Islet cell autoimmunity in a triethnic adult population of the Third National Health and Nutrition Examination Survey

The role of autoimmunity in the pathophysiology of type 2 diabetes: Looking at the other side of the moon

Efforts to unravel the pathophysiological mechanisms of type 2 diabetes (T2D) have been traditionally trapped into a metabolic perspective. However, T2D is a phenotypically and pathophysiologically heterogenous disorder, and the need for a tailored approach in its management is becoming increasingly evident. There is emerging evidence that irregular immune responses contribute to the development of hyperglycemia in T2D and, inversely, that insulin resistance is a component of the pathogenesis of autoimmune diabetes. Nevertheless, it has not yet been fully elucidated to what extent the presence of conventional autoimmune markers, such as autoantibodies, in subjects with T2D might affect the natural history of the disease and particularly each response to various treatments. The challenge for future research in the field is the discovery of novel genetic, molecular, or phenotypical indicators that would enable the characterization of specific subpopulations of people with T2D who would benefit most from the addition of immunomodulatory therapies to standard glucose-lowering treatment. This narrative review aims to discuss the plausible mechanisms through which the immune system might be implicated in the development of metabolic disturbances in T2D and obesity and explore a potential role of immunotherapy in the future management of the disorder and its complications.

Predictive Value of GAD Antibody for Diabetes in Normal Chinese Adults: A Retrospective Cohort Study in China

PURPOSE

To investigate the prevalence of GAD antibody (GADA) in the general adult population and to evaluate its predictive value for diabetes in China.

PATIENTS AND METHODS

We searched the PUMCH-HM database and identified 36,731 adult subjects with GADA test results from 2012 to 2015. We then established a retrospective cohort of 4835 nondiabetic subjects at baseline with complete annual health evaluation records through 2019. The median follow-up time was 4.8 (3.0-7.3) years.

RESULTS

The overall prevalence of GADA was 0.53% and was higher in diabetic subjects (1.25%) than in nondiabetic subjects (0.47%). We found a decrease in baseline body mass index (BMI) from the GADA- to GADA_high subgroups among baseline diabetic and prediabetic patients and also those who developed diabetes later in the cohort study. A total of 136 subjects (2.8%) developed diabetes after a median follow-up of 3.5 years. For GADA⁺ participants, BMI was not associated with the risk for diabetes. In the Cox regression model, the GADA_low and GADA_high exhibited 2.63-fold and 4.16-fold increased risk for diabetes, respectively. This increased risk for diabetes by GADA-positivity is only found in male adults (HR 4.55, 95% CI 2.25-9.23).

CONCLUSION

GADA has a low prevalence in China but is associated with a 2.63-4.16-fold increased risk for diabetes.

Management of Latent Autoimmune Diabetes in Adults: A Consensus Statement From an International Expert Panel

A substantial proportion of patients with adult-onset diabetes share features of both type 1 diabetes (T1D) and type 2 diabetes (T2D). These individuals, at diagnosis, clinically resemble T2D patients by not requiring insulin treatment, yet they have immunogenetic markers associated with T1D. Such a slowly evolving form of autoimmune diabetes, described as latent autoimmune diabetes of adults (LADA), accounts for 2-12% of all patients with adult-onset diabetes, though they show considerable variability according to their demographics and mode of ascertainment. While therapeutic strategies aim for metabolic control and preservation of residual insulin secretory capacity, endotype heterogeneity within LADA implies a personalized approach to treatment. Faced with a paucity of large-scale clinical trials in LADA, an expert panel reviewed data and delineated one therapeutic approach. Building on the 2020 American Diabetes Association (ADA)/European Association for the Study of Diabetes (EASD) consensus for T2D and heterogeneity within autoimmune diabetes, we propose "deviations" for LADA from those guidelines. Within LADA, C-peptide values, proxy for β-cell function, drive therapeutic decisions. Three broad categories of random C-peptide levels were introduced by the panel: 1) C-peptide levels <0.3 nmol/L: a multiple-insulin regimen recommended as for T1D; 2) C-peptide values ≥0.3 and ≤0.7 nmol/L: defined by the panel as a "gray area" in which a modified ADA/EASD algorithm for T2D is recommended; consider insulin in combination with other therapies to modulate β-cell failure and limit diabetic complications; 3) C-peptide values >0.7 nmol/L: suggests a modified ADA/EASD algorithm as for T2D but allowing for the potentially progressive nature of LADA by monitoring C-peptide to adjust treatment. The panel concluded by advising general screening for LADA in newly diagnosed non-insulin-requiring diabetes and, importantly, that large randomized clinical trials are warranted.

Geographic location determines beta-cell autoimmunity among adult Ghanaians: Findings from the RODAM study

Introduction

Beta‐cell autoantibodies are established markers of autoimmunity, which we compared between Ghanaian adults with or without diabetes, living in rural and urban Ghana and in three European cities.

Methods

In the multicenter cross‐sectional Research on Obesity and Diabetes among African Migrants (RODAM) study (N = 5898), we quantified autoantibodies against glutamic acid decarboxylase (GAD65Ab) by radioligand binding assay (RBA) and established cut‐offs for positivity by displacement analysis. In a subsample, we performed RBA for zinc transporter‐8 autoantibodies (ZnT8Ab). Associations of environmental, sociodemographic, and clinical factors with GAD65Ab were calculated.

Results

In this study population (age: 46.1 ± 11.9 years; female: 62%; Ghana‐rural: 1111; Ghana‐urban: 1455; Europe: 3332), 9.2% had diabetes with adult‐onset. GAD65Ab concentrations were the highest in Ghana‐rural (32.4; 10.8‐71.3 U/mL), followed by Ghana‐urban (26.0; 12.3‐49.1 U/mL) and Europe (11.9; 3.0‐22.8 U/mL) with no differences between European cities. These distributions were similar for ZnT8Ab. Current fever, history of fever, and higher concentrations of liver enzymes marginally explained site‐specific GAD65Ab concentrations. GAD65Ab positivity was as frequent in diabetes as in nondiabetes (5.4% vs 6.1%; P = .25). This was also true for ZnT8Ab positivity.

Conclusion

Geographic location determines the occurrence of GAD65Ab and ZnT8Ab more than the diabetes status. Beta‐cell autoimmunity may not be feasible to differentiate diabetes subgroups in this population.

Population-based estimates of humoral autoimmunity from the U.S. National Health and Nutrition Examination Surveys, 1960-2014

Objective

Based on US National Health and Nutrition Examination Survey (NHANES) data, we attempted to provide an unbiased, population-based estimate of autoantibody prevalence overall and by age and sex.

Methods

US autoantibody prevalence estimates for detectable rheumatoid factor, anti-thyroglobulin, anti-thyroperoxidase, anti-transglutaminase, anti-endomysial, anti-GAD65, antinuclear autoantibodies, and autoantibodies to extractable nuclear antigens were estimated from the 1960–1962 National Health Examination Survey, NHANES III (1988–1994), and the NHANES 1999–2014 cross-sectional surveys. Survey design variables and sample weights were used to account for differential probabilities of selection within the complex survey design. Data analysis used SAS^TM and SUDAAN^™ software. US Census Bureau data were used to estimate the absolute numbers of persons with autoantibodies.

Results

NHANES III data show that the overall US prevalence of having a detectable serum autoantibody is substantial in adults, in both women and men. Thyroid autoantibodies were present in 18% of US adults (31 million persons) including 10% of younger adults and 25% of older persons. Overall autoantibody prevalences increased significantly with age: 32% of US adults 60+ years of age (12.8 million persons) had at least one of the four autoantibodies rheumatoid factor, anti-thyroglobulin, anti-thyroperoxidase, or anti-tissue transglutaminase. Older women had higher levels of autoantibodies, but this was a relative difference. Autoantibody prevalence in both sexes was substantial (women 39%; men 22%). Fourteen percent of adults 60+ years of age have multiple autoantibodies.

Conclusions

Autoantibodies are present in a significant fraction of the general population, especially in older adults and women relative to men. Although all known clinically significant autoantibodies were not analyzed, these data provide an important population perspective on the scope and magnitude of humoral autoimmunity in the US. This is vital for prevention efforts to reduce autoimmune disease and helps clarify the potential impact of autoimmunity on the general population.

US National Health and Nutrition Examination Survey Arthritis Initiatives, Methodologies and Data

The US National Health and Nutrition Examination Survey (NHANES) has collected population-based, nationally representative examination, laboratory, and radiographic data for arthritis and musculoskeletal diseases for more than 50 years. The resulting body of data and publications are substantial, yet much data remain unpublished. This review provides a basic understanding of the design and capabilities of the NHANES survey, reviewing the major accomplishments in the area of arthritis and musculoskeletal diseases. Currently available US National Health and Nutrition Examination Survey arthritis-related datasets are identified. Guidelines for using these data, and opportunities for data analysis and designing future studies are presented.

Latent Autoimmune Diabetes in Adults: A Review on Clinical Implications and Management

Latent autoimmune diabetes in adults (LADA) is a heterogeneous disease characterized by a less intensive autoimmune process and a broad clinical phenotype compared to classical type 1 diabetes mellitus (T1DM), sharing features with both type 2 diabetes mellitus (T2DM) and T1DM. Since patients affected by LADA are initially insulin independent and recognizable only by testing for islet-cell autoantibodies, it could be difficult to identify LADA in clinical setting and a high misdiagnosis rate still remains among patients with T2DM. Ideally, islet-cell autoantibodies screening should be performed in subjects with newly diagnosed T2DM, ensuring a closer monitoring of those resulted positive and avoiding treatment of hyperglycaemia which might increase the rate of β-cells loss. Thus, since the autoimmune process in LADA seems to be slower than in classical T1DM, there is a wider window for new therapeutic interventions that may slow down β-cell failure. This review summarizes the current understanding of LADA, by evaluating data from most recent studies, the actual gaps in diagnosis and management. Finally, we critically highlight and discuss novel findings and future perspectives on the therapeutic approach in LADA.

Ethnic differences in progression of islet autoimmunity and type 1 diabetes in relatives at risk

AIMS/HYPOTHESIS

We hypothesised that progression of islet autoimmunity and type 1 diabetes mellitus differs among races/ethnicities in at-risk individuals.

METHODS

In this study, we analysed the data from the Type 1 Diabetes TrialNet Pathway to Prevention Study. We studied 4873 non-diabetic, autoantibody-positive relatives of individuals with type 1 diabetes followed prospectively (11% Hispanic, 80.9% non-Hispanic white [NHW], 2.9% non-Hispanic black [NHB] and 5.2% non-Hispanic other [NHO]). Primary outcomes were time from single autoantibody positivity confirmation to multiple autoantibody positivity, and time from multiple autoantibody positivity to type 1 diabetes mellitus diagnosis.

RESULTS

Conversion from single to multiple autoantibody positivity was less common in Hispanic individuals than in NHW individuals (HR 0.66 [95% CI 0.46, 0.96], p = 0.028) adjusting for autoantibody type, age, sex, Diabetes Prevention Trial Type 1 Risk Score and HLA-DR3-DQ2/DR4-DQ8 genotype. In participants who screened positive for multiple autoantibodies (n = 2834), time to type 1 diabetes did not differ by race/ethnicity overall (p = 0.91). In children who were <12 years old when multiple autoantibody positivity was determined, being overweight/obese had differential effects by ethnicity: type 1 diabetes risk was increased by 36% in NHW children (HR 1.36 [95% CI 1.04, 1.77], p = 0.024) and was nearly quadrupled in Hispanic children (HR 3.8 [95% CI 1.6, 9.1], p = 0.0026). We did not observe this interaction in participants who were ≥12 years old at determination of autoantibody positivity, although this group size was limited. No significant differential risks were observed between individuals of NHB and NHW ethnicity.

CONCLUSIONS/INTERPRETATION

The risk and rate of progression of islet autoimmunity were lower in Hispanic compared with NHW at-risk individuals, while significant differences in the development of type 1 diabetes were limited to children <12 years old and were modified by BMI.

A Global Perspective of Latent Autoimmune Diabetes in Adults

Latent autoimmune diabetes in adults (LADA) is characterized by the presence of islet autoantibodies and initial insulin independence, which can lead to misdiagnosis of type 2 diabetes (T2D). As such, understanding the genetic etiology of LADA could aid in more accurate diagnosis. However, there is ongoing debate regarding the exact definition of LADA, so understanding its impact in different populations when contrasted with type 1 diabetes (T1D) and T2D is one potential strategy to gain insight into its etiology. Unfortunately, the lack of consistent and thorough autoantibody screening around the world has hampered well-powered genetic studies of LADA. This review highlights recent genetic and epidemiological studies of LADA in diverse populations as well as the importance of autoantibody screening in facilitating future research.

Latent Autoimmune Diabetes in Adults: Current Status and New Horizons

Autoimmune diabetes is a heterogeneous disease which can arise at any age. Subjects with adult-onset autoimmune diabetes who do not necessitate insulin-therapy for at least 6 months after diagnosis are demarcated as having latent autoimmune diabetes in adults (LADA). This condition is more heterogeneous than young-onset autoimmune diabetes and shares clinical and metabolic characteristics with both type 2 and type 1 diabetes. Patients with LADA are considered by having highly variable β-cell destruction, different degrees of insulin resistance and heterogeneous titre and pattern of islet autoantibody, suggesting different pathophysiological pathways partially explaining the heterogeneous phenotypes of LADA. To date the heterogeneity of LADA does not allow to establish a priori treatment algorithm and no specific guidelines for LADA therapy are available. These subjects are mostly treated as affected by type 2 diabetes, a factor that might lead to the progression to insulin-dependency quickly. A personalised medicine approach is necessary to attain optimal metabolic control and preserve β-cell function to decrease the risk of long-term diabetes complications. Recent data concerning the use of oral antidiabetic agents as dipeptidyl peptidase 4 inhibitors and glucagon-like peptide 1 receptor agonists indicate up-and-coming results in term of protect C-peptide levels and improving glycaemic control. This review summarises current knowledge on LADA, emphasising controversies regarding its pathophysiology and clinical features. Moreover, we discuss data available about novel therapeutic approaches that can be considered for prevention of β-cell loss in LADA.

Genetics of type 1 diabetes

Type 1 diabetes (T1D) results from immune-mediated loss of pancreatic beta cells leading to insulin deficiency. It is the most common form of diabetes in children, and its incidence is on the rise. This article reviews the current knowledge on the genetics of T1D. In particular, we discuss the influence of HLA and non-HLA genes on T1D risk and disease progression through the preclinical stages of the disease, and the development of genetic scores that can be applied to disease prediction. Racial/ethnic differences, challenges and future directions in the genetics of T1D are also discussed.

Adult-onset autoimmune diabetes: current knowledge and implications for management

Adult-onset autoimmune diabetes is a heterogeneous disease that is characterized by a reduced genetic load, a less intensive autoimmune process and a mild metabolic decompensation at onset compared with young-onset type 1 diabetes mellitus (T1DM). The majority of patients with adult-onset autoimmune diabetes do not require insulin treatment for at least 6 months after diagnosis. Such patients are defined as having latent autoimmune diabetes in adults (LADA), which is distinct from classic adult-onset T1DM. The extensive heterogeneity of adult-onset autoimmune diabetes is apparent beyond the distinction between classic adult-onset T1DM and LADA. LADA is characterized by genetic, phenotypic and humoral heterogeneity, encompassing different degrees of insulin resistance and autoimmunity; this heterogeneity is probably a result of different pathological mechanisms, which have implications for treatment. The existence of heterogeneous phenotypes in LADA makes it difficult to establish an a priori treatment algorithm, and therefore, a personalized medicine approach is required. In this Review, we discuss the current understanding and gaps in knowledge regarding the pathophysiology and clinical features of adult-onset autoimmune diabetes and highlight the similarities and differences with classic T1DM and type 2 diabetes mellitus.

Identification of Unique Antigenic Determinants in the Amino Terminus of IA-2 (ICA512) in Childhood and Adult Autoimmune Diabetes: New Biomarker Development

OBJECTIVE

The characterization of diverse subtypes of diabetes is a dynamic field of clinical research and an active area of discussion. The objective of this study was to identify new antigenic determinants in the neuroendocrine autoantigen IA-2 (ICA512) and assess whether circulating autoantibodies directed to new IA-2 epitopes identify autoimmune diabetes in young and adult populations with diabetes.

RESEARCH DESIGN AND METHODS

Clinically diagnosed patients with type 2 diabetes (n = 258; diabetes duration: 0.01-31 years) were evaluated using a new biomarker detecting autoantibodies directed to the extracellular domain of the neuroendocrine autoantigen IA-2 (IA-2ec). The proportion of IA-2ec autoantibodies was also evaluated in newly diagnosed patients with type 1 diabetes (n = 150; diabetes duration: 0.04-0.49 years). In addition, IA-2 (intracellular domain), GAD65, and zinc transporter 8 autoantibodies were assayed.

RESULTS

IA-2ec autoantibodies were detected in patients with type 1 diabetes and, surprisingly, in 5% of patients with type 2 diabetes without serologic responses to other IA-2 antigenic epitopes or other islet autoantigens. We also assessed the ability of IA-2ec-derived peptides to elicit CD4⁺ T-cell responses by stimulating peripheral blood mononuclear cells from patients with type 1 diabetes (n = 18) and HLA-matched healthy subjects (n = 13) with peptides and staining with the peptide/DQ8-specific tetramers, observing disease-associated responses to previously unreported epitopes within IA-2ec.

CONCLUSIONS

We developed a new antibody biomarker identifying novel antigenic determinants within the N terminus of IA-2. IA-2ec autoantibodies can be detected in patients with type 1 diabetes and in a subgroup of adult autoimmune patients with type 2 diabetes phenotype negative for conventional islet autoantibody testing. These observations suggest that islet autoimmunity may be more common in clinically diagnosed type 2 diabetes than previously observed.

Low prevalence of latent autoimmune diabetes in adults in northern India

AIM

To study the frequency of islet antibodies in a large cohort of clinic- and community-based patients with Type 2 diabetes in northern India.

METHODS

We measured glutamic acid decarboxylase (GAD) antibodies in 618 adults with Type 2 diabetes (378 patients with diabetes attending a hospital clinic, 240 patients diagnosed in a community survey) and in 192 healthy subjects residing in north India. Islet antigen 2 (IA2) antibodies were also studied in a proportion of the patients with diabetes (n = 492) and in a control population (n = 191). GAD and IA2 antibodies were measured by immunoprecipitation of the respective (35) S-labelled recombinant antigen.

RESULTS

We found that GAD antibodies were present in nine (1.5%) patients with diabetes (clinic population: 0.8%, community study: 2.5%), a prevalence similar to that among the subjects without diabetes (n = 2; 1%). IA2 antibodies were detected in seven patients with Type 2 diabetes (1.4%) and in two healthy control subjects (1.0%). The frequency of either GAD or IA2 antibodies was similar in people with and without diabetes (3.2 vs 2.1%). No subject was found to have both antibodies. Insulin requirement was higher among antibody-positive than among antibody-negative patients (GAD antibody: 33 vs 6.3%; P = 0.001; GAD or IA2 antibody: 23.1 vs 6.4%; P = 0.02); however, other clinical features were similar in the two groups.

CONCLUSIONS

In the present north-Indian population with Type 2 diabetes, the overall prevalence of GAD antibodies and the prevalence of either GAD or IA2 antibodies were considerably lower than those reported in white European populations.

Islet autoimmunity identifies a unique pattern of impaired pancreatic beta-cell function, markedly reduced pancreatic beta cell mass and insulin resistance in clinically diagnosed type 2 diabetes

There is a paucity of literature describing metabolic and histological data in adult-onset autoimmune diabetes. This subgroup of diabetes mellitus affects at least 5% of clinically diagnosed type 2 diabetic patients (T2DM) and it is termed Latent Autoimmune Diabetes in Adults (LADA). We evaluated indexes of insulin secretion, metabolic assessment, and pancreatic pathology in clinically diagnosed T2DM patients with and without the presence of humoral islet autoimmunity (Ab). A total of 18 patients with at least 5-year duration of clinically diagnosed T2DM were evaluated in this study. In those subjects we assessed acute insulin responses to arginine, a glucose clamp study, whole-body fat mass and fat-free mass. We have also analyzed the pancreatic pathology of 15 T2DM and 43 control cadaveric donors, using pancreatic tissue obtained from all the T2DM organ donors available from the nPOD network through December 31, 2013. The presence of islet Ab correlated with severely impaired β-cell function as demonstrated by remarkably low acute insulin response to arginine (AIR) when compared to that of the Ab negative group. Glucose clamp studies indicated that both Ab positive and Ab negative patients exhibited peripheral insulin resistance in a similar fashion. Pathology data from T2DM donors with Ab or the autoimmune diabetes associated DR3/DR4 allelic class II combination showed reduction in beta cell mass as well as presence of autoimmune-associated pattern A pathology in subjects with either islet autoantibodies or the DR3/DR4 genotype. In conclusion, we provide compelling evidence indicating that islet Ab positive long-term T2DM patients exhibit profound impairment of insulin secretion as well as reduced beta cell mass seemingly determined by an immune-mediated injury of pancreatic β-cells. Deciphering the mechanisms underlying beta cell destruction in this subset of diabetic patients may lead to the development of novel immunologic therapies aimed at halting the disease progression in its early stage.

Diabetes autoantibodies do not predict progression to diabetes in adults: the Diabetes Prevention Program

AIMS

To determine if the presence of diabetes autoantibodies predicts the development of diabetes among participants in the Diabetes Prevention Program.

METHODS

A total of 3050 participants were randomized into three treatment groups: intensive lifestyle intervention, metformin and placebo. Glutamic acid decarboxylase (GAD) 65 autoantibodies and insulinoma-associated-2 autoantibodies were measured at baseline and participants were followed for 3.2 years for the development of diabetes.

RESULTS

The overall prevalence of GAD autoantibodies was 4.0%, and it varied across racial/ethnic groups from 2.4% among Asian-Pacific Islanders to 7.0% among non-Hispanic black people. There were no significant differences in BMI or metabolic variables (glucose, insulin, HbA(1c), estimated insulin resistance, corrected insulin response) stratified by baseline GAD antibody status. GAD autoantibody positivity did not predict diabetes overall (adjusted hazard ratio 0.98; 95% CI 0.56-1.73) or in any of the three treatment groups. Insulinoma-associated-2 autoantibodies were positive in only one participant (0.033%).

CONCLUSIONS

These data suggest that 'diabetes autoimmunity', as reflected by GAD antibodies and insulinoma-associated-2 autoantibodies, in middle-aged individuals at risk for diabetes is not a clinically relevant risk factor for progression to diabetes.

Meta-analysis of genome-wide association studies in African Americans provides insights into the genetic architecture of type 2 diabetes

Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15 × 10(-94) Collapse

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MESH Headings

• Black or African American/genetics
• Diabetes Mellitus, Type 2/genetics
• Diabetes Mellitus, Type 2/pathology
• Genome-Wide Association Study
• HLA-B27 Antigen/genetics
• HMGA2 Protein/genetics
• Humans
• KCNQ1 Potassium Channel/genetics
• Mutant Chimeric Proteins/genetics
• Polymorphism, Single Nucleotide
• Transcription Factor 7-Like 2 Protein/genetics

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Affiliation(s)

Maggie C. Y. Ng Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Daniel Shriner Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
Brian H. Chen Program on Genomics and Nutrition, School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America Center for Metabolic Disease Prevention, School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America
Jiang Li Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Wei-Min Chen Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
Xiuqing Guo Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
Jiankang Liu Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
Suzette J. Bielinski Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America
Lisa R. Yanek The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
Michael A. Nalls Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
Mary E. Comeau Center for Public Health Genomics, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Laura J. Rasmussen-Torvik Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
Richard A. Jensen Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America Department of Medicine, University of Washington, Seattle, Washington, United States of America
Daniel S. Evans San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, California, United States of America
Yan V. Sun Department of Epidemiology and Biomedical Informatics, Emory University, Atlanta, Georgia, United States of America
Ping An Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, United States of America
Sanjay R. Patel Division of Sleep Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
Yingchang Lu The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
Jirong Long Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
Loren L. Armstrong Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
Lynne Wagenknecht Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Lingyao Yang Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Beverly M. Snively Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Nicholette D. Palmer Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Poorva Mudgal Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Carl D. Langefeld Center for Public Health Genomics, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Keith L. Keene Department of Biology, Center for Health Disparities, East Carolina University, Greenville, North Carolina, United States of America
Barry I. Freedman Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Josyf C. Mychaleckyj Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
Uma Nayak Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America
Leslie J. Raffel Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
Mark O. Goodarzi Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
Y-D Ida Chen Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
Herman A. Taylor Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America Jackson State University, Tougaloo College, Jackson, Mississippi, United States of America
Adolfo Correa Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
Mario Sims Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
David Couper Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
James S. Pankow Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, United States of America
Eric Boerwinkle Human Genetics Center, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
Adebowale Adeyemo Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
Ayo Doumatey Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
Guanjie Chen Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
Rasika A. Mathias The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America Division of Allergy and Clinical Immunology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
Dhananjay Vaidya The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
Andrew B. Singleton Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
Alan B. Zonderman Laboratory of Personality and Cognition, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, United States of America
Robert P. Igo Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
John R. Sedor Department of Medicine, Case Western Reserve University, MetroHealth System campus, Cleveland, Ohio, United States of America Department of Physiology and Biophysics, Case Western Reserve University, Cleveland, Ohio, United States of America
the FIND Consortium
Edmond K. Kabagambe Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
David S. Siscovick Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America Department of Medicine, University of Washington, Seattle, Washington, United States of America Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
Barbara McKnight Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
Kenneth Rice Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
Yongmei Liu Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
Wen-Chi Hsueh Department of Medicine, University of California, San Francisco, California, United States of America
Wei Zhao Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
Lawrence F. Bielak Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
Aldi Kraja Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, United States of America
Michael A. Province Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, United States of America
Erwin P. Bottinger The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
Omri Gottesman The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
Qiuyin Cai Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
Wei Zheng Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
William J. Blot Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee; International Epidemiology Institute, Rockville, Maryland, United States of America
William L. Lowe Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
Jennifer A. Pacheco Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
Dana C. Crawford Center for Human Genetics Research and Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee, United States of America
the eMERGE Consortium
the DIAGRAM Consortium
Elin Grundberg Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
the MuTHER Consortium
Stephen S. Rich Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
M. Geoffrey Hayes Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
Xiao-Ou Shu Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
Ruth J. F. Loos The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America The Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
Ingrid B. Borecki Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, United States of America
Patricia A. Peyser Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
Steven R. Cummings San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, California, United States of America
Bruce M. Psaty Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America Department of Medicine, University of Washington, Seattle, Washington, United States of America Department of Epidemiology, University of Washington, Seattle, Washington, United States of America Department of Health Services, University of Washington, Seattle, Washington, United States of America
Myriam Fornage Human Genetics Center, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
Sudha K. Iyengar Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
Michele K. Evans Health Disparities Unit, National Institute on Aging, National Institutes of Health, Baltimore Maryland, United States of America
Diane M. Becker The GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
W. H. Linda Kao Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
James G. Wilson Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
Jerome I. Rotter Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
Michèle M. Sale Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America Department of Medicine, University of Virginia, Charlottesville, Virginia, United States of America Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, United States of America
Simin Liu Program on Genomics and Nutrition, School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America Department of Epidemiology, University of California Los Angeles, Los Angeles, California, United States of America Departments of Epidemiology and Medicine, Brown University, Providence, Rhode Island, United States of America
Charles N. Rotimi Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, Maryland, United States of America
Donald W. Bowden Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
for the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium

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Humoral autoimmunity in type 1 diabetes: prediction, significance, and detection of distinct disease subtypes

Type 1 diabetes mellitus (T1D) is an autoimmune disease encompassing the T-cell-mediated destruction of pancreatic β cells and the production of autoantibodies against islet proteins. In humoral autoimmunity in T1D, the detection of islet autoantibodies and the examination of their associations with genetic factors and cellular autoimmunity constitute major areas in both basic research and clinical practice. Although insulin is a key autoantigen and may be primus inter pares in importance among T1D autoantigens, an abundant body of research has also revealed other autoantigens associated with the disease process. Solid evidence indicates that autoantibodies against islet targets serve as key markers to enroll newly diagnosed T1D patients and their family members in intervention trials aimed at preventing or halting the disease process. The next challenge is perfecting mechanistic bioassays to be used as end points for disease amelioration following immunomodulatory therapies aimed at blocking immune-mediated β-cell injury and, in turn, preserving β-cell function in type 1 diabetes mellitus.

GAD65 autoantibodies and its role as biomarker of Type 1 diabetes and Latent Autoimmune Diabetes in Adults (LADA)

One of the hallmarks of autoimmune diabetes is the presence of adaptive responses directed to neuroendocrine proteins. One of these proteins is glutamic acid decarboxylase (GAD). While GAD is widely distributed in neuroendocrine tissues, its specific significance in diabetes has paralleled the advances in understanding humoral and cellular immunity in Type 1 diabetes (T1D) and in a subset of Type 2 diabetes (T2D), going from the seminal discoveries of islet autoantibodies to the development and standardization of bioassays as diagnostic tools, to studies on the structure of GAD and its antigenic determinants. GAD65 autoantibodies can accurately predict T1D development in combination with other surrogate humoral biomarkers and they are considered the most sensitive and specific biomarker which identifies a subset of clinically diagnosed T2D termed Latent Autoimmune Diabetes in Adults (LADA). We and others provided evidence indicating that GAD65 autoantibody detection should be part of the diagnostic assessment for clinically diagnosed T2DM mainly because it predicts the rate of progression to insulin requirement in patients affected by LADA. More recently GAD has been used as a "tolerogenic vaccine" to preserve beta cell function in autoimmune diabetes. While the results of Phase III clinical trials did not substantiate the earlier promise of Phase I and II trials, there are still many unanswered questions and approaches that need to be investigated in the applications of GAD in the therapy of T1D and LADA.

The heterogeneity of diabetes: unraveling a dispute: is systemic inflammation related to islet autoimmunity?

Diabetes is an emblematic example of a heterogeneous disease. Systemic inflammation has emerged as a prominent factor in the type 2 diabetes pathoetiology, but it remains ill-defined in type 1 diabetes. There is a wide spectrum of associations between inflammatory responses and diabetic syndromes. At one end of this spectrum, there is type 1 diabetes for which there is convincing evidence that chronic inflammation of pancreatic islets is a central aspect of disease pathogenesis. At the opposite end, is type 2 diabetes that is clearly associated with systemic inflammation, which could be either the cause or simply mark the underlying pathology. Accumulating evidence has substantiated that a subgroup of adult patients clinically diagnosed with type 2 diabetes exhibit autoantibody responses to islet autoantigens. The presence of these immunologic abnormalities is associated with a severe insulin secretory defect and the absence of signs of systemic inflammation as documented by plasma C-reactive protein and fibrinogen levels that are comparable with those of control populations. Islet autoantibody evaluation should be part of the diagnostic assessment for clinically diagnosed type 2 diabetes not only because it might predict the rate of progression to insulin requirement in adult populations but also to identify a pathogenically distinct disease phenotype characterized by the absence of systemic inflammation and its related disorders. A more appropriate characterization of this subgroup of clinically diagnosed type 2 diabetes, diabetes of autoimmune pathogenesis, will promote future research into the etiology, natural history, and treatment.

The prevalence of the 65-kilodalton isoform of glutamic acid decarboxylase autoantibodies by glucose tolerance status in elderly patients from the cardiovascular health study

CONTEXT

Autoantibodies (AA) to glutamic acid decarboxylase (GAD65), a determinant of risk for autoimmune diabetes, have been found in up to 10% of patients with type 2 diabetes. In older adults, this marker may also serve as a determinant of risk for autoimmune diabetes and enhance diabetes classification.

OBJECTIVE

The objective of this study was to evaluate the relationship between GAD65AA and glucose tolerance status, current diabetes treatment, and clinical measures in older adults.

DESIGN

GAD65AA were measured at baseline in 3318 participants from the Cardiovascular Health Study, a cohort study of 5888 individuals 65 or older.

SETTING

The population-based cohort was recruited from four U.S. sites.

PATIENTS

Patients included all Cardiovascular Health Study participants with known diabetes, newly diagnosed diabetes, impaired fasting glucose, impaired glucose tolerance, and a sample of normal glucose-tolerant participants.

MAIN OUTCOME MEASURES

GAD65AA, body mass index, fasting glucose and insulin levels, blood pressure, lipid levels, and diabetes treatment at baseline were measured.

RESULTS

The prevalence of GAD65AA increased with decreasing glucose tolerance in both Blacks (n = 560) and Whites (n = 2730), being more pronounced in known diabetic individuals. GAD65AA were found in 2.3, 5.8, 7.8, and 8.3% of diabetic participants, reporting use of no diabetes medication, oral hypoglycemic agents, insulin only, and both oral hypoglycemic agents and insulin, respectively (P = 0.02, linear trend). Among diabetic participants, GAD65AA positivity was associated with diabetes treatment, higher fasting glucose, and lower body mass index.

CONCLUSIONS

Even among older individuals with diabetes, GAD65AA may be a useful marker in identifying a subgroup of autoimmune diabetes, serve as a marker of insulin requirement, and remain stable over years.

Frequency of diabetes and thyroid autoantibodies in patients with autoimmune endocrine disease from Cameroon

BACKGROUND

Diabetes is a major cause of morbidity and mortality in both industrialized and developing countries. In Africa, there are little data on the prevalence and immunological features of patients with autoimmune endocrine diseases.

AIM OF THE STUDY

The present hospital-based study was carried out to evaluate disease-associated autoantibodies in both type 1 diabetes and thyrotoxicosis attending the Central Hospital of Yaoundee in Cameroon.

PATIENTS AND METHODS

Samples were collected from a total of 101 subjects, 47 of whom clinically had established type 1 diabetes (mean age 30.1 years +/- 7.6, mean disease duration 3.3 years), 18 had thyrotoxicosis (mean age 32.7 years +/- 7.6, mean disease duration 6.3 years +/- 2.8) and 36 normal subjects (mean age 26 years +/- 4.5). All subjects were tested for diabetes-associated glutamic acid decarboxylase (GAD) and tyrosine phosphatase (IA2) autoantibodies using antigen-specific radioimmunoassay as well as thyroiditis-associated thyroglobulin (Tg) and thyroid peroxidase (TPO) autoantibodies using commercially available kits.

RESULTS

Of 47 patients with type 1 diabetes, 16 (34%) had GAD autoantibodies (Abs), 3 (6.4%) had IA2 Abs, and 2 (4.3%) had TPO Abs. Of 18 patients with thyrotoxicosis 4 (22.2%) had GAD Abs, 5 (27.8%) showed IA2 Abs, while 8 patients (44.4%) were TPO Abs positive. No patients in either group had Tg Abs. Among normal subjects, 2 (5.6%) showed GAD Abs, and one of these was also IA2 Abs positive, but none had thyroid autoantibodies.

CONCLUSION

Adult-onset type 1 diabetic patients some years post-diagnosis from central Africa show GAD, IA2 or TPO Abs; and surprisingly, patients with thyrotoxicosis had a similar frequency of diabetes-associated autoantibodies. We conclude that, despite a different genetic and environmental background to European populations, islet cell autoimmunity is common in autoimmune endocrine patients in central Africa.

A high prevalence of organ-specific autoimmunity in patients with bipolar disorder

BACKGROUND

In a previous study, we reported an increased prevalence of thyroperoxidase antibodies (TPOA) in patients with bipolar disorder. Here we report the prevalence of other organ-specific autoantibodies: H/K adenosine triphosphatase (ATPA), glutamic acid decarboxylase-65 (GAD65A), and GAD-67 (GAD67A).

METHODS

ATPA, GAD65A, and GAD67A were determined (via a commercially available enzyme linked immunosorbent assay for ATPA, and a standardized radio immunoassays for GAD65A and GAD67A)in the sera of 239 patients with DSM-IV bipolar disorder, in 74 patients with DSM-IV schizophrenia, and in 220 healthy control subjects.

RESULTS

The positivity prevalences for ATPA and GAD65A (but not GAD67A) were elevated in bipolar patients compared with those in healthy control subjects (11.7 vs. 6.1% and 11.3 vs. 2.6% respectively; p <.05). Schizophrenia patients did not show such statistically higher prevalence. The elevated prevalence of ATPA and GAD65A in bipolar disorder was associated with neither rapid cycling nor the use of lithium. Interestingly, the presence of GAD65A (and not that of TPOA and ATPA) tended to be associated with the activity of bipolar disorder. The level of TPOA was negatively correlated with the serum level of sIL-2R, a measure of T cell activation.

CONCLUSION

Bipolar disorder is associated with organ-specific autoimmunity to the antigens TPO, H/K ATPase, and GAD65.