Sidorov, Michael S.Deck, Gina M.Dolatshahi, MarjanThibert, RonaldBird, Lynne M.Chu, CatherinePhilpot, Benjamin D.2017-06-152017Sidorov, Michael S., Gina M. Deck, Marjan Dolatshahi, Ronald L. Thibert, Lynne M. Bird, Catherine J. Chu, and Benjamin D. Philpot. 2017. “Delta rhythmicity is a reliable EEG biomarker in Angelman syndrome: a parallel mouse and human analysis.” Journal of Neurodevelopmental Disorders 9 (1): 17. doi:10.1186/s11689-017-9195-8. http://dx.doi.org/10.1186/s11689-017-9195-8.http://nrs.harvard.edu/urn-3:HUL.InstRepos:33029703Background: 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. Electronic supplementary material The online version of this article (doi:10.1186/s11689-017-9195-8) contains supplementary material, which is available to authorized users.en-USAngelman syndromeBiomarkerDeltaEEGMouse modelOutcome measureUBE3AJournal Article2017-06-1510.1186/s11689-017-9195-8