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

ABSTRACT: 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-prote

SUBMITTER: Zhang J 

PROVIDER: S-EPMC12381130 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature