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Updated: Sep 17, 2025

Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson's Disease
Published on: January 7, 2014
Pathway Analysis and Genetic Markers in Parkinson's Disease: Insights into Subtype-Specific Mechanisms
Sara Taremi Horoufi1, Davood Zaeifi2
1Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Science, Tehran, Iran.
Abstract:
Parkinson's disease (PD) is a complex disease influenced by both genetic and environmental factors. Despite advances in understanding PD genetics, subtype-specific mechanisms remain poorly characterized. This study aims to identify distinct genetic markers and pathways across PD subtypes, addressing this gap to enable targeted diagnostics and therapies. Genes associated with PD were collected from various databases and categorized into groups based on the PD type to assess the PD risk. Protein interaction analysis was conducted to identify functional clusters and key genes within each group. KEGG enrichment analysis revealed common genes and pathways among the different PD groups. This study conformed to the PRISMA 2020 guidelines for systematic data collection and analysis. Hub genes such as PRKN, SNCA, and LRRK2 have demonstrated considerable potential as biomarkers for genetic predisposition in PD, alongside the identification of additional complementary genes. Analysis of hub node variants highlighted specific genetic variations in these genes. We identified several microRNAs, including hsa-miR-335-5p, hsa-miR-19a-3p, and hsa-miR-106a-5p, as well as transcription factors that interact with crucial hub genes. This study refines subtype-specific mechanisms for established PD genes and identifies novel genetic markers and pathways associated with juvenile, young-onset, late-onset, familial, and sporadic Parkinson's disease, enhancing our understanding of their molecular mechanisms and potential for targeted diagnostics and therapies. Specifically, we highlight the roles of hub genes, such as PRKN, SNCA, and LRRK2, alongside significant microRNA interactions, which may serve as biomarkers for early detection and personalized treatment approaches.
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