Rapid diagnosis and predicting the progression rate of ALS are now possible

08.10.2021

Thanks to the artificial intelligence of machine learning, the analysis of a specific set of lipid particles present in the blood (extracellular vesicles) makes it possible to diagnose the onset of Amyotrophic Lateral Sclerosis (ALS) accurately and quickly. With machine learning, predicting the speed and future outcome of ALS progression is also possible, as is reported in a study published in the scientific journal Molecular Neurodegeneration, which includes research conduct at the University of Padua Department of Mathematics.      

Coordinated by the Head of the Laboratory of Translational Biomarkers Valentina Bonetto of the Mario Negri Institute of Pharmacological Research IRCCS, and Manuela Basso of the Department of Cellular, Computational and Integrative Biology (CIBIO) of the University of Trento, the research outlines the collection and analysis of extracellular vesicles through a simple blood sample. Francesco Rinaldi of the Department of Mathematics of the University of Padua analysed and processed data from the isolated and characterized vesicles collected from each blood sample.  Rinaldi used a trained learning machine that can distinguish the extracellular vesicles of a healthy individual from that of someone affected by the degenerative disease.    

The published research represents an important perspective for a disease diagnosed only after several medical visits by experienced neurologists. Like a message in a bottle, extracellular vesicles release a set of proteins and nucleic acids into the bloodstream that highlights the health of cells.  

Amyotrophic Lateral Sclerosis (ALS) is the most common form of motor neuron disease. The progressiveness of the disease affects the nerve cells in the brain and spinal cord, causing loss of muscle control with poor prognosis over time. Despite numerous advances in basic and clinical research, there is no cure. Unfortunately, its diagnosis occurs most often only after the first motor symptoms appear during the onset of its advanced stage of damage. For years, the Laboratory of Translational Biomarkers of the Mario Negri Institute has been studying new markers capable of anticipating the diagnosis of the disease over time and defining its prognosis more accurately.

The study was made possible due to the availability and collaboration from the many neurological experts at the CRESLA Centre, the AOU City of Health and Science of Turin, the University Hospital of Padua, the NeMO Clinical Center of Milan, ICS Maugeri of Milan, and the Casa Cura Policlinico of Milan.

The study was funded thanks to the Italian Ministry of Health’s "Young Researchers" Project, of which Dr. Basso and Dr. Pasetto are responsible and co-responsible of respectively(GR-2016-02361552), and by the European Marie-Sklodowska -Curie Individual Fellowships Funding Program awarded to Dr. Basso (752470).