Abstract
BACKGROUND: Coronary artery disease (CAD) risk traditionally has been assessed using clinical risk factors. We evaluated whether molecular genetic markers for CAD risk could add information to traditional variables. METHODS: We developed a false discovery rate 267-marker genetic risk score (FDR(267)) from markers that were significantly associated with CAD in the UK Biobank cohort meta-analysis. FDR(267) was tested in the Atherosclerosis Risk in Communities cohort using logistic regression and Cox proportional hazards analyses in the European and African American groups. RESULTS: Our genetic risk score (FDR(267)) was associated with a 1.45 (95% confidence interval, 1.39-1.51) increase in odds ratio and a 1.32 (95% confidence interval, 1.26-1.38) increase in hazard ratio per standard deviation of the score. The score modestly improved the area under the curve (AUC) statistic when added to a clinical model (ΔAUC = 0.0112, P = 0.0002). FDR(267) predicted incident CAD (C-index = 0.60), although it did not improve on clinical risk factors (ΔAUC = 0.0159, P = 0.0965). Individuals in the top quintile of FDR(267) genetic risk were at approximately 2-fold increased risk compared with the bottom quintile, which is comparable to risk associated with self-reported family history. The performance of FDR(267) was less robust in the African American sample. CONCLUSIONS: FDR(267) is significantly associated with CAD in the European sample, with an effect size comparable to self-reported family history. FDR(267) discriminated between individuals with and without CAD, but did not improve CAD risk prediction over clinical variables. FDR(267) was less predictive of CAD risk in African Americans.