Pathway-based association analysis of two genome-wide screening data identifies rheumatoid arthritis-related pathways.

The pathways can explain molecular mechanisms of complex diseases from the perspective of biology function. We carried out a genome-wide pathway-based association analysis to identify the risk pathways of rheumatoid arthritis (RA). First, we performed two genome-wide association studies using two RA data sets from GAW16 (Genetic Analysis Workshop 16) and the Wellcome Trust Case Control Consortium, and obtained risk P-value for each single-nucleotide polymorphism (SNP). Next, we mapped all the SNPs to genome-wide autosomal genes and calculated gene-wise risk values by minimum P-value method. We calculated the KEGG (Kyoto Encyclopedia of Gene and Genomes) pathway risk scores according to Fisher combination method and identified the significant pathways by permutation test. At last, we merged the results from the two pathway-based genome-wide association analyses to identify the high-risk pathways, which were found in both the data sets. The results showed that there were nine pathways, focal adhesion pathway, extracellular matrix-receptor interaction pathway, calcium signaling pathway, dopaminergic synapse pathway, long-term potentiation pathway, retrograde endocannabinoid signaling pathway, glutamatergic synapse pathway, cholinergic synapse pathway and morphine addiction pathway, associated with susceptibility to RA. Among these pathways, four pathways were reported as RA-risk pathways in the previous literatures. We also inferred that other five pathways may be related to RA. Further researches of these pathways will help us to understand the molecular mechanisms of RA.