A multicondition polygenic risk report validated in U.S. health systems could help clinicians spot inherited cardiovascular risk earlier, refine prevention strategies, and guide more personalized care.
Study: Development and Validation of a Clinical Polygenic Risk Report in U.S.-Based Health Systems for 8 Cardiovascular Conditions. Image Credit: ArtemisDiana / Shutterstock
In a recent study published in the Journal of the American College of Cardiology (JACC), researchers described the development and validation of integrated polygenic risk scores (PRS) for eight cardiovascular conditions using data from 245,394 participants in the All of Us (AOU) Research Program and 53,306 participants from the Mass General Brigham Biobank (MGBB).
The integrated PRS platform demonstrated robust risk stratification and clinically structured reporting, generally matching or exceeding individual input models, offering a transparent framework for identifying individuals at high genetic risk who traditional clinical markers might miss.
Cardiovascular Polygenic Risk Score Background
Cardiovascular diseases (CVDs) remain the leading cause of global mortality, but their incidence is characterized by a complex genetic architecture involving substantial heritability and pleiotropy. While some heart conditions are caused by rare, high-impact mutations in a single gene (monogenic), decades of research have established that the vast majority of cases result from thousands of common genetic variations across the genome, each with a minute individual effect.
Traditional clinical risk models, exemplified by the Pooled Cohort Equations (PCE), estimate risk using demographic and phenotypic markers, such as blood pressure and cholesterol, whereas PRS quantify inherited risk from common genetic variants. However, a holistic methodology for risk stratification remains lacking. Systematic reviews and meta-analyses of available PRS approaches indicate that they often fail to capture the full spectrum of inherited risk, particularly in younger or "intermediate-risk" populations.
There consequently exists a pressing need for a standardized, "consensus" approach that could aggregate these scores into a single, reliable report across multiple conditions.
Integrated PRS Study Design and Validation
The present study aimed to address these knowledge gaps by creating a transparent pipeline to bring genetic risk stratification into routine preventive care. The entire project comprised a multi-phase development and validation study across three large-scale biobanks:
The training dataset was derived from genomic and electronic health record (EHR) data from 245,394 All of Us (AOU) participants (mean age = 51.7 ± 17.0 years). Seven trait models were trained using this dataset, while the elevated lipoprotein(a) model was trained in the UK Biobank because standardized Lp(a) measurements were not available in AOU. Training methodology focused on eight clinical conditions, namely atrial fibrillation (AF), coronary artery disease (CAD), type 2 diabetes mellitus (T2DM), thoracic aortic aneurysm (TAA), extreme hypertension, venous thromboembolism (VTE), severe hypercholesterolemia, and elevated lipoprotein(a).
The PRSmix software package was used to integrate publicly available PRS from the PGS Catalog. An 80/20 stratified split was applied to the AOU cohort for internal model testing before external validation, with an equivalent UK Biobank-based approach used for Lp(a).
Subsequently, external model performance validation was performed in an independent cohort comprising 53,306 participants from the Mass General Brigham Biobank (MGBB). The study adjusted for age, sex, and genetic ancestry using computed principal components (PCs; derived from a shared 1000 Genomes-based PC space) to account for genetic diversity.
Notably, discrimination was assessed using C-statistics, and model calibration was evaluated across age, sex, and ancestry subgroups.
PRS Risk Stratification Across Cardiovascular Traits
The novel integrated PRS platform demonstrated consistent risk stratification, generally matching or exceeding the performance of individual input scores across the eight traits. However, predictive performance varied by condition, with more modest discrimination for some outcomes, including VTE, TAA, and extreme hypertension.
The study’s most striking results were those in elevated Lipoprotein(a) levels, where individuals in the high genetic-risk category (the top 10%) had a substantial 41.0-fold increased odds (95% CI: 27.0-62.2) of having elevated levels compared to those with average genetic risk (P < 0.0001).
While not as dramatic, high-risk individuals (top 10%) for severe hypercholesterolemia (odds ratio [OR] = 4.1), CAD (OR = 3.73), T2DM (OR = 3.1), AF (OR = 3.0), and extreme hypertension (OR = 2.1) demonstrated several times the risks of their average-risk counterparts. The study also showed that elevated genetic risk was common in this biobank-based analysis, with 71.2% of the MGBB population having at least one PRS-defined threshold corresponding to at least a 3-fold increased relative genetic risk for one or more of the eight traits.
Crucially, the study found that adding PRS to existing clinical tools, such as the Pooled Cohort Equations (PCE), significantly improved "net reclassification". In CAD, incorporating the genetic score improved risk classification by 17% (P < 0.0001) among patients previously considered "borderline" or "intermediate" risk. Prospective tracking (over a median of 7.6 years) confirmed that a high PRS was associated with incident CAD, AF, T2DM, VTE, and TAA, even in participants younger than 50 years old.
Clinical Implications of Multicondition PRS Testing
The present study marks an important step toward a clinically orderable, multicondition cardiovascular PRS test. By validating an integrated PRS panel across eight conditions, the study’s novel approach has provided a scalable framework that identifies individuals who may harbor previously unrecognized inherited genetic risks despite having normal traditional biomarkers.
However, the authors emphasize that currently, limitations remain. While the scores performed across ancestry groups, the predictive power remained strongest in European populations, underscoring the need for more diverse research data. The authors also noted that broader prospective validation and further evidence on clinical utility are needed before PRS-guided care pathways can be fully established.
Moving forward, this report is now available as a clinically orderable test, allowing doctors to use genetic "risk enhancers" to inform preventive discussions, targeted screening, lifestyle counseling, and medication decisions where clinically appropriate for their patients.
Journal reference:
- Misra, A., et al. (2026). Development and validation of a clinical polygenic risk report in U.S.-based health systems for 8 cardiovascular conditions. Journal of the American College of Cardiology. Advance online publication. DOI: 10.1016/j.jacc.2026.03.035. https://www.jacc.org/doi/full/10.1016/j.jacc.2026.03.035
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