Genetics

This blog post examines the scientific case for MS risk prediction as presented in a Frontiers in Neurology mini-review, focusing on how polygenic risk scores (PRS) and environmental risk scores (ERS) can be combined to stratify susceptibility and, crucially, to enrich cohorts for prevention trials. It explains why MS genetics is simultaneously informative and insufficient for individual-level certainty, how major environmental exposures (notably EBV-related measures, vitamin D, smoking, and obesity) contribute additive and interactive risk, and why hybrid models often outperform genetics alone. The post also underscores the central translational constraint—low disease prevalence driving low positive predictive value—even when discrimination metrics look promising, and closes by outlining how improved data, calibration, and cross-ancestry validation can move MS prediction from academic models toward prevention-ready research and screening frameworks.