Development of a Novel Electrochemiluminescence ELISA for Quantification of α-Synuclein Phosphorylated at Ser129 in Biological Samples

开发一种新型电化学发光 ELISA 方法,用于定量测定生物样品中 Ser129 位点磷酸化的 α-突触核蛋白

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作者:Suman Dutta, Simon Hornung, Hash Brown Taha, Karl Biggs, Ibrar Siddique, Lea M Chamoun, Hedieh Shahpasand-Kroner, Carter Lantz, Marcos Herrera-Vaquero, Nadia Stefanova, Joseph A Loo, Gal Bitan

Abstract

Synucleinopathies are a group of neurodegenerative diseases including Parkinson's disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). These diseases are characterized by the aggregation and deposition of α-synuclein (α-syn) in Lewy bodies (LBs) in PD and DLB or as glial cytoplasmic inclusions in MSA. In healthy brains, only ∼4% of α-syn is phosphorylated at Ser129 (pS129-α-syn), whereas >90% pS129-α-syn may be found in LBs, suggesting that pS129-α-syn could be a useful biomarker for synucleinopathies. However, a widely available, robust, sensitive, and reproducible method for measuring pS129-α-syn in biological fluids is currently missing. We used Meso Scale Discovery (MSD)'s electrochemiluminescence platform to create a new assay for sensitive detection of pS129-α-syn. We evaluated several combinations of capture and detection antibodies and used semisynthetic pS129-α-syn as a standard for the assay at a concentration range from 0.5 to 6.6 × 104 pg/mL. Using the antibody EP1536Y for capture and an anti-human α-syn antibody (MSD) for detection was the best combination in terms of assay sensitivity, specificity, and reproducibility. We tested the utility of the assay for the detection and quantification of pS129-α-syn in human cerebrospinal fluid, serum, plasma, saliva, and CNS-originating small extracellular vesicles, as well as in mouse brain lysates. Our data suggest that the assay can become a widely used method for detecting pS129-α-syn in biomedical studies including when only a limited volume of sample is available and high sensitivity is required, offering new opportunities for diagnostic biomarkers, monitoring disease progression, and quantifying outcome measures in clinical trials.

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