Cardiovascular disease is the leading cause of death in the United States, accounting for roughly one in three fatalities nationwide. However, a significant portion of those people aren’t identified as high risk until after a cardiovascular event occurs. And part of the problem is that traditional risk prediction calculators depend on cumulative factors such as elevated cholesterol, high blood pressure, and age.
For patients with few or none of those factors, traditional risk calculators can miss what’s written in biology. But polygenic risk scores are changing that. Here’s how.
Understanding Polygenic Risk Scores to Predict Cardiovascular Disease
A polygenic risk score (PRS) is an estimate of a person’s inherited genetic susceptibility calculated by analyzing thousands of genetic variants across a genome. Although no single variant causes cardiovascular disease, many common variants can accumulate into a meaningful risk. A PRS aggregates those risks into a score that physicians and researchers can compare against population distribution.
That comparison provides a picture of a patient’s genetic predisposition to heart disease and other conditions. The data can be calculated from blood or saliva samples to reflect a risk entirely independent of traditional risk factors, lifestyle, weight, or current lab values.
PRS vs Traditional Risk Assessment
A polygenic risk score complements traditional risk assessment; PRS does not replace it. Nor does it replace blood pressure readings, cholesterol panels, or clinical judgment. PRS adds a layer of information that traditional risk assessment tools couldn’t see.
For example, prediction tools such as SCORE2 estimate a 10-year cardiovascular event risk based on conventional risk factors, and PRS works alongside it to refine the data for patients who fall into ambiguous categories. Therefore, incorporating polygenic risk scores into clinical practice can significantly improve the predictive powers of tools and make risk assessment more equitable and precise.
Early Cardiovascular Disease Detection
PRS can surface risk in patients who are systemically underserved by age-based calculators. For instance, traditional heart disease risk tools weigh heavily for age. But a 45-year-old with genetic predisposition for coronary artery disease could still score low risk because they haven’t lived long enough to accumulate the clinical markers that the calculator is looking for.
Adding a polygenic risk score to this standard clinical risk calculation can increase the proportion of those identified as high risk. And that gap is particularly significant for women, since current sex-blind cardiovascular PRS can systematically misclassify women and contribute to underdiagnosis and undertreatment.
Research has found that over 70% more female participants were classified as very high genetic risk for heart disease when sex-stratified scoring was applied, compared with standard scoring. Incorporating genetic risk scoring into standard evaluation creates an opportunity to correct that gap before it becomes a missed diagnosis.
Polygenic Risk Scores: Conditions and Assessment
PRS isn’t limited to one condition; the most clinically developed models cover coronary artery disease, arterial fibrillation, and hypertension. A recently validated report assessed eight heart conditions, identifying those at high versus average risk across all 53,000 participants. And what makes this clinically significant is that a high PRS can flag risk that standard lab work would miss.
Someone in the top 5% of coronary artery disease genetic risk carries roughly 3 times the odds of developing CAD. This is a level of risk comparable to familial hypocholesterolemia but without the elevated LDL that would prompt a closer look. So, those patients might appear unremarkable on a standard panel.
PRS Limitations
Most of the genetic association data risk scores are derived from populations of European ancestry. This is a significant and well documented limitation of polygenic risk scores for heart disease. Approximately 78% of those included in genome-wide association studies were of European ancestry, with only about 11% of Asian ancestry, and other populations making up even smaller minorities.
PRS models trained predominantly on European data can perform much less accurately in populations of South Asian, African, or admixed ancestry. This is a disparity that, if ignored, could worsen existing cardiovascular health inequities.
How the Field Is Responding
Multi-ancestry polygenic risk scores that incorporate genome-wide association data across multiple populations are finally in development and validation. Expanding representation in genomic databases is now one of the field’s most pressing priorities.
One approach developed is using polygenic score to predict cardiovascular disease and coronary artery disease using data from over 269,000 cases and 1.17 million controls across five ancestries. Researchers identified 20% of the population at threefold increased risk. Conversely, it also found 14% at threefold decreased risk compared to those in the middle quintile.
That discrimination across diverse ancestries represents a meaningful step forward. A risk tool that works well for one population and poorly for another is not a precision medicine tool. The field is responding by adding PRS to traditional calculators instead of replicating the same disparities already present in cardiovascular care.
What a High Polygenic Genetic Risk Score Means
Polygenic risk scores tell physicians and patients that their inherited biology warrants early attention, close monitoring, and potentially more aggressive preventative interventions. It is not a sign that a cardiovascular event is inevitable.
A high polygenic risk score is not a diagnosis, but it is actionable. PRS measures genetics to establish a baseline of susceptibility, not to determine outcomes. Furthermore, the interventions that work for high-risk patients are the same ones available to everyone.
Many individuals at high risk of cardiovascular vascular disease are invisible to the system because genetics are not being used as part of risk prediction. That matters because statins are even more effective in people with high PRS than in the general population. This means the patients most likely to benefit from early intervention are also the ones most likely to be missed.
The Current State of Polygenic Risk Prediction Scoring
Polygenic risk scoring surfaces the genetic information that traditional risk calculators can’t. For patients caught between thresholds, the data can change clinical conversations and outlooks.
PRS technology has significant limitations around ancestral diversity, but the field is actively working to close that gap. What’s already clear is that adding genetic context to cardiovascular risk assessment allows for more customized and proactive care.
Visit the Nora Eccles Harrison Cardiovascular Research and Training Institute (CVRTI) to follow the latest advances in cardiovascular research.
