Symptom–Gene Network Analysis for Exploring the Potential Application of Korean Medicine in Parkinson’s Disease

Objectives: Parkinson’s disease (PD) is a multifactorial neurodegenerative disorder characterized by both motor and non-motor symptoms. While pharmacological and surgical treatments primarily target symptom alleviation, they often fall short in addressing disease progression or the complexity of symptoms. This study aimed to identify key genes associated with diverse PD symptoms through network centrality analysis and investigate their relevance to herbal medicines used in Korean Medicine (KM), thereby exploring the scientific basis for KM interventions in PD.Methods: PD-related symptoms and associated genes were collected via GeneCards, and a two-mode network was constructed. Centrality measures (degree, betweenness, closeness, eigenvector) were calculated using NetMiner software to identify key genes. These core genes were then matched with herbal medicines listed in Korean clinical practice guidelines for PD. Enrichment analyses were performed using DAVID to evaluate the biological functions and pathways linked to gene-herb associations.Results: REM sleep behavior disorder emerged as the most central symptom across all network indices. A total of 13 key genes (e.g., SNCA, MAPT, APOE, IL6, APP) were identified. Among 41 herbs analyzed, Prunus persica and Pheretima aspergillum showed strong associations with these genes, indicating their potential multi-target effects on synaptic regulation, neuroinflammation, and amyloid metabolism.Conclusions: This study presents a systems biology approach integrating symptom-gene networks with traditional herbal prescriptions, offering a novel framework for personalized KM strategies in PD management. The findings support the potential of selected herbs as multi-target modulators and warrant further experimental validation.