Genome-wide association studies (GWAS) testing several hundred thousand SNPs have been performed in
multiple sclerosis (MS) and other complex diseases. Typically, the number of markers in which the evidence
for association exceeds the genome-wide significance threshold is very small, and markers that do not
exceed this threshold are generally neglected. Classical statistical analysis of these datasets in MS revealed
genes with known immunological functions. However, many of the markers showing modest association
may represent false negatives. We hypothesize that certain combinations of genes flagged by these markers
can be identified if they belong to a common biological pathway. Here we conduct a pathway-oriented analysis
of two GWAS in MS that takes into account all SNPs with nominal evidence of association (
P
<
0.05). Gene-wise
P
-values were superimposed on a human protein interaction network and searches were conducted to identify
sub-networks containing a higher proportion of gen
es associated with MS than expected by chance. These
sub-networks, and others generated at random as a control, were categorized for membership of biological
pathways. GWAS from eight other diseases were analyzed to assess the specificity of the pathways identified.
In the MS datasets, we identified sub-networks of genes from several immunological pathways including cell
adhesion, communication and signaling. Remarkably, neural pathways, namely axon-guidance and synaptic
potentiation, were also over-represented in MS. In addition to the immunological pathways previously ident-
ified, we report here for the first time the potential involvement of neural pathways in MS susceptibility.