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Genotype and phenotype in Multiple Sclerosis - potential for disease course prediction?
Citation
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]
Copyright Statement
Copyright Springer Science+Business Media, LLC, part of Springer Nature 2018
DOI: doi:10.1007/s11940-018-0505-6
Abstract
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 |
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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 |
Downloads: | 0 |
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