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

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Creator
  • Deck, Gina M
    • Other Affiliation: Department of Neurology, Massachusetts General Hospital, Boston, USA; Harvard Medical School, Boston, USA; Present Address: The Neurology Foundation, Rhode Island Hospital and Warren Alpert School of Medicine at Brown University, Providence, USA
  • Sidorov, Michael S
    • Affiliation: School of Medicine, Neuroscience Center, Neurodevelopment Disorders Research Center, Carolina Institute for Developmental Disabilities, Department of Cell Biology and Physiology
  • Chu, Catherine J
    • Other Affiliation: Department of Neurology, Massachusetts General Hospital, Boston, USA; Harvard Medical School, Boston, USA
  • Bird, Lynne M
    • Other Affiliation: Department of Pediatrics, University of California, San Diego, USA; Division of Dysmorphology/Genetics, Rady Children’s Hospital, San Diego, USA
  • Dolatshahi, Marjan
    • Other Affiliation: Department of Neurology, Massachusetts General Hospital, Boston, USA; Harvard Medical School, Boston, USA
  • Philpot, Benjamin
    • Affiliation: School of Medicine, Neuroscience Center, Neurodevelopment Disorders Research Center, Carolina Institute for Developmental Disabilities, Department of Cell Biology and Physiology
  • Thibert, Ronald L
    • Other Affiliation: Department of Neurology, Massachusetts General Hospital, Boston, USA
Abstract
  • 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.
Date of publication
Identifier
  • doi:10.1186/s11689-017-9195-8
Resource type
  • Article
Rights statement
  • In Copyright
Rights holder
  • The Author(s).
Language
  • English
Bibliographic citation
  • Journal of Neurodevelopmental Disorders. 2017 May 08;9(1):17
Publisher
  • BioMed Central
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