ArticleMedical science monitor : international medical journal of experimental and clinical research2020
Bioinformatics Analysis Identifies Hub Genes and Molecular Pathways Involved in Sepsis-Induced Myopathy.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 9 citations in OpenAlex.
- A comparative analysis of HMGB1 and pCTS-L immunomodulatory properties in human peripheral blood mononuclear cells.Frontiers in immunology · 2026Article
- Inflammatory Alterations to Renal Lymphatic Endothelial Cell Gene Expression in Mouse Models of Hypertension.Kidney & blood pressure research · 2024Article
- Screening of ferroptosis-related genes in sepsis-induced liver failure and analysis of immune correlation.PeerJ · 2022Article
- Identification of key genes and pathways of BMP-9-induced osteogenic differentiation of mesenchymal stem cells by integrated bioinformatics analysis.Journal of orthopaedic surgery and research · 2021Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND Sepsis-induced myopathy (SIM) is a complication of sepsis that results in prolonged mechanical ventilation, long-term functional disability, and increased patient mortality. This study aimed to use bioinformatics analysis to identify hub genes and molecular pathways involved in SIM, to identify potential diagnostic or therapeutic biomarkers. MATERIAL AND METHODS The Gene Expression Omnibus (GEO) database was used to acquire the GSE13205 expression profile. The differentially expressed genes (DEGs) in cases of SIM and healthy controls, and the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using the limma R/Bioconductor software package and clusterProfiler package in R, respectively. The protein-protein interaction (PPI) network data of DEGs was retrieved using the STRING database and analyzed using the Molecular Complex Detection (MCODE) Cytoscape software plugin. RESULTS A total of 196 DEGs were obtained in SIM samples compared with healthy samples, including 93 upregulated genes. The DEGs were significantly upregulated in mineral absorption, and the interleukin-17 (IL-17) signaling pathway and 103 down-regulated genes were associated with control of the bile secretion signaling pathway. A protein-protein interaction (PPI) network was constructed with 106 nodes and 192 edges. The top two important clusters were selected from the PPI by MCODE analysis. There were 16 hub genes with a high degree of connectivity in the PPI network that were selected, including heme oxygenase 1 (HMOX1), nicotinamide adenine dinucleotide phosphate quinone dehydrogenase 1 (NQO1), and metallothionein (MT)-1E. CONCLUSIONS Bioinformatics network analysis identified key hub genes and molecular mechanisms in SIM.
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