1263-OR: Genetic Subtyping of Type 2 Diabetes Using Partitioned Polygenic Scores within the Definition, Etiology, Function: Integration to Enhance Type 2 Diabetes Treatment (DEFINE-T2D) Consortium

Introduction and Objective: T2D is a heterogeneous disease involving defects in multiple metabolic processes, which could be assessed by partitioned pathway-specific polygenic scores (pPS) developed from clustering T2D GWAS lead variants based on associations with related cardiometabolic traits. Here, we demonstrate the use of T2D pPS to identify T2D patient subgroups with distinct clinical features and outcomes. Methods: We calculated standardized values of 7 T2D pPS (beta.cell.1, beta.cell.2, lipodystrophy.1, lipodystrophy.2, hyper.insulin, proinsulin, and obesity) in 29,887 US whites (All of Us, BioVU, MGBB) and 2,490 US Hispanics (SOL) with T2D. In each cohort, we assessed association of pPS with cardiometabolic traits adjusted for age, sex, BMI and principal components. We grouped individuals by k-means consensus clustering based on their pPS profiles, and meta-analyzed group-specific association with metabolic traits and outcomes including cardiovascular disease, diabetic kidney disease and diabetic retinopathy (DR). Results: The associations of pPSs with respective cardiometabolic traits were consistent with previous findings (P<0.0007). We identified 4 genetically anchored T2D subgroups with differential metabolic traits and outcomes, of which three subgroups replicate across all cohorts. Subgroup 1, characterized by lower beta.cell and lipodystrophy pPSs was associated with lower HbA1c, higher BMI, and reduced risk for DR. Subgroup 2, characterized by higher beta.cell and lipodystrophy pPSs was associated with higher HbA1c, lower BMI and HDL-C. Subgroup 3, characterized by higher beta.cell but lower lipodystrophy pPSs was associated with lower BMI, higher HDL-C, and higher risk for DR (β estimate=-0.21 to 0.21, P<0.0036). Conclusion: This study demonstrates the utility of pPS to subgroup individuals with T2D based on genetic profiles representing their underlying disease mechanisms. Disclosure J. Kim: None. K. Smith: None. P. Wu: None. X. Zhong: None. M.M. Shuey: None. F. Hsu: None. E. Gamazon: None. J.I. Rotter: None. M. Udler: Advisory Panel; Ended; Novo Nordisk. Research Support; Current; Novo Nordisk. Q. Qi: None. J. Mercader: None. M.C. Ng: None. Funding The National Institute of Diabetes and Digestive and Kidney Diseases (U01DK140757, U01DK140761, U01DK140778, U01DK140952)