基于GEO数据库的脓毒症诱发慢加急性肝衰竭关键基因的生物信息学探究

doi:10.3969/j.issn.1009-976X.2024.03.003

摘要/Abstract

摘要： 目的本研究旨在比较有无脓毒症的慢加急性肝衰竭（ACLF）患者的基因表达谱,识别脓毒症诱发ACLF的差异表达基因。方法从Gene expression Omnibus数据库下载GSE142255的基因表达谱,根据有无脓毒症分为ACLF组和脓毒症诱发的ACLF组,对数据进行预处理,后筛选出差异表达基因,通过功能通路富集分析（GO、KEGG、GSEA）筛选出关键基因。结果共鉴定出883个差异表达基因,其中上调基因371个,下调基因512个。GO、KEGG、GSEA主要富集体液免疫应答、补体激活、自然杀伤细胞介导的细胞毒作用、淋巴细胞介导的免疫反应和Notch信号通路等。结论生物信息学分析确定了脓毒症诱发ACLF的差异基因,其通过免疫反应中的体液免疫应答、补体激活及Notch信号通路等导致疾病的发生发展,未来可作为脓毒症合并ACLF诊断和治疗的潜在指标。

关键词: 脓毒症, 慢加急性肝衰竭（ACLF）, 基因, 生物信息学分析

Abstract: Objective The aim of the present study was to compare the Gene expression profiling of chronic acute Liver failure （ACLF） patients with and without sepsis, and identify the differential expressed genes （DEGs） in acute-on-chronic liver failure （ACLF） patients with sepsis. Methods The gene chip datasets were obtained from the Gene Expression Omnibus （GEO） database. Then the common differential genes were carried out for later analyses according to the occurrence of sepsis in acute-on-chronic liver failure （ACLF） patients. The genes were analyzed by Gene ontology （GO）, pathway enrichment analysis （KEGG, GSEA） for screening out key genes. Results A total of 883 DEGs were identified, with 371 up-regulated genes and 512 down-regulated genes compared with acute-on-chronic liver failure （ACLF） patients without sepsis. Further bioinformatics analysis revealed that the GO, KEGG, GSEA were mainly enriched in humoral immune response, complement activation, Natural killer cell mediated cytotoxicity, lymphocyte mediated immunity and Notch signaling pathway. Conclusion Bioinformatics analysis identified the differential genes of ACLF induced by sepsis, which lead to the occurrenceand development of diseases through humoral immunity response, complement activation and Notch signal pathway in immune response, and may be used as potential indicators for diagnosis and therapy of sepsis-related ACLF in the future.

Key words: sepsis, acute-on-chronic liver failure, gene, bioinformatics analysis

中图分类号:

R631

易小玲, 顾杨, 李莉, 余涛. 基于GEO数据库的脓毒症诱发慢加急性肝衰竭关键基因的生物信息学探究[J]. 岭南现代临床外科, 2024, 24(03): 157-161.

YI Xiao-ling, GU Yang, LI Li, YU Tao. Bioinformatic exploration of key genes in sepsis induced acute-on-chronic liver failure based on GEO database[J]. Lingnan Modern Clinics In Surgery, 2024, 24(03): 157-161.

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