Parkinson's disease (PD) and insomnia are prevalent neurological disorders, with emerging evidence implicating tryptophan (TRP) metabolism in their pathogenesis. However, the precise mechanisms by which TRP metabolism contributes to these conditions remain insufficiently elucidated. This study explores shared tryptophan metabolism-related genes (TMRGs) and molecular mechanisms underlying PD and insomnia, aiming to provide insights into their shared pathogenesis. We analyzed datasets for PD (GSE100054) and insomnia (GSE208668) obtained from the Gene Expression Omnibus (GEO) database. TMRGs were obtained from the Molecular Signatures Database (MSigDB) and the Genecards database. Tryptophan metabolism-related differentially expressed genes (TM-DEGs) were identified by intersecting TMRGs with shared differentially expressed genes (DEGs) from these datasets. Through Protein-Protein Interaction (PPI) network analysis, Support Vector Machine-Recursive Feature Elimination (SVM-RFE) , and Extreme Gradient Boosting (XGBoost) machine learning, we identified Cytochrome P4501B1 (CYP1B1) and Electron Transfer Flavoprotein Alpha (ETFA) as key hub genes. Subsequently, we employed CIBERSORT and single-sample gene set enrichment analysis (ssGSEA) to further investigate the association between hub genes and peripheral immune activation and inflammatory response. Additionally, gene interaction, Drug-mRNA, Transcription Factor (TF)-mRNA, and competing endogenous RNA (ceRNA) networks centered on these hub genes were constructed to explore regulatory mechanisms and potential drug interactions. Finally, validation through bioinformatics and animal experiments identified CYP1B1 as a promising biomarker associated with both PD and insomnia.
Keywords: Biomarker; Insomnia; Parkinson’s disease; Tryptophan.
© 2025. The Author(s).