Researchers at a major U.S. university report that computed tomography of the heart can forecast the chance of heart disease in middle-aged adults more accurately than analyzing genetic data. The findings were published in a leading medical journal.
Because the risk of heart disease can run in families, scientists have explored the idea of using a polygenic risk score, which adds up many genetic variants to guide personalized care. That approach follows a line of thinking that a person’s inherited blueprint could help tailor prevention strategies.
In a direct comparison, the study drew on data from 3,208 adults sourced from two large cohorts, one based in the United States and another in the Netherlands. Participants were followed for as long as 17 years, providing a substantial window to observe who developed heart problems.
The addition of genetic information did not shift an individual’s overall risk estimate. Yet when genetic data were considered alongside CT measurements that detect calcium deposits in the coronary arteries, about half of the participants were reclassified into a higher risk category. This suggests that combining imaging with genetics may strengthen risk stratification in some people.
In this framework, a low-risk designation refers to a predicted probability of fewer than 7.5 percent for developing heart disease within the next decade. A predicted risk at or above 7.5 percent typically leads clinicians to consider preventive measures, including statin therapy to lower cholesterol and reduce event risk.
Traditionally, doctors gauge cardiovascular risk using a mix of blood pressure, cholesterol, age, and related factors. Nevertheless, some individuals experience heart attacks or related events even when measurements appear normal. This reality motivates ongoing research to identify reliable biomarkers that indicate heightened risk beyond standard tests.
These findings contribute to a broader effort to refine how clinicians assess heart risk and tailor prevention. They highlight the potential value of imaging data when making decisions about preventive care and illuminate how genetics may fit into a comprehensive risk picture without dominating it. As science advances, clinicians may integrate multiple data streams to identify those at greatest risk and to guide treatment choices more precisely.