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Development of islet autoimmunity precedes the onset of type 1 diabetes in children, however, the presence of autoantibodies does not necessarily lead to manifest disease and the onset of clinical symptoms is hard to predict. Here we show, by longitudinal sampling of islet autoantibodies (IAb) to insulin, glutamic acid decarboxylase and islet antigen-2 that disease progression follows distinct trajectories. Of the combined Type 1 Data Intelligence cohort of 24662 participants, 2172 individuals fulfill the criteria of two or more follow-up visits and IAb positivity at least once, with 652 progressing to type 1 diabetes during the 15 years course of the study. Our Continuous-Time Hidden Markov Models, that are developed to discover and visualize latent states based on the collected data and clinical characteristics of the patients, show that the health state of participants progresses from 11 distinct latent states as per three trajectories (TR1, TR2 and TR3), with associated 5-year cumulative diabetes-free survival of 40% (95% confidence interval [CI], 35% to 47%), 62% (95% CI, 57% to 67%), and 88% (95% CI, 85% to 91%), respectively (p

Analyzing disease progression patterns can provide useful insights into the disease processes of many chronic conditions. These analyses may help inform recruitment for prevention trials or the development and personalization of treatments for those affected. We learn disease progression patterns using Hidden Markov Models (HMM) and distill them into distinct trajectories using visualization methods. We apply it to the domain of Type 1 Diabetes (T1D) using large longitudinal observational data from the T1DI study group. Our method discovers distinct disease progression trajectories that corroborate with recently published findings. In this paper, we describe the iterative process of developing the model. These methods may also be applied to other chronic conditions that evolve over time.

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 x 10(-7)) with Bonferroni-corrected significance and another known region near PTPN22 (HR = 1.46, p = 2.17 x 10(-6)) and one novel region near PPIL2 (HR = 2.47, p = 9.64 x 10(-7)) with suggestive evidence (p < 10(-5)). Two known regions (PTPN22: p = 2.25 x 10(-6), INS; p = 1.32 x 10(-7)) and one novel region (PXK/PDHB: p = 8.99 x 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 x 10(-6) and TTC34/PROM16: 6.45 x 10(-6)) were associated if the fist appearing autoantibody was IAA and one region (RBFOXI: p = 8.02 x 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 x 10(-7)) and three novel regions (RNASET2, PLEKHA1, and PPIL2; 5.42 x 10(-6) > p > 2.31 x 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. (C) 2017 Elsevier Ltd. All rights reserved.

Objective: We investigated the association between maternal use of vitamin D and omega-3 fatty acids (n-3 FAs) supplements during pregnancy and risk of islet autoimmunity (IA) in the offspring. Methods: The Environmental Determinants of Diabetes in the Young (TEDDY) Study is prospectively following 8676 children with increased genetic risk for type 1 diabetes in Finland, Germany, Sweden, and the United States. Blood samples were collected every 3 months between 3 and 48 months of age then every 6 months thereafter to determine persistent IA. Duration, frequency, and supplement dose during pregnancy were recalled by mothers at 3 to 4 months postpartum. Cumulative intakes of supplemental vitamin D and n-3 FAs were analyzed as continuous or binary variables. We applied time-to-event analysis to study the association between maternal supplement use and IA, adjusting for country, human leukocyte antigen-DR-DQ genotype, family history of type 1 diabetes and sex. Secondary outcomes included insulin autoantibodies (IAA) or glutamic acid decarboxylase (GADA) as the first appearing autoantibody. Results: As of February 2018, there were 747 (9.0%) children with IA. Vitamin D supplement intake during pregnancy (any vs none) was not associated with risk for IA (hazard ratio [HR] 1.11; 95% confidence interval [CI] 0.94, 1.31); neither was cumulative vitamin D supplement intake. Supplemental n-3 FA intake was similarly not associated with IA risk (HR: 1.19, 95% CI 0.98, 1.45). Similar lack of association was observed for either IAA or GADA as the first appearing autoantibody. Conclusions: The TEDDY cohort showed no evidence of benefit regarding IA risk for vitamin D or n-3 FA supplementation during pregnancy. (Less)

OBJECTIVE β-Cell autoantibodies are a feature of the preclinical phase of type 1 diabetes. Here, we asked how frequently they revert in a cohort of children at risk for type 1 diabetes and whether reversion has any effect on type 1 diabetes risk. RESEARCH DESIGN AND METHODS Children were up to 10 years of age and screened more than once for insulin autoantibody, GAD antibody, and insulinoma antigen-2 antibodies. Persistent autoantibody was defined as an autoantibody present on two or more consecutive visits and confirmed in two reference laboratories. Reversion was defined as two or more consecutive negative visits after persistence. Time-dependent Cox regression was used to examine how reversion modified the risk of development of multiple autoantibodies and type 1 diabetes. RESULTS Reversion was relatively frequent for autoantibodies to GAD65 (19%) and insulin (29%), but was largely restricted to children who had single autoantibodies (24%) and rare in children who had developed multiple autoantibodies ( CONCLUSIONS Type 1 diabetes risk remained high in children who had developed multiple β-cell autoantibodies even when individual autoantibodies reverted. We suggest that monitoring children with single autoantibodies for at least 1 year after seroconversion is beneficial for stratification of type 1 diabetes risk.

The possible interrelations between human leukocyte antigen (HLA)-DQ, non-HLA single-nucleotide polymorphisms (SNPs) and islet autoantibodies were investigated at clinical onset in 1-34-year-old type 1 diabetes (T1D) patients (n=305) and controls (n=203). Among the non-HLA SNPs reported by the Type 1 Diabetes Genetics Consortium, 24% were supported in this Swedish replication set including that the increased risk of minor PTPN22 allele and high-risk HLA was modified by GAD65 autoantibodies. The association between T1D and the minor AA+AC genotype in ERBB3 gene was stronger among IA-2 autoantibody-positive patients (comparison P=0.047). The association between T1D and the common insulin (AA) genotype was stronger among insulin autoantibody (IAA)-positive patients (comparison P=0.008). In contrast, the association between T1D and unidentified 26471 gene was stronger among IAA-negative (comparison P=0.049) and IA-2 autoantibody-negative (comparison P=0.052) patients. Finally, the association between IL2RA and T1D was stronger among IAA-positive than among IAA-negative patients (comparison P=0.028). These results suggest that the increased risk of T1D by non-HLA genes is often modified by both islet autoantibodies and HLA-DQ. The interactions between non-HLA genes, islet autoantibodies and HLA-DQ should be taken into account in T1D prediction studies as well as in prevention trials aimed at inducing immunological tolerance to islet autoantigens.

BACKGROUND: Deficient soluble fiber intake has been suggested to dysregulate the immune response either directly or through alterations of the microbial composition in the gut. OBJECTIVE: We hypothesized that a high intake of dietary soluble fiber in early childhood decreases the risk of type 1 diabetes (T1D)-associated islet autoimmunity. DESIGN: We analyzed 17,620 food records collected between age 9 and 48 mo from 3358 children from the United States and Germany prospectively followed in the TEDDY (The Environmental Determinants of Diabetes in the Young) study. HRs for the development of any/multiple islet autoantibodies (242 and 151 events, respectively) and T1D (71 events) by soluble fiber intake were calculated in Cox regression models and adjusted for potential confounders. RESULTS: There were no statistically significantly protective associations observed between a high intake of soluble fiber and islet autoimmunity or T1D. For example, the adjusted HRs (95% CIs) for high intake (highest vs. lowest quintile) at age 12 mo were 0.90 (0.55, 1.45) for any islet autoantibody, 1.20 (0.69, 2.11) for multiple islet autoantibodies, and 1.24 (0.57, 2.70) for T1D. In analyzing soluble fiber intake as a time-varying covariate, there were also no short-term associations between soluble fiber intake and islet autoimmunity development, with adjusted HRs of 0.85 (0.51, 1.42) for high intake and development of any islet autoantibody, for example. CONCLUSION: These results indicate that the intake level of dietary soluble fiber is not associated with islet autoimmunity or T1D in early life.

BACKGROUND: The vast array and quantity of longitudinal samples collected in The Environmental Determinants of Diabetes in the Young study present a series of challenges in terms of quality control procedures and data validity. To address this, pilot studies have been conducted to standardize and enhance both biospecimen collection and sample obtainment in terms of autoantibody collection, stool sample preservation, RNA, biomarker stability, metabolic biomarkers and T-cell viability. RESEARCH DESIGN AND METHODS: The Environmental Determinants of Diabetes in the Young is a multicentre, international prospective study (n = 8677) designed to identify environmental triggers of type 1 diabetes (T1D) in genetically at-risk children from ages 3 months until 15 years. The study is conducted through six primary clinical centres located in four countries. RESULTS: As of May 2012, over three million biological samples and 250 million total data points have been collected, which will be analysed to assess autoimmunity status, presence of inflammatory biomarkers, genetic factors, exposure to infectious agents, dietary biomarkers and other potentially important environmental exposures in relation to autoimmunity and progression to T1D. CONCLUSIONS: Detailed procedures were utilized to standardize both data harmonization and management when handling a large quantity of longitudinal samples obtained from multiple locations. In addition, a description of the available specimens is provided that serve as an invaluable repository for the elucidation of determinants in T1D focusing on autoantibody concordance and harmonization, transglutaminase autoantibody, inflammatory biomarkers (T-cells), genetic proficiency testing, RNA lab internal quality control testing, infectious agents (monitoring cross-contamination, virus preservation and nasal swab collection validity) and HbA1c testing.

In type 1 diabetes (T1D) an intense inflammatory response destroys β cells in the pancreas, where insulin is produced and released. A therapy for T1D that reduces the specific autoimmune response in this disease while leaving the remainder of the immune system intact has long been sought. Proinsulin is a major target of adaptive immunity in T1D. We hypothesized that an engineered DNA plasmid encoding proinsulin (BHT-3021) would preserve β cell function in T1D patients through reduction of insulin-specific T cells. We studied 80 subjects over 18 years of age who were diagnosed with T1D within 5 years. Subjects were randomized 2:1 to receive intramuscular injections of BHT-3021 or BHT-placebo, weekly for 12 weeks, and then monitored for safety and immune responses in a blinded fashion. Four dose levels of BHT-3021 were evaluated: 0.3, 1.0, 3.0, and 6.0 mg. C-peptide served as an exploratory measure of efficacy and safety. Islet-specific CD8+ T cell frequencies were assessed with multimers of monomeric human leukocyte antigen class I molecules loaded with peptides containing pancreatic or unrelated antigens. No serious adverse events related to BHT-3021 occurred. C-peptide levels improved relative to placebo at all doses, most notably at 1 mg at 15 weeks (+19.5% BHT-3021 versus −8.8% BHT-placebo, P < 0.026). Proinsulin-reactive CD8+ T cells, but not T cells against unrelated islet or foreign molecules, declined in the BHT-3021 arm (P < 0.006). Thus, we demonstrate that a plasmid encoding proinsulin reduces the frequency of CD8+ T cells reactive to proinsulin while preserving C-peptide over the course of dosing.

Stiff-man syndrome is a neurologic disorder characterized by progressive rigidity of skeletal muscles. Deficiency of the neurotransmitter gamma-aminobutyric acid and autoantibodies to glutamic acid decarboxylase (GAD), the enzyme synthesizing gamma-aminobutyric acid, are closely associated with the disorder, although the relevant antigenic epitopes have not been identified. In the present study, sera from two patients with SMS was used in an immunoblotting assay with recombinant GAD67 (M(r) 67,000) and GAD65 (M(r) 65,000) isoforms to test whether SMS sera can recognize specific epitopes. We found that both SMS sera recognized the GAD65, but not the GAD67, isoform. Using 13 different synthetic GAD peptides to block the autoantibodies, two GAD65 epitopes were identified. One epitope recognized by both patients' sera, was blocked by the peptide representing amino acid residues 354-368. In one patient only, blocking was also observed by a peptide representing residues 390-402, which includes the binding site of the GAD cofactor, pyridoxal 5'-phosphate. A single amino acid substitution in GAD65 at position 401 (leucine to proline) and representing the analogous GAD67 sequence in this region significantly reduced the peptide's inhibitory effect. These findings suggest that SMS GAD autoantibodies share distinct GAD65 linear epitopes and that some SMS patients' autoantibodies may block the active site, explaining SMS GABA deficiency.