Artificial Intelligence at the service of patients with Amyotrophic Lateral Sclerosis (ALS) who are given the opportunity not only to receive a prompt diagnosis but also to have a sort of forecast of the more or less rapid progression of the disease. It is possible thanks to an Italian study, published in the scientific journal Molecular Neurodegeneration, which demonstrates that a particular blood test will allow to decode a sort of ‘messages in the bottle’ released by the cells and from which it will be possible to know their state of health. The news comes on the eve of the XIV National ALS Day, promoted by Aisla, the Italian Association of Amyotrophic Lateral Sclerosis, and which is celebrated on Sunday 19 September in hundreds of Italian squares.
The delay of diagnosis
Amyotrophic Lateral Sclerosis is the most common disease of the motor neuron, an essential cell for sending commands to our skeletal muscles and allowing movement. ALS is a neurodegenerative disease with a poor prognosis. Despite the numerous advances in basic and clinical research, there is no cure and it is diagnosed after several medical investigations repeated over time by an experienced neurologist and at the appearance of the first motor symptoms that reveal a situation of advanced damage. “ALS patients – they explain Andrea Calvo, of the Regional Expert Center for ALS of Turin (Aou City of Health and Science of Turin and Department of Neuroscience of the University of Turin) and Christian Lunetta of the NeMO Clinical Center in Milan and medical director of Aisla – receive a conclusive diagnosis, on average, after about a year from the onset of symptoms, experiencing long periods of frustration, and are inserted with great delay in experimental treatment protocols, reducing the chance of success. The disease is also very heterogeneous both in terms of aggression and speed of progression, making prognosis and treatment planning difficult ”.
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A team effort
That is why the result of this research is particularly valuable to patients. The discovery is the result of the Italian multicenter study designed and coordinated by Valentina Bonetto, head of the Laboratory of Translational Biomarkers of the Institute of Pharmacological Research Mario Negri Irccs and by Manuela Basso of the Department of Cellular, Computational and Integrated Biology (Cibio) of the University of Trento in collaboration with the Cresla center, Aou City of Health and Science of Turin, the University Hospital of Padua and in Milan: the NeMO Clinical Center, ICS Maugeri and the Polyclinic Nursing Home.
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Vesicles under examination with the AI
The researchers collected the vesicles that were isolated and characterized by simple blood sampling. The data obtained were then analyzed and processed by Francesco Rinaldi of the Department of Mathematics of the University of Padua, which used Artificial Intelligence (AI) models to accurately predict whether the extracellular vesicles belonged to a healthy individual or an individual suffering from degenerative disease. “We have developed – he explains Laura Pasetto of the Mario Negri Institute, first author of the work – a rapid protocol that allows to measure the characteristics of the extracellular vesicles in the blood of patients with ALS. We have decoded the information deriving from these small lipid particles circulating in the blood and we have understood how to distinguish these patients from others suffering from different neurological and muscular diseases ”.
Characterization of ALS patients
“The data collected with this characterization – adds Manuela Basso – show that the vesicles of ALS patients have different sizes and levels of proteins from healthy controls and patients with muscular dystrophies or Kennedy’s disease, diseases that can show similar symptoms in the early stages. Using these parameters we were also able to accurately predict the rate of disease progression “. In addition to offering a possibility of early diagnosis, what other perspectives does this discovery open? “The identification of biomarkers – replies Valentina Bonetto – specific and predictive for diagnosis and prognosis would be of great help not only for the clinical management of patients but also for the development of an effective therapy. The same results have emerged in animal models and this also holds promise for the monitoring of future drug trials. Now validation studies await us to be able to transfer the findings, detected on a sample made up of 106 ALS patients and 96 control subjects, to clinical practice “.
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