Classification of a-synuclein-induced changes in the AAV a-synuclein rat model of Parkinson’s disease using electrophysiological measurements of visual processing

FG Østergaard, etc
Scientific Reports, 2020


Biomarkers suitable for early diagnosis and monitoring disease progression are the cornerstone of developing disease-modifying treatments for neurodegenerative diseases such as Parkinson’s disease (PD). Besides motor complications, PD is also characterized by deficits in visual processing. Here, we investigate how virally-mediated overexpression of a-synuclein in the substantia nigra pars compacta impacts visual processing in a well-established rodent model of PD. After a unilateral injection of vector, human a-synuclein was detected in the striatum and superior colliculus (SC). In parallel, there was a significant delay in the latency of the transient VEPs from the affected side of the SC in late stages of the disease. Inhibition of leucine-rich repeat kinase using PFE360 failed to rescue the VEP delay and instead increased the latency of the VEP waveform. A support vector machine classifier accurately classified rats according to their `disease state’ using frequency-domain data from steady-state visual evoked potentials (SSVEP). Overall, these findings indicate that the latency of the rodent VEP is sensitive to changes mediated by the increased expression of a-synuclein and especially when full overexpression is obtained, whereas the SSVEP facilitated detection of a-synuclein across reflects all stages of PD model progression.

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Journal
Scientific Reports
Year
2020
Page
doi: 10.1038/s41598-020-68808-3
Institute
H. Lundbeck A/S