OBJECTIVE: To develop a Drosophila model for testing gene-environment interactions in Parkinson’s disease.
BACKGROUND: Parkinson’s disease (PD) is a neurodegenerative disease characterized by α-synuclein aggregation and the progressive loss of dopamine (DA) neurons in the substantia nigra. Risk of PD arises due to a combination of genetic and environmental factors, which may interact with one another, termed gene-environment (GxE) interactions. An inverse association between smoking cigarettes and risk of developing PD is well-established, but trials of nicotine as a therapeutic option for PD have yielded mixed results. A previous genome-wide GxE interaction study identified genetic variation in the synaptic-vesicle glycoprotein 2C (SV2C) locus as an important mediator of the degree to which smoking is inversely associated with PD. We sought to determine the mechanism of the smoking-SV2C interaction in a Drosophila model of PD.
DESIGN/METHODS: In this model, human α-synuclein is expressed in all neurons, and flies develop the hallmarks of PD, including motor dysfunction, loss of DA neurons, and formation of α-synuclein inclusions. We assessed the effects of increasing doses of nicotine on these parameters of neurodegeneration, in the presence or absence of SV2C knockdown.
RESULTS: We demonstrate that α-synuclein-expressing flies treated with nicotine (the presumed active ingredient in tobacco) have significant improvement in locomotion, in total number of brain cells and in DA neuron counts, and in α-synuclein aggregation. However, in α-synuclein-expressing flies in which Drosophila homologs of SV2C are knocked down, nicotine fails to rescue neurodegeneration and in fact further worsens motor behavior and loss of dopaminergic neurons.
CONCLUSIONS: This work confirms a GxE interaction between nicotine and SV2C, defines a role for this interaction in α-synuclein proteostasis, and strengthens the idea that future clinical trials on nicotine should take genetic variation in SV2C into account. Further, this study provides proof of concept that our model can be used for mechanistic study of GxE, paving the way for investigation of additional known GxE interactions or identification of novel GxE.