Apizi Anwaier, Li Jian, Kamilijiang Paiheriding, Yang Chun-Bo, Wang Zheng-Kai, Chai Rui-Feng, Yu Zhao-Xia
Department of Intensive Care Unit, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, People's Republic of China.
J Inflamm Res. 2025 Aug 22;18:11493-11508. doi: 10.2147/JIR.S530849. eCollection 2025.
This study aimed to evaluate the extent of organ damage associated with sepsis and to identify key genes implicated in its pathogenesis.
Eighteen rats were randomized into experimental and control groups. Cecal ligation and puncture induced sepsis in the experimental group, with lung and kidney inflammatory injury assessed at 12, 24, and 36 hours. Gene expression profiles of sepsis patients and healthy controls were obtained from Gene Expression Omnibus database. Weighted gene co-expression network analysis and bioinformatics identified sepsis-related pathways and core genes, constructing a predictive risk model. Immune cell composition was compared between groups, and correlations between core gene expression and immune cell populations were analyzed.
The experimental group exhibited greater lung and kidney tissue damage at all time points compared to the control group, with severity increasing over time. Cross-analysis identified 505 core genes associated with sepsis. Gene Ontology enrichment analysis revealed that differentially expressed genes were predominantly enriched in biological processes, molecular functions, cellular components, and the hematopoietic cell lineage pathway. A sepsis risk model constructed using five key genes-, and -demonstrated high predictive accuracy. Notable differences in immune cell composition were observed, with a statistically significant variation in T cells CD4 naïve and activated dendritic cells between the sepsis and control groups ( < 0.05). Additionally, a positive correlation was identified between expression and the proportion of activated dendritic cells.
The severity of lung and kidney tissue damage in sepsis increased over time. The five identified sepsis-related genes have predictive value in assessing sepsis risk. Insights into the interactions between key genes and immune cell populations may contribute to improved clinical management of sepsis.
本研究旨在评估与脓毒症相关的器官损伤程度，并确定其发病机制中涉及的关键基因。
将18只大鼠随机分为实验组和对照组。实验组采用盲肠结扎穿刺法诱导脓毒症，分别在12、24和36小时评估肺和肾的炎性损伤。从基因表达综合数据库中获取脓毒症患者和健康对照的基因表达谱。采用加权基因共表达网络分析和生物信息学方法确定脓毒症相关通路和核心基因，构建预测风险模型。比较两组间的免疫细胞组成，并分析核心基因表达与免疫细胞群体之间的相关性。
与对照组相比，实验组在所有时间点的肺和肾组织损伤均更严重，且严重程度随时间增加。交叉分析确定了505个与脓毒症相关的核心基因。基因本体富集分析显示，差异表达基因主要富集于生物过程、分子功能、细胞成分和造血细胞谱系通路。使用五个关键基因构建的脓毒症风险模型显示出较高的预测准确性。观察到免疫细胞组成存在显著差异，脓毒症组和对照组之间的幼稚CD4 T细胞和活化树突状细胞有统计学意义的变化（<0.05）。此外，还发现 表达与活化树突状细胞比例之间呈正相关。
脓毒症中肺和肾组织损伤的严重程度随时间增加。所确定的五个脓毒症相关基因在评估脓毒症风险方面具有预测价值。深入了解关键基因与免疫细胞群体之间的相互作用可能有助于改善脓毒症的临床管理。
