RNA Sequencing identifies three new candidate genes in RA pathogenesis

Through integration of RNA-sequencing data with association study findings, researchers identified ERBB2, TP53 and THOP1 as new candidate genes in the pathogenesis of rheumatoid arthritis.

In the blood cells of five patients newly diagnosed with rheumatoid arthritis (RA), seven patients with treated RA and 12 healthy controls, Leonid Padyukov, MD, PhD, a researcher and group leader in the Rheumatology Unit of the Karolinska Institute in Sweden, and colleagues performed RNA-sequencing-based expression analysis of 377 genes from loci previously associated with RA. For pathway analysis, they selected 11 differentially expressed genes with a similar expression pattern in treated and untreated RA. In a set of 56 connector genes derived from pathway analysis, they tested for differential expression in the initial discovery cohort and then validated expression in peripheral blood mononuclear cells from 73 patients with RA and 35 healthy controls.

Researchers found differential expression of ERBB2, TP53 and THOP1 was similar in both patients treated and untreated for RA. Compared with healthy controls, an additional nine genes were differentially expressed in at least one group of patients. In an independent collection of blood cell samples from healthy controls and non-treated patients with RA, the expression profiles of the three genes were replicated in RNA-sequencing data.

Pathway-based analysis of differentially expressed genes reveals new candidate genes for RA


a A network derived from experimental data for immune cells containing corresponding input molecules for six genes, which were differentially expressed in whole blood RNA-sequencing (RNA-seq) data (Ingenuity Pathway Analysis (IPA)). b A network derived from experimental data with no tissue filter applied, containing corresponding input molecules for eight genes, which were differentially expressed in whole blood according to RNA-seq data. Coloured shapes represent genes previously associated with RA, which were also DE in RNA-seq data (input data) – expression log2 fold change is represented with colour intensity (red increased expression in patients with RA; blue decreased expression in patients with RA) and a corresponding value (RA patients versus healthy controls); white shapes represent interaction molecules; solid lines direct interaction evidence; broken lines indirect interaction evidence; *verified differentially expressed connector molecules, IPA

Source – Healio Rheumatology – by Will Offit

Shchetynsky K, Diaz-Gallo LM, Folkersen L, Hensvold AH, Catrina AI, Berg L, Klareskog L, Padyukov L. (2017) Discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis. Arthritis Res Ther 19(1):19. [article]

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