Deep Plasma Proteomics Coupled with Functional Genomics Reveals Drivers of Parkinson's Disease Progression and Levodopa Response
Parkinsons disease (PD) is a progressive neurodegenerative disorder lacking disease-modifying therapies, and its clinical management is limited by the absence of accessible biomarkers for tracking disease progression and treatment response. To map these complex disease trajectories, we implemented an ultra-deep plasma proteomics workflow integrating Mag-Net extracellular vesicle enrichment with Orbitrap Astral mass spectrometry to profile longitudinal samples from PD patients. This approach quantified 6,481 plasma proteins at unprecedented depth in PD studies, revealing distinct signatures directly associated with disease duration and dopaminergic therapy exposure. Candidate biomarkers were subsequently validated in an independent cohort using ELISA, demonstrating robust predictive utility in AI-driven prediction models. To uncover the mechanistic drivers underlying these systemic changes, we intersected our proteomic data with novel proteome-wide gene overexpression perturbation screens designed to identify regulators of alpha-synuclein pre-formed fibril (PFF) uptake and PFF-induced neuronal toxicity. Finally, an integrative network analysis combining three independent proteome-wide assays revealed that key pathological hubs, such as CD14, IFNG, and PLAT, are targets of currently approved pharmacological agents. Collectively, these findings provide a comprehensive, systems-level map for PD biomarker discovery and highlight druggable pathways to advance precision medicine strategies.