Objective Chronic Rhinosinusitis with Nasal Polyps (CRSwNP) affects 1%–4% of the global population with high recurrence rates. While methionine metabolism abnormalities contribute to various inflammatory diseases, their role in CRSwNP pathogenesis remains unclear. This study aimed to systematically investigate the role of methionine metabolism in CRSwNP and identify potential biomarkers and therapeutic targets through integrating multi-omics data and interpretable machine learning approaches. Methods CRSwNP transcriptomic datasets (GSE136825, GSE179265) and single-cell data (GSE276503) were obtained from GEO database. Single-cell RNA sequencing analysis, differential expression analysis using limma, and Weighted Gene co-expression Network Analysis (WGCNA) were performed to identify methionine metabolism-related candidate genes. Three machine learning algorithms (LASSO, SVM-RFE, XGBoost) with SHAP interpretation screened core genes. Functions and mechanisms were explored through single-gene GSEA, ceRNA network construction, transcription factor prediction, immune infiltration analysis, and pseudotime trajectory analysis. Potential therapeutic drugs were identified via molecular docking. Results Among 14 candidate genes, CSTB, IGFBP3, and TCN1 were identified as core genes with excellent diagnostic performance (AUC > 0.85). SHAP analysis revealed CSTB and IGFBP3 as disease risk-promoting factors, while TCN1 showed protective effects. Single-cell analysis demonstrated all three genes were predominantly expressed in epithelial cells with significant differential expression patterns. They were enriched in primary immunodeficiency pathways and significantly correlated with immune cell infiltration, particularly M2 macrophages and activated dendritic cells. Molecular docking identified five potential therapeutic drugs including ambroxol, carbamazepine, and curcumin with favorable binding energies. Conclusion Methionine metabolism participates in CRSwNP pathogenesis by regulating CSTB, IGFBP3, and TCN1, affecting epithelial cell function and immune microenvironment. These genes represent promising biomarkers for diagnosis and potential therapeutic targets, providing theoretical basis for developing metabolic-immune intervention strategies in CRSwNP management. Level of Evidence 3.
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Dan Lin (2026) studied this question.
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