PubMed · 2013 · 17 citations · 20 references
Life SciencesBioinformaticsMolecular BiologyGene ExpressionGene Expression AnalysisGenomicsDifferential Expression AnalysisDifferential Gene Expression AnalysisGene Expression ProfilingCellular Component EnrichmentDifferential Expression EnrichmentDifferential Gene ExpressionEnrichment AnalysisGene Expression Network AnalysisMicroarray Differential Expression Analysis
OBJECTIVES: The purpose of this study was to identify differentially expressed genes (DEGs) related to acute lung injury (ALI) induced by sepsis with DNA microarray. MATERIALS AND METHODS: Gene expression profile GSE10474 was downloaded from Gene Expression Omnibus (GEO) database which includes 34 samples, among which 13 patients with ALI + sepsis and 21 patients with sepsis alone. The DEGs were identified between ALI + sepsis and sepsis alone samples using R, which were further analyzed using bioinformatics methods. Firstly, HitPredict was used to search protein-protein interactions of the DEGs. Secondly, WebGestalt was adopted for functional enrichment analysis of genes in the interaction networks. Finally, DNA methylation was analyzed to explain the differential expression. RESULTS: A total of 12 genes were identified as DEGs by comparing chip data from ALI + sepsis samples and those from sepsis alone samples, among which occludin (OCLN) and major histocompatibility complex, class II, DQ beta 1 (HLA-DQB1) had 21 and 6 interactors, respectively. Functional enrichment analysis revealed several significantly over-represented terms: cellular component organization, macromolecular organization and biosynthesis, and response to stimulus. In addition, methylation was found in the promoters of OCLN and HLA-DQB1. CONCLUSIONS: We screened DEGs in septic ALI samples, and several interesting genes were obtained, especially OCLN and HLA-DQB1. They may be developed into marker genes for diagnosis or treatment of ALI.
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