Clinical Focus ›› 2021, Vol. 36 ›› Issue (9): 811-819.doi: 10.3969/j.issn.1004-583X.2021.09.010

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Analysis of bioinformatics in pediatric influenza based on chip with high-throughput

Jin Hong, Li Xiaolan()   

  1. Department of Pediatrics, Taikang Tongji (Wuhan) Hospital, Wuhan 430050, China
  • Received:2021-05-21 Online:2021-09-20 Published:2021-10-05
  • Contact: Li Xiaolan E-mail:1138914165@qq.com

Abstract:

Objective To screen the related differential genes(DEGs) of pediatric influenza by bioinformatics tools, aiming to explore core genes and elucidate pathogenesis. Methods The transcriptome data of pediatric influenza that met the requirements were downloaded from gene expression omnibus(GEO) database, and DEGs were screened by gene analysis tool GEO2R. Gene ontology(GO) and Kyoto encyclopedia of genes and genomes(KEGG) were analyzed for the function and enrichment pathway of DEGs. The protein-protein interaction(PPI) network was constructed by using the STRING database, and the core differential genes were selected by using Cytoscape software. Results A total of four databases (GSE42026, GSE29366, GSE34205 and GSE38900) and 30 DEGs were included in the study with 29 down regulated and 1 up regulated. GO analysis showed that DEGs were mainly involved in type I IFN signaling pathway, cell response to type I IFN, 2'-5'-oligoadenylate synthase activation and double stranded RNA binding. KEGG analysis showed that DEGs were mainly enriched in influenza A virus, measles, hepatitis C and herpes simplex virus infection signaling pathways. PPI analysis showed that the potential 10 core genes were IFIT3, MX1, OAS3, OAS2, OAS1, IFI27, IFI44, RSAD2, IFI44L and LY6E. Conclusion Interferon centered gene enrichment pathway may be the main pathogenesis for pediatric influenza. The core genes screened out may participate in the infection process of children with influenza, and become a new target for clinical treatment.

Key words: influenza, human, influenza core genes, differential gene, computational biology

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