Objective: As the most prevalent type of rhinitis, allergic rhinitis is consisted of seasonal allergic rhinitis (SAR) and perennial allergic rhinitis. This study is carried out for revealing the mechanisms of SAR.
Methods: Microarray data set GSE43523 (including 7 SAR nasal epithelial cells and 5 nonallergic control nasal epithelial cells) was extracted from Gene Expression Omnibus database. Based on limma package, differential expression analysis for the 2 groups was performed to obtain differentially expressed genes (DEGs). Using Multifaceted Analysis Tool for Human Transcriptome online tool, the functions involving the DEGs were predicted by enrichment analysis. Combined with Cytoscape software, protein-protein interaction (PPI) network was built and a significant network module was acquired. In addition, transcription factor (TF)-target and miRNA-target pairs were predicted using WebGestalt tool, and then TF-miRNA-target regulatory network was built by Cytoscape software.
Results: There were 274 DEGs between rhinitis and control samples, including 144 upregulated genes and 130 downregulated genes. After PPI for the DEGs was built, a significant network module was identified. In the TF-miRNA-target regulatory network, ABCA1, CPEB4, CD69, MIR-17-5P, and CREB had higher degrees. Furthermore, both ABCA1 and CD69 were targeted by MIR-17-5P in the regulatory network.
Conclusion: CPEB4 and CREB might be implicated in the pathogenesis of SAR. Besides, MIR-17-5P might also act in SAR via targeting ABCA1 and CD69.
Keywords: differentially expressed genes; enrichment analysis; protein–protein interaction network; regulatory network; seasonal allergic rhinitis.