Genetic risk score for coronary artery calcification and its predictive ability for coronary artery disease

Abstract

Aim: The modest added predictive value of the existing genetic risk scores (GRSs) for coronary artery disease (CAD) could be partly due to missing genetic components, hidden in the genetic architecture of intermediate phenotypes such as coronary artery calcification (CAC). In this study, we investigated the predictive ability of CAC GRS for CAD. Materials and methods: We investigated the association of CAC GRSs with CAD and coronary calcification among the participants in the Ludwigshafen Risk and Cardiovascular Health study (LURIC) (n = 2742), the Tampere Vascular Study (TVS) (n = 133), and the Tampere Sudden Death Study (TSDS) (n = 660) using summary data from the largest multi-ancestry GWAS meta-analysis of CAC to date. Added predictive value of the CAC GRS over the traditional CVD risk factors as well as metaGRS, a GRS for CAD constructed with 1.7 million genetic variants, was tested with standard train–test machine learning approach using the LURIC data, which had the largest sample size. Results: CAC GRS was significantly associated with CAD in LURIC (OR=1.41, 95 % CI [1.28–1.55]), TVS (OR=1.79, 95 % CI [1.05–3.21]) as well as in TSDS (OR=4.20, 95 % CI [1.74–10.52]). CAC GRS showed strong association with calcification areas in left (OR=1.78, 95 % CI [1.16–2.74]) and right (OR=1.71, 95 % CI [1.98–2.67]) coronary arteries. There was statistically significant added predictive value of the CAC GRS for CAD over the used traditional CVD risk factors (AUC 0.734 vs 0.717, p-value = 0.02). Furthermore, CAC GRS improved the prediction accuracy for CAD when combined with metaGRS. Conclusions: This study showed that CAC GRS is a new risk marker for CAD in three European cohorts, with added predictive value over the traditional CVD risk factors.