More MS genes found

What has the genome still have to hide? #MSBlog #MSResearch

Epub: International Multiple Sclerosis Genetics Consortium Network-Based Multiple Sclerosis Pathway Analysis with GWAS Data from 15,000 Cases and 30,000 Controls. Am J Hum Genet. 2013 May 22.

Multiple sclerosis (MS) is an inflammatory CNS disease with a substantial genetic component, originally mapped to only the human leucocyte antigen (HLA) region (Transplantion=DNA fingerprinting antigen). In the last 5 years, a total of seven genome-wide association studies and one meta-analysis successfully identified 57 non-HLA susceptibility loci. Here, we merged nominal statistical evidence of association and physical evidence of interaction to conduct a protein-interaction-network-based pathway analysis (PINBPA) on two large genetic MS studies comprising a total of 15,317 cases and 29,529 controls. The distribution of nominally significant (marginally important) loci (genes) at the gene level matched the patterns of extended linkage disequilibrium (inherited together more often than would occur by chance) in regions of interest. We found that products of genome-wide significantly associated genes are more likely to interact physically and belong to the same or related pathways. We next searched for subnetworks (modules) of genes (and their encoded proteins) enriched with nominally associated loci within each study and identified those modules in common between the two studies. We demonstrate that these modules are more likely to contain genes with bona fide susceptibility variants and, in addition, identify several high-confidence candidates (including BCL10, CD48, REL, TRAF3, and TEC). PINBPA is a powerful approach to gaining further insights into the biology of associated genes and to prioritizing candidates for subsequent genetic studies of complex traits.


Gene hunters think that some genes that control susceptibility to MS work together in networks abit like you need elven players, some substitutes, a manager and fans to make a football team, Looking at networks they are finding more candiadate genes.

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