Jill L. Silverman

Angelman syndrome (AS) is a genetic neurodevelopmental disorder characterized by developmental delay, lack of speech, seizures, intellectual disability, hypotonia, and motor coordination deficits. Motor abilities are an important outcome measure in AS as they comprise a broad repertoire of metrics including ataxia, hypotonia, delayed ambulation, crouched gait, and poor posture, and motor dysfunction affects nearly every individual with AS. Guided by collaborative work with AS clinicians studying gait, the goal of this study was to perform an in‐depth gait analysis using the automated treadmill assay, DigiGait. Our hypothesis is that gait presents a strong opportunity for a reliable, quantitative, and translational metric that can serve to evaluate novel pharmacological, dietary, and genetic therapies. In this study, we used an automated gait analysis system, in addition to standard motor behavioral assays, to evaluate components of motor, exploration, coordination, balance, and gait impairments across the lifespan in an AS mouse model. Our study demonstrated marked global motoric deficits in AS mice, corroborating previous reports. Uniquely, this is the first report of nuanced aberrations in quantitative spatial and temporal components of gait in AS mice compared to sex‐ and age‐matched wildtype littermates followed longitudinally using metrics that are analogous in AS individuals. Our findings contribute evidence toward the use of nuanced motor outcomes (i.e., gait) as valuable and translationally powerful metrics for therapeutic development for AS, as well as other genetic neurodevelopmental syndromes. Lay Summary Movement disorders affect nearly every individual with Angelman Syndrome (AS). The most common motor problems include spasticity, ataxia of gait (observed in the majority of ambulatory individuals), tremor, and muscle weakness. This report focused on quantifying various spatial and temporal aspects of gait as a reliable, translatable outcome measure in a preclinical AS model longitudinally across development. By increasing the number of translational, reliable, functional outcome measures in our wheelhouse, we will create more opportunities for identifying and advancing successful medical interventions.