RNA Networks of Lysosomal-Related Biomarkers in Parkinson’s Disease and Their Correlations with Freezing of Gait-Associated Genes
Abstract
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.
Fields of Study & Subjects
Parkinson's Disease Mechanisms and Treatments
Bioinformatics and Genomic Networks
Nuclear Receptors and Signaling
Publication details
- Journal / source
- Figshare
- Publication date
- 1 January 2026
- Document type
- Dataset