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Interaction between ECG and Genetic Markers of Coronary Artery Disease

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. Green open access

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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.

Type: Proceedings paper
Title: Interaction between ECG and Genetic Markers of Coronary Artery Disease
Event: 2020 Computing in Cardiology (CinC 2020)
Open access status: An open access version is available from UCL Discovery
DOI: 10.22489/CinC.2020.478
Publisher version: https://doi.org/10.22489/CinC.2020.478
Language: English
Additional information: This is an Open Access article published under a Creative Commons Attribution 4.0 International (CC BY 4.0) Licence (https://creativecommons.org/licenses/by/4.0/).
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Clinical Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Population Science and Experimental Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Population Science and Experimental Medicine > MRC Unit for Lifelong Hlth and Ageing
URI: https://discovery.ucl.ac.uk/id/eprint/10123267
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