Integrated analysis of transcriptomics to identify hub genes in primary Sjögren's syndrome.

OBJECTIVE

The treatment of patients with primary Sjögren's syndrome is a clinical challenge. Gene expression profile analysis and comprehensive network methods for complex diseases can provide insight into molecular characteristics in the clinical context.

MATERIALS AND

METHODS

We downloaded gene expression datasets from the Gene Expression Omnibus (GEO) database. We screened differentially expressed genes (DEG) between the pSS patients and the controls by the robust rank aggregation (RRA) method. We explored DEGs' potential function using gene function annotation and PPI network analysis.

RESULTS

GSE23117, GSE40611, GSE80805, and GSE127952 were included, including 38 patients and 30 controls. The RRA integrated analysis determined 294 significant DEGs (241 upregulated and 53 downregulated), and the most significant gene aberrantly expressed in SS was CXCL9 (p = 6.39E-15), followed by CXCL13 (p = 1.53E-13). Immune response (GO:0006955; p = 4.29E-32) was the most significantly enriched biological process in GO (gene ontology) analysis. KEGG pathway enrichment analysis showed that cytokine-cytokine receptor interaction (hsa04060; p = 6.46E-10) and chemokine signaling pathway (hsa04062; p = 9.54E-09) were significantly enriched. We defined PTPRC, CD86, and LCP2 as the hub genes based on the PPI results.

CONCLUSION

Our integrated analysis identified gene signatures and helped understand molecular changes in pSS.