Parkinson's disease (PD) is a neurodegenerative disorder that is characterized by symptoms such as rigor, tremor and bradykinesia. A reliable and early diagnosis could improve the development of early therapeutic strategies before death of dopaminergic neurons leads to the first clinical symptoms. The sFIDA (surface-based fluorescence intensity distribution analysis) assay is a highly sensitive method to determine the concentration of α-synuclein (α-syn) oligomers which are presumably the major toxic isoform of α-syn and potentially the most direct biomarker for PD. Oligomer-based diagnostic tests require standard molecules that closely mimic the native oligomer. This is particularly important for calibration and assessment of inter-assay variation. In this study, we generated a standard in form of α-syn coated silica nanoparticles (α-syn-SiNaPs) that are in the size range of α-syn oligomers and provide a defined number of α-syn epitopes. The preparation of the sFIDA assay was realized on an automated platform to allow handling of high number of samples and reduce the effects of human error. The assay outcome was analyzed by determination of coefficient of variation and linearity for the applied α-syn-SiNaPs concentrations. Additionally, the limit of detection and lower limit of quantification were determined yielding concentrations in the lower femtomolar range.
Keywords: Automation; Diagnostic biomarker; Neurodegenerative diseases; Parkinson's disease; Protein aggregates; Silica nanoparticles (SiNaPs); Surface-based fluorescence intensity distribution analysis (sFIDA); α-Synuclein.
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