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Abraham G, Rutten-Jacobs L, Inouye M. Risk Prediction Using Polygenic Risk Scores for Prevention of Stroke and Other Cardiovascular Diseases. Stroke. 2021;52(9):2983-2991doi: 10.1161/STROKEAHA.120.032619.
Abraham, G., Rutten-Jacobs, L., & Inouye, M. (2021). Risk Prediction Using Polygenic Risk Scores for Prevention of Stroke and Other Cardiovascular Diseases. Stroke, 52(9), 2983-2991. https://doi.org/10.1161/STROKEAHA.120.032619
Abraham, Gad, et al. "Risk Prediction Using Polygenic Risk Scores for Prevention of Stroke and Other Cardiovascular Diseases." Stroke vol. 52,9 (2021): 2983-2991. doi: https://doi.org/10.1161/STROKEAHA.120.032619
Abraham G, Rutten-Jacobs L, Inouye M. Risk Prediction Using Polygenic Risk Scores for Prevention of Stroke and Other Cardiovascular Diseases. Stroke. 2021 Aug;52(9):2983-2991. doi: 10.1161/STROKEAHA.120.032619. Epub 2021 Aug 17. PMID: 34399584; PMCID: PMC7611731.
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Stroke. 2021 Aug;52(9):2983-2991. doi: 10.1161/STROKEAHA.120.032619. Epub 2021 Aug 17.

Risk Prediction Using Polygenic Risk Scores for Prevention of Stroke and Other Cardiovascular Diseases.

Stroke

Gad Abraham, Loes Rutten-Jacobs, Michael Inouye

Affiliations

  1. Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia (G.A., M.I.).
  2. Department of Clinical Pathology, University of Melbourne, Parkville, VIC, Australia (G.A., M.I.).
  3. Personalized Health Care Data Science, Real World Data, F. Hoffmann-La Roche Ltd, Basel, Switzerland (L.R.-J.).
  4. Cambridge Baker Systems Genomics Initiative (M.I.), Department of Public Health and Primary Care, University of Cambridge, United Kingdom.
  5. British Heart Foundation Cardiovascular Epidemiology Unit (M.I.), Department of Public Health and Primary Care, University of Cambridge, United Kingdom.
  6. British Heart Foundation Centre of Research Excellence, University of Cambridge, United Kingdom (M.I.).
  7. National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, United Kingdom (M.I.).
  8. Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, United Kingdom (M.I.).
  9. The Alan Turing Institute, London, United Kingdom (M.I.).

PMID: 34399584 PMCID: PMC7611731 DOI: 10.1161/STROKEAHA.120.032619

Abstract

Early prediction of risk of cardiovascular disease (CVD), including stroke, is a cornerstone of disease prevention. Clinical risk scores have been widely used for predicting CVD risk from known risk factors. Most CVDs have a substantial genetic component, which also has been confirmed for stroke in recent gene discovery efforts. However, the role of genetics in prediction of risk of CVD, including stroke, has been limited to testing for highly penetrant monogenic disorders. In contrast, the importance of polygenic variation, the aggregated effect of many common genetic variants across the genome with individually small effects, has become more apparent in the last 5 to 10 years, and powerful polygenic risk scores for CVD have been developed. Here we review the current state of the field of polygenic risk scores for CVD including stroke, and their potential to improve CVD risk prediction. We present findings and lessons from diseases such as coronary artery disease as these will likely be useful to inform future research in stroke polygenic risk prediction.

Keywords: cardiovascular disease; genetics; myocardial infarction; risk assessment; stroke

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