Differentially expressed genes between systemic sclerosis and rheumatoid arthritis

Abstract

Background: Evidence is accumulating to characterise the key differences between systemic sclerosis (SSc) and rheumatoid arthritis (RA), which are similar but distinct systemic autoimmune diseases. However, the differences at the genetic level are not yet clear. Therefore, the aim of the present study was to identify key differential genes between patients with SSc and RA.

Methods: The Gene Expression Omnibus database was used to identify differentially expressed genes (DEGs) between SSc and RA biopsies. The DEGs were then functionally annotated using Gene Ontology (GO) terms and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways with the Database for Annotation, Visualization and Integrated Discovery (DAVID) tools. A protein-protein interaction (PPI) network was constructed with Cytoscape software. The Molecular Complex Detection (MCODE) plugin was also used to evaluate the biological importance of the constructed gene modules.

Results: A total of 13,556 DEGs were identified between the five SSc patients and seven RA patients, including 13,465 up-regulated genes and 91 down-regulated genes. Interestingly, the most significantly enriched GO terms of up- and down-regulated genes were related to extracellular involvement and immune activity, respectively, and the top six highly enriched KEGG pathways were related to the same processes. In the PPI network, the top 10 hub nodes and top four modules harboured the most relevant genes contributing to the differences between SSc and RA, including key genes such as IL6, EGF, JUN, FGF2, BMP2, FOS, BMP4, LRRK2, CTNNB1, EP300, CD79, and CXCL13.

Conclusions: These genes such as IL6, EGF, JUN, FGF2, BMP2, FOS, BMP4, LRRK2, CTNNB1, EP300, CD79, and CXCL13 can serve as new targets for focused research on the distinct molecular pathogenesis of SSc and RA. Furthermore, these genes could serve as potential biomarkers for differential diagnoses or therapeutic targets for treatment.

Keywords: Differentially expressed genes; Gene expression data; Key genes; Microarray; Rheumatoid arthritis; Systemic sclerosis.

Fig. 1

Heatmap of the 13,556 differentially expressed genes (DEGs) between systemic sclerosis and rheumatoid arthritis

Fig. 2

Gene Ontology enrichment analyses. a Gene Ontology enrichment of up-regulated genes. b Gene Ontology enrichment of down-regulated genes. The criteria for enrichment were: P-value < 0.05, FDR < 0.05, and fold enrichment > 1. Each gene was assigned to at least six terms

Fig. 3

Protein–protein interaction network constituted by differentially expressed genes identified in this study. Red nodes represent up-regulated genes, and green nodes represent down-regulated genes

Fig. 4

Four significant modules identified from the protein–protein interaction network using the molecular complex detection method with a score > 6.0: Module 1 (MCODE score = 18), Module 2 (MCODE score = 11), Module 3 (MCODE score = 8.035), and Module 4 (MCODE score = 7.048)