Using Polygenic Risk Scores for Prioritizing Individuals at Greatest Need of a Cardiovascular Disease Risk Assessment
Background The aim of this study was to provide quantitative evidence of the use of polygenic risk scores for systematically identifying individuals for invitation for full formal cardiovascular disease (CVD) risk assessment. Methods and Results A total of 108 685 participants aged 40 to 69 years, w...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-08-01
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| Series: | Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease |
| Subjects: | |
| Online Access: | https://www.ahajournals.org/doi/10.1161/JAHA.122.029296 |
| _version_ | 1797738416683614208 |
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| author | Ryan Chung Zhe Xu Matthew Arnold Samantha Ip Hannah Harrison Jessica Barrett Lisa Pennells Lois G. Kim Emanuele Di Angelantonio Ellie Paige Scott C. Ritchie Michael Inouye Juliet A. Usher‐Smith Angela M. Wood |
| author_facet | Ryan Chung Zhe Xu Matthew Arnold Samantha Ip Hannah Harrison Jessica Barrett Lisa Pennells Lois G. Kim Emanuele Di Angelantonio Ellie Paige Scott C. Ritchie Michael Inouye Juliet A. Usher‐Smith Angela M. Wood |
| author_sort | Ryan Chung |
| collection | DOAJ |
| description | Background The aim of this study was to provide quantitative evidence of the use of polygenic risk scores for systematically identifying individuals for invitation for full formal cardiovascular disease (CVD) risk assessment. Methods and Results A total of 108 685 participants aged 40 to 69 years, with measured biomarkers, linked primary care records, and genetic data in UK Biobank were used for model derivation and population health modeling. Prioritization tools using age, polygenic risk scores 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. We modeled the implications of initiating guideline‐recommended statin therapy after prioritizing individuals for invitation to a formal CVD risk assessment. If primary care records were used to prioritize individuals for formal risk assessment using age‐ and sex‐specific thresholds corresponding to 5% false‐negative rates, then the numbers of men and women needed to be screened to prevent 1 CVD event are 149 and 280, respectively. In contrast, adding polygenic risk scores to both prioritization and formal assessments, and selecting thresholds to capture the same number of events, resulted in a number needed to screen of 116 for men and 180 for women. Conclusions Using both polygenic risk scores and primary care records to prioritize individuals at highest risk of a CVD event for a formal CVD risk assessment can efficiently prioritize 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 risk assessments in primary care while still preventing the same number of CVD events. |
| first_indexed | 2024-03-12T13:43:28Z |
| format | Article |
| id | doaj.art-c219f2af3e6b407891c106228668ab08 |
| institution | Directory Open Access Journal |
| issn | 2047-9980 |
| language | English |
| last_indexed | 2024-03-12T13:43:28Z |
| publishDate | 2023-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease |
| spelling | doaj.art-c219f2af3e6b407891c106228668ab082023-08-23T10:41:23ZengWileyJournal of the American Heart Association: Cardiovascular and Cerebrovascular Disease2047-99802023-08-01121510.1161/JAHA.122.029296Using Polygenic Risk Scores for Prioritizing Individuals at Greatest Need of a Cardiovascular Disease Risk AssessmentRyan Chung0Zhe Xu1Matthew Arnold2Samantha Ip3Hannah Harrison4Jessica Barrett5Lisa Pennells6Lois G. Kim7Emanuele Di Angelantonio8Ellie Paige9Scott C. Ritchie10Michael Inouye11Juliet A. Usher‐Smith12Angela M. Wood13British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care University of Cambridge United KingdomBritish Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care University of Cambridge United KingdomBritish Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care University of Cambridge United KingdomBritish Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care University of Cambridge United KingdomCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care University of Cambridge United KingdomMedical Research Council Biostatistics Unit University of Cambridge United KingdomBritish Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care University of Cambridge United KingdomBritish Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care University of Cambridge United KingdomBritish Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care University of Cambridge United KingdomNational Centre for Epidemiology and Population Health Australian National University Canberra AustraliaBritish Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care University of Cambridge United KingdomBritish Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care University of Cambridge United KingdomPrimary Care Unit, Department of Public Health and Primary Care University of Cambridge United KingdomBritish Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care University of Cambridge United KingdomBackground The aim of this study was to provide quantitative evidence of the use of polygenic risk scores for systematically identifying individuals for invitation for full formal cardiovascular disease (CVD) risk assessment. Methods and Results A total of 108 685 participants aged 40 to 69 years, with measured biomarkers, linked primary care records, and genetic data in UK Biobank were used for model derivation and population health modeling. Prioritization tools using age, polygenic risk scores 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. We modeled the implications of initiating guideline‐recommended statin therapy after prioritizing individuals for invitation to a formal CVD risk assessment. If primary care records were used to prioritize individuals for formal risk assessment using age‐ and sex‐specific thresholds corresponding to 5% false‐negative rates, then the numbers of men and women needed to be screened to prevent 1 CVD event are 149 and 280, respectively. In contrast, adding polygenic risk scores to both prioritization and formal assessments, and selecting thresholds to capture the same number of events, resulted in a number needed to screen of 116 for men and 180 for women. Conclusions Using both polygenic risk scores and primary care records to prioritize individuals at highest risk of a CVD event for a formal CVD risk assessment can efficiently prioritize 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 risk assessments in primary care while still preventing the same number of CVD events.https://www.ahajournals.org/doi/10.1161/JAHA.122.029296cardiovascular diseaseelectronic health recordsgenomicsprimary care recordsscreening |
| spellingShingle | Ryan Chung Zhe Xu Matthew Arnold Samantha Ip Hannah Harrison Jessica Barrett Lisa Pennells Lois G. Kim Emanuele Di Angelantonio Ellie Paige Scott C. Ritchie Michael Inouye Juliet A. Usher‐Smith Angela M. Wood Using Polygenic Risk Scores for Prioritizing Individuals at Greatest Need of a Cardiovascular Disease Risk Assessment Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease cardiovascular disease electronic health records genomics primary care records screening |
| title | Using Polygenic Risk Scores for Prioritizing Individuals at Greatest Need of a Cardiovascular Disease Risk Assessment |
| title_full | Using Polygenic Risk Scores for Prioritizing Individuals at Greatest Need of a Cardiovascular Disease Risk Assessment |
| title_fullStr | Using Polygenic Risk Scores for Prioritizing Individuals at Greatest Need of a Cardiovascular Disease Risk Assessment |
| title_full_unstemmed | Using Polygenic Risk Scores for Prioritizing Individuals at Greatest Need of a Cardiovascular Disease Risk Assessment |
| title_short | Using Polygenic Risk Scores for Prioritizing Individuals at Greatest Need of a Cardiovascular Disease Risk Assessment |
| title_sort | using polygenic risk scores for prioritizing individuals at greatest need of a cardiovascular disease risk assessment |
| topic | cardiovascular disease electronic health records genomics primary care records screening |
| url | https://www.ahajournals.org/doi/10.1161/JAHA.122.029296 |
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