Autoantibodies against insulin (IAA) are early appearing markers of autoimmunity against the pancreatic islet beta cells and predict progression to type 1 diabetes if additional islet autoantibodies also develop. It is still controversial if proinsulin rather than insulin is the primary autoantibody. The aim of the present study was to compare the half-maximal concentration (IC50) between insulin and proinsulin to displace the binding of insulin to insulin autoantibodies (IAA) in the Antibody Detection by Agglutination PCR (ADAP) assay. IC50 as a measure of potency to displace insulin binding to IAA was determined in 36 newly diagnosed type 1 diabetes children. The ability of either insulin or proinsulin to displace IAA was heterogenous. Proinsulin curves were consistently right-shifted relative to insulin as median IC50 was 21.0 nM (IQR 14.9-25.1) for insulin and 26.1 nM (IQR 12.3-37.5) for proinsulin. A significant age × sex interaction was observed (F (1,31) = 14.3, P < 0.001), indicating that IC50 for both insulin and proinsulin increased with age in boys but decreased in girls. It may reflect whether autoantibodies to insulin or proinsulin were first appearing or of variable maturation from the time of initiation through progression to clinical onset. It was concluded that the IC50 of insulin and proinsulin for IAA was comparable in children with newly diagnosed type 1 diabetes. The ADAP IAA assay should prove useful to determine whether insulin or proinsulin is the primary target at the time of seroconversion to IAA.

This paper presents a joint model of multivariate longitudinal data and multistate data with application to modeling and predicting autoantibody development in The Environmental Determinants of Diabetes in the Young (TEDDY) study. The model quantifies the risks of state transitions based on observed time-varying and non-time-varying risk factors. Based on the estimated model, a dynamic prediction approach is suggested to predict future state occupation probabilities using historical data. The proposed method can handle uncertainties in the observed data, due to measurement errors in the observed longitudinal data and interval censoring or missing information in the observed multistate data. For evaluating the predictions by the proposed approach, some performance metrics and their estimation are discussed. The proposed method is evaluated by some simulation studies. It is discussed in detail how this method can be used in analyzing the TEDDY data by properly handling the missing information and predicting future disease status using the proposed dynamic prediction algorithm.

AIMS:To study the associations of dietary intake of A and E vitamins, as well as plasma retinols, carotenoids, and tocopherols in relation to development of islet autoimmunity and progression to T1D. MATERIALS AND METHODS:The Environmental Determinants of Diabetes in the Young (TEDDY) Study followed 7659 newborns with genetic susceptibility to T1D for 6 years in the USA, Finland, Germany, and Sweden. Dietary vitamin intake was assessed repeatedly with 3-day food-records in full cohort at ages 6 months to 6 years. Plasma retinols, carotenoids, and tocopherols were analysed in a nested case-control setting with 359 children with islet autoimmunity and 1033 matched controls. RESULTS:In the full cohort analyses, dietary intake of retinol, β-carotene, and vitamin E was not associated with the risk of islet autoimmunity or progression to T1D. Further, none of the plasma retinol, carotenoid, and tocopherol biomarkers were associated with islet autoimmunity or T1D in the full nested case-control analyses. We observed effect modification by country, breastfeeding, sex, and follow-up time for both intake and biomarkers of vitamins on the risk of islet autoimmunity or T1D, and some subgroup associations. Finally, a plasma carotenoid metabolite (likely zeinoxanthin) (OR 0.61, 95% CI 0.39, 0.95, p = 0.03) and γ-carotene at 6 months (OR 0.65, 95% CI 0.45, 0.94, p = 0.02) were inversely associated with the odds of developing GADA-first. CONCLUSIONS:Retinol, carotenoids and tocopherols were not consistently associated with islet autoimmunity. This study adds to the understanding of factors and their interactions related to T1D development.

We aimed to determine if thyroid autoimmunity is associated with a child's risk for subsequent development of islet or celiac autoantibodies. Children at high genetic risk of type 1 diabetes were followed for thyroid autoimmunity (thyroid peroxidase antibodies [TPOAb] and thyroglobulin antibodies [TGAb]), islet autoimmunity (IA), and celiac disease autoimmunity (CDA) in The Environmental Determinants of Diabetes in the Young study. Out of 5482 children tested for thyroid autoimmunity, IA, and CDA, 39% developed at least one autoantibody. At age 14 years, thyroid autoimmunity co-occurred with IA in 59 children (15 more cases than expected by chance alone, P = 0.02) and with CDA in 125 children (26 cases above expected, P = 0.01). The risk of developing IA or CDA after thyroid autoimmunity varied by which thyroid autoantibody appeared first: TPOAb-first was associated with both IA (HR 1.92, 95% CI, 1.09-3.40) and CDA (1.69, 95% CI, 1.03-2.76), whereas TGAb-first was not associated with the risk of either. Islet autoimmunity and CDA are frequently found in connection to thyroid autoimmunity in children and young adolescents. The relationships of thyroid autoimmunity with IA and CDA depend on which thyroid autoantibody appears first.

Polymorphisms in genes in the human leukocyte antigen (HLA) class II region comprise the most important inherited risk factors for many autoimmune diseases, including type 1 diabetes (T1D) and celiac disease (CD): both diseases are positively associated with the HLA-DR3 haplotype (DRB1*03:01-DQA1*05:01-DQB1*02:01). Studies of two different populations have recently documented that T1D susceptibility in HLA-DR3 homozygous individuals is stratified by a haplotype consisting of three single nucleotide polymorphisms ('tri-SNP') in intron 1 of the HLA-DRA gene. In this study, we use a large cohort from the longitudinal 'The Environmental Determinants of Diabetes in the Young' (TEDDY) study to further refine the tri-SNP association with T1D and with autoantibody-defined T1D endotypes. We found that the tri-SNP association is primarily in subjects whose first-appearing T1D autoantibody is to insulin. In addition, we discovered that the tri-SNP is also associated with CD, and that the particular tri-SNP haplotype ('101') that is negatively associated with T1D risk is positively associated with risk for CD. The opposite effect of the tri-SNP haplotype on two DR3-associated diseases can enhance and refine current models of disease prediction based on genetic risk. Finally, we investigated possible functional differences between the individuals carrying high and low-risk tri-SNP haplotypes and found that differences in complement system genes C4A and C4B may underlie the observed divergence in disease risk.

The primary objective of this study was to investigate whether ligand-receptor interactions (LRIs) between IGHG and FCGR gene products are associated with progression to type 1 diabetes (T1D). Using two completed clinical trials (DPT-1 and TN07), we applied next-generation targeted sequencing to genotype IGHG and FCGR genes in a cohort of 1,214 individuals and assessed LRI associations with disease progression. A Cox regression model was used to quantify LRI associations. IGHG or FCGR alone was found to have weak and sporadic associations with progression. Multiple LRIs between IGHG and FCGR gene products were found to be associated with progression, especially LRIs of IGHG2 with multiple FCGR receptors that accelerate progression and those of IGHG4 with multiple FCGR receptors (some overlapping) that delay progression. Furthermore, as several crystal structures of FcγRs complexed with distinct IgG molecules are known, application of this knowledge here was hampered by the absence of any information on the subclass distribution of each of the several T1D-related autoantibodies. It cannot be excluded that their respective state of glycosylation may influence binding affinity to various FcγRs and the function of thus-formed complexes. Our findings suggest that LRIs of the IGHG and FCGR gene products probably influence progression, shedding new insights into some of the immunological mechanisms involved in progression to T1D. Our findings potentially facilitate the search for new immunotherapeutic treatment through intervening at key steps in the progression. ARTICLE HIGHLIGHTS:This study investigated ligand-receptor interactions (LRIs) between IGHG and FCGR gene products in type 1 diabetes progression. Genes of 1,214 participants from the DPT-1 and TN07 trials were sequenced using next-generation targeted sequencing technology, and LRI associations with the progression time to type 1 diabetes were analyzed using Cox regression modeling. Weak associations were found for IGHG or FCGR variants individually, but multiple LRIs significantly impacted progression. Several IGHG2-FCGR interactions accelerated progression, while a few other IGHG4-FCGR interactions delayed it. The results may provide insights into certain immunogenetic mechanisms of T1D and suggest therapeutic potential of targeting specific LRIs.

In 2025, the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) at the National Institutes of Health celebrates 75 years of leadership in diabetes research. The NIDDK serves people of the U.S. affected by or at risk for many chronic diseases, including diabetes and other endocrine, metabolic, and digestive disorders, by funding innovative research to develop better treatment and prevention and a cure for these conditions. Autoimmunity that leads to type 1 diabetes or celiac disease or thyroid autoimmunity affects 1 in 20 children and adolescents in the U.S. While treatments are available, prevention of these common autoimmune diseases has been elusive due to poor understanding of the environmental causes and their interactions with common predisposing or protective genetic variants. In 2002, the NIDDK established The Environmental Determinants of Diabetes in the Young (TEDDY) consortium to advance understanding of the causes and the natural history of type 1 diabetes and other autoimmune diseases. The overarching goal of TEDDY is to inform novel approaches to primary prevention of autoimmunity. In this large international prospective birth cohort study, standardized information has been collected concerning candidate environmental exposures along with serial blood, stool, nasal swab, and other biosamples, with creation of a central repository of data and biologic samples for hypothesis-based research. This review summarizes TEDDY's major contributions to our understanding of environmental triggers, drivers, and modifiers of autoimmunity, and gene-environment interactions, leading to type 1 diabetes.

CONTEXT:When clinically stable, patients with A-β+ ketosis-prone diabetes (KPD) manifest unique markers of amino acid metabolism. Biomarkers differentiating KPD from type 1 (T1D) and type 2 diabetes (T2D) during hyperglycemic crises would accelerate diagnosis and management. OBJECTIVE:Compare serum metabolomics of KPD, T1D, and T2D patients during hyperglycemic crises, and utilize classification and regression tree (CART) modeling to distinguish these forms of diabetes. METHODS:At an urban hospital emergency center, adults with KPD, T1D, and T2D during hyperglycemic crises with or without diabetic ketoacidosis (DKA), and healthy controls, underwent comparisons of serum metabolite and hormonal profiles and CART analyses. Group differences in concentrations of amino acids, their metabolites, and relationship to glucose counterregulatory hormones were determined, as well as C-peptide cutoffs and analytes to distinguish KPD, T1D, and T2D. RESULTS:Concentrations of most amino acids were similar in KPD and T1D and lower compared to T2D (P < .05). Glucagon and cortisol concentrations were correlated with 3-methylhistidine and blood urea nitrogen in KPD but not in T1D. A C-peptide cutoff of 0.496 ng/mL differentiated T1D from KPD during DKA. CART revealed that a regression model based on the concentrations of β-hydroxybutyrate, C-peptide, glucagon, alpha-keto-β-methylvalerate, cystine, and myristoyl-L-carnitine distinguished KPD from T1D and T2D. CONCLUSION:During DKA, KPD and T1D patients have similarly altered amino acid profiles that differentiate them from T2D patients. Elevated protein catabolic hormones drive altered amino acid metabolism in KPD, rather than insulin deficiency as with T1D. A combination of 6 analytes differentiates KPD from T1D and T2D during hyperglycemic crises.

Purpose:A randomized clinical trial was conducted to evaluate the impact of a gluten-free diet (GFD) on β-cell function and glucose tolerance in persons with multiple islet autoantibodies. Methods:Individuals (n = 59; median age 11 years) with multiple islet autoantibodies were recruited to a randomized clinical trial between April 2016 and April 2021. The participants were randomized to a GFD (n = 30; female n = 14) or a normal diet (ND) (n = 29; female n = 16). The study was conducted at 6 clinical research centers in Finland and Sweden, with a dietary intervention for 17 months followed by a 6-month washout on a ND. The primary outcomes were (1) the proportion of participants going from normal glucose tolerance at the time of the randomization to abnormal glucose tolerance by 18 months, (2) a change in first-phase insulin response in IV glucose tolerance tests between randomization and 18 months, and (3) a change in C-peptide area under the curve in oral glucose tolerance test between randomization and 18 months. Results:We did not find differences between participants randomized to GFD and ND in any of the glucose tolerance outcomes. No serious adverse events or adverse events related to a GFD were noted. Conclusion:Being on a GFD was not found to differ from being on a ND in preserving β-cell function or maintaining normal glucose tolerance in persons with multiple islet autoantibodies.

Objective Childhood obesity may impact the risk of islet autoimmunity (IA). The trajectory of BMI through childhood resembles the early peak incidence of first-appearing autoantibodies against insulin (IAA-first) but not GAD65 (GADA-first). We studied if a child’s BMI can impact the age-related risk of first appearing IA phenotypes. Research Design and Methods We identified 7,724 children at risk of IA with at least three BMI measurements in the Environmental Determinants of Diabetes in the Young (TEDDY) study. We modeled the risk of IAA-first, GADA-first, and IA overall, on a child’s BMI z-score and change in BMI during infancy (2 weeks to 1.5 years, n=7,724), early childhood (age 1.5-8.5 years, n=6,396), and puberty (age 8.5-15 years, n=4,732) using joint modeling of longitudinal BMI and time-to-event IA. Results An infant’s BMI z-score was not associated with IA risk before 18 months of age (n=185, HR 1.03, 95% CI [0.88, 1.19]). In contrast, a child’s BMI correlated with an increased risk of IA from 1.5 to 8.5 years (n=470, HR 1.20, 95% CI [1.04, 1.32]) and from 8.5 to 15 years (n =209, HR 1.27, 95% CI [1.09,1.49]). No interactions with first appearing IA phenotypes were observed. However, high BMI z-score (SD > 0.5) from age 9 months increased the risk of IA in early childhood specifically for children with HLA-DR4/4,8 and not with HLA-DR3/3,4 (HLA*BMI interaction, p<0.005). Conclusions The contribution of BMI to risk of IA during early childhood is dependent on HLA-DR-DQ genotype more so than first appearing IA phenotype.

HLA-DR genes are associated with the progression from stage 1 and stage 2 to onset of stage 3 type 1 diabetes (T1D), after accounting HLA-DQ genes with which they are in high linkage disequilibrium. Based on an integrated cohort of participants from 2 completed clinical trials, this investigation finds that, sharing a haplotype with the DRB1*03:01 (DR3) allele, DRB3*01:01:02 and *02:02:01 have respectively negative and positive associations with the progression. Furthermore, we uncovered 2 residues (β11, β26, participating in pockets 6 and 4, respectively) on the DRB3 molecule responsible for the progression among DR3 carriers; motif RY and LF respectively delay and promote the progression (hazard ratio [HR] = 0.73 and 2.38, P = 0.039 and 0.017, respectively). Two anchoring pockets 6 and 4 probably bind differential autoantigenic epitopes. We further investigated the progression association with the motifs RY and LF among carriers of DR3 and found that carriers of the motif LF have significantly faster progression than carriers of RY (HR = 1.48, P = 0.019 in unadjusted analysis; HR = 1.39, P = 0.047 in adjusted analysis), results of which provide an impetus to examine the possible role of specific DRB3-binding peptides in the progression to T1D.

The objective was to determine the association between serum IgE levels and the infiltration order of T lymphocytes and macrophages in pancreatic islets in relation to the loss of insulin and glucagon cells in presymptomatic congenic BB Gimap5-DP (Diabetes Prone) rats. Congenic prediabetes BB Gimap5-DP and control Gimap5-DR (Diabetes Resistant) rats were followed every other day from 29 to 32 days of age until peak serum IgE (≤ 55 days of age). Serum IgE was measured using ELISA. The HALO™ platform facilitated quantitative image analysis of infiltrating T lymphocytes, macrophages, and target organ insulin and glucagon cells. Whole genome sequencing (WGS) was employed to identify candidate type 1 diabetes genes. Serum IgE levels increased with age in normoglycemic BB Gimap5-DP rats. Quantification of infiltrating cells per mm2 in and around the islets indicated that T lymphocytes are the initial infiltrators, followed by macrophages. Elevated serum IgE levels inversely correlated with beta-cell mass (total mg insulin/mg pancreas). WGS refined the risk segment for islet inflammation to 1.02 Mbp, leaving 10 candidate genes, including Gimap4 and Gimap5. Elevated IgE levels herald T lymphocyte and macrophage infiltration. Pancreatic islet inflammation was linked to Gimap4, Gimap5, and other potential candidate genes on rat chromosome 4.

Objective: To design a dynamic prediction model for estimating the time of progression from a single glutamic acid decarboxylase autoantibody (GADA) to multiple islet autoantibodies and type 1 diabetes in children, exploring different longitudinally measured risk variables. Research Design and Methods: GADA-positive children (n = 379) participating in The Environmental Determinants of Diabetes in the Young (TEDDY) study were followed for the appearance of additional autoantibodies against either insulin autoantibody (IAA), insulinoma-like 2 autoantibody (IA-2A), or zinc transporter 8 antibody (ZnT8A) and type 1 diabetes. A dynamic prediction model was designed, including trajectories of longitudinal risk variables, autoantibody titers, and metabolic variables (C-peptide, glucose, and HbA1c) together with time-invariant variables (gender, age at GADA positivity, and high-risk HLA genotypes). Results: Transition risk from GADA to multiple autoantibodies was increased by lower age (p < 0.001) and by increased GADA titers during follow-up (p < 0.001), and was less likely in children with HLA DQ2/X but not DQ2/8 (p=0.004). The transition risk from multiple autoantibodies without IA-2A to IA-2A positivity was associated with increased levels of 2 h glucose following oral glucose tolerance test (OGTT) (p < 0.001) and increased ZnT8A titers (p < 0.001). Increasing HbA1c (p < 0.001) and GADA titers (p < 0.001) were associated with an increased risk of transition from GADA only to type 1 diabetes; while increasing HbA1c (p < 0.001) was associated with the transition from multiple autoantibodies to type 1 diabetes. Risk of transition from multiple autoantibodies, including IA-2A to type 1 diabetes was also associated with 2 h glucose level (p < 0.001). Conclusion: The dynamic prediction model presented an individual time-specific risk of transition from a single GADA to multiple autoantibodies and type 1 diabetes.

Context Autoantibodies to thyroid peroxidase (TPOAb) and thyroglobulin (TgAb) define preclinical autoimmune thyroid disease (AITD), which can progress to either clinical hypothyroidism or hyperthyroidism.Objective We determined the age at seroconversion in children genetically at risk for type 1 diabetes.Methods TPOAb and TgAb seropositivity were determined in 5066 healthy children with human leukocyte antigen (HLA) DR3- or DR4-containing haplogenotypes from The Environmental Determinants of Diabetes in the Young (TEDDY) study. Children seropositive on the cross-sectional initial screen at age 8 to 13 years had longitudinally collected samples (from age 3.5 months) screened retrospectively and prospectively for thyroid autoantibodies to identify age at seroconversion. The first-appearing autoantibody was related to sex, HLA genotype, family history of AITD, and subsequent thyroid dysfunction and disease.Results The youngest appearance of TPOAb and TgAb was age 10 and 15 months, respectively. Girls had higher incidence rates of both autoantibodies. Family history of AITD was associated with a higher risk of TPOAb hazard ratio (HR) 1.90; 95% CI, 1.17-3.08; and TgAb HR 2.55; 95% CI, 1.91-3.41. The risk of progressing to hypothyroidism or hyperthyroidism was not different between TgAb and TPOAb, but children with both autoantibodies appearing at the same visit had a higher risk compared to TPOAb appearing first (HR 6.34; 95% CI, 2.72-14.76).Conclusion Thyroid autoantibodies may appear during the first years of life, especially in girls, and in children with a family history of AITD. Simultaneous appearance of both autoantibodies increases the risk for hypothyroidism or hyperthyroidism.

The primary objective is to investigate if ligand-receptor interactions (LRIs) between IGHG and FCGR gene products associate with progression to type 1 diabetes. Utilizing two completed clinical trials (DPT-1 and TN07), we apply next-generation targeted sequencing to genotype IGHG and FCGR genes in a cohort of 1214 individuals and assess LRI associations with disease progression. A Cox regression model is used to quantify LRI associations. Our investigation shows the following results: 1) IGHG or FCGR alone are found to have weak and sporadic associations with progression; 2) Multiple LRIs between IGHG and FCGR gene products are found to associate with progression; especially, LRIs of IGHG2 with multiple FCGR receptors accelerate progression, while those of IGHG4 with multiple FCGR receptors (some are overlapping) delay progression; and 3) as several crystal structures of FcgRs complexed with distinct IgG molecules are known, application of this knowledge here is hampered by the absence of any information on the subclass distribution of each of the several type 1 diabetes-related autoantibodies. It cannot be excluded that their respective state of glycosylation, may influence binding affinity to various FcgRs, and function of thus formed complexes. We found that LRIs of the IGHG and FCGR gene products probably influence progression, likely shedding new insights into some of the immunological mechanisms involved in progression to T1D; our findings potentially facilitate the search for new immunotherapeutic treatment through intervening at key steps in the progression.

The aim of this work was to explore associations between type 1 diabetes progression from stages 1 or 2 to stage 3 and interacting ligand–receptor complexes of HLA class I (HLA-I) and KIR gene products. Applying next-generation sequencing technology to genotype HLA-I genes (HLA-A, -B, -C) and KIR genes (KIR2DL1, KIR2DL2, KIR2DL3, KIR2DL4, KIR2DL5, KIR2DS1, KIR2DS2, KIR2DS3, KIR2DS4, KIR2DS5, KIR3DL1, KIR3DL3, KIR3DS1, KIR2DP1, KIR3DP1) from 1215 participants in the Diabetes Prevention Trial-Type 1 (DPT-1) and the Diabetes Prevention Trial (TN07), we systematically explored associations of HLA-I–KIR ligand–receptor interactions (LRIs) with disease progression via a Cox regression model. We investigated the structural properties of identified LRI complexes. KIR and HLA-I genes had no or sporadic associations with disease progression. Out of all possible LRIs, nine HLA-A Ligands and 14 HLA-B ligands with corresponding receptors had modest associations with progression (p<0.05). As an example, carriers of A*03:01-KIR2DS4 had slower progression (HR 0.36, p=3.06 × 10−2), as did B*07:02-KIR2DL3 carriers (HR 0.26, p=7.76 × 10−3). Structural investigations of KIR–HLA-I complexes via homology modelling based on already-solved respective complex structures suggested that the respective electrostatic and van der Waals interactions encoded in the protein sequences result in strong biophysical LRIs, which could alter the progression of type 1 diabetes. These results reveal that LRIs of KIR–HLA-I gene products, rather than individual genes, contribute to type 1 diabetes progression, and such interactions are likely to be stabilised by electrostatic and van der Waals forces. As the KIR–HLA-I interactions involve part of the C-terminus of the antigen-binding groove of HLA-I, but may be affected by the respective bound peptide, this suggests a new mechanism for type 1 diabetes pathogenesis. Clinical data on participants in DPT-1 and TN07 can be obtained from the NIDDK-Central Repository ( https://repository.niddk.nih.gov/home ) following the formal approval process.