Abstract 9843: Dynamic Importance of Genomic and Nongenomic Risk Factors for Coronary Artery Disease Over the Life Course

Abstract

Introduction: Current cardiovascular risk models are limited by fixed window estimates of risk rather than lifetime trajectories. We create a novel framework to understand the time-varying profiles of genomic and non-genomic risk factors over the life span. Methods: We examine 325,948 individuals from the UK Biobank (UKB) (57% female, enrollment age 40-70 years, mean follow-up 11.9 years) with baseline clinical risk factors, composite Pooled Cohort Equations (PCE), and coronary artery disease (CAD) polygenic risk score (PRS). We compare Cox hazard ratios (HR) and the proportion of variation explained (PVE) at each age of enrollment. We extend analyses to a younger cohort of 3,821 individuals from the Framingham Health Study (FHS) Offspring Cohort, (51% female, enrollment ages 18-57, mean follow-up 35.1 years). Results: Results: HR and PVE of CAD PRS are greater early in life with HR 2.47, [95% CI 2.45-2.50] at age 40 to HR 1.67 [1.64,1.70] at age 70 in UKB; PVE of 7.8% to 2.3% in UKB. Parallel results were observed in FHS (Fig 1A-C) earlier in the life span. While the variation in lifetime risk increases with time, the HR for single risk factors estimated at each age are dynamic. The PCE, via inclusion of age, absorb much of this variation. Reclassification of intermediate 10-year PCE risk (7.5-19.9%) using PRS is most informative in younger individuals. In the UKB, the top-quintile of PRS, when compared to PCE alone, accurately predicts more individuals under age 55 (1108 versus 844) who ultimately develop CAD, but loses superiority over age 55 (Fig. 1D). Conclusions: Depending on when the question is asked, the HR of CAD of both genomic and non-genomic risk factors changes dramatically, with PRS demonstrating superiority early on. Our novel framework incorporates time-varying effects in portraying risk trajectory rather than fixed-window estimates. We show that polygenic scores also predict lifetime risk of disease early on rather than predicting only early-onset disease.