Delta rhythmicity is a reliable EEG biomarker in Angelman syndrome: A parallel mouse and human analysis

Abstract

Background: Clinicians have qualitatively described rhythmic delta activity as a prominent EEG abnormality in individuals with Angelman syndrome, but this phenotype has yet to be rigorously quantified in the clinical population or validated in a preclinical model. Here, we sought to quantitatively measure delta rhythmicity and evaluate its fidelity as a biomarker. Methods: We quantified delta oscillations in mouse and human using parallel spectral analysis methods and measured regional, state-specific, and developmental changes in delta rhythms in a patient population. Results: Delta power was broadly increased and more dynamic in both the Angelman syndrome mouse model, relative to wild-type littermates, and in children with Angelman syndrome, relative to age-matched neurotypical controls. Enhanced delta oscillations in children with Angelman syndrome were present during wakefulness and sleep, were generalized across the neocortex, and were more pronounced at earlier ages. Conclusions: Delta rhythmicity phenotypes can serve as reliable biomarkers for Angelman syndrome in both preclinical and clinical settings.