[Integrated bioinformatics analysis of key genes in allergic rhinitis]

Objective: To obtain biomarkers of allergic rhinitis (AR) by performing bioinformatics analysis on gene chips related to allergic rhinitis in the Gene Expression Database (GEO). Methods: From June 2018 to December 2019, we downloaded data (GSE46171) involving 3 control individuals and 6 AR patients from the publicallyavailable Gene Expression Omnibus database (GEO,http://www.ncbi.nlm.nih.gov/geo), and differentially expressed genes (DEGs) were screened between AR and normal tissues by using the GEO2R online tool comprehensively. Then, we used the bioinformatics methods, including Gene Ontology (GO) analysis and Kyoto Encyclopedia of Gene, Genome (KEGG) pathway analysis and protein-protein interaction (PPI) network construction to identify key genes in AR. In the same period, the inferior turbinate mucosa tissues of 15 AR patients and 15 healthy controls were collected during operationinthe Department of Otolaryngology Head and Neck Surgery of the People 's Hospital of Wuhan Universityto further verify important genes and pathways and perform real-time quantitative PCR.SPSS9.0 statistical software was used for statistical analysis. Results: Two hundred and seventeen DEGs genes were selected, of which 112 were down-regulated genes and 105 were up-regulated genes. Among them, the five up-regulated genes with the most significant differences were KLK7, TMPRSS11A, SPRR2C, TPSAB1, and TXLNGY; the five down-regulated genes with the most significant differences were: XIST, CTAG1A, PRB1, CXCL11 and PRB2. By constructing a PPI network among 217 DEGs, the 15 hub genes obtained were IFIH1, CCR2, CD80, TLR7, EIF1AY, DDX3Y, RSAD2, RPS4Y2, RPS4Y1, XAF1, KDM5D, ZFY, NLGN4Y, IFIT5 and DDX60L, these Genes were at a hub in a gene network. We collected inferior turbinate mucosa tissue during surgery,and these 15 genes were verified, and the expressions of IFIH1, CCR2, CD80, TLR7, RSAD2, XAF1, IFIT5 and DDX60L were reduced, wherea the expressions of EIF1AY, DDX3Y, RPS4Y2, RPS4Y1, KDM5D, ZFY and NLGN4Y were increased, differences were statistically significant (all P<0.05). Conclusions: The study finds 217 genes closely related to allergic rhinitis and obtains 15 hub genes through the PPI network. These genes may be involved in the pathogenesis of allergic rhinitis and are expected to become new biomarkers for allergic rhinitis.