Haplotype-based approach to known MS-associated regions increases the amount of explained risk

Abstract

Genome-wide association studies (GWAS), using single nucleotide polymorphisms (SNPs), have yielded 110 nonhuman leucocyte antigen genomic regions that are associated with multiple sclerosis (MS). Despite this large number of associations, however, only 28% of MSheritability can currently be explained. Here we compare the use of multi-SNP-haplotypes to the use of single- SNPs as alternative methods to describe MS genetic risk. SNP-haplotypes (of various lengths from 1 up to 15 contiguous SNPs) were constructed at each of the 110 previously identified, MS-associated, genomic regions. Even after correcting for the larger number of statistical comparisons made when using the haplotype-method, in 32 of the regions, the SNP-haplotype based model was markedly more significant than the single-SNP based model. By contrast, in no region was the single-SNP based model similarly more significant than the SNPhaplotype based model. Moreover, when we included the 932 MS-associated SNP-haplotypes (that we identified from 102 regions) as independent variables into a logistic linear model, the amount of MSheritability, as assessed by Nagelkerke's R-squared, was 38%, which was considerably better than 29%, which was obtained by using only single-SNPs. This study demonstrates that SNP-haplotypes can be used to finemap the genetic associations within regions of interest previously identified by single-SNP GWAS. Moreover, the amount of the MS genetic risk explained by the SNPhaplotype associations in the 110 MS-associated genomic regions was considerably greater when using SNP-haplotypes than when using single-SNPs. Also, the use of SNP-haplotypes can lead to the discovery of new regions of interest, which have not been identified by a single-SNP GWAS.