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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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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. |
format | Online Article Text |
id | pubmed-5422949 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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