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This study aimed to investigate the molecular mechanism of systemic vasculitis via bioinformatics analysis. Gene express profile of E-GEOD-16945 (13 Takayasu arteritis samples and 13 control samples) was downloaded from European Bioinformatics Institute (EBI) database. Differentially expressed genes (DEGs) were screened between Takayasu arteritis and normal controls (|log FC| > 1). Basic local alignment search tool (BLASTX) was used for the Clusters of Orthologous Groups (COG) classification of DEGs. Gene ontology analysis was performed for the DEGs (P < 0.05). A gene expression network was built with DEGs. Mcode in Cytoscape software was used to extract modules from the network (degree ≥ 2, K-core ≥ 2 and adjusted P-value < 0.05) followed by pathway analysis using GenMAPP (false discovery rate < 0.05). A total of 747 DEGs were identified. There were 16 significant GO function terms enriched with DEGs, of which immune and defence response was the most significant GO term. Totally, three modules were extracted from gene expression network, including one module constituted with upregulated genes and two modules constituted with downregulated genes. Furthermore, human leucocyte antigen (HLA)-DRB1, HLA-DPA1, HLA-DPB1, HLA-DOA and HLA-DRA in the downregulated modules were significantly linked to immune-related pathways (intestinal immune network for IgA production and systemic lupus erythematosus pathways), while ribosomal protein L 31 (RPL31), RPS3A and RPL9 in the upregulated module were enriched in ribosome pathway. The immune-related pathways, ribosome pathway, immune-related genes including (HLA-DRB1, HLA-DPA1, HLA-DPB1, HLA-DOA and HLA-DRA) and ribosome-related genes (RPL31, RPS3A and RPL9) might be involved in systemic vasculitis.