基于生物信息学分析的细胞衰老基因和免疫渗透在脓毒症和脓毒症诱发的 ARDS 中的作用

IF 4.2 2区 医学 Q2 IMMUNOLOGY
Journal of Inflammation Research Pub Date : 2024-11-19 eCollection Date: 2024-01-01 DOI:10.2147/JIR.S488463
Xiao-Ling Wu, Ya-Nan Guo
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引用次数: 0

摘要

简介脓毒症是危重病人死亡的主要原因,它会导致多器官功能障碍,包括急性呼吸窘迫综合征(ARDS)。我们的研究旨在通过生物信息学分析确定细胞衰老基因和免疫浸润在脓毒症和脓毒症诱发的 ARDS 中的作用:数据集 GSE66890 和 GSE145227 来自基因表达总库(GEO)数据库,用于生物信息学分析。对差异表达基因(DEGs)进行了基因本体(GO)术语和京都基因组百科全书(KEGG)富集分析,以确定关键功能模块。利用两种机器学习算法,即最小绝对收缩和选择算子(LASSO)和支持向量机递归特征消除(SVM-RFE),筛选脓毒症和脓毒症诱发的ARDS中的特征基因。生成的 ROC 曲线用于评估基因中心的预测能力。通过ssGSEA比较了疾病组和对照组之间免疫浸润水平的差异。在住院患者中通过定量 PCR(qPCR)验证了中心基因的诊断价值:结果:四个特征基因(ATM、CCNB1、CCNA1 和 E2F2)被确定为脓毒症诱发 ARDS 进展的生物标志物。E2F2 对脓毒症患者发生 ARDS 的预测能力最高。在脓毒症诱发的 ARDS 组中,CD56bright 和类浆细胞树突状细胞呈高浸润状态,而嗜酸性粒细胞、MDSCs、巨噬细胞和中性粒细胞呈低浸润状态。此外,脓毒症患者的ATM表达低于非脓毒症患者(n = 6):脓毒症诱发的 ARDS 与循环免疫反应相关,ATM、CCNB1、CCNA1 和 E2F2 的表达可作为脓毒症诱发 ARDS 的潜在诊断生物标记物和治疗靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Role of Cellular Senescence Genes and Immune Infiltration in Sepsis and Sepsis-Induced ARDS Based on Bioinformatics Analysis.

Introduction: Sepsis is the leading cause of death in critically ill patients; it results in multiorgan dysfunction, including acute respiratory distress syndrome (ARDS). Our study was conducted to determine the role of cellular senescence genes and immune infiltration in sepsis and sepsis-induced ARDS via bioinformatic analyses.

Experimental procedures: Datasets GSE66890 and GSE145227 were obtained from the Gene Expression Omnibus (GEO) database and utilized for bioinformatics analyses. Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of the differentially expressed genes (DEGs) were performed to identify the key functional modules. Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE), were used to screen for characteristic genes in sepsis and sepsis-induced ARDS. ROC curves were generated to evaluate the predictive ability of gene hubs. Differences in immune infiltration levels between the disease and control groups were compared via ssGSEA. The diagnostic value of the hub genes was verified via quantitative PCR (qPCR) in hospitalized patients.

Results: Four characteristic genes (ATM, CCNB1, CCNA1, and E2F2) were identified as biomarkers for the progression of sepsis-induced ARDS. E2F2 showed the highest predictive ability for the occurrence of ARDS in patients with sepsis. CD56bright and plasmacytoid dendritic cells exhibited high infiltration in the sepsis-induced ARDS group, whereas eosinophils, MDSCs, macrophages, and neutrophils exhibited low infiltration. In addition, ATM expression was lower in patients with sepsis than in those without sepsis (n = 6).

Conclusion: Sepsis-induced ARDS is correlated with circulating immune responses, and the expression of ATM, CCNB1, CCNA1, and E2F2 may serve as potential diagnostic biomarkers and therapeutic targets in sepsis-induced ARDS.

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来源期刊
Journal of Inflammation Research
Journal of Inflammation Research Immunology and Microbiology-Immunology
CiteScore
6.10
自引率
2.20%
发文量
658
审稿时长
16 weeks
期刊介绍: An international, peer-reviewed, open access, online journal that welcomes laboratory and clinical findings on the molecular basis, cell biology and pharmacology of inflammation.
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