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Hippocampal gene expression patterns in Sevoflurane anesthesia associated neurocognitive disorders: A bioinformatic analysis
BACKGROUND: Several studies indicate general anesthetics can produce lasting effects on cognitive function. The commonly utilized anesthetic agent Sevoflurane has been implicated in neurodegenerative processes. The present study aimed to identify molecular underpinnings of Sevoflurane anesthesia lin...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9763458/ https://www.ncbi.nlm.nih.gov/pubmed/36561300 http://dx.doi.org/10.3389/fneur.2022.1084874 |
Sumario: | BACKGROUND: Several studies indicate general anesthetics can produce lasting effects on cognitive function. The commonly utilized anesthetic agent Sevoflurane has been implicated in neurodegenerative processes. The present study aimed to identify molecular underpinnings of Sevoflurane anesthesia linked neurocognitive changes by leveraging publically available datasets for bioinformatics analysis. METHODS: A Sevoflurane anesthesia related gene expression dataset was obtained. Sevoflurane related genes were obtained from the CTD database. Neurocognitive disorders (NCD) related genes were downloaded from DisGeNET and CTD. Intersecting differentially expressed genes between Sevoflurane and NCD were identified as cross-talk genes. A protein-protein interaction (PPI) network was constructed. Hub genes were selected using LASSO regression. Single sample gene set enrichment analysis; functional network analysis, pathway correlations, composite network analysis and drug sensitivity analysis were performed. RESULTS: Fourteen intersecting cross-talk genes potentially were identified. These were mainly involved in biological processes including peptidyl-serine phosphorylation, cellular response to starvation, and response to gamma radiation, regulation of p53 signaling pathway, AGE-RAGE signaling pathway and FoxO signaling. Egr1 showed a central role in the PPI network. Cdkn1a, Egr1, Gadd45a, Slc2a1, and Slc3a2 were identified as important or hub cross-talk genes. Among the interacting pathways, Interleukin-10 signaling and NF-kappa B signaling enriched among Sevoflurane-related DEGs were highly correlated with HIF-1 signaling enriched in NCD-related genes. Composite network analysis showed Egr1 interacted with AGE-RAGE signaling and Apelin signaling pathways, Cdkn1a, and Gadd45a. Cdkn1a was implicated in in FoxO signaling, PI3K-Akt signaling, ErbB signaling, and Oxytocin signaling pathways, and Gadd45a. Gadd45a was involved in NF-kappa B signaling and FoxO signaling pathways. Drug sensitivity analysis showed Egr1 was highly sensitive to GENIPIN. CONCLUSION: A suite of bioinformatics analysis revealed several key candidate hippocampal genes and associated functional signaling pathways that could underlie Sevoflurane associated neurodegenerative processes. |
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