The Framingham Risk Score and ASCVD Pooled Cohort Equations have long served as clinical cornerstones for cardiovascular risk stratification.
However, they often fail to identify high-risk individuals early, particularly in younger or asymptomatic populations.
According to Dr. Sekar Kathiresan, CEO of Verve Therapeutics and a pioneer in genomic cardiology, "Polygenic risk scores offer a new layer of prediction that captures lifelong inherited risk — something traditional models overlook."
Understanding Polygenic Risk Scores
Genetic Architecture of Cardiovascular Disease
Cardiovascular disease, particularly coronary artery disease (CAD), is polygenic in nature. Unlike Mendelian conditions caused by single-gene mutations (e.g., familial hypercholesterolemia), CAD arises from the cumulative effect of many small-effect variants spread across the genome. These single nucleotide polymorphisms (SNPs), though individually modest in impact, together can explain a significant portion of genetic risk.
Construction of a Polygenic Risk Score
PRS are computed by summing risk alleles weighted by their effect sizes derived from genome-wide association studies (GWAS). For CAD, current PRS incorporate up to 6 million SNPs. A 2023 paper in Nature Genetics by Khera et al. demonstrated that individuals in the top 5% of CAD PRS had a threefold increased risk of myocardial infarction compared to the general population — independent of traditional risk factors.
Clinical Utility and Predictive Performance
Identifying High-Risk Individuals Early
A key advantage of PRS is their ability to identify genetically high-risk individuals decades before clinical events occur. This is especially valuable in asymptomatic individuals with normal biometrics but strong inherited risk. Recent data from the UK Biobank cohort (n > 500,000) showed that PRS outperformed LDL-C levels alone in predicting premature coronary events in patients under 50.
Stratifying Therapy and Preventive Interventions
PRS may guide the intensity of preventive strategies. For example, statin therapy has shown greater absolute risk reduction in individuals with high genetic risk. In a 2024 randomized study published in The Lancet, incorporating PRS into decision-making improved the number-needed-to-treat (NNT) for primary prevention with statins in intermediate-risk patients.
Challenges and Limitations
Ancestry Bias and Generalizability
Most PRS have been derived from European ancestry populations, raising concerns about transferability to other ethnic groups. This limitation reduces predictive power in diverse cohorts. Ongoing efforts, such as the All of Us Research Program and the H3Africa initiative, aim to diversify genomic databases for more equitable prediction.
Clinical Interpretation and Ethical Considerations
Integrating PRS into routine practice requires clinician education, genetic counseling, and standardized reporting. Moreover, ethical issues around genetic privacy, insurance discrimination, and patient anxiety must be addressed. Dr. Eimear Kenny of the Icahn School of Medicine at Mount Sinai notes, "Polygenic risk is a probability, not a diagnosis — context matters."
Integration Into Clinical Practice
From Bench to Bedside
Several institutions have begun incorporating PRS into electronic health records (EHRs). For instance, the Massachusetts General Brigham system has initiated PRS-guided preventive cardiology clinics. Algorithms automatically flag patients with elevated PRS for lifestyle counseling and preventive pharmacotherapy.
Combining PRS with Traditional Metrics
PRS are most effective when used alongside established clinical markers. Hybrid models combining PRS with phenotypic data — such as blood pressure, BMI, and lipid profiles — yield superior predictive accuracy. A 2023 machine learning model at Stanford demonstrated a 20% improvement in C-statistics for CAD prediction when PRS was added to clinical variables.
Future Directions and Precision Cardiology
The field is evolving rapidly. Future PRS will likely be condition-specific (e.g., PRS for arrhythmias vs. atherosclerosis) and may integrate rare variants, epigenetic modifiers, and gene-environment interactions. Moreover, as polygenic risk information becomes embedded in newborn screening or adolescent health evaluations, it could transform lifelong cardiovascular management. Large-scale prospective trials, such as the PRIMED (Polygenic Risk Impact on Management and Evaluation of Disease) study, are underway to determine whether PRS-based interventions reduce cardiovascular events in real-world settings.
Polygenic risk scores represent a paradigm shift in cardiovascular medicine — offering a genomically informed layer of risk stratification that complements, but does not replace, traditional methods. As genomic data becomes more representative and integration tools mature, PRS may become foundational in identifying at-risk individuals early, personalizing preventive strategies, and improving long-term cardiovascular outcomes. Clinicians, geneticists, and policymakers must work in concert to ensure these tools are used responsibly, equitably, and effectively in modern medicine.
