medRxivGenetic & Genomic MedicinePreprint
Type 2 diabetes polygenic risk score demonstrates context-dependent effects and associations with type 2 diabetes-related risk factors and complications across diverse populations
Boya GuoiD, Yanwei CaiiD, Daeeun KimiD, Roelof A. J. SmitiD, Zhe WangiD, Kruthika Raman IyeriD, Austin T. HilliardiD, Jeffrey HaessleriD, Ran TaoiD, K. Alaine BroadawayiD, Yujie WangiD, Nikita V. PozdeyeviD, Frederik Filip StægeriD, Chaojie YangiD, Brett R. VanderwerffiD, Amit PatkiiD, Lauren A. StalbowiD, Meng Hsuan LiniD, Nicholas M. RafaelsiD, Jonathan ShorttiD, Laura Wiley, Maggie A. StanislawskiiD, Jack W. PatteeiD, Lea Karatheodoris DavisiD, Péter StraubiD, , Burcu F. DarstiD
Abstract
Polygenic risk scores (PRS) hold prognostic value for identifying individuals at higher risk of type 2 diabetes (T2D). However, further characterization is needed to understand the generalizability of T2D PRS in diverse populations across various contexts. We characterized a multi-ancestry T2D PRS among 244,637 cases and 637,891 controls across eight populations from the Population Architecture Genomics and Epidemiology (PAGE) Study and 13 additional biobanks and cohorts. PRS performance was context dependent, with better performance in those who were younger, male, with a family history of T2D, without hypertension, and not obese or overweight. Additionally, the PRS was associated with various diabetes-related cardiometabolic traits and T2D complications, suggesting its utility for stratifying risk of complications and identifying shared genetic architecture between T2D and other diseases. These findings highlight the need to account for context when evaluating PRS as a tool for T2D risk prognostication and potentially generalizable associations of T2D PRS with diabetes-related traits despite differential performance in T2D prediction across diverse populations.
- organism: human
- assay: GWAS summary statistics
- research focus: polygenic risk
- approach: statistical model
- Citations
- 4
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