Suppr超能文献

整合生物信息学分析、机器学习和实验验证,以鉴定脓毒症合并急性肝衰竭诊断中与细胞焦亡相关的基因。

Integrating bioinformatics analysis, machine learning, and experimental validation to identify pyroptosis-related genes in the diagnosis of sepsis combined with acute liver failure.

作者信息

Yan Jing, Pan Yifeng, Chen Chaoqi, Liu Lijian, Tan Jinjing, Li Juan, Li Liqun, Xie Sheng

机构信息

Graduate School of Guangxi University of Chinese Medicine, Nanning, 530200, Guangxi, China.

The Eighth Clinical Medical College of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong, China.

出版信息

Hereditas. 2025 Aug 8;162(1):153. doi: 10.1186/s41065-025-00522-4.

Abstract

BACKGROUND

Sepsis is frequently combined with acute liver failure (ALF), a critical determinant in the mortality of septic patients. Pyroptosis is a significant form of programmed cell death that plays an important role in the inflammatory response. Research has been conducted to elucidate the relationship between pyroptosis, sepsis, and ALF, but the mechanism of action remains unclear.

METHODS

Datasets relating to sepsis and ALF were obtained from the Gene Expression Omnibus (GEO). The intersection of differentially expressed genes (DEGs) and pyroptosis-related genes for sepsis and ALF was identified. Simultaneously, a gene diagnosis model for sepsis and ALF was developed using machine learning, and the model's accuracy was assessed through the plotting of the ROC curves and confusion matrix. The Hub genes identified by the model with an area under the curve (AUC) value ≥ 0.7 were used for the investigation of immune cell infiltration to explain the molecular mechanism of sepsis combined with ALF. The precise mechanism of action of these model genes in sepsis combined with ALF was evaluated through animal experiments.

RESULTS

Machine learning revealed that GABARAP and ITCH may serve as diagnostic biomarkers for pyroptosis in sepsis combined with ALF. The examination of immune cell infiltration indicated that immune dysregulation is present in both sepsis and ALF and preliminarily suggested that GABARAP and ITCH may be pivotal in cellular immunity responses, particularly those mediated by T cells. Animal experiments further validated that in the process of sepsis combined with ALF, the expression level of GABARAP is elevated, while the expression level of ITCH is diminished.

CONCLUSIONS

We found GABARAP and ITCH may serve as diagnostic biomarkers for pyroptosis in sepsis combined with ALF, suggesting their potential involvement in the initiation and advancement of sepsis combined with ALF through cellular immunomodulatory pathways.

CLINICAL TRIAL NUMBER

Not applicable.

摘要

背景

脓毒症常合并急性肝衰竭(ALF),这是脓毒症患者死亡率的关键决定因素。细胞焦亡是程序性细胞死亡的一种重要形式,在炎症反应中起重要作用。已有研究阐明细胞焦亡、脓毒症和ALF之间的关系,但作用机制仍不清楚。

方法

从基因表达综合数据库(GEO)获取与脓毒症和ALF相关的数据集。确定脓毒症和ALF的差异表达基因(DEG)与细胞焦亡相关基因的交集。同时,利用机器学习建立脓毒症和ALF的基因诊断模型,并通过绘制ROC曲线和混淆矩阵评估模型的准确性。将曲线下面积(AUC)值≥0.7的模型鉴定出的枢纽基因用于免疫细胞浸润研究,以解释脓毒症合并ALF的分子机制。通过动物实验评估这些模型基因在脓毒症合并ALF中的具体作用机制。

结果

机器学习显示,GABARAP和ITCH可能作为脓毒症合并ALF中细胞焦亡的诊断生物标志物。免疫细胞浸润检查表明,脓毒症和ALF中均存在免疫失调,并初步提示GABARAP和ITCH可能在细胞免疫反应中起关键作用,尤其是由T细胞介导的免疫反应。动物实验进一步证实,在脓毒症合并ALF的过程中,GABARAP的表达水平升高,而ITCH的表达水平降低。

结论

我们发现GABARAP和ITCH可能作为脓毒症合并ALF中细胞焦亡的诊断生物标志物,表明它们可能通过细胞免疫调节途径参与脓毒症合并ALF的发生和发展。

临床试验编号

不适用。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验