Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults: Implications for Primary Prevention.
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Authors
Abraham, Gad
Nelson, Christopher P
Wood, Angela M
Sweeting, Michael J
Dudbridge, Frank
Lai, Florence Y
Brozynska, Marta
Wang, Tingting
Ye, Shu
Webb, Thomas R
Rutter, Martin K
Tzoulaki, Ioanna
Patel, Riyaz S
Loos, Ruth JF
Keavney, Bernard
Hemingway, Harry
Thompson, John
Watkins, Hugh
Deloukas, Panos
Butterworth, Adam S
Samani, Nilesh J
UK Biobank CardioMetabolic Consortium CHD Working Group
Publication Date
2018-10-16Journal Title
J Am Coll Cardiol
ISSN
0735-1097
Publisher
Elsevier BV
Volume
72
Issue
16
Pages
1883-1893
Language
eng
Type
Article
Physical Medium
Print
Metadata
Show full item recordCitation
Inouye, M., Abraham, G., Nelson, C. P., Wood, A. M., Sweeting, M. J., Dudbridge, F., Lai, F. Y., et al. (2018). Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults: Implications for Primary Prevention.. J Am Coll Cardiol, 72 (16), 1883-1893. https://doi.org/10.1016/j.jacc.2018.07.079
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.
Keywords
UK Biobank CardioMetabolic Consortium CHD Working Group, Humans, Mass Screening, Risk Assessment, Risk Factors, Predictive Value of Tests, Genomics, Primary Prevention, Multifactorial Inheritance, Research Design, Middle Aged, Female, Male, Coronary Artery Disease, Genome-Wide Association Study, United Kingdom
Sponsorship
British Heart Foundation (None)
British Heart Foundation (CH/12/2/29428)
Medical Research Council (MR/L003120/1)
Medical Research Council (G0701619)
Identifiers
External DOI: https://doi.org/10.1016/j.jacc.2018.07.079
This record's URL: https://www.repository.cam.ac.uk/handle/1810/285844
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