240-OR: Combining Type 2 Diabetes Polygenic Scores Improves Prediction in 36,000 European and Non-European Participants in the Partners Healthcare Biobank

Abstract

Polygenic scores constructed by the aggregation of effect sizes of associated genetic variants have been shown to predict type 2 diabetes (T2D). Polygenic scores can be defined as “restricted-to-significant polygenic scores” (rsPS), and “globally expanded polygenic scores” (gePS), which can include millions of variants beyond those that are genome-wide significant. Most polygenic scores have been generated based on genome-wide association studies (GWAS) conducted predominantly in participants of European ancestry (EU); how these polygenic scores perform in non-European individuals in the healthcare system has not been thoroughly evaluated. We applied the rsPS and gePS for T2D in 30,240 EU participants, 3,029 Latinos (LA), and 2,201 African Americans (AA) from the Partners HealthCare Biobank, which maintains blood and DNA samples from patients seen at Partners HealthCare-affiliated hospitals in Boston. We compared rsPS based on the DIAMANTE consortium meta-analysis, with 398 variants (rsPS_398), rsPS based on the latest Million Veterans Program meta-analysis, with 682 variants (rsPS_682), and a gePS based on ldpred, including 6.9M variants adjusted for their effects based on linkage disequilibrium. rsPS_682 was most strongly associated with T2D in all ancestries (OR per SD in EU=1.73 p=7×10-142, OR per SD in LA =1.88, p=7×10-19, OR per SD in AA =1.47, p=1×10-8 compared to the other polygenic scores. We observed that rsPS_682 and the gePS provided both complementary information, and that combining them into the model improved the prediction in all ancestries, with 16%, 22%, and 16% increase in accuracy in EU, LA, and AA, respectively. We show the advantage of combining rsPS and gePS to improve prediction of T2D in multi-ethnic populations within a healthcare system. The results suggest that larger and multi-ethnic T2D GWAS are needed to avoid major health disparities. Disclosure J.M. Mercader: None. J.C. Florez: Advisory Panel; Self; Doris Duke Charitable Foundation. Other Relationship; Self; Novo Nordisk Inc., Park Street School. A. Leong: None. V. Kaur: None. M. Udler: None. J.B. Meigs: Consultant; Self; Quest Diagnostics. B. Porneala: None. Funding American Diabetes Association (1-19-ICTS-068 to J.M.M.)