Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/43034
Title: Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults: Implications for Primary Prevention.
Authors: Inouye, Michael
Abraham, Gad
Nelson, Christopher P.
Wood, Angela M.
Sweeting, Michael J.
Dudbridge, Frank
Lai, Florence Y.
Kaptoge, Stephen
Brozynska, Marta
Wang, Tingting
Ye, Shu
Webb, Thomas R.
Rutter, Martin K.
Tzoulaki, Ionna
Patel, Riyaz S.
Loos, Ruth J. F.
Keavney, Bernard
Hemingway, Harry
Thompson, John
Watkins, Hugh
Deloukas, Panos
Di Angelantonio, Emanuele
Butterworth, Adam S.
Danesh, John
Samani, Nilesh J.
UK Biobank CardioMetabolic Consortium CHD Working Group
First Published: 8-Oct-2018
Publisher: Elsevier for American College of Cardiology
Citation: Journal of the American College of Cardiology, 2018, 72 (16), pp. 1883-1893
Abstract: BACKGROUND: Coronary artery disease (CAD) has substantial heritability and a polygenic architecture. However, the potential of genomic risk scores to help predict CAD outcomes has not been evaluated comprehensively, because available studies have involved limited genomic scope and limited sample sizes. OBJECTIVES: This study sought to construct a genomic risk score for CAD and to estimate its potential as a screening tool for primary prevention. METHODS: Using a meta-analytic approach to combine large-scale, genome-wide, and targeted genetic association data, we developed a new genomic risk score for CAD (metaGRS) consisting of 1.7 million genetic variants. We externally tested metaGRS, both by itself and in combination with available data on conventional risk factors, in 22,242 CAD cases and 460,387 noncases from the UK Biobank. RESULTS: The hazard ratio (HR) for CAD was 1.71 (95% confidence interval [CI]: 1.68 to 1.73) per SD increase in metaGRS, an association larger than any other externally tested genetic risk score previously published. The metaGRS stratified individuals into significantly different life course trajectories of CAD risk, with those in the top 20% of metaGRS distribution having an HR of 4.17 (95% CI: 3.97 to 4.38) compared with those in the bottom 20%. The corresponding HR was 2.83 (95% CI: 2.61 to 3.07) among individuals on lipid-lowering or antihypertensive medications. The metaGRS had a higher C-index (C = 0.623; 95% CI: 0.615 to 0.631) for incident CAD than any of 6 conventional factors (smoking, diabetes, hypertension, body mass index, self-reported high cholesterol, and family history). For men in the top 20% of metaGRS with >2 conventional factors, 10% cumulative risk of CAD was reached by 48 years of age. CONCLUSIONS: The genomic score developed and evaluated here substantially advances the concept of using genomic information to stratify individuals with different trajectories of CAD risk and highlights the potential for genomic screening in early life to complement conventional risk prediction.
DOI Link: 10.1016/j.jacc.2018.07.079
ISSN: 0735-1097
eISSN: 1558-3597
Links: https://www.sciencedirect.com/science/article/pii/S0735109718369493?via%3Dihub
http://hdl.handle.net/2381/43034
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © the authors, 2018. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Appears in Collections:Published Articles, Dept. of Cardiovascular Sciences

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