Abstract
BACKGROUND: Parkinson's disease (PD) and multiple system atrophy (MSA) are two distinct α-synucleinopathies traditionally differentiated through clinical symptoms. Early diagnosis of MSA is problematic, and seed amplification assays (SAAs), such as real-time quaking-induced conversion (RT-QuIC), offer the potential to distinguish these diseases through their underlying α-synuclein (α-Syn) pathology and proteoforms. Currently, SAAs provide a binary result, signifying either the presence or absence of α-Syn seeds. To enhance the diagnostic potential and biological relevance of these assays, there is a pressing need to incorporate quantification and stratification of α-Syn proteoform-specific aggregation kinetics into current SAA pipelines. METHODS: Optimal RT-QuIC assay conditions for α-Syn seeds extracted from PD and MSA patient brains were determined, and assay kinetics were assessed for α-Syn seeds from different pathologically relevant brain regions (medulla, substantia nigra, hippocampus, middle temporal gyrus, and cerebellum). The conformational profiles of disease- and region-specific α-Syn proteoforms were determined by subjecting the amplified reaction products to concentration-dependent proteolytic digestion with proteinase K. RESULTS: Using our protocol, PD and MSA could be accurately delineated using proteoform-specific aggregation kinetics, including α-Syn aggregation rate, maximum relative fluorescence, the gradient of amplification, and core protofilament size. MSA cases yielded significantly higher values than PD cases across all four kinetic parameters in brain tissues, with the MSA-cerebellar phenotype having higher maximum relative fluorescence than the MSA-Parkinsonian phenotype. Statistical significance was maintained when the data were analysed regionally and when all regions were grouped. CONCLUSIONS: Our RT-QuIC protocol and analysis pipeline can distinguish between PD and MSA, and between MSA phenotypes. MSA α-Syn seeds induce faster propagation and exhibit higher aggregation kinetics than PD α-Syn, mirroring the biological differences observed in brain tissue. With further validation of these quantitative parameters, we propose that SAAs could advance from a yes/no diagnostic to a theranostic biomarker that could be utilised in developing therapeutics.