Decoding distinctive features of plasma extracellular vesicles in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis is a multifactorial and multisystem motor neuron disease with currently no effective treatment. There is an urgent need to identify biomarkers that can tackle the disease's complexity and help in early diagnosis, prognosis, and therapy development. Extracellular vesicles (EVs) are nanostructures that are released by any cell type into body fluids. Their variable biophysical and biochemical characteristics reflect the parent cell's physiological and pathological state and make them an attractive source of multidimensional data for patient classification and stratification. To test whether EVs could be exploited as diagnostic and prognostic biomarkers in ALS, we analyzed plasma-derived EVs of ALS patients and relative healthy and diseased controls. Using the nickel-based isolation, a recently developed EV purification method, we unmasked peculiar features in plasma EVs of ALS patients with a potential straightforward application in a clinical setting. We report that the number of particles is increased in the plasma of ALS patients and two mouse models of ALS while the average diameter is decreased. Proteins like HSP90 and phosphorylated TDP-43 are differentially represented in ALS patients and mice compared to the controls. In terms of disease progression, the levels of phosphorylated TDP-43 and cyclophilin A, along with the EV size distribution, discriminated fast and slow disease progressors suggesting a new means for patient stratification. Finally, we conceived an innovative mathematical model based on machine learning techniques that integrating EV size distribution data with biochemical EV parameters resulted in very high prediction rates for disease diagnosis and prognosis.