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Herausgeber: John Wiley & Sons
Kategorie: Fachliteratur
Sprache: Englisch

Beschreibung

Now in its fifth edition, the Textbook of Diabetes has established itself as the modern, well-illustrated, international guide to diabetes. Sensibly organized and easy to navigate, with exceptional illustrations, the Textbook hosts an unrivalled blend of clinical and scientific content. Highly-experienced editors from across the globe assemble an outstanding set of international contributors who provide insight on new developments in diabetes care and information on the latest treatment modalities used around the world. The fifth edition features an array of brand new chapters, on topics including:

Ischaemic Heart Disease
Glucagon in Islet Regulation
Microbiome and Diabetes
Diabetes and Non-Alcoholic Fatty Liver Disease
Diabetes and Cancer
End of Life Care in Diabetes

as well as a new section on Psychosocial aspects of diabetes.

In addition, all existing chapters are fully revised with the very latest developments, including the most recent guidelines from the ADA, EASD, DUK and NICE.

Includes free access to the Wiley Digital Edition providing search across the book, the full reference list with web links, illustrations and photographs, and post-publication updates

Via the companion website, readers can access a host of additional online materials such as:

200 interactive MCQ's to allow readers to self-assess their clinical knowledge
every figure from the book, available to download into presentations
fully searchable chapter pdfs

Once again, Textbook of Diabetes provides endocrinologists and diabetologists with a fresh, comprehensive and multi-media clinical resource to consult time and time again.

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We dedicate this book to all people living with diabetes and the healthcare professionals who look after them. We would also like to dedicate this book to our families without whose support and encouragement the book would never have been finished.

Textbook of Diabetes

EDITED BY

RICHARD I.G. HOLT MA, MB BChir, PhD, FRCP, FHEA

Professor in Diabetes & Endocrinology Human Development and Health Academic Unit University of Southampton Faculty of Medicine Southampton, UK

CLIVE S. COCKRAM MBBS, BSc, MD (Lond), FRCP, FRACP, FHKAM (Med)

Emeritus Professor of Medicine Chinese University of Hong Kong Hong Kong SAR People’s Republic of China

ALLAN FLYVBJERG MD, DMSc

CEO at Steno Diabetes Center Copenhagen (SDCC) The Capital Region of Denmark Professor of Clinical Endocrinology Faculty of Health and Medical Sciences University of Copenhagen, Copenhagen, Denmark

BARRY J. GOLDSTEIN MD, PhD, FACP, FACE

Vice President and Global Therapeutic Area Head Cardiovascular, Metabolic, Endocrine and Renal Medical and Scientific Affairs Covance Clinical Development Services Princeton, NJ, USA

FIFTH EDITION

Previous editions: 1991, 1997, 2003, 2010

Registered office: John Wiley & Sons, Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK

Editorial offices: 9600 Garsington Road, Oxford, OX4 2DQ, UK The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK 111 River Street, Hoboken, NJ 07030-5774, USA

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The right of the author to be identified as the author of this work has been asserted in accordance with the UK Copyright, Designs and Patents Act 1988.

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by the UK Copyright, Designs and Patents Act 1988, without the prior permission of the publisher.

Designations used by companies to distinguish their products are often claimed as trademarks. All brand names and product names used in this book are trade names, service marks, trademarks or registered trademarks of their respective owners. The publisher is not associated with any product or vendor mentioned in this book. It is sold on the understanding that the publisher is not engaged in rendering professional services. If professional advice or other expert assistance is required, the services of a competent professional should be sought.

The contents of this work are intended to further general scientific research, understanding, and discussion only and are not intended and should not be relied upon as recommending or promoting a specific method, diagnosis, or treatment by health science practitioners for any particular patient. The publisher and the author make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of fitness for a particular purpose. In view of ongoing research, equipment modifications, changes in governmental regulations, and the constant flow of information relating to the use of medicines, equipment, and devices, the reader is urged to review and evaluate the information provided in the package insert or instructions for each medicine, equipment, or device for, among other things, any changes in the instructions or indication of usage and for added warnings and precautions. Readers should consult with a specialist where appropriate. The fact that an organization or Website is referred to in this work as a citation and/or a potential source of further information does not mean that the author or the publisher endorses the information the organization or Website may provide or recommendations it may make. Further, readers should be aware that Internet Websites listed in this work may have changed or disappeared between when this work was written and when it is read. No warranty may be created or extended by any promotional statements for this work. Neither the publisher nor the author shall be liable for any damages arising herefrom.

Library of Congress Cataloging-in-Publication Data

Names: Holt, Richard I. G., editor. | Cockram, Clive S., editor. | Flyvbjerg, Allan, editor. | Goldstein, Barry J., editor. Title: Textbook of diabetes / edited by Richard I.G. Holt, Clive S. Cockram, Allan Flyvbjerg, Barry J. Goldstein. Other titles: Textbook of diabetes (Pickup) Description: Fifth edition. | Chichester, West Sussex, UK; Hoboken, NJ : Wiley-Blackwell, 2016. | Preceded by Textbook of diabetes / edited by Richard I.G. Holt … [et al.]. 4th ed. 2010. | Includes bibliographical references and index. Identifiers: LCCN 2016014428| ISBN 9781118912027 (cloth) | ISBN 9781118924860 (epub) | ISBN 9781118924877 (Adobe PDF) Subjects: | MESH: Diabetes Mellitus Classification: LCC RC660 | NLM WK 810 | DDC 616.4/62–dc23 LC record available at https://lccn.loc.gov/2016014428

A catalogue record for this book is available from the British Library.

Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books.

Cover images: Left inset: Gettyimages/AndreyPopov; Right inset: Gettyimages/SCIEPRO

List of Contributors

Preface to the Fifth Edition

List of Abbreviations

About the Companion Website and Companion Digital Edition

Part 1 Diabetes in its Historical and Social Context

1 The History of Diabetes Mellitus

Ancient times

The 17th and 18th centuries

The 19th century

The 20th century

Causes and natural history of diabetes

Chronic diabetic complications

Physiology

Management of diabetes

Diabetic ketoacidosis

Diabetic pregnancy

List of Tables

Chapter 1

Table 1.1

Table 1.2

Table 1.3

Table 1.4

Chapter 2

Table 2.1

Table 2.2

Table 2.3

Chapter 4

Table 4.1

Table 4.2

Table 4.3

Table 4.4

Table 4.5

Table 4.6

Table 4.7

Table 4.8

Table 4.9

Chapter 5

Table 5.1

Table 5.2

Table 5.3

Chapter 6

Table 6.1

Chapter 10

Table 10.1

Table 10.2

Table 10.3

Chapter 14

Table 14.1

Table 14.2

Table 14.3

Chapter 16

Table 16.1

Table 16.2

Table 16.3

Table 16.4

Table 16.5

Chapter 18

Table 18.1

Table 18.2

Table 18.3

Table 18.4

Table 18.5

Chapter 19

Table 19.1

Table 19.2

Table 19.3

Chapter 20

Table 20.1

Table 20.2

Table 20.3

Table 20.4

Table 20.5

Table 20.6

Chapter 21

Table 21.1

Table 21.2

Table 21.3

Table 21.4

Table 21.5

Table 21.6

Chapter 22

Table 22.1

Chapter 23

Table 23.1

Table 23.2

Chapter 24

Table 24.1

Table 24.2

Chapter 25

Table 25.1

Table 25.2

Chapter 26

Table 26.1

Table 26.2

Table 26.3

Table 26.4

Table 26.5

Table 26.6

Table 26.7

Chapter 27

Table 27.1

Table 27.2

Table 27.3

Chapter 28

Table 28.1

Table 28.2

Table 28.3

Table 28.4

Table 28.5

Chapter 29

Table 29.1

Table 29.2

Chapter 31

Table 31.1

Table 31.2

Table 31.3

Table 31.4

Table 31.5

Table 31.6

Table 31.7

Table 31.8

Table 31.9

Table 31.10

Table 31.11

Table 31.12

Table 31.13

Table 31.14

Chapter 32

Table 32.1

Chapter 33

Table 33.1

Table 33.2

Chapter 34

Table 34.1

Table 34.2

Table 34.3

Table 34.4

Table 34.5

Chapter 35

Table 35.1

Table 35.2

Table 35.3

Table 35.4

Table 35.5

Table 35.6

Chapter 36

Table 36.1

Chapter 38

Table 38.1

Table 38.2

Chapter 39

Table 39.1

Table 39.2

Table 39.3

Table 39.4

Chapter 40

Table 40.1

Table 40.2

Table 40.3

Table 40.4

Table 40.5

Table 40.6

Table 40.7

Chapter 42

Table 42.1

Table 42.2

Table 42.3

Table 42.4

Chapter 43

Table 43.1

Chapter 45

Table 45.1

Table 45.2

Table 45.3

Chapter 46

Table 46.1

Table 46.2

Table 46.3

Chapter 47

Table 47.1

Table 47.2

Chapter 48

Table 48.1

Table 48.2

Table 48.3

Table 48.4

Table 48.5

Chapter 49

Table 49.1

Table 49.2

Chapter 50

Table 50.1

Table 50.2

Table 50.3

Chapter 51

Table 51.1

Table 51.2

Table 51.3

Table 51.4

Table 51.5

Table 51.6

Table 51.7

Table 51.8

Table 51.9

Chapter 52

Table 52.1

Chapter 53

Table 53.1

Table 53.2

Chapter 54

Table 54.1

Table 54.2

Chapter 57

Table 57.1

Table 57.2

Table 57.3

Table 57.4

Table 57.5

Table 57.6

Chapter 58

Table 58.1

Table 58.2

Table 58.3

Table 58.4

Table 58.5

Table 58.6

Table 58.7

Chapter 59

Table 59.1

Table 59.2

Table 59.3

Table 59.4

Table 59.5

Chapter 60

Table 60.1

Chapter 61

Table 61.1

Table 61.2

Table 61.3

Table 61.4

Table 61.5

Table 61.6

Table 61.7

Table 61.8

Table 61.9

Table 61.10

Chapter 62

Table 62.1

Table 62.2

Chapter 63

Table 63.1

Table 63.2

Table 63.3

Table 63.4

Chapter 67

Table 67.1

Table 67.2

Chapter 69

Table 69.1

Chapter 70

Table 70.1

List of Illustrations

Chapter 1

Figure 1.1

The Ebers papyrus.

Figure 1.2

(a) Clinical description of diabetes by Aretaeus of Cappadocia (2nd century AD). Adapted from Papaspyros NS (1952)

The History of Diabetes Mellitus

. (b) Sushrut (Susrata), an Indian physician who wrote medical texts with Charak (Charuka) between 500 BC and 400 BC.

Figure 1.3

Frontispiece and opening page of the paper by Matthew Dobson (1776), in which he described the sweet taste of both urine and serum from a person with diabetes [2].

Figure 1.4

Extract from John Rollo's account of two cases of diabetes (1797). Rollo was well aware of the problem of non-adherence. Note that “the patient was strongly remonstrated with, and told of the consequences of repeated deviations.”

Figure 1.5

Claude Bernard (1813–1878).

Figure 1.6

Oskar Minkowski (1858–1931).

Figure 1.7

Paul Langerhans (1847–1888).

Figure 1.8

Pictures from

Jaeger's Atlas of the Optic Fundus

, 1869 [14]. Top left: Bright's disease. Top right: Jaeger's retinitis hemorrhagica is now recognized as central retinal vein occlusion. Bottom left: A 22-year-old man with suspected diabetes. Bottom right: Central retinal artery occlusion.

Figure 1.9

Elliott P. Joslin (1869–1962), arguably the most famous diabetes specialist of the 20th century and the frontispiece to his 1916 textbook [22].

Figure 1.10

(a) Georg Zuelzer (1840–1949) and (b) the title page from his paper (1907) reporting that a pancreatic extract reduced glycosuria in pancreatectomized dogs [23] (top). (c) Nicolas Paulesco (1869–1931).

Figure 1.11

The discoverers of insulin. Clockwise from top left: Frederick G. Banting (1891–1941); James B. Collip (1892–1965); J.J.R. Macleod (1876–1935); and Charles H. Best (1899–1978).

Figure 1.12

Leonard Thompson, the first person to receive insulin, in January 1922.

Figure 1.13

Nodular glomerulosclerosis. Figure from the paper by Kimmelstiel and Wilson, 1936 [41].

Figure 1.14

Knud Lundbæk (1912–1995).

Figure 1.15

Frederick Sanger (1918–2013) and Dorothy Hodgkin, née Crowfoot (1910–1994).

Figure 1.16

Solomon Berson and Rosalyn Yalow.

Figure 1.17

Hans Christian Hagedorn (1888–1971) from the Hagedorn Medal.

Figure 1.18

Robert Turner (1939–1999), instigator of the UKPDS, the first study to show that good control of blood glucose and blood pressure was beneficial in type 2 diabetes.

Figure 1.19

Jørgen Pedersen (1914–1978) and Ivo Drury (1905–1988), pioneers, with Priscilla White (1900–1989), in the management of pregnancy in women with type 1 diabetes.

Figure 1.20

Ernesto Roma (1887–1978) and (right) Robin D. Lawrence (1892–1968).

Chapter 3

Figure 3.1

Incidence rate of type 1 diabetes per 100,000/year in Swedish males and females by age during 1983–1998. Source: Pundziute-Lyckå et al. 2002 [11]. Reproduced with permission of Springer.

Figure 3.2

Geographic variation in childhood onset type 1 diabetes incidence rates, 1990–1999. Note that most registries were not nationwide and that several countries display within-country variation. Source: The DIAMOND Project Group 2006 [5]. Reproduced with permission of John Wiley & Sons.

Figure 3.3

Long-term time trends in incidence rate of type 1 diabetes diagnosed before 15 years of age in Finland, Sweden, Norway, and Germany. Source: Data from Tuomilehto et al. 1999 [40], Harjutsalo et al. 2008 [7], Harjutsalo et al. 2013 [41], Hussen et al. 2013 [43], Joner & Søvik 1989 [163], Skrivarhaug 2014 [50], and Ehehalt et al. 2012 [44]. Finish data 1965–1996 are for age group 1–14 years, and thereafter 0–14 years (and data from 1997 to 2005 are averages for three calendar years); all other data are observed incidence per calendar year without smoothing of curves. Nordic data are from nation-wide registries and German data are from former Eastern Germany (GDR) and the Baden-Württemberg registry 1987–2006.

Figure 3.4

Incidence trends in type 1 diabetes among ethnic groups in Sweden and Israel (left panel) and Yorkshire, UK (right panel). Source: Data from Hussen et al. 2013 [43] and Harron et al. 2011 [47]. Note that the data from Israel shown here are for ages below 15 years, as for the Swedish and UK data. R.C. Parslow and O. Blumenfeld kindly provided raw data for UK and Israel, respectively.

Figure 3.5

Seasonal variation in diagnosis of type 1 diabetes among >22,000 children diagnosed 1989–1998 in European centers, by age at onset.

Age (years) at first insulin injection. Source: Green and Patterson 2001 [26]. Reproduced with permission of Springer.

Figure 3.6

Diabetes-free survival in non-diabetic monozygotic twins whose co-twin had type 1 diabetes, after several years of follow-up. Dotted lines represent 95% confidence intervals. Source: Redondo et al. 2001 [75]. Reproduced with permission of Springer.

Figure 3.7

Standardized mortality ratios (SMRs) for people followed from diagnosis of childhood-onset type 1 diabetes. Data are from different studies, summarized by Morgan et al. 2015 [143]. Only studies with at least 10 observed deaths are shown. An SMR of 1.0 means a mortality rate among people with type 1 diabetes that is equal to that in the background population for the same age, sex, and calendar period. Studies were sorted by the earliest year of diagnosis of type 1 diabetes, and secondarily by SMR. Note that there were differences in duration of follow-up and other minor methodological differences between studies.

Chapter 4

Figure 4.1

Risk factors in the development of T2DM. HDL, high-density lipoprotein cholesterol; PCOS, polycystic ovarian syndrome; TG, triglycerides.

Figure 4.2

Diabetes epidemiological model. Factors directly affecting the prevalence of diabetes included in the present analysis. Source: Adapted from Colagiuri et al. 2005 [49]

Figure 4.3

Global prevalence of diabetes. Source: Adapted from

IDF Diabetes Atlas

, International Diabetes Federation 2015 [1], Chapter 3, Map 3.1.

Figure 4.4

Changes in prevalence of diabetes among Chinese adults aged 35–64 years. Source: Data from the 1994 Chinese National Survey and the 2000–2001 InterASIA study (Gu et al. 2003 [209]).

Chapter 5

Figure 5.1

Diagram illustrating the cyclical relationship between poverty and ill-health: poverty predisposes one to illness, and costs of illness in a system of fee-for-service care have the potential to impoverish households, further perpetuating poverty.

Chapter 6

Figure 6.1

Anatomy of the islet of Langerhans. (a) Mouse islet. The image shows a section through a mouse pancreas in which insulin and glucagon are identified by red and green immunofluorescence, respectively, demonstrating the typical β-cell core surrounded by a thin mantle of α cells. In mouse islets, β cells comprise ~80% of the endocrine cell mass. Scale bar is 10 μm. Source: image courtesy of C. Li, King's College London. (b) Human islet. The image shows a section through a human pancreas in which insulin and glucagon are identified by red and green immunofluorescence respectively, demonstrating the less organized structure of the human islet when compared with mouse islets. In human islets, β cells comprise ~50–60% of the endocrine cell mass. Scale bar is 10 μm. Source: image courtesy of V. Foot, King's College London. (c) Transmission electron micrograph of human islet cells. The image shows a transmission electron micrograph of several cells within a human islet. The two cells at the top with the electron-dense secretory granules surrounded by a clear halo are β cells. The cells in the lower part of the micrograph are α cells. Scale bar is 2 μm. Source: authors' unpublished data.

Figure 6.2

Intra-islet autocrine–paracrine interactions. The heterogeneous nature and complex anatomy of the islet permit numerous interactions between islet cells that are mediated by the release of biologically active molecules.

Figure 6.3

Structure of the human insulin gene. The coding region of the human insulin (INS) gene comprises three exons, which encode the signal peptide (SP), B chain, C-peptide, and A chain. The exons are separated by two introns (In1 and In2). Beyond the 5′ untranslated region (5′UT), upstream of the coding sequence, lies a hypervariable region in which three alleles (classes I, II and III) can be distinguished by their size.

Figure 6.4

The intracellular pathways of (pro)insulin biosynthesis, processing, and storage. The molecular folding of the proinsulin molecule, its conversion to insulin, and the subsequent arrangement of the insulin hexamers into a regular pattern are shown at the left. The time course of the various processes and the organelles involved are also shown.

Figure 6.5

Insulin biosynthesis and processing. Proinsulin is cleaved on the C-terminal side of two dipeptides, namely Arg

–Arg

(by prohormone convertase 3) and Lys

–Arg

(prohormone convertase 2). The cleavage dipeptides are liberated, so yielding the “split” proinsulin products and ultimately insulin and C-peptide.

Figure 6.6

Glucose-induced insulin secretion from islets of Langerhans. No stimulation is seen below a threshold value of ~5 mmol/L glucose. Potentiators amplify insulin secretion at stimulatory concentrations of glucose, but are ineffective at subthreshold glucose levels.

Figure 6.7

Glucose-induced insulin release

in vitro

. The image shows the pattern of glucose-induced insulin secretion from perfused pancreas, in response to an increase in the glucose concentration. An acute first phase, lasting a few minutes, is followed by a sustained second phase of secretion that persists for the duration of the high-glucose stimulus.

Figure 6.8

Intracellular mechanisms through which glucose stimulates insulin secretion. Glucose is metabolized within the β cell to generate ATP, which closes ATP-sensitive potassium channels in the cell membrane. This prevents potassium ions from leaving the cell, causing membrane depolarization, which in turn opens voltage-gated calcium channels in the membrane and allows calcium ions to enter the cell. The increase in cytosolic calcium initiates granule exocytosis. Sulfonylureas act downstream of glucose metabolism, by binding to the SUR1 component of the K

ATP

channel (inset). GLUT, glucose transporter.

Figure 6.9

Adenylate cyclase and the regulation of insulin secretion. Some receptor agonists (e.g. glucagon, glucagon-like peptide 1, pituitary adenylate cyclase activating polypeptide) bind to cell-surface receptors that are coupled to adenylate cyclase (AC) via the heterotrimeric GTP-binding protein Gs. Adenylate cyclase hydrolyzes ATP to generate adenosine 5′ cyclic monophosphate (cAMP), which activates protein kinase A (PKA) and exchange proteins activated by cAMP (EPACs). Both of these pathways potentiate glucose-stimulated insulin secretion. Glucose also activates adenylate cyclase, but increases in intracellular cyclic AMP levels in response to glucose are generally smaller than those obtained with receptor agonists. Some inhibitory agonists (e.g. norepinephrine, somatostatin) bind to receptors that are coupled to adenylate cyclase via the inhibitory GTP-binding protein G

, resulting in reduced adenylate cyclase activity and a decrease in intracellular cAMP.

Figure 6.10

Phospholipase C and the regulation of insulin secretion. Some receptor agonists (e.g. acetylcholine, cholecystokinin) bind to cell-surface receptors that are coupled to phospholipase C (PLC) via the heterotrimeric GTP-binding protein G

. Phospholipase C hydrolyzes phosphatidylinositol bisphosphate (PIP

), an integral component of the membrane, to generate inositol 1,4,5-trisphosphate (IP

) and diacylglycerol (DAG). IP

mobilizes calcium from the endoplasmic reticulum and DAG activates protein kinase C (PKC), both of which enhance insulin secretion. Nutrients also activate PLC in a calcium-dependent manner but the importance of IP

and DAG in nutrient-induced insulin secretion is uncertain.

Chapter 7

Figure 7.1

Islet development and anatomy. A simplified model of pancreatic islet–cell differentiation in the developing pancreas and the role of islet transcription factors during islet–cell development. Transcriptional factors such as neurogenin 3 (Ngn3) and pancreatic duodenal homeobox 1 (Pdx1) are critical for the endocrine cell fate determination, and aristaless-related homeobox (Arx) and forkhead box A2 (Foxa2) are important for the initial or terminal differentiation stages of α-cell differentiation, respectively. In mice and rats, the organization of the islet includes a mantle of α and δ cells on the periphery of the islet, surrounding a core of β cells. In humans, the major endocrine cell types are spread more diffusely throughout the islet and most β cells have contact with either α or δ cells.

Figure 7.2

Regulation of

Gcg

gene expression. IGF (insulin-like growth factor), other growth factors, nutrients, and insulin are stimulatory factors for

Gcg

expression. IGF, growth factors, and nutrients activate a GPCR/cAMP signaling that has multiple downstream effects including activation of PKA and subsequently CREB (cAMP response element-binding protein). cAMP either directly or indirectly (via EPAC) activates other transcription factors (beta-cat/TCF7L2, Pax6/MafB, or Foxa1 depending on whether the activation occurs in the intestine or pancreas) that bind to promoter regions of the

Gcg

gene. Additionally, insulin signaling is also upstream of these transcription factors and can stimulate transcription in both the pancreas and intestine.

Figure 7.3

Regulation of glucagon secretion. Neural (SNS stimulates and PNS inhibits), paracrine (insulin and somatostatin inhibit), autocrine (glucagon stimulates its own secretion), endocrine (GIP stimulates and GLP-1 inhibits), and nutrient (low glucose stimulates) factors all regulate glucagon secretion. ADP, adenosine diphosphate; ANS, autonomic nervous system; ATP, adenosine triphosphate; EPI, epinephrine; SNS, sympathetic nervous system; TCA, tricarboxylic acid cycle.

Figure 7.4

Glucagon GPCR signaling via PKA activates glycogenolysis (via inhibition of glycogen synthase; activation of phosphorylase kinase and glycogen phosphorylase) and inhibits glycolysis (via inhibition of fructose 2,6-bisphosphatase and pyruvate kinase) via regulation of major rate-limiting enzymes in these pathways. PKA also activates CREB, which increases transcription of Pck1 and G6PC, major enzymes regulating gluconeogenesis, and also FGF21, which activates several downstream genes that increase lipid oxidation and inhibit lipid synthesis.

Figure 7.5

Pharmacological targeting of glucagon signaling. Approaches to block glucagon action to suppress the elevated hepatic glucose production (HGP) seen in T2DM has been explored for decades. However, the additional effect of inhibiting fatty acid oxidation (FAO) and increasing triglyceride synthesis may limit this therapeutic target. Newer hybrid peptides that favor glucagon's ability to suppress feeding and increase energy expenditure combined with hypoglycemic agents (such as GLP-1 agonists) have potent effects on weight loss in preclinical models. BAT, brown adipose tissue; CNS, central nervous system.

Chapter 8

Figure 8.1

A linear diagram of the insulin receptor (IR) precursor protein showing the position of important modules in the α and β subunits including leucine-rich regions (L1 and L2), a cysteine-rich region (CR), disulfide bonds , the alternative IRA/IRB splice site that generates the short CT

IRA

or long CT

IRB

, a transmembrane region (TM), the furin cleavage site, the IRS binding motif (NPEpY), the kinase activation loop autophosphorylation sites, and C-terminal tyrosine phosphorylation sites (CT).

Figure 8.2

Diagram of the mature insulin receptor composed of two extracellular α-subunits and two transmembrane β-subunits. The juxtaposed α-subunit are labeled with either black or white (L1, CR, L2, Fn

1, Fn

2, Fn

3) symbols to outline the two α-subunit. The holoreceptor is stabilized extracellularly by disulfide bonds between cysteine residues (S–S) in the α and β subunits, and also by non-covalent interactions. Two regions within the α subunit contribute to insulin binding including L1•CR (and the extra 12 amino acids encoded by exon-11 in the B form of the insulin receptor) that binds the S1 site of insulin; and the junction between Fn

1 and Fn

2 that binds the S2 site of insulin. The β subunit contains the tyrosine kinase catalytic domain with an ATP binding site (Lys

1030

) and a number of tyrosine phosphorylation sites, including those in the juxtamembrane region (pY

972

), activation loop (pY

1158, 1162, 1163

), and C-terminal regions (gray box). A structure of the catalytic domain is shown. An inset shows the insulin structure with the position of some critical amino acids that compose the two binding surfaces (S1 and S2) that interact with the L1•CR•CT and Fn

1•Fn

2 regions of the insulin receptor, respectively. The A chain is shown in green and the B chain in blue, and some amino acids composing each binding site are shown as space-filling residues in red (S1) or orange (S2). The N- and C-terminal residues of each chain are labeled in black.

Figure 8.3

Alignments of IRS1 and IRS2 tyrosine phosphorylation sites relative to the N-terminal pleckstrin homology (PH) and phosphotyrosine-binding (PTB) domains. Conserved tyrosine phosphorylation sites—including their number in the human protein and the surrounding amino acid sequences—are color coded; white boxes indicates unique sites in IRS1 or IRS2. The relative position of serine/threonine phosphorylation sites in IRS1 or IRS2 revealed by MS/MS are indicated with red circles (•).

Figure 8.4

A canonical insulin/IGF signaling cascade. Two main branches propagate insulin signals generated via the IRS-proteins initiated by PI3K and GRB2•SOS. Activation of the receptors for insulin and IGF1 results in tyrosine phosphorylation of the IRS proteins, which bind PI3K and Grb2/SOS. The Grb2/SOS complex promotes GDP/GTP exchange on p21

ras

, which activates the ras→raf→MEK→ERK1/2 cascade. Activated ERK stimulates transcriptional activity by direct phosphorylation of ELK1 (ETS domain-containing protein) and by indirect phosphorylation of cFOS through MAPKAPK1 (MAPK-activated protein kinase-1). MAPKAP1 also phosphorylates other proteins, including S6 (ribosomal protein S6), NFκB, PP1, and MYT1 (myelin transcription factor 1). The activation of PI3K by recruitment to IRS1 or IRS2 produces PI3,4P

, and PI(3,4,5)P

(antagonized by the action of PTEN or SHIP2), which recruits PDK1 and AKT to the plasma membrane. AKT is activated upon phosphorylation at T308 by PDK1 and at S473 by mTORC2. mTORC1 is activated by Rheb

GTP

, which accumulates upon inhibition of the GAP (GTPase-activating protein) activity of the TSC1•TSC2 complex following AKT-mediated phosphorylation of TSC2. The S6K is primed through mTORC1-mediated phosphorylation. AKT phosphorylates many cellular proteins, inactivating PGC1α, p21

kip

, GSK3β, BAD, and AS160, and activating PDE3b and eNOS. AKT-mediated phosphorylation of forkhead proteins, including FOXO1, results in their sequestration in the cytoplasm, which inhibits their influence upon transcriptional activity. Insulin stimulates protein synthesis by altering the intrinsic activity or binding properties of key translation initiation and elongation factors (eIFs and eEFs, respectively) and also critical ribosomal proteins. Components of the translational machinery that are targets of insulin regulation include eIF2B, eIF4E, eEF1, eEF2, and the S6 ribosomal protein [215].

Figure 8.5

Schematic diagram of heterologous and feedback inhibition of insulin signaling mediated by Ser/Thr-phosphorylation and degradation of IRS1/IRS2. Various kinases in the insulin signaling cascade are implicated in this feedback mechanism, including PKB, mTOR, S6K, ERK, AKT, and atypical PKC isoforms. Other IRS kinases are activated by heterologous signals, including lipids, TNFα or other cytokines. Serine phosphorylation of IRS1 can recruit CRL7 ubiquitinylation (purple oval) complex to mediate degradation of IRSs through the 26S proteasome. Proinflammatory cytokines that cause insulin resistance also induce the expression of SOCS family members, which contain an N-terminal SH2 domain and a C-terminal SOCS box [216, 217]. SOCS1 or SOCS3 can target phosphotyrosine residues in IRS1 or IRS2 for ubiquitinylation and degradation, because the SOCS box associates with elongin BC-containing ubiquitin ligase E3 [218–220].

Figure 8.6

The integrative role of IRS2 signaling in pancreatic β-cell function. The diagram shows the relation between the IRS2 branch of the insulin signaling pathway and upstream and downstream mechanisms regulating β-cell growth and function. The production of PI(3,4,5)P

by the PI3K recruits the Ser/Thr-kinases PDK1 and AKT to the plasma membrane where AKT is activated by PDK1 and mTORC2-mediated phosphorylation. AKT phosphorylates many proteins that play important physiological roles in β cells including GSK3β (glycogen synthesis), the BAD•BCL2 heterodimer (apoptosis inhibition), TSC1/2 (protein synthesis and nutrient sensing), and FOXO (transcriptional regulation). Activation of GLP1→cAMP→PKA→CREB, glucose→Ca

→CRTC2 and calcineurin→NFAT induce IRS2 expression in β cells, revealing a mechanism that places β-cell growth, function, and survival under the control of glucose and incretins. Since insulin and IGF1R are constitutively active, IRS2 expression can act as the regulatory gateway to mTORC1, FOXO1, and p27

kip

. Together, this integrated pathway shows how signals known to promote β-cell and islet growth and function can be integrated by the IRS2 signaling cascade into a common pathway.

Chapter 10

Figure 10.1

Schematic presentation of the early natural history of T1DM divided into three different disease stages.

Figure 10.2

Incidence of the first islet autoantibody in relation to HLA-DQ genetic risk. In all four panels the red line represents IAA as the first β-cell autoantibody, the blue as GADA and the black simultaneously GADA and IAA. The Environmental Determinants of Diabetes in the Young (TEDDY) children in (a) were HLA-DQ2/8, in (b) HLA-DQ4/8, in (c) HLA-DQ8/8 and in (d) HLA-DQ 2/2. Source: Data from [12].

Figure 10.3

Putative genetic factors and proposed function for non-HLA type 1 diabetes genes determined by the Type 1 Diabetes Genetics Consortium.

Figure 10.4

Probability of progression to symptomatic T1DM in relation to number of β-cell autoantibodies analyzed from birth. Source: Data from [11].

Chapter 11

Figure 11.1

There are considerable overlaps between the phenotypes of type 1 and type 2 diabetes due to heterogeneous genetic and autoimmune etiologies. These include maturity-onset diabetes of the young (MODY), latent autoimmune diabetes in adults (LADA), and genetic variants affecting the insulin, amylin, and mitochondrial pathways. Other rare causes include fibrocalculous pancreatic diabetes and fulminant type 1 diabetes.

Figure 11.2

(a) The cascade of transcription factors involved in pancreatic development and also neogenesis, differentiation, and maturation of pancreatic β cells. Maturity-onset diabetes of the young (MODY) includes subtypes with mutations in transcription factors, namely MODY 1 with mutations of hepatic nuclear factor (HNF-4α); MODY 3, HNF-1α; MODY 4, insulin promotion factor (IDF-1); MODY 5, HNF-1β; MODY 6, NeuroD1 (neurogenic differentiation 1); and MODY 7, carboxyl ester lipase (CEL), and also glucokinase, which is the glucose sensor of the pancreatic β cells (MODY 2). There are also involvement and interactions of glucose transporter 2 (GLUT-2) and endodermal factor, including GATA and various important genes and transcription factor governing the differentiation and maturation of pancreatic islet and β cells. These include Pax genes family and genes encoding the homeodomain transcription factors Nkx 2.2 and Nkx 6.1. In the Southern Indian population, interaction of the NeuroD1, neurogenin-3 (Neurog3), and HNF-1α genes has been observed to have a combined effect in controlling islet cell development and insulin secreting, thus contributing to the overall glucose tolerance [106]. (b) The multiple steps involved in regulation of insulin secretion commencing with sensing of ambient blood glucose level by GLUT-2, glycolysis by glucokinase (GK), and ATP production by mitochondria. The generated ATP particles then close the potassium channel, leading to membrane depolarization and opening of calcium channels. The intracellular calcium influx is associated with translocation of insulin- and amylin-containing vesicles to the cellular surface for extracytosis. During these processes, transcription factors are also activated, resulting in insulin gene transcription and production to replenish the insulin-containing vesicles and maintain continuous insulin secretion.

Chapter 12

Figure 12.1

Mechanisms of nutrient stimulus–secretion coupling in the pancreatic β cell. Source: Newsholme et al. 2014 [14].

Figure 12.2

First- and second-phase plasma insulin response during hyperglycemic clamp in healthy individuals. Plasma glucose is acutely raised +125 mg/dL above baseline and maintained for the ensuing 2 h. Plasma insulin concentration is measured at regular intervals. Source: DeFronzo et al. 1979 [7]. Reproduced with permission of the American Physiological Society.

Figure 12.3

T2DM and glycemic trait-associated variants. The variants are represented by gene names here, which could indicate that the location is present either in the gene or in the vicinity of the gene. The white circle represents T2DM and the gene names in black in that circle represent variants only associated with T2DM. The overlapping circles indicate additional reporting associations for that variant. Source: Prasad and Groop 2015 [26] (this is an open-access article distributed under the Creative Commons Attribution License [CC BY]).

Figure 12.4

Associations between the genotypes of rs7903146 polymorphism in the

TCF7L2

gene with insulin secretion during a hyperglycemic clamp in 73 participants. Black lines, CC; red lines, CT and TT. AIR, acute insulin response. Arrow, administration of 5 g of arginine. The

values show the differences for the first- and second-phases of glucose-induced insulin secretion, first- and second-phases of GLP-1-induced insulin secretion, and acute insulin secretory response to arginine (AIR). Source: Schäfer et al. 2007 [31]. Reproduced with permission of Springer.

Figure 12.5

Relationship between the insulin secretion/insulin resistance index (ΔI/ΔG factored by the severity of insulin resistance measured with the euglycemic insulin clamp) and (a) the fasting plasma glucose (FPG) and (b) the 2-h plasma glucose (2-h PG) concentration (log–log scale). Source: Gastaldelli et al. 2004 [53], Figure 4. Reproduced with permission of Springer.

Figure 12.6

(a, b) Electron microscopy images showing the ER in (a) non-diabetic β cells and (b) T2DM β cells. The ER components (arrows) are scarcely visible in non-diabetic cells and more apparent in T2DM cells. Magnification ×10,000. IG, insulin granules; M, mitochondria; N, nucleus. (c) The ER density volume was significantly higher inT2DM β cells (red box) than non-diabetic β cells (yellow box).

<0.05 (Student's

-test for unpaired data). Source: Marchetti et al. 2007 [105], Figure 3. Reproduced with permission of Springer.

Figure 12.7

Mechanisms of β-cell damage in T2DM. Environmental factors and genetic backgrounds interact to activate stress processes that contribute to functional abnormalities and also progressive loss/dedifferentiation of β cells. Source: Adapted from Halban et al. 2014 [135].

Figure 12.8

β-Cell mass in the pancreas of people without (left) and with T2DM (right). Data are presented for individual values as scatterplots and mean values ± SD as columns. Although on average the β-cell mass is about 40% less in people with T2DM, there is some degree of overlap between the two groups. Source: Rahier et al. 2008 [138], Figure 2B. Reproduced with permission of John Wiley & Sons.

Figure 12.9

Insulin secretion rates (ISRs) during the hyperglycemic clamp studies related to the prevailing severity of insulin resistance (ISR

). On comparing control participants with healthy participants with a strong family history of T2DM (FH+), the first-phase ISR

is similar during the saline studies; with lipid infusion, the first-phase ISR

deteriorates in FH+ participants, whereas it increases in control participants. The second-phase ISR

is also reduced by lipid infusion in the FH+ group but is unchanged in healthy control.

<0.01 vs. saline; †

<0.05 vs. saline; ‡

<0.001 vs. control participants; ¶

<0.05 vs. control participants. Source: Adapted from Kashyap et al. 2003 [141].

Chapter 13

Figure 13.1

Basal and insulin-stimulated muscle and liver metabolism. In skeletal muscle (top left), insulin-stimulated glucose disposal is reduced in insulin-resistant non-obese elderly individuals and in those with type 2 diabetes mellitus (T2DM) compared with insulin-sensitive, lean, young individuals without diabetes. Both basal and insulin-stimulated ATP synthase flux show similar patterns (top middle), whereas intracellular triacylglycerols (TAGs) are frequently higher in insulin resistant persons (top right). In the liver, insulin-mediated suppression of glucose production is reduced in the insulin-resistant individuals (bottom left). ATP synthase flux is also lower only in persons with T2DM (bottom middle), whereas intracellular TAGs are markedly increased (bottom right). Source: data from Schmid et al. 2011 [138] and Szendroedi et al. 2007 [58] and 2009 [138].

Figure 13.2

Cellular mechanism of insulin resistance in human skeletal muscle. Augmented lipid availability, mainly increased fatty acid flux, raises the intramyocellular pool of the long-chain fatty acyl (CoA) pool, which fuels mitochondrial oxidation or serves to synthesize diacylglycerols (DAGs) for storage as triglyceride (TAG) lipid droplets. When fatty acid delivery and uptake exceed the rates of mitochondrial long-chain fatty acyl-CoA oxidation and incorporation of DAGs into TAGs, the intramyocellular DAG content transiently or chronically increases. Specific, mainly C

-containing, DAGs in the membrane and cytosol promote the activate novel protein kinase C (nPKC) isoforms. Translocation of the PKCθ isoform to the membrane leads to increased serine phosphorylation of insulin receptor substrate 1 (IRS-1) on critical sites (e.g. Ser 1101), which in turn blocks insulin-stimulated tyrosine phosphorylation of IRS-1 and the binding and activation of phosphatidylinositol 3-kinase (PI3K). This results in reduced recruitment of glucose transporter type 4 (GLUT-4) units to the membrane with impaired insulin-stimulated glucose uptake and phosphorylation to glucose-6-phosphate (G-6-P) and ultimately decreased insulin-stimulated glycogen synthesis. Source: Shulman 2014 [51]. Copyright © 2014 Massachusetts Medical Society. Reprinted with permission.

Figure 13.3

Cellular mechanism of insulin resistance in human liver. An imbalance of intrahepatocellular fluxes gives rise to hepatocellular diacylglyerols (DAGs), particularly when DAG synthesis, from both fatty acid re-esterification and

de novo

lipogenesis, exceeds the rates of mitochondrial oxidation of long-chain fatty acyl-coenzyme A (CoA) and/or the rates of DAG incorporation as triglycerides (TAGs) into lipid droplets. This activates the epsilon isoform of protein kinase C (PKCϵ), which likely phosphorylates the insulin receptor tyrosine kinase. In turn, phosphorylation of glycogen synthase kinase 3 (GSK3) phosphorylation increases, while that of forkhead box subgroup O (FOXO) decreases. This results in inhibition of glycogen synthase activity and thereby lower insulin-stimulated glycogen storage and in FOXO-mediated gene transcription of the gluconeogenic enzymes (e.g. phosphoenolpyruvate carboxykinase [PEP-CK] and G6P), with decreased insulin suppression of hepatic gluconeogenesis. Source: Shulman 2014 [51]. Copyright © 2014 Massachusetts Medical Society. Reprinted with permission.

Figure 13.4

Hypothesis of adaptation of hepatic energy metabolism in the pathogenesis of non-alcoholic fatty liver disease and progression of hepatic insulin resistance. (a) In states of obesity, increased fatty acid delivery upregulates hepatic mitochondrial oxidative capacity, which prevents excessive storage of triacylglycerols (TAGs) but promotes the accumulation of reactive oxygen species and lipid peroxides, which are scavenged by hepatic catalase activity. (b) During the development of non-alcoholic fatty liver disease (NAFLD), the efficiency of mitochondrial coupling fails, which accelerates the generation of hydrogen peroxide (H

) in the face of decreasing catalase activity. Finally, oxidative stress decreases mitochondrial biogenesis, but increases leakage of mitochondria and activates c-Jun N-terminal kinase (JNK), which drives cellular inflammation and progression to steatohepatitis (NASH). Source: Koliaki et al. 2015 [144]. Copyright 2015 Elsevier.

Figure 13.5

Hypothesis of macrophage-induced lipolysis in the pathogenesis of fasting hyperglycemia and insulin resistance. During the development of obesity, macrophage infiltration of white adipose tissue results in increased lipolysis by release of macrophage-derived cytokines such as interleukin-6. Increased rates of lipolysis lead to accelerated rates of hepatic gluconeogenesis by two mechanisms. (a) First, increased fatty acid delivery to the liver gives rise to hepatic acetyl-CoA levels, when its production through fat oxidation exceeds its rates of oxidation in the TCA cycle. This leads to increased pyruvate carboxylase activity. (b) Second, increased delivery of glycerol promotes its conversion to dihydroxyacetone (glyceraldehyde) 3-phosphate, which serves as precursor of glucose. Source: Shulman 2014 [51]. Copyright © 2014 Massachusetts Medical Society. Reprinted with permission.

Figure 13.6

Concept of the stepwise development of insulin resistance from skeletal muscle to atherogenic dyslipidemia and non-alcoholic fatty liver disease. In healthy, young, lean persons, selective insulin resistance in skeletal muscle results in diversion of ingested carbohydrates from muscle glycogen synthesis to the liver. Combined with compensatory hyperinsulinemia, this stimulates hepatic de novo lipogenesis, synthesis of triglycerides and secretion of very low-density lipoproteins (VLDL) resulting in hypertriglyceridemia and reduced plasma high-density lipoprotein (HDL) levels. Of note, even one bout of exercising is able to restore the abnormal pattern of energy storage after carbohydrate ingestion by stimulating glucose uptake and glycogen synthesis in muscle through insulin-independent adenosine 5′-monophosphate-activated protein kinase (AMPK) activation of glucose transporter 5 (GLUT-4) recruitment. Source: Shulman 2014 [51]. Copyright © 2014 Massachusetts Medical Society. Reprinted with permission.

Chapter 14

Figure 14.1

The spectrum of diabetes subgroups. The data are from the ANDIS project (All New Diabetics in Scania) (http://andis.ludc.med.lu.se) in April 2012, which at that time included 5800 individuals aged 0–100 years with newly diagnosed diabetes. The criteria used for diagnosis are as follows. T1DM: age at onset <35 years, C-peptide <0.2 nmol/L, and GAD antibodies >20; T1DM with relative insulin deficiency if C-peptide 0.2–0.6 nmol/L. T2DM: age at onset >35 years, C-peptide >0.6 nmol/L, GAD antibodies <10; T2DM with relative insulin deficiency C-peptide 0.2–0.6 nmol/L. LADA: age at onset >35 years, GAD antibodies >20; LADA light if GAD antibodies 10–20. The data clearly illustrate the difficulty in classifying persons with diabetes at diagnosis, with 19% unclassifiable. Source: Prasad RB, Groop L. Genetics of type 2 diabetes—Pitfalls and possibilities.

Genes

2015;

:87–123 (this is an open-access article distributed under the Creative Commons Attribution License [CC BY]).

Figure 14.2

T2DM risk variants. The

-axis shows the chromosomal location, the

-axis shows the effect sizes, and the

-axis shows the year of discovery. One risk variant was reported in 1998, two in 2002, to a total of 153 T2DM variants that we have today. Source: Prasad RB, Groop L. Genetics of type 2 diabetes—Pitfalls and possibilities.

Genes

2015;

:87–123 (this is an open-access article distributed under the Creative Commons Attribution License [CC BY]).

Figure 14.3

T2DM and glycemic trait-associated variants. The variants are represented by gene names here, which could indicate that the location is present either in the gene or in the vicinity of the gene. The black circle represents T2DM, and the gene names in black in this represent variants associated only with T2DM. The overlapping circles indicate additional reporting associations for that variant; for instance,

TCF7L2

KCNQ1

MTNR1B

, etc., are associated with T2DM and also with β-cell dysfunction. An ADCY5 variant is associated with 2-h insulin adjusted for 2-h glucose, 2-h glucose/T2DM (in brown) ***Variants in TMEM163 are also associated with fasting insulin,

TCF7L2

, associated with fasting and 2-h glucose, and

MADD

variants, associated with fasting proinsulin, fasting glucose and HOMA-B. Source: Prasad RB, Groop L. Genetics of type 2 diabetes—Pitfalls and possibilities.

Genes

2015;

:87–123 (this is an open-access article distributed under the Creative Commons Attribution License [CC BY]).

Chapter 15

Figure 15.1

Insulin dose–response curves for glucose production and utilization in individuals without diabetes. Source: Adapted from Vella A.

Diabetologia

2002;

:1410–1415. Reproduced with permission from Springer-Verlag.

Figure 15.2

In an experiment in otherwise healthy volunteers, a non-diabetic postprandial insulin profile coupled with postprandial glucagon suppression results in a normal postprandial glucose profile (a). In the same individuals, absent postprandial glucagon suppression in the presence of a non-diabetic postprandial insulin profile resulted in a minimal increase in postprandial glucose (b). On the other hand, a diabetic insulin profile produced glucose intolerance (c), which was markedly worsened by the absence of postprandial glucagon suppression (d).

Chapter 16

Figure 16.1

Contribution of five body mass index (BMI) categories to the overall prevalence of diabetes. National Health and Nutrition Examination Survey (NHANES) samples of 1976–1980 and 1999–2004 were compared. Source: Gregg et al. 2007 [7]. Copyright 2007 Elsevier.

Figure 16.2

Hyperbolic relation between β-cell function and insulin sensitivity. IGT, impaired glucose tolerance; NGT, normal glucose tolerance; T2DM, type 2 diabetes mellitus. Source: Stumvoll M, et al. Type 2 diabetes: Principles of pathogenesis and therapy.

Lancet

2005;

365

Figure 16.3

Secretory products from adipose tissue and functional relationship. SNS: sympathetic nervous system. Source: Lafontan M. Fat cells: Afferent and efferent messages define new approaches to treat obesity.

Annu Rev Pharmacol Toxicol

2005;

:119–146. Reproduced with permission from Annual Reviews.

Figure 16.4

Potential cellular mechanisms for inflammation and development of insulin resistance. AP-1, activator protein 1; ER, endoplasmic reticulum; IKK, Iκ kinase; IL, interleukin; IRS, insulin receptor substrate; JNK, c-Jun N-terminal kinase; NF-κB, nuclear transcription factor κB; PKC, protein kinase C; ROS, reactive oxygen species; TLR, toll-like receptor; TNFR, tumor necrosis factor receptor; TZD, thiazolidinedione. Source: Shoelson and Lee 2006 [55]. Reproduced with permission from the American Society for Clinical Investigation.

Figure 16.5

Nutrition and obesity-induced inflammation and development of systemic insulin resistance. Source: De Luca C, Olefsky JM. Stressed out about obesity and insulin resistance.

Nat Med

2006;

:41–42. Reproduced with permission from Nature Publishing Group.

Chapter 17

Figure 17.1

A synergistic relationship between the intestinal microbiome and host provides a number of benefits, including (1) competitive exclusion of pathogenic strains, (2) energy harvest, (3) promotion of barrier integrity, and (4) immune education. Source: Modified from Cox et al. 2014 [11]. Copyright 2014 Elsevier.

Figure 17.2

Components of the intestinal microbiota (namely lipopolysaccharide, LPS) have the potential to activate innate immune pathways. Cross-talk between TLR4 and insulin signaling pathways provide a mechanism linking the intestinal microbiota to insulin resistance.

Figure 17.3

Short-chain fatty acids (SCFAs) are produced during microbial fermentation of non-digestible dietary starches. SCFA signaling via G protein-coupled receptors (GPRs) can regulate incretin signaling, namely glucagon-like peptide 1 (GLP-1) and polypeptide YY (PYY), with downstream effects on glycemic control.

Figure 17.4

The intestinal microbiome influences the composition of the bile acid pool and metabolites. Bile acid signaling through the farnesoid X receptor (FXR) and the G protein-coupled receptor TRG5 pathways can effect transcriptional regulation of various metabolic pathways. Regulation of other signaling pathways can also contribute to alterations in glycemic control.

Chapter 18

Figure 18.1

Clinical subtypes of monogenic β-cell diabetes. To convert plasma glucose measurements to mg/dL multiply by 18. ABCC8, ATP binding cassette subfamily C;

GCK

, glucokinase gene; HNF, hepatocyte nuclear factor;

KCNJ11

, potassium inwardly rectifying channel, subfamily J, member 11 gene; OGTT, oral glucose tolerance test.

Figure 18.2