A group of scientists from University College London (UCL) and University Medical Center Goettingen, London [UK], have created a straightforward blood test that uses artificial intelligence to predict Parkinson's disease up to seven years before symptoms appear. .
Parkinson's disease, which currently affects approximately 10 million people worldwide, is the neurological disease with the highest growth rate in the world.
The disease progresses over time and is caused by the death of nerve cells in the substantia nigra, an area of the brain that controls movement. Due to the accumulation of the protein alpha-synuclein, these nerve cells degenerate or degenerate, losing their ability to produce the important neurotransmitter dopamine. Currently, people with Parkinson's have already developed symptoms. Symptoms such as tremors, slowing of movement and gait, and memory problems are treated with dopamine replacement therapy.But researchers believe early prediction and diagnosis will be valuable in finding treatments that can slow or stop Parkinson's by protecting dopamine-producing brain cells.
Senior author, Professor Kevin Mills (UCL Great Ormond Street Institute of Child Health) said: “As new treatments become available to treat Parkinson's, we need to diagnose patients before symptoms develop. Our brain cells cannot regrow and so we need to protect the ones we have.
“We are currently closing the stable door after the horse has bolted and we need to start experimental treatments before patients develop symptoms. Therefore, we are using cutting-edge technology to find new and better biomarkers for Parkinson's disease. Ready to use.And develop them into a test that we can translate into any large NHS laboratory with sufficient funding, we hope this could be possible within two years." The research, published in Nature Communications, found that when AI A branch called machine learning analyzed a panel of eight blood-based biomarkers whose concentrations are altered in Parkinson's patients, so it can provide a diagnosis with 100% accuracy.
The team then conducted experiments to see whether the test could predict the likelihood that a person would develop Parkinson's disease.
They did this by analyzing the blood of 72 patients with rapid eye movement behavior disorder (IRBD). This disorder results in patients physically acting out their dreams without realizing it (having vivid or violent dreams).It is now known that about 75-80% of people with IRBD will develop synucleinopathy (a type of brain disorder caused by an abnormal buildup of a protein called alpha-synuclein in brain cells) – including Parkinson's. When machine learning The tool analyzed the blood of these patients and found that 79% of the IRBD patients had a similar profile to someone with Parkinson's.
Patients were followed over the course of ten years and the AI predictions have so far matched the clinical conversion rate – the team correctly predicted that 16 patients were going to develop Parkinson's and up to seven years before onset They were able to do this. Of any symptoms. The team is now continuing to look at predictors of developing Parkinson's to further verify the test's accuracy.
Co-first-author Dr. Michael Bartl (University Medical Center Goettingen and Paracelsus-Elena-Clinic Kassel) who conducted the research from the clinical side with Dr. Jenny Hallqvist (UCL Queen Square Institute of Neurology and the National Hospital for Neurology and Neurosurgery), he said.: "By determining 8 proteins in the blood, we can identify potential Parkinson's patients several years earlier. This means that drug treatment can potentially be given at an earlier stage, potentially slowing the progression of the disease. Or may even prevent it from occurring."We have developed not only 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. These markers therefore represent potential targets for new drug treatments."
Co-author, Professor Kailash Bhatia (UCL Queen Square Institute of Neurology and the National Hospital for Neurology and Neurosurgery) and his team are currently investigating the accuracy of the test by analyzing samples from people who have, for example, developed Parkinson's. Are at high risk of.Those in which there is a mutation in a particular gene such as 'LRRK2' or 'GBA' that causes Gaucher disease.
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. Such biological markers Finding those that can be identified and measured in the blood is much less invasive than lumbar puncture, which is being used more and more in clinical research. "With more work, it may be possible that This blood-based test can distinguish between Parkinson's and other conditions that have some initial similarities, such as multiple system atrophy or dementia with Lewy bodies.
"The findings add to an exciting flurry of recent activity towards finding a simpler way to test and measure Parkinson's."
Parkinson's disease, which currently affects approximately 10 million people worldwide, is the neurological disease with the highest growth rate in the world.
The disease progresses over time and is caused by the death of nerve cells in the substantia nigra, an area of the brain that controls movement. Due to the accumulation of the protein alpha-synuclein, these nerve cells degenerate or degenerate, losing their ability to produce the important neurotransmitter dopamine. Currently, people with Parkinson's have already developed symptoms. Symptoms such as tremors, slowing of movement and gait, and memory problems are treated with dopamine replacement therapy.But researchers believe early prediction and diagnosis will be valuable in finding treatments that can slow or stop Parkinson's by protecting dopamine-producing brain cells.
Senior author, Professor Kevin Mills (UCL Great Ormond Street Institute of Child Health) said: “As new treatments become available to treat Parkinson's, we need to diagnose patients before symptoms develop. Our brain cells cannot regrow and so we need to protect the ones we have.
“We are currently closing the stable door after the horse has bolted and we need to start experimental treatments before patients develop symptoms. Therefore, we are using cutting-edge technology to find new and better biomarkers for Parkinson's disease. Ready to use.And develop them into a test that we can translate into any large NHS laboratory with sufficient funding, we hope this could be possible within two years." The research, published in Nature Communications, found that when AI A branch called machine learning analyzed a panel of eight blood-based biomarkers whose concentrations are altered in Parkinson's patients, so it can provide a diagnosis with 100% accuracy.
The team then conducted experiments to see whether the test could predict the likelihood that a person would develop Parkinson's disease.
They did this by analyzing the blood of 72 patients with rapid eye movement behavior disorder (IRBD). This disorder results in patients physically acting out their dreams without realizing it (having vivid or violent dreams).It is now known that about 75-80% of people with IRBD will develop synucleinopathy (a type of brain disorder caused by an abnormal buildup of a protein called alpha-synuclein in brain cells) – including Parkinson's. When machine learning The tool analyzed the blood of these patients and found that 79% of the IRBD patients had a similar profile to someone with Parkinson's.
Patients were followed over the course of ten years and the AI predictions have so far matched the clinical conversion rate – the team correctly predicted that 16 patients were going to develop Parkinson's and up to seven years before onset They were able to do this. Of any symptoms. The team is now continuing to look at predictors of developing Parkinson's to further verify the test's accuracy.
Co-first-author Dr. Michael Bartl (University Medical Center Goettingen and Paracelsus-Elena-Clinic Kassel) who conducted the research from the clinical side with Dr. Jenny Hallqvist (UCL Queen Square Institute of Neurology and the National Hospital for Neurology and Neurosurgery), he said.: "By determining 8 proteins in the blood, we can identify potential Parkinson's patients several years earlier. This means that drug treatment can potentially be given at an earlier stage, potentially slowing the progression of the disease. Or may even prevent it from occurring."We have developed not only 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. These markers therefore represent potential targets for new drug treatments."
Co-author, Professor Kailash Bhatia (UCL Queen Square Institute of Neurology and the National Hospital for Neurology and Neurosurgery) and his team are currently investigating the accuracy of the test by analyzing samples from people who have, for example, developed Parkinson's. Are at high risk of.Those in which there is a mutation in a particular gene such as 'LRRK2' or 'GBA' that causes Gaucher disease.
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. Such biological markers Finding those that can be identified and measured in the blood is much less invasive than lumbar puncture, which is being used more and more in clinical research. "With more work, it may be possible that This blood-based test can distinguish between Parkinson's and other conditions that have some initial similarities, such as multiple system atrophy or dementia with Lewy bodies.
"The findings add to an exciting flurry of recent activity towards finding a simpler way to test and measure Parkinson's."
