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Parkinson's disease is the second most common neurological disease in Australia with 50 people diagnosed every day, yet there is currently no conclusive screening or test to help catch it early.
To be diagnosed with Parkinson's disease a person must undergo a clinical examination by a doctor, where certain physical symptoms such as resting tremors, rigidity and changes in walk and gait need to be present.
But a team of European researchers believe that a simple blood test could soon provide the answers to predicting the disease up to seven years before the onset of the motor symptoms, such as the characteristic tremors.
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The early markers for the disease lie in the blood, according to the study published in Nature Communications today.
Parkinson's disease is typically defined by slowness of movement, rigidity, and resting tremor but before these physical symptoms, there is a period of non-motor symptoms including sleep disorders such as REM sleep behaviour disorder.
Research teams from the UCL Institute of Child Health in the UK and the University Medical Center Goettingen in Germany analysed blood samples from three groups of individuals: those with Parkinson's, those with REM sleep behaviour disorder but no motor symptoms and healthy individuals.
They identified 23 proteins in the blood that were consistently dysregulated in the blood of individuals with Parkinson's disease and of these, six were also dysregulated in those with the sleep disorder.
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They then used an artificial intelligence model to predict a diagnosis based on blood composition.
The machine was able to predict which individuals would go on to develop Parkinson's disease with 79 per cent accuracy up to seven years before the onset of motor symptoms.
As well as providing earlier treatment for the person affected, it's hoped that being able to more accurately predict who will go on to develop Parkinson's disease will improve recruitment into preventative clinical trials, driving further research to improve the lives of sufferers.
However, the authors also caution that further validation of their results in larger populations is needed.
