ORIGINAL RESEARCH article
Front. Genet.
Sec. Genetics of Common and Rare Diseases
Volume 16 - 2025 | doi: 10.3389/fgene.2025.1607575
Identification of key modules and hub genes for sepsis-induced myopathy using weighted gene co-expression network analysis
Provisionally accepted
- Fujian Medical University, Fuzhou, China
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Background: Sepsis-induced myopathy (SIM) is a severe complication of sepsis, leading to significant muscle dysfunction and increased mortality. The molecular mechanisms underlying SIM remain poorly understood, necessitating comprehensive studies to identify potential therapeutic targets. This study aims to explore the molecular basis of SIM through gene expression analysis and bioinformatics approaches.In this study, we employed a lipopolysaccharide-induced mouse model to investigate the molecular basis of SIM. We conducted comprehensive RNA sequencing of the gastrocnemius muscle, which resulted in the identification of 1166 genes exhibiting altered expression levels. To further analyze the data, we applied weighted gene co-expression network analysis (WGCNA) to distinguish critical gene clusters associated with SIM. Additionally, we performed functional enrichment analyses using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) network approaches.: Our findings revealed that the identified gene clusters predominantly pertained to immune response, inflammation, and apoptosis pathways. Notably, validation through real-time quantitative polymerase chain reaction (RT-qPCR) confirmed the significant upregulation of key hub genes, including Cxcl10, Il6, and Stat1. Receiver Operating Characteristic (ROC) curve analysis further indicated the potential diagnostic utility of these hub genes. Additionally, leveraging the Connectivity Map (CMAP) database allowed us to predict six potential pharmacological agents-halcinonide, lomitapide, TG-101348, GSK-690693, loteprednol, and indacaterol-that might serve as therapeutic interventions for SIM. Conclusion: This research advances our understanding of the molecular basis of SIM, presenting new diagnostic biomarkers and potential drug targets. Further studies with larger clinical datasets are warranted to validate these findings and explore the therapeutic potential of the identified drugs.
Keywords: sepsis-induced myopathy, skeletal muscle, Hub genes, biomarkers, bioinformatics, WGCNA Sepsis-induced myopathy, WGCNA
Received: 07 Apr 2025; Accepted: 18 Jul 2025.
Copyright: © 2025 Lin, Kexin, Chen, Wu, Lian, Feng, Lin and Xie. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Siming Lin, Fujian Medical University, Fuzhou, China
Liangdi Xie, Fujian Medical University, Fuzhou, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.