Abstract: Objective: To identify the key differentially expressed genes (DEGs) of Sjogren's syndrome (SS) by bioinformatics methods. Methods: The gene expression profiles of GSE23117 and GSE127952 were downloaded from the gene database, the DEGs were selected by GEO2R online tool and Venn diagram software. GO and KEGG analysis were carried out through DAVID website. The (PPI) network of protein-protein interaction was established by STRING tool, the module analysis was carried out by Cytoscape software. Results: A total of 31 overlapping regions of DEGs were detected in SS specimens, including 28 up-regulated genes and 3 down-regulated genes, which mainly played a role in immune inflammation. KEGG analysis showed that DEGs pathways were related to cytokine-cytokine receptor interaction, chemokine signaling pathway, amoebiasis and leukocyte transendothelial migration. PPI and module analysis showed that CXCL9, CXCL11, CXCL13, CCR1, CD69, PTPRC, GPR183, MMP9 and IL-10 genes were significantly enriched. Conclusion: CXCL9, CXCL11, CXCL13, CCR1, CD69, PTPRC, GPR183, MMP9 and IL-10 may be related to the onset and progress of SS. 

Key words: biological markers, gene expression profiles, Sjogren's syndrome