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

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 α-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 α-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 α-synuclein and especially when full overexpression is obtained, whereas the SSVEP facilitated detection of α-synuclein across reflects all stages of PD model progression.