Using polygenic risk scores for prioritising individuals at greatest need of a CVD risk assessment

Background To provide quantitative evidence of the use of polygenic risk scores (PRS) for systematically identifying individuals for invitation for full formal cardiovascular disease (CVD) risk assessment. Methods 108,685 participants aged 40-69, with measured biomarkers, linked primary care records and genetic data in UK Biobank were used for model derivation and population health modelling. Prioritisation tools using age, PRS for coronary artery disease and stroke, and conventional risk factors for CVD available within longitudinal primary care records were derived using sex-specific Cox models. Rescaling to account for the healthy cohort effect, we modelled the implications of initiating guideline-recommended statin therapy after prioritising individuals for invitation to a formal CVD risk assessment. Results 1,838 CVD events were observed over median follow up of 8.2 years. If primary care records were used to prioritise individuals for formal risk assessment using age- and sex-specific thresholds corresponding to 5% false negative rates then we would capture 65% and 43% events amongst men and women respectively. The numbers of men and women needed to be screened to prevent one CVD event (NNS) are 74 and 140 respectively. In contrast, adding PRS to both prioritisation and formal assessments, and selecting thresholds to capture the same number of events resulted in a NNS of 60 for men and 90 for women. Conclusion The use of PRS together with primary care records to prioritise individuals at highest risk of a CVD event for a formal CVD risk assessment can more efficiently prioritise those who need interventions the most than using primary care records alone. This could lead to better allocation of resources by reducing the number of formal risk assessments in primary care while still preventing the same number CVD events. ### Competing Interest Statement During the drafting of the manuscript, M.A. became an employee of AstraZeneca. ### Funding Statement This work was supported by core funding from the: British Heart Foundation (RG/13/13/30194; RG/18/13/33946), BHF Cambridge Centre of Research Excellence (RE/13/6/30180) and NIHR Cambridge Biomedical Research Centre (BRC-1215-20014) [*]. *The views expressed are those of the author(s) and not necessarily those of the NIHR, NHSBT or the Department of Health and Social Care. This work was funded by the Medical Research Council (MR/K014811/1). The study funders played no role in the design, analysis or interpretation of the study. R.C. is funded by a BHF PhD studentship (FS/18/56/34177). Z.X. is funded by the Chinese Scholarship Council. M.A. was funded by a British Heart Foundation Programme Grant (RG/18/13/33946). S.I. was funded by a BHF-Turing Cardiovascular Data Science Award (BCDSA\100005) and is funded by a University College London FB Cancer Research UK Award (C18081/A31373). H.H. is funded by an International Alliance for Cancer Early Detection Project Award (ACEDFR3\_0620I135PR007). J.B. was funded by a Medical Research Council fellowship (MR/L501566/1) and unit programme (MC\_UU_00002/5). L.P. is funded by a British Heart Foundation Programme Grant (RG/18/13/33946). L.G.K. was funded by the NIHR BTRU in Donor Health and Genomics (NIHR BTRU-2014-10024) and is funded by the NIHR BTRU in Donor Health and Behaviour (NIHR203337) [*]. M.I. is supported by the Munz Chair of Cardiovascular Prediction and Prevention and the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014) and EU Horizon 2020 (No 101016775 INTERVENE). M.I. was also supported by the UK Economic and Social Research 878 Council (ES/T013192/1). J.A.U. is funded by an NIHR Advanced Fellowship (NIHR300861). A.M.W. is part of the BigData@Heart Consortium, funded by the Innovative Medicines Initiative-2 Joint Undertaking under grant agreement No 116074. A.M.W. is supported by the BHF-Turing Cardiovascular Data Science Award (BCDSA\100005). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This research has been conducted using the UK Biobank Resource under Application Number 26865. Data from the Clinical Practice Research Datalink (CPRD) were obtained under licence from the UK Medicines and Healthcare products Regulatory Agency (protocol 162RMn2). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All data files are available from the UK Biobank and CPRD databases.