Ramírez, J;
Van Duijvenboden, S;
Young, WJ;
Tinker, A;
Lambiase, PD;
Munroe, PB;
Orini, M;
(2020)
Interaction between ECG and Genetic Markers of Coronary Artery Disease.
In:
Proceedings of 2020 Computing in Cardiology (CinC 2020).
Computing in Cardiology (CinC): Rimini, Italy.
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Abstract
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.
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