Chen Zhidong, Tang Kankai, Zhang Hui
Department of Intensive Care Unit, the First Affiliated Hospital of Huzhou University, Huzhou, Zhejiang Province, China.
Department of Anesthesiology, the First Affiliated Hospital of Huzhou University, Huzhou, Zhejiang Province, China.
Histol Histopathol. 2025 Mar;40(3):401-409. doi: 10.14670/HH-18-789. Epub 2024 Jul 3.
This study analyzed potential key genes involved in the mechanism of acute liver injury induced by sepsis through bioinformatics techniques, aiming to provide novel insights for the identification of early-stage sepsis-induced acute liver injury and its diagnosis.
Gene chip data sets containing samples from acute liver injury induced by sepsis and control groups (GSE22009 and GSE60088) were selected from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) with |log fold change| >1 and <0.05 were screened with the GEO2R tool, which was also used for the selection of upregulated DEGs in the chips with <0.05. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Gene Ontology, and protein-protein interaction (PPI) analyses were then conducted. Results were visualized using R language packages, including volcano plots, Venn diagrams, and boxplots. The intersection of candidate genes with relevant genes in the Comparative Toxicogenomics Database (CTD) was performed, and the clinical significance of these genes was explored through a literature review. A rat model of acute liver injury was developed by inducing sepsis with the cecum ligation and puncture method. Real-time PCR was performed to determine the gene expression in rat liver tissues.
A total of 646 upregulated DEGs were determined in GSE22009 and 146 in GSE60088. A Venn diagram was used to find the intersection of the upregulated DEGs between the two data sets, and 67 DEGs associated with sepsis-mediated acute liver damage were obtained. Enrichment analysis from the KEGG pathway showed that DEG upregulation was primarily associated with various pathways: TNF, NF-κB, IL-17, ferroptosis, mTOR, and JAK-STAT signaling pathways. DEGs resulted in three clusters and 15 candidate genes, as revealed by the PPI network and module analyses. Intersection with sepsis-induced acute liver injury-related genes in the CTD resulted in the identification of three significant differentially co-expressed genes: and . Sepsis-induced liver tissue indicated the overexpression of and mRNA, as compared with the control group (<0.05).
The key genes identified and related signaling pathways provided insights into the molecular mechanisms of sepsis-induced acute liver injury. In vivo studies revealed the overexpression of , and mRNA in sepsis-mediated injured liver tissues, providing a theoretical basis for early diagnosis and targeted treatment research.
本研究通过生物信息学技术分析脓毒症诱导急性肝损伤机制中潜在的关键基因,旨在为脓毒症诱导的急性肝损伤的早期识别及其诊断提供新的见解。
从基因表达综合数据库(GEO)中选取包含脓毒症诱导急性肝损伤样本和对照组(GSE22009和GSE60088)的基因芯片数据集。使用GEO2R工具筛选|log倍数变化|>1且<0.05的差异表达基因(DEG),该工具还用于筛选芯片中上调的DEG且<0.05。然后进行京都基因与基因组百科全书(KEGG)通路、基因本体论和蛋白质-蛋白质相互作用(PPI)分析。结果使用R语言包进行可视化,包括火山图、维恩图和箱线图。将候选基因与比较毒理基因组学数据库(CTD)中的相关基因进行交集分析,并通过文献综述探讨这些基因的临床意义。采用盲肠结扎穿刺法诱导脓毒症建立急性肝损伤大鼠模型。进行实时PCR以确定大鼠肝组织中的基因表达。
在GSE22009中确定了646个上调的DEG,在GSE60088中确定了146个。使用维恩图找到两个数据集中上调的DEG的交集,获得了67个与脓毒症介导的急性肝损伤相关的DEG。KEGG通路的富集分析表明,DEG上调主要与各种通路相关:TNF、NF-κB、IL-17、铁死亡、mTOR和JAK-STAT信号通路。PPI网络和模块分析显示,DEG产生了三个簇和15个候选基因。与CTD中脓毒症诱导的急性肝损伤相关基因的交集分析确定了三个显著差异共表达基因:和。与对照组相比,脓毒症诱导的肝组织显示和mRNA的过表达(<0.05)。
鉴定出的关键基因和相关信号通路为脓毒症诱导急性肝损伤的分子机制提供了见解。体内研究揭示了脓毒症介导的损伤肝组织中和mRNA的过表达,为早期诊断和靶向治疗研究提供了理论依据。