Identification of SNCA and DRD2 as key genes linking parkinson's disease and circadian rhythm through bioinformatics...

This study aims to screen for common differentially expressed genes (DEGs) related to Parkinson's disease (PD) and circadian rhythm (CR) through bioinformatics methods, and further analyze their potential molecular mechanisms and traditional Chinese medicine-targeted components, providing new targets and drug development ideas for the treatment of PD. This study first obtained PD-related microarray data from the GEO database to screen for differentially expressed genes. Using the WGCNA algorithm to construct a gene co-expression network and filter key module genes. Combine GeneCards and Msigdb databases to obtain CR-related genes, and use the Venny2.1 tool to screen for common DEGs between PD and CR. Further, the String database and Cytoscape software were used to construct a protein-protein interaction network, and the DAVID platform was utilized for KEGG and GO enrichment analysis. Using the Cytohubba plugin to screen hub genes and evaluate their diagnostic value with ROC curves. In addition, the mRNA-miRNA regulatory network was constructed using the Mirwalk database, and potential targeted traditional Chinese medicines and their core components were predicted using the Coremine and HERB databases. Finally, molecular docking was used to verify the binding activity of key components with the targets. This study identified a total of 659 PD-related DEGs and 2555 CR-related genes. Through WGCNA analysis, 3586 key module genes were obtained, and finally, 62 common key genes for PD and CR were screened and a PPI network was constructed. GO and KEGG enrichment analyses showed that these genes are mainly enriched in biological processes such as dopamine biosynthesis and neurodegenerative disease pathways. Through Cytohubba, two hub genes, SNCA and DRD2, were identified, and their expression levels were significantly lower in the PD group compared to the control group. ROC curve analysis showed that DRD2 and SNCA had high diagnostic value (AUC of 0.87 and 0.80, respectively). The further constructed mRNA-miRNA network shows that SNCA and DRD2 are associated with 669 and 404 miRNAs, respectively, and there are 143 common miRNAs. Three core traditional Chinese medicines (Gastrodia Elata, Malt, Papaya) and their five core components (ent-Epicatechin, HMF, Protocatechuic Acid, Succinic Acid, and Vanillin) were screened through the Coremine database and the HERB database. The molecular docking results show that ent-Epicatechin, vanillin, and protocatechuic acid have binding energies with the target protein below - 5.5 kcal/mol, indicating stable binding. This study identified the hub genes SNCA and DRD2 related to PD and CR through bioinformatics analysis, revealing their potential molecular mechanisms and targeted traditional Chinese medicine components. These findings provide new biomarkers and candidate molecules for drug development in the diagnosis and treatment of PD.