Identification of novel genes in Behcet’s disease using integrated bioinformatic analysis

Abstract

AbstractBehcet’s disease (BD) is a chronic vascular inflammatory disease. However, the etiology and molecular mechanisms underlying BD development have not been thoroughly understood. Gene expression data for BD were obtained from the Gene Expression Omnibus database. We used robust rank aggregation (RRA) to identify differentially expressed genes (DEGs) between patients with BD and healthy controls. Gene ontology functional enrichment was used to investigate the potential functions of the DEGs. Protein–protein interaction (PPI) network analysis was performed to identify the hub genes. Receiver operating characteristic analyses were performed to investigate the value of hub genes in the diagnosis of BD. GSE17114 and GSE61399 datasets were included, comprising 32 patients with BD and 26 controls. The RRA integrated analysis identified 44 significant DEGs among the GSE17114 and GSE61399 CD4 + T lymphocytes. Functional enrichment analysis revealed that protein tyrosine/threonine phosphatase activity and immunoglobulin binding were enriched in BD. PPI analysis identified FCGR3B as a hub gene in the CD4 + T lymphocytes of BD patients. Our bioinformatic analysis identified new genetic features, which will enable further understanding of the pathogenesis of BD.