Genetics

This blog post examines how polygenic risk scores can refine the assessment of multiple sclerosis susceptibility and disease-related phenotypes in European populations. Drawing on genome-wide association data, the article highlights how aggregated genetic risk improves prediction beyond conventional factors such as sex, age, smoking, mononucleosis history, body mass index, and family history. It also discusses pathway-specific genetic signals, familial risk patterns, and associations between genetic predisposition and neuroimaging markers such as thalamic atrophy. Overall, the post presents polygenic profiling as a promising but not yet standalone tool for early risk stratification, mechanistic discovery, and future precision-medicine approaches in multiple sclerosis.