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Objective To screen the differentially expressed genes (DEGs) of ankylosing spondylitis (AS) by bioinformatic analysis and make literature review for their functions. Methods The data about genome microarray of AS were retrieved from the Gene Expression Omnibus (GEO) database, and then employed to screen out DEGs between synovial biopsies from AS and undifferentiated spondylitis patients and the samples from healthy individuals and osteoarthritis patients by GEO2R. The DEGs were then subjected to Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis in DAVID 6.8 database. Finally, protein-protein interaction (PPI) network was constructed by STRING10.5 and then further analyzed by the Cytoscape software. Results A total of 190 differential genes were screened out, of which 75 were up-regulated and 115 were down-regulated. GO analysis showed that the obtained DGEs were mainly involved in inflammatory response, leukocyte migration, extracellular domain, extracellular region, extracellular matrix, lipoprotein particle binding and carbohydrate binding. KEGG analysis suggested that these DGEs were enriched in rheumatoid arthritis and cytokine-cytokine receptor interaction, and others. The PPI network was constructed by STRING database. And then, with the aid of Cytoscape, 12 Hub genes with highest degree of ankylosing spondylitis (including CXCR4, SELL, CD79A, MMP3, CD68, ADIPOQ, CCL19, IL-7R, IL-1β, MYH14, APOE and FCGR3A) were screened out. What's more, 41 transcription factors (TFs) interacting with the above 12 Hub genes, including ETS1, GATA3, IRF8 and so on were screened out with the iRegulon, a plugin in Cytoscape. Conclusion The firstly selected 12 Hub genes and 41 TFs may play important roles in pathogenesis of AS, and are regarded as new biomarkers for the diagnosis and treatment for AS.