Abstract
IntroductionRheumatoid arthritis (RA) is a systemic autoimmune disease in which T cells play a pivotal role in the pathogenesis. Knowledge in terms of the CD4 T-cell transcriptome in RA is limited. The aim of this study was to examine the whole-genome transcription profile of CD4 T cells in RA by comparing patients with RA to healthy controls.MethodsPeripheral blood CD4 T cells were isolated from 53 RA patients with active disease and 45 healthy individuals; 13 cases and 10 controls were enrolled in microarray analysis. The remaining 40 cases and 35 controls were recruited as an independent cohort for the validation study. Bioinformatics was performed on Gene Ontology (GO), gene-gene interaction networks, and pathway analysis. The gene modules, by combining the results from GO, gene networks, and pathway analysis, were selected for further validation.ResultsThe CD4 T cells showed 1,496 differentially expressed (DE) genes in RA patients relative to healthy individuals. GO analysis revealed that the DE genes were enriched in immune response, T-cell response, apoptosis process, and Wnt receptor signaling. Pathway analysis also identified that ‘Wnt signaling pathway’ was differentially regulated between two groups (P = 2.78 × 10−10). By gene-gene network analysis, we found that the DE genes were enriched in T-cell receptor (TCR), JAK-STAT signaling, and Wnt signaling pathway. By gene module analysis, we found that a number of DE genes overlapped in the three different analyses. In total, 23 genes were selected for further validation, and nine genes were confirmed. Of these, four genes (SOCS3, CBL, IFNAR1, and PIK3CA) were involved in STAT3 (signal transducer and activator of transcription 3) signaling, and three genes (CBL, KLF9, and CSNK2A1) were involved in the Wnt signaling pathway. Additionally, several zinc finger transcription factors (ZEB1, ZNF292, and ZNF644) were confirmed.ConclusionsWe report here the first case–control study of the CD4 T-cell transcriptome profile in RA. Our data provide evidence that CD4 T cells from patients with RA have abnormal functional networks in STAT3 signaling and Wnt signaling. Our results also suggest that the aberrant expression of several zinc finger transcription factors (ZEB1, ZNF292, and ZNF644) may be potential pathogenic factors for RA.Electronic supplementary materialThe online version of this article (doi:10.1186/s13075-015-0590-9) contains supplementary material, which is available to authorized users.
Highlights
Rheumatoid arthritis (RA) is a systemic autoimmune disease in which T cells play a pivotal role in the pathogenesis
A number of transcriptome studies have focused on peripheral blood mononuclear cells (PBMCs) or fibroblast-like synoviocytes (FLSs) to understand the aberrant biological pathways involved in the pathogenesis of RA [4,5,6,7,8,9]
CD4 T-cell transcriptome in patients with active rheumatoid arthritis versus healthy controls The transcriptome profiles of CD4 T cells from 13 cases with active RA and nine healthy controls were accessed by microarrays
Summary
Rheumatoid arthritis (RA) is a systemic autoimmune disease in which T cells play a pivotal role in the pathogenesis. The aim of this study was to examine the whole-genome transcription profile of CD4 T cells in RA by comparing patients with RA to healthy controls. To gain insight into the molecular signature underlying disease pathogenesis, gene expression profiling studies have emerged as a powerful way to comprehensively identify the genes that are differentially expressed in blood and tissues between patients and healthy individuals [3]. To better understand the complex molecular mechanisms and discover the potential predictive biomarkers for RA, we performed a case–control study of CD4 T-cell transcriptome analysis by comparing RA patients to healthy controls. We found a great difference in gene expression profiling of CD4 T cells between active RA cases and healthy controls and discovered several aberrant signaling pathways in CD4 T cells from patients with RA. By quantitative real-time polymerase chain reaction (qPCR) validation, we identified nine genes involved in STAT3 (signal transducer and activator of transcription 3) signaling, Wnt signaling pathway, and zinc finger transcription regulation
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