Bioinformatics-based study to identify immune infiltration and inflammatory-related hub genes as biomarkers for the treatment of rheumatoid arthritis.

Rheumatoid arthritis (RA) is a systemic autoimmune disease whose principal pathological change is aggressive chronic synovial inflammation; however, the specific etiology and pathogenesis have not been fully elucidated. We downloaded the synovial tissue gene expression profiles of four human knees from the Gene Expression Omnibus database, analyzed the differentially expressed genes in the normal and RA groups, and assessed their enrichment in functions and pathways using bioinformatics methods and the STRING online database to establish protein-protein interaction networks. Cytoscape software was used to obtain 10 hub genes; receiver operating characteristic (ROC) curves were calculated for each hub gene and differential expression analysis of the two groups of hub genes. The CIBERSORT algorithm was used to impute immune infiltration. We identified the signaling pathways that play important roles in RA and 10 hub genes: Ccr1, Ccr2, Ccr5, Ccr7, Cxcl5, Cxcl6, Cxcl13, Ccl13, Adcy2, and Pnoc. The diagnostic value of these 10 hub genes for RA was confirmed using ROC curves and expression analysis. Adcy2, Cxcl13, and Ccr5 are strongly associated with RA development. The study also revealed that the differential infiltration profile of different inflammatory immune cells in the synovial tissue of RA is an extremely critical factor in RA progression. This study may contribute to the understanding of signaling pathways and biological processes associated with RA and the role of inflammatory immune infiltration in the pathogenesis of RA. In addition, this study shows that Adcy2, Cxcl13, and Ccr5 have the potential to be biomarkers for RA treatment.

Fang S ，Xu X ，Zhong L ，Wang AQ ，Gao WL ，Lu M ，Yin ZS ... -  《-》

Identification of Disease-Specific Hub Biomarkers and Immune Infiltration in Osteoarthritis and Rheumatoid Arthritis Synovial Tissues by Bioinformatics Analysis.

Osteoarthritis (OA) and rheumatoid arthritis (RA) are well-known cause of joint disability. Although they have shown the analogous clinical features involving chronic synovitis that progresses to cartilage and bone destruction, the pathogenesis that initiates and perpetuates synovial lesions between RA and OA remains elusive. This study is aimed at identifying disease-specific hub genes, exploring immune cell infiltration, and elucidating the underlying mechanisms associated with RA and OA synovial lesion. Gene expression profiles (GSE55235, GSE55457, GSE55584, and GSE12021) were selected from Gene Expression Omnibus for analysis. Differentially expressed genes (DEGs) were identified by the "LIMMA" package in Bioconductor. The DEGs were identified by Gene Ontology (GO) and KEGG pathway analysis. A protein-protein interaction network was constructed to identify candidate hub genes by using STRING and Cytoscape. Hub genes were identified by validating from GSE12021. Furthermore, we employed the CIBERSORT website to assess immune cell infiltration between OA and RA. Finally, we explored the correlation between the levels of hub genes and relative proportion of immune cells in OA and RA. We identified 68 DEGs which were mainly enriched in immune response and chemokine signaling pathway. Six hub genes with a cutoff of AUC > 0.80 by ROC analysis and relative expression of P < 0.05 were identified successfully. Compared with OA, the RA synovial tissues consisted of a higher proportion of 7 immune cells, whereas 4 immune cells were found in relatively lower proportion (P < 0.05). In addition, the levels of 6 hub genes were closely associated with relative proportion of 11 immune cells in OA and RA. We used bioinformatics analysis to identify hub genes and explored immune cell infiltration of immune microenvironment in synovial tissues. Our results should offer insights into the underlying molecular mechanisms of synovial lesion and provide potential target for immune-based therapies of OA and RA.

Sun F ，Zhou JL ，Peng PJ ，Qiu C ，Cao JR ，Peng H ... -  《-》

Identification of differentially expressed genes, signaling pathways and immune infiltration in rheumatoid arthritis by integrated bioinformatics analysis.

Ge Y ，Zhou L ，Chen Z ，Mao Y ，Li T ，Tong P ，Shan L ... -  《HEREDITAS》

Identification of differential key biomarkers in the synovial tissue between rheumatoid arthritis and osteoarthritis using bioinformatics analysis.

Rheumatoid arthritis (RA) and osteoarthritis (OA) are two common joint diseases with similar clinical manifestations. Our study aimed to identify differential gene biomarkers in the synovial tissue between RA and OA using bioinformatics analysis and validation. GSE36700, GSE1919, GSE12021, GSE55235, GSE55584, and GSE55457 datasets were downloaded from the Gene Expression Omnibus database. A total of 57 RA samples and 46 OA samples were included. The differentially expressed genes (DEGs) were identified. The Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were also performed. Protein-protein interaction (PPI) network of DEGs and the hub genes were constructed and visualized via Search Tool for the Retrieval of Interacting Genes/Proteins, Cytoscape, and R. Selected hub genes were validated via reverse transcription-polymerase chain reaction. A total of 41 DEGs were identified. GO functional enrichment analysis showed that DEGs were enriched in immune response, signal transduction, regulation of immune response for biological process, in plasma membrane and extracellular region for cell component, and antigen binding and serine-type endopeptidase activity for molecular function. KEGG pathway analysis showed that DEGs were enriched in cytokine-cytokine receptor interaction and chemokine signaling pathway. PPI network analysis established 70 nodes and 120 edges and 15 hub genes were identified. The expression of CXCL13, CXCL10, and ADIPOQ was statistically different between RA and OA synovial tissue. Differential expression of CXCL13, CXCL10, and ADIPOQ between RA and OA synovial tissue may provide new insights for understanding the RA development and difference between RA and OA. Key Points • Bioinformatics analysis was used to identify the differentially expressed genes in the synovial tissue between rheumatoid arthritis and osteoarthritis. • CXCL13, CXCL10, and ADIPOQ might provide new insight for understanding the differences between RA and OA.

Zhang R ，Zhou X ，Jin Y ，Chang C ，Wang R ，Liu J ，Fan J ，He D ... -  《-》

Three hematologic/immune system-specific expressed genes are considered as the potential biomarkers for the diagnosis of early rheumatoid arthritis through bioinformatics analysis.

Cheng Q ，Chen X ，Wu H ，Du Y ... -  《Journal of Translational Medicine》