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Fasting insulin (FI) is a heterogeneous trait with high variability between individuals and populations. Increased FI is associated with an increased risk of type 2 diabetes (T2D) and its complications, including coronary artery disease (CAD) and hypertension (HTN) . We hypothesize that we could use a genetic approach to cluster FI-associated variants, characterize the clusters in terms of insulin processes within the Mexican American Cardiovascular Disease Study (MACAD; N=821) , and test for association of polygenic scores (PS) created from these clusters with T2D, CAD and HTN in three cohorts: Mass General Brigham Biobank (MGBB; N=18,127) , Aspirin in Reducing Events in the Elderly (ASPREE; N=13,349) , and Framingham Heart Study (FHS; N=7,145) . We identified six clusters using a soft clustering approach with 446 FI-increasing genetic alleles and 27 FI-related traits. Associations in two of the clusters, allowed us to characterize them and show their impact on T2D and T2D-associated complications. The first cluster had alleles associated with increased subcutaneous and visceral adiposity and was characterized by reduced insulin sensitivity (from euglycemic clamp; P=0.02) , increased insulin secretion (from oral glucose tolerance test [OGTT]; P=0.04) , and increased insulin clearance (from euglycemic clamp; P=0.02) in MACAD. This cluster’s PS was associated with HTN (MGBB Odds ratio (OR) = 1.04, P=0.013) , T2D (MGBB OR = 1.04, P =0.001) and CAD (MGB OR=1.07, P =0.008; ASPREE OR=1.04, P =0.036) The second cluster had alleles associated with a lipodystrophy phenotype and was characterized by increased insulin secretion (from OGTT P =0.019) in MACAD. We observed associations of the PS with T2D (MGBB OR= 1.13, P =2.3x10-10) and HTN (MGBB OR = 1.06, P =0.001) which were replicated in ASPREE and FHS. Our results suggest the presence of two different FI-associated genetic domains and elucidate the deleterious mechanisms by which increased FI is associated with T2D and T2D complications. Disclosure M.Sevilla: None. M.O.Goodarzi: None. D.A.Dicorpo: None. J.I.Rotter: None. J.B.Meigs: Consultant; Quest Diagnostics. M.Udler: None. A.Manning: None. Funding UM1DK078616

Nontargeted metabolomics methods have increased potential to identify new disease biomarkers, but assessments of the additive information provided in large human cohorts by these less biased techniques are limited. To diversify our knowledge of diabetes associated metabolites, we leveraged a method that measures 305 targeted or “known” and 2,342 nontargeted or “unknown” compounds in fasting plasma samples from 2,750 participants (315 incident cases) in the Jackson Heart Study (JHS)—a community cohort of self-identified African Americans (AAs), who are underrepresented in omics studies. We found 307 unique compounds (82 known) associated with diabetes after adjusting for age and sex at a false discovery rate (FDR)

Objective: CHIP is an aging-related accumulation of somatic mutations in hematopoietic stem cells, leading to clonal expansion. CHIP presence has been implicated in elevated atherosclerotic heart disease (CHD) and all-cause mortality, but its association with incident T2D is unknown. We hypothesize CHIP is adversely associated with glycemic traits and T2D. Methods: We included N=16,054 participants in NHLBI Trans-omics for Precision Medicine (TOPMed), without prior T2D or chronic disease at blood draw. CHIP was derived from blood DNA whole genome sequencing using the GATK MuTECT2 somatic variant caller in pre-specified leukemogenic driver mutations. We estimated CHIP overall and candidate CHD-related mutations (DNMT3A, TET2, ASXL1, JAK2) in relation to baseline glycemic traits (fasting glucose, insulin, HOMA-IR) with linear regression. We evaluated CHIP with incident T2D using Cox regression to estimate hazard ratios and 95% confidence intervals (HR [CI]). Models adjusted for age, sex, body mass index, smoking, and family history of T2D. We combined cohort-specific estimates via random effects meta-analysis with inverse variance weighting. Results: CHIP was present in n=1,088 (7%) of participants. We observed 1,853 incident T2D cases over mean=10y follow-up. Baseline fasting glucose, insulin, and HOMA-IR did not differ by CHIP status. Participants with CHIP had a higher risk of incident T2D than those without CHIP (1.27 [1.08, 1.51]), with a significant dose-response per additional CHIP mutation (p-trend=0.005). Analyses of CHD-related CHIP vs. no CHIP mutations suggested associations with higher T2D risk for DNMT3A (1.21 [0.97, 1.51]) and TET2 (1.35 [0.93, 1.97]), and ASXL1 (1.92 [0.71, 5.13]), although analyses of individual mutations were underpowered. Conclusions: CHIP is associated with a higher T2D risk. This relationship may be unrelated to baseline glycemic traits. CHIP-T2D association suggests a potential role for CHD-related pathology in T2D. Disclosure D. K. Tobias: None. D. A. Dicorpo: None. B. M. Psaty: None. A. C. Morrison: None. V. S. Ramachandran: None. L. Cupples: None. L. Lange: None. A. Correa: None. C. L. Kooperberg: None. L. F. Tinker: None. B. V. Howard: None. A. Manning: Employee; Spouse/Partner; Emulate, Inc, Stock/Shareholder; Spouse/Partner; Invitae. A. Reiner: None. J. I. Rotter: None. J. M. Collins: None. J. B. Meigs: Consultant; Self; Quest Diagnostics. J. E. Manson: None. J. Wessel: Employee; Spouse/Partner; Eli Lilly and Company. K. E. Westerman: None. S. Raghavan: None. L. Raffield: None. J. Dupuis: None. A. Bick: None. P. Wu: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (U01DK078616 to J.B.M., J.D., D.A.D., P.W.), (U01DK105554 to J.D., D.A.D.)

The prevalence of type 2 diabetes is increasing in youth, particularly in certain ethnic groups, and studies have highlighted differences between youth- and adult-onset disease. However, its genetic determinants remain largely unexplored. To identify genetic variants predisposing to type 2 diabetes in youth, we formed ProDiGY, a multi-ethnic collaboration of the TODAY, SEARCH for Diabetes in Youth, and T2D-GENES studies, with 30young cases (mean age= 15.1 y ±2.8, 63% female, 22% white, 36% African American, 42% Hispanic) and 6061 diabetes-free adult controls (mean age = 54.2 y ±12.4; 57% female, 24% white, 18% African American, 58% Hispanic). After stratifying by self-reported and principal component-clustered ethnicity, we performed association analyses on 206,928 directly genotyped variants using a generalized linear mixed model using a genetic relationship matrix to account for population structure. We identified 5 genome-wide significant loci, including the novel locus rs13130484 in GNPDA2 (P= 1.4 ×10-8, odds ratio [OR]= 1.24), which has nominal association with type 2 diabetes in adults. Known loci identified in our analysis include rs4132670 in the well-known type 2 diabetes locus TCF7L2 (P= 4.2×10-13, OR 1.35) in high linkage disequilibrium with causal SNP rs7903146 (R2=0.83), rs11662368 near the obesity locus MC4R (P= 3.9×10-9, OR =1.31), rs11257655 in RN7SL232P (P= 5.7×10-12, OR= 1.33), and rs7075724 in CDC123 (P= 8.3×10-11, OR= 1.29); effect sizes are greater for these latter three loci than those found in adults (Pdiff= 8.2×10-5, 2.4×10-5, and 1.7×10-6, respectively). Secondary analysis with 856 diabetes-free youth controls demonstrated consistent direction of effect but no additional loci. In conclusion, we identified known and novel genetic loci predisposing to type 2 diabetes in youth. Our future analysis of ∼10 million variants holds the potential to uncover additional new type 2 diabetes susceptibility loci. Disclosure S. Srinivasan: None. J. Todd: None. L. Chen: None. J. Divers: None. S. Gidding: None. S. Chernausek: Advisory Panel; Self; Novo Nordisk Inc.. R. Gubitosi-Klug: None. M.M. Kelsey: Other Relationship; Self; Daiichi Sankyo Company, Limited, Merck Sharp & Dohme Corp.. R. Shah: None. M. Black: None. L.E. Wagenknecht: None. J.M. Mercader: None. A. Manning: None. J. Flannick: None. D. Dabelea: None. J.C. Florez: Consultant; Self; Intarcia Therapeutics, Inc.. Consultant; Spouse/Partner; Santen.