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Step-by-Step Construction of Gene Co-Expression Network Analysis for Identifying Novel Biomarkers of Sepsis Occurrence and Progression

BACKGROUND: Sepsis is the leading cause of death in critically ill patients. Although it is well known that the immune system plays a key role in sepsis, exactly how it works remains unknown. METHODS: In our study, we used weighted gene co-expression network analysis (WGCNA) to screen out the immune...

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Detalles Bibliográficos
Autores principales: Yu, Xianqiang, Qu, Cheng, Ke, Lu, Tong, Zhihui, Li, Weiqin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8478343/
https://www.ncbi.nlm.nih.gov/pubmed/34594129
http://dx.doi.org/10.2147/IJGM.S328076
Descripción
Sumario:BACKGROUND: Sepsis is the leading cause of death in critically ill patients. Although it is well known that the immune system plays a key role in sepsis, exactly how it works remains unknown. METHODS: In our study, we used weighted gene co-expression network analysis (WGCNA) to screen out the immune-related genes that may play a critical role in the process of sepsis. RESULTS: A total of three sepsis-related hub genes were screened for further verification. Subsequent analysis of immune subtypes suggested their potential predictive effect in the clinic. CONCLUSION: Our study shows that three immune-related genes CHMP1A, MED15 and MGAT1 are important biomarkers of sepsis. The screened genes may help to distinguish normal individuals from patients with different degrees of sepsis.