Abstract
Multiple sclerosis (MS) is characterized as an autoimmune demyelinating disease. Numerous family studies have confirmed a strong genetic component underlying its etiology. After several decades of frustrating research, the advent and application of affordable genotyping of dense SNP maps in large datasets has ushered in a new era in which rapid progress is being made in our understanding of the genetics underlying many complex traits. For MS, one of the first discoveries to emerge in this new era was the association with rs6897932[T244I] in the interleukin-7 receptor alpha chain (
IL7RA
) gene (
Gregory et al. 2007
;
International Multiple Sclerosis Genetics Consortium 2007
;
Lundmark 2007
), a discovery that was accompanied by functional data that suggest this variant is likely to be causative rather than a surrogate proxy (
Gregory et al. 2007
). We hypothesized that variations in other genes functionally related to
IL7RA
might also influence MS. We investigated this hypothesis by examining genes in the extended biological pathway related to
IL7RA
to identify novel associations. We identified 73 genes with putative functional relationships to
IL7RA
and subsequently genotyped 7,865 SNPs in and around these genes using an Illumina Infinium BeadChip assay. Using 2,961 case-control dataset, two of the gene regions examined,
IL7
and
SOCS1
, had significantly associated single-nucleotide polymorphisms (SNPs) that further replicated in an independent case-control dataset (4,831 samples) with joint p-values as high as 8.29×10
-6
and 3.48×10
-7
, respectively, exceeding the threshold for experiment-wise significance. Our results also implicate two additional novel gene regions that are likely to be associated with MS:
PRKCE
with p-values reaching 3.47×10
-4
and
BCL2
with p-values reaching 4.32×10
-4
. The
TYK2
gene, which also emerged in our analysis, has recently been associated with MS (
Ban et al. 2009
). These results help to further delineate the genetic architecture of MS and validate our pathway approach as an effective method to identify novel associations in a complex disease.
