Parkinson Hastalığında Entegre Çok Kohortlu Transkriptomik Meta-Analiz ve Moleküler Yerleştirme, Çekirdek Disregüle Hub Yollarını ve Terapötik Ligandları Tanımlar

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Abstract A significant loss of dopaminergic neurons is a hallmark of Parkinson's disease (PD), a progressive neurodegenerative movement disorder. Even though it is quite common throughout the world, there is still a critical clinical need for early molecular diagnostic markers before serious physical symptoms appear. Recent studies indicate that pyroptosis and chronic neuroinflammation work in concert as major drivers of disease development. This study proposed a reliable Parkinson's disease diagnostic model based on two key pyroptosis-related hub genes, DRD2 and SLC18A3, by combining multi-cohort transcriptome meta-analysis with functional pathway enrichment. Beyond genetic mapping, multi-target computational blind docking using AutoDock Vina predicts that the medicinal ligands donepezil and bromocriptine had strong conformational stability and structural binding affinity against these target macromolecules.This work suggests a novel, dual-purpose diagnostic and treatment pipeline that enhances early Parkinson's disease detection and finds possible small-molecule scaffolds for focused, disease-modifying treatments.

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