ArticleBioengineered2021
Consensus analysis via weighted gene co-expression network analysis (WGCNA) reveals genes participating in early phase of acute respiratory distress syndrome (ARDS) induced by sepsis.
Article in Bioengineered, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- Potential role of a three-gene signature in predicting diagnosis in patients with myocardial infarction.Bioengineered · 2021Pooled it
- Peptide IRW upregulates ACE2 in spontaneously hypertensive rats via dopamine/D1R signaling pathway.Journal of advanced research · 2026Article
- Mechanisms and therapeutics of immunometabolic reprogramming driving macrophage-ECs interactions in sepsis-associated ARDS from the gut-lung axis perspective.Frontiers in immunology · 2026Review
- Screening and experimental study of potential biomarkers for ulcerative colitis based on weighted gene co-expression network analysis and machine learning.Journal of translational medicine · 2025Article
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- Cancer predisposition signaling in Beckwith-Wiedemann Syndrome drives Wilms tumor development.British journal of cancer · 2024Article
- Role of Cellular Senescence Genes and Immune Infiltration in Sepsis and Sepsis-Induced ARDS Based on Bioinformatics Analysis.Journal of inflammation research · 2024Article
- P2X7 receptor antagonist A-438079 alleviates oxidative stress of lung in LPS-induced septic rats.Purinergic signalling · 2023Article
- A novel pyroptosis gene expression-based risk score for survival in gastric cancer.Frontiers in endocrinology · 2023Article
- The effect of N6-methyladenosine (m6A) factors on the development of acute respiratory distress syndrome in the mouse model.Bioengineered · 2022Article
- The Application of Consensus Weighted Gene Co-expression Network Analysis to Comparative Transcriptome Meta-Datasets of Multiple Sclerosis in Gray and White Matter.Frontiers in neurology · 2022Article
- Identification of Hub Genes With Differential Correlations in Sepsis.Frontiers in genetics · 2022Article
- Bioinformatics Analysis Identifies TNFRSF1A as a Biomarker of Liver Injury in Sepsis TNFRSF1A is a Biomarker for Septic Liver Injury.Genetics research · 2022Article
- Special electromagnetic field-treated water and far-infrared radiation alleviates lipopolysaccharide-induced acute respiratory distress syndrome in rats by regulating haptoglobin.Bioengineered · 2021Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The understanding of mechanism during conversion from sepsis to sepsis-related ARDS remains limited. In this study, we collected gene expression matrix from the Gene Expression Omnibus (GEO) database and constructed networks using weighted gene co-expression network analysis (WGCNA) to identify the consensus and opposite modules between sepsis and sepsis-induced ARDS and obtained 27 consensus modules associated with sepsis and sepsis-related ARDS, including one model (160 genes) with opposite correlation and 1 sepsis-ARDS specific model with 34 genes. Differentially expressed genes analysis, functional enrichment and protein-protein interactions analyses of candidate genes were performed; 15 of these genes showed different expressions in sepsis-induced ARDS patients, compared with sepsis patients; genes were enriched in processes associated with ribosome, tissue mechanics and extracellular matrix. Feature selection analysis revealed that three genes,
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