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With help from artificial intelligence, researchers have identified a biological signature of Parkinson’s disease they hope could lead to a simple blood test for the condition at least seven years before symptoms appear.
A predictive test for Parkinson’s could be game changing.
The progressive condition affects more than 150,000 people in the UK and is currently the world’s fastest-growing neurodegenerative disorder.
Parkinson’s is a broad spectrum of conditions, but the most common symptoms are slowness of movement, tremors, and muscle stiffness.
There are currently no drugs that slow or stop Parkinson’s, and efforts to develop preventative treatments are hampered by the ability to know whether someone is going to develop the condition.
Like many progressive neurological conditions, by the time symptoms emerge, the damage to brain cells caused by Parkinson’s has already occurred.
“At present, we are shutting the stable door after the horse has bolted, and we need to start experimental treatments before patients develop symptoms,” said Professor Kevin Mills at UCL Great Ormond Street Institute of Child Health, who helped develop the blood test.
Using machine learning – a form of artificial intelligence – researchers from University College London and University Medical Centre in Goettingen, Sweden, screened blood samples from people with Parkinson’s and detected eight key proteins or “biomarkers” common to those with the condition.
They then used their machine learning tool to analyse blood samples taken a decade ago from people with a sleep condition called Rapid Eye Movement Disorder, around 75% of whom go on to develop Parkinson’s.
The AI has so far been able to correctly predict which patients went on to develop Parkinson’s and did so up to seven years before symptoms first appeared.
“By determining eight proteins in the blood, we can identify potential Parkinson’s patients several years in advance,” said Dr Michale Bartl at UMC…
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