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Updated: May 12, 2025

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大量RNA-seq和scRNA-seq的整合揭示了与深静脉血栓症相关的转录组签名

Bao-Ze Pan¹, Ming-Jun Jiang¹, Li-Ming Deng¹

¹The Second Affiliated Hospital, Department of Vascular Surgery, Hengyang Medical School, University of South China, Hengyang, Hunan, China.

Frontiers in genetics

|May 9, 2025

概括

这项研究确定CXCR4是深静脉血栓症 (DVT) 的潜在遗传标记物. MIF - (CD74 + CXCR4) 途径也可能在DVT发展中发挥作用.

科学领域:

基因组学和生物信息学
血管生物学血管生物学
免疫学免疫学免疫学

背景情况:

深静脉血栓症 (DVT) 是一种常见的血管疾病,其复杂的机制阻碍了目标识别.
了解DVT的遗传基础对于开发有效治疗方法至关重要.

研究的目的:

识别和表征与深静脉血栓症 (DVT) 相关的独特基因.
探索涉及DVT病变的细胞和通路水平机制.

主要方法:

在患者和对照样本上进行批量和单细胞RNA测序 (RNA-seq).
蛋白与蛋白相互作用 (PPI) 网络分析,加权基因共表达网络分析 (WGCNA) 和机器学习 (ML) 用于基因识别和验证.
分析CellChat通路,以调查细胞间通信.

主要成果:

确定了193个差异表达基因 (DEG),其中8个关键基因包括TLRs,CXCR4,DDX58,TNFSF10,FCGR1A和CD36.
CXCR4显示出显著的诊断潜力 (AUC=1,000),并被验证为潜在的DVT标.
scRNA-seq揭示了B细胞,T细胞和单细胞在DVT中的活性作用,其中涉及MIF- (CD74 + CXCR4) 途径.

结论:

CXCR4成为深静脉血栓症 (DVT) 的有希望的遗传标记物.
MIF - (CD74 + CXCR4) 复合体可能参与DVT的调节机制.

关键词:

这就是ScRNA-seqq.在WGCNA中,WGCNA是WGCNA.大量的RNA-seqq.深静脉血栓形成的原因是深静脉血栓形成.机器学习是机器学习.静脉血栓塞栓症是一种静脉血栓塞栓.

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