Integrating single-cell analysis and machine learning to identify COPD hub genes and explore the intervention
Chunlei Liu1, Yange Tian1, Ruilong Lu1
1Henan 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.
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.
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