Literature DB >> 35035698

Identification of key genes associated with sepsis patients infected by staphylococcus aureus through weighted gene co-expression network analysis.

Han Wu1, Haoting Chen2, Junjie Wang1, Shaohua Yin1, Jiaqian Huang1, Zhiqiang Wang1, Xiaojie Zhang3, Minghua Wang1,4.   

Abstract

The prevention and treatment of staphylococcus aureus septicemia is one of the thorniest problems in modern medicine. However, as the underlying pathogenesis of sepsis is still unclear, there is currently no golden standard for clinical diagnosis. In this study, we used GSE33341 dataset for differentially expressed gene (DEG) analysis and screened out 857 differentially expressed genes associated with staphylococcus aureus infection. The module having the highest correlation with clinical features of sepsis was screened by weighted gene co-expression network analysis (WGCNA). The genes in the selected module and the differentially expressed genes were represented in Venn diagram, and 59 pathogenic genes at the intersection were obtained. GO and KEGG analysis showed that these genes were mainly related to aerobic respiration, cellular stress response, mitochondrial electron transport, mitochondrial transport, oxidative phosphorylation. Kaplan-Meier was used to analyze the influence of the top 10 key genes on the prognosis of sepsis patients. The results showed that the high expression of NDUFA4, NDUFB3, COX7A2, ATP5J and COX7C was significantly correlated with the poor overall survival (OS) in patients with bacterial sepsis. These findings may potentially provide a reference for the diagnosis and treatment of bacterial septicemia. AJTR
Copyright © 2021.

Entities:  

Keywords:  Bacterial sepsis; differential analysis; staphylococcus aureus; survival analysis; weighted gene coexpression network

Year:  2021        PMID: 35035698      PMCID: PMC8748107     

Source DB:  PubMed          Journal:  Am J Transl Res        ISSN: 1943-8141            Impact factor:   4.060


  24 in total

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