Polygenic score informed by genome-wide association studies of multiple ancestries and related traits improves risk prediction for coronary artery disease

Abstract

AbstractAccurate stratification of coronary artery disease (CAD) risk remains a critical need. A new polygenic score (GPSMult) incorporates CAD genome-wide association data across five ancestries (>269,000 cases, >1,178,000 controls) with genetic association data for ten CAD risk factors. GPSMultassociates with an OR/SD 2.14, (95%CI:2.10-2.19,P<0.001) for prevalent CAD and HR/SD 1.73 (95%CI 1.70-1.76,P<0.001) for incident CAD. When compared with the previously published GPS2018in external datasets, GPSMultdemonstrated 73%, 46%, and 113% increase in effect size for individuals of African, European, and South Asian ancestry, respectively, and significantly outperformed recently published CAD polygenic scores. GPSMultidentifies individuals with CAD risk extremes, including the top 3% of the population at equivalent risk for a new CAD event as those with prior CAD having a second event. Integrating GPSMultwith the Pooled Cohort Equations results in 7.0% [95%CI:5.9%-8.2%,P<0.001] net reclassification improvement at the 7.5% threshold. Large-scale integration genetic association data for CAD and related traits from diverse populations meaningfully improves polygenic risk prediction.