TIGP (BIO)—Polygenic Risk Prediction at Scale: Methods, Equity, and Public Health Applications

Abstract

The genomics era has transformed our understanding of how genetic variation shapes human health, revealing the extensive polygenicity and pleiotropy underlying common complex traits and diseases. Alongside advances in epidemiological prediction modeling, innovative methods have emerged that harness polygenic architecture to estimate individual disease risk from their unique genetic profiles. In this talk, I will highlight our collaborative work developing polygenic risk scores (PRS) using single- and cross-ancestry information, discuss how these models can be applied to stratify risk for disease onset and treatment response, and quantify the attributable impact of PRS on disease burden and healthcare utilization at the population and individual levels. I will also address the public health potential—and ongoing challenges—of polygenic risk prediction in the context of large-scale biobank studies.

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