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Genotype and phenotype in Multiple Sclerosis - potential for disease course prediction?


Jokubaitis, VG and Zhou, Y and Butzkueven, H and Taylor, BV, Genotype and phenotype in Multiple Sclerosis - potential for disease course prediction?, Current Treatment Options in Neurology, 20, (6) Article 18. ISSN 1092-8480 (2018) [Refereed Article]

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Copyright Springer Science+Business Media, LLC, part of Springer Nature 2018

DOI: doi:10.1007/s11940-018-0505-6


Purpose of Review: This review will examine the current evidence that genetic and/or epigenetic variation may influence the multiple sclerosis (MS) clinical course, phenotype, and measures of MS severity including disability progression and relapse rate.

Recent Findings: There is little evidence that MS clinical phenotype is under significant genetic control. There is increasing evidence that there may be genetic determinants of the rate of disability progression. However, studies that can analyse disability progression and take into account all the confounding variables such as treatment, clinical characteristics, and environmental factors are by necessity longitudinal, relatively small, and generally of short duration, and thus do not lend themselves to the assessment of hundreds of thousands of genetic variables obtained from GWAS. Despite this, there is recent evidence to support the association of genetic loci with relapse rate.

Summary: Recent progress suggests that genetic variations could be associated with disease severity, but not MS clinical phenotype, but these findings are not definitive and await replication. Pooling of study results, application of other genomic techniques including epigenomics, and analysis of biomarkers of progression could functionally validate putative severity markers.

Item Details

Item Type:Refereed Article
Keywords:genotype, multiple sclerosis, phenotype, severity
Research Division:Biomedical and Clinical Sciences
Research Group:Neurosciences
Research Field:Central nervous system
Objective Division:Health
Objective Group:Clinical health
Objective Field:Clinical health not elsewhere classified
UTAS Author:Zhou, Y (Mr Yuan Zhou)
UTAS Author:Taylor, BV (Professor Bruce Taylor)
ID Code:126476
Year Published:2018
Web of Science® Times Cited:4
Deposited By:Menzies Institute for Medical Research
Deposited On:2018-06-14
Last Modified:2019-12-03

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