Polygenic risk scores improve CAD risk prediction in individuals at borderline and intermediate clinical risk

Polygenic risk scores (PRSs) can improve clinical risk tools for coronary artery disease (CAD). This study assessed a risk model integrating PRS across populations, focusing on individuals with borderline/intermediate clinical risk. We developed ancestry-specific ensemble models combining multi-ancestry PRSs for CAD and type 2 diabetes. The cross-ancestry PRS (caPRS) was integrated with the Pooled Cohort Equations (PCE) to derive the cross-ancestry Integrated Risk Score (caIRS), estimating 10-year CAD risk. The caIRS outperformed the PCE across four cohorts, including UK Biobank and Penn Medicine Biobank, with significant improvements for Hispanic and South Asian individuals. For those at borderline/intermediate PCE risk (5-20%), the caIRS reclassified between 7.0% and 10.7% into the high-risk group, which had higher CAD incidence and hazard ratios ranging from 3.20 to 3.84. The CAD caIRS, combining genetic and clinical factors, enhances high-risk CAD identification across diverse populations, potentially improving treatment guidance.

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Publication Details

Journal
npj Cardiovascular Health
Published
2025-05-01
DOI
https://doi.org/10.1038/s44325-025-00049-7
Citations
11
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
19.99

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article

Polygenic risk scores improve CAD risk prediction in individuals at borderline and intermediate clinical risk

Matthew Rabinowitz, Tate Tunstall, Kate M. Im, Premal Shah et al.
11 citations
npj Cardiovascular Health
Genetic Associations and Epidemiology
19.99
article

Polygenic risk scores improve CAD risk prediction in individuals at borderline and intermediate clinical risk

Matthew Rabinowitz, Tate Tunstall, Kate M. Im, Premal Shah, Daniel James Rader, Dariusz Ratman, Robert J. Maier, Michael G. Levin, Placede Tshiaba, Jiayi Sun, Akash Kumar
article en
11 citations

Abstract

Polygenic risk scores (PRSs) can improve clinical risk tools for coronary artery disease (CAD). This study assessed a risk model integrating PRS across populations, focusing on individuals with borderline/intermediate clinical risk. We developed ancestry-specific ensemble models combining multi-ancestry PRSs for CAD and type 2 diabetes. The cross-ancestry PRS (caPRS) was integrated with the Pooled Cohort Equations (PCE) to derive the cross-ancestry Integrated Risk Score (caIRS), estimating 10-year CAD risk. The caIRS outperformed the PCE across four cohorts, including UK Biobank and Penn Medicine Biobank, with significant improvements for Hispanic and South Asian individuals. For those at borderline/intermediate PCE risk (5-20%), the caIRS reclassified between 7.0% and 10.7% into the high-risk group, which had higher CAD incidence and hazard ratios ranging from 3.20 to 3.84. The CAD caIRS, combining genetic and clinical factors, enhances high-risk CAD identification across diverse populations, potentially improving treatment guidance.

npj Cardiovascular HealthVol. 2(1)
Natera (United States) (US), University of Pennsylvania (US), Depomed (United States) (US)
U.S. Department of Health and Human Services, Office of Dietary Supplements, University of Miami, Jackson State University, Northwestern University, San Diego State University, Broad Institute, Georgia Clinical and Translational Science Alliance, Mississippi State Department of Health, National Institute on Aging, National Heart, Lung, and Blood Institute, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Neurological Disorders and Stroke, National Center on Minority Health and Health Disparities, National Institute on Minority Health and Health Disparities
Openalex Percentile: Top 1%
Genetic Associations and Epidemiology
19.99
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