Sahi, Nitin;
Ciccarelli, Olga;
Houlden, Henry;
Chard, Declan T;
(2025)
Unlocking Multiple Sclerosis Genetics.
Neurology
, 105
(8)
, Article e214141. 10.1212/wnl.0000000000214141.
(In press).
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Abstract
Multiple sclerosis (MS) is a clinically diverse and unpredictable CNS disorder. The considerable heterogeneity in disease course between people with MS is believed to reflect the varying magnitude and extent of the pathologic processes present at different stages of the disease. Genetic factors are known to contribute to the risk of developing MS and are emerging as predictors of clinical outcomes. They may also offer insights into the biological processes influencing disability. In this review, we evaluate the role of genetic factors in MS from disease susceptibility to disease severity. We consider how understanding of the geneticcontribution to the risk of developing MS has evolved to recognize over 230 genetic variants that implicate peripheral immune cells at disease onset. Although MS-risk genes have shown little association with disease severity outcomes, we re-evaluate associations of the main MS-risk allele, HLADRB1*1501, with disease activity using observations from long-term longitudinal cohorts. We summarize progress identifying genetic variants associated with clinical phenotypes, including the discovery of the first genetic variant associated with age-related MS severity, rs10191329, and its pathologic associations. We assess the challenges faced by replication studies, including low statistical power, methodologic variations in disability outcomes, and the potential impact from differences in treatmentand disease temporality. Reconciling these findings, in contrast to MS-risk genes, MS severity variants appear enriched in CNS tissues, suggesting at least in part distinct geneticarchitectures for MS risk and severity. Despite advances in our understanding of MS genetics, there remain significant gaps in our knowledge that reflect the elaborate genetic architecture underlying disease progression. Potential gains are to be made from exploring rare variants and ancestrally diverse populations, while the causality of variants may be interrogated through analyses of gene sets and recognized biological pathways. However, further work is required to improve phenotyping of disease severity beyond physical disability measuresand to disentangle complex genetic interactions, which may vary with environmental factors and time. Resolving these challenges is crucial if genetic analyses are going to be able to power clinically useable predictive models and inform mechanistic targets for novel treatments in progressive MS.
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