{"title":"探索冠状动脉旁路移植手术后麻醉剂诱导的心房组织基因表达变化和免疫细胞动态。","authors":"Mengmeng Bao, Anshi Wu","doi":"10.1515/med-2024-1014","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>This study leverages the GSE4386 dataset, obtained from atrial tissue samples post-coronary artery bypass graft (CABG) surgery, to investigate the impact of anesthetic agents (sevoflurane and propofol) on gene expression and immune cell infiltration.</p><p><strong>Methods: </strong>Hierarchical clustering and box plots were employed for dataset preprocessing, highlighting a significant outlier (sample GSM99282), subsequently removed to ensure data integrity. Differentially expressed genes (DEGs) were identified using volcano plots based on specific log-fold-change and <i>P</i>-value thresholds. Additional analyses included the Friends approach, Spearman's correlation, and gene set enrichment analysis (GSEA), exploring functional annotations and pathways.</p><p><strong>Results: </strong>Heatmaps and bubble plots depicted DEGs, revealing distinct expression patterns between the sevoflurane and propofol groups. Friends analysis identified top genes based on log fold changes, further correlated using Spearman's method. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses illustrated functional annotations of DEGs, while GSEA highlighted enriched biological categories. Immune cell infiltration analysis showcased varied cellular presence post-CABG. ESTIMATE algorithm scores demonstrated differences in immune, stroma, and estimate scores. Microenvironment Cell Populations-counter (MCPcounter) revealed an increased abundance of cytotoxic lymphocytes in the sevoflurane group, confirmed by a single sample GSEA. CIBERSORT algorithm identified distinct immune cell compositions, highlighting differences in macrophage M0 prevalence between sevoflurane and propofol groups.</p><p><strong>Conclusions: </strong>This comprehensive analysis provides insights into anesthetic-induced gene expression changes and immune cell dynamics in atrial tissue post-CABG surgery. The identified DEGs and immune cell compositions offer potential biomarkers and therapeutic targets for refining anesthetic strategies in cardiac surgeries.</p>","PeriodicalId":19715,"journal":{"name":"Open Medicine","volume":"19 1","pages":"20241014"},"PeriodicalIF":1.7000,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11330158/pdf/","citationCount":"0","resultStr":"{\"title\":\"Exploring anesthetic-induced gene expression changes and immune cell dynamics in atrial tissue post-coronary artery bypass graft surgery.\",\"authors\":\"Mengmeng Bao, Anshi Wu\",\"doi\":\"10.1515/med-2024-1014\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>This study leverages the GSE4386 dataset, obtained from atrial tissue samples post-coronary artery bypass graft (CABG) surgery, to investigate the impact of anesthetic agents (sevoflurane and propofol) on gene expression and immune cell infiltration.</p><p><strong>Methods: </strong>Hierarchical clustering and box plots were employed for dataset preprocessing, highlighting a significant outlier (sample GSM99282), subsequently removed to ensure data integrity. Differentially expressed genes (DEGs) were identified using volcano plots based on specific log-fold-change and <i>P</i>-value thresholds. Additional analyses included the Friends approach, Spearman's correlation, and gene set enrichment analysis (GSEA), exploring functional annotations and pathways.</p><p><strong>Results: </strong>Heatmaps and bubble plots depicted DEGs, revealing distinct expression patterns between the sevoflurane and propofol groups. Friends analysis identified top genes based on log fold changes, further correlated using Spearman's method. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses illustrated functional annotations of DEGs, while GSEA highlighted enriched biological categories. Immune cell infiltration analysis showcased varied cellular presence post-CABG. ESTIMATE algorithm scores demonstrated differences in immune, stroma, and estimate scores. Microenvironment Cell Populations-counter (MCPcounter) revealed an increased abundance of cytotoxic lymphocytes in the sevoflurane group, confirmed by a single sample GSEA. CIBERSORT algorithm identified distinct immune cell compositions, highlighting differences in macrophage M0 prevalence between sevoflurane and propofol groups.</p><p><strong>Conclusions: </strong>This comprehensive analysis provides insights into anesthetic-induced gene expression changes and immune cell dynamics in atrial tissue post-CABG surgery. 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引用次数: 0
摘要
研究背景本研究利用从冠状动脉旁路移植术(CABG)术后心房组织样本中获得的 GSE4386 数据集,研究麻醉剂(七氟烷和异丙酚)对基因表达和免疫细胞浸润的影响。方法:采用层次聚类和箱形图对数据集进行预处理,突出显示一个显著的离群点(样本 GSM99282),随后将其移除以确保数据的完整性。差异表达基因(DEG)是根据特定的对数折叠变化和 P 值阈值使用火山图确定的。其他分析包括好友方法、斯皮尔曼相关性和基因组富集分析(GSEA),以探索功能注释和通路:热图和气泡图描述了DEGs,揭示了七氟醚组和丙泊酚组之间不同的表达模式。好友分析根据对折变化确定了顶级基因,并使用斯皮尔曼方法进一步进行了相关分析。基因本体和京都基因和基因组百科全书的富集分析说明了DEGs的功能注释,而GSEA则突出了富集的生物类别。免疫细胞浸润分析显示了CABG后不同细胞的存在。ESTIMATE算法评分显示了免疫、基质和估计评分的差异。微环境细胞群计数器(MCPcounter)显示,七氟醚组细胞毒性淋巴细胞的数量增加,这一点得到了单样本 GSEA 的证实。CIBERSORT算法确定了不同的免疫细胞组成,突出显示了七氟烷组和丙泊酚组之间巨噬细胞M0流行率的差异:这项综合分析深入揭示了麻醉诱导的基因表达变化以及心房造影术后心房组织中免疫细胞的动态变化。已确定的 DEGs 和免疫细胞组成为完善心脏手术中的麻醉策略提供了潜在的生物标记物和治疗靶点。
Exploring anesthetic-induced gene expression changes and immune cell dynamics in atrial tissue post-coronary artery bypass graft surgery.
Background: This study leverages the GSE4386 dataset, obtained from atrial tissue samples post-coronary artery bypass graft (CABG) surgery, to investigate the impact of anesthetic agents (sevoflurane and propofol) on gene expression and immune cell infiltration.
Methods: Hierarchical clustering and box plots were employed for dataset preprocessing, highlighting a significant outlier (sample GSM99282), subsequently removed to ensure data integrity. Differentially expressed genes (DEGs) were identified using volcano plots based on specific log-fold-change and P-value thresholds. Additional analyses included the Friends approach, Spearman's correlation, and gene set enrichment analysis (GSEA), exploring functional annotations and pathways.
Results: Heatmaps and bubble plots depicted DEGs, revealing distinct expression patterns between the sevoflurane and propofol groups. Friends analysis identified top genes based on log fold changes, further correlated using Spearman's method. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses illustrated functional annotations of DEGs, while GSEA highlighted enriched biological categories. Immune cell infiltration analysis showcased varied cellular presence post-CABG. ESTIMATE algorithm scores demonstrated differences in immune, stroma, and estimate scores. Microenvironment Cell Populations-counter (MCPcounter) revealed an increased abundance of cytotoxic lymphocytes in the sevoflurane group, confirmed by a single sample GSEA. CIBERSORT algorithm identified distinct immune cell compositions, highlighting differences in macrophage M0 prevalence between sevoflurane and propofol groups.
Conclusions: This comprehensive analysis provides insights into anesthetic-induced gene expression changes and immune cell dynamics in atrial tissue post-CABG surgery. The identified DEGs and immune cell compositions offer potential biomarkers and therapeutic targets for refining anesthetic strategies in cardiac surgeries.
期刊介绍:
Open Medicine is an open access journal that provides users with free, instant, and continued access to all content worldwide. The primary goal of the journal has always been a focus on maintaining the high quality of its published content. Its mission is to facilitate the exchange of ideas between medical science researchers from different countries. Papers connected to all fields of medicine and public health are welcomed. Open Medicine accepts submissions of research articles, reviews, case reports, letters to editor and book reviews.