Identifying Immune Cell Infiltration and Effective Diagnostic Biomarkers in Rheumatoid Arthritis by Bioinformatics Analysis

Abstract

BackgroundRheumatoid arthritis (RA) is a chronic systemic autoimmune disorder characterized by inflammatory cell infiltration, leading to persistent synovitis and joint destruction. The pathogenesis of RA remains unclear. This study aims to explore the immune molecular mechanism of RA through bioinformatics analysis.MethodsFive microarray datasets and a high throughput sequencing dataset were downloaded. CIBERSORT algorithm was performed to evaluate immune cell infiltration in synovial tissues between RA and healthy control (HC). Wilcoxon test and Least Absolute Shrinkage and Selection Operator (LASSO) regression were conducted to identify the significantly different infiltrates of immune cells. Differentially expressed genes (DEGs) were screened by “Batch correction” and “RobustRankAggreg” methods. Functional correlation of DEGs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Candidate biomarkers were identified by cytoHubba of Cytoscape, and their diagnostic effectiveness was predicted by Receiver Operator Characteristic Curve (ROC) analysis. The association of the identified biomarkers with infiltrating immune cells was explored using Spearman’s rank correlation analysis in R software.ResultsTen significantly different types of immune cells between RA and HC were identified. A total of 202 DEGs were obtained by intersection of DEGs screened by two methods. The function of DEGs were significantly associated with immune cells. Five hub genes (CXCR4, CCL5, CD8A, CD247, and GZMA) were screened by R package “UpSet”. CCL5+CXCR4 and GZMA+CD8A were verified to have the capability to diagnose RA and early RA with the most excellent specificity and sensitivity, respectively. The correlation between immune cells and biomarkers showed that CCL5 was positively correlated with M1 macrophages, CXCR4 was positively correlated with memory activated CD4+ T cells and follicular helper T (Tfh) cells, and GZMA was positively correlated with Tfh cells.ConclusionsCCL5, CXCR4, GZMA, and CD8A can be used as diagnostic biomarker for RA. GZMA-Tfh cells, CCL5-M1 macrophages, and CXCR4- memory activated CD4+ T cells/Tfh cells may participate in the occurrence and development of RA, especially GZMA-Tfh cells for the early pathogenesis of RA.

[Retracted] Identification of Diagnostic Biomarkers, Immune Infiltration Characteristics, and Potential Compounds in Rheumatoid Arthritis

“…The synovium is the main target tissue of RA. Several studies reported the hub genes of RA in bioinformatics [ 26 – 33 ]. These reports also showed that hub genes have a certain diagnostic value in RA.…”

“…Six datasets were obtained from the Gene Expression Omnibus (GEO) database [ 29 – 33 ], which were all sampled from the synovium. These datasets are detailed in Table 1 .…”

“…The synovial tissue is of interest for gene analysis in RA. In several previous studies on RA, bioinformatic analyses have been performed with the following research objectives: identifying key genes for diagnosis [ 26 – 33 ], immune infiltration [ 28 , 31 – 33 ], and therapeutic targets [ 26 , 32 ]; however, the sample size of these studies was not very large, and the research content that integrates these three research objectives is lacking. Therefore, various bioinformatic tools were used in this study to analyse differentially expressed gene (DEG) data between patients with RA and healthy individuals from the comprehensive gene expression database [ 34 – 38 ].…”

Analysis of Sepsis Markers and Pathogenesis Based on Gene Differential Expression and Protein Interaction Network

“…The main function of TCR is to recognize and bind the MHC antigen peptide complex, while CD3 further transfers the signal recognized by TCR into T lymphocytes to induce T lymphocyte activation, and the TCR/CD3 membrane expression level determines the initiation of T lymphocyte activation. Studies have shown that the gene CD247 is also involved in other autoimmune diseases, such as systemic lupus erythematosus [ 16 , 17 ], rheumatoid arthritis [ 18 ], and systemic sclerosis [ 19 ], which shows that CD247 is closely related to the occurrence of autoimmune diseases. The expression of CD247 can affect the development of T cells and lead to abnormal activation of T lymphocytes.…”

Novel Insights Into Gene Signatures and Their Correlation With Immune Infiltration of Peripheral Blood Mononuclear Cells in Behcet’s Disease

“…For subsequent analysis, we rigorously chose the turquoise module as a candidate module which gains highest correlation coefficient and significant corresponding p value with clinical features among patients suffering Behcet's disease and healthy controls. Recently, a few of studies have comprehensively utilize WGCNA to filtrate synergistically altered gene sets in autoimmune diseases (14)(15)(16)(17)(18). Up till now, amassed structure and function of single protein fragmented our comprehension of their intracellular interactions and pathogenesis pathways.…”