Li Xin-Yu, Yu Wen-Kai, Wu Jing-Hao, He Wen-Jun, Cheng Yu-Nan, Gao Kai, Wei Yi-Han, Li Yu-Sheng
Department of Neurology, The First Affiliated Hospital of Zhengzhou University, No.1 Jianshe Dong Road, Zhengzhou, Henan, China.
Henan Engineering Research Center of Neural Function Detection and Regulation, Zhengzhou, Henan, China.
Sci Rep. 2025 Jan 8;15(1):1362. doi: 10.1038/s41598-024-84362-8.
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.
帕金森病(PD)和失眠是常见的神经系统疾病,越来越多的证据表明色氨酸(TRP)代谢与它们的发病机制有关。然而,TRP代谢导致这些疾病的确切机制仍未得到充分阐明。本研究探索与PD和失眠相关的共同色氨酸代谢相关基因(TMRG)及其潜在分子机制,旨在深入了解它们的共同发病机制。我们分析了从基因表达综合数据库(GEO)获得的PD(GSE100054)和失眠(GSE208668)数据集。TMRG来自分子特征数据库(MSigDB)和基因卡片数据库。通过将TMRG与这些数据集中的共同差异表达基因(DEG)进行交叉分析,确定了色氨酸代谢相关差异表达基因(TM-DEG)。通过蛋白质-蛋白质相互作用(PPI)网络分析、支持向量机递归特征消除(SVM-RFE)和极端梯度提升(XGBoost)机器学习,我们确定细胞色素P4501B1(CYP1B1)和电子传递黄素蛋白α(ETFA)为关键枢纽基因。随后,我们使用CIBERSORT和单样本基因集富集分析(ssGSEA)进一步研究枢纽基因与外周免疫激活和炎症反应之间的关联。此外,构建了以这些枢纽基因为中心的基因相互作用、药物-mRNA、转录因子(TF)-mRNA和竞争性内源RNA(ceRNA)网络,以探索调控机制和潜在药物相互作用。最后,通过生物信息学和动物实验验证,确定CYP1B1是一种与PD和失眠均相关的有前景的生物标志物。