Year: 2016
Type: review
Study design: Observational Study
Abstract: AIMS: Genetics plays an important role in coronary heart disease (CHD) but the clinical utility of genomic risk scores (GRSs) relative to clinical risk scores, such as the Framingham Risk Score (FRS), is unclear. Our aim was to construct and externally validate a CHD GRS, in terms of lifetime CHD risk and relative to traditional clinical risk scores. METHODS AND RESULTS: We generated a GRS of 49 310 SNPs based on a CARDIoGRAMplusC4D Consortium meta-analysis of CHD, then independently tested it using five prospective population cohorts (three FINRISK cohorts, combined n = 12 676, 757 incident CHD events; two Framingham Heart Study cohorts (FHS), combined n = 3406, 587 incident CHD events). The GRS was associated with incident CHD (FINRISK HR = 1.74, 95% confidence interval (CI) 1.61-1.86 per S.D. of GRS; Framingham HR = 1.28, 95% CI 1.18-1.38), and was largely unchanged by adjustment for known risk factors, including family history. Integration of the GRS with the FRS or ACC/AHA13 scores improved the 10 years risk prediction (meta-analysis C-index: +1.5-1.6%, P < 0.001), particularly for individuals ≥60 years old (meta-analysis C-index: +4.6-5.1%, P < 0.001). Importantly, the GRS captured substantially different trajectories of absolute risk, with men in the top 20% of attaining 10% cumulative CHD risk 12-18 y earlier than those in the bottom 20%. High genomic risk was partially compensated for by low systolic blood pressure, low cholesterol level, and non-smoking. CONCLUSIONS: A GRS based on a large number of SNPs improves CHD risk prediction and encodes different trajectories of lifetime risk not captured by traditional clinical risk scores.
Source: European Heart Journal
Institutions: The University of Melbourne, Finnish Institute for Health and Welfare, University of Helsinki, Institute for Molecular Medicine Finland, German Centre for Cardiovascular Research, Deutsches Herzzentrum München, Technical University of Munich, Erasmus MC, Broad Institute, Harvard University, Massachusetts General Hospital, Massachusetts Institute of Technology, University of Leicester, Glenfield Hospital, National Institute for Health and Care Research, NIHR Leicester Cardiovascular Biomedical Research Unit, Wellcome Sanger Institute
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: bronze
Funders: American Heart Association, Foundation for Cardiovascular Research, Wellcome Trust, Broad Institute, National Institute for Health and Care Research, British Heart Foundation, European Commission, National Heart Foundation of Australia, Academy of Finland, NordForsk, Sydäntutkimussäätiö, National Institutes of Health, Medical Research Council, National Health and Medical Research Council, National Heart, Lung, and Blood Institute, National Center for Research Resources
Awards: G119964413, META-DAC - Managing Ethico-social and Technical issues and Administration of Data Access Committee, WTCCC2 core activities, G2473961061, G2583510894, G2973790809, A Genome-wide Association Study for Early-Onset Myocardial Infarction, Using systems biology to model and predict human diseases, G3207356259, G3216122662, NIHR Senior Investigator Award, G378987182, G393177772, G3942382998, Biobank Standardisation and Harmonisation for Research Excellence in the European Union, Large-Scale Multi-Omic Analysis and Risk Prediction of Complex Human Disease, Integrative genomics and prediction of cardiovascular disease, G5702163051, G7221506883, The Productive Robot Apprentice, G8311891658, G8653388093, The genetics of weight, BMI, adiposity and obesity
OpenAlex ID: W2521147375