Annals of the Academy of Medicine, Singapore · 2026
Selection of pyroptosis-related genes and potential pharmacological targets in sepsis-induced myopathy.
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Wang Dongfang, Xu Zhikai, Zhao Xuan, Liu Yukun, Wang Yuchang
Аннотация
INTRODUCTION: Sepsis-induced myopathy (SIM) is a severe complication contributing to long-term morbidity and mortality in sepsis survivors. Emerging evidence highlights the role of pyroptosis in SIM pathogenesis. This study aims to identify pyroptosis-related genes and potential pharmacological targets for SIM and explore their therapeutic implications.
METHOD: The GSE13205 dataset from the Gene Expression Omnibus database was analysed to identify differentially expressed pyroptosis-related genes in SIM. Gene Set Variation Analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to investigate the biological functions and associated pathways. Hub genes were identified through protein-protein interaction network analysis. The Connectivity Map (CMap) database was used to predict candidate therapeutic compounds targeting these genes.
RESULTS: A total of 39 pyroptosis-related genes were identified as differentially expressed in SIM. These genes were primarily associated with apoptosis, regulation of cell death, p53 signalling, circadian rhythm and responses to hypoxia and chemical stress. KEGG pathway analysis revealed enrichment in apoptosis, p53 signalling, microRNA in cancer and endocrine resistance pathways. Ten potential therapeutic compounds were predicted via CMap based on hub gene profiles. However, experimental validation of these compounds in the context of SIM is needed to assess their therapeutic efficacy.
CONCLUSION: This study identifies key pyroptosis-related genes and potential therapeutic compounds for SIM, providing new insights into its molecular mechanisms and suggesting novel strategies for treatment. Further experimental validation is required to confirm the clinical relevance and therapeutic potential of these findings.
METHOD: The GSE13205 dataset from the Gene Expression Omnibus database was analysed to identify differentially expressed pyroptosis-related genes in SIM. Gene Set Variation Analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to investigate the biological functions and associated pathways. Hub genes were identified through protein-protein interaction network analysis. The Connectivity Map (CMap) database was used to predict candidate therapeutic compounds targeting these genes.
RESULTS: A total of 39 pyroptosis-related genes were identified as differentially expressed in SIM. These genes were primarily associated with apoptosis, regulation of cell death, p53 signalling, circadian rhythm and responses to hypoxia and chemical stress. KEGG pathway analysis revealed enrichment in apoptosis, p53 signalling, microRNA in cancer and endocrine resistance pathways. Ten potential therapeutic compounds were predicted via CMap based on hub gene profiles. However, experimental validation of these compounds in the context of SIM is needed to assess their therapeutic efficacy.
CONCLUSION: This study identifies key pyroptosis-related genes and potential therapeutic compounds for SIM, providing new insights into its molecular mechanisms and suggesting novel strategies for treatment. Further experimental validation is required to confirm the clinical relevance and therapeutic potential of these findings.