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. 2021 Dec;14(6):e003452.
doi: 10.1161/CIRCGEN.121.003452. Epub 2021 Oct 21.

Polygenic Risk Score for Coronary Artery Disease Improves the Prediction of Early-Onset Myocardial Infarction and Mortality in Men

Hasanga D Manikpurage  1 , Aida Eslami  1   2 , Nicolas Perrot  1 , Zhonglin Li  1 , Christian Couture  1 , Patrick Mathieu  1   3 , Yohan Bossé  1   4 , Benoit J Arsenault  1   5 , Sébastien Thériault  1   6
Affiliations

Polygenic Risk Score for Coronary Artery Disease Improves the Prediction of Early-Onset Myocardial Infarction and Mortality in Men

Hasanga D Manikpurage et al. Circ Genom Precis Med. 2021 Dec.

Abstract

Background: Several 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.

Methods: A PRSCAD including the weighted effects of >1.14 million single nucleotide polymorphisms 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 myocardial infarction (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).

Results: From 7746 incident MI cases and 393 725 controls, hazard ratio for MI reached 1.53 (95% CI, 1.49-1.56; P=2.69×10-296) per 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 and 51 years (hazard ratio, 2.00 [95% CI, 1.86-2.16], P=1.93×10-72). 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, hazard ratio for mortality was 1.08 (95% CI, 1.06-1.09; P=5.46×10-30) per SD increase of PRSCAD, with a stronger association in men (interaction P=1.60×10-6).

Conclusions: Our PRSCAD predicts MI incidence and all-cause mortality, especially in men aged between 40 and 51 years. PRS could optimize the identification and management of individuals at risk for CAD.

Keywords: coronary artery disease; genetics; incidence; mortality; myocardial infarction; risk assessment; risk factors.

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