Fruit flies have provided clues that could lead to better ways of diagnosing early-onset Parkinson’s disease.
Ryan West, PhD, of York University, England, and colleagues compared fruit flies with mutations associated with early-onset Parkinson’s to healthy control flies. Based on an analysis of visual responses of the flies, the ones with the mutations had increased neuronal activity to stimulation compared to the others.
Creating a data bank with the results, the researchers were able to classify uncategorized flies as either having the Parkinson’s mutation or not with 85% accuracy, they reported. The researchers added that the results are likely applicable to human detection of Parkinson’s given that visual profiling has been used in the past to identify genetic markers.
In addition, it is possible to translate the result in the clinic where early vision changes could provide a biomarker for Parkinson’s prior to the onsets of traditional symptoms that impact the motor system. In other words, profiling visual responses in humans could become a reliable test in diagnosing early-onset Parkinson’s.
“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,” West said in a statement. “Such early detection is essential if we are to understand disease progression and develop novel therapeutics,”
New research by biologists at the University of York could lead to improved methods of detection for early-onset Parkinson’s Disease.
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.
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% accuracy.