Journal article
Polygenic risk scores in cardiovascular risk prediction: A cohort study and modelling analyses
Luanluan Sun, Lisa Pennells, Stephen Kaptoge, Christopher P Nelson, Scott C Ritchie, Gad Abraham, Matthew Arnold, Steven Bell, Thomas Bolton, Stephen Burgess, Frank Dudbridge, Qi Guo, Eleni Sofianopoulou, David Stevens, John R Thompson, Adam S Butterworth, Angela Wood, John Danesh, Nilesh J Samani, Michael Inouye Show all
PLOS MEDICINE | PUBLIC LIBRARY SCIENCE | Published : 2021
Abstract
BACKGROUND: Polygenic risk scores (PRSs) can stratify populations into cardiovascular disease (CVD) risk groups. We aimed to quantify the potential advantage of adding information on PRSs to conventional risk factors in the primary prevention of CVD. METHODS AND FINDINGS: Using data from UK Biobank on 306,654 individuals without a history of CVD and not on lipid-lowering treatments (mean age [SD]: 56.0 [8.0] years; females: 57%; median follow-up: 8.1 years), we calculated measures of risk discrimination and reclassification upon addition of PRSs to risk factors in a conventional risk prediction model (i.e., age, sex, systolic blood pressure, smoking status, history of diabetes, and total and..
View full abstractGrants
Awarded by UK Medical Research Council
Awarded by British Heart Foundation
Awarded by British Heart Foundation Programme Grant
Awarded by NIHR Blood and Transplant Research Unit in Donor Health and Genomics
Awarded by MRC
Funding Acknowledgements
This work was supported by core funding from the UK Medical Research Council (MR/L003120/1), the British Heart Foundation (RG/13/13/30194; RG/18/13/33946), and the National Institute for Health Research (NIHR) (Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust and NIHR Leicester Biomedical Research Centre). This work was supported by Health Data Research UK, which is funded by the the UK Medical Research Council, the Engineering and Physical Sciences Research Council, the Economic and Social Research Council, the Department of Health and Social Care (England), the Chief Scientist Office of the Scottish Government Health and Social Care Directorates, the Health and Social Care Research and Development Division (Welsh Government), the Public Health Agency (Northern Ireland), the British Heart Foundation, and Wellcome. Luanluan Sun, Lisa Pennells, Stephen Kaptoge, and Matthew Arnold are funded by a British Heart Foundation Programme Grant (RG/18/13/33946). Christopher P. Nelson is funded by a British Heart Foundation Grant (SP/16/4/32697). Scott Ritchie, Mike Inouye, and Stephen Burgess are funded by the National Institute for Health Research (Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust). David Stevens was funded by the National Institute for Health Research (Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust). Thomas Bolton is funded by the NIHR Blood and Transplant Research Unit in Donor Health and Genomics (NIHR BTRU-2014-10024). Steven Bell was funded by the NIHR Blood and Transplant Research Unit in Donor Health and Genomics (NIHR BTRU-2014-10024). Angela Wood is supported by a BHF-Turing Cardiovascular Data Science Award and by the EC-Innovative Medicines Initiative (BigData@Heart).Professor John Danesh holds a British Heart Foundation Professorship and a National Institute for Health Research Senior Investigator Award.