A blood test could in future help doctors diagnose Parkinson’s disease as many as seven years before symptoms appear. Indeed, thanks to the use ofArtificial intelligencea group of researchers led by University College London And University Medical Center Goettingen (Germany), to which the University of Bologna and the Institute of Neurological Sciences of Bologna also contributed, has identified a series of biomarkers associated with the disease. The results, published in the journal Nature Communicationsallow us to hypothesize the administration of preventive interventions capable of slowing down, if not even blocking, the damage caused by the disease.
Parkinson’s, which affects nearly 10 million people worldwide, is a progressive neurodegenerative disease caused by the death of nerve cells in the part of the brain called the “substantia nigra”, responsible for controlling movement. In people with Parkinson’s, these nerve cells die or deteriorate, losing the ability to produce dopamine, an important chemical, due to the buildup of the protein alpha-synuclein. Today, people with Parkinson’s are treated with dopamine replacement therapy after they have already developed symptoms such as tremor, slow movement and gait, stiffness and memory problems. However, researchers believe that a prediction and early diagnosis they would be invaluable in finding treatments that can slow down or even stop Parkinson’s by protecting brain cells.
“As new therapies for Parkinson’s become available, we need to diagnose patients with the disease before they develop symptoms,” notes the study’s senior author, Kevin Mills, from the Ucl Great Ormond Street Institute of Child Health. “We can’t regrow our brain cells, so we have to protect the ones we have,” she adds. At the moment, however, “we are closing the stable door after the oxen have escaped – underlines Mills – and we have to start experimental treatments sooner. So we set out to use cutting-edge technology to find new and better biomarkers for Parkinson’s disease and develop them into a test that we can translate into any large NHS laboratory. With sufficient funding, we hope it will be possible within two years.”
Scientists have discovered that with the help of machine learning, by analyzing a panel of 8 biomarkers in the blood whose concentrations are altered in patients with Parkinson’s disease, it is possible to obtain a diagnosis with 100% accuracy. This tool was then tested on its ability to predict the disease in advance on 72 people affected by it REM sleep behavior disorder, which often anticipates Parkinson’s: 79% of participants were found to have the same profile as people suffering from Parkinson’s and so far, in the following 10 years of monitoring, the AI’s predictions have proven to be correct. The research team, in fact, correctly predicted that 16 patients would develop Parkinson’s and was able to do so up to 7 years before the onset of any symptoms.
Now researchers are continuing to follow patients who may develop the disease to further test the test’s accuracy. “By determining 8 proteins in the blood – explains one of the first authors of the study, Michael Bartl, University Medical Center Goettingen – we can identify potential Parkinson’s patients several years in advance. This means that drug therapies could be administered at an earlier stage, which could slow the progression of the disease or even prevent it from appearing,” she adds. The co-author Kailash Bhatia, Ucl Queen Square Institute of Neurology, and his team are currently examining the accuracy of the test by analyzing samples from people who are part of the population at high risk of developing Parkinson’s, for example those who have mutations in particular genes such as Lrrk2 or Gba . The researchers hope to also obtain funding to create a test that can be performed more easily by leaving a drop of blood on a card to be sent to the laboratory.
Emanuele Perugini
I study
