Researchers have developed a new stroke risk score that leverages genetic data to identify people at a particularly high risk of ischemic stroke.
Michael Inouye, PhD, of the Baker Heart and Diabetes Institute in Australia and the University of Cambridge in the U.K., and colleagues reported in Nature Communications that their model can derive stroke risk from just one blood draw or sample, effectively flagging patients at a threefold increased risk of ischemic stroke. Around 80% of strokes are ischemic, and the authors said that by using a genetic risk score to predict future events, physicians can help patients manage their risk factors earlier and more effectively.
Inouye, alongside research teams in Australia, the U.K. and Germany, employed machine learning to integrate stroke-related genetic data from a variety of research projects into a single risk score. They then tested their model in a population of 420,000 individuals enrolled in the UK Biobank, ultimately finding the score could detect the roughly 1 in 400 individuals at a threefold increased risk of ischemic stroke.
The authors said their score outperformed existing genetic risk scores and demonstrated similar predictive performance as other well-known risk factors for stroke, including BMI and smoking status.
Inouye et al. said patients flagged by their algorithm can mitigate their risk for future adverse events by reducing other conventional risk factors and living a healthier lifestyle.
“The sequencing of the human genome has revealed many insights,” Inouye said in a release. “For common diseases, such as stroke, it is clear that genetics is not destiny; however, each person does have their own innate risk for any particular disease. The challenge is now how we best incorporate this risk information into clinical practice so that the public can live healthier and longer.”