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

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 m...

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Autores principales: Sidorov, Michael S., Deck, Gina M., Dolatshahi, Marjan, Thibert, Ronald L., Bird, Lynne M., Chu, Catherine J., Philpot, Benjamin D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5422949/
https://www.ncbi.nlm.nih.gov/pubmed/28503211
http://dx.doi.org/10.1186/s11689-017-9195-8
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author Sidorov, Michael S.
Deck, Gina M.
Dolatshahi, Marjan
Thibert, Ronald L.
Bird, Lynne M.
Chu, Catherine J.
Philpot, Benjamin D.
author_facet Sidorov, Michael S.
Deck, Gina M.
Dolatshahi, Marjan
Thibert, Ronald L.
Bird, Lynne M.
Chu, Catherine J.
Philpot, Benjamin D.
author_sort Sidorov, Michael S.
collection PubMed
description 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. 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.
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spelling pubmed-54229492017-05-12 Delta rhythmicity is a reliable EEG biomarker in Angelman syndrome: a parallel mouse and human analysis Sidorov, Michael S. Deck, Gina M. Dolatshahi, Marjan Thibert, Ronald L. Bird, Lynne M. Chu, Catherine J. Philpot, Benjamin D. J Neurodev Disord Research 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. 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. BioMed Central 2017-05-08 /pmc/articles/PMC5422949/ /pubmed/28503211 http://dx.doi.org/10.1186/s11689-017-9195-8 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Sidorov, Michael S.
Deck, Gina M.
Dolatshahi, Marjan
Thibert, Ronald L.
Bird, Lynne M.
Chu, Catherine J.
Philpot, Benjamin D.
Delta rhythmicity is a reliable EEG biomarker in Angelman syndrome: a parallel mouse and human analysis
title Delta rhythmicity is a reliable EEG biomarker in Angelman syndrome: a parallel mouse and human analysis
title_full Delta rhythmicity is a reliable EEG biomarker in Angelman syndrome: a parallel mouse and human analysis
title_fullStr Delta rhythmicity is a reliable EEG biomarker in Angelman syndrome: a parallel mouse and human analysis
title_full_unstemmed Delta rhythmicity is a reliable EEG biomarker in Angelman syndrome: a parallel mouse and human analysis
title_short Delta rhythmicity is a reliable EEG biomarker in Angelman syndrome: a parallel mouse and human analysis
title_sort delta rhythmicity is a reliable eeg biomarker in angelman syndrome: a parallel mouse and human analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5422949/
https://www.ncbi.nlm.nih.gov/pubmed/28503211
http://dx.doi.org/10.1186/s11689-017-9195-8
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