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整合单细胞分析和机器学习以鉴定慢性阻塞性肺疾病(COPD)核心基因并探索补肺益肾方Ⅲ有效成分配伍的干预机制

Integrating single-cell analysis and machine learning to identify COPD hub genes and explore the intervention mechanism of effective component compatibility of Bufei Yishen formula III.

作者信息

Liu Chunlei, Tian Yange, Lu Ruilong, Yue Changyuan, Xie Yuan, Zhang Tiantian, Li Jiansheng, Guan Qingzhou

机构信息

Henan Key Laboratory of Chinese Medicine for Respiratory Disease, Collaborative Innovation Center for Chinese Medicine and Respiratory Diseases Co-constructed by Henan Province and Education Ministry of PR China, Henan University of Chinese Medicine, Zhengzhou, 450046, China; Academy of Chinese Medical Sciences, Henan University of Chinese Medicine, Zhengzhou, 450046, China.

Henan Key Laboratory of Chinese Medicine for Respiratory Disease, Collaborative Innovation Center for Chinese Medicine and Respiratory Diseases Co-constructed by Henan Province and Education Ministry of PR China, Henan University of Chinese Medicine, Zhengzhou, 450046, China; Department of Respiratory Diseases, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, 450000, China.

出版信息

J Ethnopharmacol. 2025 Jul 24;351:120126. doi: 10.1016/j.jep.2025.120126. Epub 2025 Jun 10.

Abstract

ETHNOPHARMACOLOGICAL RELEVANCE

Chronic obstructive pulmonary disease (COPD) is a prevalent condition that poses a major threat to public health. Endothelial cells play a critical role in COPD pathogenesis. Recent evidence suggests that the effective-component combination of Bufei Yishen formula III (ECC-BYF III) significantly improves clinical symptoms and quality of life in COPD patients.

AIM OF THE STUDY

To identify endothelial cell-associated hub genes in COPD using single-cell analysis and machine learning, and to elucidate the intervention mechanism underlying ECC-BYF III.

MATERIALS AND METHODS

Single-cell analysis was used to identify altered cellular subtypes in COPD samples. High-dimensional weighted gene co-expression network analysis (hdWGCNA) and multiple machine learning algorithms were applied to identify COPD-related hub genes. These genes were validated using receiver operating characteristic (ROC) curves, independent datasets, qRT-PCR in human umbilical vein endothelial cells (HUVECs) and a rat model of COPD.

RESULTS

Single-cell analysis revealed nine distinct cell subtypes, with endothelial cells markedly reduced in COPD samples compared to controls. Cell communication and pseudotime trajectory analysis highlighted the role and developmental trajectory of endothelial cells in COPD. Differential expression analysis and hdWGCNA identified 269 endothelial cell-associated genes, from which six hub genes were selected via machine learning. qRT-PCR confirmed that CD74, AQP1, SOX4, and ANXA1 were significantly dysregulated in both HUVECs and COPD rat models, consistent with the data analysis results. Notably, ECC-BYF III intervention reversed these gene expression abnormalities. Molecular docking demonstrated that the components of ECC-BYF III exhibited strong binding affinities for the hub genes.

CONCLUSIONS

Four hub genes (CD74, SOX4, AQP1, and ANXA1) involved in the pathogenesis of endothelial cells in COPD were identified. ECC-BYF III was shown to modulate their expression, supporting its potential as a therapeutic agent in traditional Chinese medicine (TCM) for COPD. These findings offer novel insights into the mechanisms of COPD and open avenues for TCM treatment.

摘要

民族药理学相关性

慢性阻塞性肺疾病(COPD)是一种普遍存在的疾病,对公众健康构成重大威胁。内皮细胞在COPD发病机制中起关键作用。最近的证据表明,补肺益肾方Ⅲ号有效成分组合(ECC-BYFⅢ)能显著改善COPD患者的临床症状和生活质量。

研究目的

利用单细胞分析和机器学习确定COPD中与内皮细胞相关的核心基因,并阐明ECC-BYFⅢ的干预机制。

材料与方法

采用单细胞分析确定COPD样本中改变的细胞亚型。应用高维加权基因共表达网络分析(hdWGCNA)和多种机器学习算法来识别与COPD相关的核心基因。使用受试者工作特征(ROC)曲线、独立数据集、人脐静脉内皮细胞(HUVECs)中的qRT-PCR以及COPD大鼠模型对这些基因进行验证。

结果

单细胞分析揭示了9种不同的细胞亚型,与对照组相比,COPD样本中的内皮细胞明显减少。细胞通讯和伪时间轨迹分析突出了内皮细胞在COPD中的作用和发育轨迹。差异表达分析和hdWGCNA确定了269个与内皮细胞相关的基因,通过机器学习从中选择了6个核心基因。qRT-PCR证实,CD74、AQP1、SOX4和ANXA1在HUVECs和COPD大鼠模型中均显著失调,与数据分析结果一致。值得注意的是,ECC-BYFⅢ干预逆转了这些基因表达异常。分子对接表明,ECC-BYFⅢ的成分对核心基因表现出很强的结合亲和力。

结论

确定了4个参与COPD内皮细胞发病机制的核心基因(CD74、SOX4、AQP1和ANXA1)。结果表明ECC-BYFⅢ可调节它们的表达,支持其作为COPD中医治疗药物的潜力。这些发现为COPD的机制提供了新的见解,并为中医治疗开辟了道路。

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