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2D-SEED aims to improve early diagnosis of different synucleinopathies. These diseases, encompassing Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy, are all related to a-synuclein (aS) aggregation. It is currently a major challenge to detect and distinguish disease-specific aggregated forms of aS before symptoms arise, while treatment may only be successful in the prodromal phase of the disease. 

To address this challenge, seed-amplification assays have been developed in recent years, in which patient fluids are mixed with recombinantly-expressed aS, which leads to measurable protein aggregation if the patient fluid contains fibril seeds, while no aggregation occurs in the absence of pathologic seeds. In practice, , these assays are challenging and time-consuming to perform, show limited inter-lab reproducibility, and cannot differentiate between different types of aS fibrils, which is important for disease diagnostic. Here, we propose to apply a highly protein-structure sensitive technology from the vibrational spectroscopy field, two-dimensional infrared (2DIR) spectroscopy, to assess the strain type present in the essay end products, potentially in a matter of minutes. 

While 2DIR has never been applied in the neurodegeneration clinic to date, our previous data shows that it is able to distinguish different in-vitro formed strains of aS. A multitude of fibril-structure sensitive features in 2DIR-spectra can be used to train neural networks against the diagnosis, allowing the sensitive and specific prediction of a patient’s synucleinopathy before symptoms arise. The development of such a tool will greatly help the development of patient-specific personalized therapies.