Related Experiment Video
Updated: Jan 15, 2026
08:27
Bronchoalveolar Lavage Exosomes in Lipopolysaccharide-induced Septic Lung Injury
Published on: May 21, 2018
11.4K
Identification of Biomarkers for Sepsis-Induced Acute Lung Injury Through Bioinformatics and Machine Learning
Yannian Luo1, Juan Xu2, Nannan He1
1Department of Critical Care Medicine, The Second Hospital of Lanzhou University, Lanzhou, Gansu Province, People's Republic of China.
Journal of Inflammation Research
|October 10, 2025
Summary
This study identifies four key genes as potential diagnostic biomarkers for sepsis-induced acute lung injury (ALI). Resveratrol shows promise as a therapeutic agent by targeting these identified genes, offering new avenues for treatment.
Area of Science:
- Genomics and Bioinformatics
- Computational Biology
- Immunology
Background:
- Sepsis-induced acute lung injury (ALI) is a critical condition lacking reliable early diagnostic biomarkers.
- Machine learning (ML) can analyze high-dimensional gene expression data for biomarker discovery and therapeutic target identification.
Purpose of the Study:
- To identify novel diagnostic biomarkers for sepsis-induced ALI using gene expression data and ML.
- To explore potential therapeutic strategies targeting identified biomarkers.
Main Methods:
- Integrated analysis of multiple gene expression datasets (GSE10474, GSE32707, GSE66890, GSE10361, GSE3037).
- Differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA).
- Application of eight ML algorithms for diagnostic model development and validation, followed by molecular docking and in vitro experiments.
Main Results:
- Identified 213 overlapping genes between differentially expressed genes (DEGs) and WGCNA modules, enriched in immune and infection pathways.
- Selected four key genes (DDAH2, PNPLA2, STXBP2, TCN1) using ML algorithms, forming a robust diagnostic model.
- Resveratrol demonstrated stable binding to target genes and alleviated LPS-induced ALI in vitro.
Conclusions:
- The identified four genes (DDAH2, PNPLA2, STXBP2, TCN1) show potential as diagnostic biomarkers for sepsis-ALI.
- Resveratrol emerges as a promising therapeutic candidate for sepsis-ALI by targeting these core genes.
