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PREDICTION OF CORONARY ARTERY DISEASE AND MAJOR ADVERSE CARDIOVASCULAR EVENTS USING CLINICAL AND GENETIC RISK SCORES FOR CARDIOVASCULAR RISK FACTORS
Abstract
Background and Aims
Risk stratification of coronary artery disease (CAD) and major adverse cardiovascular events (MACE) remains suboptimal. CAD genetic risk scores (GRSs) predict risk independently from the QRISK3 score. We assessed the added value of GRSs for cardiovascular traits (CV GRSs).
Methods
We used data from 379,581 participants in the UK Biobank without known cardiovascular conditions (follow-up 11.3 years, 3.3% CAD cases, 5.2% MACE cases). In a training subset (50%) we built (1) QRISK3; (2) QRISK3 and an established CAD GRS; and (3) QRISK3, the CAD GRS and the CV GRSs. In an independent subset (50%), we evaluated their performance using the area under the curve (AUC) and odds ratio (ORs). We, then, repeated the analyses with (4) CAD GRS; and (5) CAD GRS and CV GRSs.
Results
For CAD, the combination of QRISK3 and the CAD GRS had a better performance than QRISK3 alone (AUC of 0.767 versus 0.756, P = 3.0x10-7, OR of 5.47 versus 4.82). Adding the CV GRSs did not significantly improve risk stratification. When only looking at genetic information, the combination of CV GRSs and the CAD GRS had a better performance than the CAD GRS alone (AUC of 0.635 versus 0.624, P = 1.4x10-13, OR of 2.17 versus 2.07). Similar results were obtained for MACE.
Conclusions
The inclusion of CV GRSs to QRISK3 and an established CAD GRS does not improve CAD or MACE risk stratification. However, their combination only with the CAD GRS increases prediction performance indicating potential use before the advanced development of conventional CV risk factors.