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:
Original Research
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
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author Yu, Xianqiang
Qu, Cheng
Ke, Lu
Tong, Zhihui
Li, Weiqin
author_facet Yu, Xianqiang
Qu, Cheng
Ke, Lu
Tong, Zhihui
Li, Weiqin
author_sort Yu, Xianqiang
collection PubMed
description 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.
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spelling pubmed-84783432021-09-29 Step-by-Step Construction of Gene Co-Expression Network Analysis for Identifying Novel Biomarkers of Sepsis Occurrence and Progression Yu, Xianqiang Qu, Cheng Ke, Lu Tong, Zhihui Li, Weiqin Int J Gen Med Original Research 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. Dove 2021-09-24 /pmc/articles/PMC8478343/ /pubmed/34594129 http://dx.doi.org/10.2147/IJGM.S328076 Text en © 2021 Yu et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Yu, Xianqiang
Qu, Cheng
Ke, Lu
Tong, Zhihui
Li, Weiqin
Step-by-Step Construction of Gene Co-Expression Network Analysis for Identifying Novel Biomarkers of Sepsis Occurrence and Progression
title Step-by-Step Construction of Gene Co-Expression Network Analysis for Identifying Novel Biomarkers of Sepsis Occurrence and Progression
title_full Step-by-Step Construction of Gene Co-Expression Network Analysis for Identifying Novel Biomarkers of Sepsis Occurrence and Progression
title_fullStr Step-by-Step Construction of Gene Co-Expression Network Analysis for Identifying Novel Biomarkers of Sepsis Occurrence and Progression
title_full_unstemmed Step-by-Step Construction of Gene Co-Expression Network Analysis for Identifying Novel Biomarkers of Sepsis Occurrence and Progression
title_short Step-by-Step Construction of Gene Co-Expression Network Analysis for Identifying Novel Biomarkers of Sepsis Occurrence and Progression
title_sort step-by-step construction of gene co-expression network analysis for identifying novel biomarkers of sepsis occurrence and progression
topic Original Research
url 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
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