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Epidemiology of Pediatric and Adolescent Diabetes, Notas de estudo de Enfermagem

Epidemiology of Pediatric and Adolescent Diabetes

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2011

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Baixe Epidemiology of Pediatric and Adolescent Diabetes e outras Notas de estudo em PDF para Enfermagem, somente na Docsity! informa [iai Epidemiology of Pediatric and Adolescent Diabetes Informa Healthcare USA, Inc. 52 Vanderbilt Avenue New York, NY 10017 # 2008 by Informa Healthcare USA, Inc. Informa Healthcare is an Informa business No claim to original U.S. Government works Printed in the United States of America on acid-free paper 10 9 8 7 6 5 4 3 2 1 International Standard Book Number-10: 1-4200-4797-3 (Hardcover) International Standard Book Number-13: 978-1-4200-4797-4 (Hardcover) This book contains information obtained from authentic and highly regarded sources. Reprinted material is quoted with permission, and sources are indicated. A wide variety of references are listed. Reasonable efforts have been made to publish reliable data and information, but the author and the publisher cannot assume responsibility for the validity of all materials or for the conse- quence of their use. No part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, please access www. copyright.com (http://www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC) 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Library of Congress Cataloging-in-Publication Data Epidemiology of Pediatric and Adolescent Diabetes / edited by Dana Dabelea, Georgeanna J. Klingensmith. p. ; cm. Includes bibliographical references and index. ISBN-13: 978-1-4200-4797-4 (hardcover : alk. paper) ISBN-10: 1-4200-4797-3 (hardcover : alk. paper) 1. Diabetes in adolescence—Epidemiology. 2. Diabetes in children—Epidemiology. I. Dabelea, Dana. II. Klingensmith, Georgeanna J. [DNLM: 1. Diabetes Mellitus, Type 1. 2. Adolescent. 3. Child. 4. Diabetes Mellitus, Type 1—epidemiology. 5. Diabetes Mellitus, Type 2—epidemiology. 6. Diabetes Mellitus, Type 2. 7. Risk Factors. WK 810 E642 2008] RJ420.D5E65 2008 618.920462—dc22 2007039134 For Corporate Sales and Reprint Permissions call 212-520-2700 or write to: Sales Department, 52 Vanderbilt Avenue, 16th floor, New York, NY 10017. Visit the Informa Web site at www.informa.com and the Informa Healthcare Web site at www.informahealthcare.com We would like to dedicate this book to all youth with diabetes, their loving and supportive families, around the world. We would like to express our gratitude to our contributors who have written comprehensive, up-to-date, highly informative chapters. Finally, we remain indebted to our own, always supportive, families. Dana Dabelea and Georgeanna J. Klingensmith Contents Preface . . . . v Contributors . . . . ix 1. Definition, Diagnosis, and Classification of Diabetes in Youth 1 Nancy A. Crimmins and Lawrence M. Dolan 2. Descriptive Epidemiology of Type 1 Diabetes in Youth: Incidence, Mortality, Prevalence, and Secular Trends 21 Anders Green 3. Genetic Epidemiology of Type 1 Diabetes 35 George S. Eisenbarth and Theresa A. Aly 4. Early-Life Diet and Risk of Type 1 Diabetes 49 Melissa D. Simpson and Jill M. Norris 5. Environmental Determinants: The Role of Viruses and Standard of Hygiene 63 Mikael Knip and Heikki Hy€oty 6. Tempo and Type 1 Diabetes: The Accelerator Hypothesis 85 Terence J. Wilkin 7. Epidemiology of Type 2 Diabetes in Children and Adolescents 103 Kristen Nadeau and Dana Dabelea 8. Obesity and T2DM in Youth 125 Ram Weiss and Sonia Caprio 9. Insulin Resistance and Insulin Secretion in the Pathophysiology of Youth Type 2 Diabetes 139 Fida Bacha and Silva Arslanian 10. High and Low Birth Weights as Risk Factors for Diabetes 157 Rachel Pessah, Lois Jovanovic, and David J. Pettitt vii 11. Monogenic Forms of Diabetes in the Young 165 Martine Vaxillaire and Philippe Froguel 12. Natural Evolution, Prediction, and Prevention of Type 1 Diabetes in Youth 185 Craig E. Taplin and Jennifer M. Barker 13. Prevention and Screening for Type 2 Diabetes in Youth 201 Phil Zeitler and Orit Pinhas-Hamiel 14. Chronic Complications of Childhood Diabetes 217 Kim C. Donaghue, Fauzia Mohsin, and Monique L. Stone 15. Cardiovascular Disease Risk Factors 235 R. Paul Wadwa, Elaine M. Urbina, and Stephen R. Daniels 16. Epidemiology of Acute Complications in Youth: Diabetic Ketoacidosis and Hypoglycemia 251 Arleta Rewers and Georgeanna J. Klingensmith 17. Dietary Factors in Youth with Diabetes 277 Elizabeth J. Mayer-Davis and Franziska K. Bishop 18. Health Care Cost and Utilization 293 Reena Oza-Frank, Ping Zhang, Giuseppina Imperatore, and K.M. Venkat Narayan 19. Treatment Patterns in Youth with Diabetes 303 Harvey K. Chiu and Catherine Pihoker 20. Psychosocial Issues in Childhood Diabetes 323 Barbara J. Anderson Index . . . . 339 viii Contents Contributors Theresa A. Aly Barbara Davis Center for Childhood Diabetes and Human Medical Genetics Program, University of Colorado at Denver and Health Sciences Center, Aurora, Colorado, U.S.A. Barbara J. Anderson Department of Pediatrics, Baylor College of Medicine, Houston, Texas, U.S.A. Silva Arslanian Division of Weight Management andWellness, Children’s Hospital of Pittsburgh, Pittsburgh, Pennsylvania, U.S.A. Fida Bacha Division of Pediatric Endocrinology, Metabolism and Diabetes Mellitus, and Division of Weight Management and Wellness, Children’s Hospital of Pittsburgh, Pittsburgh, Pennsylvania, U.S.A. Jennifer M. Barker Barbara Davis Center for Childhood Diabetes, Aurora, Colorado, U.S.A. Franziska K. Bishop Barbara Davis Center for Childhood Diabetes, University of Colorado at Denver and Health Sciences Center, Aurora, Colorado, U.S.A. Sonia Caprio Department of Pediatrics and the Children’s General Clinical Research Center, Yale University School of Medicine, New Haven, Connecticut, U.S.A. Harvey K. Chiu Division of Endocrinology, Children’s Hospital and Regional Medical Center, University of Washington, Seattle, Washington, U.S.A. Nancy A. Crimmins Department of Pediatrics, Cincinnati Children’s Hospital Medical Center and University of Cincinnati School of Medicine, Cincinnati, Ohio, U.S.A. Dana Dabelea Department of Preventive Medicine and Biometrics, University of Colorado at Denver, Denver, Colorado, U.S.A. Stephen R. Daniels Department of Pediatrics, The Children’s Hospital, University of Colorado School of Medicine, Denver, Colorado, U.S.A. Lawrence M. Dolan Department of Pediatrics, Cincinnati Children’s Hospital Medical Center and University of Cincinnati School of Medicine, Cincinnati, Ohio, U.S.A. Kim C. Donaghue Institute of Endocrinology and Diabetes, The Children’s Hospital at Westmead, University of Sydney, Westmead, Australia ix 1 Definition, Diagnosis, and Classification of Diabetes in Youth Nancy A. Crimmins and Lawrence M. Dolan Department of Pediatrics, Cincinnati Children’s Hospital Medical Center and University of Cincinnati School of Medicine, Cincinnati, Ohio, U.S.A. HISTORICAL PERSPECTIVE: EARLIEST DESCRIPTIONS TO 1965 Early Descriptions of Diabetes Ancient records up to 3000 years old describe a disease in youth that was sudden in onset, resulted in acute metabolic decompensation, and culminated in death. Although this clinical picture described millennia ago was likely that of diabetes, the first accepted description of diabetes as a disorder associated with increased urine output came from ancient Egypt (the Ebers papyrus) around 1550 B.C. It was not until the second century B.C. that the term ‘‘diabetes’’ was used. Credit for coining ‘‘diabetes’’ is given to Demetrios of Apamaia who derived the term from the Greek word diabeinein, meaning ‘‘siphon’’ or ‘‘pass through.’’ Aretaeus of Cappadocia reported the first clinical description of the disease in the second century A.D. using the term ‘‘diabetes.’’ Focusing on the polyuric aspect of diabetes, he wrote of the ‘‘melting down of flesh and limbs into urine’’ and stated that the disease was infrequent. Diabetes was recognized in Indian medicine in the fifth and sixth centuries as a disorder associated with the production of sweet urine that attracted insects. The term diabetes did not appear in an English text until 1425. In 1674, Thomas Willis, physician to England’s King Charles II, became the first European to discover the sweetness in the urine of those afflicted with dia- betes. Perhaps the first English diabetes epidemiologist, Thomas, also noted the importance of lifestyle in the development of diabetes. He noted that the preva- lence of diabetes was increasing because of ‘‘good fellowship and gusling down chiefly of unalloyed wine.’’ A century later, Matthew Dobson proved that the sweetness in urine was caused by sugar and was associated with sugar in the blood. John Rollo was the first person to coin the term ‘‘diabetes mellitus’’ (mellitus from Latin for honey) and distinguished this disease from another disease of polyuria, ‘‘diabetes insipidus’’ (insipidus from Latin for tasteless) around the turn of the 18th century. Early Recognition of Two Distinct Phenotypes of Diabetes As early as the fifth and sixth centuries, Indian descriptions of the diabetes rec- ognized two phenotypes: one that appeared in older, fatter people, and the other in thin people, which was more acute in presentation and quickly led to death. It was not until 1866 that this concept emerged again in a text written by George Harley. He wrote, ‘‘. . .I differ from my predecessors and contemporaries in believing that there are at least two different forms of the disease, requiring diametrically opposite lines of treatment. . . . one of which might be named Diabetes from excessive formation; the other Diabetes from defective assimilation (malnutrition)’’ (1). Etienne 1 Lancereaux, a French physician who made significant contributions in under- standing the clinical spectrum of diabetes, is given much of the credit for sug- gesting a basis for the modern classification of diabetes. He proposed that there were two fundamental forms of presentation: ‘‘thin or pancreatic diabetes’’ and ‘‘fat or constitutional diabetes’’ (2). With the discovery and subsequent use of insulin as a therapy for diabetes, clinicians recognized insulin responsive or insulin resistant as the two main forms of diabetes. C. Wesley Dupertuis, a physical anthropologist, first suggested the terms ‘‘group I and group II diabetes’’ on the basis of the two main phenotypes of the disease in the 1940s; however, this clas- sification was not widely embraced by the scientific community at that time (3). MODERN PERSPECTIVE: 1965--2003 Definition of Diabetes Mellitus Through the extraordinary efforts of great scientists in the 19th and 20th centuries (too vast to cover in this chapter), we now have a better understanding of the physiologic basis of diabetes mellitus. Diabetes mellitus is defined as inappropriate hyperglycemia resulting from a deficiency of insulin production, insulin action, or both with derangements in carbohydrate, protein, and lipid metabolism and sub- sequent long-term vascular complications. Previous Classification Systems: WHO and ADA An attempt to apply a universal classification system to diabetes mellitus did not occur until advances in molecular biology in the 20th century provided a better understanding of the etiology and genetics leading to the various clinical pre- sentations of the disease. Amongst these advances were the discovery of insulitis in animal models and humans, the identification of islet cell antibodies, and histo- compatibility antigens (HLA) associations with diabetes. 1965: First Report of the WHO Expert Committee on Diabetes Mellitus The World Health Organization (WHO), in 1965, detailed the first attempt to apply a universal classification to diabetes mellitus and utilized age and insulin require- ments as the main criteria for classification (4). This report written by the WHO Expert Committee on Diabetes Mellitus divided patients into one of four categories: 1. Infantile or childhood diabetic—onset under 14 years of age and insulin dependent 2. Young diabetic—onset between 15 and 24 years with most becoming insulin dependent 3. Adult diabetic—onset between 25 and 64 years, presenting with variable requirements for insulin 4. Elderly diabetic—onset after 65 years of age, frequently presenting with symp- toms of diabetic complications and often controllable without insulin Although other nomenclature was recognized in that report (i.e., juvenile-type diabetes, insulin-resistant diabetes, and gestational diabetes), it was recommended to hold to the classification terms introduced by the committee. This report also outlined criteria for diagnosis on the basis of an oral glucose challenge, although a testing standard was not provided. Diabetes was diagnosed if the venous blood glucose was 130 mg/dL two hours after a glucose load. Persons with a blood 2 Crimmins and Dolan TABLE 2 Etiologic Classification of Diabetes Mellitus I. Type 1 diabetes (b-cell destruction, usually leading to absolute insulin deficiency) A. Immune mediated B. Idiopathic II. Type 2 diabetes (may range from predominantly insulin resistance with relative insulin deficiency to a predominantly secretory defect with insulin resistance) III. Other specific types A. Genetic defects of b-cell function 1. Chromosome 12, HNF-1a (MODY3) 2. Chromosome 7, glucokinase (MODY2) 3. Chromosome 20, HNF-4a (MODY1) 4. Chromosome 13, insulin promoter factor-1 (IPF-1; MODY4) 5. Chromosome 17, HNF-1b (MODY5) 6. Chromosome 2, NeuroD1 (MODY6) 7. Mitochondrial DNA 8. Others B. Genetic defects in insulin action 1. Type A insulin resistance 2. Leprechaunism 3. Rabson-Mendenhall syndrome 4. Lipoatrophic diabetes 5. Others C. Diseases of the exocrine pancreas 1. Pancreatitis 2. Trauma/pancreatectomy 3. Neoplasia 4. Cystic fibrosis 5. Hemochromatosis 6. Fibrocalculous pancreatopathy 7. Others D. Endocrinopathies 1. Acromegaly 2. Cushing’s syndrome 3. Glucagonoma 4. Pheochromocytoma 5. Hyperthyroidism 6. Somatostatinoma 7. Aldosteronoma 8. Others E. Drug- or chemical-induced 1. Vacor 2. Pentamidine 3. Nicotinic acid 4. Glucocorticoids 5. Thyroid hormone 6. Diazoxide 7. b-Adrenergic agonists 8. Thiazides 9. Dilantin 10. a-Interferon 11. Others F. Infections 1. Congenital rubella 2. Cytomegalovirus 3. Others (Continued) Definition, Diagnosis, and Classification of Diabetes in Youth 5 against the 65 kDa isoform of glutamic acid decarboxylase (GAD65), tyrosine phosphatase–related IA-2 molecule (IA-2), insulin autoantibodies (IAAs), and islet cell autoantibodies (ICAs). Whether these antibodies contribute to the destruction of the b-cells or are formed as a result of other immune processes are a matter of debate. What is known is that these antibodies are present prior to the appearance of clinical disease and can predict disease development (9,10). The presence of each antibody at diagnosis is dependent on the age of onset and sex of the indi- vidual. GAD65 antibodies are present in between 70% and 80% of Caucasian children diagnosed with diabetes and are less frequently found in boys. The presence of IA-2 antibodies varies with age and has been reported in 50–70% of children recently diagnosed with T1DM (11). IAAs vary the most with age, with young children having the highest prevalence at diagnosis. IAAs are found in 83% of children younger than 4 years of age, 40% of children between 7 to 13 years of age, 20% of adolescents, and 10% in adults with new-onset disease (11–13). ICAs are the most commonly found antibodies in children at diagnosis with an overall prevalence greater than 80% (11,12). One or more of the islet cell antibodies is present during diagnosis of T1DM in 80–90% of individuals (13,14). If antibodies are present under the context of clear insulinopenia and ketosis, a diagnosis of type 1a diabetes is given. If patients have a clinical picture consistent with T1DM but no antibodies present, a diagnosis of type 1b (or idiopathic T1DM) is given. Patients with type 1b diabetes are often of African or Asian decent, tend to be older, and have a greater body mass index (BMI) than age-matched children with type 1a diabetes (13). It is not clear if these patients have a different underlying pathology to their disease or if they manifest autoantibodies that are not measured by common assays. Of note, recent concerns have arisen regarding the lack of standardization of autoantibody assays between various laboratories. Because of these concerns, the NIH convened an international committee of experts in 2006 to ensure standard- ization of these assays. This standardization will be a significant step forward in ensuring correct classification of autoimmune-mediated diabetes. TABLE 2 Etiologic Classification of Diabetes Mellitus (Continued ) G. Uncommon forms of immune-mediated diabetes 1. Stiff-man syndrome 2. Anti-insulin receptor antibodies 3. Others H. Other genetic syndromes sometimes associated with diabetes 1. Down’s syndrome 2. Klinefelter’s syndrome 3. Turner’s syndrome 4. Wolfram’s syndrome 5. Friedreich’s ataxia 6. Huntington’s chorea 7. Laurence-Moon-Biedl syndrome 8. Myotonic dystrophy 9. Porphyria 10. Prader-Willi syndrome 11. Others IV. GDM Abbreviations: HNF, hepatocyte nuclear factor; MODY, maturity-onset diabetes of the young; IPF-1, insulin pro- moter factor-1; GDM, Gestational diabetes mellitus. Source: Adapted from Ref. 14. 6 Crimmins and Dolan The genetics underlying T1DM is complex and is covered in depth in chap- ter 4. T1DM has both genetic and environmental components. Specific HLA can protect or confer risk for T1DM and in fact can predict autoantibody development. HLA genes are thought to contribute up to 50% of the genetic risk for T1DM (15). Yet, studies in monozygotic twins have shown at most a 50% concordance of T1DM (16,17), proving that an environmental exposure of some kind is required for pro- gression to disease. Type 2 Diabetes Mellitus Type 2 diabetes mellitus (T2DM) is primarily characterized by insulin resistance detected at the level of skeletal muscle, liver, and adipose tissues with a failure of b-cell compensation and a relative insulin deficiency. In adults, there is an estab- lished progression from insulin resistance to glucose intolerance (IFG or IGT) to T2DM. Progression through these stages can occur over many years and is often unaccompanied by symptoms of disease. The extent to which children progress through stages of obesity, insulin resistance, and glucose intolerance is not fully understood; however, it appears that the pathway to disease is much shorter and less predictable in children than in adults. Pediatric patients with T2DM are usually overweight or obese (BMI  85th percentile for age and sex), and comorbidities such as hypertension and dyslipi- demia can be present at diagnosis. Polycystic ovarian syndrome is a common comorbidity in adolescent girls diagnosed with T2DM. Often there is a strong family history in first and second degree family members. Weight loss at diagnosis is less common than in T1DM, and acanthosis is frequently identified on exami- nation. Patients frequently present with evidence of residual b-cell function, although no standardized cutoffs exist for insulin or C-peptide levels. These patients usually lack evidence of autoimmunity. Ketosis is less common than in T1DM as individuals with T2DM usually produce enough insulin secretion to prevent lipolysis. Diet and exercise are the mainstays of treatment for T2DM. Unlike T1DM, T2DM can successfully be treated with oral hypoglycemic agents. Insulin may or may not be required at diagnosis or for long-term treatment of hyperglycemia, but insulin is not required for survival. Because of a period of ‘‘silent’’ disease in adults, hyperglycemic complications can be recognized at diagnosis. In contrast, youth rarely have hyperglycemic complications at diagnosis. Once thought to be a disease of adulthood, T2DM is becoming increasingly common in children and adolescents. T2DM now accounts for 20–50% of new-onset diabetes cases in pediatric populations within the United States (18–20). The increase in incidence in T2DM in youth is thought to be secondary to concurrent increases in obesity in children and adolescents. Other Types of Diabetes Mellitus Genetic Defects of -cell function MODY. Maturity-onset diabetes of the young (MODY) refers to monogenetic dis- orders of b-cell function leading to hyperglycemia and nonketotic diabetes melli- tus. Onset is usually before 25 years of age. Inheritance is autosomal dominant with 80–95% penetrance (21). MODY3, the most common form of MODY, is associated with mutations in the hepatocyte nuclear factor gene HNF-1a. HNF-1a is a tran- scription factor important for regulation of expression of both the insulin gene and Definition, Diagnosis, and Classification of Diabetes in Youth 7 which encodes the sulfonylurea receptor (the other subunit of the potassium channel of the b-cell), have recently been described as a less common cause of this disease (28). Homozygous inactivating mutations in the pancreas duodenum homeobox 1 gene (PDX-1) and in the glucokinase gene (affecting pancreas for- mation and glucose sensing, respectively) have also been implicated. Of note, heterozygous mutations of these genes lead to MODY4 (PDX-1) and MODY2 (glucokinase). Genetic Defects in Insulin Action Mutations in the insulin receptor leading to defects in insulin action have been identified. Type A insulin resistance manifests as a severe presentation of polycystic ovary syndrome and is characterized by marked hyperandrogenism, acanthosis nigricans, and insulin resistance. Leprechaunism and Rabson-Mendenhall syn- drome both present with severe insulin resistance and are diagnosed in infancy. Leprechaunism is characterized by intrauterine and postnatal growth retardation, dysmorphic facial features, severe insulin resistance and acanthosis, fasting hypo- glycemia, and postprandial hyperglycemia. Most patients with this disorder die in the first year of life. Rabson-Mendenhall syndrome is associated with extreme insulin resistance and acanthosis, pineal hyperplasia, and abnormal nails and teeth. The clinical picture is not as severe as seen in those children with Leprechaunism, and most children with this disorder live beyond the first year of life. Secondary Diabetes: Diseases of the Exocrine Pancreas, Endocrinopathies, Infections Diabetes can occur commonly as a secondary process from either the direct effects of primary disease or as a result of the treatment of that disease. While the specific etiologies that lead to secondary diabetes are too numerous to expound on in detail (Table 2), three main categories exist according to ADA classification: (1) diseases of the exocrine pancreas (i.e., cystic fibrosis, pancreatitis), (2) endocrinopathies (i.e., Cushing’s disease, acromegaly), and (3) infections (i.e., congenital rubella). These forms of diabetes can be transient and resolve as the primary disease abates or is cured such as in pancreatitis or hyperthyroidism. In some individuals, the primary disease may ‘‘unmask’’ developing diabetes which either continues after the pri- mary disease resolves or reveals itself in the future. Often secondary diabetes is muddied by one or more processes. For example, cystic fibrosis–related diabetes appears to be caused by both structural pancreatic damage with subsequent insulinopenia and other complicating factors leading to insulin resistance, such as undernutrition and increases in counterregulatory hormones and inflammatory cytokines. In addition, pulmonary exacerbations are frequently treated with glu- cocorticoids, worsening insulin resistance in these patients. ‘‘Stress hyperglycemia/diabetes’’ or ‘‘diabetes of injury’’ is not a separate category of diabetes according to the ADA classification system. However, this usually transient form is seen not uncommonly in pediatric critical care settings subsequent to a wide range of pathologies ranging from severe infection to head injuries. The mechanisms behind stress hyperglycemia are not fully clear and may be multifactorial. Factors involved in the pathogenesis of stress hyperglycemia include cytokine effects, hepatic and skeletal muscle insulin resistance, and unchecked counterregulatory responses (29). Yet, evidence in both adults and kids suggests that tight glucose control in stress hyperglycemia can strongly influence 10 Crimmins and Dolan morbidity and mortality outcomes in these patients, and thus needs to be men- tioned here as a significant form of diabetes. Drug- or Chemical-Induced Diabetes Mellitus Many drugs can cause hyperglycemia through either b-cell toxicity or worsening insulin resistance (Table 2). Furthermore, these drugs may not always cause diabetes in themselves, but can synergistically lead to diabetes in conjunction with the disease process they are treating (i.e., steroids in cystic fibrosis, l-asparaginase in transplant patients). In addition, drugs can increase appetite and lead to weight gain, which can accelerate diabetes development (i.e., antipsychotic medications). Once the offending agent is removed, the hyperglycemia often resolves; however, like the diseases in the last category, medications can also ‘‘unmask’’ developing diabetes. Uncommon Forms of Immune-Mediated Diabetes Two conditions exist in this category: the stiff-man syndrome and anti-insulin receptor antibodies. Stiff-man syndrome is an uncommon autoimmune disorder that leads to muscle stiffness, rigidity, and spasm involving the axial muscles, which can result in poor mobility. Other autoimmune diseases can accompany this syndrome including thyroiditis, vitiligo, and most commonly, type 1 diabetes. The autoimmune basis for this syndrome is the formation of anti-GAD antibodies, which target both GABAergic neurons and the pancreas. The onset of this disorder in childhood is rare and occurs usually between the third and seventh decades of life. Anti-insulin antibodies can block the binding of insulin to its receptor, thereby leading to decreased insulin action. These antibodies can be found in patients with other autoimmune diseases and these patients often have acanthosis. This type of diabetes has also been referred to as type B insulin resistance. Anti-insulin anti- bodies are rare in children. Other Genetic Syndromes Sometimes Associated with Diabetes Several genetic syndromes diagnosed in childhood are associated with diabetes (Table 2). Although some of these syndromes can be uncommon, collectively they make up approximately 5% of patients seen in diabetes clinics (23). Trisomy 21 is associated with an increased risk of diabetes-related antibodies and T1DM as compared with normal populations (prevalence of diabetes ranges between 1.4% and 10%) (30,31). Klinefelter’s and Turner’s syndromes can lead to diabetes with a predominately insulin-resistant phenotype. Some neuromuscular disorders such as Huntington’s disease, Friedreich’s ataxia, and myotonic dystrophy are associated with an increased risk of diabetes, which presents in adulthood. The pathophysi- ology behind diabetes in many of these syndromes is not fully understood. Wolfram’s syndrome (DIDMOAD, diabetes insipidus, diabetes mellitus, optic atrophy, deafness) is a rare autosomal recessive disorder characterized by b-cell loss and diabetes mellitus without evidence of autoimmunity as well as optic atrophy. Diabetes insipidus and deafness can also be associated with this syn- drome. Family studies have identified the gene responsible for this syndrome as the WFS1 gene. This gene is expressed abundantly in the b-cells and encodes for a transmembrane glycoprotein in the endoplasmic reticulum. Loss of function mutations of the WFS1 gene could lead to diabetes through endoplasmic reticulum membrane instability in the b-cells (32,33). Definition, Diagnosis, and Classification of Diabetes in Youth 11 Gestational Diabetes Gestational diabetes is defined as any degree of glucose intolerance with onset or first recognition during pregnancy. Diagnostic criteria based on oral glucose tolerance testing are more stringent than the criteria used for nonpregnant indi- viduals (Table 4). Gestational diabetes occurs in 4–7% of pregnancies (14,34). Insulin resistance is progressive during pregnancy, beginning mid-pregnancy and worsening during the third trimester. Placental hormones are thought to be, in part, responsible as insulin sensitivity improves dramatically after delivery. Like other insulin-resistance states, the b-cells of the pancreas must increase insulin secretion in order to maintain normal glucose homeostasis. If the pan- creatic b-cells cannot increase insulin production accordingly, gestational diabe- tes results. Most women with gestational diabetes have chronic insulin resistance prior and after pregnancy, and many go on to develop diabetes later in life. The insulin-resistant state can unmask monogenic diabetes (MODY) as well. WHERE THE CURRENT CLASSIFICATION SYSTEM FAILS: MIXED TYPES OF DIABETES In Youth: Type 1.5 Diabetes or Double Diabetes Although the terms ‘‘type 1.5 diabetes’’ (T1.5DM), ‘‘double diabetes,’’ ‘‘latent dia- betes of the young,’’ or ‘‘mixed diabetes’’ are not terms found within the current recognized classification system, they are now familiar to most endocrinologists and found in well-respected journals. For over a decade, it has been recognized that obese adults and adolescents with a clinic picture suggestive of T2DM can present in ketoacidosis of varying degrees (35,36). Some of these individuals will have evidence of autoimmunity as well (37,38). If a patient is obese and insulin resistant (T2DM), yet presents in diabetic ketoacidosis and/or with positive islet cell antibodies (T1DM), it becomes difficult to assign an appropriate label according to the current method of diabetes classification. When the phenotype and presentation of disease is mixed in children and adolescents, terms such as ‘‘ T1.5DM’’ and ‘‘double diabetes’’ have been used (39). TABLE 4 Diagnosis of GDM with a 100-g or 75-g Glucose Load mg/dL mmol/L 100-g glucose load Fasting 95 5.3 1 hr 180 10 2 hr 155 8.6 3 hr 140 7.8 75-g glucose load Fasting 95 5.3 1 hr 180 10 2 hr 155 8.6 Two or more of the venous plasma concentrations must be met or exceeded for a positive diagnosis. The test should be done in the morning after an overnight fast of between 8 and 14 hours and after at least three days of unrestricted diet (150 g carbohydrate/day) and unlimited physical activity. The subject should remain seated and should not smoke throughout the test. Abbreviation: GDM, gestational diabetes mellitus. Source: Adapted from Ref. 14. 12 Crimmins and Dolan compared with patients with T2DM; however, the C-peptide levels are higher and demonstrate a slower decline than in T1DM. In one study, 94% of patients with LADA required insulin within six years as compared with 14% of those diagnosed with T2DM and no evidence of autoimmunity (47). Oral hypoglycemic agents are initially effective in LADA; however, ultimately b-cell failure progresses to the point at which insulin is required. ICAs and GAD antibodies are common in LADA, whereas IAAs and IA-2 antibodies are less common (49). Patients with LADA are most often positive for only one antibody in contrast to T1DM patients who often present with multiple antibody positivity. Like T1DM, LADA shows HLA genetic susceptibility (50,51). These findings suggest that LADA is an autoimmune disease like T1DM; however, there are some differences in antibody positivity and T-cell responses that lead to different tempo of b-cell failure in the two disorders. DIABETES AS A SPECTRUM OF DISEASE The more we learn about the pathophysiology and clinical heterogeneity of dia- betes mellitus, the more it appears to be a spectrum of disease. The remainder of this chapter summarizes data that in addition to the mixed types of diabetes support the concept of diabetes as a spectrum of disease. The Accelerator Hypothesis Wilkin, in 2001, initially proposed the accelerator hypothesis that outlines how a spectrum of diabetes phenotypes could occur (see chap. 7 for a full discussion). The accelerator hypothesis proposes that T1DM and T2DM are the same disease and are only distinguishable by the rate of b-cell loss and the ‘‘accelerators’’ responsible (52). The three accelerators are: (1) an intrinsically high rate of b-cell apoptosis, (2) weight gain and subsequent insulin resistance, and (3) the development of b-cell autoimmunity. Accelerators 1 and 2 are common to both T1DM and T2DM. Only the addition of accelerator 3—autoimmunity—leads to the more acute and severe presentation seen in T1DM. In fact, the prevalence of T1DM has been increasing over the last several years in various populations. Since the underlying genetic structure of the population is unlikely to change drastically within a generation, it is likely that some change in the environment has led to the increase. The rise in the prevalence of obesity in children and adolescents over the same time frame has been suggested as a possible culprit and is one of the proposed accelerators. In fact, insulin resistance has been shown to be associated with progression to diabetes in antibody positive first degree relatives of individuals with T1DM (53). In addition, weight gain in infancy may be associated with increased risk of developing T1DM later in childhood (54,55). Family Studies Family studies suggest that there might be overlap in the pathophysiologic processes that underlie T1DM and T2DM. Studies have reported an increased frequency of T2DM in families with T1DM, and a parental history of T2DM was associated with an increased risk of T1DM in siblings of type 1 diabetic patients (56). In addition, evidence suggests that there might be an increased risk of diabetes-related compli- cations such as cardiovascular disease and nephropathy in individuals with T1DM and a family history of T2DM (57–59). Interestingly, a family history of T1DM Definition, Diagnosis, and Classification of Diabetes in Youth 15 appears to convey less risk of cardiovascular disease in individuals with T2DM (60,61). Basic Science Studies Epidemiologic studies provided much of the fuel for the argument of overlapping pathophysiology of T1DM and T2DM. However, basic science has also provided some clues in this regard. Recently, Chaparro et al. reported that many genes differentially regulated in the NOD mouse (a murine model of T1DM) are more commonly associated with T1DM than T1DM (62). The authors suggest that the NOD mouse is a better model for T1.5DM in humans than for T1DM. Furthermore, factors leading to b-cell failure are similar in T1DM and T2DM, and recent studies have shown immune processes in the islets of patients with T2DM (63). SUMMARY: COMING FULL CIRCLE IN CLASSIFYING DIABETES MELLITUS The diabetes classification system endorsed by the ADA and WHO clearly has limitations. These limitations include arbitrary cutoffs for antibody positivity, no specific guidelines for what constitutes insulin deficiency or insulin resistance, and considerable overlap between phenotypes of disease. As a result, ‘‘mixed’’ types of diabetes are difficult to classify. So why classify at all? As Gale stated in an editorial entitled ‘‘Declassifying Diabetes,’’ a classification system provides a ‘‘construct—or paradigm—that encapsulates current scientific understanding of a disease, and offers guidance as to how this might translate into clinical practice’’ (64). Currently, the diabetes classification system approaches diabetes as a categorical disease. This approach provides clinicians, parents, and scientists a common ground for communication. Physicians offer prognostic guidance and patients develop expectations on further treatment based on diabetes type. However, different types of diabetes frequently require similar treatments, monitoring, metabolic derangements, and long-term vascular complications. Furthermore, research into the pathophysiologic mecha- nisms by type of diabetes has led to a common and unifying theme of a balance between insulin resistance and b-cell compromise in all diabetes types. As Dr. Gale also states, ‘‘Above all, we need to avoid the humiliation of being taken prisoner by constructs invented for our own convenience’’ (64). Although the classification of diabetes is an important tool for practitioners, its limitations secondary to gaps in current knowledge need to be recognized. Over the past 40 years, the diabetes community appears to have come full circle. Prior to the first proposed classification system in 1965, diabetes mellitus was largely considered a single entity. As the science and treatment of diabetes advanced, categories of diabetes were created on the basis of age at diagnosis and the need for insulin. By 1997, clinicians and investigators recognized that neither age nor insulin requirements were accurate bases for classification. Instead, path- ophysiology was used to attempt to better classify disease. Recently, mixed types of diabetes have been recognized that challenge the current classification system. Thus, we have moved from the concept of diabetes as a single entity to treatment and pathophysiology-based classifications, to most recently considering diabetes as a spectrum of disease. In some respects, the debate over classification has divided the diabetes community. In our view, challenging the current classification of 16 Crimmins and Dolan diabetes should not be devised. Rather, this process is a natural, ongoing conse- quence of scientific investigation. REFERENCES 1. Harley G. Diabetes: Its Various Forms and Different Treatments. London: Walton and Mabberly, 1866. 2. Master Series: Etienne Lancereaux. Diabetologia 2005; 48(11). 3. Gale EA. The discovery of type 1 diabetes. Diabetes 2001; 50(2):217–226. 4. World Health Organization. Diabetes Mellitus: Report of a WHO Expert Committee. World Health Organization Technical Support Series 1965(310). 5. National Diabetes Data Group. Classification and diagnosis of diabetes mellitus and other categories of glucose intolerance. Diabetes 1979; 28(12):1039–1057. 6. The Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care 1997; 20(7):1183–1197. 7. World Health Organization. Definition, Diagnosis, and Classification of Diabetes Mel- litus and Its Complications. Report of a WHO Consultation. Part 1: Diagnosis and Classification of Diabetes Mellius. World Health Organization, 1999. 8. American Diabetes Association. Follow-up report on the diagnosis of diabetes mellitus. Diabetes Care 2003; 26(11):3160–3167. 9. Riley WJ, Maclaren NK, Krischer J, et al. A prospective study of the development of diabetes in relatives of patients with insulin-dependent diabetes. N Engl J Med 1990; 323 (17):1167–1172. 10. Srikanta S, Ganda OP, Eisenbarth GS, et al. Islet-cell antibodies and beta-cell function in monozygotic triplets and twins initially discordant for Type I diabetes mellitus. N Engl J Med 1983; 308(6):322–325. 11. Pihoker C, Gilliam LK, Hampe CS, et al. Autoantibodies in diabetes. Diabetes 2005; 54 (suppl 2):S52–S61. 12. Graham J, Hagopian WA, Kockum I, et al. Genetic effects on age-dependent onset and islet cell autoantibody markers in type 1 diabetes. Diabetes 2002; 51(5):1346–1355. 13. Wang J, Miao D, Babu S, et al. Prevalence of autoantibody-negative diabetes is not rare at all ages and increases with older age and obesity. J Clin Endocrinol Metab 2007; 92 (1):88–92. 14. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Dia- betes Care 2007; 30(suppl 1):s42–s47. 15. Achenbach P, Bonifacio E, Koczwara K, et al. Natural history of type 1 diabetes. Dia- betes 2005; 54(suppl 2):s25–s31. 16. Kyvik KO, Green A, Beck-Nielsen H. Concordance rates of insulin-dependent diabetes mellitus: a population based study of young Danish twins. BMJ 1995; 311(7010):913–917. 17. Redondo MJ, Rewers M, Yu L, et al. Genetic determination of islet cell autoimmunity in monozygotic twin, dizygotic twin, and non-twin siblings of patients with type 1 dia- betes: prospective twin study. BMJ 1999; 318(7185):698–702. 18. Hannon TS, Rao G, Arslanian SA. Childhood obesity and type 2 diabetes mellitus. Pediatrics 2005; 116(2):473–480. 19. Diabetes in Children Adolescents Work Group of the National Diabetes Education Program. An update on type 2 diabetes in youth from the national diabetes education program. Pediatrics 2004; 114:259–263. 20. Duncan G. Prevalence of diabetes and impaired fasting glucose levels among US ado- lescents: National Health and Nutrition Examination Survey, 1999–2002. Arch Pediatr Adolesc Med 2006; 160(5):523–528. 21. Fajans SS, Bell GI, Polonsky KS. Molecular mechanisms and clinical pathophysiology of maturity-onset diabetes of the young. N Engl J Med 2001; 345(13):971–980. 22. Maassen JA, Lm TH, Van Essen E, et al. Mitochondrial diabetes: molecular mechanisms and clinical presentation. Diabetes 2004; 53(suppl 1):S103–S109. 23. Barrett TG. Mitochondrial diabetes, DIDMOAD and other inherited diabetes syn- dromes. Best Pract Res Clin Endocrinol Metab 2001; 15(3):325–343. Definition, Diagnosis, and Classification of Diabetes in Youth 17 2 Descriptive Epidemiology of Type 1 Diabetes in Youth: Incidence, Mortality, Prevalence, and Secular Trends Anders Green Department of Epidemiology, Institute of Public Health, University of Southern Denmark and Department of Applied Research and Health Technology Assessment, Odense University Hospital, Odense, Denmark INTRODUCTION Diabetes mellitus with onset in childhood represents one of the most frequent chronic diseases in children and young adults. The disease is associated with a significant burden to society and patients because most cases require lifelong treatment with insulin as well as access to day-to-day monitoring and treatment of complications and because the disease confers increased risk of severe late com- plications such as renal failure, blindness, amputations, heart disease, and stroke. Even in societies with unrestricted access to the treatment of diabetes and its complications, the disease is associated with the risk of premature death. This chapter concerns the contemporary epidemiological characteristics of type 1 diabetes with onset in the age group 0–14 years, with a particular focus on the pro- jected future trends in the global epidemiology of the disease. Only type 1 diabetes with onset in childhood will be considered. Even though the clinical presentation of type 2 diabetes represents a growing problem in childhood and adolescence, the available epidemiological information suggests that so far patients with type 2 diabetes in childhood are outnumbered by cases with classical type 1 diabetes (1,2). Type 2 diabetes with onset in childhood will be dealt with elsewhere in this volume. The etiology and pathogenesis of childhood-onset type 1 diabetes are reviewed from various perspectives elsewhere in this volume and will only be commented upon sporadically. It is, however, important to note that it is generally accepted that type 1 diabetes develops as a consequence of interaction(s) between susceptibility genotypes and environmental factors. THE EPIDEMIOLOGY OF TYPE 1 DIABETES IN CHILDREN During the last decades large international collaborative studies, using stand- ardized ascertainment schemes, such as the Diabetes Epidemiology Research International (DERI) studies (3), WHO Diabetes Mondiale (WHO DiaMond) Project (4), and studies on the childhood-onset type 1 diabetes as part of the Concerted Action EURODIAB (Europe and Diabetes) Program (5), have offered significant contributions to our knowledge of the global epidemiology of the disease. Yet, epidemiological data on type 1 diabetes are still lacking for the major part of the global population of children, especially in Africa, Asia, and South America (4). Incidence The measure of incidence represents an enumeration of new cases of a disease in a well-defined population. Incidence may be expressed in absolute numbers and in 21 rates (where the absolute numbers are expressed relative to the background pop- ulation at risk of developing the disease). It is important to stress that incidence is specific for the calendar time period during which new cases are accumulated. Even though the incidence level may be constant over a period, any changes in the demography of the background risk population will lead to changes in the absolute number of incident cases over time. Type 1 diabetes in children typically has a rather abrupt onset with a few weeks of specific symptoms and may be even diagnosed on the background of severe ketoacidosis. This consideration, combined with the fact that the health care of sick children is often centralized in societies with well-established health care systems, makes regional incidence-based registration systems feasible. On the other hand, in societies without a well-organized health care service and with limited access to treatment and care, it is difficult to establish a valid incidence registration system, and even the diagnosis of type 1 diabetes may be missed. Geography The incidence of childhood-onset type 1 diabetes exhibits huge geographical variation. The recent account from the DiaMond studies covers incidence regis- trations from year 1990 until year 2000 and has demonstrated a >350-fold vari- ability in incidence level across the populations studied (4). Finland has a record high incidence level at more than 40 new cases per 100,000 children at risk, whereas regions in China have the lowest recorded incidence level at about 0.1 cases per 100,000 children at risk. Europe, particularly Finland and the Scandinavian coun- tries, is generally considered the continent with the highest risk level, but even within Europe a substantial variability has been demonstrated between pop- ulations (6) with a range from the record high incidence in Finland to a level at some 4.2 cases per 100,000 in the Former Yugoslavian Republic of Macedonia (6). In the American continent, the incidence level is relatively high in the Caucasian populations of the United States and Canada with an incidence level approaching that of Norway and Sweden (4). Africa and particularly Asia represent continents where the incidence level is low, but the estimates are affected by some uncer- tainties due to possible underreporting in societies with less developed health care systems (4). In terms of population size, Oceania is dominated by Australia and New Zealand where the incidence level is comparable to that seen in Central and Western Europe (4). Ethnicity The incidence of childhood-onset type 1 diabetes by ethnicity correlates strongly with the variability in incidence across countries. In general, Caucasian pop- ulations, in particular of Northern European ancestry, have the highest incidence levels (4). As mentioned above, the incidence levels in the Scandinavian countries parallel those of Canada, the United States (non-Hispanic whites), and New Zealand and Australia. Even within Europe, remarkably sharp contrasts are found between neighboring countries and populations (6). Thus, Sardinia represents a ‘‘hot spot’’ with an incidence level approaching that of Finland, which is several times higher than the surrounding Italian and other neighboring populations. Estonia, with its ethnic and cultural similarities with Finland, has an incidence level that is several times less than in Finland. Iceland, founded many centuries ago by migration from Western Norway, has an incidence level much less than the level in Norway and 22 Green connection with the diagnosis of type 1 diabetes or soon after disease onset due to acute complications. In many such children it is likely that type one diabetes may have remained undiagnosed, being masked by the clinical picture of competing infectious diseases and malnutrition (23). The situation for the children with type 1 diabetes in these societies is similar to the children in the developed part of the world before the introduction of insulin treatment and modern diabetes care. Prevalence Prevalence as a measure is defined as the size (in absolute number or as a propor- tion) of the patient population in a well-defined general population at a given point of time. It is important to realize that the prevalence is a consequence of the number of new cases (incidence) and the number of deaths (regardless of cause of death) among the patients and the number of cured patients that have occurred prior to the point of time the prevalence estimate refers to. In this context, migrations across the borders delineating the population concerned have been ignored. Thus, the preva- lence at a given point of time depends not only on past incidence levels and secular trends in incidence but also on mortality and changes in mortality. Another deter- minant of the prevalence is past changes in the size of the population at risk of developing the disease since such trends affect the accumulated absolute number of incident cases. Because type 1 diabetes is a lifelong disease, currently without the possibility of a cure, the only possible mode of exit from the prevalence population of patients is death (again, ignoring migrations to and from the population). However, when restricting the scope to the population of children aged 0 to 14 years, tran- sitions to age 15 years represent another mode of exit from the prevalence population of affected children. Empirical estimates of the prevalence of type 1 diabetes in children are rel- atively rare. In areas with no or restricted access to treatment and care, it must be assumed that the prevalence of type 1 diabetes in children is low and mainly determined by the incidence level, since the patients will most likely die shortly after diagnosis. In societies with well-developed system for treatment and care of children with the disease, it is reasonable to assume that only few children with the disease will die before reaching the age of 15 years, even in spite of the increased relative mortality (see above). In these societies, the prevalence of type 1 diabetes in children will depend largely on past accumulated numbers of incident cases incidence as well as of upgrades to 15 years of age. The Diabetes Atlas, updated by the International Diabetes Federation every third year since year 2000, presents global estimates of the incidence and preva- lence of type 1 diabetes in children (1,24,25). These estimates have been produced by combining known or assumed incidence numbers with expected mean duration of the disease from the time of diagnosis until death or reaching the age of 15 years. The estimates have been established for each country in the World, with subse- quent grouping into global regions. Estimates of the contemporary and future prevalence of type 1 diabetes in children will be presented below. EPIDEMIOLOGICAL PROJECTIONS OF TYPE 1 DIABETES IN CHILDREN Methodology Epidemiological projections of type 1 diabetes in children involve estimation of the future incidence, mortality, and prevalence of the disease. This procedure requires Descriptive Epidemiology of Type 1 Diabetes in Youth 25 knowledge (or, at least, reasonably valid estimates) of the prevalence of the disease, size of the background population, mortality level, and incidence level at a specified starting point in calendar time as well as assumptions concerning any future trends in background population demography, incidence, and mortality. Thus, the future prevalence will depend on the current prevalence level and any future changes in demography, incidence, and prognosis. For the present purpose, epidemiological projections for type 1 diabetes in children aged 0 to 14 years are made for the period 2000–2025. This has been ach- ieved by applying epidemiological modeling techniques previously described (26) and consists of building up year by year the future prevalence under assumptions concerning baseline estimates of prevalence, incidence, mortality, and background population size as well as the future annual levels of incidence, mortality, and population size. Formally, this estimate may be expressed as follows: Number of prevalent casesend of year t+1 ¼Number of prevalent casesend of year t þ number of incident casesduring year t – number of deathsduring year t – number of upgrades to age 15 yearsduring year t. The projections have been made at the level of the five continents, i.e., for Europe, Asia, America, Africa, and Oceania, with summary aggregation at global level. Information on the size of the population of children in the age group 0–14 years has been obtained similarly to that used for the Diabetes Atlas 2000, with estimates of annual growth in the population size obtained from information available with the World Bank (27). The prevalence estimates (in absolute numbers) of type 1 diabetes in children aged 0 to 14 years at the end of year 1999 follow those published with the Diabetes Atlas 2000 (24). The estimated numbers of incident cases and corresponding incidence rates for year 2000 also follow those published with the Diabetes Atlas 2000 (24). Concerning the incidence rates during the period 2000 through 2024, it is assumed that for each continent the incidence will increase with an increment corresponding to 3% of the incidence rate by year 2000. Using increments rather than proportional annual increases is considered more realistic since it will lead to a linear increase rather than an exponential increase in the inci- dence rates during the period concerned. The mortality rates in children with type 1 diabetes have been assumed as follows: For well-established societies with optimal facilities for managing treatment and care of children with type 1 diabetes, a mortality rate at 0.09 deaths per 100 patient-years has been used. In contrast, in less developed societies the mortality rate is assumed to be much higher, representing an average with a range from an extremely high value at some 65 deaths per 100 patient-years (assuming that the patients die within 1.5 years) to the mortality level seen in well-established societies (assuming that some population segments in the less developed countries have access to optimal treatment and care). It is globally assumed that the mortally rate is decreasing by 2% annually from year 2000 under the expectation of continuous improvements in the access to insulin and diabetes care in less developed societies. In the modeled projections, it is a delicate issue how to adjust for the children with childhood-onset type 1 diabetes that live beyond the age of 15 years and thus disappear from the universe of patients concerned. For the present purpose, it has been assumed that globally the mean age at diagnosis of type 1 diabetes among 26 Green children aged 0 to 14 years is 8 years. This means that for patients who do not die before reaching the age of 15 years, the mean length of stay in the population of children with type 1 diabetes is 7 years. Accordingly, the annual number of chil- dren who upgrade from childhood to age 15 years has been estimated with a rate of upgrading at 1/7 ¼ 14.3/100 patient-years. The rate of upgrading has, for a given year, been applied to the size of the prevalent population the year before minus the estimated number of deaths for the year before. Baseline Characteristics Year 2000 Table 1 (upper panel) summarizes the key baseline data estimated for year 2000. Concerning incidence, about 100,000 children aged 0 to 14 years developed diabetes within year 2000. In spite of a low incidence level in Asia, this continent contributed with almost half of the incident cases because of the huge popula- tion of children in Asia. In contrast, Europe together with Oceania contributed with less than 20% to the global incidence in spite of high incidence levels. America, representing a high incidence level in North America and lower incidence levels in Central and South America, contributed with 20–25% of the global incidence. The African continent, representing about 19% of the global population of children, contributed with less than 10% because of the assumed low incidence level. The mortality rate varies considerably between continents as reviewed above. Oceania has the lowest assumed mortality rate because this continent is, in terms of prevalence of type 1 diabetes in children, completely dominated by Australia and New Zealand, and the patients here are assumed to have close to optimal living conditions with type 1 diabetes. The mortality rate in Europe is assumed to be slightly lower because Europe also represents populations that may not yet have reached a level of optimal treatment and care of children with type 1 diabetes. America is considered to have a somewhat higher mortality level because of the inclusion of patients from less developed countries in South America. Asia and, in particular, Africa are continents in which the mortality rate must be considered high and in certain societies at the level seen in the developed societies before insulin treatment was introduced. The mortality rates applied in Asia and Africa for year 2000 represent weighted averages across subregions by socioeconomic development within each of these continents. Regarding world- wide prevalence of type 1 diabetes, it is estimated that among some 2 billion children aged 0 to 14 years almost 400,000 (0.2 per 1000) had type 1 diabetes at the end of year 1999. In spite of low incidence level and high mortality level, Asia has the largest contribution (*43%) to the global prevalence because of its huge background population of children. On the relative scale, Europe and Oceania have the highest prevalence level because of high incidence level and low mor- tality level. In America, representing a mixture of the well-developed societies in North America and less developed societies in South America, the prevalence proportion is slightly less than those of Europe and Oceania because of slightly lower incidence and slightly higher mortality level. The prevalence proportion is considered to be very low in Africa because of a combination of low incidence and high mortality levels. Table 1 (lower panel) specifies the annual changes that have been considered in the epidemiological projections concerning background population size, inci- dence rate, and mortality rate as discussed above. Descriptive Epidemiology of Type 1 Diabetes in Youth 27 FIGURE 1 Estimated projection of the annual global incidence (in absolute numbers) of type 1 diabetes with onset in age group 0–14 years by contrasting scenarios. For specification of scenarios, see Table 1 and text. FIGURE 2 Estimated projection of the annual global prevalence (in absolute numbers) of type 1 diabetes in age group 0–14 years by contrasting scenarios. For specification of scenarios, see Table 1 and text. 30 Green background population at risk and unchanged incidence and mortality rates from year 2000 onward, the prevalence is expected to rise from almost 400,000 children in year 2000 to almost 550,000 by year 2025. This rise is an effect of the epi- demiological disequilibrium that characterizes childhood-onset type 1 diabetes. Allowing for growth in the background population but no changes in incidence and mortality rates will result in a prevalence number at more than 710,000 by year 2025. If future increases in incidence (as specified in Table 1) but no further improvements in the prognosis are also allowed for, the expected prevalence number will be more than 1,000,000. Finally, in the key reference scenario, also allowing for future improvements in prognosis, the projected prevalence number by year 2025 is expected to be almost 1,130,000 children. Since it is unrealistic to assume no increase in the global population of children and no further increase in the incidence rate, it seems reasonable to assume that the prevalence by year 2025 will comprise at least some 1,000,000 children aged 0 to 14 years. The upper part of Table 2 enumerates the estimated prevalence under the key reference scenario for the end of year 2024 globally as well as by continent. Worldwide, the expected increase in prevalence since the end of year 1999 corre- sponds with 186%. However, the increase varies considerably across the continents, with the relatively smallest increases expected in Oceania and Europe and the largest increases expected in America, Asia, and particularly Africa. Drivers of the Future Prevalence The lower part of Table 2 quantifies the components that drive the future preva- lence increase. Globally, almost half of the increase in prevalence is estimated to be caused by the assumed increasing incidence; some 20% may be ascribed to the effect of epidemiological disequilibrium and about 23% will be accounted for by demographical evolution. The assumed improvement in prognosis accounts for only 9% of the expected increase in prevalence. The drivers of the prevalence increase vary markedly across the continents. Thus, the effect of assumed improvement in prognosis is relatively largest in Asia and Africa where the current mortality level supposedly is considerably higher than elsewhere. In the more developed continents like Oceania, Europe, and partly America, the effect of epidemiological disequilibrium is relatively largest and the effects of demographical changes and improved prognosis are very modest (with the exemption of America concerning population growth). COMMENTS Childhood-onset type 1 diabetes represents a global health problem and is a dis- ease undergoing dramatic epidemiological changes, with marked differences in the epidemiological characteristics between the continents. Inevitably, projections of the future incidence and prevalence will depend on the assumptions made in the epidemiological modeling. In the analysis presented here, most uncertainty must be attached to the assumptions regarding current and future mortality. However, the projections also suggest that the effects on the future prevalence from future changes in mortality are modest only. It is therefore reasonable to assume that the prevalence of type 1 diabetes will increase dramatically and reach a level about 1,000,000 children by year 2025, against a level at less than 400,000 by year 2000. The prevalence will increase most in the less developed part of the world, even Descriptive Epidemiology of Type 1 Diabetes in Youth 31 T A B L E 2 E s tim a te d G lo b a l P re v a le n c e o f T y p e 1 D ia b e te s in C h ild re n A g e d 0 to 1 4 Y e a rs fo r Y e a r 2 0 2 5 b y C o n tin e n t, w ith E s tim a te d In c re a s e in P re v a le n c e N u m b e rs S in c e Y e a r 2 0 0 0 a n d th e B re a k D o w n o f th e In c re a s e b y C o n tr ib u ta b le C o m p o n e n ts E u ro p e A s ia A m e ri c a A fr ic a O c e a n ia W o rl d E s tim a te d p o p u la tio n s iz e b y y e a r 2 0 2 5 (n u m b e r in 1 0 0 0 ’s ) 1 5 0 ,0 6 7 1 ,8 8 2 ,1 5 0 3 6 0 ,0 3 8 7 7 0 ,2 6 9 7 ,6 3 6 3 ,1 7 0 ,1 6 0 E s tim a te d p re v a le n c e (n u m b e r) b y e n d o f y e a r 2 0 2 4 1 7 9 ,5 1 9 5 1 6 ,5 4 0 2 9 8 ,6 8 8 1 2 5 ,3 7 4 7 ,9 0 3 1 ,1 2 8 ,0 2 4 E s tim a te d in c re a s e in p re v a le n c e (n u m b e r) s in c e y e a r 2 0 0 0 9 3 ,5 3 4 3 4 7 ,3 8 1 1 9 4 ,7 6 8 9 4 ,4 1 8 3 ,6 5 4 7 3 3 ,7 5 5 In c re a s e (i n % ) 1 0 9 2 0 5 1 8 7 3 0 5 8 6 1 8 6 E s tim a te d in c re a s e in p re v a le n c e (n u m b e rs ) a tt ri b u ta b le to E p id e m io lo g ic a l d is e q u ili b ri u m 3 5 ,9 0 9 4 9 ,9 3 4 5 2 ,2 5 8 9 ,7 2 8 1 ,0 9 4 1 4 8 ,9 2 4 G ro w th in p o p u la tio n a t ri s k 1 ,4 8 8 8 7 ,4 4 2 4 6 ,8 6 8 3 2 ,1 3 7 9 3 1 6 8 ,0 2 8 In c re a s e in in c id e n c e 5 5 ,8 4 0 1 6 0 ,0 8 5 9 4 ,5 0 4 3 8 ,9 1 7 2 ,4 5 6 3 5 1 ,8 0 3 R e d u c e d m o rt a lit y 2 9 7 4 9 ,9 2 0 1 ,1 3 7 1 3 ,6 3 6 1 1 6 5 ,0 0 1 P ro p o rt io n o f in c re a s e in p re v a le n c e a tt ri b u ta b le to (i n % ) E p id e m io lo g ic a l d is e q u ili b ri u m 3 8 .4 1 4 .4 2 6 .8 1 0 .3 2 9 .9 2 0 .3 G ro w th in p o p u la tio n a t ri s k 1 .6 2 5 .% 2 4 .1 3 4 .0 2 .6 2 2 .9 In c re a s e in in c id e n c e 5 9 .7 4 6 .1 4 8 .5 4 1 .2 6 7 .2 4 7 .9 R e d u c e d m o rt a lit y 0 .3 1 4 .4 0 .6 1 4 .4 0 .3 8 .9 32 Green 3 Genetic Epidemiology of Type 1 Diabetes George S. Eisenbarth and Theresa A. Aly Barbara Davis Center for Childhood Diabetes and Human Medical Genetics Program, University of Colorado at Denver and Health Sciences Center, Aurora, Colorado, U.S.A. INTRODUCTION Diabetes mellitus results from multiple genetic and pathologic processes in human and animal models. The current nomenclature from the American Diabetes Association Expert Committee classifies diabetes into broad groups on the basis of the etiological causes of diabetes. This review focuses on type 1A diabetes, which is caused by the immune-mediated destruction of b cells. Type 1A diabetes is a genetically heterogeneous disorder with certain well-defined rare syndromes. In particular, both the neonatal diabetes of the immunodysregulation, polyendocrino- pathy, enteropathy, X-linked (IPEX) syndrome and the diabetes of approximately 15% of patients with autoimmune polyendocrine syndrome type 1 (APS-1) are determined by major ‘‘monogenic’’ mutations (IPEX: FOXP3 gene and APS-1: AIRE gene) (1–3). In contrast, type 1A diabetes is more typically associated with a polygenic pattern of inheritance (typical type 1A diabetes), with risk predominantly determined by genes within or linked to the major histocompatibility complex (MHC) on chro- mosome 6. The rare monogenic syndromes provide important and precise informa- tion as to the pathologic processes that can cause immune-mediated diabetes when mechanisms of self-tolerance fail. It is likely that mutations of the FOXP3 gene lead to diabetes by eliminating a major class of regulatory T lymphocytes (CD4+CD25+), while mutations of the AIRE gene contribute to diabetes by decreasing the expression of ‘‘peripheral’’ antigens within the thymus, such as insulin, and thereby reduce the negative selection of T cells within the thymus (4). It is likely that just as critical but less dramatic failures of mechanisms of main- tenance of self-tolerance cause typical type 1A diabetes. In addition, the genes asso- ciated with typical type 1A diabetes have a lower penetrance than the genes associated with the monogenic forms of type 1A diabetes, and typical type 1A diabetes is more likely to be influenced by environmental factors. A general hypothesis is that type 1A diabetes is mediated by autoreactive T lymphocytes and that polymorphic HLA alleles (e.g., HLA-DP, HLA-DQ, HLA-DR, HLA-A, and HLA-B), which influence the targeting of islet b-cell antigens in combination with polymorphisms of genes, which in turn influence T-cell receptor signaling (e.g., PTPN22, CTLA4) or expression of major islet autoantigens (e.g., INS gene), determine the probability that an individual will develop type 1A diabetes. To date, genetic loci/genes associated with type II diabetes (e.g., TCF7L2) do not appear to contribute to the genetic risk of type 1A diabetes (5), and insulin resistance is likely not crucial to genetic susceptibility of type 1A diabetes, although it can influence when an individual will present with hyperglycemia. PATHOPHYSIOLOGY: GENES AND THE ENVIRONMENT The onset of type 1A diabetes occurs when the destruction of pancreatic b cells by the immune system has progressed to a level where not enough insulin is being produced to regulate glucose levels in the blood. The onset of diabetes in both 35 humans and animal models is associated with insulitis, an infiltrate of CD8 and CD4 T lymphocytes, B lymphocytes, and macrophages (6). Whereas the etiology of the autoimmune attack on the b cells is not fully understood, evidence suggests that an environmental exposure, such as an infection (7) or a food introduction (e.g., cereal exposure prior to 3 months of age) (8), may lead to autoimmunity in individuals with an underlying genetic predisposition for diabetes. Vitamin D deficiency might also contribute to risk for diabetes (9). Interestingly, the infection of a colony of diabetes resistant BB (DR-BB) rats with the Kilham rat virus led to the spontaneous development of diabetes (10). Extensive studies of this spontaneous animal model suggest that the Kilham rat virus does not infect the islets, but rather activates innate immunity in a genetically susceptible animal leading to T-cell mediated islet b-cell destruction. Similarly, activation of the innate immune system with inosinic cytidylic acid (poly-IC), a mimic of double-stranded RNA, can induce diabetes. For diabetes to develop with poly-IC injection, a rat strain must have high-risk MHC alleles, such as RT1-U (11). In a similar poly-IC mouse model, the induction of interferon alfa expression fol- lowing poly-IC injection is essential for the triggering of diabetes (12). Thus, rela- tively nonspecific activation of innate immunity by viruses in genetically susceptible individuals may relate to diabetes induction. The one viral infection clearly associated with type 1A diabetes in humans is congenital rubella infection, but only congenital (resulting from rubella exposure in utero). Predominantly, individuals with higher genetic susceptibility (i.e., with higher risk HLA alleles) develop diabetes following congenital rubella (13), and the onset of diabetes often occurs decades after birth. These individuals are also at a higher risk for a series of other autoimmune disorders, in particular, thyroiditis. One possible explanation for the clinical course of these individuals is that the rubella virus induces long-term changes in T-cell function that leads to an increase in diabetes risk (14). POPULATION STUDIES Type 1A diabetes affects approximately 1.4 million people in the United States, with siblings at a higher risk than offspring, and both with a higher risk than the general population (sibling risk relative to population risk, ls ¼ 6/0.4 ¼ 15) (15–17). Approximately half of the newly diagnosed cases of type 1A diabetes occur in adults and the condition is one of the most common chronic diseases diagnosed in youth (15). Approximately 160,000 children in the United States under the age of 15 years have type 1A diabetes (15). The SEARCH for Diabetes in Youth study found a crude prevalence of 2.8 cases out of 1000 children at ages 10 through 19 years, with the highest prevalence in non-Hispanic white children (3.2 per 1000) (18). The incidence of type 1A diabetes is increasing in most countries around the world; the EURODIAB study has reported an increased incidence of approximately 3–4% each year in Europe (19). Interestingly, there is a large amount of variation of disease incidence by country, with a child in Finland at 100 times the risk for type 1A diabetes than a child in the Zunyi region of China (19). The incidence of type 1A diabetes is particularly increasing in developed countries around the world, and it is postulated that the increased risk of diabetes is caused by a change (an increase or a decrease) in environmental exposures in these countries. Given a genetically susceptible host, one or more environmental exposures may help to protect against the development of immune-mediated 36 Eisenbarth and Aly diabetes (20). One hypothesis (the ‘‘hygiene hypothesis’’) for the increasing inci- dence of type 1A diabetes in developed countries is that potentially protective environmental exposures, such as infectious agents, are decreasing in these coun- tries (21). An interesting observation is the unusually high incidence rate of type 1A diabetes in Jewish children from Yemen living in Israel (as high as in Finland), with the highest risk associated with the DR3-DQ2/DR4-DQ8 genotype (22). By oral history, this Jewish population was not aware of any cases of childhood diabetes in their population until they were transplanted from Yemen to Israel. This ‘‘anec- dote’’ may well reflect a lower risk of type 1A diabetes in populations that carry major burden of chronic infections (such as in Yemen) and suggests that a major increase in diabetes risk can occur within one generation with a change in envi- ronmental exposures (such as with a reduced exposure to pathogens). TWIN STUDIES The genetic liability for diabetes has been investigated by comparing concordance rates for diabetes in monozygotic (identical) twins versus dizygotic twins. In a study of 187 initially discordant monozygotic twins in Great Britain and the United States, the nondiabetic monozygotic twin of a proband diagnosed with diabetes prior to six years of age had a 60% risk for developing diabetes within 40 years of follow-up (23). The risk for initially discordant dizygotic twins was reported as being similar to the risk of non-twin siblings (with a risk of 5–10% for diabetes) (24,25). A study of 228 Finish twin pairs with diabetes suggested that 88% of the phenotypic variance was due to genetic factors, and a model with additive genetic and individual environmental effects was the best-fitting liability model (26). THE MAJOR HISTOCOMPATIBILITY COMPLEX Although type 1A diabetes is a complex genetic disorder, it is linked more with the MHC region on chromosome 6p21.3 (LOD score*116, p = 1.9 x 10–52) (27) than any other chromosomal region. The HLA-DR and HLA-DQ genes are established as being associated with diabetes risk by genetic, functional, structural, and animal model studies (28–31). The heterozygous DR3-DQ2/DR4-DQ8 genotype represents the highest risk combination of HLA-DR and HLA-DQ alleles (with the HLA- DRB1*03-DQA1*0501-DQB1*0201 and HLA-DRB1*04-DQA1*0301-DQB1*0302 hap- lotypes). Only 2.4% of the general population have the high-risk DR3-DQ2/DR4- DQ8 genotype, whereas almost 50% of children developing anti-islet autoimmunity by the age of five years have the DR3-DQ2/DR4-DQ8 genotype (17). Moderate-risk HLA-DR-DQ genotypes include the HLA-DR3-DQ2/DR3-DQ2, the HLA-DR4-DQ8/ DR4-DQ8, and the HLA-DR4-DQ8/X genotypes (where X is not DQ2, DQ8, or DQB1*0602). Lower-risk genotypes have protective alleles such as HLA- DQB1*0602, HLA-DQB1*0503 (with HLA-DRB1*1401), and HLA-DQB1*0303 (with HLA-DRB1*0701). Other HLA-DQ genotypes are associated with neutral risk. HLA- DRB1*04 subtypes can change the risk associated with the HLA-DR4-DQ8 hap- lotype. The HLA-DRB1*0405 and HLA-DRB1*0401 subtypes are associated with higher risk, the HLA-DRB1*0402 and HLA-DRB1*0404 subtypes are predisposing, and the HLA-DRB1*0403 subtype is protective. Each class II HLA molecule (DR, DQ, and DP) is composed of an a chain and a b chain with the HLA-DQA loci coding for DQ-a subunits and the HLA-DQB loci coding for DQ-b subunits. Class II HLA dimers present peptide antigens to the Genetic Epidemiology of Type 1 Diabetes 37 confirmed in other studies, it suggests that the genetic factors associated with risk of type 1A diabetes autoimmunity is very high, at least for siblings, and rare triggering environmental factors are unlikely. Common environmental factors may, however, still be present and essential for disease. It will be important to predict extreme type 1A diabetes risk not only for siblings of patients but also in the general population because the great majority (over 85%) of individuals with type 1A diabetes do not have a first-degree relative with type 1A diabetes. A recent analysis using HLA-DPB1 and HLA-DRB1 sub- typing indicates a lower risk for type 1A diabetes in DR3-DQ2/DR4-DQ8 children that have the protective HLA-DPB1*0402 or HLA-DRB1*0403 allele (43). Prospec- tively followed children from the general population had a 19% (5%) risk for expression of persistent anti-islet autoantibodies if they had the DR3-DQ2/DR4- DQ8 genotype but did not have the HLA-DPB1*0402 or HLA-DRB1*0403 allele (Fig. 3). The identification and localization of additional genetic determinants that FIGURE 2 Haplotype sharing survival curves. Progression to anti-islet autoimmunity (left panel ) and type 1A diabetes (right panel ) in DR3-DQ2/DR4-DQ8 siblings stratified by the number of HLA haplotypes shared with their proband siblings. N = 48 for both panels; error bars for all panels represent the SEM. Abbreviation: SEM, standard error of the mean. Source: From Ref. 41. FIGURE 3 Progression to anti-islet autoantibody positivity in prospectively followed newborns with the HLA-DR3-DQ2/DR4-DQ8 genotype from the general population (NEwborn Cohort, NECs). Children with the DR3-DQ/DR4-DQ8 genotype that did not have either a DRB1*0403 or a DPB1*0402 allele had a 19% ( 5%) risk for anti- islet autoantibody positivity by age 12 versus a 2% (2%) risk if the DR3-DQ2/DR4-DQ8 children did have a DRB1*0403 or a DPB1*0402 allele. Source: From Ref. 42. 40 Eisenbarth and Aly cause the risk observed with MHC haplotype sharing may further improve prediction of risk in children from the general population. EXTENDED MHC HAPLOTYPES Given the evidence for diabetes-associated loci in or linked to the MHC in addition to classical HLA alleles, a major effort is underway to identify such loci. The localization of MHC and MHC-linked loci is complicated by the extensive linkage disequilibrium (the nonrandom association between alleles of linked genes) in the MHC (44,45). For instance, HLA-A1, HLA-B8, and HLA-DR3 each occur on approximately 17%, 11%, and 12% of chromosomes in the United States popu- lation (www.allelefrequencies.net). If random ‘‘equilibrium’’ existed between these alleles, one would predict that chromosomes with the HLA-A1, HLA-B8, HLA-DR3 combination would be present on 0.2% (17% x 11% x 12%) of the chromosomes. Since approximately 9% of Caucasian chromosomes have this combination of alleles (44) (much more than 0.2%), there is linkage disequilibrium between the HLA-A1, HLA-B8, and HLA-DR3 alleles and this combination of the HLA-A, HLA-B, and HLA-DRB1 alleles is a haplotype (series of alleles at linked loci on a chromosome). Such disequilibrium could be present due to founder effects in the population or selection for the specific haplotype. The HLA-A1-B8-DR3-DQ2 extended haplotype (8.1 haplotype) is common (in *18% of individuals in Caucasian populations), extended, and extremely con- served (45,46). It is associated with multiple autoimmune diseases, including type 1A diabetes, celiac disease, systemic lupus erythematosus, common variable immuno- deficiency, myasthenia gravis, and accelerated human immunodeficiency virus (HIV) disease (47,48). Although this haplotype is associated with diabetes, it is less associated than at least another HLA-DR3-DQ2 haplotype (46,49). The HLA-A30-B18- DR3-DQ2 haplotype has a high frequency in the Basque population, is more strongly associated with diabetes than the 8.1 haplotype, and is also highly conserved (49). Comparison of 8.1 haplotypes from unrelated individuals indicates that they can be identical for greater than 99% of single nucleotide polymorphisms (SNPs) for as long as 9 million nucleotides (the MHC is less than 4 million nucleotides long) (50). Thus, for extended haplotypes, such as the 8.1 and Basque haplotypes, SNPs anywhere on the haplotype will be ‘‘overtransmitted’’ to children with type 1A diabetes, even if the overtransmission is only caused by linkage disequilibrium with the high-risk HLA-DRB1*0301 allele. We believe it is likely that better characterization of such haplotypes in populations of patients with type 1A diabetes will contribute to identifying additional MHC or MHC-linked type 1A diabetes relevant genes. NON-MHC LOCI There are a large number of reported putative non-MHC type 1A diabetes– associated loci in addition to the MHC loci (Table 1). Analysis of poly- morphisms of the insulin (INS) and PTPN22 genes identified these genes as candidate genes for type 1A diabetes prior to the current era of ‘‘genome’’ wide linkage and association studies. The genome-wide linkage and association studies have not found any major loci with effect sizes similar to the MHC for type 1A diabetes risk. It appears that most of the original reported insulin- dependent diabetes mellitus loci identified with linkage analysis are non- reproducible in large studies of different populations and were likely ‘‘false Genetic Epidemiology of Type 1 Diabetes 41 T A B L E 1 S e le c te d G e n e A s s o ci a tio n s w ith T y p e 1 A D ia b e te s L o c u s C h ro m o s o m e H ig h e r ri s k v a ri a n ts L o w e r ri s k v a ri a n ts O d d s ra tio R e fe re n c e F O X P 3 X p 1 1 .2 3 -q 1 3 .3 V a ri o u s m u ta tio n s 1 A IR E 2 1 q 2 2 .3 V a ri o u s m u ta tio n s 2 H L A -D R /D Q 6 p 2 1 .3 , C la s s II re g io n D R B 1 *0 3 – D Q B 1 *0 2 0 1 D R B 1 *0 4 – D Q B 1 *0 3 0 2 D R B 1 *0 4 0 5 , D R B 1 *0 4 0 1 D R B 1 *1 5 0 1 – D Q B 1 *0 6 0 2 , D R B 1 *0 4 0 3 % 3 0 2 7 ,5 4 H L A -D P 6 p 2 1 .3 , C la s s II re g io n D P B 1 *0 3 0 1 D P B 1 *0 4 0 2 5 5 ,4 3 IT P R 3 6 p 2 1 (M H C , c e n tr o m e ri c ) rs 2 2 9 6 3 3 6 , G a lle le rs 2 2 9 6 3 3 6 , C a lle le 2 .5 5 6 H L A -A 6 p 2 1 .3 , C la s s I re g io n A *2 4 0 2 (e a rl ie r o n s e t) 3 5 M IC A 6 p 2 1 .3 , C la s s II I re g io n D iff e rs b y p o p u la tio n M IC A *A 6 0 .7 3 (* A 6 ) 5 7 IN S 1 1 p 1 5 .5 C la s s I V N T R (s h o rt ), ( 2 3 ) H p h I A a lle le C la s s II I V N T R (l o n g ), ( 2 3 ) H p h I T a lle le 1 .9 5 3 ,2 7 C T L A 4 2 q 3 3 + 6 2 3 0 G > A , C T 6 0 1 .2 5 8 P T P N 2 2 1 p 1 3 1 8 5 8 C > T , A rg 6 2 0 T rp (T T a n d C T g e n o ty p e s ) (C C g e n o ty p e ) 1 .7 2 7 ,5 9 IF IH 1 2 q 2 4 .3 rs 1 9 9 0 7 6 0 , A a lle le rs 1 9 9 0 7 6 0 , G a lle le 1 .2 6 0 S U M O 4 6 q 2 5 1 6 3 A > G , M 5 5 V 1 .3 6 1 IL 2 R A /C D 2 5 1 0 p 1 5 .1 rs 3 1 1 8 4 7 0 , C a lle le rs 3 1 1 8 4 7 0 , T a lle le 1 .3 5 2 ,5 1 42 Eisenbarth and Aly (P30 DK57516), Clinical Research Centers (MO1 RR00069, MO1 RR00051), the Immune Tolerance Network (AI15416), the American Diabetes Association, the Juvenile Diabetes Research Foundation, and the Children’s Diabetes Foundation. 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Lack of peripheral tolerance has been implicated in the development of many autoimmune diseases (5,6). The process of oral tolerance is ongoing but there are times during development when the gut immune system is more active with respect to oral tolerance (7). In addition, it is thought that there is a dose-dependent response wherein high oral doses of antigen suppress humoral immunity and low oral doses induce cell-mediated tolerance (4). Regardless of the mechanism, the overriding theme is that repetitive exposure to antigenic proteins in the diet prompts the immune system to tolerate them as harmless. In order to properly maintain immunological homeostasis, normal oral tol- erance is essential. In the case of type 1 diabetes, it is thought that disruption of this system allows the immune system to initiate immune responses against antigens normally tolerated when ingested. When this immune response is initiated, a cycle of exposure and inflammation is induced with the result potentially being IA, which is the first step in the pathway to type 1 diabetes. The early-life dietary factors that may be of special importance in this process include breast-feeding, and exposures to bovine insulin, cow’s milk proteins, cereals, omega-3 polyun- saturated fatty acids (n-3 PUFAs), or vitamin D. Breast milk contains many beneficial components that help ensure normal GI and physiological development during infancy, including immunoglobulins, human insulin, and the appropriate balance of macronutrients essential for human development. These components help establish normal gut environment, nutrient metabolism, and immune function. All three of these factors are important in oral tolerance. The immunoglobulins contained in breast milk confer passive immunity on an infant who is breast-fed. These molecules train an infant’s naı̈ve immune system for normal immune function later in childhood and into adult life. A normally functioning immune system is essential for generation of oral tolerance because of its intrinsic checks and balances intended to differentiate between harmless and harmful foreign antigens and microbes. Because it appears that a great deal of oral tolerance is formed early in life, it also appears intuitive that early-life exposure to the immunoglobulins present in breast milk is imperative in this process. In addition to immune factors, breast milk also contains human insulin. Exposure to human insulin via breast milk may help in developing tolerance to human insulin, which first occurs in the GALT (4). If lack of tolerance to insulin is a precipitating factor in the development of type 1 diabetes, then exposure to breast milk may have a protective effect on the risk of type 1 diabetes by helping the child to develop tolerance to insulin (6). In support of this hypothesis, a pilot study in children at increased risk for type 1 diabetes showed that children consuming breast milk with higher concentrations of insulin had lower antibody response to insulin from foreign sources than infants consuming breast milk with lower con- centrations of insulin (8). 50 Simpson and Norris Given the theory of oral tolerance, one might expect that breast-feeding ini- tiation as well as longer duration of breast-feeding may result in a lower risk of type 1 diabetes. However, the epidemiological evidence has been inconsistent. While some studies have found a decreased risk of type 1 diabetes in breast-fed children, others have found equivocal results (1). These studies were case-control design and were accordingly subject to inaccuracies, and recall and selection biases (9). Interestingly, the three prospective studies investigating predictors of IA found no association between either breast-feeding initiation or duration and the appearance of IA in children at increased risk for type 1 diabetes (10–12). Another mechanism by which breast milk may protect against type 1 diabetes is via decreased exposure to breast-milk substitutes. Infants who are not breast-fed or are not exclusively breast-fed are exposed to breast-milk substitutes, such as infant formulas, which may contain diabetogenic antigens. Therefore, variation in the age at introduction to these substitutes may be a more important variable than overall breast-feeding duration in terms of diabetes risk and may, in part, explain why overall breast-feeding duration is not consistently associated with type 1 diabetes risk in the above studies. Cow’s milk, primarily in the form of cow’s milk–based formulas, is a common component of the diet of the infant who receives little or no breast milk. While the association between cow’s milk and cow’s milk–based infant formulas has been examined extensively, there is still disagreement not only on the nature of this relationship as it pertains to timing of exposure but also on what is present in cow’s milk that may be associated with increased risk. The timing of introduction to foreign antigens is an important factor in the development or disruption of oral tolerance. Many case-control studies have found an inverse association between the age at exposure to cow’s milk and type 1 diabetes (13–17). These findings may suggest that infants exposed early in life to cow’s milk are more susceptible to disruption in oral tolerance, possibly due to prolonged exposure that results from earlier exposure, a sensitive period effect, or a combination of both. However, like the breast-milk studies, there have been multiple case-control studies that have failed to find an association between the timing of cow’s milk introduction and type 1 diabetes (18,19). In addition, all three of the cohort studies discussed above examined age at exposure to cow’s milk as well, and found no association between exposure and risk for development of IA (10–12). Studies have also addressed this question by measuring antibodies in cow’s milk proteins, such as bovine serum albumin and b-lactoglobulin, and found that newly diagnosed type 1 diabetic patients had higher antibody levels to bovine serum albumin (20) and b-lactoglobulin (21) than their healthy counterparts. Because associations were seen with different cow’s milk proteins, these results indicate that there may be multiple ways in which to disrupt normal oral tolerance, or that dis- ruption in oral tolerance is the result of a constellation of exposures. However, these studies were done in children with existing diabetes, so it is unknown whether these antibodies are elevated prior to the development of clinical diabetes or auto- immunity. This information would inform as to whether elevated antibodies are a marker of the disruption of oral tolerance, which subsequently results in disease, or whether they are simply a marker of the autoimmune process that leads to type 1 diabetes, or perhaps a consequence of the disease itself. Bovine insulin is another protein in cow’s milk that may have a role in oral tolerance disruption. Its molecular structure differs from that of human insulin by three amino acids and it is this feature that researchers believe is the origin of its Early-Life Diet and Risk of Type 1 Diabetes 51 role in type 1 diabetes (6). Because it is structurally similar to human insulin, it is able to gain access to the GALT while other more dissimilar antigenic proteins will pass through the GI tract without being absorbed. It is hypothesized that once exposed to the GALT, bovine insulin is different enough from human insulin that it may initiate an immune response that lacks the specificity to differentiate between human and bovine insulin, thus generating antibodies that are cross reactive, potentially resulting in type 1 diabetes. In a study comparing how different infant formulas affect antibody response to bovine insulin and islet autoantibodies, investigators found that infants who were fed a hydrolyzed protein-based infant formula had lower levels of antibodies to bovine insulin at three months of age compared with those who were fed a cow’s milk–based infant formula. Moreover, the children receiving the hydrolyzed infant formula had lower levels of islet autoantibodies at 12 months of age than the children receiving cow’s milk–based formula (22). While the authors concluded that exposure to bovine insulin at an early stage in the development of the GI tract can predispose children to the formation of islet autoantibodies, further confir- mation is needed. Another observation that may lend support for the theory of oral tolerance as it pertains to bovine insulin is the finding that children born to mothers who have type 1 diabetes have a lower incidence of type 1 diabetes when compared with their counterparts who are born to fathers with the disease (23). Although there are many possible explanations for this relationship, in this case the relevancy lies in the fact that ingestion of amniotic fluid represents the earliest possible dietary exposure for mammals. In the case of a mother who has type 1 diabetes, her fetus is presumably exposed to consistently administered high levels of insulin orally via the amniotic fluid, and therefore may be undergoing early programming for tol- erance to orally ingested insulin. In contrast, infants with fathers who have type 1 diabetes carry similar genetic risk but are more likely to develop type 1 diabetes in the absence of high insulin exposure. This hypothesis has not yet been tested. In addition to breast-milk substitutes, such as infant formulas, the infant is exposed to other dietary antigens in the first year of life that may impact oral tolerance. In the United States, cereals are often the first solid foods to which the infant is exposed, making cereals a potentially important dietary factor to study when defining the role of diet in the development of type 1 diabetes. Like all foods, cereals have antigenic characteristics that could play a role in oral tolerance in infants. Because gluten is the environmental trigger for clinical symptoms of celiac disease, another childhood autoimmune disease, and because it is a component of many cereals, it has been studied in the context of type 1 diabetes as a potentially important environmental exposure as well. In the biobreeding (BB) diabetes-prone rat, gluten precipitates the onset of IA (24). MacFarlane et al. identified a wheat storage protein called glb1 that may be associated with islet damage, by observing that antibodies to this protein were detectable in patients with diabetes but not in nondiabetic patients (25). Moreover, the timing of introduction of cereals (and/or gluten) during infancy has been examined in all three prospective studies of the development of IA. Both BABYDIAB and DAISY have shown an increased risk for IA associated with exposure to cereals prior to the third month of life when compared with intro- duction in the fourth to sixth month of life. Norris et al. found that the timing of introduction of any type of cereal was associated with an increased IA risk and also found that there appears to be a U-shaped relationship between risk and age at 52 Simpson and Norris so its presence may have multiple protective factors that act to maintain an optimal level of gut health (41). This phenomenon becomes especially important in children at increased risk for diabetes because the interaction between their genetic suscep- tibility and the absence of proper or complete cultivation of gut health facilitated by breast milk may precipitate the onset of IA and diabetes. On the basis of this discussion, one would expect to see evidence in the literature showing that breast-feeding reduces the risk for IA, but as reported earlier in this chapter, this is not the case. The exception is the finding by Norris et al. that breast-feeding at the time of cereal introduction reduces IA risk (10), which may suggest that breast-feeding has a role in either oral tolerance or gut permeability. The discrepancy between theory and results may be attributed to the complexity of the relationship. The following factors may obscure the true rela- tionship between breast-feeding and IA: (1) the difficulty in defining what duration of breast-feeding is optimal for gut closure, (2) the likelihood that there is an interaction between breast-feeding and the presence of pathogens that prolong gut permeability, or (3) the likelihood that there is an interaction between breast- feeding and the presence of specific antigens in the diet. Another way in which increased gut permeability could lead to diabetes is through increased exposure to the microbial inhabitants of the intestinal tract. Some of the suggested mechanisms by which microbes may play a role in type 1 diabetes etiology include direct cytolysis of islet cells, molecular mimicry, and lymphocyte activation that favors a Th-1 response (42). These processes may be attributed to the microbes themselves or to a microbe-induced increased gut permeability resulting in increased dietary antigen exposure. Furthermore, if initiation of these mechanisms is predicated by colonization of the GI tract, then breast milk may be an important factor in these hypothesized processes by helping to inhibit colonization. To date, literature about the role of microbes in type 1 diabetes has focused on enteroviruses. Ex vivo studies have demonstrated that some viruses exhibit a tropism for the pancreas (43), which suggests that viruses may induce islet cell cytolysis. Vaarala et al. found that in infants exposed to cow’s milk formulas before the age of three months, those who had a T-cell proliferation response to enter- ovirus antigen at three months of age had higher concentrations of IgG antibodies to bovine insulin at the age of six and nine months than those who did not have the T-cell proliferation response to enterovirus antigen (44). This finding may support either molecular mimicry or the type of T-helper response as a mechanism. Alternatively, it could suggest an enterovirus-induced increase in gut permeability that results in exposure to dietary antigens. Further studies are needed to identify the role (if any) of microbes and to characterize the nature of that role in humans. One of the mechanistic explanations for the association between the timing of introduction to cereals in the infant diet and the risk of IA may be the effect of gluten on gut permeability (10,12). Zonulin is a newly identified biomarker for intestinal permeability and is a modulator of small intestinal tight junctions (45). Using celiac disease positive cell lines, investigators identified a relationship between gliadin, which is the portion of gluten known to cause damage in celiac disease, and zonulin. They found that zonulin levels increased as a response to exposure to gluten in these cell lines which, in turn, perpetuated the intestinal permeability to macromolecules, including gliadin. Two studies involving BB rats identified higher levels of zonulin in their diabetes-prone colonies compared with wild-type rats (34,46). Finally, in humans, Sapone et al. found that mean serum zonulin was higher in type 1 diabetes patients compared with their first-degree Early-Life Diet and Risk of Type 1 Diabetes 55 relatives and controls, and that this elevation was correlated with increased gut permeability in these patients (47). The report that gliadin may activate a zonulin- dependent intracellular pathway in the enterocyte may suggest a cycle of gliadin- induced zonulin production and subsequent increased intestinal permeability. If left unchecked, this cycle could lead to escalating exposures to the body as gliadin intake continues. In order to further test this hypothesis, prospective studies are needed to establish temporality as well as the role of diet in the process. Also of interest is the many ways that gut permeability and oral tolerance are interrelated. Because the physical barrier in the GI tract is meant to prevent chronic exposure and immune stimulation in the GALT, it is possible that in the face of increased permeability there is increased potential for disruption of oral tolerance. For example, if a dietary antigen is introduced that is capable of delaying closure of the gut, it may allow multiple macromolecules gain access to the GALT, which in turn initiates a Th1-mediated response to these molecules that eventually results in the IA that precedes clinical diabetes. OXIDATIVE STRESS THEORY Oxidative stress is a general term used to describe the level of oxidative damage in a cell, tissue, or organ, caused by reactive oxygen species (e.g., free radicals). Free radicals are highly reactive chemical species that, at physiological levels, are part of normal homeostasis, but when allowed to proliferate unchecked, cause biological damage. Because the untoward consequences of oxidative damage are most noticeable in rapidly dividing tissues, the GI tract is one of the places where oxi- dative stress can have the most profound effects. Normally there are multiple defense mechanisms in place that help prevent free radical formation, inactivate free radicals that are formed (via reduction), and repair the damage done by these species. These defenses can be intrinsic or obtained through the diet; both sources are important in everyday functioning. Immune function and dysfunction are inextricably tied to the reduction/ oxidation (redox) balance of an individual and this relationship that may be sig- nificant in the pathogenesis of type 1 diabetes. There is evidence to indicate that diabetics have impaired redox balance characterized by decreased antioxidant defenses and increased byproducts of oxidative damage (48). Studies suggest that a similar imbalance exists among healthy first-degree relatives of type 1 diabetes patients, which can be interpreted as evidence that redox imbalance precedes the onset of clinical disease (49). Because children who develop diabetes may have a preexisting impairment of antioxidant capacity, it is especially important that they have ample exogenous sources of antioxidants and free radical scavengers along with limited exposure to dietary oxidants. The most notable early-life dietary factors that may have a protective effect are breast-feeding and dietary intake of fish oils and vitamins D and E, and that may have a diabetogenic effect is exposure to exogenous free radical substrates like nitrates. Breast milk is high in antioxidant species including enzymatic antioxidants and vitamins C, E, and b-carotene especially when compared with infant formula (50). These antioxidants may help to bolster the antioxidant capabilities in the infant, which in turn, is essential to proper immune function as evidenced by the observation that healthy infants who were exclusively breast-fed had better overall antioxidant capacity than their contemporaries who were fed formula only (51). Given this observation and the proposed hypothesis that increased oxidative stress 56 Simpson and Norris may result in type 1 diabetes, one might expect to see a protective effect with breast-feeding, particularly longer durations of breast-feeding, on type 1 diabetes and IA. However, the results concerning longer duration of breast-feeding and diabetes or autoimmunity are equivocal. The lack of a clear relationship may suggest that early infancy, the time when breast-feeding is most likely to occur, is not the most important time for exposure to the antioxidants found in breast milk, at least with respect to the etiology of type 1 diabetes. It is also possible that endogenous antioxidants are more important than those acquired through the diet with respect to their role in type 1 diabetes pathogenesis, or that children at increased risk for type 1 diabetes are less able to utilize dietary antioxidants. Besides breast milk there are multiple early-life diet exposures that affect antioxidant status, including vitamin E, fish oils, and vitamin D. Vitamin E, or a-tocopherol, is a powerful antioxidant that is important in the control of lipid peroxidation, a marker of oxidative stress. Lipids are one of the basic cellular building blocks and are the molecules that maintain normal membrane receptor and transport function as well as normal membrane fluidity. In addition, when lipid peroxidation occurs, abnormalities in the outer lipid membrane can result in death of the cell and a subsequent immune response. Two Finnish studies examined whether serum a-tocopherol levels were associated with type 1 diabetes. In the first study, investigators identified 19 type 1 diabetic cases developing within a cohort of 7526 men initially examined at age 20 or older. The diabetic cases, with an average age at onset of 28 years, had sig- nificantly lower serum a-tocopherol levels at baseline than healthy age-matched controls (52). In the second study, siblings of type 1 diabetic individuals were followed prospectively for the development of type 1 diabetes. The siblings who progressed to type 1 diabetes had lower serum a-tocopherol levels than the siblings who remained autoantibody negative, although these results were only marginally significant (53). These studies suggest that vitamin E may in some way be pro- tective against type 1 diabetes. Even though fish oil is not an antioxidant itself, it has been shown to increase antioxidant enzyme activity. In a case-control study from Norway, use of cod liver oil supplements in the first year of life was associated with a lower risk of devel- oping type 1 diabetes (28). The same study found no association between maternal use of fish oil supplements during pregnancy and diabetes in their children. Fronczak et al. found similar negative results when they prospectively investigated the association between in utero exposure to dietary n-3 PUFA and the risk of IA (54). These findings suggest that the most pronounced benefits come from direct exposure to the infant. Vitamin D possesses immune modulating properties that may provide pro- tection against type 1 diabetes. The protective effect may be through the relation- ship between oxidative reactions and the balance between Th1 and Th2 cellular responses. The redox status of macrophages (e.g., dendritic cells in the intestine) dictates the type of cytokines that are secreted and therefore the type of helper cell response elicited. If a macrophage has decreased antioxidant capacity then the balance of cytokines is shifted preferentially to a Th1 response (55). Since vitamin D has been shown to help shift the balance back toward the regulatory characteristics of the Th2 response, its role in immunological repair may be one of its mechanisms of action (56). Multiple studies have examined the role of vitamin D in the pathogenesis of type 1 diabetes. The EURODIAB multicenter case-control study found that diabetic Early-Life Diet and Risk of Type 1 Diabetes 57 25. MacFarlane AJ, Burghardt KM, Kelly J, et al. A type 1 diabetes-related protein from wheat (Triticum aestivum). cDNA clone of a wheat storage globulin, Glb1, linked to islet damage. J Biol Chem 2003; 278(1):54–63. 26. Ivarsson A, Hernell O, Stenlund H, et al. Breast-feeding protects against celiac disease. Am J Clin Nutr 2002; 75(5):914–921. 27. Singh VK, Mehrotra S, Agarwal SS. The paradigm of Th1 and Th2 cytokines: its rele- vance to autoimmunity and allergy. Review. Immunol Res 1999; 20(2):147–161. 28. Stene LC, Joner G. Norwegian Childhood Diabetes Study Group. Use of cod liver oil during the first year of life is associated with lower risk of childhood-onset type 1 diabetes: a large, population-based, case-control study [see comment]. Am J Clin Nutr 2003; 78(6):1128–1134. 29. Giulietti A, Gysemans C, Stoffels K, et al. Vitamin D deficiency in early life accelerates Type 1 diabetes in non-obese diabetic mice. Diabetologia 2004; 47(3):451–462. 30. Gregori S, Giarratana N, Smiroldo S, et al. A 1alpha,25-dihydroxyvitamin D(3) analog enhances regulatory T-cells and arrests autoimmune diabetes in NOD mice. Diabetes 2002; 51(5):1367–1374. 31. Kleemann R, Scott FW, Worz-Pagenstert U, et al. Impact of dietary fat on Th1/ Th2 cytokine gene expression in the pancreas and gut of diabetes-prone BB rats. J Autoimmun 1998; 11(1):97–103. 32. Hughes DA, Pinder AC. n-3 polyunsaturated fatty acids inhibit the antigen-presenting function of human monocytes. Am J Clin Nutr 2000; 71(1 suppl):357S–360S. 33. Liu Z, Li N, Neu J. Tight junctions, leaky intestines, and pediatric diseases. Acta Paediatr 2005; 94(4):386–393. 34. Neu J, Reverte CM, Mackey AD, et al. Changes in intestinal morphology and perme- ability in the biobreeding rat before the onset of type 1 diabetes. J Pediatr Gastroenterol Nutr 2005; 40(5):589–595. 35. Courtois P, Nsimba G, Jijakli H, et al. Gut permeability and intestinal mucins, invertase, and peroxidase in control and diabetes-prone BB rats fed either a protective or a dia- betogenic diet. Dig Dis Sci 2005; 50(2):266–275. 36. Courtois P, Jurysta C, Sener A, et al. Quantitative and qualitative alterations of intestinal mucins in BioBreeding rats. Int J Mol Med 2005; 15(1):105–108. 37. Malaisse WJ, Courtois P, Scott FW. Insulin-dependent diabetes and gut dysfunction: the BB rat model. Review. Horm Metab Res 2004; 36(9):585–594. 38. Secondulfo M, Iafusco D, Carratu R, et al. Ultrastructural mucosal alterations and increased intestinal permeability in non-celiac, type I diabetic patients. Dig Liver Dis 2004; 36(1):35–45. 39. Catassi C, Bonucci A, Coppa GV, et al. Intestinal permeability changes during the first month: effect of natural versus artificial feeding. J Pediatr Gastroenterol Nutr 1995; 21(4):383–386. 40. Kuitunen M, Savilahti E, Sarnesto A. Human alpha-lactalbumin and bovine beta- lactoglobulin absorption in infants. Allergy 1994; 49(5):354–360. 41. Lawrence RM, Pane CA. Human breast milk: current concepts of immunology and infectious diseases. Review. Curr Probl Pediatr Adolesc Health Care 2007; 37(1):7–36. 42. Lammi N, Karvonen M, Tuomilehto J. Do microbes have a causal role in type 1 diabetes? Med Sci Monit 2005; 11(3):RA63–RA69. 43. Ylipaasto P, Klingel K, Lindberg AM, et al. Enterovirus infection in human pancreatic islet cells, islet tropism in vivo and receptor involvement in cultured islet beta cells. Diabetologia 2004; 47(2):225–239. 44. Vaarala O, Klemetti P, Juhela S, et al. Effect of coincident enterovirus infection and cow’s milk exposure on immunisation to insulin in early infancy. Diabetologia 2002. 45(4):531–534. 45. Fasano A. Intestinal zonulin: open sesame! Gut 2001; 49(2):159–162. 46. Watts T, Berti I, Sapone A, et al. Role of the intestinal tight junction modulator zonulin in the pathogenesis of type I diabetes in BB diabetic-prone rats. Proc Natl Acad Sci U S A 2005; 102(8):2916–2921. 60 Simpson and Norris 47. Sapone A, de Magistris L, Pietzak M, et al. Zonulin upregulation is associated with increased gut permeability in subjects with type 1 diabetes and their relatives. Diabetes 2006; 55(5):1443–1449. 48. Martin-Gallan P, Carrascosa A, Gussinye M, et al. Estimation of lipoperoxidative damage and antioxidant status in diabetic children: relationship with individual anti- oxidants. Free Radic Res 2005; 39(9):933–942. 49. Matteucci E, Giampietro O. Oxidative stress in families of type 1 diabetic patients. Diabetes Care 2000; 23(8):1182–1186. 50. Friel JK, Martin SM, Langdon M, et al. Milk from mothers of both premature and full- term infants provides better antioxidant protection than does infant formula. Pediatr Res 2002; 51(5):612–618. 51. Aycicek A, Erel O, Kocyigit A, et al. Breast milk provides better antioxidant power than does formula. Nutrition 2006; 22(6):616–619. 52. Knekt P, Reunanen A, Marniemi J, et al. Low vitamin E status is a potential risk factor for insulin-dependent diabetes mellitus. J Intern Med 1999; 245(1):99–102. 53. Uusitalo L, Knip M, Kenward MG, et al. Serum alpha-tocopherol concentrations and risk of type 1 diabetes mellitus: a cohort study in siblings of affected children. J Pediatr Endocrinol 2005; 18(12):1409–1416. 54. Fronczak CM, Baron AE, Chase HP, et al. In utero dietary exposures and risk of islet autoimmunity in children. Diabetes Care 2003; 26(12):3237–3242. 55. Murata Y, Amao M, Hamuro J. Sequential conversion of the redox status of macro- phages dictates the pathological progression of autoimmune diabetes. Eur J Immunol 2003; 33(4):1001–1011. 56. Mathieu C, Badenhoop K. Vitamin D and type 1 diabetes mellitus: state of the art. Trends Endocrinol Metab 2005; 16(6):261–266. 57. The EURODIAB Substudy 2 Study Group. Vitamin D supplement in early childhood and risk for Type I (insulin-dependent) diabetes mellitus. Diabetologia 1999; 42(1):51–54. 58. Hypponen E, Laara E, Reunanen A, et al. Intake of vitamin D and risk of type 1 diabetes: a birth-cohort study. Lancet 2001; 358(9292):1500–1503. 59. Kostraba JN, Gay EC, Rewers M, et al. Nitrate levels in community drinking waters and risk of IDDM. An ecological analysis. Diabetes Care 1992; 15(11):1505–1508. 60. Parslow RC, McKinney PA, Law GR, et al. Incidence of childhood diabetes mellitus in Yorkshire, northern England, is associated with nitrate in drinking water: an ecological analysis [see comment]. Diabetologia 1997; 40(5):550–556. 61. Virtanen SM, Jaakkola L, Rasanen L, et al. Nitrate and nitrite intake and the risk for type 1 diabetes in Finnish children. Childhood Diabetes in Finland Study Group. Diabet Med 1994; 11(7):656–662. 62. Dahlquist GG, Blom LG, Persson LA, et al. Dietary factors and the risk of developing insulin dependent diabetes in childhood. BMJ 1990; 300(6735):1302–1306. Early-Life Diet and Risk of Type 1 Diabetes 61 population in developed countries are daily exposed to gluten-containing cereals, but in spite of that only maximally 1.3% of the population present with clinical disease (16). Accordingly, some other factor(s) in addition to HLA-conferred pre- disposition and daily gluten intake are needed for progression to overt celiac disease. It seems unlikely that non-HLA genes should totally account for the missing link, and it is tempting to speculate that one may need a triggering gastrointestinal infection inducing a primary target cell damage and/or a proinflammatory cytokine milieu in the gut epithelium to initiate the disease process subsequently driven by dietary gluten toward clinical celiac disease in genetically predisposed individuals. Previous studies have indicated that adenovirus and rotavirus infections might contribute to the pathogenesis of celiac disease (17–19), but only a few studies have focused on the possible role of viruses and other microbes in this disease. In parallel to celiac disease, about one-fifth of Caucasians carry HLA- conferred susceptibility to type 1 diabetes, whereas the lifetime cumulative inci- dence of clinical disease can be estimated to be close to 1%, indicating that only about 5% of those with HLA-conferred predisposition progress to overt diabetes. Our hypothesis holds that progression to clinical diabetes requires the combination of genetic disease susceptibility, a critically timed trigger, and high subsequent exposure to a driving antigen (1). If any of these determinants is missing or any of the exogenous factors is inappropriately timed, the risk of type 1 diabetes would be minimal even in the presence of the other predisposing elements. Such a model could explain why only a small minority of those with HLA-conferred diabetes susceptibility do present with overt disease. In addition to the trigger and the driving antigen there are most likely a series of environmental factors modifying the fate and pace of the b-cell destructive process, some having protective and others predisposing effects. VIRAL INFECTIONS Viral infections have been implicated in the etiology of type 1 diabetes for more than 100 years. More recently, a variety of studies have been published showing that certain viruses, such as enteroviruses (EV), are capable of inducing diabetes in experimental animals, and seroepidemiological studies have indicated their role in human type 1 diabetes as well (5,20). Table 1 lists viruses suspected to contribute to the diabetic disease process. Viruses may act by at least two pos- sible mechanisms, either via a direct cytolytic effect or by triggering an auto- immune process leading gradually to b-cell destruction (21). The role of molecular mimicry in diabetes-associated autoimmune responses has been indicated by the observations of structural and functional homology between viral structures and b-cell antigens. Persistent or slow virus infections, like in the congenital rubella syndrome (CRS) and cytomegalovirus (CMV) infections, may also be important in the induction of the autoimmune response. The role of viral infections in the etiopathogenesis of human type 1 diabetes has been elucidated by serological and epidemiological studies and case histories (22). Three key hypotheses for the role of viruses in the development of type 1 diabetes are presented in Figure 1. Environmental Determinants: The Role of Viruses and Standard of Hygiene 65 FIGURE 1 Three key hypotheses describing various stages of virus-induced diabetes. The virus hypothesis is based on an assumption that certain viruses have strong tropism to pancreatic islets. These viruses target to pancreatic islets and trigger the autoimmune process by damaging b cells and activating dendritic cells to present b-cell autoantigens to T cells. The polio hypothesis is related to immune protection against these viruses. This protection depends on individual characteristics (e.g., genetic factors) as well as population-dependent factors that are related to the dynamic bal- ance between virus circulation and herd immunity in a given population (maternal antibodies transferred to the infant, in particular). The third hypothesis, the hygiene hypothesis, was first pro- posed to explain the increasing incidence of allergic diseases, and recent observations suggest that it may also be relevant for autoimmune diseases, such as type 1 diabetes. Accordingly, viruses and other microbes are important for the development of immune regulatory networks controlling the autoimmune process. The scarcity of this kind of microbial exposure may lead to inability to down- regulate immune responses against self and foreign antigens (allergens). TABLE 1 Viruses Implicated in the Pathogenesis of Type 1 Diabetes. Virus Family Size (nm) Enteroviruses Picornavirus 30 Mumps Paramyxovirus 100–600 Rubella Togavirus 60–70 Cytomegalovirus Herpesvirus 120–300 Rotavirus Reovirus 100 Ljungan virus Picornavirus 30 Retroviruses Retrovirus 100 66 Knip and Hyöty EV EV belong to the picornavirus family comprising small, naked icosahedral RNA viruses. The EV genus comprises a series of subgroups that have been formed according to their antigenic properties and, more recently, according to their genetic relationships. Traditional antigenic classification includes the groups of polioviruses, coxsackie B viruses (CBV), coxsackie A viruses (CAV), echoviruses, and new numbered serotypes including altogether more than 100 distinct sero- types. Epidemiological, serological, and biological indications suggest that EV may be involved in the pathogenesis of type 1 diabetes (20,23,24). Infections with dif- ferent serotypes are common, starting in infancy. The virus frequently causes viremia and spreads to many organs including the pancreas. Most of these infec- tions are mild and subclinical. The role of EV in the pathogenesis of type 1 diabetes have been strengthened over the last 10 to 20 years, one reason being methodological developments in the diagnosis of EV infections and the other insight that the diabetic disease process starts months and years before the clinical presentation of the disease requiring prospective studies to identify potential triggers and boosters of the process. Gamble and Taylor (25) reported in 1969 parallel changes in the seasonal variation in the incidence of type 1 diabetes and in the frequency of CBV infections. A series of serological case-control studies have shown an increased prevalence of elevated levels of CBV antibodies in patients with newly diagnosed type 1 diabetes (23,24). There are, however, also contradictory results, since some other reports have been unable to find any difference between patients with diabetes and controls (26,27) or even demonstrated decreased levels of CBV antibodies in patients (28). The first serological studies measured neutralizing EV antibodies that are good markers of infection immunity but poor indicators of a recent infection, if the analyses do not include IgM antibodies. More recent studies have assessed the occurrence of recent or current EV infections by quantifying IgM antibodies with m-antibody capture methods based on enzyme or radioimmunoassays. With such a methodology patients with newly diagnosed type 1 diabetes were found to have increased IgM class antibodies against EV suggesting an excess of recent infections (29). A Swedish group detected IgM class antibodies to CBV in 40% of children with newly diagnosed type 1 diabetes and in none of the controls (30). The majority of those, who had IgM class antibodies at the diagnosis of diabetes, had experi- enced previously an EV infection caused by a different serotype, indicated by IgG class antibodies (31). As increased IgM titers reflect an ongoing or recent infection, Fohlman and Friman concluded that these observations suggest that successive infections by different CBV and other EVs increase the risk of manifestation of overt diabetes in genetically susceptible individuals. Such a process fits well into the ‘‘Copenhagen model’’ for the pathogenesis of type 1 diabetes, i.e., the multiple hit hypothesis (32). The use of polymerase chain reaction (PCR) methodology has enabled the detection of viruses by molecular methods from serum, whole blood, or mono- nuclear cells with high sensitivity, thus circumventing the indirect approach through antibody-based analyses. An additional advantage is that these methods can be extended to delineate virus nucleotide sequences. Studies from six different countries show an increased frequency of EV detected with PCR from the peripheral circulation in subjects with newly diagnosed type 1 diabetes (Table 2) (33–43). The prevalence of EV mRNA varied from 20% to 64% among the patients Environmental Determinants: The Role of Viruses and Standard of Hygiene 67 Could a Diabetogenic Enterovirus Infection Qualify as a Trigger of Type 1 Diabetes? As mentioned earlier, the first signs of b-cell autoimmunity may appear very early in life. The authors have focused their research on defining the characteristics of the trigger(s) of b-cell autoimmunity by observing subjects with increased HLA- conferred diabetes susceptibility prospectively from birth with frequent follow-up visits with an interval of 3 to 6 months up to the age of 2 years and thereafter with an interval of 6 to 12 months (64). These studies have revealed that there is an unequivocal temporal variation in the appearance of the first diabetes-associated autoantibodies reflecting the initiation of the disease process and paralleling the seasonal variation previously observed in the presentation of clinical diabetes (9,65). Most initial autoantibodies appear during the cold period in the fall and winter while rarely in the spring or in the summer. There also seems to be some variation from one year to another in the timing and height of the autoantibody peaks. When studying families with more than one child experiencing seroconversion to auto- antibody positivity, we have noticed that the autoantibodies rarely appear simulta- neously in seroconverting siblings (66). The first autoantibodies do emerge, however, more often than expected during the same season among such siblings but infre- quently in the same year. On the basis of these observations we conclude that the trigger of b-cell autoimmunity (1) has a seasonal pattern, being more common during the cold season; (2) shows some temporal variation from year to year; and (3) does not necessarily induce b-cell autoimmunity at the same time in all genetically susceptible siblings within the same family. On the basis of the characteristics listed above, some exogenous factors implicated as potential triggers of b-cell autoimmunity may be excluded. These include exogenous factors with a stable or consistently increasing exposure, such as most dietary components in early childhood. The pattern of autoantibody appearance strongly points to the role of infectious agents with conspicuous sea- sonal variation as triggers of b-cell autoimmunity. Such variations are typical for viral infections, and the pattern of laboratory confirmed EV infections in Finland fits well into the proposed role of EV infections as triggers of b-cell autoimmunity. In addition to viral infections, one should also consider other environmental var- iables with seasonal variation. There is definitely seasonal variation in the amount of daylight and sunshine hours, especially in Northern Europe, the region with the highest incidence of type 1 diabetes in the world (67). Without oral substitution, the sun light-dependent synthesis of vitamin D in the skin is the most important source of this immunologically active hormone. Some studies have indicated that the lack of oral vitamin D substitution in infancy increases the subsequent risk of type 1 diabetes (68,69). The following two arguments do, however, speak against the role of vitamin D deficiency as a trigger of b-cell autoimmunity: (1) there is a general recommendation that all young children should be substituted with daily vitamin D drops in Northern Europe, and this recommendation is implemented by more than 95% of the parents at least up to the age of two years; and (2) there are regions with a low incidence of type 1 diabetes in Northern Europe, e.g., Russian Karelia having an annual incidence rate of 7.8 per 100,000 children under the age of 15 years in the time period 1990–1999 compared with that of 42 in Finland (70), while there were no significant differences in the circulating vitamin D concen- trations in pregnant women and schoolchildren between Russian Karelia and Finland (71). It has been shown that the mean HbA1c level varies over the year in children with manifest type 1 diabetes, with the highest values in the fall and 70 Knip and Hyöty winter and with lower levels in the spring and summer (72–74). This may reflect improved insulin sensitivity in the spring and summer due to more physical exercise. Improved insulin sensitivity diminishes b-cell stress, as the work load on the b-cells decreases. It is, however, unlikely that there should be substantial sea- sonal variation in the physical exercise in very young children, the target group in whom the seasonal variation in the appearance of the first diabetes-associated autoantibodies have been observed. Accordingly we are left with viral infections as the most likely explanation to the seasonal variation in the emergence of the first signs of b-cell autoimmunity. Taking into account the timing and profiles of autoantibody peaks observed in the Finnish DIPP study, EV infections appear to be one of the most probable triggers of b-cell autoimmunity. This is further supported by our previous observations of a strong temporal relationship between EV infections and the appearance of the first diabetes-associated autoantibodies in prospective series of young children with increased genetic susceptibility to type 1 diabetes (44–48). The implicated link between EV infections and b-cell autoimmunity has been questioned, since most of the supportive data have come out of Finnish studies, and two other prospective studies, i.e., BABYDIAB in Germany and the Diabetes Autoimmunity Study in the Young (DAISY) in Denver, Colorado, have failed to demonstrate any association between EV infections and b-cell autoimmunity (49,50). There are, however, at least three critical issues with a decisive impact on the ability of any prospective study to provide meaningful observations in this context. The first one is the size of the study and the number of subjects who develop signs of b-cell autoimmunity; fac- tors clearly related to the statistical power of the study (75). Each prospective study has so far included less than 50 seroconverters, which confers a high risk of missing even major influences of EV infections on b-cell autoimmunity. A second critical consideration is the study design and the sampling interval. Long sampling intervals definitely hamper the possibility to detect EV infections from collected samples. In the BABYDIAB study, coxsackie virus antibodies were measured from serum samples taken at the age of 9 months, 2 years, 5 years, and 8 years, and in DAISY, the samples were obtained at the age of 9 months, 15 months, 2 years, and then annually. In contrast, the DIPP study has a more frequent sampling schedule collecting samples with an interval of 3 to 6 months over the first 2 years of life and subsequently with an interval of 6 to12 months. The third crucial point is related to the type of samples collected and the methodological arsenal used for the detection of EV infections, taking into account that there are more than 100 different sero- types. The DIPP study used the most extensive strategy including detection of EV RNA with PCR from serum and stool samples, and analysis of IgA, IgM, and IgG class EV antibodies using both group- and serotype-specific assays. The impact of these differences are reflected by the substantially lower frequency of infections diagnosed, e.g., in the BABYDIAB cohort compared with the DIPP study (7% vs. 81% of the children had an EV infection by the age of 2 years). It is unlikely that such a difference could be due to a lower frequency of EV infections in Germany, as EV infections actually seem to be more common in the background population in Germany than in Finland (76). The frequency of EV infections has decreased over the last decades in the background population in developed countries, e.g., in Finland and Sweden (76). These countries have in spite of that a high and increasing incidence of type 1 diabetes among children. This appears to be paradoxical. The paradox can, however, be explained by the so called ‘‘poliohypothesis’’ introduced by Viskari et al. (77). The Environmental Determinants: The Role of Viruses and Standard of Hygiene 71 polioviruses comprise three serotypes among more than 100 EV serotypes. When the frequency of acute poliovirus infections started to decrease at the beginning of the last century among the general population in countries with an increasing standard of hygiene, the incidence of paralytic polio being a complication of the acute infection began to increase. This was obviously the consequence of the concerted action of decreased levels of protective maternal poliovirus antibodies transferred transplacentally and through breastmilk to the infant and the delay of infections to the age when the maternal antibodies had already declined, leading to a situation where the risk of the infant to get the first poliovirus infection at the time when no maternal protection was around increased. In the absence of maternal neutralizing antibodies, poliovirus was able to spread from the intestine to the blood and then to the central nervous system where it has strong tropism to motoneurons leading to their damage and subsequent paralysis. Similarly, the decreasing frequency of EV infections in the background population would increase the susceptibility of young children to the diabetogenic effect of EVs. The same phenomenon may also contribute to the marked international variation in the incidence of type 1 diabetes, as EV infections seem to be rare in countries where the rate of type 1 diabetes is high (77). Other Viruses Mumps Gundersen (78), in his classical study in 1927, reported an increase in the number of cases with type 1 diabetes two to four years after a mumps epidemic. Subsequently, there have been numerous case reports describing a temporal relationship between mumps and clinical presentation of diabetes (4). In epidemiological studies, peaks in the incidence of childhood type 1 diabetes have been observed two to four years after mumps epidemics. Serological evidence of an association between mumps infection and type 1 diabetes has been difficult to obtain because of the long interval between the infection and the clinical manifestation of type 1 diabetes. A Finnish study reported decreased IgG class mumps antibody titers in children with newly diagnosed type 1 diabetes compared with those in controls, the finding being interpreted as indicative of an abnormal immunological response to mumps infection (79). Interestingly, in patient series collected earlier, when natural mumps was still common in Finland, IgG class mumps virus antibodies were not decreased, and IgA antibodies were elevated in diabetic children. This decline in mumps antibody levels may reflect the elimination of cases with mumps-induced type 1 diabetes by the triple vaccine comprising mumps, measles, and rubella. Rubella Diabetes has been observed in 10–20% of patients with the CRS with a latent period of 5 to 25 years (4). However, a recent study showed that signs of humoral b-cell autoimmunity are extremely rare among patients with the CRS, indicating that CRS- associated diabetes may be caused by other than autoimmune mechanisms (80). CMV The human CMV can be transmitted before birth, like the rubella virus, either transplacentally or at conception from an infected parent carrying the CMV genome in his or her genomic DNA. CMV infections may also be transmitted prenatally or postnatally through close contact or breast milk. CMV has been implicated in the development of type 1 diabetes by a case report of an infant with congenital CMV 72 Knip and Hyöty may play a role in the development of virus-induced tissue pathology and the eradication of the virus (107). From an immunological point of view, the mechanisms behind the devel- opment of organ-specific autoimmune disorders and allergy represent the antip- odes of each other. In organ-specific autoimmune diseases, autoreactive T cells are assumed to attack and destroy the target tissue, while allergic disorders are char- acterized by a strong humoral immune response including IgE antibodies against environmental antigens, i.e., allergens. Accordingly, organ-specific autoimmune disorders are perceived as a Th1-polarized process, and allergic diseases as a Th2- biased condition. Although this is likely an oversimplification of biologically multifaceted disease processes, where regulatory T cells are strongly involved, there are observations indicating that allergic diseases are less frequent in patients with an organ-specific autoimmune disease than in unaffected subjects (108,109). Hence, it is intriguing that both autoimmune disorders and allergic diseases have become more and more common in parallel over the last half of the 20th century in populations with increasing prosperity and improving standard of hygiene. A series of evidence suggest that the maturation of the immune system over the first few years of life is an important determinant of autoimmune and allergic diseases. The first signs of b-cell autoimmunity preceding the progression to clinical type 1 diabetes emerge already in infancy (8,9), and similarly, infants are affected by allergic diseases such as food allergy presenting with gastrointestinal, respiratory, and/or cutaneous symptoms. Microbial infections are thought to be important in this maturation process and certain degree of exposure to microbial agents may be needed for the development of a proper balance and regulation of the Th1- and Th2-type immune responses. Several studies have implicated that early childhood infections may be linked to decreased risk of allergic diseases (110,111). In the United States, serologic evidence of acquisition of certain infec- tions, mainly food-borne and orofecal infections, is associated with a reduced likelihood of presenting with hay fever and asthma later in life (112). The effect of microbes might be very complex. Certain viral infections may predispose to these diseases, e.g., respiratory syncytial virus and rhinoviruses may increase the risk of asthma or precipitate its symptom, while other viruses may protect from the same diseases, as hepatitis A virus seem to protect from asthma. Thus, the evaluation of the role of microbes, their mutual interactions, and interactions with host susceptibility genes and other host-related factors in the pathogenesis of these diseases is complicated. A series of genes regulate the indi- vidual susceptibility to type 1 diabetes and allergy, and many of them are known to be involved in the resistance to microbial infections and to play a role in the infectious process. The commensal microflora may also contribute to the matura- tion of the immune system in infants and young children (113). Recent Data in Favor of the Hygiene Hypothesis The Karelian Republic of the Russian Federation is an area immediately east of Finland with a total population of approximately 720,000 inhabitants. One of the steepest gradients in standard of living worldwide is present at the border between Russian Karelia and Finland with a sevenfold difference in the gross national product. Accordingly, these two populations comprise a ‘‘living laboratory’’ pro- viding a unique possibility to test the hygiene hypothesis and gene-environment interactions in the development of immune-mediated diseases. Environmental Determinants: The Role of Viruses and Standard of Hygiene 75 Recent studies have shown that there are substantial differences in the fre- quency of allergy between Russian Karelia and Finland both among schoolchildren and adults. Skin prick tests (SPT) among seven- to nine-year-old schoolchildren revealed that SPT positivity to birch and cat was about three times more frequent in Finland (114). In a population based study of two generations von Herzen et al. showed that SPT positivity to airborne and food allergens were less common both among schoolchildren and their mothers in Russian Karelia compared with their counterparts in Finland (115). In our own studies we have observed that the inci- dence rate of type 1 diabetes among children under the age of 15 years was almost six times lower in Russian Karelia than in Finland (7.4 vs. 41.4/100,000 children) over a 10-year time period (1990–1999) (Fig. 2A) (70). There was no significant difference in the frequency of HLA DQ genotypes conferring type 1 diabetes susceptibility or protection between Finland and Russian Karelia strongly sug- gesting that lifestyle and/or environmental factors must be major contributors to the steep difference in the incidence rate of type 1 diabetes between these two areas. In another study we analyzed the frequency of diabetes-associated auto- antibodies, i.e., ICA, IAA, GADA, and IA-2A. There was no difference in the fre- quency of ICA, IAA, or GADA between the two populations, but Finnish schoolchildren often tested about four times more positive for IA-2A, which usu- ally appears as the last autoantibody reactivity during the preclinical disease process. The data suggest that signs of b-cell autoimmunity are induced as frequently in children in Russian Karelia as in Finland. However, the Karelian children seem to be characterized by a less frequent and/or retarded progression in their prediabetic disease process (116). These findings indicate that the Russian Karelian environment and/or lifestyle are less diabetogenic than that in Finland. In the same series we observed that Finnish schoolchildren tested positive for celiac disease-associated tissue transglutaminase autoantibodies 2.5 times more frequently than Karelian children (Fig. 2B) (117). This implies that celiac disease- associated autoimmunity is more than two times more frequent in Finland than in Russian Karelia. This difference was confirmed by small bowel biopsies carried out from subjects positive for transglutaminase antibodies in both countries. The prevalence of biopsy-proven celiac disease was one in 496 children in Karelia compared with one in 107 children in Finland. Autoantibodies to the thyroid gland were also about six times less frequent among schoolchildren in Russian Karelia compared with their Finnish peers. The fact that the studied populations share partly the same ancestry and that the frequency of HLA genes predisposing to autoimmune diseases is quite similar suggests that environmental and life-style associated factors play a major role in the development of thyroid autoimmunity (118). Total and allergen-specific IgE were measured in 350 children in Finland and in 350 children of Finnish-Karelian ancestry in Russian Karelia. Karelian school- children had significantly higher concentrations of total IgE than their Finnish counterparts, which may reflect an increased exposure to parasite infections in Russian Karelia. In contrast the Finnish schoolchildren had significantly higher levels of birch and cat-specific IgE suggesting increased allergic sensitization to these common allergens in Finland. Altogether allergic sensitization to these allergens was detected in 22% of the children in Finland compared with 6 % of the children in Russian Karelia (Fig. 2C; p < 0.001) (119). In the same study we com- pared the frequency of signs of several microbial infections in 7- to 14-year-old children in Russian Karelia and in Finland. EV antibodies were analyzed as an 76 Knip and Hyöty indicator of exposure to one plausible trigger of b-cell autoimmunity. In addition, Helicobacter pylori, hepatitis A virus, and Toxoplasma gondii antibodies were mea- sured as indicators of the microbial load. All these microbial infections were sig- nificantly more frequent in Russian Karelia than in Finland (Fig. 2D–F) (119). In addition, some of the microbes, EV in particular, were associated with decreased risk of IgE-mediated allergic sensitization. These findings are in line with the hygiene hypothesis and suggest that the conspicuous difference in microbial exposures between the two countries may partly explain the higher incidence of type 1 diabetes and allergy in Finland. This is also consistent with our observations in other countries suggesting that a clean environment and a low frequency of EV infections may increase the risk of type 1 diabetes by reducing the levels of pro- tective maternal antibodies and thereby making the infants more susceptible for such infections (120). How to Test the Hygiene Hypothesis in Type 1 Diabetes? All the studies referred to in the section above have been performed either in school- children or young adults. Accordingly, they are not able to address early events in the disease process, which in type 1 diabetes and most other immune-mediated diseases FIGURE 2 The mirror image of autoimmunity/allergy and infectious diseases among schoolchildren in Russian Karelia and in Finland. The Russian Karelian children had a sixfold lower incidence of type 1 diabetes over the time period 1990–1999 (A) (70), a 2.5-fold lower prevalence of tissue transglutaminase antibodies (B) (117), and an almost fourfold lower frequency of allergen-specific IgE to cat, birch, and/or egg albumen (C) (119) than their Finnish peers, whereas they had a 15-fold higher prevalence of Helicobacter pylori antibodies, (D), a 12-fold higher prevalence of hepatitis A antibodies (E), and a fivefold higher prevalence of Toxoplasma gondii antibodies (F) than the Finnish schoolchildren (119). Environmental Determinants: The Role of Viruses and Standard of Hygiene 77 7. Knip M. Can we predict type 1 diabetes in the general population? Diabetes Care 2002; 25:623–625. 8. Ziegler AG, Hummel M, Schenker M, et al. Autoantibody appearance and risk for development of childhood diabetes in offspring of parents with type 1 diabetes: the 2-year analysis of the German BABYDIAB Study. Diabetes 1999; 48:460–468. 9. 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