Bao Mengmeng, Wu Anshi
Department of Anesthesiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100020, China.
Open Med (Wars). 2024 Aug 13;19(1):20241014. doi: 10.1515/med-2024-1014. eCollection 2024.
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.
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 -value thresholds. Additional analyses included the Friends approach, Spearman's correlation, and gene set enrichment analysis (GSEA), exploring functional annotations and pathways.
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.
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.
本研究利用从冠状动脉搭桥术（CABG）后心房组织样本中获取的GSE4386数据集，以研究麻醉剂（七氟醚和丙泊酚）对基因表达和免疫细胞浸润的影响。
采用层次聚类和箱线图进行数据集预处理，突出显示了一个显著的离群值（样本GSM99282），随后将其去除以确保数据完整性。基于特定的对数变化倍数和P值阈值，使用火山图识别差异表达基因（DEG）。其他分析包括Friends方法、Spearman相关性分析和基因集富集分析（GSEA），以探索功能注释和通路。
热图和气泡图描绘了DEG，揭示了七氟醚组和丙泊酚组之间不同的表达模式。Friends分析基于对数变化倍数确定了顶级基因，并使用Spearman方法进一步进行相关性分析。基因本体论和京都基因与基因组百科全书富集分析阐明了DEG的功能注释，而GSEA突出了富集的生物学类别。免疫细胞浸润分析展示了CABG术后不同的细胞存在情况。ESTIMATE算法评分显示了免疫、基质和估计评分的差异。微环境细胞群体计数器（MCPcounter）显示七氟醚组中细胞毒性淋巴细胞的丰度增加，单样本GSEA证实了这一点。CIBERSORT算法确定了不同的免疫细胞组成，突出了七氟醚组和丙泊酚组之间巨噬细胞M0患病率的差异。
这项综合分析为CABG术后心房组织中麻醉诱导的基因表达变化和免疫细胞动态提供了见解。所确定的DEG和免疫细胞组成提供了潜在的生物标志物和治疗靶点，以优化心脏手术中的麻醉策略。
