyme systems was also indicated by data showing no statistically or clinically significant effect of pioglitazone on the pharmacokinetics of ethinyloestradiol/norethindrone or ethinyloestradiol/oestrone as used in oral contraceptive or hormone replacement therapy regimens.1 However, adverse effects reported include headache, sinusitis, myalgia, tooth disorders and pharyngitis.2 In the UK, although licensed for use as monotherapy as an alternative to metformin (if intolerant of metformin) and also in combination with metformin or sulfonylurea, their use is restricted within the National Health Service by current guidelines. It has been recommended that their use is confined to those patients inadequately controlled on oral monotherapy and who are unable to tolerate or have contraindications to conventional drug combination therapy of metformin and a sulfonylurea. These guidelines seriously limit the current clinical use of TZDs in the UK. Several studies have clearly shown an advantage for the glitazones in drug-na¨ıve type 2 diabetic patients.69, 70 The same research shows the complementary effect of the three major classes of oral hypoglycaemic agents. Their effects are synergistic and particularly effective in combination

550

THERAPEUTIC STRATEGIES FOR INSULIN RESISTANCE

therapy.84 The combination of TZDs with insulin in insulin-resistant patients is a logical strategy but under current guidelines it is not recommended because of potential problems, including fluid retention.

Thiazolidinediones and weight gain Weight gain is associated with both thiazolidinediones. There were initial concerns that weight gain with TZD use may have an adverse impact on glycaemic control, and that the increase in the absolute number of fat cells may lead to refractory obesity. However, increases in body weight with TZD use are positively correlated with reductions in HbA1c and weight gain appears to stabilize after the initial reductions in HbA1c . Significant variability in the adipose tissue distribution of PPAR-γ may be responsible for the observation that TZDs have a site-specific effect on differentiation of human preadipocytes, with the effect being markedly enhanced in subcutaneous fat, with less effect in visceral fat.86, 87 Several studies have attempted to elucidate the mechanisms behind the apparent paradox of TZDs improving insulin sensitivity while simultaneously causing weight gain. These include increased appetite and a decrease in serum leptin,88 although not all studies have shown this effect. Fat redistribution may also explain the weight gain seen with TZDs. Fat redistribution may be explained by induced remodelling of abdominal fat tissue, characterized by differentiation of preadipocytes into small fat cells in subcutaneous fat depots and apoptosis of differentiated large adipocytes (hypertrophic adipocytes) in visceral and/or subcutaneous fat depots. Indeed, several studies have demonstrated that the weight gain with TZDs is associated with an increase in subcutaneous adipose tissue and a concomitant decrease in visceral fat content. This altered fat distribution also improves insulin sensitivity. Carey et al.89 reported that 16 weeks therapy with rosiglitazone (8 mg daily), in patients with type 2 diabetes, increased subcutaneous fat by eight per cent (p = 0.02 versus placebo) and decreased intrahepatic fat by 45 per cent (p = 0.04 versus placebo). In another study by Kelley et al.,90 rosiglitazone improved insulin sensitivity and led to a 10 per cent reduction in visceral fat. These beneficial effects of fat redistribution have also been seen with pioglitazone.91 Fluid retention is another potential mechanism by which TZDs lead to weight gain, although the precise cause remains unclear. Peripheral oedema is particularly a problem when TZDs are used in combination with insulin,2 and this is one reason why TZDs are not licensed for use in combination with insulin in the UK, although they are in the USA. Fluid retention and the potential precipitation of congestive cardiac failure in patients with underlying heart disease represent the major concern of most health care providers. Because of increases in plasma volume, rosiglitazone and pioglitazone should be used cautiously in patients with signs of impaired cardiac function, such as peripheral oedema. Although in animal studies TZDs have been reported to cause cardiac hypertrophy, in

INSULIN SENSITIZERS AND CARDIOVASCULAR RISK FACTORS

551

echocardiographic clinical studies (a 52 week study using rosiglitazone, and a 26 week study with pioglitazone) in patients with type 2 diabetes no deleterious alterations in cardiac structure or function were observed.92, 93 Apart from fluid retention, lack of compliance with diet is another factor that contributes to weight gain. In addition, weight gain appears to be greatest when TZDs are used in combination with insulin or sulphonylureas and least when used as monotherapy or in combination with metformin. Therefore, previous glycaemic control and type of concomitant therapy may prove to be to the bases for predicting which patients are most likely to gain weight. Education about diet and exercise at time of prescription, low-calorie diets and concomitant use of metformin are strategies to minimize weight gain in individuals given TZDs.

18.9

Insulin sensitizers and cardiovascular risk factors

Most patients with obesity and the insulin resistance syndrome exhibit a spectrum of clinical abnormalities (Table 18.1) that play an important role in the pathogenesis of atherosclerosis (Figure 18.1). It has therefore been proposed that drugs that directly improve insulin sensitivity, such as metformin and the TZDs, may correct other abnormalities of the insulin resistance syndrome in addition to improving hyperglycaemia. Thus, treatment of patients with type 2 diabetes with these agents may confer benefits beyond the lowering of glucose.

Metformin Metformin is frequently perceived as a drug that induces weight loss. However, data from the UKPDS showed no change in the weight of patients taking metformin throughout the study.53 In the Diabetes Prevention Program,18 metformin did not cause a greater weight loss than that seen with placebo, and there was a minimal change in weight during the 4 years of the study. This contrasted with the lifestyle-change group, in which participants lost an average of 5.6 kg. Thus, metformin appears to be weight neutral in the long term. To date, metformin is the only drug that has been shown to decrease cardiovascular events in patients with type 2 diabetes, independently of glycemic control.53 More importantly, the UKPDS demonstrated that patients who were obese and randomized to receive metformin had a significantly reduced rate (30 per cent reduction) of cardiovascular disease events and mortality compared with those receiving conventional therapy when analysed on an intention-totreat basis.53 Although the reason for this difference is not clear, it may be related to moderate effects exerted by metformin on the insulin resistance syndrome; metformin treatment lowers plasma insulin levels and corrects many of the non-traditional risk factors associated with the insulin resistance syndrome.94 Metformin has a favorable, albeit modest, effect on plasma lipids, particularly lowering levels of triglycerides and LDL cholesterol; however, it has little if any

552

THERAPEUTIC STRATEGIES FOR INSULIN RESISTANCE

effect on HDL cholesterol levels.95 Although TZDs were not included in the UKPDS, several long term trials, including A Diabetes Outcome Progression Trial (ADOPT), Diabetes Reduction Approaches with Ramipril and Rosiglitazone Medications (DREAM) and the Action to Control Cardiovascular Risk in Diabetes (ACCORD) Trial, are ongoing to evaluate their effect on prevention of cardiovascular events in patients with type 2 diabetes.

Thiazolidinediones Because of their beneficial effects on hyperinsulinaemia and insulin resistance, the cardiovascular effect of thiazolidinediones is a subject of considerable research interest (Table 18.4). Several studies have observed beneficial effects of the thiazolidinediones on lipid metabolism. With rosiglitazone therapy, changes in serum lipids included the increase in HDL cholesterol and total cholesterol, but the LDL:HDL cholesterol ratio did not change.72, 73 Serum triglycerides increased slightly.73 Clinical trials suggest that pioglitazone has more impressive effects, compared with rosiglitazone, on serum lipids,84, 85, 96 with significant decrease in mean fasting serum triglyceride levels and significant increases in fasting HDL cholesterol levels. Caution needs to be exercised in comparing rosiglitazone and pioglitazone, as no head-to-head study has been conducted. In addition, the differences between the thiazolidinediones with respect to their lipid effects may reflect the fact that populations with different baseline values have been studied, and therefore a randomized comparative trial is needed to determine whether a true difference exists. Several studies have noted that TZDs can reduce blood pressure in normotensive and hypertensive animals, without any obvious correlation with either Table 18.4 Impact of TZDs on traditional and non-traditional cardiovascular risk factors Risk factor Lipids

Vascular effects

Microalbuminuria Coagulation Inflammation Endothelial function

Effects ↓ ↑ ↓ ↓ ↓ ↓ ↓ ↑ ↓ ↓ ↓ ↓ ↓ ↓ ↓

LDL oxidation HDL levels Triglyceride levels blood pressure vascular contraction vascular smooth muscle cell migration intima–media thickness cardiac output microalbuminuria plasma activator inhibitor-1 (PAI-1) fibrinogen C-reactive protein interleukin-6 cell adhesion molecules PAI-1

CONCLUSIONS

553

the glucose-lowering or insulin-lowering effects.97 Improving insulin sensitivity has the potential to lower blood pressure in patients with insulin resistance and/or diabetes. A study of 24 hypertensive patients without diabetes treated with rosiglitazone demonstrated that rosiglitazone treatment that was added on to the patient’s usual antihypertensive medication resulted in a decrease in both systolic and diastolic blood pressure and improved insulin resistance.98 Pioglitazone in normotensive and hypertensive patients with diabetes has been shown to decrease systolic blood pressure.99 Similar results were also seen in those without diabetes who were obese.100 Elevated plasma plasminogen activator–inhibitor type 1 (PAI-1) is associated with increased risk of atherosclerosis and cardiovascular disease, and PAI-1 levels are elevated both in patients with diabetes and in those who are insulin resistant without diabetes. Increased PAI-1 levels are now recognized as an integral part of the insulin resistance syndrome and correlate significantly with plasma insulin. Studies with rosiglitazone101 and pioglitazone102 have demonstrated a decrease in plasma PAI-1 levels in patients with diabetes, suggesting that PAI-1 reduction may well be a class effect of the insulin sensitizers. Other non-traditional cardiovascular risk factors, such as C-reactive protein and interleukin-6, have been shown to decrease with TZD therapy. Microalbuminuria, widely considered as a marker of impaired vascular integrity, is a recognized marker of cardiovascular disease. Rosiglitazone has been recently shown to significantly reduce urinary albumin excretion in patients with type II diabetes,103 adding to the beneficial effects of TZDs. Carotid intima–media complex thickness, which is an indicator for early atherosclerosis and a surrogate marker for atherosclerotic events, is associated with insulin resistance. Treatment with pioglitazone was shown to significantly decrease intima–media thickness in patients with type 2 diabetes.104 Furthermore, endothelial dysfunction is a complication of the insulin resistance syndrome, and improvement of vascular reactivity in insulin-resistant obese subjects without diabetes after treatment with rosiglitazone has been reported.105 This improvement was associated with beneficial changes in several markers of inflammation and endothelial activation. Recently, metformin also has been shown to improve endothelial function.106 Because metformin does not stimulate PPARs, other mechanisms are likely to be involved in the pathogenesis of endothelial dysfunction in insulin resistance. It is possible, therefore, that these effects of the thiazolidinediones are direct cellular effects on the atherosclerotic process that are not linked to their effects on insulin resistance.

18.10

Conclusions

The prevalence of the metabolic syndrome is increasing and reaching epidemic proportions. Obesity plays a pivotal role in the development of insulin resistance and its complications. Strategies to manage body weight should be

554

THERAPEUTIC STRATEGIES FOR INSULIN RESISTANCE

part of the treatment plan for obese insulin-resistant patients, and will include a multidisciplinary approach with dietetic input, exercise and anti-obesity therapeutic intervention. However, many of these strategies will not be able to have a major and lasting effect on insulin sensitivity, and there is therefore a need for ‘insulin-sensitizing’ drugs using metformin and/or TZDs. Because many cardiovascular risk factors are linked with insulin resistance, treatment with insulin sensitizers has the potential to modulate these traditional and nontraditional cardiovascular risk factors favourably, including a favourable redistribution of fat. Finally, although weight gain may occur with TZD therapy, it is not inevitable and can be controlled with dietary methods; the addition of metformin also mitigates additional weight gain and may have an additive effect on insulin sensitivity.

References 1. Kissebah, A. H. and Krakower, G. R. (1994) Regional adiposity and morbidity. Physiol Rev 74, 761–811. 2. Boden, G., Chen, X., Capulong, E. and Mozzoli, M. (2001) Effects of free fatty acids on gluconeogenesis and autoregulation of glucose production in type 2 diabetes. Diabetes 50, 810–816. 3. Steinberg, H. O., Paradisi, G., Hook, G., Crowder, K., Cronin, J. and Baron, A. D. (2000) Free fatty acid elevation impairs insulin-mediated vasodilation and nitric oxide production. Diabetes 49, 1231–1238. 4. Reaven, G. M., Lithell, H. and Landsberg, L. (1996) Hypertension and associated metabolic abnormalities: the role of insulin resistance and the sympathoadrenal system. N Engl J Med 334, 374–381. 5. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. (2001) Executive summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA 285, 2486–2497. 6. Sims, E. A. H., Danforth, E., Jr. and Horton, E. S. et al. (1973) Endocrine and metabolic effects of experimental obesity in man. Recent Progr Hormone Res 29, 457–496. 7. Hansen, B. C. and Bodkin, N. L. (1986) Heterogeneity of insulin responses: phases in the continuum leading to non-insulin dependent diabetes mellitus. Diabetolgica, 29, 713–719. 8. Ortmeyer, H. K., Bodkin, N. L., Varghese, S. S. and Hansen, B. C. (1996) Glycogen phosphorylase activity and glycogen concentrations in muscle of normal to overtly diabetic rhesus monkeys. Int J Obes 20, 98–105. 9. Ford, E. S., Williamson, D. F. and Liu, S. (1997) Weight change and diabetes incidence: findings from a cohort of US adults. Am J Epidemiol 146, 214–222. 10. Lean, M. E. J., Powrioge, J. K., Anderson, A. S. and Garthwaite P. H. (1990) Obesity, weight loss and prognosis in type 2 diabetes. Diabet Med 7, 228–233. 11. Williamson, D. F., Pamuk, E., Thun, M., Flanders, D., Byers, T. and Heath, C. (1995) Prospective study of intentional weight loss and mortality in never-smoking overweight US white women aged 40–64 years. Am J Epidemiol 141, 1128–1141.

REFERENCES

555

12. Goldstein, D. J. (1992) Beneficial effects of modest weight loss. Int J Obes 16, 397–415. 13. Stamler, J., Farinaro, E., Mojonnier, L. M., Hall, Y., Moss, D. and Stamler, R. (1980) Prevention and control of hypertension by nutritional–hygienic means. Longterm experience of the Chicago Coronary Prevention Evaluation Program. JAMA 243, 1819–1823. 14. Kanalay, J. A., Anderson-Reid, M. L., Oening, L., Kottke, B. A. and Jenson, M. D. (1993) Differential health benefits of weight loss in upper body and lower body obese women. Am J Clin Nutr 57, 20–26. 15. King, A. C. and Tribble, D. L. (1991) The role of exercise in weight reduction in nonatheletes. Sports Med 11, 331–349. 16. Perri, M. G., Shapiro, R. M., Warren, W. L. and McAdoo, W. G. (1984) Maintenance strategies for the treatment of obesity: an evaluation of relapse prevention training and post treatment contact by mail and telephone. J Consult Clin Psychol 52 (3), 404–413. 17. Perri, M. G., Neyu, A. M., Patti, E. T. and McCann, L. L. (1989) Effect of length of treatment on weight loss. J Consult Clin Psychol 57 (3), 450–452. 18. Diabetes Prevention Program Research Group. (2002) Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 346, 393–403. 19. Eriksson, J. and Lindstrom, J. et al. (1999) Prevention of type II diabetes in subjects with impaired glucose tolerance: the Diabetes Prevention Study (DPS) in Finland. Study design and 1 year interim report on the feasibility of the lifestyle modification programme. Diabetologia; 42 (7), 793–801. 20. Tuomilehto, J., Lindstrom, J. and Eriksson, J. G. et al. (2001) Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 344, 1343–1350. 21. Chiasson, J. L., Josse, R. G. and Gomis, R. et al. (2002) Acarbose for prevention of type 2 diabetes mellitus: the STOP-NIDDM randomized trial. Lancet 359, 2072–2077. 22. Pan, X. R., Li, G. W. and Hu, Y. H. et al. (1997) Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance. The Da Qing IGT and Diabetes Study. Diabetes Care 20, 537–544. 23. Hu, F. B., Sigal, R. J. and Rich-Edwards, J. W. et al. (1999) Walking compared with vigorous physical activity and risk of type 2 diabetes in women. JAMA 282, 1433–1439. 24. Lee, I. M., Rexrode, K. M., Cook, N. R., Manson, J. E. and Buring, J. E. (2001) Physical activity and coronary heart disease in women: is ‘no pain, no gain’ passe? JAMA 285, 1447–1454. 25. Wood, P. D., Stefanick, M. L., Williams, P. T. and Haskell, W. L. (1991) The effect on plasma lipoproteins of a prudent weight reducing diet, with or without exercise, in overweight men and women. N Engl J Med 325, 461–466. 26. Krotievski, M., Mandroukas, L. and Sjostrom, L. et al. (1979) Effects of longterm physical training on body fat, metabolism, and blood pressure in obesity. Metabolism 28, 650–658. 27. Helmrick, S. P., Ragland, D. R., Leung, R. W. and Paffenbarger, R. S. (1991) Physical activity and reduced occurrence of non-insulin dependent diabetes mellitus. N Engl J Med 325, 147–152. 28. Hambrecht, R., Wolf, A. and Gielen, S. et al. (2000) Effect of exercise on coronary endothelial function in patients with coronary artery disease. N Engl J Med 342, 454–460. 29. Randeva, H. S., Lewandowski, K. C., Drzewoski, J., Brooke-Wavell, K., O’Callaghan, C., Czupryniak, L., Hillhouse, E. W. and Prelevic, G. M. (2002) Exercise decreases

556

30.

31. 32. 33. 34. 35. 36.

37.

38. 39.

40. 41. 42. 43. 44. 45.

46. 47.

48. 49. 50. 51. 52.

THERAPEUTIC STRATEGIES FOR INSULIN RESISTANCE

plasma total homocysteine in overweight young women with polycystic ovary syndrome. J Clin Endocrinol Metab 87, 4496–4501. Stratton, J. R., Chandler, W. L. and Schwartz, R. S. et al. (1991) Effects of physical conditioning on fibrinolytic variables and fibrinogen in young and old healthy adults. Circulation 83, 16. Barlow, C. E., Kohl, H. W., Gibbons, L. W. and Blair, S. N. (1995) Physical fitness, mortality and obesity. Int J Obes 19 (Suppl. 4), S41–S44. Lee, C. D., Jackson, A. S. and Blair, S. N. (1998) US weight guidelines: is it also important to consider cardio-respiratory fitness? Int J Obes 22 (Suppl. 20), S2–S7. Obesity. (1999) The Report of the British Nutrition Foundation Task Force. Hanif, M. W. and Kumar, S. (2002) Pharmacological management of obesity. Expert Opin Pharmacother 3 (120), 1711–1728. Roche. (2000) Xenical . Summary of product characteristics. Sojostrom, L., Risanen, A. and Anderson, T. et al. (1998) Randomised placebocontrolled trial of orlistat for weight loss and prevention of weight regain in obese patients. Lancet 352, 167–172. Davidson, M. H., Hauptman, J. and Digirolamo, M. et al. (1999) Weight control and risk factor reduction in obese subjects treated for 2 years with orlistat. JAMA 281, 235–242. NICE Guidelines for Treatment of Obesity. O’Meare, S., Riemsma, R., Shirran, L., Mather, L. and Reit, J. (2000) A Systematic Review of the Clinical Effectiveness and Cost Effectiveness of Sibutramine and Orlistat in the Management of Obesity. Health technology assessment report. McNelly, W. and Goa, K. L. (1998) Sibutramine in obesity: a review. Drugs 56, 1093–1124. Kaiser, P. E. and Hinson, J. L. (1994) Sibutramine dose response and plasma metabolite concentration in weight loss. J. Clin Pharmacol 34, 1019. Johnson, F., Velagapudi, R. and Hind, I. et al. (1997) Effects of renal dysfunction on the pharmacokinetics of sibutramine and its metabolites. J Clin Pharmacol 37, 865. Philip, W., James, T. and Astrup, A. et al. (2000) Effect of sibutramine on weight maintenance after weight loss: a randomized trial. Lancet 356, 2119–2125. Bray, G. A., Ryan, D. H. and Gordon, D. et al. (1996) Double blind randomized placebo-controlled trial of sibutramine. Obes Res 4, 263–270. Fujioka, K., Seaton, T. B. and Rowe, E. et al. (2000) Weight loss with sibutramine improves glycaemic control and other metabolic parameters in obese patients type 2 diabetes mellitus. Diabetes Obes Metab 2, 175–187. Coskun, H., Bozbora, A., Oguna, G. and Peter, Y. (2003) Adjustable gastric banding in multicentre study in Turkey. Obes Surg 13 (2), 294–296. Dixon, J. B., Dixon, A. F. and O’Brien, P. E. (2003) Improvements in insulin sensitivity and β cell function (HOMA) with weight loss in the severely obese. Diabet Med 20 (2), 127. Siter, M., Giusti, V., Heraief, E., Zysset, F. and Calmes, J. M. (2003) Laproscopic Roux en Y gastric bypass: initial 2 year experience. Surg Endosc 17 (4), 603–609. Sj¨ostr¨om, L. (2002) Surgical outcomes from the SOS study. IJO 26 (Suppl. 1), 825. Msika, S. (2003) Surgery for morbid obesity: 2 complications, results of a technologic evaluation by ANAES. J Chir (Paris) 140 (1), 4–21. Bailey, C. J. (2000) Antidiabetic drugs. Br J Cardiol 7, 350–360. Zhou, G., Myers, R., Li, Y., Chen, Y., Shen, X. and Fenyk-Melody, J. et al. (2001) Role of AMP-activated protein kinase in mechanism of metformin action. J Clin Invest 108, 1167–1174.

REFERENCES

557

53. UKPDS Group. (1998) Effect of intensive blood glucose control with metformin on complications in overweight patients with type 2 diabetes (UKPDS 34). Lancet 352, 854–865. 54. Crave, J. C., Fimbel, S. and Lejeune, H. et al. (1995) Effects of diet and metformin administration on sex hormone binding globulin, androgens, and insulin in hirsute and obese women. J Clin Endocrinol Metab 80 (7), 2057–2062. 55. Arslanian, S. A., Lewy, V., Danadian, K. and Saad, R. (2002) Metformin therapy in obese adolescents with polycystic ovary syndrome and impaired glucose tolerance: amelioration of exaggerated adrenal response to adreocorticotrophin with reduction of insulinaemia/insulin resistance. J Clin Endocrinol Metab 87 (4), 1555– 1559. 56. Tankova, T., Koev, D., Dakovska, L. and Kirilov, G. (2002) Therapeutic approach in insulin resistance with acanthosis nigricans. Int J Clin Pract 56 (8), 578–581. 57. Kay, J. P., Alemzadeh, R., Langley, G. and D’Angelo, L. et al. (2001) Beneficial effects of metformin in normglycaemic morbid obese adolescents. Metabolism 50 (12), 1457–1461. 58. Lehtovirta, M., Forsen, B., Gullstom, M. and Haggblom, M. et al. (2001) Metabolic effects of metformin in patients with impaired glucose tolerance. Diabet Med 18 (7), 578–583. 59. Eldershaw, T. P. D., Rattigan, S. and Cawthorne, M. A. et al. (1995) Prior treatment of obese Zucker rats with the thiazolidinedione (BRL 49653) decreases insulin resistance in perfused hindlimb. Diabetes Care 18, A16. 60. Oakes, N. D., Kennedy, C. J. and Jenkins, A. B. et al. (1994) A new antidiabetic agent, BRL 49653, reduces lipid availability and improves insulin action and glucoregulation in the rat. Diabetes 43, 1203–1210. 61. Young, P. W., Cawthorne, M. A. and Coyle, P. J. et al. (1995) Repeat treatment of obese mice with BRL 49653, a new and potent insulin sensitiser, enhances insulin action in white adipocytes: association with increased insulin binding and cell surface GLUT4 as measured by photoaffinity labeling. Diabetes 44, 1087–1092. 62. Moore, G., Pickvance, L. and Clapham, J. et al. (2001) Insulin sensitizing effect of rosiglitazone: effects on metabolism and gene expression [abstract No. 2128-PO]. Diabetes 50 (Suppl. 2), A506. 63. Spiegelman, B. M. (1998) PPARγ: adipogenic regulator and thiazolidindione receptor. Diabetes 47, 507–514. 64. Kletzien, R., Clarke, S. and Ulrich, R. (1992) Enhancement of adipocyte differentiation by an insulin sensitising agent. Mol Pharmacol 41, 393–398. 65. Olefsky, J. M. (2000) Treatment of insulin resistance with peroxisome proliferatoractivated receptor γ agonists. J Clin Invest 106, 467–472. 66. Saltiel, A. R. and Olefsky, J. M. (1996) Thiazolidinediones in the treatment of insulin resistance and type 2 diabetes. Diabetes 45, 1661–1669. 67. Smithkline Beecham. (2000) Avandia: Draft Product Characteristics. 68. Patel, J., Anderson, R. J. and Rappaport, E. B. (1999) Rosiglitazone monotherapy improves glycaemic control in patients with type 2 diabetes: a twelve week, randomized, placebo-controlled study. Diabetes Obes Metab 1, 165–172. 69. Grunberger, G., Dole, J. F. and Freed, M. I. (2000) Rosiglitazone monotherapy significantly lowers HbA1c levels in treatment na¨ıve type 2 diabetic patients. Diabetes 49, A109 441–. 70. Phillips, L. S., Grunberger, G. and Miller, E. et al. (2001) Once and twice-daily dosing with rosiglitazone improves glycaemic control in patients with type 2 diabetes. Diabetes Care 24, 308–315.

558

THERAPEUTIC STRATEGIES FOR INSULIN RESISTANCE

71. Raskin, P., Rappaport, E. B. and Cole, S. T. et al. (2000) Rosiglitazone short-term monotherapy lowers fasting and post prandial glucose in patients with type 2 diabetes. Diabetologia 43, 278–284. 72. Nolan, J. J., Jones, J. P., Patwardhan, R. and Deacon, L. F. (2000) Rosiglitazone taken once daily is effective in the treatment of type 2 diabetes mellitus. Diabet Med 17, 287–294. 73. Wolfenbutttel, B. I. R., Gomist, R. and Patwardhan, R. et al. (2000) Rosiglitazone once or twice daily improves glycaemic control in patients with type 2 diabetes. Diabet. Med. 17, 40–47. 74. Fonseca, V., Biswas, N. and Salzman, A. (1999) Once daily rosiglitazone in combination with metformin effectively reduces hyperglycaemia in patients with type 2 diabetes. Diabetes; 48, 0431. 75. Gerich, J., Doustou, J. and Islam, N. et al. (2001) Mechanisms by which rosiglitazone improves glycaemic control in type 2 diabetes. Diabetologia 44 (Suppl. 1), 201. 76. Leonard, T., Bakst, A. and Warsi, G. et al. (2001) Rosiglitazone may reduce insulin resistance related cardiovascular disease risk in patients with type 2 diabetes. 61st American Diabetes Association Annual Meeting, Philadelphia, PA, 2001, abstract No. 1838-PO. 77. Leonard, T., Bakst, A., Warsi, G. and Bonora, E. (2001) Rosiglitazone may reduce insulin resistance related cardiovascular disease risk in type 2 diabetes patients. Diabetologia 44 (Suppl. 1), 222. 78. Carey, D. G., Cowin, G. J. and Galloway, G. J. et al. (2000) Rosiglitazone increases insulin sensitivity and reduces factors associated with insulin resistance in type 2 diabetics. Diabetes Res Clin Pract 50 (Suppl. 1), P311. 79. Garber, A., Cobitz, A. R. and Deacon, L. et al. Rosiglitazone: Effects on the InsulinResistance Metabolic Syndrome [web page]. http://endoip.abstractcentral.com. 80. Patel, J., Weston, W. M. and Hemyari, P. (1999) Rosiglitazone decreases insulin resistance and improves β cell function in patients with type 2 diabetes mellitus (SmithKline Beecham, data on file, quoted in Barman Balfour J, Plosker G. L. Rosiglitazone). Drugs 57, 921–930. 81. Sugiyama, Y., Shimura, Y. and Ikeda, H. (1990) Effects of pioglitazone on hepatic and peripheral insulin resistance in Wistar fatty rats. Arz Forsch/Drug Res 40, 436–440. 82. Ikeda, H., Taketomi, S. and Sugiyama, Y. et al. (1990) Effects of pioglitazone on glucose and lipid metabolism in normal and insulin resistant animals. Arz Forsch/Drug Res 40, 156–162. 83. Crijns-Kortboyer, J. and Eckland, D. (1999) Pioglitazone has low potential for drug interactions [abstract]. Diabetologia 42 (Suppl. 1), A228. 84. Kaneko, T., Baba, S. and Toyoto, T. et al. (1997) Clinical evaluation of an insulin resistance improving agent, AD-4833, in patients with non-insulin dependent diabetes mellitus on diet therapy alone – a placebo controlled double blind clinical study. Rinsho to Kenkyu 74 (6), 1491–1515. 85. Schneider, R., Lessem, J. and Lekich, R. (1999) Pioglitazone is effective in the treatment of patients with type 2 diabetes [abstract]. Diabetes 48 (Suppl. 1), A109. 86. Pelton, P. D., Zhou, L., Demarest, K. T. and Burris, T. P. (1999) PPARγ activation induces the expression of the adipocyte fatty acid binding protein gene in human monocytes. Biochem Biophys Res Commun 261, 456–458. 87. Albrektsen, T., Frederiksen, K. S., Holmes W. E. et al. (2002) Novel genes regulated by the insulin sensitizer rosiglitazone during adipocyte differentiation. Diabetes 51, 1042–1051.

REFERENCES

559

88. Shimizu, H., Tsuchiya, T. and Sato, N. et al. (1998) Troglitazone reduces plasma leptin concentration but increases hunger in NIDDM patients. Diabetes Care 21, 1470–1474. 89. Carey, D. G., Cowin, G. J. and Galloway, G. J. et al. (2002) Sensitivity effect of rosiglitazone on insulin and body fat composition in type 2 diabetic patients. Obes Res 10, 1008–1015. 90. Kelley, D. E., McKolanis, T. M. and Kelley, C. A. (2002) Comparative effects of rosiglitazone and metformin on fatty liver and visceral adiposity in type 2 diabetes mellitus [abstract]. Diabetes 51 (Suppl. 2), A35. 91. Miyazaki, Y., Mahankali, A. and Matsuda, M. et al. (2002) Effect of pioglitazone on abdominal fat distribution and insulin sensitivity in type 2 diabetic patients. J Clin Endocrinol Metab 87, 2784–2791. 92. GlaxoSmithKline. (2003) Avandia Prescribing Information. 93. Takeda. (1999) Actos Prescribing Information. 94. Kirpichnikov, D., McFarlane, S. I. and Sowers, J. R. (2002) Metformin: an update. Ann Intern Med 137, 25–33. 95. Robinson, A. C., Burke, J., Robinson, S., Johnston, D. G. and Elkeles, R. S. (1998) The effects of metformin on glycemic control and serum lipids in insulin-treated NIDDM patients with suboptimal metabolic control. Diabetes Care 21, 701–705. 96. Yamazaki, H., Suzuki, M. and Tane, K. et al. (2000) In vitro inhibitory effects of troglitazone and its metabolites on drug oxidation activators of human cytochrome P450 enzymes: comparison with pioglitazone and rosiglitazone. Xenobiotica 30 (1), 61–70. 97. Stevenson, R. W., Gibbs, E. M. and Krenter, D. K. et al. (1995) The thiazolidinedione drug series. In: Marshall S. M., Home P. D., Rizza R. A., eds. The Diabetes Annual 9 Amsterdam: Elsevier, 175–191. 98. Raji, A., Seely, E. W., Bekins, S. A., Williams, G. H. and Simonson, D. C. (2003) Rosiglitazone improves insulin sensitivity and lowers blood pressure in hypertensive patients. Diabetes Care 26, 172–178. 99. Scherbaum, W. German Pioglitazone Study Group and G¨oke, B. (2001) Pioglitazone reduces blood pressure in patients with type-2-diabetes mellitus [abstract]. Diabetes 50 (Suppl. 2), A462. 100. Tack, C. J., Ong, M. K., Lutterman, J. A. and Smits, P. (1998) Insulin-induced vasodilatation and endothelial function in obesity/insulin resistance: effects of troglitazone. Diabetologia 41, 569–576. 101. Freed, M., Fuell, D., Menci, L., Heise, M. and Goldstein, B. (2000) Effect of combination therapy with rosiglitazone and glibenclamide on PAI-1 antigen, PAI-1 activity, and tPA in patients with type 2 diabetes [abstract]. Diabetologia 43 (Suppl. 1), p. A267. 102. Kato, K., Satoh, H., Endo, Y., Yamada, D., Midorikawa, S., Sato, W., Mizuno, K., Fujita, T., Tsukamoto, K. and Watanabe, T. (1999) Thiazolidinediones down-regulate plasminogen activator inhibitor type 1 expression in human vascular endothelial cells: a possible role for PPAR γ in endothelial function. Biochem Biophys Res Commun 258, 431–435. 103. Bakris, G. L., Viberti, G., Weston, W. M., Heise, M., Porter, L. E. and Freed, M. I. (2003) Rosiglitazone reduces urinary albumin excretion in type 2 diabetes mellitus. J Hum Hypertens 17, 7–12. 104. Koshiyama, H., Shimono, D., Kuwamura, N., Minamikawa, J. and Nakamura, Y. (2001) Inhibitory effect of pioglitazone on carotid arterial wall thickness in type 2 diabetes. J Clin Endocrinol Metab 86, 3452–3456.

560

THERAPEUTIC STRATEGIES FOR INSULIN RESISTANCE

105. Mohanty, P., Aljada, A., Ghanim, H., Tripathy, D., Syed, T., Hofmeyer D. and Dandona, P. (2001) Rosiglitazone improves vascular reactivity, inhibits reactive oxygen species (ROS) generation, reduces p47phox subunit expression in mononuclear cells (MNC) and reduces C reactive protein (CRP) and monocyte chemotactic protein-1 (MCP 1): evidence of a potent anti-inflammatory effect [abstract]. Diabetes 50 (Suppl. 2), p. A68. 106. Mather, K. J., Verma, S. and Anderson, T. J. (2001) Improved endothelial function with metformin in type 2 diabetes mellitus. J Am Coll Cardiol 37, 1344–1350.

19 Drug Therapy for Insulin Resistance – a Look at the Future Bei B. Zhang and David E. Moller

19.1 Introduction Type 2 diabetes is a complex metabolic disorder characterized by abnormal insulin secretion caused by impaired β-cell function and insulin resistance in target tissues.1, 2 The worldwide prevalence of type 2 diabetes is reaching epidemic proportions, with an expected total of 221 million cases by the year 2010.3 The single most important risk factor for the pathogenesis of diabetes is obesity and its associated insulin resistance. Indeed, insulin resistance per se and type 2 diabetes are components of the more complex ‘metabolic syndrome’ that also encompasses impaired glucose tolerance, obesity, hypertension and dyslipidaemia.3 Insulin is essential for maintaining glucose homeostasis and regulating carbohydrate, lipid and protein metabolism.2 The hormone elicits a diverse array of biological responses by binding to its specific receptor4, 5 (Figure 19.1). Extensive studies have indicated that the ability of the receptor to autophosphorylate and to phosphorylate intracellular substrates is essential for its mediation of the complex cellular responses of insulin.6 – 9 Insulin receptors trans-phosphorylate several immediate substrates (on Tyr residues) including insulin receptor substrate (IRS) proteins 1–4, Shc and Gab 1, each of which provides specific docking sites for other signalling proteins containing Src homology 2 (SH2) domains.10 These events lead to insulin-mediated activation of glucose transport and glycogen synthesis through activation of downstream signalling molecules including phosphatidylinositol-3-kinase (PI-3-kinase) and Akt (or PKB).11, 12 Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

562

DRUG THERAPY FOR INSULIN RESISTANCE – A LOOK AT THE FUTURE Glucose transporter (GLUT-4)

Insulin receptor P P

P P

Cbl/CAP complex

PTP 1B SHC SOS/Ras

Grb2

JNK IKK β

Hexokinase

IRS1/2/3/4

PI-3 K

G-6-P

PTEN SHIP2 UGPglucose

PDK

Oxidative glucose metabolism

MEK aPKC

Akt

Glycogen synthase

MAP kinase GSK3

Gene expression Growth regulation

p70S6k

PP1

Signal transduction

Glycogen

Glucose utilization Glycogen/lipid/protein synthesis

Figure 19.1 Diagram of insulin signal transduction pathways

Mice lacking the insulin receptor (IR) gene via targeted disruption die within the first week after birth due to severe diabetic ketoacidosis.13 – 15 Decreased cellular responses to insulin or perturbation of the insulin signalling pathways are associated with a number of pathological states. Mutations in the IR gene that lead to alterations of receptor synthesis, degradation and function have been described in patients with several uncommon syndromes associated with severe insulin resistance.16 Several studies have also shown modest decreases in insulin receptor number, attributed to downregulation in response to hyperinsulinaemia, in tissues or cells from type 2 diabetes patients.17, 18 Substantial decreases in insulin-stimulated receptor tyrosine kinase activity have been reported. More importantly, substantial defects affecting the insulin signal transduction pathway, including receptor-mediated IRS phosphorylation or phosphatidylinositol (PI)-3 kinase activation, have been described using samples of tissue (e.g. muscle or fat) derived from rodents or human subjects with type 2 diabetes.19 – 22 However, the detailed molecular basis for insulin resistance that precedes, or is associated with, common forms of type 2 diabetes remains poorly understood. As discussed in earlier chapters, a number of agents are currently being used as therapies for insulin resistance. Notably, PPARγ ligands appear to principally target this aspect of the pathogenesis of type 2 diabetes. However, the diabetes and metabolic syndrome epidemic is growing at an alarming rate and current therapies are clearly suboptimal with respect to net efficacy and their potential for adverse effects.23 These facts underscore the importance of identifying new therapeutic targets for insulin resistance. There is emerging evidence

TARGETING THE INSULIN SIGNALLING PATHWAY

563

suggesting that modulation of specific components of the insulin signal transduction pathways could impact on insulin sensitivity in vivo, thereby presenting putative targets for amelioration of insulin resistance. Furthermore, since insulin resistance in association with obesity is likely to be related to excessive levels of circulating lipids and tissue lipid accumulation (known as ‘lipotoxicity’), selective modulation of lipid metabolism, apart from engaging PPARγ directly, also represents a future avenue for the treatment of insulin resistance. In this chapter, we will discuss potential advantages and concerns that pertain to a number of newer drug ‘targets’ that have been implicated as being useful in the treatment of insulin resistance.

19.2 Targeting molecules within the insulin signal transduction pathway Insulin receptor The insulin receptor (IR) is a heterotetrameric protein consisting of two extracellular α-subunits and two transmembrane β-subunits. The binding of the ligand to the IR α-subunits stimulates the tyrosine kinase activity intrinsic to the β-subunits. Structural biology studies reveal that the two α-subunits jointly participate in insulin binding and that the kinase domains in the two β-subunits are juxtaposed in order to permit autophosphorylation of tyrosine residues as the first step of IR activation.24 The kinase domain undergoes a conformational change upon autophosphorylation, providing a basis for activation of the kinase and binding of downstream signalling molecules.25, 26 The IR is homologous to the insulin-like growth factor 1 receptor (IGF1R) with the highest degree of homology in the tyrosine kinase domain.27, 28 Indeed, hybrid receptors containing α/β-halves of both the IR and IGF-1R have been identified in mammalian tissues.29, 30 Another homologous receptor in the insulin-receptor family is the insulin-receptor-related receptor (IRR).31 The cognate hormone ligand for and biological function of IRR are yet to be identified. Since the IR has an important role in the regulation of whole body metabolism and diabetes pathogenesis, small molecule agents that can activate IRs or potentiate insulin action at the receptor level might prove to be useful as novel therapeutics for diabetes. In recent years, several small molecule IR activators have been discovered and shown to activate insulin signalling in cells and to decrease blood glucose levels in murine models of diabetes when dosed orally.32 – 35 These molecules have also shown insulin-sensitizing effects in cellular and animal models. Although these agents are still in early preclinical research stages, the identification of such molecules demonstrates, in principle, the feasibility of an ‘insulin pill’ that could potentially be developed as an insulin mimetic or sensitizer.

564

DRUG THERAPY FOR INSULIN RESISTANCE – A LOOK AT THE FUTURE

IRS proteins The four IRS proteins identified to date are highly homologous with overlapping and differential tissue distribution. Studies with genetic deletion in mouse models and cell lines indicate that IRS proteins serve complementary functions in different tissues as immediate substrates for IRs and IGF-1Rs.36 – 38 Combined heterozygous deletions of IRs and IRS-1 or IRS-2 suggest that IRS-1 has a prominent role in skeletal muscle and IRS-2 in liver.39 Since IRS proteins are key docking proteins that serve to relay signals from IRs, intervention to modulate the interactions of IRS proteins with other signalling molecules could potentially represent a new avenue for up-regulation of insulin sensitivity. Although IRS proteins are not considered ‘druggable’ targets, several molecules that may directly or indirectly affect IRS function are plausible targets (discussed below).

PI3 kinase/Akt pathways PI3 kinase plays a pivotal role in the metabolic and mitogenic actions of insulin. PI3K consists of a catalytic subunit and a regulatory subunit. Three distinct genes encode the regulatory subunit: the p85α , p85β and p55γ genes. The p85α gene also generates two splicing variants, p50α and p55α .40 – 42 All forms of the structurally distinct regulatory subunits are capable of associating with the IRS proteins upon insulin stimulation.42 – 44 Activated PI3K specifically phosphorylates PI substrates to produce PI(3)P, PI(3,4)P2 and PI(3,4,5)P3. Acting as second messengers, these phospholipids recruit the PI3K-dependent serine/threonine kinases (PDK1) and Akt from the cytoplasm to the plasma membrane by binding to the ‘pleckstrin homology domain’ (PH domain) of kinases. Lipid binding and membrane translocation lead to conformational changes in Akt, which is subsequently phosphorylated on Thr 308 and Ser 473 by PDK1. Phosphorylation by PDK1 leads to full activation of Akt.45 – 47 Activated Akt phosphorylates and regulates the activity of many downstream proteins involved in multiple aspects of cellular physiology, including glucose transporter 4 (GLUT4) complex, protein kinase C (PKC) isoforms and GSK3, all of which are critical in insulin-mediated metabolic effects.46 – 49 Pharmacological inhibition of PI3K by wortmannin and LY294002 is associated with blockade of insulin-stimulated translocation of GLUT4 to cell surface and glucose uptake into cells.50 – 53 Overexpression of constitutively active forms of PI3K p110 catalytic subunit or Akt stimulates,49, 54, 55 whereas that of dominant-negative p85 regulatory subunit constructs blocks, insulin-mediated metabolic effects.11, 54, 56 – 58 Although controversy still surrounds the role of Akt in insulin-mediated GLUT4 translocation,59 recent reports show that Akt2 deficiency but not Akt1 deficiency in mice is associated with insulin resistance and diabetes, strongly supporting the notion that Akt is important in insulin action.60, 61 Surprisingly, recent studies suggest that down-regulation of PI3K regulatory subunit expression actually improves insulin sensitivity in mice.62 – 65 Given the

TARGETING THE INSULIN SIGNALLING PATHWAY

565

positive role of the regulatory subunit in PI3K activation and the essential role of PI3K in insulin action reported in earlier studies, it is perplexing that a reduction of regulatory subunit levels resulted in greater insulin sensitivity in a number of genetically engineered mouse lines. It is possible that the relative abundance of the regulatory and the catalytic subunits is important in determining net levels of PI3K activation. Consistent with this notion, excessive amounts of p85 protein, in comparison with p110 protein abundance, reportedly occurs in normal cells. Therefore, inhibition of this molecule might represent a novel therapeutic strategy for treating insulin resistance. However, several potential pitfalls for such an approach should be considered. If down-regulation of the regulatory subunit leads to constitutive activation of PI3K or Akt, one has to be concerned about tumourigenesis as PI3K is shared by a number of growth factor signal transduction pathways. Moreover, a more marked decrease in PI3K activity could lead to liver necrosis as occurs in combined regulatory subunit knockout mice.63 From a practical standpoint, PI3K regulatory subunits are not enzymes; thus their inhibition and down-regulation would require interruption of protein–protein interactions or approaches such as antisense oligonucleotides to inhibit protein expression. These approaches have limitations even when current state-of-the-art technologies are applied.

GLUT4 translocation Insulin promotes glucose uptake by muscle and adipose tissue via stimulation of glucose transporter (GLUT) 4 translocation from intracellular sites to the plasma membrane. Attenuated GLUT4 translocation and glucose uptake following insulin stimulation represents a prime defect in insulin-resistant states.66 Validation of the critical role of GLUT4 is derived from numerous studies that examined genetically engineered mice with partial or complete GLUT4 deficiency84, 85 and selective loss of muscle GLUT4 expression.67 As noted above, the PI3 kinase/Akt pathway has been demonstrated to be upstream of GLUT4 translocation. However, recent studies have shown that GLUT4 translocation is also downstream of a PI3-kinase-independent pathway.68 Insulin stimulates tyrosine phosphorylation of c-Cbl in the metabolically responsive cells. c-Cbl is recruited to complex with IRs via the adaptor protein CAP (c-Cbl-associated protein).69 Upon Cbl phosphorylation, the Cbl/CAP complex is translocated to the plasma membrane domain enriched in lipid rafts or caveolae. In the lipid rafts, CAP associates with caveolar protein flotillin and forms a complex with a number of proteins including TC10, CRKII and other accessory proteins involved in vesicular trafficking and membrane fusion.70 Expression of a dominant negative CAP mutant completely blocked insulin-stimulated glucose uptake and GLUT4 translocation. These data suggest that the PI3 kinase/Akt pathway and the CAP/Cbl complex represent two compartmentalized parallel pathways leading to GLUT4 translocation. In addition, one can now envisage new approaches by which selective augmentation of the CAP/Cbl pathway might enhance insulin

566

DRUG THERAPY FOR INSULIN RESISTANCE – A LOOK AT THE FUTURE

sensitivity. Taken together, current knowledge implies that alteration of GLUT4 expression and/or function could contribute to the development of insulin resistance and diabetes. Therefore, agents that stimulate or facilitate GLUT4 translocation may represent new therapeutic approaches for insulin resistance.

GSK3 Insulin action includes key regulatory effects to promote hepatic and muscle glycogen synthesis. A net increase in liver glycogen synthesis would be predicted to attenuate excessive hepatic glucose output in diabetic states. Glycogen synthase kinase 3 (GSK-3) is a cytoplasmic serine/threonine kinase that has key roles in insulin signal transduction and metabolic regulation.71 – 73 This enzyme also has a key role in Wnt signalling that is critical for determination of cell fates during embryonic development.71 In the insulin signalling pathway, GSK-3 is active in the absence of insulin; it phosphorylates (and thereby inhibits) glycogen synthase and several other substrates. Insulin binding to the IR activates a phosphorylation cascade, leading to inhibitory phosphorylation of GSK-3 by Akt. Thus, insulin activates glycogen synthase, in part, by promoting its dephosphorylation through the inhibition of GSK-3. Increased GSK-3 activity has been shown to occur in diabetic animals74 and human subjects.75 Lithium and other small molecule inhibitors of GSK-3 have been shown to promote net activity of glycogen synthase in cells. Importantly, these compounds have antidiabetic effects in animal models, suggesting that specific inhibitors of GSK-3 hold potential as novel therapeutics for diabetes.76 Specifically, a recent report using novel GSK-3 inhibitors demonstrated improved insulin-stimulated glucose metabolism via increasing liver glycogen synthesis in Zucker diabetic fatty (fa/fa) rats.77 Surprisingly, no significant increase in muscle glycogen synthesis was evident despite increased muscle glycogen synthase activity.77 Since GSK-3 is a central element in the Wnt-β-catenin pathway, inhibitors of GSK-3 could potentially cause tumourigenesis via this pathway. Indeed, lithium has been shown to inhibit GSK-3 and mimic Wnt signalling in intact cells.78 This presents a serious issue with implications regarding the approach of GSK-3 inhibition for chronic treatment. However, significant advancements in the field during the past 2 years have demonstrated that the insulin and Wnt signalling pathways differentially regulate GSK-3. The crystal structure of GSK-3β, together with biochemical studies, revealed how GSK3 selectively regulates different downstream targets according to which signalling pathway is activated.72, 73 Therefore, it is now theoretically possible to identify GSK-3 inhibitors that selectively block the activity of the enzyme towards glycogen synthase for the treatment of diabetes. Despite these developments, all currently described GSK-3 inhibitors that are ATP-site competitors are likely to have effects to augment both insulin and Wnt signalling pathways. Therefore, continued caution is advisable when considering such compounds.

TARGETING NEGATIVE MODULATORS OF INSULIN SIGNALLING

567

19.3 Targeting negative modulators of insulin signalling PTP1B Protein tyrosine phosphatases (PTPases) catalyse the dephosphorylation of IRs and IR substrates, leading to attenuation of insulin action. Vanadate inhibits PTPases and augments tyrosyl phosphorylation of a wide variety of cellular proteins, including the IR.79 Vanadate has been shown to have antidiabetic effects in animal models and in human diabetic subjects.80 – 82 A number of PTPases have been implicated as negative regulators of insulin signalling. Among them, the intracellular PTPase PTP1B has been shown to function as a key IR phosphatase. Mice lacking PTP1B have increased insulin sensitivity and improved glucose tolerance.83, 84 These mice also have increased energy expenditure and are resistant to the development of obesity. Interestingly, PTP1B has also been shown to negatively regulate leptin signalling.85, 86 These findings imply that specific inhibition of PTP1B represents a valid therapeutic target for treating both obesity and diabetes. Many potent small molecule inhibitors of PTP1B have now been reported.87 Some of the inhibitors have been shown to inhibit the catalytic activity of recombinant PTP1B in vitro, to promote insulin signalling in cultured cells and, most importantly, to have antidiabetic activity in animal models. Recent reports utilizing PTPB1B antisense oligonucleotides also strongly support the antidiabetic and anti-obesity benefits of inhibition of PTP1B. Thus, in multiple mouse models, PTP1B antisense oligonucleotides have been shown to halt the development of diabetes, to improve insulin sensitivity and provide glycaemic control and to reduce adiposity.88 – 90 There are several challenges in developing small molecule PTP1B inhibitors as insulin sensitizers. It has been difficult to obtain selective inhibitors for PTP1B versus related enzymes such as T-cell PTPase (TCPTP).91, 92 The finding that PTP1B inhibitors can be designed to bind simultaneously to both a catalytic site and a proximal non-catalytic site may increase potency and selectivity.93, 94 Given that the phosphate group of PTPase substrates has a negative charge, competitive inhibitors for PTP1B will likely be charged. This may strongly limit their cell permeability and in vivo efficacy. In this aspect, non-phosphorus-based phosphotyrosine surrogate-containing compounds have been evaluated and may prove useful. It should also be noted that the approach of PTP1B inhibition for diabetes or obesity remains to be validated in humans.

SHIP/PTEN As discussed above, PI3 kinase is a critical player in insulin signal transduction. The activity of this pathway is also determined by phosphatidylinositol-3phosphatases such as PTEN and the SH2-domain-containing inositol-5-phosphatase SHIP2. Overexpression of these lipid phosphatases leads to decreased levels of PI(3,4,5)P3 in the cell, which could dampen or terminate insulin signalling.

568

DRUG THERAPY FOR INSULIN RESISTANCE – A LOOK AT THE FUTURE

PTEN was identified and cloned as a tumour suppresser gene; it was found to be mutated in many animal and human cancers.95 The PTEN gene encodes a protein of 403 residues that shows homology to dual-specificity protein phosphatases. Importantly, it has been clearly demonstrated that PTEN negatively regulates insulin signalling. In cultured cells, overexpression of PTEN protein has been found to inhibit insulin-induced PI(3,4)P2 and PI(3,4,5)P3 production, Akt activation, GLUT4 translocation to the cell membrane and glucose uptake into cells.96, 97 Additionally, microinjection of an anti-PTEN antibody increases basal and insulin-stimulated GLUT4 translocation.96 In contrast to overexpression of wild type PTEN, overexpression of catalytically inactive PTEN mutant does not negatively affect insulin signalling,97 indicating that lipid phosphatase activity is required for the action of PTEN on insulin signallling. Finally, it was reported that treatment with an antisense oligonucleotide that specifically inhibits the expression of PTEN (80 per cent reduction in mRNA level in liver and adipose tissue) normalized plasma glucose in the db/db mice.98 Taken together, these studies indicate that PTEN plays a negative role in insulin signalling and its inhibition improves insulin sensitivity. SHIP2 is another negative regulator of insulin signalling. Overexpression of SHIP2 protein decreases insulin-dependent PI(3,4,5)P3 production as well as insulin-stimulated Akt activation, GSK3 inactivation and glycogen synthase activation.99 The inhibitory effects of SHIP2 on insulin signalling are lipid phosphatase activity dependent. The potential of SHIP2 as a target for diabetes treatment was implicated by a recent study demonstrating that genetic deletion of SHIP2 increases insulin sensitivity in vivo.100 SHIP2−/− newborn mice have severe hypoglycaemia and mortality that can be rescued by infusion of either glucose or an insulin-neutralizing antibody. Tissues of the newborn knockout mice also have decreased expression of gluconeogenesis genes. Most interestingly, SHIP2+/− mice have improved insulin sensitivity and glucose tolerance. SHIP2+/− mice also demonstrate increased translocation of GLUT4 and glycogen synthesis in skeletal muscles. These results suggest that inhibitors of SHIP2 may represent a novel class of therapeutics for the treatments of type 2 diabetes by improving insulin sensitivity. Importantly, excessive inhibition of both SHIP2 and PTEN can be deleterious. SHIP2−/− mice have severe hypoglycaemia and high mortality.100 Given that SHIP2+/− mice have improved insulin sensitivity, however, 50 per cent or less inhibition may be sufficient for improving insulin sensitivity. On the other hand, given that PTEN mutations and deficiency are associated with multiple types of tumour,101 PTEN-based therapy may pose greater risk, particularly in long term treatment. In this regard, it is important to note that, in contrast to PTEN deficiency, SHIP2 deficiency does not increase tumour susceptibility in mice.100 From a practical standpoint, no known selective, small molecule inhibitors for either SHIP2 or PTEN have been reported in the scientific or patent literature. Competitive inhibitors of these lipid phosphatases are likely to

TARGETING OBESITY AND INSULIN RESISTANCE

569

be highly charged due to the charged nature of their physiological substrates such as PI(3,4,5)P3. Such charged inhibitors will have limited in vivo efficacy due to low cell permeability.

19.4

Targeting obesity and insulin resistance

Obesity is the predominant cause of insulin resistance; systemic abnormalities of lipid and energy metabolism are now appreciated as links between increased adiposity and insulin resistance in muscle and liver. Via complex mechanisms,102, 103 PPARγ ligands enhance whole body insulin sensitivity by affecting lipid metabolism in specific ways. However, they do so at the expense of generally increased body adiposity. Apart from this approach (discussed elsewhere in this book), more recently described aspects of the pathogenesis of obesity-related insulin resistance and additional pathways that regulate lipids or energy metabolism are coming into focus as possible future opportunities for therapeutic intervention.

Targets in the obesity/insulin resistance axis Obesity and its associated insulin resistance and hyperlipidaemia are hallmarks of the metabolic syndrome104, 105 and are the major risk factors for type 2 diabetes mellitus.106, 107 Elevated circulating levels of free fatty acids (FFAs) derived from adipocytes have been demonstrated in numerous insulin resistance states and contribute to insulin resistance by inhibiting glucose uptake, glycogen synthesis and glycolysis, and by increasing hepatic glucose production.108 – 111 In the proximal insulin signalling pathway, elevated FFAs are associated with impaired IRS-1 phosphorylation and PI3-kinase activation following insulin stimulation.112 FFAs also stimulate expression of gluconeogenic enzymes, including glucose-6phosphatase.113 Peripheral insulin resistance has also been linked to intramyocellular triglyceride and long chain fatty-acyl-CoA accumulation.114 – 118 Selective depletion of intramyocellular lipids is accompanied by reversal of insulin resistance associated with morbid obesity.119 The link between tissue lipid levels and insulin resistance has been further substantiated in transgenic mice that selectively overexpress lipoprotein lipase in liver or muscle.120 In addition to tyrosine phosphorylation, the IR and IRS proteins undergo serine phosphorylation; this attenuates insulin signalling by inhibiting insulin-stimulated tyrosine phosphorylation and promoting association with other regulatory molecules.66 Elevation of lipid-derived metabolites (such as diacylglycerol) can lead to activation of a number of protein kinases, including protein kinase C isoforms, resulting in serine/threonine phosphorylation of IRs and IRS proteins.121 – 127 These serine phosphorylation events function as negative feedback loops for insulin signal transduction and provide a basis for cross-talk with other pathways that may mediate insulin resistance. Increased protein kinase C-θ(PKCθ) activity has been

570

DRUG THERAPY FOR INSULIN RESISTANCE – A LOOK AT THE FUTURE

shown to associate with fatty-acid-induced insulin resistance,66 suggesting inhibition of PKCθ may be a potential new drug target for improving insulin sensitivity. Recently, several additional serine/threonine kinases have been implicated in this process; these include the inhibitor of nuclear factor-κB (IκB) kinase (IKKβ) and Jun N-terminal kinase (JNK), which are described below.

IKKβ/JNK IKKβ, a serine/threonine kinase, is a component of the larger IKK signalsome and plays an important role in the IKKβ/IκB/NF–κB. pathway. The IKK signalsome regulates cellular responses to stimuli such as cytokines, viral infection and stresses. It was also reported that deficiency of IKKβ in mice resulted in immunodeficiency, suggesting that IKKβ is critical in mediating immune responses.128, 129 Salicylates including aspirin (acetylsalicylic acid) are anti-inflammatory drugs. Interestingly, high doses of aspirin have also been shown to lower blood glucose. Recent studies indicate that long term (3–4 week) salicylate treatment improved insulin sensitivity and glucose haemostasis in Zucker obese rats and ob/ob mice.130 Shorter term (19 h) salicylate treatments also prevented lipid-induced insulin resistance in animals.131 Moreover, treatment with high dose (approximately 7 g/day) of aspirin for two weeks also improved glucose metabolism in type 2 diabetic human subjects.132 Importantly, IKKβ inhibition has been implicated as the mechanism for these effects. Several lines of evidence suggest that salicylates act by inhibiting IKKβ. It was reported that aspirin selectively inhibits IKKβ in a competitive fashion in vitro.133 IKKβ heterogenous mice have improved insulin sensitivity and are resistant to lipid-induced insulin resistance.131 In addition, in the presence of the ob/ob genetic background, IKKβ heterozygosity improves insulin sensitivity.130 Moreover, fatspecific overexpression of an activated IKKβ mutant leads to insulin resistance in mice.134 Overexpression of dominant positive or dominant inhibitory IKKβ mutants via adenovirus also promotes or reverses insulin resistance in mice, respectively.135 Finally, long term treatment with parthenolide, another IKKβ inhibitor, was also found to improve insulin sensitivity in ob/ob mice.136 Taken together, these observations suggest that IKKβ deficiency and its inhibition by aspirin improve insulin sensitivity in vivo. There is also evidence suggesting that IKKβ may inhibit insulin signalling by facilitating serine phosphorylation of IR and IRS proteins and that salicylates block these effects of IKKβ.130, 137 Since IKKβ plays an important role in immune regulation and deletion of the IKKβ gene is associated with embryonic lethality in mice due to massive hepatocyte apoptosis,138, 139 it is possible that excessive IKKβ inhibition will result in hepatic toxicity and immunosuppression. IKKβ selective inhibitors have already been reported140 and testing of these agents will yield critical information relating to the net efficacy and tolerability of this approach, which may then be more seriously considered as a means of improving insulin sensitivity in humans.

TARGETING OBESITY AND INSULIN RESISTANCE

571

Recent studies also indicate that JNK has a central role in obesity and insulin resistance.141 JNK is a member of the mitogen-activated protein kinase (MAPK) family,142, 143 and is capable of binding to the NH2 -terminal activation domain of c-Jun and phosphorylating c-Jun on multiple serine residues. JNK is activated by treatment of cells with cytokines (e.g. TNF and IL-1) and by exposure of cells to many forms of environmental stress (e.g, bacterial endotoxin, osmotic shock, redox stress, hypoxia and UV radiation). Three isoforms of JNK (1, 2, and 3) have been cloned. Targeted deletion of each of the JNK isoforms separately or in combination have revealed important and differential roles in T-cell differentiation, neurotube morphogenesis, early brain development and excitotoxicityinduced apoptosis in the hippocampus.144 – 150 JNK activity is abnormally elevated in liver, adipose and muscle of ob/ob mice and in diet-induced obese mice.141 Furthermore, JNK1 knockout mice exhibited a phenotype of decreased adiposity, improved insulin sensitivity and enhanced IR signalling when challenged with high fat diet feeding and in the context of a genetic cross with ob/ob. These findings suggest that inhibition of JNK1 could serve as a novel target for treating obesity and/or insulin resistance. Selective JNK inhibitors have been reported and have demonstrated efficacy in animal models of inflammation and arthritis.151, 152 SP600125 has also been shown to block PMA- and TNF-α-induced IRS-1 serine 307 phosphorylation153, 154 in cells, suggesting a possibly link between JNK and IKKβ in the modulation of insulin sensitivity. The critical issue for a new therapeutic modality that relies on pan-JNK inhibition is the chronic tolerability of such agents given that JNK isoforms have apparently crucial physiologic roles as described above. Interestingly, amelioration of obesity-related insulin resistance involved only the JNK1 isoform, and not JNK2.141 Therefore, a JNK1-selective inhibitor may be preferred and sufficient for insulin-sensitizing efficacy.

Adipose-secreted proteins Adipose is now recognized as an active endocrine organ that secretes a variety of hormones with potential metabolic effects. Elevated TNF-α expression has been observed in adipose tissue derived from obese animal models and human subjects. TNF-α has also been implicated as a causative factor in the development of insulin resistance associated with obesity and diabetes.155 – 158 Treatment of cells with TNF-α impairs insulin signalling through IRS-1 serine phosphorylation159, 160 or through reduced expression of IRS-1 and GLUT4.161 TNF-α also suppresses adipocyte differentiation and expression of adipocyte-specific genes in vitro.162 Agonists of PPARγ such as TZDs (e.g. troglitazone, pioglitazone and rosiglitazone) promote adipocyte differentiation and improve insulin sensitivity in animal models of obesity and diabetes as well as in type 2 diabetic patients.163 TNF-α and PPARγ signalling pathways are mutually antagonistic and activation of PPARγ can attenuate the negative metabolic effects of TNF-α in cells and in vivo.164 – 166

572

DRUG THERAPY FOR INSULIN RESISTANCE – A LOOK AT THE FUTURE

These findings suggest that alternative approaches that can result in a net reduction of TNFα action, other than JNK or IKK inhibition–discussed above, might have utility as insulin sensitizing mechanisms. Leptin belongs to the cytokine family of hormones and is secreted by adipose tissue. Leptin exerts its effect by interacting with specific receptors in the central nervous system and periphery.105 Severe leptin deficiency or leptin signalling deficiency is associated with marked insulin resistance as manifested in db/db, ob/ob mice, Zucker fatty rats or animal models of genetic lipodystrophic diabetes.167 In addition to its effect on satiety and body weight, leptin may also modulate insulin action in liver and muscle.168 – 170 Leptin replacement in human subjects with lipodystrophy and leptin deficiency leads to improved glycaemia control and decreased lipid levels.171 Thus, attempts to enhance leptin secretion or action might produce insulin sensitization beyond a simple effect to reduce food intake. Acrp30 (adipocyte complement-related protein of 30 kDa, also known as adiponectin) is an additional serum protein secreted by adipocytes, which shares homology with complement protein C1q.172 The circulating level of Acrp30 is reduced in obesity and type 2 diabetes and is correlated with insulin resistance and hyperinsulinaemia.173, 174 PPARγ ligands increase expression and plasma concentrations of this protein.175, 176 Moreover, Acrp30 has also been shown to enhance hepatic insulin action,177 reverse insulin resistance associated with both lipoatrophy and obesity,178 and increase fatty acid oxidation in muscle and cause weight loss in mice.179 The role of Acrp30 in insulin sensitivity and energy homeostasis has been further validated in mouse models with targeted deletion of the Acrp30 gene.180 – 185 Obviously, recombinant forms of Acrp30 might be developed as new therapies. However, if a specific ‘druggable’ receptor for Acrp30 can be identified, it would represent a clearly compelling approach to potential new insulin-sensitizing small molecule drugs. Resistin is yet another adipocyte-secreted protein that potentially links obesity to type 2 diabetes. Initial studies reported that resistin levels are elevated in animal models of diabetes and obesity and that treatment with insulin-sensitizing agents (such as TZDs) results in reduction of circulating resistin levels,186, 187 although the role and regulation of resistin still remain controversial.188 Correlation of increased resistin expression with obesity and insulin resistance has been observed in some human subjects,189 but not others.190 – 192 Further studies will be required to elucidate the role of resistin in humans; if it is indeed an insulin resistance factor, new approaches designed to reduce its levels or actions (e.g. neutralizing antibodies or receptor antagonists) can be envisaged.

AMP kinase, lipid synthesis and oxidation Insulin is an anabolic hormone, and promotes lipid synthesis and suppresses lipid degradation. Recent studies indicate that the transcription factor, steroid

TARGETING OBESITY AND INSULIN RESISTANCE

573

regulatory element-binding protein (SREBP)-1c, is a major mediator of insulin action towards the expression of glucokinase and lipogenesis-related genes in the liver.193 – 195 Transgenic mice expressing SREBP-1c in adipose tissue exhibit a phenotype of abnormal adipose differentiation, marked insulin resistance and diabetes mellitus.196 Increased levels of SREBP-1c are also associated with hepatic steatosis in two mouse models of diabetes.197 In streptozotocin-induced diabetic rats, insulin stimulates lipid synthesis by selectively increasing hepatic SREBP-1c mRNA levels.198 Moreover, studies in lipodystrophic mice and obese ob/ob mice demonstrate that, while insulin resistance (e.g. deficient IRS-2 signalling) is evident in the liver, insulin’s effect to stimulate the SREBP-1c pathway is selectively enhanced in the same tissue, leading to a vicious cycle of abnormally high levels of glucose production and lipid synthesis.199 These concepts highlight the need to target therapies for ‘insulin resistance’ to those aspects of insulin action that will yield a net benefit in the context of diabetes or obesity (rather than attempting to promote all effects of insulin). In addition to promoting lipogenesis in the liver, insulin also stimulates lipid synthesis enzymes (fatty acid synthase, acetyl-CoA carboxylase) and inhibits lipolysis in adipose tissue. The anti-lipolytic effect of insulin is primarily mediated by inhibition of hormone-sensitive lipase through a mechanism that involves activation of a cAMP-specific phosphodiesterase.200 – 202 Direct, but not excessive, inhibition of lipogenic enzymes represents one possible way to treat abnormal lipogenesis and possibly enhance insulin sensitivity. Alternatively, and by analogy to mechanisms of PPARγ action, inhibition of lipolysis may afford some increase in insulin sensitivity by curtailing excessive release of FFAs from adipose tissue. AMP-activated protein kinase (AMPK) is activated in response to reduced cellular energy charge.203 It functions as a cellular energy sensor and a key regulator of carbohydrate and lipid metabolism via its multifaceted effects on fatty acid and cholesterol synthesis, hepatic glucose production and fatty acid oxidation. AMPK is a serine/threonine protein kinase; its heterotrimeric structures consists of one catalytic subunit (α) and two non-catalytic regulatory subunits (β and γ). Each of the subunits can be encoded by two or three different genes; thus, AMPK exists in over 12 forms with different compositions depending upon subunit isoform composition. Conditions that include stress or exercise result in AMPK activation in response to a reduced ratio of ATP:AMP. This occurs via allosteric activation by AMP and via activating phosphorylation of AMPK by an as-yet unidentified AMPK-kinase.203, 204 A key AMPK substrate is acetyl-CoA carboxylase (ACC) which is phosphorylated and inactivated. Since ACC is the key enzyme for the formation of malonyl CoA, a potent inhibitor of fatty acid oxidation and the first step in fatty acid synthesis,205 AMPK activation and the consequent ACC inhibition leads to reduced lipid synthesis and increased fat oxidation. Activation of AMPK also results in reduced expression of SREBP-1 and its downstream lipogenic genes.

574

DRUG THERAPY FOR INSULIN RESISTANCE – A LOOK AT THE FUTURE

Recent studies suggest that the metabolic effects of metformin, a widely prescribed antidiabetic agent, may be mediated, at least in part, via AMPK.206 Metformin activates AMPK in hepatocytes and in skeletal muscle; activation of AMPK by metformin coincides with an increase in insulin-stimulated glucose uptake. Furthermore, an AMPK inhibitor blocked metformin-mediated inhibition of glucose production by hepatocytes. Consistent with an important role of AMPK in mediating the metabolic effects of metformin, treatment with another AMPK activator, aminoimidazole-4-carboxamide riboside (AICAR), also favourably affects metabolic processes in multiple insulin-responsive tissues.207 – 212 Specifically, AICAR treatment increases fatty acid oxidization and ketogenesis, and decreases triglyceride and cholesterol synthesis and lipogenesis in liver. It also decreases lipolysis and lipogenesis in adipose tissues while increasing glucose uptake and utilization, and fatty acid oxidization, in skeletal muscle. AMPK has also been implicated in the action of leptin.170 The beneficial metabolic effects of AMPK activation by AICAR and the probable role of AMPK in metformin action naturally suggest that AMPK is an attractive target for the treatment of type 2 diabetes. One of the foreseeable advantages of targeting AMPK, given the pleiotropic effects of AMPK on glucose and lipid metabolism, is that such therapeutics may prove beneficial for treating multiple aspects of the metabolic syndrome. However, targeting AMPK may also have deleterious effects. Given that AMPK is a key energy sensor, one can speculate that chronic elevation of AMPK activity may result in global effects beyond improved metabolic control. This concern is highlighted by the recent discovery of AMPK mutations in association with congenital cardiac syndromes including familial ventricular pre-excitation and tachyarrhythmias (Wolff–Parkinson–White syndrome), and cardiac hypertrophy.213, 214 These mutants have been proposed as having constitutive AMPK activity.215 Based on the role of AMPK in glucose metabolism, it has been proposed that AMPK activation may induce cardiac glycogen accumulation due to increased glucose uptake and increased hexokinase activity.216 In this respect, it will be important to identify AMPK activators with tissue selectivity.

Concluding remarks Since the cloning of the IR gene in 1985, significant progress has been made in our understanding of insulin signal transduction pathways and their alterations in the development of insulin resistance. Much work is still needed to further unravel the detailed molecular mechanisms by which insulin regulates intricate cellular processes in a variety of tissues. These efforts may yield viable new drug targets, which could specifically modulate the insulin signalling pathway. Given the emerging recognition of a crucial role for adipose tissue and altered lipid metabolism in the pathogenesis of insulin resistance, it is anticipated that a wide array of new therapeutic approaches designed to target these pathways and

REFERENCES

575

to prevent or treat insulin resistance will be forthcoming. Such newer approaches include mechanisms of either augmenting (e.g. Acrp30-adiponectin) or inhibiting (e.g. TNF-α) the net effects of adipose-derived factors that have been implicated in the systemic control of insulin action. Alternatively, mechanisms that have the potential to directly attenuate tissue lipotoxicity (e.g. activation of AMPK) can now be regarded as possible therapeutic approaches to insulin sensitization. It is important to recognize that a primary goal of new therapeutic approaches to insulin resistance will be to selectively augment desirable metabolic effects of insulin, such as peripheral tissue glucose uptake, while avoiding an increase in undesirable effects of insulin, such as hepatic lipogenesis or mitogenic effects. An exciting aspect of insulin-sensitizing therapies, not discussed above, involves the prospect of enhancing insulin action within the hypothalamus. This represents a promising therapeutic approach to obesity (via increased satiety) and diabetes (via potential CNS-hepatic signals, which tend to reduce liver glucose output).217, 218

References 1. Taylor, S. I. (1999) Deconstructing type 2 diabetes. Cell 97, 9–12. 2. Saltiel, A. R. and Kahn, C. R. (2001) Insulin signalling and the regulation of glucose and lipid metabolism. Nature 414, 799–806. 3. Zimmet, P., Alberti, K. G. and Shaw, J. (2001) Global and societal implications of the diabetes epidemic. Nature 414, 782–787. 4. Goldfine, I. D. (1987) The insulin receptor: molecular biology and transmembrane signaling. Endocr Rev 8, 235–255. 5. White, M. F. and Kahn, C. R. (1994) The insulin signaling system. J Biol Chem 269, 1–4. 6. Kasuga, M., Karlsson, F. A. and Kahn, C. R. (1982) Insulin stimulates the phosphorylation of the 95,000-dalton subunit of its own receptor. Science 215, 185–187. 7. Rosen, O. M., Herrera, R., Olowe, Y., Petruzzelli, M. and Cobb, M. H. (1983) Phosphorylation activates the insulin receptor tyrosine protein kinase. Proc Natl Acad Sci USA 80, 3237–3240. 8. Yu, K. T. and Czech, M. P. (1984) Tyrosine phosphorylation of the insulin receptor beta subunit activates the receptor-associated tyrosine kinase activity. J Biol Chem 259, 5277–5286. 9. Ellis, L., Morgan, D. O., Clauser, E., Roth, R. A. and Rutter, W. J. (1987) A membraneanchored cytoplasmic domain of the human insulin receptor mediates a constitutively elevated insulin-independent uptake of 2-deoxyglucose. Mol Endocrinol 1, 15–24. 10. White, M. F. and Yenush, L. (1998) The IRS-signaling system: a network of docking proteins that mediate insulin and cytokine action. Curr Top Microbiol Immunol 228, 179–208. 11. Kohn, A. D., Summers, S. A., Birnbaum, M. J. and Roth, R. A. (1996) Expression of a constitutively active Akt Ser/Thr kinase in 3T3-L1 adipocytes stimulates glucose uptake and glucose transporter 4 translocation. J Biol Chem 271, 31 372–31 378. 12. Alessi, D. R. and Cohen, P. (1998) Mechanism of activation and function of protein kinase B. Curr Opin Genet Dev 8, 55–62. 13. Accili, D. et al. (1996) Early neonatal death in mice homozygous for a null allele of the insulin receptor gene. Nat Genet 12, 106–109.

576

DRUG THERAPY FOR INSULIN RESISTANCE – A LOOK AT THE FUTURE

14. Joshi, R. L. et al. (1996) Targeted disruption of the insulin receptor gene in the mouse results in neonatal lethality. EMBO J 15, 1542–1547. 15. Accili, D., Nakae, J., Kim, J. J., Park, B. C. and Rother, K. I. (1999) Targeted gene mutations define the roles of insulin and IGF-I receptors in mouse embryonic development. J Pediatr Endocrinol Metab 12, 475–485. 16. Taylor, S. I. (1992) Lilly lecture: molecular mechanisms of insulin resistance, lessons from patients with mutations in the insulin-receptor gene. Diabetes 41, 1473–1490. 17. Olefsky, J. M. (1976) Decreased insulin binding to adipocytes and circulating monocytes from obese subjects. J Clin Invest 57, 1165–1172. 18. Caro, J. F. et al. (1986) Studies on the mechanism of insulin resistance in the liver from humans with noninsulin-dependent diabetes. J Clin Invest 78, 249–258. 19. Caro, J. F. et al. (1987) Insulin receptor kinase in human skeletal muscle from obese subjects with and without non-insulin dependent diabetes. J Clin Invest 79, 1330–1337. 20. Goodyear, L. J. et al. (1995) Insulin receptor autophosphorylation, insulin receptor substrate-1 phosphorylation, and phosphatidylinositol 3-kinase activity are decreased in intact skeletal muscle strips from obese subjects. J Clin Invest 95, 2195–2204. 21. Kerouz, N. J., Horsch, D., Pons, S. and Kahn, C. R. (1997) Differential regulation of insulin receptor substrates-1 and -2 (IRS-1 and IRS-2) and phosphatidylinositol 3-kinase isoforms in liver and muscle of the obese diabetic (ob/ob) mouse. J Clin Invest 100, 3164–3172. 22. Krook, A., Roth, R. A., Jiang, X. J., Zierath, J. R. and Wallberg-Henriksson, H. (1998) Insulin-stimulated Akt kinase activity is reduced in skeletal muscle from NIDDM subjects. Diabetes 47, 1281–1286. 23. Kopelman, P. G. (2000) Obesity as a medical problem. Nature 404, 635–643. 24. Luo, R. Z., Beniac, D. R., Fernandes, A., Yip, C. C. and Ottensmeyer, F. P. (1999) Quaternary structure of the insulin–insulin receptor complex. Science 285, 1077–1080. 25. Hubbard, S. R. (1997) Crystal structure of the activated insulin receptor tyrosine kinase in complex with peptide substrate and ATP analog. EMBO J 16, 5572–5581. 26. Hubbard, S. R., Wei, L., Ellis, L. and Hendrickson, W. A. (1994) Crystal structure of the tyrosine kinase domain of the human insulin receptor. Nature 372, 746–754. 27. Adams, T. E., Epa, V. C., Garrett, T. P. and Ward, C. W. (2000) Structure and function of the type 1 insulin-like growth factor receptor. Cell Mol Life Sci 57, 1050–1093. 28. Nakae, J., Kido, Y. and Accili, D. (2001) Distinct and overlapping functions of insulin and IGF-I receptors. Endocr Rev 22, 818–835. 29. Siddle, K., Soos, M. A., Field, C. E. and Nave, B. T. (1994) Hybrid and atypical insulin/insulin-like growth factor I receptors. Horm Res 41 (Suppl. 2), 56–64; discussion 65. 30. Pessin, J. E. (1993) Molecular properties of insulin/IGF-1 hybrid receptors. 4th International Symposium on Insulin, IGFs and their Receptors. Adv Exp Med Biol 343, 133–144. 31. Shier, P. and Watt, V. M. (1989) Primary structure of a putative receptor for a ligand of the insulin family. J Biol Chem 264, 14 605–14 608. 32. Zhang, B. et al. (1999) Discovery of a small molecule insulin mimetic with antidiabetic activity in mice [see comments]. Science 284, 974–977. 33. Qureshi, S. A. et al. (2000) Activation of insulin signal transduction pathway and anti-diabetic activity of small molecule insulin receptor activators. J Biol Chem 275, 36 590–36 595. 34. Manchem, V. P. et al. (2001) A novel small molecule that directly sensitizes the insulin receptor in vitro and in vivo. Diabetes 50, 824–830. 35. Li, M. et al. (2001) Small molecule insulin receptor activators potentiate insulin action in insulin-resistant cells. Diabetes 50, 2323–2328.

REFERENCES

577

36. Tamemoto, H. et al. (1994) Insulin resistance and growth retardation in mice lacking insulin receptor substrate-1. Nature 372, 182–186. 37. Araki, E. et al. (1994) Alternative pathway of insulin signalling in mice with targeted disruption of the IRS-1 gene. Nature 372, 186–190. 38. Tamemoto, H. et al. (1997) Insulin resistance syndrome in mice deficient in insulin receptor substrate-1. Ann NY Acad Sci 827, 85–93. 39. Kido, Y. et al. (2000) Tissue-specific insulin resistance in mice with mutations in the insulin receptor, IRS-1, and IRS-2. J Clin Invest 105, 199–205. 40. Inukai, K. et al. (1996) A novel 55-kDa regulatory subunit for phosphatidylinositol 3kinase structurally similar to p55PIK Is generated by alternative splicing of the p85alpha gene. J Biol Chem 271, 5317–5320. 41. Fruman, D. A., Cantley, L. C. and Carpenter, C. L. (1996) Structural organization and alternative splicing of the murine phosphoinositide 3-kinase p85 alpha gene. Genomics 37, 113–121. 42. Inukai, K. et al. (1997) p85alpha gene generates three isoforms of regulatory subunit for phosphatidylinositol 3-kinase (PI 3-kinase), p50alpha, p55alpha, and p85alpha, with different PI 3-kinase activity elevating responses to insulin. J Biol Chem 272, 7873–7882. 43. Baltensperger, K., Kozma, L. M., Jaspers, S. R. and Czech, M. P. (1994) Regulation by insulin of phosphatidylinositol 3
-kinase bound to alpha- and beta-isoforms of p85 regulatory subunit. J Biol Chem 269, 28 937–28 946. 44. Pons, S. et al. (1995) The structure and function of p55PIK reveal a new regulatory subunit for phosphatidylinositol 3-kinase. Mol Cell Biol 15, 4453–4465. 45. Avruch, J. (1998) Insulin signal transduction through protein kinase cascades. Mol Cell Biochem 182, 31–48. 46. Czech, M. P. and Corvera, S. (1999) Signaling mechanisms that regulate glucose transport. J Biol Chem 274, 1865–1868. 47. Farese, R. V. (2001) Insulin-sensitive phospholipid signaling systems and glucose transport. Update II. Exp Biol Med (Maywood) 226, 283–295. 48. Shepherd, P. R., Withers, D. J. and Siddle, K. (1998) Phosphoinositide 3-kinase: the key switch mechanism in insulin signalling. Biochem J 333, 471–490. 49. Ueki, K. et al. (1998) Potential role of protein kinase B in insulin-induced glucose transport, glycogen synthesis, and protein synthesis. J Biol Chem 273, 5315–5322. 50. Okada, T., Sakuma, L., Fukui, Y., Hazeki, O. and Ui, M. (1994) Blockage of chemotactic peptide-induced stimulation of neutrophils by wortmannin as a result of selective inhibition of phosphatidylinositol 3-kinase. J Biol Chem 269, 3563–3567. 51. Clarke, J. F., Young, P. W., Yonezawa, K., Kasuga, M. and Holman, G. D. (1994) Inhibition of the translocation of GLUT1 and GLUT4 in 3T3-L1 cells by the phosphatidylinositol 3-kinase inhibitor, wortmannin. Biochem J 300, 631–635. 52. Kanai, F. et al. (1993) Insulin-stimulated GLUT4 translocation is relevant to the phosphorylation of IRS-1 and the activity of PI3-kinase. Biochem Biophys Res Commun 195, 762–768. 53. Cheatham, B. et al. (1994) Phosphatidylinositol 3-kinase activation is required for insulin stimulation of pp70 S6 kinase, DNA synthesis, and glucose transporter translocation. Mol Cell Biol 14, 4902–4911. 54. Katagiri, H. et al. (1996) Overexpression of catalytic subunit p110alpha of phosphatidylinositol 3-kinase increases glucose transport activity with translocation of glucose transporters in 3T3-L1 adipocytes. J Biol Chem 271, 16 987–16 990. 55. Martin, S. S. et al. (1996) Activated phosphatidylinositol 3-kinase is sufficient to mediate actin rearrangement and GLUT4 translocation in 3T3-L1 adipocytes. J Biol Chem 271, 17 605–17 608.

578

DRUG THERAPY FOR INSULIN RESISTANCE – A LOOK AT THE FUTURE

56. Calera, M. R. et al. (1998) Insulin increases the association of Akt-2 with Glut4containing vesicles. J Biol Chem 273, 7201–7204. 57. Sakaue, H. et al. (1997) Phosphoinositide 3-kinase is required for insulin-induced but not for growth hormone- or hyperosmolarity-induced glucose uptake in 3T3-L1 adipocytes. Mol Endocrinol 11, 1552–1562. 58. Sharma, P. M. et al. (1998) Inhibition of phosphatidylinositol 3-kinase activity by adenovirus-mediated gene transfer and its effect on insulin action. J Biol Chem 273, 18 528–18 537. 59. Hajduch, E., Litherland, G. J. and Hundal, H. S. (2001) Protein kinase B (PKB/Akt)–a key regulator of glucose transport? FEBS Lett 492, 199–203. 60. Cho, H. et al. (2001) Insulin resistance and a diabetes mellitus-like syndrome in mice lacking the protein kinase Akt2 (PKB beta). Science 292, 1728–1731. 61. Cho, H., Thorvaldsen, J. L., Chu, Q., Feng, F. and Birnbaum, M. J. (2001) Akt1/pkbalpha is required for normal growth but dispensable for maintenance of glucose homeostasis in mice. J Biol Chem 276, 38 349–38 352. 62. Terauchi, Y. et al. (1999) Increased insulin sensitivity and hypoglycaemia in mice lacking the p85 alpha subunit of phosphoinositide 3-kinase. Nat Genet 21, 230–235. 63. Fruman, D. A. et al. (2000) Hypoglycaemia, liver necrosis and perinatal death in mice lacking all isoforms of phosphoinositide 3-kinase p85 alpha. Nat Genet 26, 379–382. 64. Ueki, K. et al. (2002) Molecular balance between the regulatory and catalytic subunits of phosphoinositide 3-kinase regulates cell signaling and survival. Mol Cell Biol 22, 965–977. 65. Mauvais-Jarvis, F. et al. (2002) Reduced expression of the murine p85alpha subunit of phosphoinositide 3- kinase improves insulin signaling and ameliorates diabetes. J Clin Invest 109, 141–149. 66. Shulman, G. I. (2000) Cellular mechanisms of insulin resistance. J Clin Invest 106, 171–176. 67. Zisman, A. et al. (2000) Targeted disruption of the glucose transporter 4 selectively in muscle causes insulin resistance and glucose intolerance. Nat Med 6, 924–928. 68. Baumann, C. A. et al. (2000) CAP defines a second signalling pathway required for insulin-stimulated glucose transport. Nature 407, 202–207. 69. Ribon, V., Printen, J. A., Hoffman, N. G., Kay, B. K. and Saltiel, A. R. (1998) A novel, multifuntional c-Cbl binding protein in insulin receptor signaling in 3T3-L1 adipocytes. Mol Cell Biol 18, 872–879. 70. Chiang, S. H. et al. (2001) Insulin-stimulated GLUT4 translocation requires the CAPdependent activation of TC10. Nature 410, 944–948. 71. Harwood, A. J. (2001) Regulation of GSK-3: a cellular multiprocessor. Cell 105, 821–824. 72. Dajani, R. et al. (2001) Crystal structure of glycogen synthase kinase 3 beta: structural basis for phosphate-primed substrate specificity and autoinhibition. Cell 105, 721–732. 73. Frame, S., Cohen, P. and Biondi, R. M. (2001) A common phosphate binding site explains the unique substrate specificity of GSK3 and its inactivation by phosphorylation. Mol Cell 7, 1321–1327. 74. Eldar-Finkelman, H., Schreyer, S. A., Shinohara, M. M., LeBoeuf, R. C. and Krebs, E. G. (2001) Increased glycogen synthase kinase-3 activity in diabetes- and obesityprone C57BL/6J mice. Diabetes 48, 1662–1666. 75. Nikoulina, S. E. et al. (2000) Potential role of glycogen synthase kinase-3 in skeletal muscle insulin resistance of type 2 diabetes. Diabetes 49, 263–271. 76. Ryves, W. J. and Harwood, A. J. (2001) Lithium inhibits glycogen synthase kinase-3 by competition for magnesium. Biochem Biophys Res Commun 280, 720–725.

REFERENCES

579

77. Cline, G. W. et al. (2002) Effects of a novel glycogen synthase kinase-3 inhibitor on insulin-stimulated glucose metabolism in Zucker diabetic fatty (fa/fa) rats. Diabetes 51, 2903–2910. 78. Stambolic, V., Ruel, L. and Woodgett, J. R. (1996) Lithium inhibits glycogen synthase kinase-3 activity and mimics wingless signalling in intact cells. Curr Biol 6, 1664– 1668. 79. Huyer, G. et al. (1997) Mechanism of inhibition of protein–tyrosine phosphatases by vanadate and pervanadate. J Biol Chem 272, 843–851. 80. Goldfine, A. B., Simonson, D. C., Folli, F., Patti, M. E. and Kahn, C. R. (1995) In vivo and in vitro studies of vanadate in human and rodent diabetes mellitus. Mol Cell Biochem 153, 217–231. 81. Boden, G., Chen, X., Ruiz, J., van Rossum, G. D. and Turco, S. (1996) Effects of vanadyl sulfate on carbohydrate and lipid metabolism in patients with non-insulindependent diabetes mellitus. Metabolism 45, 1130–1135. 82. Halberstam, M., Cohen, N., Shlimovich, P., Rossetti, L. and Shamoon, H. (1996) Oral vanadyl sulfate improves insulin sensitivity in NIDDM but not in obese nondiabetic subjects. Diabetes 45, 659–666. 83. Elchebly, M. et al. (1999) Increased insulin sensitivity and obesity resistance in mice lacking the protein tyrosine phosphatase-1B gene [see comments]. Science 283, 1544–1548. 84. Klaman, L. D. et al. (2000) Increased energy expenditure, decreased adiposity, and tissue-specific insulin sensitivity in protein-tyrosine phosphatase 1B-deficient mice. Mol Cell Biol 20, 5479–5489. 85. Zabolotny, J. M. et al. (2002) PTP1B regulates leptin signal transduction in vivo. Dev Cell 2, 489–495. 86. Kaszubska, W. et al. (2002) Protein tyrosine phosphatase 1B negatively regulates leptin signaling in a hypothalamic cell line. Mol Cell Endocrinol 195, 109–118. 87. Zhang, Z. Y. (2002) Protein tyrosine phosphatases: structure and function, substrate specificity, and inhibitor development. Annu Rev Pharmacol Toxicol 42, 209–234. 88. Johnson, T. O., Ermolieff, J. and Jirousek, M. R. (2002) Protein tyrosine phosphatase 1B inhibitors for diabetes. Nat Rev Drug Discov 1, 696–709. 89. Zinker, B. A. et al. (2002) PTP1B antisense oligonucleotide lowers PTP1B protein, normalizes blood glucose, and improves insulin sensitivity in diabetic mice. Proc Natl Acad Sci USA 99, 11 357–11 362. 90. Rondinone, C. M. et al. (2002) Protein tyrosine phosphatase 1B reduction regulates adiposity and expression of genes involved in lipogenesis. Diabetes 51, 2405–2411. 91. Shen, K. et al. (2001) Acquisition of a specific and potent PTP1B inhibitor from a novel combinatorial library and screening procedure. J Biol Chem 276, 47 311–47 319. 92. Asante-Appiah, E. et al. (2001) The YRD motif is a major determinant of substrate and inhibitor specificity in T-cell protein–tyrosine phosphatase. J Biol Chem 276, 26 036–26 043. 93. Puius, Y. A. et al. (1997) Identification of a second aryl phosphate-binding site in protein- tyrosine phosphatase 1B: a paradigm for inhibitor design. Proc Natl Acad Sci USA 94, 13 420–13 425. 94. Asante-Appiah, E. et al. (2002) The structure of PTP-1B in complex with a peptide inhibitor reveals an alternative binding mode for bisphosphonates. Biochemistry 41, 9043–9051. 95. Ali, I. U., Schriml, L. M. and Dean, M. (1999) Mutational spectra of PTEN/MMAC1 gene: a tumor suppressor with lipid phosphatase activity. J Natl Cancer Inst 91, 1922–1932.

580

DRUG THERAPY FOR INSULIN RESISTANCE – A LOOK AT THE FUTURE

96. Nakashima, N., Sharma, P. M., Imamura, T., Bookstein, R. and Olefsky, J. M. (2000) The tumor suppressor PTEN negatively regulates insulin signaling in 3T3-L1 adipocytes. J Biol Chem 275, 12 889–12 895. 97. Ono, H. et al. (2001) Regulation of phosphoinositide metabolism, Akt phosphorylation, and glucose transport by PTEN (phosphatase and tensin homolog deleted on chromosome 10) in 3T3-L1 adipocytes. Mol Endocrinol 15, 1411–1422. 98. McKay, R. A. et al. (2000) Specific inhibition of PTEN expression with an antisense oligonucleotide normalizes plasma glucose in db/db mice. Diabetes 49, A51. 99. Blero, D. et al. (2001) The SH2 domain containing inositol 5-phosphatase SHIP2 controls phosphatidylinositol 3,4,5-trisphosphate levels in CHO-IR cells stimulated by insulin. Biochem Biophys Res Commun 282, 839–843. 100. Clement, S. et al. (2001) The lipid phosphatase SHIP2 controls insulin sensitivity. Nature 409, 92–97. 101. Maehama, T., Taylor, G. S. and Dixon, J. E. (2001) PTEN and myotubularin: novel phosphoinositide phosphatases. Annu Rev Biochem 70, 247–279. 102. Berger, J. and Moller, D. E. (2002) The mechanisms of action of PPARs. Annu Rev Med 53, 409–435. 103. Olefsky, J. M. and Saltiel, A. R. (2000) PPAR gamma and the treatment of insulin resistance. Trends Endocrinol Metab 11, 362–368. 104. Kahn, B. B. and Flier, J. S. (2000) Obesity and insulin resistance. J Clin Invest 106, 473–481. 105. Spiegelman, B. M. and Flier, J. S. (2001) Obesity and the regulation of energy balance. Cell 104, 531–543. 106. Reaven, G. M. (1993) Role of insulin resistance in the pathophysiology of non-insulin dependent diabetes mellitus. Diabetes Metab Rev 9 (Suppl. 1), 5S–12S. 107. Zimmet, P., Alberti, K. G. and Shaw, J. (2001) Global and societal implications of the diabetes epidemic. Nature 414, 782–787. 108. Reaven, G. M., Hollenbeck, C., Jeng, C. Y., Wu, M. S. and Chen, Y. D. (1988) Measurement of plasma glucose, free fatty acid, lactate, and insulin for 24 h in patients with NIDDM. Diabetes 37, 1020–1024. 109. McGarry, J. D. (1992) What if Minkowski had been ageusic? An alternative angle on diabetes. Science 258, 766–770. 110. Boden, G., Chen, X., Ruiz, J., White, J. V. and Rossetti, L. (1994) Mechanisms of fatty acid-induced inhibition of glucose uptake. J Clin Invest 93, 2438–2446. 111. Bergman, R. N. and Ader, M. (2000) Free fatty acids and pathogenesis of type 2 diabetes mellitus. Trends Endocrinol Metab 11, 351–356. 112. Dresner, A. et al. (1999) Effects of free fatty acids on glucose transport and IRS-1associated phosphatidylinositol 3-kinase activity. J Clin Invest 103, 253–259. 113. Massillon, D., Barzilai, N., Hawkins, M., Prus-Wertheimer, D. and Rossetti, L. (1997) Induction of hepatic glucose-6-phosphatase gene expression by lipid infusion. Diabetes 46, 153–157. 114. Krssak, M. et al. (1999) Intramyocellular lipid concentrations are correlated with insulin sensitivity in humans: a 1H NMR spectroscopy study. Diabetologia 42, 113–116. 115. Perseghin, G. et al. (1999) Intramyocellular triglyceride content is a determinant of in vivo insulin resistance in humans: a 1H-13C nuclear magnetic resonance spectroscopy assessment in offspring of type 2 diabetic parents. Diabetes 48, 1600–1606. 116. Jacob, S. et al. (1999) Association of increased intramyocellular lipid content with insulin resistance in lean nondiabetic offspring of type 2 diabetic subjects. Diabetes 48, 1113–1119. 117. Ruderman, N. B., Saha, A. K., Vavvas, D. and Witters, L. A. (1999) Malonyl-CoA, fuel sensing, and insulin resistance. Am J Physiol 276, E1–E18.

REFERENCES

581

118. Virkamaki, A. et al. (2001) Intramyocellular lipid is associated with resistance to in vivo insulin actions on glucose uptake, antilipolysis, and early insulin signaling pathways in human skeletal muscle. Diabetes 50, 2337–2343. 119. Greco, A. V. et al. (2002) Insulin resistance in morbid obesity: reversal with intramyocellular fat depletion. Diabetes 51, 144–151. 120. Kim, J. K. et al. (2001) Tissue-specific overexpression of lipoprotein lipase causes tissue-specific insulin resistance. Proc Natl Acad Sci USA 98, 7522–7527. 121. De Fea, K. and Roth, R. A. (1997) Modulation of insulin receptor substrate-1 tyrosine phosphorylation and function by mitogen-activated protein kinase. J Biol Chem 272, 31 400–31 406. 122. De Fea, K. and Roth, R. A. (1997) Protein kinase C modulation of insulin receptor substrate-1 tyrosine phosphorylation requires serine 612. Biochemistry 36, 12 939–12 947. 123. Delahaye, L., Mothe-Satney, I., Myers, M. G., White, M. F. and Van Obberghen, E. (1998) Interaction of insulin receptor substrate-1 (IRS-1) with phosphatidylinositol 3-kinase: effect of substitution of serine for alanine in potential IRS-1 serine phosphorylation sites. Endocrinology 139, 4911–4919. 124. Qiao, L. Y., Goldberg, J. L., Russell, J. C. and Sun, X. J. (1999) Identification of enhanced serine kinase activity in insulin resistance. J Biol Chem 274, 10 625–10 632. 125. Aguirre, V. et al. (2001) Phosphorylation of SER307 in IRS-1 blocks interactions with the insulin receptor and inhibits insulin action. J Biol Chem 17, 17. 126. Ravichandran, L. V., Esposito, D. L., Chen, J. and Quon, M. J. (2001) Protein kinase C-zeta phosphorylates insulin receptor substrate-1 and impairs its ability to activate phosphatidylinositol 3-kinase in response to insulin. J Biol Chem 276, 3543–3549. 127. Rui, L. et al. (2001) Insulin/IGF-1 and TNF-alpha stimulate phosphorylation of IRS-1 at inhibitory Ser307 via distinct pathways. J Clin Invest 107, 181–189. 128. Karin, M. and Ben-Neriah, Y. (2000) Phosphorylation meets ubiquitination: the control of NF-κB activity. Annu Rev Immunol 18, 621–663. 129. Karin, M. and Delhase, M. (2000) The I kappa B kinase (IKK) and NF-kappa B: key elements of proinflammatory signalling. Semin Immunol 12, 85–98. 130. Yuan, M. et al. (2001) Reversal of obesity- and diet-induced insulin resistance with salicylates or targeted disruption of Ikkbeta. Science 293, 1673–1677. 131. Kim, J. K. et al. (2001) Prevention of fat-induced insulin resistance by salicylate. J Clin Invest 108, 437–446. 132. Hundal, R. S. et al. (2002) Mechanism by which high-dose aspirin improves glucose metabolism in type 2 diabetes. J Clin Invest 109, 1321–1326. 133. Yin, M. J., Yamamoto, Y. and Gaynor, R. B. (1998) The anti-inflammatory agents aspirin and salicylate inhibit the activity of I(kappa)B kinase-beta. Nature 396, 77–80. 134. Cai, D., Frantz D, I. M., Yuan, M., Lee, J. and Shoelson, S. E. (2002) Fat-specific expression of activated IKKβ causes insulin resistance in mice. Diabetes 51, A56. 135. Yuan, M., Melendez P, H. L., Lee, J. and Shoelson, S. E. (2002) Adenovirus-mediated expression of activated IKKβ or inhibitory IκB causes insulin resistance or reverses it, respectively, in mice. Diabetes 51, A145. 136. Yuan, M., Iwamoto M, M. P., Lee, J. and Shoelson, S. E. (2002) Selective inhibition of IKK improves insulin sensitity in mice. Diabetes 51, A358. 137. Gao, Z. et al. (2002) Serine phosphorylation of insulin receptor substrate 1 by inhibitor kappa B kinase complex. J Biol Chem 277, 48 115–48 121. 138. Li, Z. W. et al. (1999) The IKKbeta subunit of IkappaB kinase (IKK) is essential for nuclear factor kappaB activation and prevention of apoptosis. J Exp Med 189, 1839–1845.

582

DRUG THERAPY FOR INSULIN RESISTANCE – A LOOK AT THE FUTURE

139. Li, Q., Van Antwerp, D., Mercurio, F., Lee, K. F. and Verma, I. M. (1999) Severe liver degeneration in mice lacking the IkappaB kinase 2 gene. Science 284, 321–325. 140. O’Neil, L. (2001) Inhibiting NF-κB. Trends Immunol 22, 478. 141. Hirosumi, J. et al. (2002) A central role for JNK in obesity and insulin resistance. Nature 420, 333–336. 142. Weston, C. R. and Davis, R. J. (2002) The JNK signal transduction pathway. Curr Opin Genet Dev 12, 14–21. 143. Davis, R. J. (2000) Signal transduction by the JNK group of MAP kinases. Cell 103, 239–252. 144. Kuan, C. Y. et al. (1999) The Jnk1 and Jnk2 protein kinases are required for regional specific apoptosis during early brain development. Neuron 22, 667–676. 145. Yang, D. D. et al. (1997) Absence of excitotoxicity-induced apoptosis in the hippocampus of mice lacking the Jnk3 gene. Nature 389, 865–870. 146. Yang, D. et al. (1997) Targeted disruption of the MKK4 gene causes embryonic death, inhibition of c-Jun NH2-terminal kinase activation, and defects in AP-1 transcriptional activity. Proc Natl Acad Sci USA 94, 3004–3009. 147. Yang, D. D. et al. (1998) Differentiation of CD4+ T cells to Th1 cells requires MAP kinase JNK2. Immunity 9, 575–585. 148. Sabapathy, K. et al. (2001) c-Jun NH2-terminal kinase (JNK)1 and JNK2 have similar and stage-dependent roles in regulating T cell apoptosis and proliferation. J Exp Med 193, 317–328. 149. Sabapathy, K. et al. (1999) Defective neural tube morphogenesis and altered apoptosis in the absence of both JNK1 and JNK2. Mech Dev 89, 115–124. 150. Sabapathy, K. et al. (1999) JNK2 is required for efficient T-cell activation and apoptosis but not for normal lymphocyte development. Curr Biol 9, 116–125. 151. Bennett, B. L. et al. (2001) SP600125, an anthrapyrazolone inhibitor of Jun N-terminal kinase. Proc Natl Acad Sci USA 98, 13 681–13 686. 152. Han, Z. et al. (2001) c-Jun N-terminal kinase is required for metalloproteinase expression and joint destruction in inflammatory arthritis. J Clin Invest 108, 73–81. 153. Aguirre, V. et al. (2002) Phosphorylation of Ser307 in insulin receptor substrate-1 blocks interactions with the insulin receptor and inhibits insulin action. J Biol Chem 277, 1531–1537. 154. Jiang, G., Dallas-Yang, Q., Liu, F., Moller, D. E. and Zhang, B. B. (2002) Salicylic acid reverses PMA and TNF alpha-induced IRS1 serine 307 phosphorylation and insulin resistance in HEK 293 cells. J Biol Chem 29, 29. 155. Hotamisligil, G. S., Shargill, N. S. and Spiegelman, B. M. (1993) Adipose tissue expression of tumor necrosis factor alpha: direct role in obesity-linked insulin resistance. Science 259, 87–90. 156. Hotamisligil, G. S., Arner, P., Caro, J. F., Atkinson, R. L. and Spiegelman, B. M. (1995) Increased adipose tissue expression of tumor necrosis factor-α in human obesity and insulin resistance. J Clin Invest 95, 2409–2415. 157. Kern, P. A. et al. (1995) The expression of tumor necrosis factor in human adipose tissue. Regulation by obesity, weight loss, and relationship to lipoprotein lipase. J Clin Invest 95, 2111–2119. 158. Saghizadeh, M., Ong, J. M., Garvey, W. T., Henry, R. R. and Kern, P. A. (1996) The expression of TNF alpha by human muscle. Relationship to insulin resistance. J Clin Invest 97, 1111–1116. 159. Hotamisligil, G. S. et al. (1996) IRS-1-mediated inhibition of insulin receptor tyrosine kinase activity in TNF-α- and obesity-induced insulin resistance. Science 271, 665–668.

REFERENCES

583

160. Feinstein, R., Kanety, H., Papa, M. Z., Lunenfeld, B. and Karasik, A. (1993) Tumor necrosis factor-α suppresses insulin-induced tyrosine phosphorylation of insulin receptor and its substrates. J Biol Chem 268, 26 055–26 058. 161. Stephens, J. M., Lee, J. and Pilch, P. F. (1997) Tumor necrosis factor-alpha-induced insulin resistance in 3T3-L1 adipocytes is accompanied by a loss of insulin receptor substrate-1 and GLUT4 expression without a loss of insulin receptor-mediated signal transduction. J Biol Chem 272, 971–976. 162. Zhang, B. et al. (1996) Negative regulation of peroxisome proliferator-activated receptor-gamma gene expression contributes to the antiadipogenic effects of tumor necrosis factor-alpha. Mol Endocrinol 10, 1457–1466. 163. Olefsky, J. M. (2000) Treatment of insulin resistance with peroxisome proliferatoractivated receptor gamma agonists. J Clin Invest 106, 467–472. 164. Szalkowski, D., White-Carrington, S., Berger, J. and Zhang, B. (1995) Antidiabetic thiazolidinediones block the inhibitory effect of tumor necrosis factor-α on differentiation, insulin-stimulated glucose uptake, and gene expression in 3T3-L1 cells. Endocrinol 136, 1474–1481. 165. Souza, S. C., Yamamoto, M. T., Franciosa, M. D., Lien, P. and Greenberg, A. S. (1998) BRL 49653 blocks the lipolytic actions of tumor necrosis factor-alpha: a potential new insulin-sensitizing mechanism for thiazolidinediones. Diabetes 47, 691–695. 166. Miles, P. D. et al. (1997) TNF-alpha-induced insulin resistance in vivo and its prevention by troglitazone. Diabetes 46, 1678–1683. 167. Friedman, J. M. and Halaas, J. L. (1998) Leptin and the regulation of body weight in mammals. Nature 395, 763–770. 168. Halaas, J. L. et al. (1995) Weight-reducing effects of the plasma protein encoded by the obese gene. Science 269, 543–546. 169. Shimomura, I., Hammer, R. E., Ikemoto, S., Brown, M. S. and Goldstein, J. L. (1999) Leptin reverses insulin resistance and diabetes mellitus in mice with congenital lipodystrophy. Nature 401, 73–76. 170. Minokoshi, Y. et al. (2002) Leptin stimulates fatty-acid oxidation by activating AMPactivated protein kinase. Nature 415, 339–343. 171. Oral, E. A. et al. (2002) Leptin-replacement therapy for lipodystrophy. N Engl J Med 346, 570–578. 172. Scherer, P. E., Williams, S., Fogliano, M., Baldini, G. and Lodish, H. F. (1995) A novel serum protein similar to C1q, produced exclusively in adipocytes. J Biol Chem 270, 26 746–26 749. 173. Arita, Y. et al. (1999) Paradoxical decrease of an adipose-specific protein, adiponectin, in obesity. Biochem Biophys Res Commun 257, 79–83. 174. Weyer, C. et al. (2001) Hypoadiponectinemia in obesity and type 2 diabetes: close association with insulin resistance and hyperinsulinemia. J Clin Endocrinol Metab 86, 1930–1935. 175. Maeda, N. et al. (2001) PPARgamma ligands increase expression and plasma concentrations of adiponectin, an adipose-derived protein. Diabetes 50, 2094–2099. 176. Combs, T. P. et al. (2002) Induction of Acrp30 levels by PPARg agonists: a potential mechanism of insulin sensitization. Endocrinology 143, 998–1007. 177. Berg, A. H., Combs, T. P., Du, X., Brownlee, M. and Scherer, P. E. (2001) The adipocyte-secreted protein Acrp30 enhances hepatic insulin action. Nat Med 7, 947–953. 178. Yamauchi, T. et al. (2001) The fat-derived hormone adiponectin reverses insulin resistance associated with both lipoatrophy and obesity. Nat Med 7, 941–946. 179. Fruebis, J. et al. (2001) Proteolytic cleavage product of 30-kDa adipocyte complementrelated protein increases fatty acid oxidation in muscle and causes weight loss in mice. Proc Natl Acad Sci USA 98, 2005–2010.

584

DRUG THERAPY FOR INSULIN RESISTANCE – A LOOK AT THE FUTURE

180. Ma, K. et al. (2002) Increased beta-oxidation but no insulin resistance or glucose intolerance in mice lacking adiponectin. J Biol Chem 277, 34 658–34 661. 181. Matsuda, M. et al. (2002) Role of adiponectin in preventing vascular stenosis. The missing link of adipo-vascular axis. J Biol Chem 277, 37 487–37 491. 182. Bluher, M. et al. (2002) Adipose tissue selective insulin receptor knockout protects against obesity and obesity-related glucose intolerance. Dev Cell 3, 25–38. 183. Maeda, N. et al. (2002) Diet-induced insulin resistance in mice lacking adiponectin/ACRP30. Nat Med 8, 731–737. 184. Kubota, N. et al. (2002) Disruption of adiponectin causes insulin resistance and neointimal formation. J Biol Chem 277, 25 863–25 866. 185. Havel, P. J. (2002) Control of energy homeostasis and insulin action by adipocyte hormones: leptin, acylation stimulating protein, and adiponectin. Curr Opin Lipidol 13, 51–59. 186. Steppan, C. M. et al. (2001) The hormone resistin links obesity to diabetes. Nature 409, 307–312. 187. Steppan, C. M. et al. (2001) A family of tissue-specific resistin-like molecules. Proc Natl Acad Sci USA 98, 502–506. 188. Way, J. M. et al. (2001) Adipose tissue resistin expression is severely suppressed in obesity and stimulated by peroxisome proliferator-activated receptor gamma agonists. J Biol Chem 276, 25 651–25 653. 189. McTernan, C. L. et al. (2002) Resistin, central obesity, and type 2 diabetes. Lancet 359, 46–47. 190. Nagaev, I. and Smith, U. (2001) Insulin resistance and type 2 diabetes are not related to resistin expression in human fat cells or skeletal muscle. Biochem Biophys Res Commun 285, 561–564. 191. Savage, D. B. et al. (2001) Resistin/Fizz3 expression in relation to obesity and peroxisome proliferator-activated receptor-gamma action in humans. Diabetes 50, 2199–2202. 192. Janke, J., Engeli, S., Gorzelniak, K., Luft, F. C. and Sharma, A. M. (2002) Resistin gene expression in human adipocytes is not related to insulin resistance. Obes Res 10, 1–5. 193. Brown, M. S. and Goldstein, J. L. (1998) Sterol regulatory element binding proteins (SREBPs): controllers of lipid synthesis and cellular uptake. Nutr Rev 56, S1–S3; discussion S54–S75. 194. Foretz, M., Guichard, C., Ferre, P. and Foufelle, F. (1999) Sterol regulatory element binding protein-1c is a major mediator of insulin action on the hepatic expression of glucokinase and lipogenesis-related genes. Proc Natl Acad Sci USA 96, 12 737–12 742. 195. Foretz, M. et al. (1999) ADD1/SREBP-1c is required in the activation of hepatic lipogenic gene expression by glucose. Mol Cell Biol 19, 3760–3768. 196. Shimomura, I. et al. (1998) Insulin resistance and diabetes mellitus in transgenic mice expressing nuclear SREBP-1c in adipose tissue: model for congenital generalized lipodystrophy. Genes Dev 12, 3182–3194. 197. Shimomura, I., Bashmakov, Y. and Horton, J. D. (1999) Increased levels of nuclear SREBP-1c associated with fatty livers in two mouse models of diabetes mellitus. J Biol Chem 274, 30 028–30 032. 198. Shimomura, I. et al. (1999) Insulin selectively increases SREBP-1c mRNA in the livers of rats with streptozotocin-induced diabetes. Proc Natl Acad Sci USA 96, 13 656–13 661. 199. Shimomura, I. et al. (2000) Decreased IRS-2 and increased SREBP-1c lead to mixed insulin resistance and sensitivity in livers of lipodystrophic and ob/ob mice. Mol Cell 6, 77–86. 200. Botion, L. M. and Green, A. (1999) Long-term regulation of lipolysis and hormonesensitive lipase by insulin and glucose. Diabetes 48, 1691–1697.

REFERENCES

585

201. Rosenstock, M., Greenberg, A. S. and Rudich, A. (2001) Distinct long-term regulation of glycerol and non-esterified fatty acid release by insulin and TNF-alpha in 3T3-L1 adipocytes. Diabetologia 44, 55–62. 202. Sztalryd, C., Komaromy, M. C. and Kraemer, F. B. (1995) Overexpression of hormonesensitive lipase prevents triglyceride accumulation in adipocytes. J Clin Invest 95, 2652–2661. 203. Winder, W. W. and Hardie, D. G. (1999) AMP-activated protein kinase, a metabolic master switch: possible roles in type 2 diabetes. Am J Physiol 277, E1–E10. 204. Zierath, J. R. (2002) Invited review: exercise training-induced changes in insulin signaling in skeletal muscle. J Appl Physiol 93, 773–781. 205. Ruderman, N. B. et al. (1998) Malonyl CoA as a metabolic switch and a regulator of insulin sensitivity. Adv Exp Med Biol 441, 263–270. 206. Zhou, G. et al. (2001) Role of AMP-activated protein kinase in mechanism of metformin action. J Clin Invest 108, 1167–1174. 207. Musi, N. et al. (2001) AMP-activated protein kinase (AMPK) is activated in muscle of subjects with type 2 diabetes during exercise. Diabetes 50, 921–927. 208. Musi, N. et al. (2001) AMP-activated protein kinase activity and glucose uptake in rat skeletal muscle. Am J Physiol Endocrinol Metab 280, E677–E684. 209. Merrill, G. F., Kurth, E. J., Hardie, D. G. and Winder, W. W. (1997) AICA riboside increases AMP-activated protein kinase, fatty acid oxidation, and glucose uptake in rat muscle. Am J Physiol 273, E1107–E1112. 210. Kemp, B. E. et al. (1999) Dealing with energy demand: the AMP-activated protein kinase. Trends Biochem Sci 24, 22–25. 211. Song, X. M. et al. (2002) 5-aminoimidazole-4-carboxamide ribonucleoside treatment improves glucose homeostasis in insulin-resistant diabetic (ob/ob) mice. Diabetologia 45, 56–65. 212. Iglesias, M. A. et al. (2002) AICAR administration causes an apparent enhancement of muscle and liver insulin action in insulin-resistant high-fat-fed rats. Diabetes 51, 2886–2894. 213. Gollob, M. H., Green, M. S., Tang, A. S. and Roberts, R. (2002) PRKAG2 cardiac syndrome: familial ventricular preexcitation, conduction system disease, and cardiac hypertrophy. Curr Opin Cardiol 17, 229–234. 214. Gollob, M. H. et al. (2001) Identification of a gene responsible for familial Wolff–Parkinson–White syndrome. N Engl J Med 344, 1823–1831. 215. Hamilton, S. R. et al. (2001) An activating mutation in the gamma1 subunit of the AMP-activated protein kinase. FEBS Lett 500, 163–168. 216. Arad, M. et al. (2002) Constitutively active AMP kinase mutations cause glycogen storage disease mimicking hypertrophic cardiomyopathy. J Clin Invest 109, 357–362. 217. Schwartz, M. W., Woods, S. C., Porte, D., Jr., Seeley, R. J. and Baskin, D. G. (2000) Central nervous system control of food intake. Nature 404, 661–671. 218. Obici, S., Zhang, B. B., Karkanias, G. and Rossetti, L. (2002) Hypothalamic insulin signaling is required for inhibition of glucose production. Nat Med 8, 1376–1382.

Index Page numbers in italic, e.g. 513, refer to figures. Page numbers in bold, e.g. 215, signify entries in tables. acanthosis nigricans 513, 513 acetyl CoA carboxylase (ACC) 89, 97 acquired generalized lipodystrophy 521–2 acquired partial lipodystrophy 524–5 acute insulin release (AIR) 161, 162 adaptor with PH and SH2 domains (APS) proteins 21 adipocytes 209–10 change in phenotype with obesity 210 differences between subcutaneous and visceral depots 215 adipocytokines 245–8, 476 adipogenesis 271 adipokines 66, 269–70, 269, 280 insulin resistance 272 adiponectin 279–80 interleukin-6 (IL-6) 274–6 leptin 276–8 resistin 278–9 tumour necrosis factor-α (TNFα) 272–4 adiponectin (ACRP30) 66, 143, 246–7, 253, 269, 279–80 future drug therapies 572 genetic basis of metabolic syndrome 414–16, 415 adipose tissue 207–8, 208, 224 as an endocrine organ 214–15, 215 change in adipocyte phenotype with obesity 210 effect of PPARγ 252–3 effects of insulin on glucose metabolism 65, 66 glucose metabolism GLUT4 cycle and its regulation by insulin 74 GLUT4 translocation and glucose uptake increase 76–9, 78

regulation by GLUT4 70–1 signals regulating GLUT4 traffic 75–6 modulation of insulin sensitivity 142–3, 142 pathological significance of abdominal adipose tissue 211–12 renin–angiotensin system (RAS) 216–17 subcutaneous and visceral adipose tissue 211 variation in distribution 209–10 ADP-ribosylation factor-1 (ARF-1) 99 adrenal glands, central control of glucoregulation 188–9 adrenocorticotrophic hormone (ACTH) 189, 218 agouti-related peptide (AgRP) 192, 425 Akt see protein kinase B alcohol consumption 308–9 Alstrom’s syndrome 412, 514, 525 amino acids 111–12 continuous infusion technique 116 effect of availability on protein turnover 114 flooding dose technique 115–16 measurement of free amino acid concentrations 112–13 stable isotope tracers 116–17 tracer techniques 114–15 aminoimidazole-4-carboxamide riboside (AICAR) 574 AMP-activated protein kinase (AMPK) 277 future drug therapies 573–4 androgens 223–4 android pattern of fat distribution 208, 209, 222 Angelman syndrome 412 angiotensinogen (AGT) 216, 217

Insulin Resistance. Edited by Sudhesh Kumar and Stephen O’Rahilly  2005 John Wiley & Sons, Ltd ISBN: 0-470-85008-6

588

INDEX

apolipoprotein C-III (apoC-III) 88 appetite 352–3 apple-shaped bodies 208 arcuate nucleus (ARC) 185, 192 aromatase 220–2 adipose tissue in knockout mice 221 aspirin 475, 570 atherosclerosis 469 link with obesity 538 Atherosclerosis Risk in Communities Study (ARIC) 308, 410 atropine 188 Bardet–Beidl syndrome 412 bariatric surgery 300 Barraquer–Simons syndrome 524 Berardinelli–Seip syndrome 413 β3-adrenoreceptor, genetic basis of metabolic syndrome 415, 420–1 β-cell-specific insulin receptor knockout (BIRKO) mice 141 bilio-pancreatic bypass 544 body mass index (BMI) 298, 298, 402, 537 Bradford Hill criteria 317 brain and CNS effects of insulin on glucose metabolism 65, 66–7 regulation of peripheral glucose metabolism 179, 180, 194–5 additional afferent signals 189–94, 190 brain regions involved in counter-regulation 182–4 central control of peripheral glucoregulation organs 187–9 counter-regulation by hypoglycaemia 180–2 glucosensing neurons 184–7 British Regional Heart Study 309 brown adipose tissue (BAT) 192 CAP/Cbl/TC-10 pathway 31, 32 carbohydrate in the diet 304–8, 307 carcinoembryonic antigen-related cell adhesion molecule-1 (CEACAM-1) 35 CARDIA study 410 cardiovascular disease, insulin resistance and dyslipidaemia 460–1 carnitine–palmitoyl transferases (CPTs) 96–7 CPT-1 278 Carpenter syndrome 412 Cbl 21, 31 Cbl-associated protein (CAP) 31, 565

central nervous system (CNS) see brain and CNS cholecystokinin 195 cholesterol LDL cholesterol levels versus LDL particle number 459, 460 reduced HDL cholesterol concentrations 455–7 synthesis 97 cholesterol ester transfer protein (CETP) 352, 456 chromium as a micronutrient 310 ciglitazone 545 citrate synthase (CS) 351 cocaine- and amphetamine-regulated transcript (CART) 425 Cohen syndrome 412 congenital generalized lipodystrophy (CGL) 413, 514, 521, 522 corticotrophin-releasing hormone (CRH) 189, 218 cortisol 189, 218 Cushing’s syndrome 217–18 cytochalasin 72 cytochrome P450 enzymes 220 2-deoxyglucose (2-DG) 182, 183–4, 188 dexamethasone 218, 239 diabetes mellitus 87 double heterozygous mice models of polygenic diabetes 139–40 historical perspective 105 insulin and mixed muscle protein in type 1 diabetes 121 insulin and regional protein metabolism in type 1 diabetes 120–1 insulin and regional protein metabolism in type 2 diabetes 123–4 whole body leucine flux measurement in type 1 diabetes 117–18 diabetes mellitus, type 2 (T2D) 87, 155–7 hyperglycaemia 474 insulin-resistant states 162, 171–2 biochemical defects in hepatic insulin action 170 glucose disposal in skeletal muscle 163–6 hepatic glucose production 168–70 pathophysiology 168 secondary defects in insulin action in skeletal muscle 168 obesity 207–8, 208, 209 Diabetes Prevention Program 301 diet 297–8, 310

INDEX

excess of nutrients as a cause of insulin resistance 147 importance of body fatness 298–302 lipid intake 242–5, 244 PPARs as key mediators of nutritional-related gene expression 148 specific dietary factors 302 alcohol 308–9 carbohydrate 304–8, 307 fat 302–4 micronutrients 309–10 protein 308 very low calorie diets (VLCD) 300 dietary fibre 305–6 docosahexanoic acid (DHA) 303 Donohue’s syndrome (leprechaunism) 489, 512, 514, 515 dorsomedial hypothalamic nucleus (DMH) 192 downstream of kinases (DOKs) proteins 19 downstream signalling 1–2, 38–9, 562 CAP/Cbl/TC-10 pathway 31, 32 further potential signalling components 35–7 MAPK/ERK cascade 31–5, 33 phosphoinositide 3-kinase 23–5 reaction and structure 24 phosphoinositide-dependent kinases and protein kinase B/Akt 25–30 atypical PKCs 30–1 other substrates of PDK1 30–1 specificity 37–8 drug therapies for insulin resistance, future perspectives 561–3, 574–5 see also therapies for insulin resistance targeting negative modulators of insulin signalling PTP1B 567 SHIP/PTEN 567–9 targeting obesity 569 adipose-secreted proteins 571–2 AMP kinase, lipid synthesis and oxidation 572–4 IKKβ/JNK 570–1 targets in the obesity/insulin resistance axis 569–70 targeting signal transduction pathway molecules GLUT4 translocation 565–6 GSK3 566 insulin receptor (IR) 563 IRS proteins 564 PI3 kinase/Akt pathways 564–5

589

Dunnigan–Kobberling syndrome see familial partial lipodystrophy (FPL) dyslipidaemia 451, 461 historical perspective 451–3, 452 hypertriglyceridaemia 453–5, 454 insulin resistance and risk of cardiovascular disease 460–1 LDL cholesterol levels versus LDL particle number 459, 460 obesity and insulin resistance syndrome 453 reduced HDL cholesterol concentrations 455–7 small and dense LDL particles 457–9, 458 eicosapentanoic acid (EPA) 303 elongation factor 2 (eEF-2) 108 endoplasmic reticulum (ER) 89 endothelial dysfunction atherothrombotic disease 469 measurement of NO availability in vivo 470–1 role of nitric oxide (NO) 470, 470 direct vascular action of insulin 471 abnormal signalling 474–7, 475 role of endothelial dysfunction in insulin resistance 473–4 role of insulin resistance 471–3, 472, 473 insulin resistance and hypertension 467–8, 477–8, 478 possible mechanisms 468, 469 eukaryotic initiation factor 4E (eIF-4E) 108 exercise see physical activity and insulin resistance familial partial lipodystrophy (FPL; Dunnigan–Kobberling syndrome) 413, 514, 522–4, 523 fasting levels of insulin 64 fat distribution 207–9, 208, 224 see also obesity android pattern 208, 209, 222 change in adipocyte phenotype with obesity 210 gynoid pattern 208, 209, 222 mechanisms linking central obesity to metabolic syndrome 212 adipose tissue as an endocrine organ 214–15, 215 alternative hypotheses 213–14 ectopic fat storage 214 glucocorticoid metabolism 217–18

590

INDEX

fat distribution (continued ) plasminogen activator–inhibitor 1 (PAI-1) 215–16 Randle hypothesis/glucose–fatty acid hypothesis 212–13, 213 renin–angiotensin system (RAS) in adipose tissue 216–17 sex steroids and body fat 222–4 visceral obesity and steroid hormone metabolism 217 obesity and insulin resistance 210–11 pathological significance of abdominal adipose tissue 211–12 subcutaneous and visceral adipose tissue 211 variation in adipose tissue 209–10 fat in the diet 302–4 fat-specific insulin receptor knockout (FIRKO) mice 140–1 fatty acid binding proteins (FABPs) 143 fatty acid synthase (FAS) 89 fatty acid translocase (FAT) 95–6 fatty acid transport protein-1 (FATP-1) 95–6 fatty acids central regulation of peripheral glucose metabolism 194 Randle free fatty acid (FFA) cycle 164–5 synthesis 96–7 fibre in the diet 305–6 fibrinolytic activity 215–16 Finnish diabetes prevention study 301 flotillin 565 flutamide 498 Framingham Heart Study 306, 409 functional ovarian hyperandrogenism 488 G6Pase 170 galanin 188 gastric releasing peptide 188 genetics of metabolic syndrome 427 candidate genes 414, 415 11β-HSD 421–2 adiponectin 414–16 genome scans and linkages 419 glucocorticoid receptor (GR) 423–4 hypothalamic genes 424–6 leptin 416–17 plasma cell membrane glycoprotein 418–19 PPARγ 419–20 resistin 417–18 TNF-α 422–3 β3-adrenoreceptor 420–1 epidemiology 407–11

heritability of common manifestations 408 genomic scans 426–7 hierarchical relations between genetic and non-genetic components 403 historical perspective 401–3 monogenic disorders 411 lipodystrophy–lipoatrophy 412, 413 Prader–Willi syndrome 412 rare syndromic obesities 412 gherlin 195, 412 glibenclamide 186 glucagon 188 glucocorticoid metabolism and obesity 217–18 glucocorticoid receptor (GR), genetic basis of metabolic syndrome 415, 423–4 glucokinase (GK) 170, 186–7 glucopenia 188 glucose homeostasis and PPARγ 237–8 cell and rodent models 238 adipocytokines 245–8 adipose tissue insulin sensitivity 242 dietary lipid handling 242–5, 244 liver 249–51, 251 pancreatic β-cells 249, 251 skeletal muscle 248–9, 251 white adipose tissue 238–41, 239 human studies 251 adipose tissue 252–3 insulin sensitivity 251–2, 256 Pro12Ala polymorphism 255–6 rare mutations 253–5 glucose metabolism, central regulation 179, 180, 194–5 additional afferent signals fatty acids 194 insulin 193 leptin 191–2 pancreatic and hepatic glucosensing 189–91, 190 brain regions involved in counter-regulation 182–4 central control of peripheral glucoregulation organs adrenal glands 188–9 liver 187 pancreas 187–8 counter-regulation by hypoglycaemia 180–2 glucosensing neurons 184–7 glucose metabolism, insulin-mediated regulation 63, 67–9 master regulation of whole body glucose disposal

INDEX

direct and indirect regulation at classical target tissues 63–6, 65 direct and indirect regulation at non-classical target tissues 66–7 metabolic syndrome and type 2 diabetes 155–7 normal glucose disposal 162–3, 163 rate limitation by skeletal muscle uptake 69–70 GLUT4 cycle and its regulation by insulin 74 GLUT4 translocation and glucose uptake increase 76–9, 78 insulin-mediated GLUT4 traffic 71–5 regulation by GLUT4 70–1 signals regulating GLUT4 traffic 75–6 target proteins and regulation mechanisms 68 glucose sensitivity 157 glucose transporter 4 (GLUT4) cellular defects in skeletal muscle 166–7 future drug therapies 565–6 GLUT4 vesicles 25, 28 translocation 31, 32 knockout mice 139 normal glucose disposal 162 physical activity and insulin resistance and insulin resistance 351–2 primary/genetic defects in insulin action in skeletal muscle 167 regulation of glucose uptake in muscle and fat cells 70–1 GLUT4 cycle and its regulation by insulin 74 GLUT4 translocation and glucose uptake increase 76–9, 78 insulin-mediated GLUT4 traffic 71–5 signals regulating GLUT4 traffic 75–6 glucose-6-phosphate (G6P) 66, 67 cellular defects in skeletal muscle 166 normal glucose disposal 162–3 glycaemic index (GI) of foods 306–8 glycerol-3-phosphate acyltransferase (GPAT) 89, 90 glycogen 164 glycogen synthase (GS) 164, 351 activation by insulin 167, 168 glycogen synthase kinase 3 (GSK-3) 566

591

glycolytic flux (GF) rates 160–1, 163, 165–6 gonadotrophin-releasing hormone (GnRH) 488 G-proteins 36 Grb10/Grb14 family of proteins 22 Grb2-associated binders (Gabs) proteins 19 GTPases 36 guanine nucleotide exchange factor (Grb2/Sos) 2 gynoid pattern of fat distribution 208, 209, 222 Health Professionals Follow-Up Study 306 hepatic glucose production (HGP) 159–60 hepatic steatosis 214 Heritage Study 385, 411 hexokinase (HK) 351 high density lipoprotein (HDL) 451, 454 reduced HDL cholesterol concentrations 455–7 HIV-associated lipodystrophy 413, 514, 524 homeostasis assessment model (HOMA) test 158, 297 hormone-sensitive lipase (HSL) 88, 92–4, 93, 269 3-hydroxy-3-methylglutaric acid (HMG) 97 β-hydroxybutyrate 118 11β-hydroxysteroid dehydrogenase (11β-HSD) 218 genetic basis of metabolic syndrome 415, 421–2 isoenzymes 218–19 link to obesity 219–20 hyperandrogenism 485, 486, 488 hyperinsulinism 489–91 hyperandrogenism–insulin resistance and acanthosis nigricans (HAIR-AN) syndrome 514, 517 hyperglycaemia 474 hyperinsulinism and premature pubarche 495–7, 497 hyperplasia 210 hypertension 410 direct vascular action of insulin 471 role of endothelial dysfunction in insulin resistance 473–4 role of insulin resistance 471–3, 472, 473

592

INDEX

hypertension (continued ) insulin resistance and endothelial dysfunction 467–8, 477–8, 478 possible mechanisms 468, 469 hypertriglyceridaemia 453–5, 454 hypoglycaemia 180–2, 184 severe 190–1 hypogonadism 412 hypothalamo–pituitary–adrenal (HPA) axis 218 hypothalamus 182–3, 184–6, 188–9, 192 genetic basis of metabolic syndrome 415, 424–6 impaired glucose tolerance (IGT) twins 164 indinavir (HIV protease inhibitor) 70 glucose uptake inhibition in skeletal muscles and adipocytes 71 insulin central regulation of peripheral glucose metabolism 193 glucose metabolism, regulation of 63, 67–9 classical and non-classical target organs 65 GLUT4 cycle and its regulation by insulin 74 GLUT4 translocation and glucose uptake increase 76–9, 78 lipolysis, inhibition of 65–6 rate limitation by skeletal muscle uptake 69–79 signals regulating GLUT4 traffic 75–6 target proteins and regulation mechanisms 68 whole body glucose disposal 63–7 lipid metabolism 87, 98–9 lipolysis 89–94, 90, 91, 92 lipoprotein lipase and cellular fatty acid uptake 94–6, 94 molecular mechanisms 88–9 regulation of fatty acid synthesis and ketogenesis 96–7 protein metabolism 105 assessment sites 112 measurement of protein metabolism in humans 111–13 molecular mechanisms 107–11 protein turnover 106–7, 106, 107 whole body protein turnover 114–25 signalling network 136, 136 synthesis 97 insulin receptor (IR) 1–2, 38–9

future drug therapies 563 knockout mice 137 structure and function autophosphorylation 9–13 β-helical domains (L1 and L2) 6, 7, 9, 10 carboxyl-terminal domain (CT) 6, 7, 11, 12 cystein-rich (CR) region 6–8, 7, 10 extracellular domain 4, 6–9 fibronectin type III repeats (Fn0, Fn1 and Fn2) 6, 7, 8, 10 gene 2–4 hybrids 5–6 intracellular domain 9–13, 12 juxtamembrane region (JM) 6, 7, 11, 12 ligand binding 6–9, 10 receptor family 2–6, 3 regulation of expression 13–15 similarity to IGFR 4–5 tyrosine kinase activation 9–13 tyrosine kinase domain (TK) 6, 7, 12 insulin receptor substrates (IRSs) 1, 11, 15 APS and Cbl 21 DOKs and Gabs 19 Grb10/Grb14 family of proteins 22 IRS-1 protein 16–18, 18 IRS-2 protein 16–17 IRS-3 protein 17 IRS-4 protein 17 knockout mice 137–8, 141 proteins 15–19 Shc proteins 20 insulin resistance 133, 171–2 see also metabolic syndrome atherosclerosis 469 classification of states 156 definition 157–8 definition 158 factors leading to insulin resistance 137 future drug therapies 561–3, 574–5 targeting negative modulators of insulin signalling 567–9 targeting obesity 569–74 targeting signal transduction pathway molecules 563–6 genetically modified mouse models 133–5 benefits of genetic modification 135 candidate genes involved in insulin resistance 135

INDEX

defining function of cascade molecules through global knockouts 137–9 defining tissue and/or organ relevance for insulin resistance 140–2 double heterozygous mice and polygenic diabetes 139–40 excess of nutrients as a cause of insulin resistance 147 interorgan communication and fuel partitioning 144–6 lipodystrophy and obesity 143–7 modifications and phenotypes 134 modulators of insulin sensitivity 142–3 PPARs as key mediators of nutritional-related gene expression 148 hypertension and endothelial dysfunction 467–8, 477–8, 478 abnormal signalling 474–7, 475 possible mechanisms 468, 469 role of endothelial dysfunction in insulin resistance 473–4 role of insulin resistance 471–3, 472, 473 insulin resistant states 162 biochemical defects in hepatic insulin action 170 cellular defects in skeletal muscle 166–7 hepatic glucose production 168–70 increased hepatic VLDL production 170–1 pathophysiology 168 primary/genetic defects in insulin action in liver 171 primary/genetic defects in insulin action in skeletal muscle 167 secondary defects in insulin action in skeletal muscle 168 skeletal muscle 163–6, 164 insulin sensitizers and cardiovascular risk factors 551 metformin 551–2 thiazolidinediones (TZD) 552–3, 552 measurement 157–8 euglycaemic clamp technique 159–60, 159 frequently sampled IVGTT 161–2 non-dynamic 158 whole body glycolytic flux (GF) rates 160–1 metabolic syndrome and type 2 diabetes 155–7

593

relationship with obesity 210–11 risk factors 537 therapeutic strategies 535, 553–4 obesity 535–44 pharmacological treatment 544–51 type A 515–17 type B 517 insulin response element (IRE) 88 insulin sensitivity, effect of PPARγ 251–2, 256 insulin-like growth factor binding protein (IGFBP1) 486 insulin-like growth factor receptor (IGFR) 4–5 hybrids 5–6 insulin binding 5 insulin-receptor-related receptor (IRR) 5 insulin-responsive aminopeptidase (IRAP) 73 interleukin-6 (IL-6) 269 internal ribosome entry sites (IRESs) 14 Janus kinases (JAKs) 16, 35 Kaiser Permanente Women Twins Study 411 ketogenesis 96–7 ketoisocaproic acid (KIC) 117 K¨obberling–Dunnigan syndrome 413 Kuopio Ischaemic Heart Disease Risk Factor Study 383 lap-band surgical procedures 544 lateral hypothalamic area (LHA) 183, 184–5, 188–9, 192 lecithin–cholesterol acyl transferase (LCAT) 352 leprechaunism see Donohue’s syndrome leptin 66, 191–2, 245–6, 269, 276–8 disruption of AMPK activity 277 effect of physical activity and insulin resistance 353 future drug therapies 572 genetic basis of metabolic syndrome 415, 416–17 recombinant 527 leucine, whole body flux measurement in type 1 diabetes 117–18 leuprolide acetate 488 lipid metabolism, role of insulin 87, 98–9 insulin and cholesterol synthesis 97 lipolysis in vivo effects 89–92, 90, 91, 92 regulation by insulin and other hormones 92–4, 93

594

INDEX

lipid metabolism, role of insulin (continued ) lipoprotein lipase and cellular fatty acid uptake 94–6, 94 molecular mechanisms 88–9 regulation of fatty acid synthesis and ketogenesis 96–7 lipid steal hypothesis 243–5, 253 lipodystrophy 143–7, 156, 412 selected syndromes 413 lipogenesis 210 lipolysis 210 insulin-mediated inhibition 65–6, 89–94, 90, 91, 92 lipoprotein lipase (LPL) 88, 93, 273 cellular fatty acid uptake 94–6, 94 sex steroids and body fat 222–4 liver biochemical defects in insulin action 170 central control of glucoregulation 187 effects of insulin on glucose metabolism 65, 66 glucose production 168–70 glucosensing 189–91 hepatic steatosis 214 increased VLDL production 170–1 primary/genetic defects in insulin action 171 role of PPARγ 249–51, 251 liver insulin receptor knock-out (LIRKO) mice 64, 66, 141 low density lipoprotein (LDL) 98–9, 451, 454, 455 LDL cholesterol levels versus LDL particle number 459, 460 small and dense particles 457–9, 458 luteinizing hormone (LH) 486, 487, 488 M-value of euglycaemic clamp 159 magnesium as a micronutrient 309 malonyl-CoA 278 mandibulo-acral dysplasia (MAD) 514, 523 MAPK/ERK cascade 31–5, 33 α-melanocyte stimulating hormone (α-MSH) 192 men, pattern of fat distribution 208, 209, 222 mesangiocapillary glomerulonephritis type II (MCGN type II) 525 metabolic syndrome 155–7 see also insulin resistance classification 536 genetic epidemiology 407–11 heritability of common manifestations 408

hierarchical relations between genetic and non-genetic components 403 historical perspective 401–3 mechanisms linking central obesity to metabolic syndrome 212 adipose tissue as an endocrine organ 214–15, 215 alternative hypotheses 213–14 ectopic fat storage 214 Randle hypothesis/glucose–fatty acid hypothesis 212–13, 213 pathophysiology 404–7 hormones, organs, tissues and cellular pathways 405 metformin 252, 498–501, 500, 574 cardiovascular risk factors 551–2 insulin resistance treatment 544–5 syndromes of severe insulin resistance (SSIRs) 527 3-O-methyl glucose 182 methylaminoisobutyric acid (MeAIB) 114 3-methylhistidine (3-MH) 113 measurement of insulin effect on protein breakdown 113 micronutrients in the diet 309–10 microsomal triglyceride transfer protein (MTP) 98, 171 mitogen-activated protein kinases (MAPKs) 2, 352 MONA-LISA hypothesis 407 monounsaturated fatty acids (MUFAs) 303 mouse models of insulin resistance, genetically modified 133–5 benefits of genetic modification 135 candidate genes involved in insulin resistance 135 defining function of cascade molecules through global knockouts 137–9 defining tissue and/or organ relevance for insulin resistance 140–2 double heterozygous mice and polygenic diabetes 139–40 excess of nutrients as a cause of insulin resistance 147 interorgan communication and fuel partitioning 144–6 lipodystrophy and obesity 143–7 modifications and phenotypes 134 modulators of insulin sensitivity 142–3 normal insulin signalling network 136, 136 PPARs as key mediators of nutritional-related gene expression 148

INDEX

MRC ProActive Trial 384 muscles cellular defects in skeletal muscle 166–7 effects of insulin on glucose metabolism 65, 66 glucose disposal in skeletal muscle 163–6, 164 glucose metabolism, rate limitation by skeletal muscle uptake 69–70 GLUT4 cycle and its regulation by insulin 74 GLUT4 translocation and glucose uptake increase 76–9, 78 insulin-mediated GLUT4 traffic 71–5 regulation by GLUT4 70–1 signals regulating GLUT4 traffic 75–6 primary/genetic defects in insulin action in skeletal muscle 167 secondary defects in insulin action in skeletal muscle 168 skeletal muscle, role of PPARγ 248–9, 251 muscle-specific insulin receptor knockout (MIRKO) mice 140 myotonic dystrophy 514 nandrolone 224 neuronal-specific insulin receptor knockout (NIRKO) mice 141 neuropeptide Y (NPY) 188, 192, 195 nitric oxide (NO) 247, 352 measurement of availability in vivo 470–1 role in vascular endothelial function 470, 470 nitrogen balance 111–12 non-alcoholic fatty liver diseases (NAFLD) 214 non-alcoholic steatohepatisis (NASH) 214 non-esterified fatty acids (NEFAs) 65–6, 89–92, 90, 91, 92 alternative hypotheses 213–14 pathological significance of abdominal adipose tissue 212 Randle hypothesis/glucose–fatty acid hypothesis 212–13, 213 regulation of fatty acid synthesis and ketogenesis 96–7 subcutaneous and visceral adipose tissue 211 norepinephrine (NE) 181–2, 188

595

nuclear factor-κB (NFκB) 475, 475 nucleus of the solitary tract (NTS) 183–4, 185, 192 Nurses’ Health Study 303, 307, 410 obesity 143–7, 270–1 see also fat distribution change in adipocyte phenotype 210 drug therapies 540–1 orlistat 541–2 sibutramine 542–3 future drug therapies 569 targets in the obesity/insulin resistance axis 569–74 importance of body fatness 298–302, 298 link with atherosclerosis 538 management 537–8 benefits of weight loss 539 diet 539–40 exercise and physical activity 540 mechanisms linking central obesity to metabolic syndrome 212 adipose tissue as an endocrine organ 214–15, 215 alternative hypotheses 213–14 aromatase 220–2, 221 ectopic fat storage 214 glucocorticoid metabolism 217–18 11β-hydroxysteroid dehydrogenase (11β-HSD) 219–20 plasminogen activator–inhibitor 1 (PAI-1) 215–16 Randle hypothesis/glucose–fatty acid hypothesis 212–13, 213 renin–angiotensin system (RAS) in adipose tissue 216–17 sex steroid metabolism 220 sex steroids and body fat 222–4 visceral obesity and steroid hormone metabolism 217 pathological significance of abdominal adipose tissue 211–12 relationship with insulin resistance 210–11 risk of T2D 209 subcutaneous and visceral adipose tissue 211 surgery 543–4, 544 therapeutic strategies for insulin resistance 535–7 obesity (ob) gene 66 oestrogen 223 oestrogen biosynthesis 220 Online Mendelian Inheritance in Man (OMIM) website 411

596

INDEX

orlistat 300, 301 anti-obesity therapies 541–2 ovarian hyperandrogenism 514 pancreas β-cells, role of PPARγ 249, 251 central control of glucoregulation 187–8 effects of insulin on glucose metabolism 65, 66–7 glucosensing 189–91 parasympathetic nervous system (PNS) 182 paraventricular nucleus of the hypothalamus (PVN) 185, 192 parthenolide 570 pear-shaped bodies 208 peroxisome proliferator-activated receptors (PPARs) 237 key mediators of nutritional-related gene expression and insulin sensitivity 148 peroxisome proliferator-activated receptor-gamma (PPARγ) and glucose homeostasis 237–8 cell and rodent models 238 adipocytokines 245–8 adipose tissue insulin sensitivity 242 dietary lipid handling 242–5, 244 liver 249–51, 251 pancreatic β-cells 249, 251 skeletal muscle 248–9, 251 white adipose tissue 238–41, 239 genetic basis of metabolic syndrome 415, 419–20 human studies 251 adipose tissue 252–3 insulin sensitivity 251–2, 256 Pro12Ala polymorphism 255–6 rare mutations 253–5 phosphoenolpyruvate carboxykinase (PEPCK) 107 phosphoinositide 3-kinase (PI 3-kinase) 1–2, 23–5 future drug therapies 564–5 knockout mice 138 reaction and structure 24 phosphoinositide-dependent kinases (PDKs) 25–30 PDK1 26, 27 other substrates 30–1 phosphorylated heat–acid-stable protein (PHAS-1) 108 phospho-tyrosine binding (PTB) domains 16

physical activity and insulin resistance 317, 385–6 evidence from studies 318 heterogeneity of population sub-groups 375–85 management of obesity 540 mechanisms underlying association with insulin resistance 351–3 observational studies in adults 318–38, 319–37 determining whether there is a causal relationship between inactivity and insulin resistance 340 effect on insulin resistance 338 identifying sub-dimensions of activities 339 identifying which activity is most closely associated with insulin resistance 338–9 observational studies in children and adolescents 340–51, 341–50 trials on insulin sensitivity in adults 353–74, 354–73 trials on insulin sensitivity in children and adolescents 374–5, 376–82 pioglitazone 252, 545, 553 insulin resistance treatment 548–50 structure 546 plasma cell membrane glycoprotein (PC-1), genetic basis of metabolic syndrome 415, 418–19 plasminogen activator–inhibitor 1 (PAI-1) 215–16, 553 pleckstrin homology (PH) domain 16 polycystic ovary syndrome (PCOS) 485, 502 antiandrogen treatment 497–8 assessment of insulin resistance 491–2 definition and diagnostic criteria 486–8, 487 clinical and biochemical evaluation 488 endocrine and metabolic disorders 490 gene studies 492–5 hyperandrogenism and hyperinsulinism 489–91 insulin sensitizer treatments metformin 498–501, 500 thiazolidinediones 501–2 premature pubarche and hyperinsulinism 495–7, 497 polypeptide YY 195 polyunsaturated fatty acids (PUFAs) 303–4 potassium–ATP (K+ –ATP) channels 186, 194, 195

INDEX

Prader–Willi syndrome 412 proopiomelanocortin (POMC) 192, 426 cells 193, 195 protein in the diet 308 protein kinase B (Akt) 25–30, 88 activation and substrates 27 future drug therapies 564–5 knockout mice 138 protein metabolism, role of insulin 105 measurement of protein metabolism in humans assessment sites 112 3-methylhistidine (3-MH) concentration 113 3-methylhistidine (3-MH) concentration and insulin effect 113 nitrogen balance and free amino acid concentrations 112–13 protein turnover 111 whole body nitrogen balance 111–12 molecular mechanisms intracellular protein breakdown 108–9 intracellular protein synthesis 107–8 protein turnover 106–7, 106, 107 animal studies 110–11 measurement in humans 111 regulation by insulin in vivo and in situ 110 regional protein turnover 118, 124–5 effect of insulin in type 2 diabetes 123–4 effect of insulin on healthy volunteers 122–3 effect of insulin on specific proteins 122 fractional synthesis rate of specific proteins 121–2 mixed muscle protein in type 1 diabetes 121 sites of protein accretion before and after meals 120 tissue-specific protein synthesis 121 type 1 diabetes and healthy controls 119–21, 119 whole body protein turnover 124–5 amino acid availability 114 amino acid continuous infusion technique 116 amino acid flooding dose technique 115–16 amino acid stable isotope tracers 116–17

597

amino acid tracer techniques 114–15 leucine flux in type 1 diabetes 117–18 protein-tyrosine-phosphatase-1B (PTP1B) future drug therapies 567 knockout mice 139 pseudoacromegaly 514 PTEN family of phosphatases 25 future drug therapies 567–9 pubarche, premature 495–7, 497 pyruvate dehydrogenase complex (PDH) 69 pyruvate dehydrogenase kinase 4 (PDK4) 249 quantitative insulin-sensitivity check index (QUICKI) test 158 Quebec Family Study 411 Rabson–Mendenhall syndrome 489, 514, 515 racial variation 409 Randle hypothesis/glucose–fatty acid hypothesis 212–13, 213, 270 Ras protein 2 renin–angiotensin system (RAS) 216–17 resistin 247, 269, 278–9 future drug therapies 572 genetic basis of metabolic syndrome 415, 417–18 retinoic acid receptor (RXR) 238 Rheb protein 29 ribosomes 108 rosiglitazone 252, 545, 553 insulin resistance treatment 547–8 structure 546 salicylates 519–20, 570 San Antonio Family Heart Study 409 sex hormone binding globulin (SHBG) 486 SHIP family of phosphatases 25 future drug therapies 567–9 sibutramine 300 anti-obesity therapies 542–3 signal transducers and activators of transcription (Stats) 35 Silver–Russell syndrome 22 Somogyi phenomenon 181 Src homology and collagen-like (Shc) proteins 20 SREBP cleavage activating peptide (SCAP) 89

598

INDEX

stearoyl CoA desaturase (SCD-1) 89 steroid hormone metabolism and obesity 217 sex steroids 220 body fat 222–4 sterol regulated elements (SREs) 89 sterol regulatory element binding protein 1c (SREBP-1c) 88–9, 97, 146–7 future drug therapies 572–3 subcutaneous adipose tissue (SAT) 270 Swedish Adoption/Twin Study of Aging 409 sympathetic nervous system (SNS) 182, 188 syndromes of severe insulin resistance (SSIRs) 511–12 biochemical and clinical features acanthosis nigricans 513, 513 compensatory hyperinsulinaemia and disturbed glucose metabolism 512 ovarian hyperandrogenism 514 classification 514, 514 complex genetic syndromes Alstrom’s syndrome 525 other syndromes 525–6 lipodystrophic syndromes 518–20 acquired generalized lipodystrophy 521–2 acquired partial lipodystrophy 524–5 congenital generalized lipodystrophy (CGL) 521, 522 familial partial lipodystrophy (FPL) 522–4, 523 HIV-associated lipodystrophy 525 mandibulo-acral dysplasia (MAD) 524 PPARγ deficiency 524 primary disorders Donohue’s syndrome 515 Rabson–Mendenhall syndrome 515 type A insulin resistance 515–17 type B insulin resistance 517 types 1 and 2 diabetes requiring high doses of exogenous insulin 517–18 therapeutic options managing consequences 528 treatments to ameliorate insulin resistance 526–8 systemic lupus erythematosis (SLE) 517

therapies for insulin resistance 535, 553–4 anti-obesity drugs orlistat 541–2 sibutramine 542–3 obesity 535–7 anti-obesity drugs 540–1 dietary management 539–40 exercise and physical activity 540 general management 537–8 pharmacological treatment metformin 544–5 pioglitazone 548–50 rosiglitazone 547–8 thiazolidinediones (TZD) 545–7 surgical management of obesity 543–4, 544 thiazolidinediones (TZDs) 417, 419 cardiovascular risk factors 552–3, 552 effect on adipose tissue 252–3 effect on insulin sensitivity 252 effect on leptin 277 effect on resistin 277 effect on TNFα 273–4 insulin resistance treatment 545–7 weight gain 550–1 polycystic ovary syndrome (PCOS) 501–2 syndromes of severe insulin resistance (SSIRs) 527 5-thio-D-glucose (5TG) 183–4 thrifty phenotype hypothesis 383 tolbutamide 186 triacylglycerol (TG) 92, 93 troglitazone 252, 527, 545 structure 546 tumour necrosis factor-α (TNF-α) 247, 269, 272–4, 475 future drug therapies 571–2 genetic basis of metabolic syndrome 415, 422–3 ubiquitin–proteosome protein degradation pathway 108–9 urea 112 urine, total body nitrogen loss 112 vanadate 567 vascular cells, effects of insulin on glucose metabolism 67, 65 vasoactive intestinal peptide 187–8 ventromedial hypothalamus (VMH) 181–183, 185, 186, 188–9, 192

INDEX

very low calorie diets (VLCD) 300 very low density lipoprotein (VLDL) 98–9, 453, 455 increased hepatic production 170–1 visceral adipose tissue (VAT) 270 vitamin E 309

599

white adipose tissue 238–41, 239 insulin sensitivity 242 whole grain food products 306 women, pattern of fat distribution 208, 209, 222 Xendos trial 301

Index compiled by John Holmes