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Evidence for CRHR1 in multiple sclerosis using supervised machine learning and meta-analysis in 12,566 individuals.

Authors :
Briggs FB
Bartlett SE
Goldstein BA
Wang J
McCauley JL
Zuvich RL
De Jager PL
Rioux JD
Ivinson AJ
Compston A
Hafler DA
Hauser SL
Oksenberg JR
Sawcer SJ
Pericak-Vance MA
Haines JL
Barcellos LF
Source :
Human molecular genetics [Hum Mol Genet] 2010 Nov 01; Vol. 19 (21), pp. 4286-95. Date of Electronic Publication: 2010 Aug 10.
Publication Year :
2010

Abstract

The primary genetic risk factor in multiple sclerosis (MS) is the HLA-DRB1*1501 allele; however, much of the remaining genetic contribution to MS has yet to be elucidated. Several lines of evidence support a role for neuroendocrine system involvement in autoimmunity which may, in part, be genetically determined. Here, we comprehensively investigated variation within eight candidate hypothalamic-pituitary-adrenal (HPA) axis genes and susceptibility to MS. A total of 326 SNPs were investigated in a discovery dataset of 1343 MS cases and 1379 healthy controls of European ancestry using a multi-analytical strategy. Random Forests, a supervised machine-learning algorithm, identified eight intronic SNPs within the corticotrophin-releasing hormone receptor 1 or CRHR1 locus on 17q21.31 as important predictors of MS. On the basis of univariate analyses, six CRHR1 variants were associated with decreased risk for disease following a conservative correction for multiple tests. Independent replication was observed for CRHR1 in a large meta-analysis comprising 2624 MS cases and 7220 healthy controls of European ancestry. Results from a combined meta-analysis of all 3967 MS cases and 8599 controls provide strong evidence for the involvement of CRHR1 in MS. The strongest association was observed for rs242936 (OR = 0.82, 95% CI = 0.74-0.90, P = 9.7 × 10(-5)). Replicated CRHR1 variants appear to exist on a single associated haplotype. Further investigation of mechanisms involved in HPA axis regulation and response to stress in MS pathogenesis is warranted.

Details

Language :
English
ISSN :
1460-2083
Volume :
19
Issue :
21
Database :
MEDLINE
Journal :
Human molecular genetics
Publication Type :
Academic Journal
Accession number :
20699326
Full Text :
https://doi.org/10.1093/hmg/ddq328