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Modelling genetic susceptibility to multiple sclerosis with family data


O'Gorman, C and Lin, R and Stankovich, J and Broadley, SA, Modelling genetic susceptibility to multiple sclerosis with family data, Neuroepidemiology, 40, (1) pp. 1-12. ISSN 0251-5350 (2013) [Refereed Article]

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Copyright Statement

Copyright 2013 S. Karger AG, Basel

DOI: doi:10.1159/000341902


A genetic contribution to susceptibility is well established in multiple sclerosis (MS) and 57 associated genetic loci have been identified. We have undertaken a meta-analysis of familial risk studies with the aims of providing definitive figures for risks to relatives, performing a segregation analysis and estimating the proportion of the overall genetic risk that currently identified genes represent. We have used standard methods of meta-analysis combined with novel approaches to age adjustment to provide directly comparable estimates of lifetime risk. The overall recurrence risk for monozygotic twins was 18.2% and for siblings 2.7%. The recurrence risk for dizygotic twins was significantly higher than for siblings. The overall estimate of sibling relative risk (λS) was 16.8. Risks for older relatives (parents, siblings, aunts, uncles and cousins) show a latitudinal gradient, in line with population risk. No latitudinal gradient for λS was seen. Segregation analysis supports a multiplicative model of one locus of moderate effect with many loci of small effect. The estimated contribution of the 57 known MS loci is 18-24% of λS. This meta-analysis supports the notion of MS being in part the result of multiple genetic susceptibility factors and environmental factors.

Item Details

Item Type:Refereed Article
Keywords:familial risk, genetics, multiple sclerosis, relative risk, recurrence risk
Research Division:Biomedical and Clinical Sciences
Research Group:Immunology
Research Field:Immunogenetics (incl. genetic immunology)
Objective Division:Health
Objective Group:Clinical health
Objective Field:Clinical health not elsewhere classified
UTAS Author:Lin, R (Ms Lin)
UTAS Author:Stankovich, J (Dr Jim Stankovich)
ID Code:85098
Year Published:2013
Web of Science® Times Cited:73
Deposited By:Menzies Institute for Medical Research
Deposited On:2013-06-13
Last Modified:2017-11-07

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