背景:脓毒症,以全身炎症反应综合征和危及生命的器官功能障碍为特征,仍然是全球残疾和死亡的重要原因。尽管有影响,脓毒症诊断的可靠生物标志物尚待确定.
目的:本研究旨在通过对多个微阵列数据集的分析来调查和鉴定脓毒症中的关键基因和途径,为未来的临床试验提供潜在的治疗目标。
方法:从基因表达综合(GEO)数据库下载两个独立的基因表达谱(GSE54514和GSE69528)。合并和批量规范化后,使用“limma”软件包获得差异表达基因(DEGs)。使用“R”软件进行基因本体论(GO)和基因集富集分析(GSEA)。使用用于检索相互作用基因(STRING)的搜索工具构建蛋白质-蛋白质相互作用(PPI)网络。使用Cytoscape鉴定了前10个hub基因。构建并评估了预测脓毒症发生的列线图模型。
结果:210例败血症和91例对照血液样本的生物信息学分析鉴定出72DEGs。GO分析揭示了与免疫反应过程的关联。GSEA表明参与关键信号通路。S100A12、MMP9和PRTN3是脓毒症的独立危险因素。
结论:本研究通过生物信息学方法揭示了脓毒症的关键基因和途径。S100A12、MMP9和PRTN3可能在对感染的免疫反应中发挥重要作用。影响脓毒症预后。
BACKGROUND: Sepsis, characterized by systemic inflammatory response syndrome and life-threatening organ dysfunction, remains a significant global cause of disability and death. Despite its impact, reliable biomarkers for sepsis diagnosis are yet to be identified.
OBJECTIVE: This study aims to investigate and identify key genes and pathways in sepsis through the analysis of multiple microarray datasets, providing potential treatment targets for future clinical trials.
METHODS: Two independent gene expression profiles (GSE54514 and GSE69528) were downloaded from the Gene Expression Omnibus (GEO) database. After merging and batch normalization, differentially expressed genes (DEGs) were obtained using the \"limma\" package. Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) were performed using \"R\" software. A Protein-Protein Interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING). The top 10 hub genes were identified using Cytoscape. A Nomogram model for predicting sepsis occurrence was constructed and evaluated.
RESULTS: Bioinformatic analysis of 210 sepsis and 91 control blood samples identified 72 DEGs. GO analyses revealed associations with immune response processes. GSEA indicated involvement in key signaling pathways. S100A12, MMP9, and PRTN3 were identified as independent risk factors for sepsis.
CONCLUSIONS: This study unveils critical genes and pathways in sepsis through bioinformatic methods. S100A12, MMP9, and PRTN3 may play essential roles in the immune response to infection, influencing sepsis prognosis.