Discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis

Purpose: The goal of the study was to integrate verified signals from previous genetic association studies with gene expression and pathway analysis for discovery of new candidate genes and signalling networks, relevant for rheumatoid arthritis (RA). Method:RNA-seq based expression analysis of 377 genes from previously verified RA-associated loci was performed in blood cells from 5 newly diagnosed, non-treated RA patients, 7 patients with treated RA and 12 healthy controls. Differentially expressed genes sharing a similar expression pattern in treated and untreated RA sub-groups were selected for pathway analysis. A set of “connector” genes derived from pathway analysis was then tested for differential expression in the initial discovery cohort. Results: 11 qualifying genes were selected for pathway analysis and grouped into 2 evidence-based functional networks, containing 29 and 27 additional “connector” molecules. The expression of genes, corresponding to connector molecules was then tested in the initial RNA-seq data. 3 genes showed similar expression difference in both treated and non-treated RA patients and additional nine genes were differentially expressed in at least one patients' group compared to healthy controls. Conclusion: Integration of RNA-seq data with findings from association studies, and consequent pathway analysis implicate new candidate genes in the pathogenesis of RA. Overall design: Illumina RNA-seq was performed on RNA from pereferial blood mononuclear cells taken from 12 healthy individuals, 5 untreated RA patients, and 7 treated RA patients