Bioinformatic Analysis Identifies Three Potentially Key Differentially Expressed Genes in Peripheral Blood Mononuclear Cells of Patients with Takayasu’s Arteritis

OBJECTIVE: This study aimed to identify several potentially key genes associated with the pathogenesis of Takayasu’s arteritis (TA). This identification may lead to a deeper mechanistic understanding of TA etiology and pave the way for potential therapeutic approaches. MATERIALS AND METHODS: In this experimental study, the microarray dataset GSE33910, which includes expression data for peripheral blood mononuclear cell (PBMC) samples isolated from TA patients and normal volunteers, was downloaded from the publicly accessible Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified in PBMCs of TA patients compared with normal controls. Gene ontology (GO) enrichment analysis of DEGs and analysis of protein-protein interaction (PPI) network were carried out. Several hub proteins were extracted from the PPI network based on node degrees and random walk algorithm. Additionally, transcription factors (TFs) were predicted and the corresponding regulatory network was constructed. RESULTS: A total of 932 DEGs (372 up- and 560 down-regulated genes) were identified in PBMCs from TA patients. Interestingly, up-regulated and down-regulated genes were involved in different GO terms and pathways. A PPI network of proteins encoded by DEGs was constructed and RHOA, FOS, EGR1, and GNB1 were considered to be hub proteins with both higher random walk score and node degree. A total of 13 TFs were predicted to be differentially expressed. A total of 49 DEGs had been reported to be associated with TA in the Comparative Toxicogenomics Database (CTD). The only TA marker gene in the CTD database was NOS2, confirmed by three studies. However, NOS2 was not significantly altered in the analyzed microarray dataset. Nevertheless,NOS3 was a significantly down-regulated gene and was involved in the platelet activation pathway. CONCLUSION: RHOA, FOS, and EGR1 are potential candidate genes for the diagnosis and therapy of TA.