Study reveals variability in polygenic risk scores for predicting heart disease

The researchers analyzed data from more than 260,000 participants from diverse backgrounds and found that although most PRSs performed similarly when predicting CAD risk across populations, individual-level predictions varied widely. Many participants were placed in both high and low-risk categories by different PRSs, suggesting that patients could receive conflicting advice based on which score is used.

"Our research underscores a critical gap in our understanding of PRSs, which has implications for their use in personalized medicine," said the study's lead author Sarah Abramowitz, BA, a medical student at the Zucker School of Medicine at Hofstra/Northwell and a Sarnoff Cardiovascular Research Fellow at the Perelman School of Medicine. "While these scores show promise for population-level CAD risk assessment, we need more robust methods to quantify and communicate the uncertainty of individual-level predictions."

The study's findings highlight the need for more refinement before PRSs can be widely adopted in healthcare to guide an individual's CAD risk assessment. Researchers recommend that clinicians consider potential inconsistencies and use these scores as part of a broader risk assessment strategy that considers clinical and lifestyle factors, among others.

This research was supported by the National Institutes of Health (HL169458, T32HL007843), Sarnoff Cardiovascular Research Foundation, and US Department of Veterans Affairs Biomedical Research and Development Award (IK2-BX006551).

Source:

University of Pennsylvania