Enhancing Detection of Early Onset Parkinson’s Disease

New research by biologists at the University of York could lead to improved methods of detection for early-onset Parkinson’s Disease (PD).

Recording the responses of fruit flies (Drosophila melanogaster) to different visual patterns, using methods adapted from the study of vision in humans, scientists in York’s Department of Biology investigated the nervous systems of flies with different types of Parkinson’s mutations.

Researchers compared flies carrying mutations associated with early-onset Parkinson’s with ‘normal’ control flies, and found increased neuronal activity to stimulation in the former group in ‘young’ flies.

By mapping the visual responses of fruit flies with different Parkinson’s genes, the scientists built a substantial data bank of results. Using this they were able to classify unknown flies as having a Parkinson’s related mutation with 85 per cent accuracy.

artoon of a fly watching TV.
By mapping the visual responses of fruit flies with different Parkinson’s genes, the scientists built a substantial data bank of results. Using this they were able to classify unknown flies as having a Parkinson’s related mutation with 85 per cent accuracy. Credit: Dr. Ryan West.

Researchers believe it may be possible to transfer this method back to the clinic where early changes in vision may provide a ‘biomarker’ allowing screening for Parkinson’s before the onset of traditional motor-symptoms. Therefore, profiling human visual responses could prove an accurate and reliable test in diagnosing people with early-onset PD.

This method is also likely to succeed when transferred to human detection of Parkinson’s, as visual profiling in humans has proved accurate in the past in detecting genetic markers. In this study, as more complex light stimulations have been used, a more accurate picture of detecting a wider variety of different genetic markers has been revealed.

Dr. Ryan West, Postdoctoral Research Scientist in York’s Department of Biology and Lead Author on the study, said: “Increased visual activity in young fruit flies with early-onset Parkinson’s mutations is a significant finding, as it may provide an early-onset biomarker for people at risk of Parkinson’s.

“Using 64 different combinations of visual stimuli, we now have a comprehensive bank of the reactions of fruit flies carrying different genetic mutations. We can see that fruit flies carrying different mutations have distinct patterns of visual responses, suggesting this is a reliable method in classifying Parkinson’s genotypes.

“We hope this method may be translatable to the clinic where changes in vision may provide an early indication of early-onset Parkinson’s. Such early detection is essential if we are to understand disease progression and develop novel therapeutics.”

About this Parkinson’s disease research

Funding: Funded by the Wellcome Trust.

Source: Saskia Angenent – University of York
Image Source: The image is credited to Dr. Ryan West
Original Research: Full open access research for “Classification of Parkinson’s Disease Genotypes in Drosophila Using Spatiotemporal Profiling of Vision” by Ryan J.H. West, Christopher J.H. Elliott and Alex R. Wade in Scientific Reports. Published online November 24 2015 doi:10.1038/srep16933


Abstract

Classification of Parkinson’s Disease Genotypes in Drosophila Using Spatiotemporal Profiling of Vision

Electrophysiological studies indicate altered contrast processing in some Parkinson’s Disease (PD) patients. We recently demonstrated that vision is altered in Drosophila PD models and hypothesised that different types of genetic and idiopathic PD may affect dopaminergic visual signalling pathways differently. Here we asked whether visual responses in Drosophila could be used to identify PD mutations. To mimic a clinical setting a range of flies was used. Young flies from four control lines were compared to three early-onset PD mutations (PINK1, DJ-1α and DJ-1β), and to two other neurodegenerative mutations, one in the fly LRRK2 orthologue (dLRRK) the other in eggroll, a model of general neurodegeneration in Drosophila. Stimuli were contrast reversing gratings spanning 64 spatiotemporal frequency combinations. We recorded the steady-state visually-evoked response amplitude across all combinations. We found that the pattern of neuronal responses differed between genotypes. Wild-type and early-onset PD flies formed separate clusters; the late-onset mutation is an outlier. Neuronal responses in early-onset PD flies were stronger than in wild-types. Multivariate pattern analysis grouped flies by PD/non-PD genotype with an accuracy >85%. We propose that machine learning algorithms may be useful in increasing the diagnostic specificity of human electrophysiological measurements in both animal models and PD patients.

“Classification of Parkinson’s Disease Genotypes in Drosophila Using Spatiotemporal Profiling of Vision” by Ryan J.H. West, Christopher J.H. Elliott and Alex R. Wade in Scientific Reports. Published online November 24 2015 doi:10.1038/srep16933

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