Diabetes Autoimmunity Study In The Young Research Articles

DNA Methylation Near DLGAP2 May Mediate the Relationship between Family History of Type 1 Diabetes and Type 1 Diabetes Risk.

Given the differential risk of type 1 diabetes (T1D) in offspring of affected fathers versus affected mothers and our observation that T1D cases have differential DNA methylation near the imprinted DLGAP2 gene compared to controls, we examined whether methylation near DLGAP2 mediates the association between T1D family history and T1D risk. In a nested case-control study of 87 T1D cases and 87 controls from the Diabetes Autoimmunity Study in the Young, we conducted causal mediation analyses at 12 DLGAP2 region CpGs to decompose the effect of family history on T1D risk into indirect and direct effects. These effects were estimated from two regression models adjusted for the human leukocyte antigen DR3/4 genotype: a linear regression of family history on methylation (mediator model) and a logistic regression of family history and methylation on T1D (outcome model). For 8 of the 12 CpGs, we identified a significant interaction between T1D family history and methylation on T1D risk. Accounting for this interaction, we found that the increased risk of T1D for children with affected mothers compared to those with no family history was mediated through differences in methylation at two CpGs (cg27351978, cg00565786) in the DLGAP2 region, as demonstrated by a significant pure natural indirect effect (odds ratio (OR) = 1.98, 95% confidence interval (CI): 1.06-3.71) and nonsignificant total natural direct effect (OR = 1.65, 95% CI: 0.16-16.62) (for cg00565786). In contrast, the increased risk of T1D for children with an affected father or sibling was not explained by DNA methylation changes at these CpGs. Results were similar for cg27351978 and robust in sensitivity analyses. Lastly, we found that DNA methylation in the DLGAP2 region was associated (P<0:05) with gene expression of nearby protein-coding genes DLGAP2, ARHGEF10, ZNF596, and ERICH1. Results indicate that the maternal protective effect conferred through exposure to T1D in utero may operate through changes to DNA methylation that have functional downstream consequences.

Paving the way for evidence-based population screening for type 1 diabetes.

Since the 1980s, we have been gaining knowledge about the pathogenesis of type 1 diabetes and found that the measurement of diabetes-associated autoantibodies against insulin, glutamic acid decarboxylase, insulinoma-associated protein 2, and zinc transporter 8 has a central role in recognition of early stages of the disease in asymptomatic people. In the 1990s, large prospective studies were established in Finland (the Diabetes Prediction and Prevention [DIPP] study 1 Kupila A Muona P Simell T et al. Feasibility of genetic and immunological prediction of type I diabetes in a population-based birth cohort. Diabetologia. 2001; 44: 290-297 Crossref PubMed Scopus (268) Google Scholar ), Germany (the BABYDIAB study 2 Ziegler AG Hummel M Schenker M Bonifacio E Autoantibody appearance and risk for development of childhood diabetes in offspring of parents with type 1 diabetes: the 2-year analysis of the German BABYDIAB study. Diabetes. 1999; 48: 460-468 Crossref PubMed Scopus (536) Google Scholar ), Sweden (Diabetes Prediction in Skåne Study 3 Elding Larsson H A Swedish approach to the prevention of type 1 diabetes. Pediatr Diabetes. 2016; 17: 73-77 Crossref PubMed Scopus (13) Google Scholar ), and the USA (the Diabetes Autoimmunity Study in the Young [DAISY] 4 Rewers M Bugawan TL Norris JM et al. Newborn screening for HLA markers associated with IDDM: Diabetes Autoimmunity Study in the Young (DAISY). Diabetologia. 1996; 39: 807-812 Crossref PubMed Scopus (349) Google Scholar ) that followed up children with a high genetic risk of developing type 1 diabetes from birth until diagnosis of clinical type 1 diabetes. On the basis of these findings, confirmed positivity for multiple (at least two) autoantibodies predicts almost inevitable progression to clinical type 1 diabetes within 15 years from seroconversion 5 Insel RA Dunne JL Atkinson MA et al. Staging presymptomatic type 1 diabetes: a scientific statement of JDRF, the Endocrine Society, and the American Diabetes Association. Diabetes Care. 2015; 38: 1964-1974 Crossref PubMed Scopus (473) Google Scholar and thus allows the diagnosis before clinical symptoms develop. However, the disease's progression shows a high variability and mostly depends on the age at which seroconversion occurs, with prechoolers having a faster decline of residual β-cell function than adolescents. Therefore, to better understand the interaction between genetics and environmental factors in children with a high genetic risk of type 1 diabetes, further large prospective studies, such as TEDDY 6 TEDDY Study GroupThe Environmental Determinants of Diabetes in the Young (TEDDY) study: study design. Pediatr Diabetes. 2007; 8: 286-298 Crossref PubMed Scopus (219) Google Scholar or Diabetes Evaluation in Washington (DEW‑IT), 7 Wion E Brantley M Stevens J et al. Population-wide infant screening for HLA-based type 1 diabetes risk via dried blood spots from the public health infrastructure. Ann NY Acad Sci. 2003; 1005: 400-403 Crossref PubMed Scopus (24) Google Scholar were established in the USA in the early 2000s. Although maximum autoantibody conversion occurs between the first and second year of life, approximately 20% of children develop multiple antibodies after 5 years of age. Islet autoantibody screening in at-risk adolescents to predict type 1 diabetes until young adulthood: a prospective cohort studyScreening of adolescents at risk for type 1 diabetes only once at 10 years of age for islet autoantibodies was highly effective to detect type 1 diabetes by the age of 18 years, which in turn could enable prevention of diabetic ketoacidosis and participation in secondary prevention trials. Full-Text PDF

Genome-wide analysis of oxylipins and oxylipin profiles in a pediatric population.

Oxylipins are inflammatory biomarkers derived from omega-3 and-6 fatty acids implicated in inflammatory diseases but have not been studied in a genome-wide association study (GWAS). The aim of this study was to identify genetic loci associated with oxylipins and oxylipin profiles to identify biologic pathways and therapeutic targets for oxylipins. We conducted a GWAS of plasma oxylipins in 316 participants in the Diabetes Autoimmunity Study in the Young (DAISY). DNA samples were genotyped using the TEDDY-T1D Exome array, and additional variants were imputed using the Trans-Omics for Precision Medicine (TOPMed) multi-ancestry reference panel. Principal components analysis of 36 plasma oxylipins was used to capture oxylipin profiles. PC1 represented linoleic acid (LA)- and alpha-linolenic acid (ALA)-related oxylipins, and PC2 represented arachidonic acid (ARA)-related oxylipins. Oxylipin PC1, PC2, and the top five loading oxylipins from each PC were used as outcomes in the GWAS (genome-wide significance: p < 5×10-8). The SNP rs143070873 was associated with (p < 5×10-8) the LA-related oxylipin 9-HODE, and rs6444933 (downstream of CLDN11) was associated with the LA-related oxylipin 13 S-HODE. A locus between MIR1302-7 and LOC100131146, rs10118380 and an intronic variant in TRPM3 were associated with the ARA-related oxylipin 11-HETE. These loci are involved in inflammatory signaling cascades and interact with PLA2, an initial step to oxylipin biosynthesis. Genetic loci involved in inflammation and oxylipin metabolism are associated with oxylipin levels.

An Oxylipin-Related Nutrient Pattern and Risk of Type 1 Diabetes in the Diabetes Autoimmunity Study in the Young (DAISY).

Oxylipins, pro-inflammatory and pro-resolving lipid mediators, are associated with the risk of type 1 diabetes (T1D) and may be influenced by diet. This study aimed to develop a nutrient pattern related to oxylipin profiles and test their associations with the risk of T1D among youth. The nutrient patterns were developed with a reduced rank regression in a nested case-control study (n = 335) within the Diabetes Autoimmunity Study in the Young (DAISY), a longitudinal cohort of children at risk of T1D. The oxylipin profiles (adjusted for genetic predictors) were the response variables. The nutrient patterns were tested in the case-control study (n = 69 T1D cases, 69 controls), then validated in the DAISY cohort using a joint Cox proportional hazards model (n = 1933, including 81 T1D cases). The first nutrient pattern (NP1) was characterized by low beta cryptoxanthin, flavanone, vitamin C, total sugars and iron, and high lycopene, anthocyanidins, linoleic acid and sodium. After adjusting for T1D family history, the HLA genotype, sex and race/ethnicity, NP1 was associated with a lower risk of T1D in the nested case-control study (OR: 0.44, p = 0.0126). NP1 was not associated with the risk of T1D (HR: 0.54, p-value = 0.1829) in the full DAISY cohort. Future studies are needed to confirm the nested case-control findings and investigate the modifiable factors for oxylipins.

Consortium-based approach to receiving an EMA qualification opinion on the use of islet autoantibodies as enrichment biomarkers in type 1 diabetes clinical studies.

The development of medical products that can delay or prevent progression to stage 3 type 1 diabetes faces many challenges. Of note, optimising patient selection for type 1 diabetes prevention clinical trials is hindered by significant patient heterogeneity and a lack of characterisation of the time-varying probability of progression to stage 3 type 1 diabetes in individuals positive for two or more islet autoantibodies. To meet these needs, the Critical Path Institute's Type 1 Diabetes Consortium was launched in 2017 as a pre-competitive public-private partnership between stakeholders from the pharmaceutical industry, patient advocacy groups, philanthropic organisations, clinical researchers, the National Institutes of Health and the Food and Drug Administration. The Type 1 Diabetes Consortium acquired and aggregated data from three longitudinal observational studies, Environmental Determinants of Diabetes in the Young (TEDDY), Diabetes Autoimmunity Study in the Young (DAISY) and TrialNet Pathway to Prevention (TN01), and used analysis subsets of these data to support the model-based qualification of islet autoantibodies as enrichment biomarkers for patient selection in type 1 diabetes prevention trials, including registration studies. The Type 1 Diabetes Consortium has now received a qualification opinion from the European Medicines Agency for the use of these biomarkers, a major success for the field of type 1 diabetes. This endorsement will improve product developers' ability to design clinical trials of agents intended to prevent or delay type 1 diabetes that are reduced in size and/or length, while being adequately powered.

Changes in the Coexpression of Innate Immunity Genes During Persistent Islet Autoimmunity Are Associated With Progression of Islet Autoimmunity: Diabetes Autoimmunity Study in the Young (DAISY).

Longitudinal changes in gene expression during islet autoimmunity (IA) may provide insight into biological processes that explain progression to type 1 diabetes (T1D). We identified individuals from Diabetes Autoimmunity Study in the Young (DAISY) who developed IA, autoantibodies present on two or more visits. Illumina's NovaSeq 6000 was used to quantify gene expression in whole blood. With linear mixed models we tested for changes in expression after IA that differed across individuals who progressed to T1D (progressors) (n = 25), reverted to an autoantibody-negative stage (reverters) (n = 47), or maintained IA positivity but did not develop T1D (maintainers) (n = 66). Weighted gene coexpression network analysis was used to identify coexpression modules. Gene Ontology pathway analysis of the top 150 differentially expressed genes (nominal P < 0.01) identified significantly enriched pathways including leukocyte activation involved in immune response, innate immune response, and regulation of immune response. We identified a module of 14 coexpressed genes with roles in the innate immunity. The hub gene, LTF, is known to have immunomodulatory properties. Another gene within the module, CAMP, is potentially relevant based on its role in promoting β-cell survival in a murine model. Overall, results provide evidence of alterations in expression of innate immune genes prior to onset of T1D.

185-OR: T-Cell Receptor Repertoires during Type 1 Diabetes Development

In type 1 diabetes (T1D) , T cells target and destroy pancreatic beta cells. T cells express T cell receptors (TCRs) which recognize peptide antigens, and each TCR is unique to a given T cell. To understand the TCR repertoire during T1D development, we used next generation sequencing to detect TCRβ chains from longitudinal peripheral blood DNA samples at four time points from genetically at-risk cases (n=29) who progressed to T1D and age/sex/HLA matched controls (n=25) beginning early in life (median age 1.4 years) in the Diabetes Autoimmunity Study in the Young (DAISY) . Over 50 million TCRβ chains were sequenced, and the repertoires became less diverse (i.e., more clonal) over time with age in both groups (p&amp;lt;0.001) . Principal component analyses of TCRβ V gene usage identified a subset of cases (n=11) that had higher frequencies of specific V genes beginning early in life before islet autoantibody seroconversion compared to the remaining cases and controls. The subset of cases were more likely to be double positive for GADA and IA-2A compared to the remaining cases (p=0.008) . Previously, we sequenced ∼3,500 αβTCRs from the residual islets of T1D organ donors (n=9) and identified 44 TCRs that recognize preproinsulin (PPI) . We searched for the PPI-reactive TCRβs (identical V gene, J gene, and CDR3) , and 15 TCRβs (6 CD4 and 9 CD8) were found to be shared in DAISY participants. The PPI CD4 TCRβ sequences (templates) were more frequent in cases compared to controls, 180 vs. 14 (p&amp;lt;0.001) , but CD8 PPI templates were similar between cases and controls, 29 vs. 25. Using an algorithm to identify additional TCRs predicted to recognize similar PPI peptides, we found that these TCR clusters were more frequent in cases compared to controls and accumulated after islet autoantibody seroconversion. Lastly, PPI TCRs and clusters were identified in a separate cohort of new onset T1D patients (n=143, mean age 12.5 years) . Our results demonstrate that islet-derived TCR clusters have the potential to be a biomarker prior to clinical T1D onset. Disclosure A.M.Mitchell: None. M.Nakayama: None. A.W.Michels: Employee; ImmunoMolecular Therapeutics, Stock/Shareholder; ImmunoMolecular Therapeutics. E.E.Baschal: None. K.Mcdaniel: None. L.Pyle: None. K.Waugh: None. A.Steck: None. L.Yu: None. P.Gottlieb: Advisory Panel; Janssen Research &amp; Development, LLC, ViaCyte, Inc., Other Relationship; IM Therapeutics, Research Support; Caladrius Biosciences, Inc., Immune Tolerance Network, National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk, Precigen, Inc., Tolerion, Inc. M.Rewers: Consultant; Janssen Research &amp; Development, LLC, Medscape, Provention Bio, Inc., Research Support; Dexcom, Inc., JDRF, Roche Diagnostics USA. Funding National Institutes of Health (DK108868, DK110845, DK032083, DK032493, DK116073) Juvenile Diabetes Research Foundation (3-PDF-2020-943-A-N) Leona M. &amp; Harry B. Helmsley Charitable Trust (2103-05093) Colorado Clinical and Translational Science Institute (TR002535)

351-OR: Investigation of Novel Vitamin D Metabolites and Risk of Islet Autoimmunity and Progression to Type 1 Diabetes

Lower blood 25 (OH) D concentration is associated with increased risk of islet autoimmunity (IA) in some cohorts; it is not known if 25 (OH) D metabolites are important after the onset of IA. We investigated novel vitamin D metabolites in development of IA and progression from IA to T1D in the Diabetes Autoimmunity Study in the Young (DAISY) . IA was defined as two or more consecutive visits positive for ≥ 1 autoantibody (IAA, IA-2A, GAD, ZnT8) . In a nested case-control study, we examined plasma vitamin D metabolites at a pre-seroconversion visit in 114 IA cases and 116 controls. We then followed 144 IA-positive children, of whom 46 developed T1D during a mean follow-up of 8.4 years. Plasma was quantified for 25 (OH) D3, 3-epi-25 (OH) D3, 25 (OH) D2, 24,25 (OH) 2D3, and 1,25 (OH) 2D3, using targeted LC-MS/MS. Logistic regression was used to examine pre-seroconversion metabolites and IA, and Cox regression was used to examine metabolites at seroconversion and progression to T1D. Both models adjusted for age, ethnicity, T1D family history and HLA-DR3/4. Higher pre-seroconversion level of 24,25 (OH) 2D3, an inactive catabolite of 25 (OH) D3, was associated with increased odds of IA (OR: 1.35; 95%CI: 1.03,1.78 per SD of 24,25 (OH) 2D3; p=0.031) . The association between 3-epi-25 (OH) D3 at seroconversion and progression from IA to T1D was modified by age at seroconversion. Higher 3-epi-25 (OH) D3 level was more protective against progression to T1D among children who seroconverted at an older age (HR: 0.47; 95%CI: 0.26, 0.85 for children at the 75th percentile of age at seroconversion (ie years)) compared to children who seroconverted at a younger age (HR: 0.88; 95%CI: 0.63, 1.24 for children at the 25th percentile (ie 3 years)) . Neither IA nor progression to T1D was associated with 25 (OH) D3, 25 (OH) D2 or 1,25 (OH) 2D3.Increased 24,25 (OH) 2D3 may play a role in IA development. The age-related heterogeneity of the relationship between 3-epi-25 (OH) D3 and T1D progression requires further investigation. Disclosure S.Kim: None. K.Kechris: None. O.Fiehn: None. M.Rewers: Consultant; Janssen Research &amp; Development, LLC, Medscape, Provention Bio, Inc., Research Support; Dexcom, Inc., JDRF, Roche Diagnostics USA. J.M.Norris: None. N.L.Zwick: None. P.M.Carry: None. B.C.Defelice: None. R.K.Johnson: None. F.Dong: None. T.Buckner: None. L.A.Vanderlinden: None. B.I.Frohnert: Advisory Panel; Provention Bio, Inc. Funding National Institutes of Health (R01-DK104351, R01-DK32493, RI142483)

A Mediation Approach to Discovering Causal Relationships between the Metabolome and DNA Methylation in Type 1 Diabetes.

Environmental factors including viruses, diet, and the metabolome have been linked with the appearance of islet autoimmunity (IA) that precedes development of type 1 diabetes (T1D). We measured global DNA methylation (DNAm) and untargeted metabolomics prior to IA and at the time of seroconversion to IA in 92 IA cases and 91 controls from the Diabetes Autoimmunity Study in the Young (DAISY). Causal mediation models were used to identify seven DNAm probe-metabolite pairs in which the metabolite measured at IA mediated the protective effect of the DNAm probe measured prior to IA against IA risk. These pairs included five DNAm probes mediated by histidine (a metabolite known to affect T1D risk), one probe (cg01604946) mediated by phostidyl choline p-32:0 or o-32:1, and one probe (cg00390143) mediated by sphingomyelin d34:2. The top 100 DNAm probes were over-represented in six reactome pathways at the FDR <0.1 level (q = 0.071), including transport of small molecules and inositol phosphate metabolism. While the causal pathways in our mediation models require further investigation to better understand the biological mechanisms, we identified seven methylation sites that may improve our understanding of epigenetic protection against T1D as mediated by the metabolome.

High-affinity ZnT8 Autoantibodies by Electrochemiluminescence Assay Improve Risk Prediction for Type 1 Diabetes.

ContextSingle ZnT8 autoantibody (ZnT8A) positivity by standard radiobinding assay (RBA) is commonly seen in nondiabetes population-based screening and the risk of progression to type 1 diabetes (T1D) in subjects with single ZnT8A is unknown.ObjectiveIdentify the risk of progression to T1D in individuals positive only for ZnT8A.MethodsWe developed an electrochemiluminescence (ECL) assay to detect high-affinity ZnT8A and validated it in 3 populations: 302 patients newly diagnosed with T1D, 135 nondiabetic children positive for ZnT8A by RBA among 23 400 children screened by the Autoimmunity Screening for Kids (ASK) study, and 123 nondiabetic children multiple autoantibody positive or single ZnT8A positive by RBA participating in the Diabetes Autoimmunity Study in the Young (DAISY).ResultsIn 302 patients with T1D at diagnosis, the positivity for ZnT8A was 62% both in RBA and ECL. Among ASK 135 participants positive for RBA-ZnT8A, 64 were detected ZnT8A as the only islet autoantibody. Of these 64, only 9 were confirmed by ECL-ZnT8A, found to be of high affinity with increased T1D risk. The overall positive predictive value of ECL-ZnT8A for T1D risk was 87.1%, significantly higher than that of RBA-ZnT8A (53.5%, P < .001). In DAISY, 11 of 2547 children who had no positivity previously detected for other islet autoantibodies were identified as single ZnT8A by RBA; of these, 3 were confirmed positive by ECL-ZnT8A and all 3 progressed to clinical T1D.ConclusionA large proportion of ZnT8A by RBA are single ZnT8A with low T1D risk, whereas ZnT8A by ECL was of high affinity and high prediction for T1D development.

159-LB: High-Affinity ZnT8 Autoantibodies by Electrochemiluminescence Assay Improve the Risk Prediction for Type 1 Diabetes

Background: A cohort of children with single ZnT8 autoantibody (ZnT8A) positivity were identified in two large clinical trials, Autoimmunity Screening for Kids (ASK) and Diabetes Autoimmunity Study in the Young (DAISY), and their risk of type 1 diabetes (T1D) have never been studied. Methods: Three cohorts were analyzed using a high-affinity electrochemiluminescence (ECL) ZnT8A assay including 302 new onset T1D patients, 135 children positive for ZnT8A by standard radio-binding assay (RBA) from 23400 children screened in ASK study, and 123 children with multiple autoantibodies or single ZnT8A by RBA from 2547 children in DAISY study. Results: ECL-ZnT8A had a similar sensitivity with RBA-ZnT8A in the cohort of 302 new onset T1D patients (62.3% vs. 61.9%). In ASK, 135/23400 of general population children were positive for RBA-ZnT8A and 64/135 were found as single ZnT8A only without other islet autoantibodies. Of 64 children with single ZnT8A, only 14.1% (9/64) were detectable by ECL-ZnT8A. Antibody-affinity analysis revealed that the ZnT8A in RBA but not confirmed by ECL were of low affinity and they were easily disappeared during the follow-up behaving as ‘transient’ positivity. In terms of T1D classification from stage 1 to stage 3, positive predictive value (PPV) of ECL-ZnT8A (61/70 [87.1%]) was significantly higher than that of RBA-ZnT8A (73/137 [53.3%]; P&amp;lt;0.0001). The cumulative risk of clinical T1D development with ZnT8A confirmed by ECL (16/66) was significantly enhanced during a short time of follow-up, compared with ZnT8A not confirmed by ECL (1/43; p=0.023). Similarly in DAISY participants, 11/2547 children were identified as single ZnT8A by RBA while only three who developed T1D were detected ECL-ZnT8A. Conclusions: Large proportion of ZnT8A by current standard RBA are single ZnT8A with majority at low risk in population-based screening while ECL-ZnT8A can discriminate high risk from low risk and are highly predictive for T1D development. Disclosure X. Jia: None. L. He: None. D. Miao: None. K. Waugh: None. C. Geno rasmussen: None. F. Dong: None. M. Rewers: Advisory Panel; Self; Provention Bio, Inc., Consultant; Self; RTI, Research Support; Self; Janssen Research &amp; Development, LLC, JDRF. L. Yu: None. Funding Diabetes Research Center (P30DK116073); JDRF (2-SRA-2018-533-S-B, 2-SRA-2020-965-S-B, 1-SRA-2016-208-S-B); National Institutes of Health (DK32083)

109-OR: T-Cell Responses to Hybrid Insulin Peptides Precede Type 1 Diabetes Development

Type 1 diabetes (T1D) results from the T cell-mediated destruction of insulin-producing beta-cells within pancreatic islets. T cell responses to post-translationally modified hybrid insulin peptides (HIPs) have been implicated in T1D pathogenesis, and we hypothesized that CD4 T cell responses to HIPs precede clinical diabetes onset. Therefore, we measured longitudinal T cell responses to native and hybrid insulin peptides in a cohort of genetically at-risk individuals from the Diabetes AutoImmunity Study in the Young (DAISY). Using cytokine ELISPOT assays, both pro-inflammatory (IFN-γ) and anti-inflammatory (IL-10) cytokine responses to HIPs were more robust than to native peptides. Three of the 38 autoantibody negative individuals (med. age 18.7 yrs) developed islet autoimmunity during 2 years of follow-up, and the C-peptide-islet amyloid polypeptide-2 (C:IAPP-2), C-peptide-neuropeptide Y (C:NPY), and C-peptide-insulin A chain (C:A chain) HIPs induced more frequent pro-inflammatory T cell responses compared to those that did not develop autoantibodies. Five of the 25 autoantibody positive individuals (med. age 18.7 yrs) progressed to clinical T1D during the study, and the C:IAPP-2 HIP more frequently induced a pro-inflammatory response compared to those that did not progress (p=0.037). Additionally, length of time from autoantibody seroconversion correlated with proinflammatory T cell responses to the insulin B:9-23 (B22E) HIP (p=0.007) and the native B:9-23 peptide (p=0.022). T cell responses to the B22E HIP also strongly correlated with insulin autoantibody levels (p=0.0001). Furthermore, responses to the C:IAPP-2 HIP correlated with worsening measurements of blood glucose (A1c %, p=0.046; glucose area under the curve, p=0.054). Monitoring T cell responses to post-translationally modified antigens prior to T1D onset holds promise for determining which individuals are likely to progress to clinical disease and may benefit from immune intervention to prevent T1D onset. Disclosure A. M. Mitchell: None. M. Rewers: Advisory Panel; Self; Provention Bio, Inc., Consultant; Self; RTI, Research Support; Self; Janssen Research &amp; Development, LLC, JDRF. A. W. Michels: Stock/Shareholder; Self; IM Therapeutics. A. Alkanani: None. K. Mcdaniel: None. L. Pyle: None. K. Waugh: None. A. Steck: None. M. Nakayama: None. L. Yu: None. P. Gottlieb: Advisory Panel; Self; Janssen Research &amp; Development, LLC, Tolerion, Inc., Viacyte, Inc., Other Relationship; Self; ImmunoMolecular Therapeutics, Inc., Research Support; Self; Caladrius Biosciences, Inc., Immune Tolerance Network, Mercia Pharma Inc., National Institute of Diabetes and Digestive and Kidney Diseases, Precigen, Inc., Tolerion, Inc. Funding National Institutes of Health (DK108868, DK110845, DK032083, DK032493, DK116073); JDRF (3-PDF-2020-943-A-N); Children’s Diabetes Foundation; Colorado Clinical and Translational Science Institute (TR002535)

108-OR: Islet-Derived Preproinsulin T Cell Receptor Sequences Are Present throughout the Stages of Type 1 Diabetes Development

Type 1 diabetes (T1D) results from the T cell-mediated destruction of insulin-producing pancreatic β-cells as evidenced by CD8 and CD4 T cells being present within the inflamed islets of recent-onset T1D organ donors. We isolated, sequenced the T cell receptor (TCR) from ∼3,500 T cells in the residual islets of T1D organ donors (n=9), and determined antigen specificity to 41 preproinsulin-reactive T cells from these islet sequences. Among the T1D organ donor islet sequences, 32% are shared (identical Vβ, Jβ, CDR3β) within the peripheral blood of new-onset T1D patients that had sequencing done from whole blood DNA (n=162, 34x106 TCR sequences, Adaptive Biotechnologies). Similar numbers of sequences are shared between both CD4 and CD8 T cells. Furthermore, 53 unique sequences were disease-specific, as they were identified in &amp;lt;1% of TCR sequences from controls (n=786, 275x106 sequences), whereas they were detected in 54% of new-onset T1D patients (p&amp;lt;0.001). These disease-specific and preproinsulin-reactive TCR sequences are good candidates for biomarkers in T1D. Therefore, we next sequenced the TCR beta chains throughout the disease course of five participants in the Diabetes AutoImmunity Study in the Young (DAISY) at 4 time points (early in life, prior to islet autoantibody seroconversion, post-autoantibody seroconversion, and at T1D onset). 10% of these insulin-reactive TCR sequences, including those to hybrid insulin peptides, are present throughout the disease course. Interestingly, insulin-reactive CD4 TCRs were predominant early in life, while higher frequencies of both insulin-reactive CD8 and CD4 were present at clinical T1D diagnosis. With continued TCR sequencing from longitudinal patient samples across the stages of T1D and identifying antigen specificity to more islet-derived T cells outside of preproinsulin, TCR sequences from genomic DNA have the potential to be a powerful disease biomarker during the progression to clinical type 1 diabetes. Disclosure E. E. Baschal: None. A. W. Michels: Stock/Shareholder; Self; IM Therapeutics. A. M. Mitchell: None. K. Mcdaniel: None. A. Alkanani: None. T. Armstrong: None. L. Landry: None. K. Waugh: None. M. Rewers: Advisory Panel; Self; Provention Bio, Inc., Consultant; Self; RTI, Research Support; Self; Janssen Research &amp; Development, LLC, JDRF. M. Nakayama: None. Funding National Institutes of Health (DK108868, DK110845, DK032083, DK099317, DK032493)

The oxylipin profile is associated with development of type 1 diabetes: the Diabetes Autoimmunity Study in the Young (DAISY)

Oxylipins are lipid mediators derived from polyunsaturated fatty acids. Some oxylipins are proinflammatory (e.g. those derived from arachidonic acid [ARA]), others are pro-resolving of inflammation (e.g. those derived from α-linolenic acid [ALA], docosahexaenoic acid [DHA] and eicosapentaenoic acid [EPA]) and others may be both (e.g. those derived from linoleic acid [LA]). The goal of this study was to examine whether oxylipins are associated with incident type 1 diabetes. We conducted a nested case-control analysis in the Diabetes Autoimmunity Study in the Young (DAISY), a prospective cohort study of children at risk of type 1 diabetes. Plasma levels of 14 ARA-derived oxylipins, ten LA-derived oxylipins, six ALA-derived oxylipins, four DHA-derived oxylipins and two EPA-related oxylipins were measured by ultra-HPLC-MS/MS at multiple timepoints related to autoantibody seroconversion in 72 type 1 diabetes cases and 71 control participants, which were frequency matched on age at autoantibody seroconversion (of the case), ethnicity and sample availability. Linear mixed models were used to obtain an age-adjusted mean of each oxylipin prior to type 1 diabetes. Age-adjusted mean oxylipins were tested for association with type 1 diabetes using logistic regression, adjusting for the high risk HLA genotype HLA-DR3/4,DQB1*0302. We also performed principal component analysis of the oxylipins and tested principal components (PCs) for association with type 1 diabetes. Finally, to investigate potential critical timepoints, we examined the association of oxylipins measured before and after autoantibody seroconversion (of the cases) using PCs of the oxylipins at those visits. The ARA-related oxylipin 5-HETE was associated with increased type 1 diabetes risk. Five LA-related oxylipins, two ALA-related oxylipins and one DHA-related oxylipin were associated with decreased type 1 diabetes risk. A profile of elevated LA- and ALA-related oxylipins (PC1) was associated with decreased type 1 diabetes risk (OR 0.61; 95% CI 0.40, 0.94). A profile of elevated ARA-related oxylipins (PC2) was associated with increased diabetes risk (OR 1.53; 95% CI 1.03, 2.29). A critical timepoint analysis showed type 1 diabetes was associated with a high ARA-related oxylipin profile at post-autoantibody-seroconversion but not pre-seroconversion. The protective association of higher LA- and ALA-related oxylipins demonstrates the importance of both inflammation promotion and resolution in type 1 diabetes. Proinflammatory ARA-related oxylipins may play an important role once the autoimmune process has begun.

Phospholipid Levels at Seroconversion Are Associated With Resolution of Persistent Islet Autoimmunity: The Diabetes Autoimmunity Study in the Young.

Reversion of islet autoimmunity (IA) may point to mechanisms that prevent IA progression. We followed 199 individuals who developed IA during the Diabetes Autoimmunity Study in the Young. Untargeted metabolomics was performed in serum samples following IA. Cox proportional hazards models were used to test whether the metabolites (2,487) predicted IA reversion: two or more consecutive visits negative for all autoantibodies. We conducted a principal components analysis (PCA) of the top metabolites; |hazard ratio (HR) >1.25| and nominal P < 0.01. Phosphatidylcholine (16:0_18:1(9Z)) was the strongest individual metabolite (HR per 1 SD 2.16, false discovery rate (FDR)-adjusted P = 0.0037). Enrichment analysis identified four clusters (FDR P < 0.10) characterized by an overabundance of sphingomyelin (d40:0), phosphatidylcholine (16:0_18:1(9Z)), phosphatidylcholine (30:0), and l-decanoylcarnitine. Overall, 63 metabolites met the criteria for inclusion in the PCA. PC1 (HR 1.4, P < 0.0001), PC2 (HR 0.85, P = 0.0185), and PC4 (HR 1.28, P = 0.0103) were associated with IA reversion. Given the potential influence of diet on the metabolome, we investigated whether nutrients were correlated with PCs. We identified 20 nutrients that were correlated with the PCs (P < 0.05). Total sugar intake was the top nutrient. Overall, we identified an association between phosphatidylcholine, sphingomyelin, and carnitine levels and reversion of IA.

High-Affinity ZnT8 Autoantibodies by Electrochemiluminescence Assay Improve the Risk Prediction for Type 1 Diabetes

Background: A cohort of children with single ZnT8 autoantibody (ZnT8A) positivity were identified in two large clinical trials, Autoimmunity Screening for Kids (ASK) and Diabetes Autoimmunity Study in the Young (DAISY), and their risk of type 1 diabetes (T1D) have never been studied. Methods: Three cohorts were analyzed using a high-affinity electrochemiluminescence (ECL) ZnT8A assay including 302 new onset T1D patients, children with positive ZnT8A (n=135) by radio-binding assay (RBA) from 23400 general population children screened in the ASK study, and children (n=123) with multiple islet autoantibodies (IAbs) or single ZnT8A by RBA identified from 2547 longitudinally followed cases in DAISY. In addition, 1098 samples with all IAbs negative were also analyzed for ECL-ZnT8A. Findings: In ASK study, 0.58% (135/23400) of children were detected ZnT8A by RBA and 47.4% (64/135) of these ZnT8A were unexpectedly found as ZnT8A alone. Of 64 children with single ZnT8A, only 9 were detectable by ECL-ZnT8A. ZnT8A by RBA not confirmed by ECL were found low affinity with low risk. Positive predictive value of ECL-ZnT8A, in terms of high risk from T1D stage 1 to stage 3, was significantly higher (P<0.0001) than that of RBA-ZnT8A. Similarly in 2547 children of DAISY cohort, 11 cases in total were identified as single ZnT8A while only three who developed clinical T1D were detected ECL-ZnT8A. Interpretation: Majority of single ZnT8A positivity detected in screening by RBA were of low affinity with low T1D risk while ZnT8A detected by ECL assay were of high-affinity with high prediction for T1D development. Funding: JDRF, NIH Declaration of Interests: The authors declare no conflict of interest related to this study. Ethics Approval Statement: All subjects were provided written or electronic informed consent and all studies were approved by the University of Colorado Institutional Review Board.

The 3p21.31 genetic locus promotes progression to type 1 diabetes through the CCR2/CCL2 pathway

Multiple cross-sectional and longitudinal studies have shown that serum levels of the chemokine ligand 2 (CCL-2) are associated with type 1 diabetes (T1D), although the direction of effect differs. We assessed CCL-2 serum levels in a longitudinal cohort to clarify this association, combined with genetic data to elucidate the regulatory role of CCL-2 in T1D pathogenesis.The Diabetes Autoimmunity Study in the Young (DAISY) followed 310 subjects with high risk of developing T1D. Of these, 42 became persistently seropositive for islet autoantibodies but did not develop T1D (non-progressors); 48 did develop T1D (progressors). CCL-2 serum levels among the three study groups were compared using linear mixed models adjusting for age, sex, HLA genotype, and family history of T1D. Summary statistics were obtained from the CCL-2 protein quantitative trait loci (pQTL) and CCR2 expression QTL (eQTL) studies. The T1D fine mapping association data were provided by the Type 1 Diabetes Genetics Consortium (T1DGC).Serum CCL-2 levels were significantly lower in both progressors (p = 0.004) and non-progressors (p = 0.005), compared to controls. Two SNPs (rs1799988 and rs746492) in the 3p21.31 genetic locus, which includes the CCL-2 receptor, CCR2, were associated with increased CCR2 expression (p = 8.2e-5 and 5.2e-5, respectively), decreased CCL-2 serum level (p = 2.41e-9 and 6.21e-9, respectively), and increased risk of T1D (p = 7.9e-5 and 7.9e-5, respectively).The 3p21.31 genetic region is associated with developing T1D through regulatory control of the CCR2/CCL2 immune pathway.

Metabolomics-related nutrient patterns at seroconversion and risk of progression to type 1 diabetes.

Our aim was to elucidate the role of diet in type 1 diabetes (T1D) by examining combinations of nutrient intake in the progression from islet autoimmunity (IA) to T1D. We measured 2457 metabolites and dietary intake at the time of seroconversion in 132 IA-positive children in the prospective Diabetes Autoimmunity Study in the Young. IA was defined as the first of two consecutive visits positive for at least one autoantibody (insulin, GAD, IA-2, or ZnT8). By December 2018, 40 children progressed to T1D. Intakes of 38 nutrients were estimated from semiquantitative food frequency questionnaires. We tested the association of each metabolite with progression to T1D using multivariable Cox regression. Nutrient patterns that best explained variation in candidate metabolites were identified using reduced rank regression (RRR), and their association with progression to T1D was tested using Cox regression adjusting for age at seroconversion and high-risk HLA genotype. In stepwise selection, 22 nutrients significantly predicted at least two of the 13 most significant metabolites associated with progression to T1D, and were included in RRR. A nutrient pattern corresponding to intake lower in linoleic acid, niacin, and riboflavin, and higher in total sugars, explained 18% of metabolite variability. Children scoring higher on this metabolite-related nutrient pattern at seroconversion had increased risk for progressing to T1D (HR = 3.17, 95%CI = 1.42-7.05). Combinations of nutrient intake reflecting candidate metabolites are associated with increased risk of T1D, and may help focus dietary prevention efforts.

Gluten intake and risk of thyroid peroxidase autoantibodies in the Diabetes Autoimmunity Study In the Young (DAISY).

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. 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. 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). Neither the age of gluten introduction nor the amount of gluten consumed in early childhood is associated with risk of thyroid autoimmunity.

107-OR: Novel Genetic Risk Factors Influence Islet Autoimmunity Progression

Background: Type 1 diabetes (T1D) is determined by unknown environmental factors in genetically susceptible individuals. The design of most genome wide association studies of T1D involves comparison of cases (with varying duration of disease) with controls; hence, the genetic variants associated with T1D reflect current disease, ignoring variants that play a key role in the initiation of islet autoimmunity and the progression of subclinical disease. In this study, we focus on the genetic contribution to progression of islet autoimmunity using whole-genome sequencing in a collection of participants of the Diabetes AutoImmunity Study in the Young (DAISY). Methods: A total of 160 persistent islet autoantibody positive DAISY subjects were sequenced, including 87 subjects who progressed to T1D and 73 “non-progressors” over a mean of 11 years since seroconversion. Following whole genome sequence alignment, single nucleotide polymorphisms (SNPs) and small insertion/deletions (indels) were identified (∼6.8 million variants), and statistical analyses performed. Results: Genes with multiple SNPs associated with progression to T1D in subjects with islet autoimmunity (P &amp;lt; 8.5x10-8) did not overlap with known T1D risk loci; instead, four novel regions were identified - 1q21.3 (MRPS21-PRPF3), 2p25.2 (NRIR), 3q22.1 (COL6A6), and 20p12.1 (TASP1). Functional mapping of the associated SNPs within these risk loci indicates pathways critical for response to viral infections and response to interferon signaling contribute to progression to T1D once islet autoimmunity is initiated. Discussion: This study presents evidence that different genetic pathways may contribute to progression of islet autoimmunity from those identified once disease is established and support the need for follow-up studies to understand genetic risk factors that modulate progression of subclinical disease. Disclosure S. Onengut-Gumuscu: None. U. Paila: None. W. Chen: None. A. Ratan: None. Z. Zhu: None. A. Steck: None. B.I. Frohnert: None. K. Waugh: None. B. Webb-Robertson: None. J.M. Norris: None. L. Lange: None. M. Rewers: None. S.S. Rich: None.