MND Phenotypes Differentiation: The Role of Multimodal Characterization at the Time of Diagnosis

SIMPLE SUMMARY: Diverse motor neuron diseases (MNDs) are associated with distinct survival rates, so their early differentiation is pivotal to gain a more reliable prognosis estimation in clinical and research settings. In this study, we therefore evaluated whether a multimodal characterization approach embedding clinical, cognitive/behavioral, genetic, and neurophysiological data may improve the discrimination of pure/predominant upper motor neuron (pUMN) and pure/predominant lower motor neuron (pLMN) disease forms from classic amyotrophic lateral sclerosis (ALS) already by the time of diagnosis. Our results suggest common cognitive and genetic features across the distinct MND phenotypes, but also demonstrate that highly specific clinical and neurophysiological measures provide valuable tools for an early discrimination between more benign and more aggressive disease forms. ABSTRACT: Pure/predominant upper motor neuron (pUMN) and lower motor neuron (pLMN) diseases have significantly better prognosis compared to amyotrophic lateral sclerosis (ALS), but their early differentiation is often challenging. We therefore tested whether a multimodal characterization approach embedding clinical, cognitive/behavioral, genetic, and neurophysiological data may improve the differentiation of pUMN and pLMN from ALS already by the time of diagnosis. Dunn’s and chi-squared tests were used to compare data from 41 ALS, 34 pLMN, and 19 pUMN cases with diagnoses confirmed throughout a 2-year observation period. Area under the curve (AUC) analyses were implemented to identify the finest tools for phenotypes discrimination. Relative to ALS, pLMN showed greater lower limbs weakness, lower UMN burden, and progression rate (p < 0.001–0.04). PUMN showed a greater frequency of lower limbs onset, higher UMN burden, lower ALSFRS-r and MRC progression rates (p < 0.001–0.03), and greater ulnar compound muscle action potential (CMAP) amplitude and tibial central motor conduction time (CMCT) (p = 0.05–0.03). The UMN progression rate was the finest measure to identify pLMN cases (AUC = 90%), while the MRC progression rate was the finest tool to identify pUMN (AUC = 82%). Detailed clinical and neurophysiological examinations may significantly improve MNDs differentiation, facilitating prognosis estimation and ameliorating stratification strategies for clinical trials enrollment.