Pathway and network-based analysis of genome-wide association studies in multiple sclerosis

Abstract

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 genes 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 identified, we report here for the first time the potential involvement of neural pathways in MS susceptibility.

Genetic architecture of wood properties based on association analysis and co‐expression networks in white spruce

“…The aim of GWAS is to gain insight into the genetic architecture of such traits through the identification of common genetic variants against the background of random variation in a population (Baranzini et al ., 2009). One of the challenges of GWAS is that the exceedingly large number of tests and the required stringent statistical criteria typically result in very few associations that exceed a genome threshold of significance after correction for multiple testing (Greenawalt et al ., 2012).…”

“…Furthermore, most of the single nucleotide polymorphisms (SNP) variants identified in GWAS provide little or no direct causation into the molecular, cellular or physiological processes underlying the phenotype of interest. Recent studies have shown that innovative approaches may be developed to complement and overcome some of the limitations of association studies and thus optimize the discovery of causative genetic variants (Baranzini et al ., 2009; Chan et al ., 2011; Greenawalt et al ., 2012). …”

“…Protein interaction network‐based pathway analysis was proposed as a strategy to further reduce the large lists of these genes and refine the results of GWAS (Baranzini et al ., 2009). In A. thaliana , network co‐expression approaches were used for the identification of novel genes that affect defense metabolism (Chan et al ., 2011).…”

“…In A. thaliana , network co‐expression approaches were used for the identification of novel genes that affect defense metabolism (Chan et al ., 2011). Even when the phenotypic effect of each SNP is very small, grouping significant genes according to their function shows that many of these genes contribute together to the same physiological process or a regulatory network (Baranzini et al ., 2009). …”

Pathway-based identification of SNPs predictive of survival

“…1-3 Baranzini et al have implemented this approach in the analysis of multiple sclerosis by using a network-based analysis to tease out SNPs with association P-values between 0.05 and 10 À8 in the original single-SNP association analysis. 4 Ballard et al performed two pathway-based tests, a binomial test and a random set method to identify pathways associated with rheumatoid arthritis. 5 Wang et al utilized a modified gene set enrichment method for SNP data to identify pathways associated with Crohn's disease.…”