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Type 1 diabetes arises from the autoimmune destruction of insulin-producing beta-cells of the pancreas, resulting in dependence on exogenously administered insulin to maintain glucose homeostasis. In this study, our aim was to identify genetic risk factors that contribute to progression from islet autoimmunity to clinical type 1 diabetes. We analyzed 6.8 million variants derived from whole genome sequencing of 160 islet autoantibody positive subjects, including 87 who had progressed to type 1 diabetes. The Cox proportional-hazard model for survival analysis was used to identify genetic variants associated with progression. We identified one novel region, 20p12.1 (TASP1; genome-wide P < 5 × 10 -8 ) and three regions, 1q21.3 (MRPS21-PRPF3), 2p25.2 (NRIR), 3q22.1 (COL6A6), with suggestive evidence of association (P < 8.5 × 10 -8 ) with progression from islet autoimmunity to type 1 diabetes. Once islet autoimmunity is initiated, functional mapping identified two critical pathways, response to viral infections and interferon signaling, as contributing to disease progression. These results provide evidence that genetic pathways involved in progression from islet autoimmunity differ from those pathways identified once disease has been established. These results support the need for further investigation of genetic risk factors that modulate initiation and progression of subclinical disease to inform efforts in development of novel strategies for prediction and intervention of type 1 diabetes.

Purpose: Autoimmune diseases co-occur, perhaps due to common risk factors. The age at gluten introduction and gluten intake in early childhood has been associated with the autoimmunity preceding celiac disease (CD) and type-1 diabetes (T1D). We explored their associations with the development of thyroid autoimmunity., Methods: DAISY has prospectively followed children at increased risk for T1D and CD since 1993. During follow-up, 107 children developed thyroid autoimmunity, defined as positivity for autoantibodies against thyroid peroxidase on at least two study visits. Age at gluten introduction was ascertained from food history interviews every 3 months until 15 months of age. Gluten intake (g/day) at age 1-2 years was estimated using a food frequency questionnaire., Results: From multivariable Cox regression, there was no association between the age of gluten introduction nor the amount of gluten intake and development of thyroid autoimmunity. However, females (hazard ratio = 2.19, 95% CI: 1.46, 3.27) and cases of islet autoimmunity (HR = 2.20, 95% CI: 1.39, 3.50) were significantly more likely to develop thyroid autoimmunity, while exposure to environmental tobacco smoke decreased the risk (HR = 0.46, 95% CI: 0.30, 0.71)., Conclusions: Neither the age of gluten introduction nor the amount of gluten consumed in early childhood is associated with risk of thyroid autoimmunity.

Context: Once islet autoantibody-positive individuals are identified, predicting which individuals are at highest risk for type 1 diabetes (T1D) is important. A metabolic risk score derived from 2-hour oral glucose tolerance test (OGTT) data, the Diabetes Prevention Trial-Type 1 risk score (DPTRS), can accurately predict T1D. However, 2-hour OGTTs are time-consuming and costly., Objective: We aimed to determine whether a risk score derived from 1-hour OGTT data can predict T1D as accurately as the DPTRS. Secondarily, we evaluated whether a 1-hour glucose value can be used for diagnostic surveillance., Methods: The DPTRS was modified to derive a 1-hour OGTT risk score (DPTRS60) using fasting C-peptide, 1-hour glucose and C-peptide, age, and body mass index. Areas under receiver operating curves (ROCAUCs) were used to compare prediction accuracies of DPTRS60 with DPTRS in Diabetes Prevention Trial-Type 1 (DPT-1) (n = 654) and TrialNet Pathway to Prevention (TNPTP) (n = 4610) participants. Negative predictive values (NPV) for T1D diagnosis were derived for 1-hour glucose thresholds., Results: ROCAUCs for T1D prediction 5 years from baseline were similar between DPTRS60 and DPTRS (DPT-1: 0.805 and 0.794; TNPTP: 0.832 and 0.847, respectively). DPTRS60 predicted T1D significantly better than 2-hour glucose (P < .001 in both cohorts). A 1-hour glucose of less than 180 mg/dL had a similar NPV, positive predictive value, and specificity for T1D development before the next 6-month visit as the standard 2-hour threshold of less than 140 mg/dL (both ≥ 98.5%)., Conclusion: A 1-hour OGTT can predict T1D as accurately as a 2-hour OGTT with minimal risk of missing a T1D diagnosis before the next visit., (© Endocrine Society 2020. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Advances in molecular methods and the ability to share large population-based datasets are uncovering heterogeneity within diabetes types, and some commonalities between types. Within type 1 diabetes, endotypes have been discovered based on demographic (e.g. age at diagnosis, race/ethnicity), genetic, immunological, histopathological, metabolic and/or clinical course characteristics, with implications for disease prediction, prevention, diagnosis and treatment. In type 2 diabetes, the relative contributions of insulin resistance and beta cell dysfunction are heterogeneous and relate to demographics, genetics and clinical characteristics, with substantial interaction from environmental exposures. Investigators have proposed approaches that vary from simple to complex in combining these data to identify type 2 diabetes clusters relevant to prognosis and treatment. Advances in pharmacogenetics and pharmacodynamics are also improving treatment. Monogenic diabetes is a prime example of how understanding heterogeneity within diabetes types can lead to precision medicine, since phenotype and treatment are affected by which gene is mutated. Heterogeneity also blurs the classic distinctions between diabetes types, and has led to the definition of additional categories, such as latent autoimmune diabetes in adults, type 1.5 diabetes and ketosis-prone diabetes. Furthermore, monogenic diabetes shares many features with type 1 and type 2 diabetes, which make diagnosis difficult. These challenges to the current classification framework in adult and paediatric diabetes require new approaches. The 'palette model' and the 'threshold hypothesis' can be combined to help explain the heterogeneity within and between diabetes types. Leveraging such approaches for therapeutic benefit will be an important next step for precision medicine in diabetes. Graphical abstract.

Objective: To assess the costs and project the potential lifetime cost-effectiveness of the ongoing Autoimmunity Screening for Kids (ASK) program, a large-scale, presymptomatic type 1 diabetes screening program for children and adolescents in the metropolitan Denver region., Research Design and Methods: We report the resource utilization, costs, and effectiveness measures from the ongoing ASK program compared with usual care (i.e., no screening). Additionally, we report a practical screening scenario by including utilization and costs relevant to routine screening in clinical practice. Finally, we project the potential cost-effectiveness of ASK and routine screening by identifying clinical benchmarks (i.e., diabetic ketoacidosis [DKA] events avoided, HbA 1c improvements vs. no screening) needed to meet value thresholds of $50,000-$150,000 per quality-adjusted life-year (QALY) gained over a lifetime horizon., Results: Cost per case detected was $4,700 for ASK screening and $14,000 for routine screening. To achieve value thresholds of $50,000-$150,000 per QALY gained, screening costs would need to be offset by cost savings through 20% reductions in DKA events at diagnosis in addition to 0.1% (1.1 mmol/mol) improvements in HbA 1c over a lifetime compared with no screening for patients who develop type 1 diabetes. Value thresholds were not met from avoiding DKA events alone in either scenario., Conclusions: Presymptomatic type 1 diabetes screening may be cost-effective in areas with a high prevalence of DKA and an infrastructure facilitating screening and monitoring if the benefits of avoiding DKA events and improved HbA 1c persist over long-run time horizons. As more data are collected from ASK, the model will be updated with direct evidence on screening effects., (© 2020 by the American Diabetes Association.)

Objective: Mechanisms underlying the role of non-human leukocyte antigen (HLA) genetic risk variants in type 1 diabetes (T1D) are poorly understood. We aimed to test the association between methylation and non-HLA genetic risk., Methods: We conducted a methylation quantitative trait loci (mQTL) analysis in a nested case-control study from the Dietary Autoimmunity Study in the Young. Controls (n = 83) were frequency-matched to T1D cases (n = 83) based on age, race/ethnicity, and sample availability. We evaluated 13 non-HLA genetic markers known be associated with T1D. Genome-wide methylation profiling was performed on peripheral blood samples collected prior to T1D using the Illumina 450 K (discovery set) and infinium methylation EPIC beadchip (EPIC validation) platforms. Linear regression models, adjusting for age and sex, were used to test to each single nucleotide polymorphism (SNP) -probe combination. Logistic regression models were used to test the association between T1D and methylation levels among probes with a significant mQTL. A meta-analysis was used to combine odds ratios from the two platforms., Results: We identified 10 SNP-methylation probe pairs (false discovery rate (FDR) adjusted P < .05 and validation P < .05). Probes were associated with the GSDMB, C1QTNF6, IL27, and INS genes. The cg03366382 (OR: 1.9, meta-P = .0495), cg21574853 (OR: 2.5, meta-P = .0232), and cg25336198 (odds ratio: 6.6, meta-P = .0081) probes were significantly associated with T1D. The three probes were located upstream from the INS transcription start site., Conclusions: We confirmed an association between DNA methylation and rs689 that has been identified in related studies. Measurements in our study preceded the onset of T1D suggesting methylation may have a role in the relationship between INS variation and T1D development., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Context: Concordance for persistent islet autoimmunity (IA) and type 1 diabetes in monozygotic twins after probands are diagnosed is variable (30%-70%). Risk for development of IA in dizygotic twins is thought to be similar to nontwin siblings. Little is known in regard to the development of celiac autoimmunity (CDA) in twins of subjects with type 1 diabetes., Objective: Our aim was to investigate the development of IA and CDA in cotwins of probands with type 1 diabetes., Methods: Since 1995, the Twin Family Study has followed 336 twins (168 twin probands with type 1 diabetes and 168 cotwins) for a median of 14 years (interquartile range:10-18 years). Cotwins were followed for the development of IA, type 1 diabetes, and CDA., Results: In monozygotic cotwins, cumulative incidence by age 20 was 14% for IA and 10% for CDA. Development of IA and CDA by age 20 was 9% and 12% in dizygotic cotwins, respectively. While the numbers are small, IA by age 30 years was 26% in monozygotic and 39% in dizygotic twins. In proportional hazards models, the proband's younger age at diagnosis, but not sex or human leukocyte antigen were associated with time to IA and CDA in cotwins., Conclusion: CDA risk by age 20 in cotwins was 10% to 12%. With long-term follow-up, cumulative incidence for IA is high in dizygotic twins, similar to monozygotic twins, suggesting a role of possible early environmental factors shared by type 1 diabetes discordant cotwins., (© Endocrine Society 2020.)

This study aims to model genetic, immunologic, metabolomics, and proteomic biomarkers for development of islet autoimmunity (IA) and progression to type 1 diabetes in a prospective high-risk cohort. We studied 67 children: 42 who developed IA (20 of 42 progressed to diabetes) and 25 control subjects matched for sex and age. Biomarkers were assessed at four time points: earliest available sample, just prior to IA, just after IA, and just prior to diabetes onset. Predictors of IA and progression to diabetes were identified across disparate sources using an integrative machine learning algorithm and optimization-based feature selection. Our integrative approach was predictive of IA (area under the receiver operating characteristic curve [AUC] 0.91) and progression to diabetes (AUC 0.92) based on standard cross-validation (CV). Among the strongest predictors of IA were change in serum ascorbate, 3-methyl-oxobutyrate, and the PTPN22 (rs2476601) polymorphism. Serum glucose, ADP fibrinogen, and mannose were among the strongest predictors of progression to diabetes. This proof-of-principle analysis is the first study to integrate large, diverse biomarker data sets into a limited number of features, highlighting differences in pathways leading to IA from those predicting progression to diabetes. Integrated models, if validated in independent populations, could provide novel clues concerning the pathways leading to IA and type 1 diabetes., (© 2019 by the American Diabetes Association.)

Background: Progression time from islet autoimmunity to clinical type 1 diabetes is highly variable and the extent that genetic factors contribute is unknown., Methods: In 341 islet autoantibody-positive children with the human leucocyte antigen (HLA) DR3/DR4-DQ8 or the HLA DR4-DQ8/DR4-DQ8 genotype from the prospective TEDDY (The Environmental Determinants of Diabetes in the Young) study, we investigated whether a genetic risk score that had previously been shown to predict islet autoimmunity is also associated with disease progression., Results: Islet autoantibody-positive children with a genetic risk score in the lowest quartile had a slower progression from single to multiple autoantibodies (p=0.018), from single autoantibodies to diabetes (p=0.004), and by trend from multiple islet autoantibodies to diabetes (p=0.06). In a Cox proportional hazards analysis, faster progression was associated with an increased genetic risk score independently of HLA genotype (HR for progression from multiple autoantibodies to type 1 diabetes, 1.27, 95% CI 1.02 to 1.58 per unit increase), an earlier age of islet autoantibody development (HR, 0.68, 95% CI 0.58 to 0.81 per year increase in age) and female sex (HR, 1.94, 95% CI 1.28 to 2.93)., Conclusions: Genetic risk scores may be used to identify islet autoantibody-positive children with high-risk HLA genotypes who have a slow rate of progression to subsequent stages of autoimmunity and type 1 diabetes., Competing Interests: Competing interests: A patent has been applied for (LU100334) with the title ‘Method the risk to develop type 1 diabetes’ by Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt. EB, A-GZ and CW are among the inventors. The patent includes the genetic score that is examined in the manuscript., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Islet autoantibody (iAb)-positive individuals have a high risk of progression to type 1 diabetes (T1D), although the rate of progression is highly variable and factors involved in the rate of progression are largely unknown. The ratio of unmethylated/methylated insulin DNA levels (unmethylated INS ratio) has been shown to be higher in participants at high risk of T1D compared to healthy controls. We aimed to evaluate whether an unmethylated INS ratio may be a useful biomarker of beta cell death and rate of progression to T1D. In TrialNet participants who were followed in the Pathway to Prevention Study and progressed to diabetes ( n = 57, median age of onset 15.3 years), we measured unmethylated INS ratio and autoantibodies by electrochemiluminescence (ECL) assays (ECL-IAA, ECL-GADA, and ECL-IA2) and radioimmunoassays (RIA) (mIAA, GADA, IA2A, and ZnT8A) longitudinally for 24 months prior to diagnosis. Linear models were used to test the association between unmethylated INS ratio and the age at T1D diagnosis and unmethylated INS ratio and iAb over time. Close to diabetes onset, the unmethylated INS ratio was associated with mIAA ( p = 0.003), ECL-IAA ( p = 0.002), and IA2A ( p = 0.01) levels, but not with GADA, ECL-GADA, ECL-IA2, or ZnT8A levels. No significant associations were found at baseline (24 months prior to T1D diagnosis). Only mIAA levels were significantly associated with an unmethylated INS ratio over time, with a 0.24 change in the ratio for each 0.1 change in mIAA z-score ( p = 0.02). Adjusting for a baseline unmethylated INS ratio, an increased rate of change in unmethylated INS ratio from baseline to diabetes onset was associated with a five-year decrease in age at T1D diagnosis ( p = 0.04).

Context: Accurate measures are needed for the prediction and diagnosis of type 1 diabetes (T1D) in at-risk persons., Objective: The purpose of this study was to explore the value of continuous glucose monitoring (CGM) in predicting T1D onset., Design and Setting: The Diabetes Autoimmunity Study in the Young (DAISY) prospectively follows children at increased risk for development of islet autoantibodies (islet autoantibody positive; Ab+) and T1D., Participants: We analyzed 23 Ab+ participants with available longitudinal CGM data., Main Outcome Measure: CGM metrics as glycemic predictors of progression to T1D., Results: Of 23 Ab+ participants with a baseline CGM, 8 progressed to diabetes at a median age of 13.8 years during a median follow-up of 17.7 years (interquartile range, 14.6 to 22.0 years). Compared with nonprogressors, participants who progressed to diabetes had significantly increased baseline glycemic variability (SD, 29 vs 21 mg/dL; P = 0.047), daytime sensor average (122 vs 106 mg/dL; P = 0.02), and daytime sensor area under the curve (AUC, 470,370 vs 415,465; P = 0.047). They spent 24% of time at >140 mg/dL and 12% at >160 mg/dL compared with, respectively, 8% and 3% for nonprogressors (both P = 0.005). A receiver-operating characteristic curve analysis showed an AUC of 0.85 for percentage of time spent at >140 or 160 mg/dL. The cutoff of 18% time spent at >140 mg/dL had 75% sensitivity, 100% specificity, and a 100% positive predictive value for diabetes prediction, although these values could change because some nonprogressors may develop diabetes with longer follow-up., Conclusions: Eighteen percent or greater CGM time spent at >140 mg/dL predicts progression to diabetes in Ab+ children., (Copyright © 2019 Endocrine Society.)

Current efforts to prevent progression from islet autoimmunity to type 1 diabetes largely focus on immunomodulatory approaches. However, emerging data suggest that the development of diabetes in islet autoantibody-positive individuals may also involve factors such as obesity and genetic variants associated with type 2 diabetes, and the influence of these factors increases with age at diagnosis. Although these factors have been linked with metabolic outcomes, particularly through their impact on β-cell function and insulin sensitivity, growing evidence suggests that they might also interact with the immune system to amplify the autoimmune response. The presence of factors shared by both forms of diabetes contributes to disease heterogeneity and thus has important implications. Characteristics that are typically considered to be nonimmune should be incorporated into predictive algorithms that seek to identify at-risk individuals and into the designs of trials for disease prevention. The heterogeneity of diabetes also poses a challenge in diagnostic classification. Finally, after clinically diagnosing type 1 diabetes, addressing nonimmune elements may help to prevent further deterioration of β-cell function and thus improve clinical outcomes. This Perspectives in Care article highlights the role of type 2 diabetes-associated genetic factors (e.g., gene variants at transcription factor 7-like 2 [ TCF7L2 ]) and obesity (via insulin resistance, inflammation, β-cell stress, or all three) in the pathogenesis of type 1 diabetes and their impacts on age at diagnosis. Recognizing that type 1 diabetes might result from the sum of effects from islet autoimmunity and type 2 diabetes-associated factors, their interactions, or both affects disease prediction, prevention, diagnosis, and treatment., (© 2019 by the American Diabetes Association.)

Objective: The capacity to precisely predict progression to type 1 diabetes (T1D) in young children over a short time span is an unmet need. We sought to develop a risk algorithm to predict progression in children with high-risk human leukocyte antigen (HLA) genes followed in The Environmental Determinants of Diabetes in the Young (TEDDY) study., Methods: Logistic regression and 4-fold cross-validation examined 38 candidate predictors of risk from clinical, immunologic, metabolic, and genetic data. TEDDY subjects with at least one persistent, confirmed autoantibody at age 3 were analyzed with progression to T1D by age 6 serving as the primary endpoint. The logistic regression prediction model was compared to two non-statistical predictors, multiple autoantibody status, and presence of insulinoma-associated-2 autoantibodies (IA-2A)., Results: A total of 363 subjects had at least one autoantibody at age 3. Twenty-one percent of subjects developed T1D by age 6. Logistic regression modeling identified 5 significant predictors - IA-2A status, hemoglobin A1c, body mass index Z-score, single-nucleotide polymorphism rs12708716&#95;G, and a combination marker of autoantibody number plus fasting insulin level. The logistic model yielded a receiver operating characteristic area under the curve (AUC) of 0.80, higher than the two other predictors; however, the differences in AUC, sensitivity, and specificity were small across models., Conclusions: This study highlights the application of precision medicine techniques to predict progression to diabetes over a 3-year window in TEDDY subjects. This multifaceted model provides preliminary improvement in prediction over simpler prediction tools. Additional tools are needed to maximize the predictive value of these approaches., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

The risk for autoimmunity and subsequently type 1 diabetes is 10-fold higher in children with a first-degree family history of type 1 diabetes (FDR children) than in children in the general population (GP children). We analyzed children with high-risk HLA genotypes ( n = 4,573) in the longitudinal TEDDY birth cohort to determine how much of the divergent risk is attributable to genetic enrichment in affected families. Enrichment for susceptible genotypes of multiple type 1 diabetes-associated genes and a novel risk gene, BTNL2 , was identified in FDR children compared with GP children. After correction for genetic enrichment, the risks in the FDR and GP children converged but were not identical for multiple islet autoantibodies (hazard ratio [HR] 2.26 [95% CI 1.6-3.02]) and for diabetes (HR 2.92 [95% CI 2.05-4.16]). Convergence varied depending upon the degree of genetic susceptibility. Risks were similar in the highest genetic susceptibility group for multiple islet autoantibodies (14.3% vs .12.7%) and diabetes (4.8% vs. 4.1%) and were up to 5.8-fold divergent for children in the lowest genetic susceptibility group, decreasing incrementally in GP children but not in FDR children. These findings suggest that additional factors enriched within affected families preferentially increase the risk of autoimmunity and type 1 diabetes in lower genetic susceptibility strata., (© 2019 by the American Diabetes Association.)

Objective: Genetic risk scores (GRS) have been developed that differentiate individuals with type 1 diabetes from those with other forms of diabetes and are starting to be used for population screening; however, most studies were conducted in European-ancestry populations. This study identifies novel genetic variants associated with type 1 diabetes risk in African-ancestry participants and develops an African-specific GRS., Research Design and Methods: We generated single nucleotide polymorphism (SNP) data with the ImmunoChip on 1,021 African-ancestry participants with type 1 diabetes and 2,928 control participants. HLA class I and class II alleles were imputed using SNP2HLA. Logistic regression models were used to identify genome-wide significant ( P < 5.0 × 10 -8 ) SNPs associated with type 1 diabetes in the African-ancestry samples and validate SNPs associated with risk in known European-ancestry loci ( P < 2.79 × 10 -5 )., Results: African-specific (HLA- DQA1 *03:01-HLA- DQB1 *02:01) and known European-ancestry HLA haplotypes (HLA- DRB1 *03:01-HLA- DQA1 *05:01-HLA- DQB1 *02:01, HLA- DRB1 *04:01-HLA- DQA1 *03:01-HLA- DQB1 *03:02) were significantly associated with type 1 diabetes risk. Among European-ancestry defined non-HLA risk loci, six risk loci were significantly associated with type 1 diabetes in subjects of African ancestry. An African-specific GRS provided strong prediction of type 1 diabetes risk (area under the curve 0.871), performing significantly better than a European-based GRS and two polygenic risk scores in independent discovery and validation cohorts., Conclusions: Genetic risk of type 1 diabetes includes ancestry-specific, disease-associated variants. The GRS developed here provides improved prediction of type 1 diabetes in African-ancestry subjects and a means to identify groups of individuals who would benefit from immune monitoring for early detection of islet autoimmunity., (© 2019 by the American Diabetes Association.)

Objective: There are variable reports of risk of concordance for progression to islet autoantibodies and type 1 diabetes in identical twins after one twin is diagnosed. We examined development of positive autoantibodies and type 1 diabetes and the effects of genetic factors and common environment on autoantibody positivity in identical twins, nonidentical twins, and full siblings., Research Design and Methods: Subjects from the TrialNet Pathway to Prevention Study ( N = 48,026) were screened from 2004 to 2015 for islet autoantibodies (GAD antibody [GADA], insulinoma-associated antigen 2 [IA-2A], and autoantibodies against insulin [IAA]). Of these subjects, 17,226 (157 identical twins, 283 nonidentical twins, and 16,786 full siblings) were followed for autoantibody positivity or type 1 diabetes for a median of 2.1 years., Results: At screening, identical twins were more likely to have positive GADA, IA-2A, and IAA than nonidentical twins or full siblings (all P < 0.0001). Younger age, male sex, and genetic factors were significant factors for expression of IA-2A, IAA, one or more positive autoantibodies, and two or more positive autoantibodies (all P ≤ 0.03). Initially autoantibody-positive identical twins had a 69% risk of diabetes by 3 years compared with 1.5% for initially autoantibody-negative identical twins. In nonidentical twins, type 1 diabetes risk by 3 years was 72% for initially multiple autoantibody-positive, 13% for single autoantibody-positive, and 0% for initially autoantibody-negative nonidentical twins. Full siblings had a 3-year type 1 diabetes risk of 47% for multiple autoantibody-positive, 12% for single autoantibody-positive, and 0.5% for initially autoantibody-negative subjects., Conclusions: Risk of type 1 diabetes at 3 years is high for initially multiple and single autoantibody-positive identical twins and multiple autoantibody-positive nonidentical twins. Genetic predisposition, age, and male sex are significant risk factors for development of positive autoantibodies in twins., (© 2018 by the American Diabetes Association.)

Objective: The type 2 diabetes-associated alleles at the TCF7L2 locus mark a type 1 diabetes phenotype characterized by single islet autoantibody positivity as well as lower glucose and higher C-peptide measures. Here, we studied whether the TCF7L2 locus influences progression of islet autoimmunity, from single to multiple (≥2) autoantibody positivity, in relatives of patients with type 1 diabetes., Research Design and Methods: We evaluated 244 participants in the Type 1 Diabetes TrialNet Pathway to Prevention study with confirmed single autoantibody positivity at screening and Immunochip single nucleotide polymorphism data (47.5% male; median age 12.8 years, range 1.2-45.9; 90.2% white). We analyzed risk allele frequency at TCF7L2 rs4506565 (in linkage disequilibrium with rs7903146). Altogether, 62.6% participants carried ≥1 risk allele. Univariate and multivariable Cox proportional hazards models and Kaplan-Meier statistical methods were used., Results: During follow-up (median 5.2 years, range 0.2-12.6), 62% of the single autoantibody-positive participants developed multiple autoantibody positivity. In the overall cohort, the TCF7L2 locus did not significantly predict progression to multiple autoantibody positivity. However, among single GAD65 autoantibody-positive participants ( n = 158), those who carried ≥1 risk allele had a lower rate of progression to multiple autoantibody positivity (hazard ratio [HR] 0.65, P = 0.033) than those who did not, after adjustment for HLA risk haplotypes and age. Among subjects who were either IA-2 or insulin autoantibody positive only, carrying ≥1 TCF7L2 risk allele was not a significant factor overall, but in overweight or obese participants, it increased the risk of progression to multiple autoantibody positivity (HR 3.02, P = 0.016) even with adjustment for age., Conclusions: The type 2 diabetes-associated TCF7L2 locus influences progression of islet autoimmunity, with differential effects by autoantibody specificity and interaction by obesity/overweight., (© 2018 by the American Diabetes Association.)

Type 1 diabetes (T1D) is most likely caused by killing of β cells by autoreactive CD8 + T cells. Methods to isolate and identify these cells are limited by their low frequency in the peripheral blood. We analyzed CD8 + T cells, reactive with diabetes Ags, with T cell libraries and further characterized their phenotype by CyTOF using class I MHC tetramers. In the libraries, the frequency of islet Ag-specific CD45RO + IFN-γ + CD8 + T cells was higher in patients with T1D compared with healthy control subjects. Ag-specific cells from the libraries of patients with T1D were reactive with ZnT8 186-194 , whereas those from healthy control recognized ZnT8 186-194 and other Ags. ZnT8 186-194 -reactive CD8 + cells expressed an activation phenotype in T1D patients. We found TCR sequences that were used in multiple library wells from patients with T1D, but these sequences were private and not shared between individuals. These sequences could identify the Ag-specific T cells on a repeated draw, ex vivo in the IFN-γ + CD8 + T cell subset. We conclude that CD8 + T cell libraries can identify Ag-specific T cells in patients with T1D. The T cell clonotypes can be tracked in vivo with identification of the TCR gene sequences., (Copyright © 2018 by The American Association of Immunologists, Inc.)

Objective: We tested the ability of a type 1 diabetes (T1D) genetic risk score (GRS) to predict progression of islet autoimmunity and T1D in at-risk individuals., Research Design and Methods: We studied the 1,244 TrialNet Pathway to Prevention study participants (T1D patients' relatives without diabetes and with one or more positive autoantibodies) who were genotyped with Illumina ImmunoChip (median [range] age at initial autoantibody determination 11.1 years [1.2-51.8], 48% male, 80.5% non-Hispanic white, median follow-up 5.4 years). Of 291 participants with a single positive autoantibody at screening, 157 converted to multiple autoantibody positivity and 55 developed diabetes. Of 953 participants with multiple positive autoantibodies at screening, 419 developed diabetes. We calculated the T1D GRS from 30 T1D-associated single nucleotide polymorphisms. We used multivariable Cox regression models, time-dependent receiver operating characteristic curves, and area under the curve (AUC) measures to evaluate prognostic utility of T1D GRS, age, sex, Diabetes Prevention Trial-Type 1 (DPT-1) Risk Score, positive autoantibody number or type, HLA DR3/DR4-DQ8 status, and race/ethnicity. We used recursive partitioning analyses to identify cut points in continuous variables., Results: Higher T1D GRS significantly increased the rate of progression to T1D adjusting for DPT-1 Risk Score, age, number of positive autoantibodies, sex, and ethnicity (hazard ratio [HR] 1.29 for a 0.05 increase, 95% CI 1.06-1.6; P = 0.011). Progression to T1D was best predicted by a combined model with GRS, number of positive autoantibodies, DPT-1 Risk Score, and age (7-year time-integrated AUC = 0.79, 5-year AUC = 0.73). Higher GRS was significantly associated with increased progression rate from single to multiple positive autoantibodies after adjusting for age, autoantibody type, ethnicity, and sex (HR 2.27 for GRS >0.295, 95% CI 1.47-3.51; P = 0.0002)., Conclusions: The T1D GRS independently predicts progression to T1D and improves prediction along T1D stages in autoantibody-positive relatives., (© 2018 by the American Diabetes Association.)

Background: The duration and patterns of β cell dysfunction during type 1 diabetes (T1D) development have not been fully defined., Methods: Metabolic measures derived from oral glucose tolerance tests (OGTTs) were compared between autoantibody-positive (aAb+) individuals followed in the TrialNet Pathway to Prevention study who developed diabetes after 5 or more years or less than 5 years of longitudinal follow-up (Progressors≥5, n = 75; Progressors<5, n = 474) and 144 aAb-negative (aAb-) relatives., Results: Mean age at study entry was 15.0 ± 12.6 years for Progressors≥5; 12.0 ± 9.1 for Progressors<5; and 16.3 ± 10.4 for aAb- relatives. At baseline, Progressors≥5 already exhibited significantly lower fasting C-peptide (P < 0.01), C-peptide AUC (P < 0.001), and early C-peptide responses (30- to 0-minute C-peptide; P < 0.001) compared with aAb- relatives, while 2-hour glucose (P = 0.03), glucose AUC (<0.001), and Index60 (<0.001) were all higher. Despite significant baseline impairment, metabolic measures in Progressors≥5 were relatively stable until 2 years prior to T1D diagnosis, when there was accelerated C-peptide decline and rising glycemia from 2 years until diabetes diagnosis. Remarkably, patterns of progression within 3 years of diagnosis were nearly identical between Progressors≥5 and Progressors<5., Conclusion: These data provide insight into the chronicity of β cell dysfunction in T1D and indicate that β cell dysfunction may precede diabetes diagnosis by more than 5 years in a subset of aAb+ individuals. Even among individuals with varying lengths of aAb positivity, our findings indicate that patterns of metabolic decline are uniform within the last 3 years of progression to T1D., Trial Registration: Clinicaltrials.gov NCT00097292., Funding: The Type 1 Diabetes TrialNet Study Group is a clinical trials network currently funded by the NIH through the National Institute of Diabetes and Digestive and Kidney Diseases, the National Institute of Allergy and Infectious Diseases, and The Eunice Kennedy Shriver National Institute of Child Health and Human Development and the Juvenile Diabetes Research Foundation.

Background: Diagnosis of type 1 diabetes often causes a negative psychological impact on families. We examined whether parents and children enrolled in The Environmental Determinants of Diabetes in the Young (TEDDY) study differ in their psychological adjustment to diabetes diagnosis compared to children diagnosed with diabetes in the community., Methods: TEDDY follows 8676 children at genetic risk for type 1 diabetes from birth. Fifty-four TEDDY children diagnosed with diabetes and 54 age-matched community control children diagnosed with diabetes were enrolled. Participants were aged 3 to 10 years and study visits occurred at 3, 6, and 12 months postdiagnosis. Psychological measures included an adapted diabetes-specific State Anxiety Inventory, the Pediatric Quality of Life Inventory-Diabetes Module, and the Pediatric Inventory for Parents, which measures frequency and difficulty of parenting stress., Results: A generalized estimating equation analysis based on a difference score between TEDDY children and community controls found no significant differences between TEDDY parents and community controls on parent diabetes-specific anxiety (P = .30). However, TEDDY children exhibited better diabetes-specific quality of life (P = .03) and TEDDY parents reported lower frequency (P = .004) and difficulty (P = .008) of parenting stress compared to community controls., Conclusions: Children diagnosed with at-risk for type 1 diabetes who have previously enrolled in research monitoring have improved diabetes quality of life and lower parenting stress postdiagnosis compared to children diagnosed in the community. Families in follow-up studies may be more prepared if their child is diagnosed with diabetes., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

While full oral glucose tolerance test (OGTT) helps improve prediction, it requires intravenous access with 6 sample collections for glucose and C-peptide. The objective of this study was to explore less costly and less time-consuming options. All children being prospectively followed by the Diabetes Autoimmunity Study in the Young (DAISY) who had a complete baseline OGTT and at least one confirmed islet autoantibody (Ab+) were included in this study (n = 68). Of 68 Ab+ subjects with a baseline OGTT, 25 developed diabetes after a mean follow-up 5.7 yrs, at a mean age of 12.4 yrs. Univariate proportional hazards (PH) models suggested that age at seroconversion, number of Ab+, IA-2A levels, HbA1c and metabolic variables from the OGTT predicted progression to diabetes, while HLA DR3/4, BMI, levels of IAA or GADA did not. Five multivariate PH predictive models were similar (p = 0.32). All five models included age at seroconversion, number of Ab+, IA-2A levels and HbA1c, and in addition included: model 1 - 1 h glucose and 1 h C-peptide; model 2 - 2 h glucose and 2 h C-peptide; model 3 - glucose sum and C-peptide sum; model 4 - glucose AUC and C-peptide AUC; and model 5: index 60. A model containing age at seroconversion, number of Ab+, IA-2A levels, HbA1c, 1 h glucose and 1 h C-peptide was as predictive for type 1 diabetes progression as models including all sum or AUC values for glucose and C-peptide from full OGTT. The performance of this model should be confirmed in an independent population of Ab+ children., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Aims/hypothesis: Multiple islet autoimmunity increases risk of diabetes, but not all individuals positive for two or more islet autoantibodies progress to disease within a decade. Major islet autoantibodies recognise insulin (IAA), GAD (GADA), islet antigen-2 (IA-2A) and zinc transporter 8 (ZnT8A). Here we describe the baseline characteristics of a unique cohort of 'slow progressors' (n = 132) who were positive for multiple islet autoantibodies (IAA, GADA, IA-2A or ZnT8A) but did not progress to diabetes within 10 years., Methods: Individuals were identified from five studies (BABYDIAB, Germany; Diabetes Autoimmunity Study in the Young [DAISY], USA; All Babies in Southeast Sweden [ABIS], Sweden; Bart's Oxford Family Study [BOX], UK and the Pittsburgh Family Study, USA). Multiple islet autoantibody characteristics were determined using harmonised assays where possible. HLA class II risk was compared between slow progressors and rapid progressors (n = 348 diagnosed <5 years old from BOX) using the χ 2 test., Results: In the first available samples with detectable multiple antibodies, the most frequent autoantibodies were GADA (92%), followed by ZnT8A (62%), IAA (59%) and IA-2A (41%). High risk HLA class II genotypes were less frequent in slow (28%) than rapid progressors (42%, p = 0.011), but only two slow progressors carried the protective HLA DQ6 allele., Conclusion: No distinguishing characteristics of slow progressors at first detection of multiple antibodies have yet been identified. Continued investigation of these individuals may provide insights into slow progression that will inform future efforts to slow or prevent progression to clinical 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., (© 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Traditional linkage analysis and genome-wide association studies have identified HLA and a number of non-HLA genes as genetic factors for islet autoimmunity (IA) and type 1 diabetes (T1D). However, the relative risk associated with previously identified non-HLA genes is usually very small as measured in cases/controls from mixed populations. Genetic associations for IA and T1D may be more accurately assessed in prospective cohorts. In this study, 5806 subjects from the TEDDY (The Environmental Determinants of Diabetes in the Young) study, an international prospective cohort study, were genotyped for 176,586 SNPs on the ImmunoChip. Cox proportional hazards analyses were performed to discover the SNPs associated with the risk for IA, T1D, or both. Three regions were associated with the risk of developing any persistent confirmed islet autoantibody: one known region near SH2B3 (HR = 1.35, p = 3.58 × 10 -7 ) with Bonferroni-corrected significance and another known region near PTPN22 (HR = 1.46, p = 2.17 × 10 -6 ) and one novel region near PPIL2 (HR = 2.47, p = 9.64 × 10 -7 ) with suggestive evidence (p < 10 -5 ). Two known regions (PTPN22: p = 2.25 × 10 -6 , INS; p = 1.32 × 10 -7 ) and one novel region (PXK/PDHB: p = 8.99 × 10 -6 ) were associated with the risk for multiple islet autoantibodies. First appearing islet autoantibodies differ with respect to association. Two regions (INS: p = 5.67 × 10 -6 and TTC34/PRDM16: 6.45 × 10 -6 ) were associated if the fist appearing autoantibody was IAA and one region (RBFOX1: p = 8.02 × 10 -6 ) was associated if the first appearing autoantibody was GADA. The analysis of T1D identified one region already known to be associated with T1D (INS: p = 3.13 × 10 -7 ) and three novel regions (RNASET2, PLEKHA1, and PPIL2; 5.42 × 10 -6  > p > 2.31 × 10 -6 ). These results suggest that a number of low frequency variants influence the risk of developing IA and/or T1D and these variants can be identified by large prospective cohort studies using a survival analysis approach., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Background: Around 0.3% of newborns will develop autoimmunity to pancreatic beta cells in childhood and subsequently develop type 1 diabetes before adulthood. Primary prevention of type 1 diabetes will require early intervention in genetically at-risk infants. The objective of this study was to determine to what extent genetic scores (two previous genetic scores and a merged genetic score) can improve the prediction of type 1 diabetes., Methods and Findings: The Environmental Determinants of Diabetes in the Young (TEDDY) study followed genetically at-risk children at 3- to 6-monthly intervals from birth for the development of islet autoantibodies and type 1 diabetes. Infants were enrolled between 1 September 2004 and 28 February 2010 and monitored until 31 May 2016. The risk (positive predictive value) for developing multiple islet autoantibodies (pre-symptomatic type 1 diabetes) and type 1 diabetes was determined in 4,543 children who had no first-degree relatives with type 1 diabetes and either a heterozygous HLA DR3 and DR4-DQ8 risk genotype or a homozygous DR4-DQ8 genotype, and in 3,498 of these children in whom genetic scores were calculated from 41 single nucleotide polymorphisms. In the children with the HLA risk genotypes, risk for developing multiple islet autoantibodies was 5.8% (95% CI 5.0%-6.6%) by age 6 years, and risk for diabetes by age 10 years was 3.7% (95% CI 3.0%-4.4%). Risk for developing multiple islet autoantibodies was 11.0% (95% CI 8.7%-13.3%) in children with a merged genetic score of >14.4 (upper quartile; n = 907) compared to 4.1% (95% CI 3.3%-4.9%, P < 0.001) in children with a genetic score of ≤14.4 (n = 2,591). Risk for developing diabetes by age 10 years was 7.6% (95% CI 5.3%-9.9%) in children with a merged score of >14.4 compared with 2.7% (95% CI 1.9%-3.6%) in children with a score of ≤14.4 (P < 0.001). Of 173 children with multiple islet autoantibodies by age 6 years and 107 children with diabetes by age 10 years, 82 (sensitivity, 47.4%; 95% CI 40.1%-54.8%) and 52 (sensitivity, 48.6%, 95% CI 39.3%-60.0%), respectively, had a score >14.4. Scores were higher in European versus US children (P = 0.003). In children with a merged score of >14.4, risk for multiple islet autoantibodies was similar and consistently >10% in Europe and in the US; risk was greater in males than in females (P = 0.01). Limitations of the study include that the genetic scores were originally developed from case-control studies of clinical diabetes in individuals of mainly European decent. It is, therefore, possible that it may not be suitable to all populations., Conclusions: A type 1 diabetes genetic score identified infants without family history of type 1 diabetes who had a greater than 10% risk for pre-symptomatic type 1 diabetes, and a nearly 2-fold higher risk than children identified by high-risk HLA genotypes alone. This finding extends the possibilities for enrolling children into type 1 diabetes primary prevention trials.

Background: Genetic predisposition for type 1 diabetes (T1D) is largely determined by human leukocyte antigen (HLA) genes; however, over 50 other genetic regions confer susceptibility. We evaluated a previously reported 10-factor weighted model derived from the Type 1 Diabetes Genetics Consortium to predict the development of diabetes in the Diabetes Autoimmunity Study in the Young (DAISY) prospective cohort. Performance of the model, derived from individuals with first-degree relatives (FDR) with T1D, was evaluated in DAISY general population (GP) participants as well as FDR subjects., Methods: The 10-factor weighted risk model (HLA, PTPN22 , INS , IL2RA , ERBB3 , ORMDL3 , BACH2 , IL27 , GLIS3 , RNLS ), 3-factor model (HLA, PTPN22, INS ), and HLA alone were compared for the prediction of diabetes in children with complete SNP data (n = 1941)., Results: Stratification by risk score significantly predicted progression to diabetes by Kaplan-Meier analysis (GP: P = .00006; FDR: P = .0022). The 10-factor model performed better in discriminating diabetes outcome than HLA alone (GP, P = .03; FDR, P = .01). In GP, the restricted 3-factor model was superior to HLA (P = .03), but not different from the 10-factor model (P = .22). In contrast, for FDR the 3-factor model did not show improvement over HLA (P = .12) and performed worse than the 10-factor model (P = .02) CONCLUSIONS: We have shown a 10-factor risk model predicts development of diabetes in both GP and FDR children. While this model was superior to a minimal model in FDR, it did not confer improvement in GP. Differences in model performance in FDR vs GP children may lead to important insights into screening strategies specific to these groups., (© 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Objective: The phenotypic diversity of type 1 diabetes suggests heterogeneous etiopathogenesis. We investigated the relationship of type 2 diabetes-associated transcription factor 7 like 2 ( TCF7L2 ) single nucleotide polymorphisms (SNPs) with immunologic and metabolic characteristics at type 1 diabetes diagnosis., Research Design and Methods: We studied TrialNet participants with newly diagnosed autoimmune type 1 diabetes with available TCF7L2 rs4506565 and rs7901695 SNP data ( n = 810; median age 13.6 years; range 3.3-58.6). We modeled the influence of carrying a TCF7L2 variant (i.e., having 1 or 2 minor alleles) on the number of islet autoantibodies and oral glucose tolerance test (OGTT)-stimulated C-peptide and glucose measures at diabetes diagnosis. All analyses were adjusted for known confounders., Results: The rs4506565 variant was a significant independent factor of expressing a single autoantibody, instead of multiple autoantibodies, at diagnosis (odds ratio [OR] 1.66 [95% CI 1.07, 2.57], P = 0.024). Interaction analysis demonstrated that this association was only significant in participants ≥12 years old ( n = 504; OR 2.12 [1.29, 3.47], P = 0.003) but not younger ones ( n = 306, P = 0.73). The rs4506565 variant was independently associated with higher C-peptide area under the curve (AUC) ( P = 0.008) and lower mean glucose AUC ( P = 0.0127). The results were similar for the rs7901695 SNP., Conclusions: In this cohort of individuals with new-onset type 1 diabetes, type 2 diabetes-linked TCF7L2 variants were associated with single autoantibody (among those ≥12 years old), higher C-peptide AUC, and lower glucose AUC levels during an OGTT. Thus, carriers of the TCF7L2 variant had a milder immunologic and metabolic phenotype at type 1 diabetes diagnosis, which could be partly driven by type 2 diabetes-like pathogenic mechanisms., (© 2017 by the American Diabetes Association.)

Background: Maturity-onset diabetes of the young (MODY) is an antibody-negative, autosomal dominant form of diabetes. With the increasing prevalence of diabetes and the expense of MODY testing, markers to identify those who need further genetic testing would be beneficial. We investigated whether HLA genotypes, random C-peptide, and/or high-sensitivity C-reactive protein (hsCRP) levels could be helpful biomarkers for identifying MODY in antibody-negative diabetes., Methods: Subjects (N = 97) with diabetes onset ≤age 25, measurable C-peptide (≥0.1 ng/mL), and negative for all four diabetes autoantibodies were enrolled at a large academic center and tested for MODY 1-5 through Athena Diagnostics. A total of 22 subjects had a positive or very likely pathogenic mutation for MODY., Results: Random C-peptide levels were significantly different between MODY-positive and MODY-negative subjects (0.16 nmol/L vs. 0.02 nmol/L; P = 0.02). After adjusting for age and diabetes duration, hsCRP levels were significantly lower in MODY-positive subjects (0.37 mg/L vs. 0.87 mg/L; P = 0.02). Random C-peptide level ≥0.15 nmol/L obtained at ≥6 months after diagnosis had 83% sensitivity for diagnosis of MODY with a negative predictive value of 96%. Receiver operating characteristic curves showed that area under the curve for random C-peptide (0.75) was significantly better than hsCRP (0.54), high-risk HLA DR3/4-DQB1*0302 (0.59), and high-risk HLA/random C-peptide combined (0.54; P = 0.03)., Conclusions: Random C-peptide obtained at ≥6 months after diagnosis can be a useful biomarker to identify antibody-negative individuals who need further genetic testing for MODY, whereas hsCRP and HLA do not appear to improve this antibody/C-peptide-based approach.

Objective: To explore whether children diagnosed with type 1 diabetes during islet autoantibody surveillance through The Environmental Determinants of Diabetes in the Young (TEDDY) study retain greater islet function than children diagnosed through the community., Methods: TEDDY children identified at birth with high-risk human leukocyte antigen and followed every 3 months until diabetes diagnosis were compared to age-matched children diagnosed with diabetes in the community. Both participated in long-term follow up after diagnosis. Hemoglobin A1c (HbA1c) and mixed meal tolerance test were performed within 1 month of diabetes onset, then at 3, 6, and 12 months, and biannually thereafter., Results: Comparison of 43 TEDDY and 43 paired control children showed that TEDDY children often had no symptoms (58%) at diagnosis and none had diabetic ketoacidosis (DKA) compared with 98% with diabetes symptoms and 14% DKA in the controls (P < 0.001 and P = 0.03, respectively). At diagnosis, mean HbA1c was lower in TEDDY (6.8%, 51 mmol/mol) than control (10.5%, 91 mmol/mol) children (P < 0.0001). TEDDY children had significantly higher area under the curve and peak C-peptide values than the community controls throughout the first year postdiagnosis. Total insulin dose and insulin dose-adjusted A1c were lower throughout the first year postdiagnosis for TEDDY compared with control children., Conclusions: Higher C-peptide levels in TEDDY vs community-diagnosed children persist for at least 12 months following diabetes onset and appear to represent a shift in the disease process of about 6 months. Symptom-free diagnosis, reduction of DKA, and the potential for immune intervention with increased baseline C-peptide may portend additional long-term benefits of early diagnosis., (© 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Purpose of Review: About 50% of the heritability of type 1 diabetes (T1D) is attributed to human leukocyte antigen (HLA) alleles and the remainder to several (close to 50) non-HLA loci. A current challenge in the field of the genetics of T1D is to apply the knowledge accumulated in the last 40 years towards differential diagnosis and risk assessment., Recent Findings: T1D genetic risk scores seek to combine the information from HLA and non-HLA alleles to improve the accuracy of diagnosis, prediction, and prognosis. Here, we describe genetic risk scores that have been developed and validated in various settings and populations. Several genetic scores have been proposed that merge disease risk information from multiple genetic factors to optimize the use of genetic information and ultimately improve prediction and diagnosis of T1D.

Context: Genome-wide association studies identified >50 type 1 diabetes (T1D) associated non-human leukocyte antigens (non-HLA) loci., Objective: The purpose of this study was to assess the contribution of non-HLA single nucleotide polymorphisms (SNPs) to risk of disease progression., Design and Setting: The TrialNet Pathway to Prevention Study follows relatives of T1D patients for development of autoantibodies (Abs) and T1D., Participants: Using the Immunochip, we analyzed 53 diabetes-associated, non-HLA SNPs in 1016 Ab-positive, at-risk non-Hispanic white relatives., Main Outcome Measure: Effect of SNPs on the development of multiple Abs and T1D., Results: Cox proportional analyses included all substantial non-HLA SNPs, HLA genotypes, relationship to proband, sex, age at initial screening, initial Ab type, and number. Factors involved in progression from single to multiple Abs included age at screening, relationship to proband, HLA genotypes, and rs3087243 (cytotoxic T lymphocyte antigen-4). Significant factors for diabetes progression included age at screening, Ab number, HLA genotypes, rs6476839 [GLIS family zinc finger 3 (GLIS3)], and rs3184504 [SH2B adaptor protein 3 (SH2B3)]. When glucose area under the curve (AUC) was included, factors involved in disease progression included glucose AUC, age at screening, Ab number, relationship to proband, HLA genotypes, rs6476839 (GLIS3), and rs7221109 (CCR7). In stratified analyses by age, glucose AUC, age at screening, sibling, HLA genotypes, rs6476839 (GLIS3), and rs4900384 (C14orf64) were significantly associated with progression to diabetes in participants <12 years old, whereas glucose AUC, sibling, rs3184504 (SH2B3), and rs4900384 (C14orf64) were significant in those ≥12., Conclusions: In conclusion, we identified five non-HLA SNPs associated with increased risk of progression from Ab positivity to disease that may improve risk stratification for prevention trials., (Copyright © 2017 by the Endocrine Society)

Purpose of Review: Type 1 diabetes (T1D) is now predictable by measuring major islet autoantibodies (IAbs) against insulin and other pancreatic β cells proteins including GAD65 (GADA), islet antigen 2 (IA-2A), and zinc transporter 8 (ZnT8A). The assay technology for IAbs has made great progress; however, several important aspects still need to be addressed and improved., Recent Findings: Currently a radio-binding assay has been well established as the 'gold' standard assay for all four IAbs. New generation of nonradioactive IAb assay with electrochemiluminescence technology has been shown to further improve sensitivity and disease specificity. Recently, multiplexed assays have opened the possibility of more efficient screening in large populations. Identification of potential new autoantibodies to neo-antigens or neo-epitopes posttranslational modification is a new important field to be explored., Summary: Individuals having a single positive autoantibody are at low risk for progression to T1D, whereas individuals expressing two or more positive autoantibodies, especially on multiple tests over time, have nearly 100% risk of developing clinical T1D when followed for over two decades. More efficient and cost effective IAb assays will hopefully lead to point-of-care screening in the general population.

Context: Islet autoantibodies are markers of type 1 diabetes, and an increase in number of autoantibodies detected during the preclinical phase predicts progression to overt disease., Objective: To refine the effect of age in relation to islet antibody type on progression from single to multiple autoantibodies in relatives of people with type 1 diabetes., Research Design and Methods: We examined 994 relatives with normal glucose tolerance who were positive for a single autoantibody, followed prospectively in the TrialNet Pathway to Prevention. Antibodies to glutamic acid decarboxylase (GADA), insulin (IAA), insulinoma-associated antigen 2, and zinc transporter 8 and islet cell antibodies were tested every 6 to 12 months. The primary outcome was confirmed development of multiple autoantibodies. Age was categorized as <8 years, 8 to 11 years, 12 to 17 years, and ≥18 years, and optimal age breakpoints were identified by recursive partitioning analysis., Results: After median follow-up of 2 years, 141 relatives had developed at least one additional autoantibodies. Five-year risk was inversely related to age, but the pattern differed by antibody type: Relatives with GADA showed a gradual decrease in risk over the four age groups, whereas relatives with IAA showed a sharp decrease above age 8 years. Recursive partitioning analysis identified age breakpoints at 14 years in relatives with GADA and at 4 years in relatives with IAA., Conclusions: In relatives with IAA, spread of islet autoimmunity is largely limited to early childhood, whereas immune responses initially directed at glutamic acid decarboxylase can mature over a longer period. These differences have important implications for monitoring these patients and for designing prevention trials., (Copyright © 2017 Endocrine Society)

Aims: To evaluate the feasibility of using self-collected capillary blood samples for islet autoantibody testing to identify risk in relatives of people with Type 1 diabetes., Methods: Participants were recruited via the observational TrialNet Pathway to Prevention study, which screens and monitors relatives of people with Type 1 diabetes for islet autoantibodies. Relatives were sent kits for capillary blood collection, with written instructions, an online instructional video link and a questionnaire. Sera from capillary blood samples were tested for autoantibodies to glutamic acid decarboxylase, islet antigen-2, insulin and zinc transporter 8. 'Successful' sample collection was defined as obtaining sufficient volume and quality to provide definitive autoantibody results, including confirmation of positive results by repeat assay., Results: In 240 relatives who returned samples, the median (range) age was 15.5 (1-49) years and 51% were male. Of these samples, 98% were sufficient for glutamic acid decarboxylase, islet antigen-2 and zinc transporter 8 autoantibody testing and 84% for insulin autoantibody testing and complete autoantibody screen. The upper 90% confidence bound for unsuccessful collection was 4.4% for glutamic acid decarboxylase, islet antigen-2 and/or zinc transporter 8 autoantibody assays, and 19.3% for insulin autoantibodies. Despite 43% of 220 questionnaire respondents finding capillary blood collection uncomfortable or painful, 82% preferred home self-collection of capillary blood samples compared with outpatient venepuncture (90% of those aged <8 years, 83% of those aged 9-18 years and 73% of those aged >18 years). The perceived difficulty of collecting capillary blood samples did not affect success rate., Conclusions: Self-collected capillary blood sampling offers a feasible alternative to venous sampling, with the potential to facilitate autoantibody screening for Type 1 diabetes risk., (© 2017 Diabetes UK.)

Aims/hypothesis: We sought to assess the frequency, determinants and prognosis for future diabetes in individuals with islet autoimmunity and whether these factors differ depending on the age of onset of islet autoimmunity., Methods: A prospective cohort (n = 2547) of children from the general population who had a high-risk HLA genotype and children who had a first-degree relative with type 1 diabetes were followed for up to 21 years. Those with the persistent presence of one or more islet autoantibodies were categorised as early-onset (<8 years of age, n = 143, median 3.3 years) or late-onset (≥8 years of age, n = 64, median 11.1 years), and were followed for a median of 7.4 and 4.7 years, respectively. Progression to diabetes was evaluated by Kaplan-Meier analysis with logrank test. Factors associated with progression to diabetes were analysed using the parametric accelerated failure time model., Results: Children with late-onset islet autoimmunity were more likely to be Hispanic or African-American than non-Hispanic white (p = 0.004), and less likely to be siblings of individuals with type 1 diabetes (p = 0.04). The frequencies of the HLA-DR3/4 genotype and non-HLA gene variants associated with type 1 diabetes did not differ between the two groups. However, age and HLA-DR3/4 were important predictors of rate of progression to both the presence of additional autoantibodies and type 1 diabetes. Late-onset islet autoimmunity was more likely to present with a single islet autoantibody (p = 0.01) and revert to an antibody-negative state (p = 0.01). Progression to diabetes was significantly slower in children with late-onset islet autoimmunity (p < 0.001)., Conclusions/interpretation: A late onset of islet autoimmunity is more common in African-American and Hispanic individuals. About half of those with late-onset islet autoimmunity progress to show multiple islet autoantibodies and develop diabetes in adolescence or early adulthood. Further investigation of environmental determinants of late-onset autoimmunity may lead to an understanding of and ability to prevent adolescent and adult-onset type 1 diabetes.

Background: Type 1 diabetes (TID) is characterized by a loss of pancreatic islet beta cell function resulting in loss of insulin production. Genetic and environmental factors may trigger immune responses targeting beta cells thus generating islet antibodies (IA). Immune response pathways involve a cascade of events, initiated by cytokines and chemokines, producing inflammation which can result in tissue damage., Methods: A nested case-control study was performed to identify temporal changes in cytokine levels in 75 DAISY subjects: 25 diagnosed T1D, 25 persistent IA, and 25 controls. Serum samples were selected at four time points: (T1) earliest, (T2) just prior to IA, (T3) just after IA, and (T4) prior to T1D diagnosis or most recent. Cytokines (IFN-α2a, IL-6, IL-17, IL-1β, IP-10, MCP-1, IFN-γ, IL-1α, and IL-1ra) were measured using the Meso Scale Discovery system Human Custom Cytokine 9-Plex assay., Results: Multivariate mixed models adjusting for HLA risk, first-degree relative status, age, and gender, showed MCP-1 and IFN-үto be significantly higher at T3 in T1D compared to IA subjects. At T4, IP-10 was significantly higher in IA subjects than controls., Conclusions: This repeated measures nested case-control study identified increased inflammatory markers in IA children who developed T1D compared to IA children who had not progressed to clinical disease. It also showed increased inflammation in both T1D and IA children when compared to controls. Results suggest inflammation may be related to both the development of IA and progression to T1D.

Background: Electrochemiluminescence (ECL) assays have shown promise for enhancing the prediction of type 1 diabetes (T1D) with autoantibodies. We thus studied relatives of T1D patients to determine whether ECL assays can be used to refine risk assessments for T1D among individuals either positive for single GADA or single mIAA autoantibodies., Subjects and Methods: TrialNet Pathway to Prevention (PTP) study participants with either GADA or mIAA single autoantibodies were tested for ECL positivity during their participation in the TrialNet PTP study. Those ECL positive (ECL + ) were compared with those ECL negative (ECL - ) for conversion to multiple autoantibodies, 6-month glycemic progression (PS6M), and the progression to T1D., Results: The progression to multiple autoantibodies was significantly higher for those GADA/ECL + (n = 107) than those GADA/ECL - (n = 78) (P = 0.001) and for those mIAA/ECL + (n = 24) than those mIAA/ECL - (n = 63) (P < 0.001). The hazard ratios with 95% confidence intervals were 3.42 (1.58-7.39; P < 0.01) for GADA and 8.15 (3.02-22.00; P < 0.001) for mIAA. GADA/ECL + and mIAA/ECL + participants had significantly higher PS6M values than their ECL - counterparts (P = 0.001 for GADA and P = 0.009 for mIAA). Of those GADA/ECL + , 14% progressed to T1D; of those mIAA/ECL + , 17% progressed to T1D. Only 1 individual (positive for GADA) of the 141 who was ECL - progressed to T1D (median follow-up: 5 years)., Conclusion: ECL measurements appear to have utility for natural history studies and prevention trials of individuals with single autoantibodies. Those ECL + are at appreciable risk for developing multiple autoantibodies and for glycemic progression toward T1D, whereas those ECL - are at very low risk.

The incidence of type 1 diabetes (T1D) has substantially increased over the past decade, suggesting a role for non-genetic factors such as epigenetic mechanisms in disease development. Here we present an epigenome-wide association study across 406,365 CpGs in 52 monozygotic twin pairs discordant for T1D in three immune effector cell types. We observe a substantial enrichment of differentially variable CpG positions (DVPs) in T1D twins when compared with their healthy co-twins and when compared with healthy, unrelated individuals. These T1D-associated DVPs are found to be temporally stable and enriched at gene regulatory elements. Integration with cell type-specific gene regulatory circuits highlight pathways involved in immune cell metabolism and the cell cycle, including mTOR signalling. Evidence from cord blood of newborns who progress to overt T1D suggests that the DVPs likely emerge after birth. Our findings, based on 772 methylomes, implicate epigenetic changes that could contribute to disease pathogenesis in T1D., Competing Interests: Paul Flicek is a member of the Scientific Advisory Board for Omicia, Inc. All other authors declare no competing financial interests.

Objective: To explore whether electrochemiluminescence (ECL) assays can help improve prediction of time to type 1 diabetes in the TrialNet autoantibody-positive population., Research Design and Methods: TrialNet subjects who were positive for one or more autoantibodies (microinsulin autoantibody, GAD65 autoantibody [GADA], IA-2A, and ZnT8A) with available ECL-insulin autoantibody (IAA) and ECL-GADA data at their initial visit were analyzed; after a median follow-up of 24 months, 177 of these 1,287 subjects developed diabetes., Results: Univariate analyses showed that autoantibodies by radioimmunoassays (RIAs), ECL-IAA, ECL-GADA, age, sex, number of positive autoantibodies, presence of HLA DR3/4-DQ8 genotype, HbA1c, and oral glucose tolerance test (OGTT) measurements were all significantly associated with progression to diabetes. Subjects who were ECL positive had a risk of progression to diabetes within 6 years of 58% compared with 5% for the ECL-negative subjects (P < 0.0001). Multivariate Cox proportional hazards models were compared, with the base model including age, sex, OGTT measurements, and number of positive autoantibodies by RIAs. The model with positivity for ECL-GADA and/or ECL-IAA was the best, and factors that remained significantly associated with time to diabetes were area under the curve (AUC) C-peptide, fasting C-peptide, AUC glucose, number of positive autoantibodies by RIAs, and ECL positivity. Adding ECL to the Diabetes Prevention Trial risk score (DPTRS) improved the receiver operating characteristic curves with AUC of 0.83 (P < 0.0001)., Conclusions: ECL assays improved the ability to predict time to diabetes in these autoantibody-positive relatives at risk for developing diabetes. These findings might be helpful in the design and eligibility criteria for prevention trials in the future., (© 2016 by the American Diabetes Association.)

Although most children with multiple islet autoantibodies develop type 1 diabetes, rate of progression is highly variable. The goal of this study was to explore potential factors involved in rate of progression to diabetes in children with multiple islet autoantibodies. The Diabetes Autoimmunity Study in the Young (DAISY) has followed 118 children with multiple islet autoantibodies for progression to diabetes. After excluding 27 children currently diabetes-free but followed for <10 years, the study population was grouped into: rapid progressors (N = 39) who developed diabetes in <5 years; moderate progressors (N = 25), diagnosed with diabetes within 5-10 years; and slow progressors (N = 27), diabetes-free for >10 years. Islet autoimmunity appeared at 4.0 ± 3.5, 3.2 ± 1.8 and 5.8 ± 3.1 years of age in rapid, moderate and slow progressors, respectively (p = 0.006). Insulin autoantibody levels were lower in slow progressors compared to moderate and rapid progressors. The groups did not differ by gender, ethnicity, family history, susceptibility HLA and non-HLA genes. The rate of development of individual islet autoantibodies including mIAA, GADA, IA-2A and ZnT8A were all slower in the slow versus moderate/rapid progressors. In multivariate analyses, older age at seroconversion and lower initial mIAA levels independently predicted slower progression to diabetes. Later onset of islet autoimmunity and lower autoantibody levels predicted slower progression to diabetes among children with multiple islet autoantibodies. These factors may need to be considered in the design of trials to prevent type 1 diabetes., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Maturity onset diabetes of the young (MODY) is a monogenic form of diabetes caused by a mutation in a single gene, often not requiring insulin. The aim of this study was to estimate the frequency and clinical characteristics of MODY at the Barbara Davis Center. A total of 97 subjects with diabetes onset before age 25, a random C-peptide ≥0.1 ng/mL, and negative for all diabetes autoantibodies (GADA, IA-2, ZnT8, and IAA) were enrolled, after excluding 21 subjects with secondary diabetes or refusal to participate. Genetic testing for MODY 1-5 was performed through Athena Diagnostics, and all variants of unknown significance were further analyzed at Exeter, UK. A total of 22 subjects [20 (21%) when excluding two siblings] were found to have a mutation in hepatocyte nuclear factor 4A (n = 4), glucokinase (n = 8), or hepatocyte nuclear factor 1A (n = 10). Of these 22 subjects, 13 had mutations known to be pathogenic and 9 (41%) had novel mutations, predicted to be pathogenic. Only 1 of the 22 subjects had been given the appropriate MODY diagnosis prior to testing. Compared with MODY-negative subjects, the MODY-positive subjects had lower hemoglobin A1c level and no diabetic ketoacidosis at onset; however, these characteristics are not specific for MODY. In summary, this study found a high frequency of MODY mutations with the majority of subjects clinically misdiagnosed. Clinicians should have a high index of suspicion for MODY in youth with antibody-negative diabetes., (© 2015 The Authors. Pediatric Diabetes published by John Wiley & Sons Ltd.)

Background: Relatives with single positive islet autoantibodies have a much lower risk of progression to diabetes than those with multiple autoantibodies., Materials and Methods: TrialNet subjects positive for single autoantibody to insulin (mIAA) (n = 50) or single autoantibody to glutamic acid decarboxylase (GADA) (n = 50) were analyzed using new electrochemiluminescence (ECL) assays (ECL-IAA and ECL-GADA, respectively) at their initial visit and longitudinally over time. Affinity assays were performed on a subset of single autoantibody-positive subjects at initial and most recent visits., Results: After a mean follow-up of 5.3 years, 20 subjects developed type 1 diabetes. Among either single GADA or single mIAA subjects, those who were positive in the ECL assay showed higher affinity at the initial visit, and affinity results stayed consistent over time. No converting events from low to high or high to low affinity were seen over time., Conclusions: Confirmed positivity for ECL is associated with high affinity and can help staging of risk for type 1 diabetes in single autoantibody-positive subjects.

Objective: Insulin is a commonly used, high-risk medication in the inpatient setting. Incorrect insulin administration can lead to preventable hypoglycemic events, which are a significant morbidity in inpatient diabetes care. The goal of this intervention was to decrease preventable insulin-related hypoglycemic events in an inpatient setting in a tertiary care pediatric hospital., Methods: Methods included the institution of several interventions such as nursing and physician education, electronic medical record order sets, electronic communication note templates, and the development of new care guidelines., Results: After the institution of multiple interventions, the rate of preventable hypoglycemic events decreased from 1.4 preventable events per 100 insulin days to 0.4 preventable events per 100 insulin days., Conclusions: Through the use of a multi-interventional approach with oversight of a multidisciplinary insulin safety committee, a sustained decreased rate of severe preventable hypoglycemic events in hospitalized pediatric patients receiving insulin was achieved., (Copyright © 2016 by the American Academy of Pediatrics.)

Genetic susceptibility to type 1 diabetes (T1D) is well supported by epidemiologic evidence; however, disease risk cannot be entirely explained by established genetic variants identified so far. This study addresses the question of whether epigenetic modification of the inherited DNA sequence may contribute to T1D susceptibility. Using the Infinium HumanMethylation450 BeadChip array (450k), a total of seven long-term disease-discordant monozygotic (MZ) twin pairs and five pairs of HLA-identical, disease-discordant non-twin siblings (NTS) were examined for associations between DNA methylation (DNAm) and T1D. Strong evidence for global hypomethylation of CpG sites within promoter regions in MZ twins with TID compared to twins without T1D was observed. DNA methylation data were then grouped into three categories of CpG sites for further analysis, including those within: 1) the major histocompatibility complex (MHC) region, 2) non-MHC genes with reported T1D association through genome wide association studies (GWAS), and 3) the epigenome, or remainder of sites that did not include MHC and T1D associated genes. Initial results showed modest methylation differences between discordant MZ twins for the MHC region and T1D-associated CpG sites, BACH2, INS-IGF2, and CLEC16A (DNAm difference range: 2.2%-5.0%). In the epigenome CpG set, the greatest methylation differences were observed in MAGI2, FANCC, and PCDHB16, (DNAm difference range: 6.9%-16.1%). These findings were not observed in the HLA-identical NTS pairs. Targeted pyrosequencing of five candidate CpG loci identified using the 450k array in the original discordant MZ twins produced similar results using control DNA samples, indicating strong agreement between the two DNA methylation profiling platforms. However, findings for the top five candidate CpG loci were not replicated in six additional T1D-discordant MZ twin pairs. Our results indicate global DNA hypomethylation within gene promoter regions may contribute to T1D; however, findings do not support the involvement of large DNAm differences at single CpG sites alone in T1D., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

The HLA-DRB1*15:01-DQA1*01:02-DQB1*06:02 haplotype is linked to protection from the development of type 1 diabetes (T1D). However, it is not known at which stages in the natural history of T1D development this haplotype affords protection. We examined a cohort of 3,358 autoantibody-positive relatives of T1D patients in the Pathway to Prevention (PTP) Study of the Type 1 Diabetes TrialNet. The PTP study examines risk factors for T1D and disease progression in relatives. HLA typing revealed that 155 relatives carried this protective haplotype. A comparison with 60 autoantibody-negative relatives suggested protection from autoantibody development. Moreover, the relatives with DRB1*15:01-DQA1*01:02-DQB1*06:02 less frequently expressed autoantibodies associated with higher T1D risk, were less likely to have multiple autoantibodies at baseline, and rarely converted from single to multiple autoantibody positivity on follow-up. These relatives also had lower frequencies of metabolic abnormalities at baseline and exhibited no overall metabolic worsening on follow-up. Ultimately, they had a very low 5-year cumulative incidence of T1D. In conclusion, the protective influence of DRB1*15:01-DQA1*01:02-DQB1*06:02 spans from autoantibody development through all stages of progression, and relatives with this allele only rarely develop T1D., (© 2016 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.)

Background: Islet autoantibody testing provides the basis for assessment of risk of progression to type 1 diabetes. We set out to determine the feasibility and acceptability of dried capillary blood spot-based screening to identify islet autoantibody-positive relatives potentially eligible for inclusion in prevention trials., Materials and Methods: Dried blood spot (DBS) and venous samples were collected from 229 relatives participating in the TrialNet Pathway to Prevention Study. Both samples were tested for glutamic acid decarboxylase, islet antigen 2, and zinc transporter 8 autoantibodies, and venous samples were additionally tested for insulin autoantibodies and islet cell antibodies. We defined multiple autoantibody positive as two or more autoantibodies in venous serum and DBS screen positive if one or more autoantibodies were detected. Participant questionnaires compared the sample collection methods., Results: Of 44 relatives who were multiple autoantibody positive in venous samples, 42 (95.5%) were DBS screen positive, and DBS accurately detected 145 of 147 autoantibody-negative relatives (98.6%). Capillary blood sampling was perceived as more painful than venous blood draw, but 60% of participants would prefer initial screening using home fingerstick with clinic visits only required if autoantibodies were found., Conclusions: Capillary blood sampling could facilitate screening for type 1 diabetes prevention studies.

Background: Children with positive islet autoantibodies monitored prospectively avoid metabolic decompensation at type 1 diabetes (T1D) diagnosis. However, the effects of early diagnosis and treatment on preservation of insulin secretion and long-term metabolic control are unknown. We compared characteristics of children detected through research screening (Diabetes Autoimmunity Study in the Young [DAISY]) versus community controls at baseline and, in a subset, 6- and 12-month metabolic outcomes., Materials and Methods: This was a case-control study comparing DAISY children with T1D to children diagnosed in the general community. All participants underwent mixed-meal tolerance testing; a subset wore a continuous glucose monitoring (CGM) device. Fasting and stimulated C-peptide levels, insulin dose-adjusted hemoglobin A1c (IDAA1c), and CGM variables were compared., Results: Children (21 DAISY, 21 community) were enrolled and matched by age, time of diagnosis, and diabetes duration; 18 were enrolled within 2 months and 24 within 2.5 years on average from diagnosis. In the overall group and the subgroup of participants enrolled 2.5 years from diagnosis, there were no IDAA1c or C-peptide differences between DAISY versus community children. The subgroup of DAISY versus community children enrolled near diagnosis, however, had lower baseline hemoglobin A1c (6.5±1.4% vs. 9.2±2.9%; P=0.0007) and IDAA1c (7.4±2.1% vs. 11.2±3.5%; P=0.04) and higher stimulated C-peptide (2.5±0.5 vs. 1.6±0.2 ng/mL; P=0.02). In this subgroup, IDAA1c differences persisted at 6 months but not at 1 year. CGM analyses revealed lower minimum overnight glycemia in community children (72 vs. 119 mg/dL; P=0.01)., Conclusions: Favorable patterns of IDAA1c and C-peptide seen in research-screened versus community-diagnosed children with T1D within 2 months of diagnosis are no longer apparent 1 year from diagnosis.

Aims/hypothesis: The discordance status of (autoimmune) type 1 diabetes within monozygotic twin pairs points to the importance of environmental factors. The aim of this study was to investigate whether the environmental events causing type 1 diabetes influence thyroid autoimmunity., Methods: Monozygotic and dizygotic twins discordant for type 1 diabetes from the UK and USA were tested for thyroid peroxidase autoantibodies (TPOA) by radioimmunoassay. Using quantitative genetic model fitting of a liability-threshold model we estimated the contribution of genetic (heritability) and environmental factors to TPOA., Results: TPOA positivity was higher in females than in males in both cohorts and was associated with later age at diagnosis in the UK and combined cohorts (p < 0.01). TPOA did not specifically segregate with type 1 diabetes in the twin pairs (p > 0.2 in all groups). The best-fitting models showed heritability (95% CI) estimates for TPOA of 63% (37%, 80%) for the UK and 80% (51%, 92%) for US twins, while the best-fitting meta-analysis model of the two twin cohorts combined included additive genetic and unique environmental factors with a heritability estimate of 69% (50%, 82%)., Conclusions/interpretation: Risk of thyroid autoimmunity, defined by TPOA, in the context of autoimmune diabetes is, substantially, genetically determined in discordant twin pairs. Environmental factors leading to type 1 diabetes were not the same as those involved with thyroid autoimmunity. It follows that it is as important to investigate for thyroid autoimmunity in relatives of type 1 diabetes patients as it is in the patients themselves.