Inferring microarray datasets reveals critical biomarkers and potential drug targets of Parkinson's disease

Parkinson's disease (PD) is a critical neurological disorder characterized by loss of voluntary motor control and substantial slowing of movement. While traditionally attributed to environmental factors, recent studies underscore the significant role of genetics in the onset and progression of PD. This study aimed to identify differentially expressed genes (DEGs) and relevant pathways in PD by analyzing gene expression data from four datasets (83 PD and 53 control substantia nigra samples) sourced from the Gene Expression Omnibus (GEO) database. Using GEO2R, we identified common DEGs and performed functional annotation and KEGG pathway enrichment analysis through Enrichr. We constructed a protein-protein interaction (PPI) network using StringDB and identified hub genes via CytoHubba. Results revealed 18 critical DEGs enriched in pathways such as dopaminergic synapse and cocaine addiction. Key hub genes included Tyrosine Hydroxylase (TH), Solute Carrier Family 18 Member A2 (SLC18A2), and Potassium Inwardly Rectifying Channel Subfamily J Member 6 (KCNJ6). These findings provide insights into the molecular mechanisms of PD, highlighting potential biomarkers and therapeutic targets. This study offers a robust framework for future research and the development of effective treatment strategies for Parkinson's disease.