Identity-by-Descent Mapping to Detect Rare Variants Conferring Susceptibility to Multiple Sclerosis
AuthorLin, Rui; Charlesworth, Jac; Stankovich, Jim; Perreau, Victoria M.; Brown, Matthew A.; Taylor, Bruce V.
Source TitlePLOS ONE
PublisherPUBLIC LIBRARY SCIENCE
University of Melbourne Author/sPerreau, Victoria; Bahlo, Melanie; Butzkueven, Helmut; Field, Judith; Kilpatrick, Trevor
AffiliationAnatomy and Neuroscience
Document TypeJournal Article
Access StatusThis item is currently not available from this repository
NHMRC Grant codeNHMRC/633275
Genome-wide association studies (GWAS) have identified around 60 common variants associated with multiple sclerosis (MS), but these loci only explain a fraction of the heritability of MS. Some missing heritability may be caused by rare variants that have been suggested to play an important role in the aetiology of complex diseases such as MS. However current genetic and statistical methods for detecting rare variants are expensive and time consuming. 'Population-based linkage analysis' (PBLA) or so called identity-by-descent (IBD) mapping is a novel way to detect rare variants in extant GWAS datasets. We employed BEAGLE fastIBD to search for rare MS variants utilising IBD mapping in a large GWAS dataset of 3,543 cases and 5,898 controls. We identified a genome-wide significant linkage signal on chromosome 19 (LOD = 4.65; p = 1.9x10(-6)). Network analysis of cases and controls sharing haplotypes on chromosome 19 further strengthened the association as there are more large networks of cases sharing haplotypes than controls. This linkage region includes a cluster of zinc finger genes of unknown function. Analysis of genome wide transcriptome data suggests that genes in this zinc finger cluster may be involved in very early developmental regulation of the CNS. Our study also indicates that BEAGLE fastIBD allowed identification of rare variants in large unrelated population with moderate computational intensity. Even with the development of whole-genome sequencing, IBD mapping still may be a promising way to narrow down the region of interest for sequencing priority.
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