Parkinson’s disease is the world’s fastest-growing neurodegenerative disorder and affects up to 10 million people across the globe. This disease has no cure; however, researchers and scientists have developed a simple blood test that uses Artificial Intelligence (AI) to predict Parkinson’s up to seven years before symptoms.
Parkinson’s disease is a progressive disorder caused by the death of nerve cells called the substantia nigra, which controls movement. These nerve cells die or become impaired, losing the ability to produce an important chemical called dopamine, due to the build-up of a protein alpha-synuclein.
Dopamine replacement therapy is given to patients who have already developed symptoms; early prediction and diagnosis tools could be valuable for finding treatments that slow or stop Parkinson’s disease by protecting the dopamine-producing brain cells.
Senior author, Professor Kevin Mills (UCL Great Ormond Street Institute of Child Health), said: “As new therapies become available to treat Parkinson’s, we need to diagnose patients before they have developed the symptoms. We cannot regrow our brain cells, and therefore we need to protect those that we have.”
Machine learning provides 100% accurate Parkinson’s disease diagnosis
Machine learning, a branch of AI, analysed eight blood-based biomarkers whose concentrations were altered in patients with Parkinson’s disease. The technology provided a diagnosis with 100% accuracy.
The team then experimented to see whether the test could predict the likelihood that a person would go on to develop Parkinson’s. They analysed blood from 72 patients with Rapid Eye Movement Behaviour Disorder (iRBD). The disorder results in patients physically acting out their dreams without knowing it. It is known that about 75-80% of people with this condition will eventually develop synucleinopathy, a type of brain disorder caused by protein buildup, including Parkinson’s disease.
When the machine learning tool analysed the blood, it identified that 79% of the iRBD patients had the same profile as someone with Parkinson’s.
The patients were followed up over ten years and the AI predictions matched the clinical conversion rate – with the team correctly predicting 16 patients who went on to develop Parkinson’s and did this up to seven years before the onset of any symptoms. The team continued to follow those predicted to get Parkinson’s to further verify the accuracy.
Co-first-author Dr Michael Bartl (University Medical Center Goettingen and Paracelsus-Elena-Klinik Kassel) who conducted the research from the clinical side alongside Dr Jenny Hällqvist (UCL Queen Square Institute of Neurology and National Hospital for Neurology & Neurosurgery), said: “By determining 8 proteins in the blood, we can identify potential Parkinson’s patients several years in advance. This means that drug therapies could potentially be given at an earlier stage, which could slow down disease progression or even prevent it from occurring.
“We have not only developed a test but can diagnose the disease based on markers that are directly linked to processes such as inflammation and degradation of non-functional proteins. So these markers represent possible targets for new drug treatments.”
Securing funding to create a simple blood test to ease the process
The team aim to secure funding to create a simpler blood test where blood can be spotted on a card and posted to the lab to predict Parkinson’s disease earlier than seven years before the onset of symptoms.
Professor David Dexter, Director of Research at Parkinson’s UK, said: “This research, co-funded by Parkinson’s UK, represents a major step forward in the search for a definitive and patient-friendly diagnostic test for Parkinson’s. Finding biological markers that can be identified and measured in the blood is much less invasive than a lumbar puncture, which is being used more and more in clinical research.
“With more work, it may be possible that this blood-based test could distinguish between Parkinson’s and other conditions that have some early similarities, such as Multiple Systems Atrophy or Dementia with Lewy Bodies.
“The findings add to an exciting flurry of recent activity towards finding a simple way to test for and measure Parkinson’s.”
