Grant: Project Grant

Amyotrophic lateral sclerosis (ALS) is a devastating heterogeneous neurodegenerative condition with abnormalities in protein accumulation (TDP-43, SOD1), vascularization, inflammation, neuronal activity and cerebral atrophy. In keeping with the tenets of Personalized Medicine, treatments should be tailored to individual therapeutic needs as opposed to treating all patients with the same approach. In ALS, however, we currently do not have appropriate methods for pathophysiological patient staging and stratification. Furthermore, because we continue to lack robust tools to characterize each patient's distinctive disease progression, evaluating the effectiveness of different therapies remains challenging. Prompted by the imperative for customized treatment of ALS, our goal is the implementation and clinical validation of a biologically-defined staging and stratification of the ALS spectrum using an artificial intelligence (AI) framework to integrate massive amounts of molecular and neuroimaging data. Consequently, we are integrating a large amount of biological data (including transcriptomics and neuroimaging) into a simplified and clinician-friendly personalized clinical profile reflecting both disease progression and variants. This framework aims to bridge the Molecular, Neuroimaging and AI fields to overcome the major limitations of traditional clinical diagnoses and eventually provide patients with true Personalized Medicine. In this project, the clinical applicability of our already developed model will be validated with two large-scale populations in the ALS spectrum. Critically, all resulting analytic tools will be shared with the international community via user-friendly multitool software, contributing to translate our research findings into daily clinical practice.