Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0036690 (sepsis)
 59,461 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

We aimed to identify crucial genes relevant to the development of consecutive trauma-induced sepsis.A microarray dataset was used to identify genes differentially expressed between peripheral blood samples from consecutive traumatized patients complicated with sepsis and not complicated with sepsis. The dataset GSE12624 was obtained from Gene Expression Omnibus, containing 34 peripheral blood samples from consecutive traumatized patients complicated by sepsis and 36 consecutive traumatized controls. The differentially expressed genes (DEGs) were identified using Linear Models for Microarray Data package. Then, gene ontology (GO) enrichment analysis for DEGs was performed by Onto-Express. Subsequently, the protein-protein interaction (PPI) network was constructed and pathway enrichment analysis was performed by Search Tool for the Retrieval of Interacting Genes (STRING). Furthermore, protein complexes in the PPI network were predicted by ClusterONE and validated through GO and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses, and protein domain analysis.Totally, 446 upregulated and 447 downregulated DEGs were identified. Some DEGs were related to acyl-CoA binding (eg, ACBD6), chromosome, and centromeric region (eg, CENPN). In the PPI network, some DEGs were enriched in renin-angiotensin system (RAS, eg, AGTR1 and AGTR2). Three predicted protein complexes were validated in the PPI network. Some genes composing protein complex A were associated with cell proliferation (eg, CDC20, CCNB1, MCM4, RPA2, and PRIM2), and several genes composing protein complex F were implicated in regulation of actin cytoskeleton (eg, PFN2, ARPC2, and WASL).The results suggest that those DEGs may be crucial in the etiology of consecutive trauma-induced sepsis, and they are expected to be therapeutic targets.
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PMID:Identification of genes related to consecutive trauma-induced sepsis via gene expression profiling analysis. 2964 83