Islet Autoantibody Standardization Program 2018 Workshop:Interlaboratory Comparison of Glutamic Acid Decarboxylase Autoantibody Assay Performance

BACKGROUND: The Islet Autoantibody Standardization Program (IASP) aims to improve the performance of immunoassays measuring type 1 diabetes (T1D)-associated autoantibodies and the concordance of results among laboratories. IASP organizes international interlaboratory assay comparison studies in which blinded serum samples are distributed to participating laboratories, followed by centralized collection and analysis of results, providing participants with an unbiased comparative assessment. In this report, we describe the results of glutamic acid decarboxylase autoantibody (GADA) assays presented in the IASP 2018 workshop. METHODS: In May 2018, IASP distributed to participants uniquely coded sera from 43 new-onset T1D patients, 7 multiple autoantibody-positive nondiabetic individuals, and 90 blood donors. Results were analyzed for the following metrics: sensitivity, specificity, accuracy, area under the ROC curve (ROC-AUC), partial ROC-AUC at 95% specificity (pAUC95), and concordance of qualitative and quantitative results. RESULTS: Thirty-seven laboratories submitted results from a total of 48 different GADA assays adopting 9 different formats. The median ROC-AUC and pAUC95 of all assays were 0.87 [interquartile range (IQR), 0.83-0.89] and 0.036 (IQR, 0.032-0.039), respectively. Large differences in pAUC95 (range, 0.001-0.0411) were observed across assays. Of formats widely adopted, bridge ELISAs showed the best median pAUC95 (0.039; range, 0.036-0.041). CONCLUSIONS: Several novel assay formats submitted to this study showed heterogeneous performance. In 2018, the majority of the best performing GADA immunoassays consisted of novel or established nonradioactive tests that proved on a par or superior to the radiobinding assay, the previous gold standard assay format for GADA measurement

Biobanking, consent, and commercialization in international genetics research: the Type 1 Diabetes Genetics Consortium

Background and Purpose This article describes several ethical, legal, and social issues typical of international genetics biobanking, as encountered in the Type 1 Diabetes Genetics Consortium (T1DGC)

Detection of antibodies directed to the N-terminal region of GAD is dependent on assay format and contributes to differences in the specificity of GAD autoantibody assays for type 1 diabetes

Autoantibodies to glutamate decarboxylase (GADA) are sensitive markers of islet autoimmunity and type 1 diabetes. They form the basis of robust prediction models and are widely used for recruitment of subjects at high risk of type 1 diabetes to prevention trials. However GADA are also found in many individuals at low risk of diabetes progression. To identify the sources of diabetes irrelevant GADA reactivity therefore, we analyzed data from the 2009 and 2010 Diabetes Autoantibody Standardization Program GADA workshop and found that binding of healthy control sera varied according to assay type. Characterization of control sera found positive by radiobinding assay, but negative by ELISA showed that many of these sera reacted to epitopes in the N-terminal region of the molecule. This finding prompted development of an N-terminally truncated GAD65 radiolabel, (35)S-GAD65(96-585), which improved the performance of most GADA radiobinding assays (RBAs) participating in an Islet Autoantibody Standardization Program GADA substudy. These detailed workshop comparisons have identified a source of disease-irrelevant signals in GADA RBAs and suggest that N-terminally truncated GAD labels will enable more specific measurement of GADA in type 1 diabetes

Measurement of islet cell antibodies in the Type 1 Diabetes Genetics Consortium: efforts to harmonize procedures among the laboratories

Background and Purpose Three network laboratories measured antibodies to islet autoantigens. Antibodies to glutamic acid decarboxylase (GAD65 [GADA]) and the intracellular portion of protein tyrosine phosphatase (IA-2ic [IA-2A]) were measured by similar, but not identical, methods in samples from participants in the Type 1 Diabetes Genetics Consortium (T1DGC)

Quality control of phenotypic forms data in the Type 1 Diabetes Genetics Consortium

Background When collecting phenotypic data in clinics across the globe, the Type 1 Diabetes Genetics Consortium (T1DGC) used several techniques that ensured consistency, completeness, and accuracy of the data

Tests for Genetic Interactions in Type 1 Diabetes: Linkage and Stratification Analyses of 4,422 Affected Sib-Pairs

OBJECTIVE - Interactions between genetic and environmental factors lead to immune dysregulation causing type 1 diabetes and other autoimmune disorders. Recently, many common genetic variants have been associated with type 1 diabetes risk, but each has modest individual effects. Familial clustering of type 1 diabetes has not been explained fully and could arise from many factors, including undetected genetic variation and gene interactions. RESEARCH DESIGN AND METHODS - To address this issue, the Type 1 Diabetes Genetics Consortium recruited 3,892 families, including 4,422 affected sib-pairs. After genotyping 6,090 markers, linkage analyses of these families were performed, using a novel method and taking into account factors such as genotype at known susceptibility loci. RESULTS - Evidence for linkage was robust at the HLA and INS loci, with logarithm of odds (LOD) scores of 398.6 and 5.5, respectively. There was suggestive support for five other loci. Stratification by other risk factors (including HLA and age at diagnosis) identified one convincing region on chromosome 6q14 showing linkage in male subjects (corrected LOD = 4.49; replication P = 0.0002), a locus on chromosome 19q in HLA identical siblings (replication P = 0.006), and four other suggestive loci. CONCLUSIONS - This is the largest linkage study reported for any disease. Our data indicate there are no major type 1 diabetes subtypes definable by linkage analyses; susceptibility is caused by actions of HLA and an apparently random selection from a large number of modest-effect loci; and apart from HLA and INS, there is no important susceptibility factor discoverable by linkage methods

Transcriptional networks in at-risk individuals identify signatures of type 1 diabetes progression.

Type 1 diabetes (T1D) is a disease of insulin deficiency that results from autoimmune destruction of pancreatic islet β cells. The exact cause of T1D remains unknown, although asymptomatic islet autoimmunity lasting from weeks to years before diagnosis raises the possibility of intervention before the onset of clinical disease. The number, type, and titer of islet autoantibodies are associated with long-term disease risk but do not cause disease, and robust early predictors of individual progression to T1D onset remain elusive. The Environmental Determinants of Diabetes in the Young (TEDDY) consortium is a prospective cohort study aiming to determine genetic and environmental interactions causing T1D. Here, we analyzed longitudinal blood transcriptomes of 2013 samples from 400 individuals in the TEDDY study before both T1D and islet autoimmunity. We identified and interpreted age-associated gene expression changes in healthy infancy and age-independent changes tracking with progression to both T1D and islet autoimmunity, beginning before other evidence of islet autoimmunity was present. We combined multivariate longitudinal data in a Bayesian joint model to predict individual risk of T1D onset and validated the association of a natural killer cell signature with progression and the model's predictive performance on an additional 356 samples from 56 individuals in the independent Type 1 Diabetes Prediction and Prevention study. Together, our results indicate that T1D is characterized by early and longitudinal changes in gene expression, informing the immunopathology of disease progression and facilitating prediction of its course.The TEDDY Study is funded by U01 DK63829, U01 DK63861, U01 DK63821, U01 DK63865, U01 DK63863, U01 DK63836, U01 DK63790, UC4 DK63829, UC4 DK63861, UC4 DK63821, UC4 DK63865, UC4 DK63863, UC4 DK63836, UC4 DK95300, UC4 DK100238, UC4 DK106955, UC4 DK112243, UC4 DK117483, and Contract No. HHSN267200700014C from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institute of Allergy and Infectious Diseases (NIAID), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institute of Environmental Health Sciences (NIEHS), Centers for Disease Control and Prevention (CDC), and JDRF. This work supported in part by the NIH/NCATS Clinical and Translational Science Awards to the University of Florida (UL1 TR000064) and the University of Colorado (UL1 TR001082). KGCS is a Lister Prize fellow and is supported by a Wellcome Trust Senior Investigator award (200871/Z/16/Z). EFM is a Wellcome-Beit prize fellow (10406/Z/14/A) supported by the Wellcome Trust and Beit Foundation (10406/Z/14/Z) and by the National Institutes for Health Research Biomedical Research Centre (Cambridge). LPX’s affiliation changed after completion of the manuscript and is now Département d'informatique et de recherche opérationnelle, Université de Montréal, Montréal, Canada and Mila, Quebec Institute for Learning Algorithms, Montréal, Canada

Metagenomics of the faecal virome indicate a cumulative effect of enterovirus and gluten amount on the risk of coeliac disease autoimmunity in genetically at risk children: the TEDDY study

Objective: Higher gluten intake, frequent gastrointestinal infections and adenovirus, enterovirus, rotavirus and reovirus have been proposed as environmental triggers for coeliac disease. however, it is not known whether an interaction exists between the ingested gluten amount and viral exposures in the development of coeliac disease. This study investigated whether distinct viral exposures alone or together with gluten increase the risk of coeliac disease autoimmunity (cDa) in genetically predisposed children. Design: The environmental Determinants of Diabetes in the Young study prospectively followed children carrying the hla risk haplotypes DQ2 and/or DQ8 and constructed a nested case–control design. From this design, 83 cDa case–control pairs were identified. Median age of cDa was 31 months. stool samples collected monthly up to the age of 2 years were analysed for virome composition by illumina next-generation sequencing followed by comprehensive computational virus profiling. Results: The cumulative number of stool enteroviral exposures between 1 and 2 years of age was associated with an increased risk for cDa. in addition, there was a significant interaction between cumulative stool enteroviral exposures and gluten consumption. The risk conferred by stool enteroviruses was increased in cases reporting higher gluten intake. Conclusions: Frequent exposure to enterovirus between 1 and 2 years of age was associated with increased risk of cDa. The increased risk conferred by the interaction between enteroviruses and higher gluten intake indicate a cumulative effect of these factors in the development of cDa.Peer reviewe

Factors Associated with Decline of C-peptide in a Cohort of Young Children Diagnosed with Type 1 Diabetes

Context: Understanding factors involved in the rate of C-peptide decline is needed to tailor therapies for type 1 diabetes (T1D).Objective: Evaluate factors associated with rate of C-peptide decline after T1D diagnosis in young children.Design: Observational study.Setting: Academic centers.Participants: 57 participants in The Environmental Determinants of Diabetes in the Young (TEDDY) enrolled at 3 months of age and followed until T1D and 56 age-matched children diagnosed with T1D in the community.Intervention: A mixed meal tolerance test was used to measure the area under the curve (AUC) C-peptide at 1, 3, 6, 12 and 24 months post-diagnosis.Outcome: Factors associated with rate of C-peptide decline during the first 2 years post-diagnosis were evaluated using mixed effects models adjusting for age at diagnosis and baseline C-peptide.Results: Adjusted slopes of AUC C-peptide decline did not differ between TEDDY subjects and community controls (p=0.21), although the former had higher C-peptide baseline levels. In univariate analyses combining both groups (n=113), younger age, higher weight and BMI z-scores, female sex, increased number of islet autoantibodies, and IA-2A or ZnT8A positivity at baseline were associated with higher rate of C-peptide loss. Younger age, female sex and higher weight z-score remained significant in multivariate analysis (all pConclusion: Younger age at diagnosis, female sex, higher weight z-score, and HbA1c were associated with higher rate of C-peptide decline after T1D diagnosis in young children.</p