Dissecting the Imbalance of Synovial Macrophages in Rheumatoid Arthritis

Altern Ther Health Med. 2023 Oct;29(7):434-439.

Abstract

Objective: This study sought to identify candidate genes of rheumatoid arthritis (RA) synovial macrophages using bioinformatics and to explore their pathways in the pathogenesis of RA.

Methods: The microarray datasets GSE10500 and GSE97779 were obtained from the Gene Express Omnibus and analyzed with synovial macrophages of 14 RA patients and 8 healthy donors. The researchers used R software to identify differentially expressed genes and determine functional enrichment pathways. A protein-protein interaction network was then constructed using STRING and Cytoscape. Gene expression was validated with the GSE71370 dataset and RT-qPCR analysis.

Results: 102 DEGs were identified in RA synovial macrophages relative to normal samples. Of these, 72 were upregulated; 30 were downregulated. GO and KEGG pathway analyses suggested that DEGs mainly regulated the immune response and signaling pathways associated with inflammatory activation, apoptosis, and cancer. The top five hub genes and top 1 gene module from the PPI network of DEGs were VEGFA, MMP9, FN1, IGF1, CXCL9, ISG20, RSAD2, IFI27, GBP2, and GBP1. The GSE71370 dataset and RT-qPCR analysis showed that CXCL9 and GBP1 were significantly upregulated (P ≤ .05).

Conclusions: CXCL9 and GBP1 may contribute to RA pathogenesis and serve as potential biomarkers and therapeutic targets for RA.

MeSH terms

  • Arthritis, Rheumatoid* / genetics
  • Gene Expression Profiling*
  • Gene Regulatory Networks
  • Humans
  • Protein Interaction Maps / genetics
  • Transcriptome