Detección y Perfilado de Vesículas Extracelulares Relacionadas con Enfermedades Neurodegenerativas a través de...

Early and accurate diagnosis of neurodegenerative diseases such as Parkinson's disease (PD) remains challenging due to the lack of reliable biomarkers during presymptomatic or nonspecific stages. Extracellular vesicles (EVs) are promising biomarkers because they carry disease-specific proteins on their membrane and within their cargo. However, conventional protein analysis methods face challenges to rapidly analyze and profile these proteins. Here, we introduce a label-free surface plasmon resonance (SPR) biosensing platform that integrates neurotoxin-induced in vitro PD models with quantitative EV biomarker profiling across intact and lysed states. Wild-type (wEVs) and disease-mimicking EVs (dEVs) are derived from human SH-SY5Y cells exposed to MPP⁺ and 6-OHDA to represent early- and late-stage PD, respectively. The multiplexed SPR chip, optimized through mixed-SAM surface chemistry and controlled antibody surface coverage, enables simultaneous detection of general EV markers (CD81, NCAM) and disease-associated α-synuclein (α-syn) species, including monomeric, aggregated, and phosphorylated forms, with a detection limit of 5.0 × 10⁶ EVs/mL. Intact-EV assays reveal stage-dependent α-syn remodeling, where MPP⁺ dEVs show 5-fold higher surface α-syn enrichment than wEVs, while 6-OHDA dEVs exhibit over 10-fold elevation of aggregated α-syn, signifying enhanced extracellular aggregation at advanced stages. Lysed-EV analysis uncovers progressive intravesicular accumulation, with aggregate-associated responses increasing by over an order of magnitude from wEVs to 6-OHDA dEVs. Normalization to the luminal marker Alix further reveals a continuous rise in α-syn/Alix ratios across PD progression. Collectively, these findings demonstrate that neurotoxic stress drives both surface externalization and luminal encapsulation of aggregated α-syn in a stage-resolved manner, establishing a quantitative, label-free strategy for profiling EV-associated biomarkers of PD progression.