Genome-Wide Polygenic Score, Clinical Risk Factors, and Long-Term Trajectories of Coronary Artery Disease

Abstract

Objective: To determine the relationship of a genome-wide polygenic score for coronary artery disease (GPS CAD ) with lifetime trajectories of CAD risk, directly compare its predictive capacity to traditional risk factors, and assess its interplay with the Pooled Cohort Equations (PCE) clinical risk estimator. Approach and Results: We studied GPS CAD in 28 556 middle-aged participants of the Malmö Diet and Cancer Study, of whom 4122 (14.4%) developed CAD over a median follow-up of 21.3 years. A pronounced gradient in lifetime risk of CAD was observed—16% for those in the lowest GPS CAD decile to 48% in the highest. We evaluated the discriminative capacity of the GPS CAD —as assessed by change in the C-statistic from a baseline model including age and sex—among 5685 individuals with PCE risk estimates available. The increment for the GPS CAD (+0.045, P <0.001) was higher than for any of 11 traditional risk factors (range +0.007 to +0.032). Minimal correlation was observed between GPS CAD and 10-year risk defined by the PCE ( r =0.03), and addition of GPS CAD improved the C-statistic of the PCE model by 0.026. A significant gradient in lifetime risk was observed for the GPS CAD , even among individuals within a given PCE clinical risk stratum. We replicated key findings—noting strikingly consistent results—in 325 003 participants of the UK Biobank. Conclusions: GPS CAD —a risk estimator available from birth—stratifies individuals into varying trajectories of clinical risk for CAD. Implementation of GPS CAD may enable identification of high-risk individuals early in life, decades in advance of manifest risk factors or disease.