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Mining the key genes for ventilator-induced lung injury using co-expression network analysis
Zhao Li1, Yajun Xiao2, Li Xu3
1Department of Anesthesiology, East Hospital, Tongji University School of Medicine, Shanghai, P.R. China.
Bioscience Reports
|March 9, 2021
Summary
Ventilator-induced lung injury (VILI) mechanisms were explored using gene expression data. Nine key genes were identified, offering potential targets for VILI prevention and treatment.
Area of Science:
- Biomedical Engineering
- Pulmonary Medicine
- Genomics
Background:
- Mechanical ventilation is crucial for anesthesia and respiratory failure but can cause lung injury (VILI).
- Understanding VILI pathogenesis is vital for developing effective prevention and treatment strategies.
Purpose of the Study:
- To identify key genes and molecular mechanisms underlying ventilator-induced lung injury (VILI).
- To integrate multi-dataset analysis for robust VILI-associated gene discovery.
Main Methods:
- Utilized Weighted Gene Co-Expression Network Analysis (WGCNA) on four integrated GEO microarray datasets (GSE9314, GSE9368, GSE11434, GSE11662).
- Identified differentially expressed genes (DEGs) using the limma package in R.
- Cross-referenced DEGs with WGCNA-identified hub genes to pinpoint key VILI-associated genes.
Main Results:
- Identified 49 VILI-associated co-expression network modules.
- Screened nine key genes (Tlr2, Hmox1, Serpine1, Mmp9, Il6, Il1b, Ptgs2, Fos, Atf3) significantly differing in VILI.
- Validated key gene expression differences using an independent dataset (GSE86229) and qPCR.
Conclusions:
- Successfully identified nine key genes implicated in ventilator-induced lung injury (VILI) through integrated bioinformatics analysis.
- These identified genes represent potential therapeutic targets for mitigating VILI.
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