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Genome-wide association study of severity in multiple sclerosis.


ABSTRACT: Multiple sclerosis (MS) is a chronic inflammatory disorder of the central nervous system with a strong genetic component. Several lines of evidence support a strong role for genetic factors influencing both disease susceptibility and clinical outcome in MS. Identification of genetic variants that distinguish particular disease subgroups and/or predict a severe clinical outcome is critical to further our understanding of disease mechanisms and guide development of effective therapeutic approaches. We studied 1470 MS cases and performed a genome-wide association study of more than 2.5 million single-nucleotide polymorphisms to identify loci influencing disease severity, measured using the MS severity score (MSSS), a measure of clinical disability. Of note, no single result achieved genome-wide significance. Furthermore, variants within previously confirmed MS susceptibility loci do not appear to influence severity. Although bioinformatic analyses highlight certain pathways that are over-represented in our results, we conclude that the genetic architecture of disease severity is likely polygenic and comprised of modest effects, similar to what has been described for MS susceptibility, to date. However, a role for major effects of rare variants cannot be excluded. Importantly, our results also show the MSSS, when considered as a binary or continuous phenotype variable is by comparison a stable outcome.

SUBMITTER: International Multiple Sclerosis Genetics Consortium 

PROVIDER: S-EPMC3640650 | biostudies-literature | 2011 Dec

REPOSITORIES: biostudies-literature

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Genome-wide association study of severity in multiple sclerosis.

Genes and immunity 20110609 8


Multiple sclerosis (MS) is a chronic inflammatory disorder of the central nervous system with a strong genetic component. Several lines of evidence support a strong role for genetic factors influencing both disease susceptibility and clinical outcome in MS. Identification of genetic variants that distinguish particular disease subgroups and/or predict a severe clinical outcome is critical to further our understanding of disease mechanisms and guide development of effective therapeutic approaches  ...[more]

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