ArticleJournal of inflammation research2020
Identification of Key Genes Associated with Changes in the Host Response to Severe Burn Shock: A Bioinformatics Analysis with Data from the Gene Expression Omnibus (GEO) Database.
Article in Journal of inflammation research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 30 citations in OpenAlex.
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- Statistical Study for the Prognostic Value of NLR Values in Patients with Severe Burns: A Study in the Service of Burns in Albania.Annals of burns and fire disasters · 2025Article
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- Role of MLIP in burn-induced sepsis and insights into sepsis-associated cancer progression.Frontiers in immunology · 2025Article
- Identification of novel hub genes and immune infiltration in atopic dermatitis using integrated bioinformatics analysis.Scientific reports · 2024Article
- Identification of Critical Genes Differentiating Stable and Unstable Atherosclerotic Plaques: A Bioinformatic and Computational Analysis.Current vascular pharmacology · 2024Article
- Blood leukocyte transcriptional modules and differentially expressed genes associated with disease severity and age in COVID-19 patients.Scientific reports · 2023Article
- Identification of hub genes significantly linked to subarachnoid hemorrhage and epilepsyFrontiers in neurology · 2023Article
- Identification of common signature genes and pathways underlying the pathogenesis association between nonalcoholic fatty liver disease and atherosclerosis.Frontiers in cardiovascular medicine · 2023Article
- Exploring the pathogenesis of colorectal carcinoma complicated with hepatocellular carcinoma via microarray data analysis.Frontiers in pharmacology · 2023Article
- Exploring the shared molecular mechanisms between systemic lupus erythematosus and primary Sjögren's syndrome based on integrated bioinformatics and single-cell RNA-seq analysis.Frontiers in immunology · 2023Article
- Exploring the inverse association of glioblastoma multiforme and Alzheimer's disease via bioinformatics analysis.Medical oncology (Northwood, London, England) · 2022Article
- Exploring the pathogenesis of diabetic kidney disease by microarray data analysis.Frontiers in pharmacology · 2022Article
- Identification of Important Modules and Biomarkers That Are Related to Immune Infiltration Cells in Severe Burns Based on Weighted Gene Co-Expression Network Analysis.Frontiers in genetics · 2022Article
- Identification of Novel Biomarkers With Diagnostic Value and Immune Infiltration in Burn Injury.Frontiers in genetics · 2022Article
- Inhibition of Matrix Metalloproteinase-8 Protects Against Sepsis Serum Mediated Leukocyte Adhesion.Frontiers in medicine · 2022Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPatients with severe burns continue to display a high mortality rate during the initial shock period. The precise molecular mechanism underlying the change in host response during severe burn shock remains unknown. This study aimed to identify key genes leading to the change in host response during burn shock.
methodsThe GSE77791 dataset, which was utilized in a previous study that compared hydrocortisone administration to placebo (NaCl 0.9%) in the inflammatory reaction of severe burn shock, was downloaded from the Gene Expression Omnibus (GEO) database and analyzed to identify the differentially expressed genes (DEGs). Functional enrichment analyses of Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed. The protein-protein interaction (PPI) network of DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) database and then visualized in Cytoscape. In addition, important modules in this network were selected using the Molecular Complex Detection (MCODE) algorithm, and hub genes were identified in cytoHubba, a Cytoscape plugin.
resultsA total of 1059 DEGs (508 downregulated genes and 551 upregulated genes) were identified from the dataset. The DEGs enriched in GO terms and KEGG pathways were related to immune response. The PPI network contained 439 nodes and 2430 protein pairs. Finally, important modules and hub genes were identified using the different Cytoscape plugins. The key genes in burn shock were identified as arginase 1 (
conclusionThe DEGs, functional terms and pathways, and hub genes identified in the present study can help shed light on the molecular mechanism underlying the changes in host response during burn shock and provide potential targets for early detection and treatment of burn shock.
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