Bioinformatics study of the TNFRSF1A mechanism involved in acute liver injury in sepsis through the mTOR signaling pathway.

IF 2.5 4区 生物学 Q3 CELL BIOLOGY Histology and histopathology Pub Date : 2024-07-03 DOI:10.14670/HH-18-789
Zhidong Chen, Kankai Tang, Hui Zhang
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Abstract

Objectives: 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.

Methods: 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 p<0.05 were screened with the GEO2R tool, which was also used for the selection of upregulated DEGs in the chips with p<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.

Results: 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: CXCL1, ICAM1, and TNFRSF1A. Sepsis-induced liver tissue indicated the overexpression of CXCL1, ICAM1, and TNFRSF1A mRNA, as compared with the control group (p<0.05).

Conclusion: 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 CXCL1, ICAM1, and TNFRSF1A mRNA in sepsis-mediated injured liver tissues, providing a theoretical basis for early diagnosis and targeted treatment research.

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通过 mTOR 信号通路研究 TNFRSF1A 参与败血症急性肝损伤的生物信息学机制。
研究目的本研究通过生物信息学技术分析脓毒症诱发急性肝损伤机制中潜在的关键基因,旨在为早期脓毒症诱发急性肝损伤的识别和诊断提供新的见解:从基因表达总库(Gene Expression Omnibus,GEO)数据库中选取包含脓毒症诱发急性肝损伤组和对照组样本的基因芯片数据集(GSE22009 和 GSE60088)。差异表达基因(DEGs)的|log折叠变化|>1和ppResults:在 GSE22009 和 GSE60088 中分别发现了 646 个和 146 个上调的 DEGs。利用维恩图找出两组数据中上调 DEGs 的交集,得到 67 个与败血症介导的急性肝损伤相关的 DEGs。KEGG通路的富集分析表明,DEG的上调主要与不同的通路有关:TNF、NF-κB、IL-17、铁变态反应、mTOR和JAK-STAT信号通路。PPI网络和模块分析显示,DEGs产生了3个集群和15个候选基因。在 CTD 中与脓毒症诱导的急性肝损伤相关基因交叉后,发现了三个重要的差异共表达基因:CXCL1、ICAM1 和 TNFRSF1A。与对照组相比,脓毒症诱导的肝组织显示 CXCL1、ICAM1 和 TNFRSF1A mRNA 过表达(pConclusion):所发现的关键基因和相关信号通路有助于深入了解脓毒症诱发急性肝损伤的分子机制。体内研究发现,CXCL1、ICAM1和TNFRSF1A mRNA在脓毒症损伤肝组织中过度表达,为早期诊断和靶向治疗研究提供了理论依据。
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来源期刊
Histology and histopathology
Histology and histopathology 生物-病理学
CiteScore
3.90
自引率
0.00%
发文量
232
审稿时长
2 months
期刊介绍: HISTOLOGY AND HISTOPATHOLOGY is a peer-reviewed international journal, the purpose of which is to publish original and review articles in all fields of the microscopical morphology, cell biology and tissue engineering; high quality is the overall consideration. Its format is the standard international size of 21 x 27.7 cm. One volume is published every year (more than 1,300 pages, approximately 90 original works and 40 reviews). Each volume consists of 12 numbers published monthly online. The printed version of the journal includes 4 books every year; each of them compiles 3 numbers previously published online.
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