Identification of Hub Genes With Differential Correlations in Sepsis

As a multifaceted syndrome, sepsis leads to high risk of death worldwide. It is difficult to be intervened due to insufficient biomarkers and potential targets. The reason is that regulatory mechanisms during sepsis are poorly understood. In this study, expression profiles of sepsis from GSE134347 w...

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Bibliographic Details
Main Authors: Feng, Q. (Author), Sheng, L. (Author), Tong, Y. (Author), Zhang, Y. (Author)
Format: Article
Language:English
Published: Frontiers Media S.A. 2022
Subjects:
Online Access:View Fulltext in Publisher
LEADER 01786nam a2200229Ia 4500
001 10-3389-fgene-2022-876514
008 220425s2022 CNT 000 0 und d
020 |a 16648021 (ISSN) 
245 1 0 |a Identification of Hub Genes With Differential Correlations in Sepsis 
260 0 |b Frontiers Media S.A.  |c 2022 
856 |z View Fulltext in Publisher  |u https://doi.org/10.3389/fgene.2022.876514 
520 3 |a As a multifaceted syndrome, sepsis leads to high risk of death worldwide. It is difficult to be intervened due to insufficient biomarkers and potential targets. The reason is that regulatory mechanisms during sepsis are poorly understood. In this study, expression profiles of sepsis from GSE134347 were integrated to construct gene interaction network through weighted gene co-expression network analysis (WGCNA). R package DiffCorr was utilized to evaluate differential correlations and identify significant differences between sepsis and healthy tissues. As a result, twenty-six modules were detected in the network, among which blue and darkred modules exhibited the most significant associations with sepsis. Finally, we identified some novel genes with opposite correlations including ZNF366, ZMYND11, SVIP and UBE2H. Further biological analysis revealed their promising roles in sepsis management. Hence, differential correlations-based algorithm was firstly established for the discovery of appealing regulators in sepsis. Copyright © 2022 Sheng, Tong, Zhang and Feng. 
650 0 4 |a biological analysis 
650 0 4 |a differential correlation 
650 0 4 |a regulatory network 
650 0 4 |a sepsis 
650 0 4 |a WGCNA 
700 1 |a Feng, Q.  |e author 
700 1 |a Sheng, L.  |e author 
700 1 |a Tong, Y.  |e author 
700 1 |a Zhang, Y.  |e author 
773 |t Frontiers in Genetics