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Evaluating the Clinical Utility of a Cross-Ancestry Integrated Risk Score for Coronary Artery Disease Prevention

Clinical Genetics and Therapeutics
  • Primary Categories:
    • Health services and Implementation
  • Secondary Categories:
    • Health services and Implementation
Introduction:
Polygenic risk scores (PRS) can enhance the precision of clinical risk tools and identify more individuals at elevated risk of coronary artery disease (CAD). However, there is limited clinical evidence supporting their use in primary prevention. We aimed to assess the utility of the cross-ancestry, Integrated Risk Score (caIRS) as a screening tool to identify high-risk individuals with uncertain risk based on traditional risk assessments for CAD and evaluate the impact of returning caIRS score report on health care use, disease incidence, and behavior changes.

Methods:
We developed a cross-ancestry PRS model for CAD and integrated it with the Pooled Cohort Equations (PCE), a standard clinical tool used to predict the risk of atherosclerotic cardiovascular disease (ASCVD), to derive the caIRS, which estimates 10-year absolute CAD risk. We retrospectively validated the performance of the caIRS in comparison to the PCE using the diverse, U.S. based Penn Medicine Biobank (PMBB). For prospective validation, we designed a randomized controlled clinical trial. We will recruit 1000, CAD-free participants with borderline/intermediate PCE risk (5-20%) across three large U.S.  healthcare centers. Using previously genotyped data, eligible participants will be stratified by caIRS into average (caIRS <20%) and high risk (caIRS ≥20%) categories and randomized into early or delayed reporting arms. Clinical genome sequencing (GS) will be performed after consent. The early reporting arm will receive their caIRS report ~2-3 months post-enrollment, while the delayed reporting arm will receive a PCE-only report initially with caIRS reported after 3 years. Participants will complete questionnaires at enrollment, post-report release, and 1 year post-enrollment to assess knowledge and behavioral impact.  CAD incidence, statin use, and lab results will be tracked over 5 years and compared to evaluate the impact of caIRS on outcomes and provider behavior.

Results:
In the retrospective analysis of PMBB participants classified as borderline/intermediate risk using the standard PCE model (5-20%) the caIRS reclassified (20% threshold) 588 out of 6067 individuals into the high-risk group, which experienced 36.8% (95% CI: 31.3-41.8) incidence of CAD compared to 11.6% (95% CI: 10.4-12.8) incidence for all others - motivating further prospective validation study.

Conclusion:
Using the CAD caIRS, which combines genetic and traditional clinical risk factors, to refine clinical risk estimates has the potential to improve treatment guidance in a primary prevention setting. The results from the prospective trial will provide insights into how the integration of caIRS influences long-term cardiovascular outcomes and personalized treatment strategies.

 

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