Screening of core genes in neuroinflammation of sepsis associated encephalopathy based on bioinformatics analysis
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1.Department of Pathogen Biology,Medical College,Nantong University,Nantong 226001 ;2.Medical Research Center, Affiliated Hospital 2 of Nantong University,Jiangsu Provincial Medical Key Discipline(Laboratory)Cultivation Unit, Human Immunology,Nantong Municipal Key Laboratory of Metabolic,Immunology,and Disease Microenvironment, Nantong Municipal Medical Key Laboratory of Molecular Immunology,Nantong Clinical Medical College,Kangda College,Nanjing Medical University,Nantong 226001 ,China

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R742

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    Abstract:

    Objective:To identity core genes of neuroinflammation mediated by microglia in sepsis-associated encephalopathy (SAE)through bioinformatics analysis and validate them through in vitro cellular experiments. Methods:Transcriptomic datasets of peripheral blood from sepsis patients(GSE65682)and in vitro lipopolysaccharide(LPS)- stimulated microglial cell activation model (GSE103156)were obtained from the Gene Expression Omnibus(GEO)database. Weighted gene co-expression network analysis (WGCNA)was used to screen the modules significantly related to clinical diagnosis of sepsis in the GSE65682 dataset. The intersection between differentially expressed genes(DEG)in LPS-treated and untreated microglial cells from the GSE103156 dataset and the WGCNA modules was determined. Functional enrichment analysis of DEG was performed using gene ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG). A protein-protein interaction network was constructed using STRING,and core genes were screened by Cytoscape and Lasso regression analysis. An in vitro cellular activation model of LPS -induced BV2 microglial was established,and gene expression was detected using quantitative real -time PCR(RT-qPCR). Histone deacetylase 9(HDAC9)was overexpressed in microglia using the lentiviral vector method,and Western blot was employed to detect the inflammation related molecule expression. Results:The WGCNA analysis identified nine modules associated with the clinical diagnosis of sepsis in the GSE65682 dataset,comprising 332 genes. Limma analysis identified 1 272 DEGs in LPS-stimulated microglial cells from the GSE103156 dataset. Eighteen overlapping genes were obtained,and the Lasso regression analysis further selected four hub genes:G protein-coupled receptor 183(GPR183),HDAC9,nicotinamide adenine dinucleotide kinase(NADK),and leucine rich repeat containing 25(LRRC25). RT-qPCR confirmed downregulation of mRNA expression of Gpr183 and Hdac9 genes and upregulation of Lrrc25 expression in the inflammatory activation model of LPS-stimulated microglial cell,with no significant change in Nadk expression. Western blot showed that overexpression of HDAC9 promoted the expression of pro-inflammatory cytokines interleukin(IL)- 1β and inducible nitric oxide synthase(iNOS)in LPS-induced microglial cells and enhanced JAK1-STAT3 phosphorylation. Conclusion:This study identitfies four key genes mediating neuroinflammation in SAE through bioinformatics analysis and preliminarily demonstrates that HDAC9 has pro-inflammatory activity in microglia,providing new insights and data for further mechanistic research on SAE.

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苏思璇,尚彦星,段程伟,梁彩霞,张冬梅.基于生信分析对脓毒症相关性脑病中神经炎症相关核心基因的筛选[J].南京医科大学学报(自然科学版英文版),2024,(7):915-926.

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  • Received:December 02,2023
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  • Online: July 10,2024
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