Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease for which reliable biomarkers for early diagnosis, prognosis, and patient stratification remain limited. Previous genetic, proteomic, imaging, and electrophysiological studies have identified potential biomarkers and phenotype modifiers, improving the understanding of motor neuron degeneration mechanisms. However, these findings have not yet been translated into a clinically useful biomarker algorithm. This observational study aims to develop a biomarker panel to support the diagnosis, prognosis, and stratification of patients with ALS. Clinical and molecular biomarkers previously associated with ALS phenotypes will be analyzed simultaneously and integrated into a multivariable predictive model. Clinical data and biological samples will be collected and analyzed to identify combinations of biomarkers associated with ALS phenotypes.