Abstract
BACKGROUND: Parkinson's disease (PD) is influenced by various factors, with lysosome function playing a critical role. However, the specific involvement of lysosome-related genes (LRGs) in PD remains unclear. OBJECTIVE: This study aims to identify biomarkers specific to PD that exhibit robust disease prediction capabilities. METHODS: Datasets for patients with PD, LRGs, and inflammation-related genes (IRGs) were retrieved from online databases. miRNAs and mRNAs within key modules were selected through Weighted Gene Co-expression Network Analysis (WGCNA), revealing strong associations with PD. A miRNA-mRNA network was constructed based on highly correlated PD-related LRGs (PD-LRGs) and miRNAs within these modules. Candidate genes were identified by intersecting target genes, differentially expressed genes (DEGs), PD-LRGs, and module-associated mRNAs. Machine learning and expression validation were employed to confirm these biomarkers. A nomogram was established, and its diagnostic performance was evaluated using a confusion matrix. Drug predictions were conducted based on these biomarkers. Spearman's correlation analyses were performed to assess the relationship between IRGs, freezing of gait (FOG)-related genes, and biomarkers. Molecular regulatory networks were constructed using datasets and online resources. Finally, clinical samples were collected for quantitative PCR (qPCR) validation of biomarker expression. RESULTS: Key modules related to PD were identified, comprising 190 miRNAs and 7,633 mRNAs. A miRNA-mRNA network was constructed based on 55 PD-LRGs and 181 miRNAs, resulting in the identification of 26 candidate genes strongly linked to lysosomal function. FGD4 and MAN2B1 were selected as biomarkers, and a gene expression-based risk prediction table was created. These biomarkers were significantly correlated with IRGs and several FOG-related genes. Gene localization analysis revealed that FGD4 and LRRK2, both critical to the FOG pathway, are located on chromosome 12. Drug prediction revealed that Tetrachlorodibenzodioxin and bisphenol A target both FGD4 and MAN2B1. qPCR analysis confirmed that FGD4 and MAN2B1 expression levels were significantly higher in patients with PD compared to healthy controls (p < 0.05). CONCLUSION: FGD4 and MAN2B1 act as lysosomal biomarkers associated with PD and exhibit strong correlations with genes involved in PD-related freezing of gait. This study offers novel insights into PD diagnosis.