Genomic risk prediction of coronary artery disease in 480,000 adults: implications for primary prevention
File(s)
Published version
Author(s)
Type
Journal Article
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.
Date Issued
2018-10-16
Date Acceptance
2018-07-24
Citation
Journal of the American College of Cardiology, 2018, 72 (16), pp.1883-1893
ISSN
0735-1097
Publisher
Elsevier
Start Page
1883
End Page
1893
Journal / Book Title
Journal of the American College of Cardiology
Volume
72
Issue
16
Copyright Statement
© 2018 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/30309464
PII: S0735-1097(18)36949-3
Subjects
coronary artery disease
genomic risk prediction
primary prevention
Publication Status
Published
Coverage Spatial
United States
Date Publish Online
2018-10-08