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基于蛋白质-蛋白质相互作用网络和机器学习,识别与败血症中的免疫微环境相关的尸生物标志物

Mengze Wu¹, Zhao Zou¹, Yuce Peng¹

¹Division of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China; Cardiovascular Disease Laboratory of Chongqing Medical University, Chongqing 400016, China.

Clinica chimica acta; international journal of clinical chemistry

|July 16, 2025

概括

这项研究确定了三种关键的亡相关基因 (CD40LG,TXN,AIM2),这些基因参与了败血症的发病. 使用这些基因的诊断签名可能有助于快速检测败血症并了解其炎症联系.

科学领域:

分子生物学分子生物学
免疫学免疫学免疫学
生物信息学是一种生物信息学.

背景情况:

亡,一种炎症性细胞死亡途径,与败血症有关.
败血症中亡和炎症之间的相互作用需要进行更深入的研究.
在败血症中识别关键的尸基因对于了解疾病机制至关重要.

研究的目的:

通过识别枢纽尸基因,揭示尸病在败血症发病过程中的作用.
探索这些基因与败血症中的免疫微环境之间的关联.
为了开发一个necroptotic基因签名用于败血症诊断.

主要方法:

利用基因表达综合 (GEO) 数据集来识别在败血症中差异表达的基因 (DEG).
与已知的亡相关基因交叉DEG,并使用蛋白质-蛋白质相互作用网络 (PPIN) 和机器学习进行分析.
在小鼠和细胞败血症模型中验证了已识别的枢纽尸DEG (枢纽NRDEG).

主要成果:

鉴定了三个枢纽NRDEG:CD40LG,TXN和AIM2,来自4974个DEG和336个亡基因.
根据转录基因特征,分类了体样本成两组,表明信号差异.
证明了枢纽NRDEG与免疫细胞的相关性,以及它们在免疫透中的作用,经过实验验证.

结论:

提出了用于败血症诊断的三基因尸体签名 (CD40LG,TXN,AIM2).
建立了枢纽NRDEGs与败血症中的免疫细胞之间的初始关联.
在实验性败血症中验证了枢纽NRDEGs的表达变化,表明了快速诊断的潜力.

关键词:

在AIM2中,AIM2是AIM2.在CD40LG中,CD40LG是CD40LG.免疫透免疫透机器学习机器学习尸体亡 (Necroptosis) 是一种致死症.败血症这是一种败血症.TXN TXN 在线观看

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