AUTHOR=Zhang Runrun , Jin Yehua , Chang Cen , Xu Lingxia , Bian Yanqin , Shen Yu , Sun Yang , Sun Songtao , Schrodi Steven J. , Guo Shicheng , He Dongyi 

TITLE=RNA-seq and Network Analysis Reveal Unique Chemokine Activity Signatures in the Synovial Tissue of Patients With Rheumatoid Arthritis

JOURNAL=Frontiers in Medicine

VOLUME=9

YEAR=2022

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2022.799440

DOI=10.3389/fmed.2022.799440

ISSN=2296-858X

ABSTRACT=<sec><title>Purpose</title><p>This study aimed to provide a comprehensive understanding of the genome-wide expression patterns in the synovial tissue samples of patients with rheumatoid arthritis (RA) to investigate the potential mechanisms regulating RA occurrence and development.</p></sec><sec><title>Methods</title><p>Transcription profiles of the synovial tissue samples from nine patients with RA and 15 patients with osteoarthritis (OA) (control) from the East Asian population were generated using RNA sequencing (RNA-seq). Gene set enrichment analysis (GSEA) was used to analyze all the detected genes and the differentially expressed genes (DEGs) were identified using DESeq. To further analyze the DEGs, the Gene Ontology (GO) functional enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. The protein–protein interaction (PPI) network of the DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and the hub genes were identified by topology clustering with the Molecular Complex Detection (MCODE)-Cytoscape. The most important hub genes were validated using quantitative real-time PCR (qRT-PCR).</p></sec><sec><title>Results</title><p>Of the 17,736 genes detected, 851 genes were identified as the DEGs (474 upregulated and 377 downregulated genes) using the false discovery rate (FDR) approach. GSEA revealed that the significantly enriched gene sets that positively correlated with RA were CD40 signaling overactivation, Th1 cytotoxic module, overactivation of the immune response, adaptive immune response, effective vs. memory CD8+ T cells (upregulated), and naïve vs. effective CD8+ T cells (downregulated). Biological process enrichment analysis showed that the DEGs were significantly enriched for signal transduction (<italic>P</italic> = 3.01 × 10<sup>−6</sup>), immune response (<italic>P</italic> = 1.65 × 10<sup>−24</sup>), and inflammatory response (<italic>P</italic> = 5.76 × 10<sup>−10</sup>). Molecule function enrichment analysis revealed that the DEGs were enriched in calcium ion binding (<italic>P</italic> = 1.26 × 10<sup>−5</sup>), receptor binding (<italic>P</italic> = 1.26 × 10<sup>−5</sup>), and cytokine activity (<italic>P</italic> = 2.01 × 10<sup>−3</sup>). Cellular component enrichment analysis revealed that the DEGs were significantly enriched in the plasma membrane (<italic>P</italic> = 1.91 × 10<sup>−31</sup>), an integral component of the membrane (<italic>P</italic> = 7.39 × 10<sup>−13</sup>), and extracellular region (<italic>P</italic> = 7.63 × 10<sup>−11</sup>). The KEGG pathway analysis showed that the DEGs were enriched in the cytokine–cytokine receptor interaction (<italic>P</italic> = 3.05 × 10<sup>−17</sup>), chemokine signaling (<italic>P</italic> = 3.50 × 10<sup>−7</sup>), T-cell receptor signaling (<italic>P</italic> = 5.17 × 10<sup>−4</sup>), and RA (<italic>P</italic> = 5.17 × 10<sup>−4</sup>) pathways. We confirmed that RA was correlated with the upregulation of the PPI network hub genes, such as <italic>CXCL13, CXCL6, CCR5, CXCR5, CCR2, CXCL3</italic>, and <italic>CXCL10</italic>, and the downregulation of the PPI network hub gene such as <italic>SSTR1</italic>.</p></sec><sec><title>Conclusion</title><p>This study identified and validated the DEGs in the synovial tissue samples of patients with RA, which highlighted the activity of a subset of chemokine genes, thereby providing novel insights into the molecular mechanisms of RA pathogenesis and identifying potential diagnostic and therapeutic targets for RA.</p></sec>