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ORIGINAL RESEARCH article
Front. Mol. Med
Sec. Molecular Mechanisms of Neurodegeneration
Volume 5 - 2025 | doi: 10.3389/fmmed.2025.1369365
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Exposure to sevoflurane in neonatal rats disrupts energy metabolism during brain development, which is associated with anesthetic-induced neurodevelopmental toxicity. Hepatic fatty acid metabolism plays a critical role in response to brain energy supply. However, how sevoflurane exposure affect hepatic fatty acid metabolism remains unclear. In this study, multiple methods were used to analyze gene changes of hepatic fatty acid metabolism and immune cell infiltration after sevoflurane exposure in neonatal rats. Related-metabolic pathways and expression changes of DCHR24 in cholesterol metabolism were also deciphered. Significant differences were found in the expression levels of differentially sequenced genes and 15 fatty acid metabolism-related differential expressed genes between the two groups. A total of 40 genes related to gene ontology (GO) and 5 pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG) were significantly enriched. Gene set enrichment analysis (GSEA) and Gene set variation analysis (GSVA) showed that 130 GO gene sets and 5 KEGG pathways were significantly up-regulated, while 62 GO gene sets and 2 KEGG pathways were significantly down-regulated. According to the Friends analysis, Dhcr24 may play a more critical role in the pathway. The analysis of mRNA-miRNA-lncRNA networks revealed that certain genes in lncRNA and mRNA played crucial roles in the regulatory network. A total of 43 key gene-drug small molecule combinations with significant differences in IC50 were identified. Bioinformatics analysis identified effective diagnostic biomarkers for fatty acid metabolism and immune cell infiltration in rat liver after sevoflurane exposure. These findings provide a basis for searching for more specific targets against the neurodevelopmental toxicity of sevoflurane.
Keywords: sevoflurane, Neurodevelopmental toxicity, Hepatic fatty acid metabolism, Immune Cell Infiltration, Bioinformatics analysis
Received: 12 Jan 2024; Accepted: 20 Jan 2025.
Copyright: © 2025 Yuan, Lv, Fan, Jia, Wang, Hu, Sun, Chen and Zhang. 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:
Pengbo Zhang, Department of Anesthesiology, Second Affiliated Hospital of Xi'an Jiaotong University, Xi’an, 710004, Shaanxi Province, 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.
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