Genomic risk prediction of coronary artery disease in nearly 500,000 adults: implications for early screening and primary prevention

Author:

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 Ioanna,Patel Riyaz S.,Loos Ruth J.F.,Keavney Bernard,Hemingway Harry,Thompson John,Watkins Hugh,Deloukas Panos,Angelantonio Emanuele Di,Butterworth Adam S.,Danesh John,Samani Nilesh J.,

Abstract

AbstractBackgroundCoronary artery disease (CAD) has substantial heritability and a polygenic architecture; however, genomic risk scores have not yet leveraged the totality of genetic information available nor been externally tested at population-scale to show potential utility in primary prevention.MethodsUsing 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, individually and in combination with available conventional risk factors, in 22,242 CAD cases and 460,387 non-cases from UK Biobank.FindingsIn UK Biobank, a standard deviation increase in metaGRS had a hazard ratio (HR) of 1.71 (95% CI 1.68–1.73) for CAD, greater than any other externally tested genetic risk score. Individuals in the top 20% of the metaGRS distribution had a HR of 4.17 (95% CI 3.97–4.38) compared with those in the bottom 20%. The metaGRS had higher C-index (C=0.623, 95% CI 0.615–0.631) for incident CAD than any of four conventional factors (smoking, diabetes, hypertension, and body mass index), and addition of the metaGRS to a model of conventional risk factors increased C-index by 3.7%. In individuals on lipid-lowering or anti-hypertensive medications at recruitment, metaGRS hazard for incident CAD was significantly but only partially attenuated with HR of 2.83 (95% CI 2.61– 3.07) between the top and bottom 20% of the metaGRS distribution.InterpretationRecent genetic association studies have yielded enough information to meaningfully stratify individuals using the metaGRS for CAD risk in both early and later life, thus enabling targeted primary intervention in combination with conventional risk factors. The metaGRS effect was partially attenuated by lipid and blood pressure-lowering medication, however other prevention strategies will be required to fully benefit from earlier genomic risk stratification.FundingNational Health and Medical Research Council of Australia, British Heart Foundation, Australian Heart Foundation.

Publisher

Cold Spring Harbor Laboratory

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