#MSBlog: There is more to our genome than meets the eye; a new data analysis technique uncovers rare variants.
Epub: Lin et al. Identity-by-Descent Mapping to Detect Rare Variants Conferring Susceptibility to Multiple Sclerosis. PLoS One. 2013;8(3):e56379. doi: 10.1371/journal.pone.0056379.
Background: 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.
Methods: ‘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. This study 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.
Results: They identified a genome-wide significant linkage signal on chromosome 19 (LOD = 4.65; p = 1.9×10). 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.
Conclusions: This study 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.
“A large part of MS is in our genes, finding these has been a long and hard job. Despite a large number of variants that can explain a part of the heritability of MS a large component is missing. Genomics experts believe this is missing part is due to rare variants, i.e. variants that are found in less than 1% of the population. This study describes a new method for searching for these variants in existing data sets. Why is this important? We need to be able identify members of the population that are at very high-risk of getting MS so that we can target prevention at them.”