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Development of a Novel Electrochemiluminescence ELISA for Quantification of α-Synuclein Phosphorylated at Ser 129 in Biological Samples.

Suman DuttaSimon HornungHash Brown TahaKarl BiggsIbrar SiddiqueLea M ChamounHedieh Shahpasand-KronerCarter LantzMarcos Herrera-VaqueroNadia StefanovaJoseph A LooGal Bitan
Published in: ACS chemical neuroscience (2023)
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 Ser 129 (pS 129 -α-syn), whereas >90% pS 129 -α-syn may be found in LBs, suggesting that pS 129 -α-syn could be a useful biomarker for synucleinopathies. However, a widely available, robust, sensitive, and reproducible method for measuring pS 129 -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 pS 129 -α-syn. We evaluated several combinations of capture and detection antibodies and used semisynthetic pS 129 -α-syn as a standard for the assay at a concentration range from 0.5 to 6.6 × 10 4 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 pS 129 -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 pS 129 -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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