Analysis of sepsis-related genes through weighted gene co-expression network
10.3760/cma.j.cn121430-20210127-00135
- VernacularTitle:通过加权基因共表达网络分析脓毒症相关基因
- Author:
Changqin CHEN
1
;
Li LI
;
Changyun ZHAO
;
Junhai ZHEN
;
Jing YAN
Author Information
1. 浙江医院重症医学科，浙江杭州 310013
- Keywords:
Sepsis;
Weighted gene co-expression network analysis;
Differentially expressed gene;
Key gene;
Protein-protein interaction network;
Functional enrichment a
- From:
Chinese Critical Care Medicine
2021;33(6):659-664
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To identify the Key genes in the development of sepsis through weighted gene co-expression network analysis (WGCNA).Methods:The gene expression dataset GSE154918 was downloaded from the public database Gene Expression Omnibus (GEO) database, which containes data from 105 microarrays of 40 control cases, 12 cases of asymptomatic infection, 39 cases of sepsis, and 14 cases of follow-up sepsis. The R software was used to screen out differentially expressed genes (DEG) in sepsis, and the distributed access view integrated database (DAVID), search tool for retrieval of interacting neighbouring genes (STRING) and visualization software Cytoscape were used to perform gene function and pathway enrichment analysis, Protein-protein interaction (PPI) network analysis and key gene analysis to screen out the key genes in the development of sepsis.Results:Forty-six candidate genes were obtained by WGCNA and combined with DEG expression analysis, and these 46 genes were analyzed by gene ontology (GO) and Kyoto City Encyclopedia of Genes and Genomes (KEGG) pathway enrichment to obtain gene functions and involved signaling pathways. The PPI network was further constructed using the STRING database, and 5 key genes were selected by the PPI network visualization software Cytoscape, including the mast cell expressed membrane protein 1 gene (MCEMP1), the S100 calcium-binding protein A12 gene (S100A12), the adipokine resistance factor gene (RETN), the c-type lectin structural domain family 4 member gene (CLEC4D), and peroxisome proliferator-activated receptor gene (PPARG), and differential expression analysis of each of these 5 genes showed that the expression levels of the above 5 genes were significantly upregulated in sepsis patients compared with healthy controls.Conclusion:In this study, 5 key genes related to sepsis were screened by constructing WGCNA method, which may be potential candidate targets related to sepsis diagnosis and treatment.
