解读焦热相关基因和自然杀伤T细胞在败血症发病机制中的作用:综合生物信息学和孟德尔随机化分析。

IF 2 4区 医学 Q3 PHYSIOLOGY
Journal of Physiology and Pharmacology Pub Date : 2025-04-01 Epub Date: 2025-05-05 DOI:10.26402/jpp.2025.2.10
L Zhou, W Dong, Y Liu
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引用次数: 0

摘要

人们越来越认识到热亡在脓毒症的发展中起着至关重要的作用,但热亡相关基因(PRGs)在脓毒症中的具体作用仍未得到充分探讨。从Gene expression Omnibus (GEO)数据库(GSE57065, GSE95233)中检索脓毒症和对照样本的基因表达谱进行分析。鉴定差异表达基因(DEGs),然后进行功能富集分析。加权基因共表达网络分析(WGCNA)用于鉴定与脓毒症相关的基因,交叉的deg和prg通过维恩图突出显示。在训练和验证数据集(GSE65682)中进一步分析Hub基因的差异表达、受试者工作特征(ROC)分析、相关分析和Kaplan-Meier (KM)生存分析。使用单样本基因集富集分析(ssGSEA)算法评估两个数据集中的免疫细胞浸润。机器学习方法被应用于识别参与败血症调节的关键免疫细胞类型,这些细胞类型随后与中心基因相关。使用GSE167363数据集对脓毒症样本进行单细胞RNA测序(scRNA-seq)分析。最后,使用孟德尔随机化(MR)来调查暴露与结果之间的因果关系。结果共鉴定出8个hub PRGs,包括NLRC4、PLCG1、TP53、AIM2、GZMB、GZMA、ELANE和CASP5。功能富集分析涉及败血症进展中失调的免疫反应,与已建立的病理生理机制一致。这八个关键基因表现出一致的表达模式。一些基因(NLRC4, PLCG1, AIM2, GZMB和ELANE)成为有希望的诊断生物标志物(AUC bb0 0.85)。机器学习揭示了15种免疫细胞类型可能在败血症中发挥重要作用。相关分析表明颗粒酶B (GZMB)与自然杀伤T (NKT)细胞呈正相关,scRNA-seq分析进一步证实了这一发现。在验证队列中,GZMB和ELANE与患者预后相关
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deciphering the role of pyroptosis-related genes and natural killer T cells in sepsis pathogenesis: a comprehensive bioinformatics and Mendelian randomization analysis.

Pyroptosis is increasingly recognized as crucial in sepsis development, but the specific roles of pyroptosis-related genes (PRGs) in sepsis remain underexplored. Gene expression profiles of sepsis and control samples were retrieved from the Gene Expression Omnibus (GEO) database for analysis (GSE57065, GSE95233). Differentially expressed genes (DEGs) were identified, followed by functional enrichment analysis. Weighted gene co-expression network analysis (WGCNA) was employed to identify genes associated with sepsis, with intersecting DEGs and PRGs highlighted via Venn diagrams. Hub genes were further analyzed across both the training and validation datasets (GSE65682) for differential expression, receiver operating characteristic (ROC) analysis, correlation analysis, and Kaplan-Meier (KM) survival analysis. Immune cell infiltration was evaluated in both datasets using the single-sample gene set enrichment analysis (ssGSEA) algorithm. Machine learning approaches were applied to identify critical immune cell types involved in sepsis regulation, which were subsequently correlated with the hub genes. Single-cell RNA sequencing (scRNA-seq) analysis of sepsis samples was conducted using the GSE167363 dataset. Finally, Mendelian randomization (MR) was utilized to investigate causal relationships between exposures and outcomes. In results eight hub PRGs were identified, including NLRC4, PLCG1, TP53, AIM2, GZMB, GZMA, ELANE, and CASP5. Functional enrichment analysis implicated dysregulated immune responses in sepsis progression, aligning with established pathophysiological mechanisms. These eight key genes exhibited consistent expression patterns. Several genes (NLRC4, PLCG1, AIM2, GZMB, and ELANE) emerged as promising diagnostic biomarkers (AUC>0.85). Machine learning revealed that 15 immune cell types may play important roles in sepsis. Correlation analysis indicated a positive relationship between granzyme B (GZMB) and natural killer T (NKT) cells, a finding further corroborated by scRNA-seq analysis. In the validation cohort, GZMB and ELANE were linked to patient prognosis (p<0.05). MR analysis using the inverse variance weighting (IVW) method demonstrated a positive causal relationship between GZMB and NKT cells (OR=1.063, 95% CI=1.013-1.115, p=0.013). Moreover, elevated NKT cell levels were associated with a reduced risk of sepsis (OR=0.977, 95% CI=0.955-1.000, p=0.046), and NKT cells served as protective factors for 28-day mortality in sepsis (OR=0.938, 95% CI=0.881-0.997, p=0.040). This study provides a comprehensive analysis of the roles of PRGs and NKT cells in sepsis, offering valuable insights for diagnostic and therapeutic approaches in sepsis immunotherapy.

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来源期刊
CiteScore
4.00
自引率
22.70%
发文量
0
审稿时长
6-12 weeks
期刊介绍: Journal of Physiology and Pharmacology publishes papers which fall within the range of basic and applied physiology, pathophysiology and pharmacology. The papers should illustrate new physiological or pharmacological mechanisms at the level of the cell membrane, single cells, tissues or organs. Clinical studies, that are of fundamental importance and have a direct bearing on the pathophysiology will also be considered. Letters related to articles published in The Journal with topics of general professional interest are welcome.
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