The following is a summary of “Combined polygenic scores for ischemic stroke risk factors aid risk assessment of ischemic stroke,” published in the June 2024 issue of Cardiology by Huang et al.
Stroke is one of the leading causes of death and disability, with 87% of all strokes classified as ischemic stroke (IS). Polygenic scores (PGS) were hypothesized to improve risk assessment for IS (PGSIS) along with related diseases like atrial fibrillation (AF), venous thromboembolism (VTE), coronary artery disease (CAD), hypertension (HTN), and Type 2 diabetes (T2D).
Researchers conducted a prospective study to assess if adding PGS boosts the accuracy of predicting IS risk.
They reviewed 479,476 participants without prior IS. Using the Cox proportional-hazards model, lifestyle factors (obesity, smoking, alcohol), clinical diagnoses, PGSIS, and 5 PGSs for related diseases were tested. Predictive performance was evaluated with the C-statistics and net reclassification index (NRI).
The results showed that over a 12.5-year follow-up, 8,374 participants developed IS. Age, gender, IS-related conditions, obesity, smoking, and PGSIS were all linked to IS (P<0.001). Adding PGSIS and PGS for related diseases improved prediction accuracy from 0.71 to 0.73 (P<0.001) and reclassified IS risk (NRI = 0.017, P<0.001), with 6.48% moving from low to high risk.
Investigators concluded that adding PGSs for IS and related diseases to clinical risk factors improves IS risk assessment. However, the clinical benefit was limited since the boost in predictive accuracy is modest.
Source: sciencedirect.com/science/article/abs/pii/S0167527324005400
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