Interaction Between ECG and Genetic Markers of Coronary Artery Disease

Coronary artery disease (CAD) is the main contributor to cardiovascular mortality in developed countries, making accurate diagnosis of utmost importance. We developed risk scores to assess CAD risk in a population without known cardiovascular disease by combining ECG and a genetic risk score (GRS) for CAD. We analysed data in 52,260 individuals in the UK Biobank study. ECG indices included heart rate, PR, QRS, QT and T-peak-to-T-end intervals, while we built the GRS from publicly available genome-wide association results for CAD that were derived in an independent population. In a training set (N = 39,195), the indices with the strongest CAD prognostic impact were the PR and QT intervals, and the GRS. When combined together into a Multivariate model, both the ECG markers and the GRS were independently associated with CAD. In an independent test set (N = 13,065), we then built three risk scores based on (1) ECG markers, (2) genetic data, and (3) a combination of ECG and genetic data, respectively. The hazard ratio (95% confidence interval) for CAD comparing high versus low-risk individuals was 6.5 (5.1 - 8.3),8.4 (6.4 - 10.8) and 8.4 (6.5 - 10.8) for the three risk scores, respectively. In conclusion, the inclusion of genetic markers into risk scores with ECG markers independently contributes to CAD risk prediction in a large population of individuals without known cardiovascular disease.