Integrative Single-Cell Transcriptomics and Network Pharmacology Analysis of Xiao Qing Long Tang in Pediatric Cough-Variant Asthma

<h4>Background</h4>Pediatric cough-variant asthma is characterized by chronic airway inflammation and epithelial dysfunction driven by complex cellular interactions and molecular regulatory networks. Understanding the cellular heterogeneity and molecular mechanisms underlying pediatric asthma pathogenesis remains challenging. Single-cell RNA sequencing (scRNA-seq) provides unprecedented resolution to dissect the molecular landscape of asthmatic airways at the individual cell level.<h4>Methods</h4>We performed a comprehensive single-cell transcriptomic analysis of airway epithelial tissues from pediatric asthma patients using the 10x Genomics platform. Following stringent quality control, dimensionality reduction analysis, and cell clustering, we identified distinct cell populations and characterized their molecular signatures. Developmental trajectory analysis was performed using the Monocle algorithm, and functional enrichment analysis was conducted to elucidate biological pathways. Additionally, network pharmacology was employed to explore the multitarget mechanisms of the traditional Chinese medicine formula Xiao Qing Long Tang (XQLT) in treating asthma.<h4>Results</h4>We successfully constructed a single-cell atlas of pediatric asthma airway epithelium, identifying seven major cell subtypes: eosinophil cells, basal cells, ciliated cells, goblet cells, club cells, ionocyte cells, and deuterosomal cells. High-resolution analysis revealed 23 distinct macrophage subpopulations (M1-M23) with unique transcriptional profiles. Key genes including KRT16, CXCL5, MMP10, ADAM12, and MALAT1 showed cell type-specific expression patterns. Pseudotime trajectory analysis revealed aberrant differentiation pathways from basal cells to specialized epithelial cells. Functional enrichment analysis highlighted inflammatory responses, immune system processes, and tissue remodeling as predominant biological processes in asthmatic airways. The network pharmacology analysis further identified 124 common targets, revealing that XQLT exerts multicomponent, synergistic therapeutic effects through core hubs such as NFE2L2 and NOS2.<h4>Conclusions</h4>This comprehensive single-cell transcriptomic atlas provides novel insights into the cellular heterogeneity and molecular mechanisms of pediatric asthma. The identification of cell type-specific gene expression patterns and developmental trajectories offers potential targets for precision therapeutic interventions.