- Research suggests a new polygenic risk score can estimate the inherited risk for 8 major cardiovascular and related conditions in a single test.
- In validation studies, those with the highest risk had a greater disease likelihood, such as a 3.7× and 3.1× higher risk of coronary heart disease and type 2 diabetes, respectively, compared to average-risk individuals.
- The tool combines multiple genetic models from the Polygenic Score Catalog and is designed to integrate into clinical workflows, with patient-friendly reports and electronic health record compatibility.
- While promising for earlier detection and prevention, further research is necessary to guide clinical use and ensure accuracy across diverse populations, as current data are largely based on European ancestry groups.
Cardiovascular disease remains the
Traditional risk assessments typically rely on factors such as age, blood pressure, cholesterol levels, and lifestyle habits. However, these methods may not fully capture inherited risk.
Some individuals may have a
While genetic testing can be useful for guiding clinical decisions, it can be difficult to identify those with a genetic predisposition, as they are less likely to raise early red flags during routine care, may lack obvious, early warning signs, and already follow recommended lifestyle choices.
Now, a recent validation study suggests a tool could help clinicians better predict an individual’s inherited risk of developing multiple cardiovascular conditions.
Published in the Journal of the American College of Cardiology, the findings indicate that the tool can evaluate a person’s genetic predisposition to 8 common cardiovascular or related diseases.
Current risk assessment for cardiovascular diseases can measure risk factors such as blood pressure and cholesterol, but may miss individuals who carry significant inherited risk.
To address this gap, a team led by researchers at the Mass General Brigham Heart and Vascular Institute created an integrated
The tool assesses risk for the following 8 conditions:
- coronary artery disease
- atrial fibrillation
- type 2 diabetes
- venous thromboembolism
- thoracic aortic aneurysm
- extreme hypertension
- severe hypercholesterolemia
- elevated lipoprotein(a).
As the name suggests, polygenic risk refers to the cumulative effect of many genetic variants, each contributing a small increase in disease risk. Evidence notes that the majority of genetic predisposition in cardiovascular diseases is polygenic.
Thus, it is possible to test for a polygenic risk score to estimate a person’s genetic predisposition, which holds promise for cardiovascular disease risk prediction.
However, polygenic risk scores are not yet part of routine cardiology practice, as challenges remain in integrating them into clinical decision making.
By consolidating multiple genetic risk models from the Polygenic Score Catalog, the Mass General Brigham researchers aimed to deliver a more comprehensive and clinically useful result.
Co-senior study author Aniruddh Pradip Patel, MD, a cardiologist and researcher with Mass General Brigham Heart and Vascular Institute, who helped develop the tool, discussed how clinicians can interpret and act on these findings with Medical News Today.
“Clinicians should think of polygenic risk scores like any other risk predictor — a tool that can tilt clinical decision-making in one direction or another — except that it is available from birth and independent of lifestyle or acquired risk factors.”
– Aniruddh Pradip Patel, MD
“If a patient has a borderline 10-year cardiovascular risk estimate, knowing their polygenic risk score can help inform whether to pursue earlier or more intensive intervention, or conversely support a more conservative approach,” said Patel.
“In our study, adding the integrated polygenic risk scores to established clinical models improved risk reclassification among borderline patients by roughly 17–18% for coronary artery disease, meaning that individuals who were previously in an ambiguous gray zone got moved into a more clearly high- or low-risk category, enabling more confident clinical decisions,” he detailed.
The research team trained the polygenic risk score tool using genetic and health data from more than 245,000 participants in the All of Us Research Program.
They then validated the results in over 53,000 individuals from the Mass General Brigham Biobank. The findings indicate a strong association between high genetic risk scores and disease likelihood.
Individuals in the top 10% of genetic risk for coronary artery disease were 3.7 times more like to develop the condition compared with those at average risk.
Similarly, those with the highest genetic risk for type 2 diabetes were 3.1 times more likely to develop the disease.
“These effect sizes are clinically meaningful. For coronary artery disease specifically, individuals in the top 10% of genetic risk had nearly four times the odds of disease compared to those at average risk, exceeding the magnitude we typically see with established risk factors like hypertension or high cholesterol, which are generally associated with around two-fold increased odds,” Patel said to MNT.
“What makes this particularly striking is that genetic risk is present and stable from birth, long before traditional risk factors have had a chance to accumulate. That creates a real opportunity for earlier, more targeted prevention in individuals who might otherwise go unidentified until they present with a cardiac event.”
– Aniruddh Pradip Patel, MD
In addition to categorizing risk levels as high, average, or low, the polygenic risk score report also includes patient-friendly explanations and visual graphs showing how an individual’s risk compares with the general population.
The tool is also designed to integrate into electronic health records and patient portals, which could make it easier for clinicians to incorporate genetic data into routine care.
The researchers add that interpreting DNA risk is new for both the public and clinicians, and emphasize the importance of making genetic risk information clear and accessible, and to provide actionable insights for both patients and clinicians.
“The report communicates each person’s risk across all eight cardiovascular conditions using intuitive percentile-based categories alongside relative risk estimates, plain-language descriptions, and links to evidence-based preventive interventions,” Patel told MNT.
“We also built in clinician-facing guidance that addresses known limitations, including reduced performance in individuals of non-European ancestry,” he added.
“Our approach addresses some longstanding challenges by unifying score selection through an integrative framework and building in a dynamic pipeline that can incorporate new scores as the field advances,” he explained.
Nevertheless, Patel highlighted that “significant gaps remain,” and that we have to take into account the fact that “most existing scores were developed predominantly in European-ancestry populations, and sustained investment in more diverse genetic studies is essential to avoid exacerbating Health disparities.”
“Perhaps most critically, prospective randomized trials showing that acting on polygenic risk score information actually improves outcomes are still lacking,” the researcher told us.
“The field also needs clearer clinical use case guidelines, smoother workflow integration into health systems, and clinician training to communicate probabilistic risk. And perhaps most fundamentally, without reimbursement from payers, these tools will struggle to reach the patients who might benefit most,” he noted.
While the results highlight the potential of genetic risk scoring, the researchers caution that further studies are necessary to determine how best to use this information in clinical decision making.
They also note that many genetic models currently rely heavily on data from populations of European ancestry, which raises questions about how well the tool performs across more diverse groups.
As genetic testing becomes more integrated into healthcare, tools like polygenic risk scores could play an increasing role in identifying hidden risk factors and guiding earlier interventions.
For now, the new test represents a step toward more personalized and preventive cardiovascular care.
