ABSTRACTBackgroundSeveral risk factors for coronary artery disease (CAD) have been described, some of which are genetically determined. The use of a polygenic risk score (PRS) could improve CAD risk assessment, but predictive accuracy according to age and sex is not well established.MethodsA PRSCAD including the weighted effects of >1.14 million SNPs associated with CAD was calculated in UK Biobank (n=408,422), using LDPred. Cox regressions were performed, stratified by age quartiles and sex, for incident MI and mortality, with a median follow-up of 11.0 years. Improvement in risk prediction of MI was assessed by comparing PRSCAD to the pooled cohort equation with categorical net reclassification index using a 2% threshold (NRI0.02) and continuous NRI (NRI>0).ResultsFrom 7,746 incident MI cases and 393,725 controls, hazard ratio (HR) for MI reached 1.53 (95% CI [1.49-1.56], p=2.69e-296) per standard deviation (SD) increase of PRSCAD. PRSCAD was significantly associated with MI in both sexes, with a stronger association in men (interaction p=0.002), particularly in those aged between 40-51 years (HR=2.00, 95% CI [1.86-2.16], p=1.93e-72). This group showed the highest reclassification improvement, mainly driven by the up-classification of cases (NRI0.02=0.199, 95% CI [0.157-0.248] and NRI>0=0.602, 95% CI [0.525-0.683]). From 23,982 deaths, HR for mortality was 1.08 (95% CI [1.06-1.09], p=5.46e-30) per SD increase of PRSCAD, with a stronger association in men (interaction p=1.60e-6).ConclusionOur PRSCAD predicts MI incidence and all-cause mortality, especially in men aged between 40-51 years. PRS could optimize the identification and management of individuals at risk for CAD.
A polygenic risk score for coronary artery disease predicts early-onset myocardial infarction and mortality in men
