Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations

Tian Ge, Marguerite R. Irvin, Amit Patki, Vinodh Srinivasasainagendra, Yen Feng Lin, Hemant K. Tiwari, Nicole D. Armstrong, Barbara Benoit, Chia Yen Chen, Karmel W. Choi, James J. Cimino, Brittney H. Davis, Ozan Dikilitas, Bethany Etheridge, Yen Chen Anne Feng, Vivian Gainer, Hailiang Huang, Gail P. Jarvik, Christopher Kachulis, Eimear E. KennyAtlas Khan, Krzysztof Kiryluk, Leah Kottyan, Iftikhar J. Kullo, Christoph Lange, Niall Lennon, Aaron Leong, Edyta Malolepsza, Ayme D. Miles, Shawn Murphy, Bahram Namjou, Renuka Narayan, Mark J. O’Connor, Jennifer A. Pacheco, Emma Perez, Laura J. Rasmussen-Torvik, Elisabeth A. Rosenthal, Daniel Schaid, Maria Stamou, Miriam S. Udler, Wei Qi Wei, Scott T. Weiss, Maggie C.Y. Ng, Jordan W. Smoller, Matthew S. Lebo, James B. Meigs, Nita A. Limdi, Elizabeth W. Karlson

Research output: Contribution to journalArticlepeer-review

26 Scopus citations


Background: Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for equitable deployment of PRS to clinical practice that benefits global populations. Methods: We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts. Results: The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined. The top 2% of the PRS distribution can identify individuals with an approximately 2.5–4.5-fold of increase in T2D risk, which corresponds to the increased risk of T2D for first-degree relatives. The post hoc ancestry adjustment method eliminated major distributional differences in the PRS across ancestries without compromising its predictive performance. Conclusions: By integrating T2D GWAS from multiple populations, we developed and validated a trans-ancestry PRS, and demonstrated its potential as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.

Original languageEnglish
Article number70
JournalGenome Medicine
Issue number1
StatePublished - Dec 2022


  • Clinical implementation
  • Diverse populations
  • Polygenic risk score
  • Type 2 diabetes


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