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Delta rhythmicity is a reliable EEG biomarker in Angelman syndrome: a parallel mouse and human analysis / M. S. SIDOROV in Journal of Neurodevelopmental Disorders, 9-1 (December 2017)
[article]
Titre : Delta rhythmicity is a reliable EEG biomarker in Angelman syndrome: a parallel mouse and human analysis Type de document : Texte imprimé et/ou numérique Auteurs : M. S. SIDOROV, Auteur ; G. M. DECK, Auteur ; M. DOLATSHAHI, Auteur ; R. L. THIBERT, Auteur ; L. M. BIRD, Auteur ; C. J. CHU, Auteur ; B. D. PHILPOT, Auteur Article en page(s) : p.17 Langues : Anglais (eng) Mots-clés : Angelman syndrome Biomarker Delta Eeg Mouse model Outcome measure Ube3a Index. décimale : PER Périodiques Résumé : 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. En ligne : http://dx.doi.org/10.1186/s11689-017-9195-8 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=350
in Journal of Neurodevelopmental Disorders > 9-1 (December 2017) . - p.17[article] Delta rhythmicity is a reliable EEG biomarker in Angelman syndrome: a parallel mouse and human analysis [Texte imprimé et/ou numérique] / M. S. SIDOROV, Auteur ; G. M. DECK, Auteur ; M. DOLATSHAHI, Auteur ; R. L. THIBERT, Auteur ; L. M. BIRD, Auteur ; C. J. CHU, Auteur ; B. D. PHILPOT, Auteur . - p.17.
Langues : Anglais (eng)
in Journal of Neurodevelopmental Disorders > 9-1 (December 2017) . - p.17
Mots-clés : Angelman syndrome Biomarker Delta Eeg Mouse model Outcome measure Ube3a Index. décimale : PER Périodiques Résumé : 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. En ligne : http://dx.doi.org/10.1186/s11689-017-9195-8 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=350 Evaluation of electroencephalography biomarkers for Angelman syndrome during overnight sleep / Yuval LEVIN in Autism Research, 15-6 (June 2022)
[article]
Titre : Evaluation of electroencephalography biomarkers for Angelman syndrome during overnight sleep Type de document : Texte imprimé et/ou numérique Auteurs : Yuval LEVIN, Auteur ; Nishitha S. HOSAMANE, Auteur ; Taylor E. MCNAIR, Auteur ; Shrujana S. KUNNAM, Auteur ; Benjamin D. PHILPOT, Auteur ; Zheng FAN, Auteur ; Michael S. SIDOROV, Auteur Article en page(s) : p.1031-1042 Langues : Anglais (eng) Mots-clés : Angelman Syndrome/complications/diagnosis/genetics Autism Spectrum Disorder Biomarkers Electroencephalography Humans Retrospective Studies Sleep/physiology Angelman syndrome Eeg biomarker delta sleep spindle Medpace, Inc. for EEG analysis. Index. décimale : PER Périodiques Résumé : Angelman syndrome (AS) is a neurodevelopmental disorder caused by loss-of-function mutations in the maternal copy of the UBE3A gene. AS is characterized by intellectual disability, impaired speech and motor skills, epilepsy, and sleep disruptions. Multiple treatment strategies to re-express functional neuronal UBE3A from the dormant paternal allele were successful in rodent models of AS and have now moved to early phase clinical trials in children. Developing reliable and objective AS biomarkers is essential to guide the design and execution of current and future clinical trials. Our prior work quantified short daytime electroencephalograms (EEGs) to define promising biomarkers for AS. Here, we asked whether overnight sleep is better suited to detect AS EEG biomarkers. We retrospectively analyzed EEGs from 12 overnight sleep studies from individuals with AS with age and sex-matched Down syndrome and neurotypical controls, focusing on low frequency (2-4?Hz) delta rhythms and sleep spindles. Delta EEG rhythms were increased in individuals with AS during all stages of overnight sleep, but overnight sleep did not provide additional benefit over wake in the ability to detect increased delta. Abnormal sleep spindles were not reliably detected in EEGs from individuals with AS during overnight sleep, suggesting that delta rhythms represent a more reliable biomarker. Overall, we conclude that periods of wakefulness are sufficient, and perhaps ideal, to quantify delta EEG rhythms for use as AS biomarkers. LAY SUMMARY: Electroencephalography (EEG) is a safe and reliable way of measuring abnormal brain activity in Angelman syndrome. We found that low-frequency "delta" EEG rhythms are increased in individuals with Angelman syndrome during all stages of overnight sleep. Delta rhythms can be used as a tool to measure improvement in future clinical trials. En ligne : http://dx.doi.org/10.1002/aur.2709 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=476
in Autism Research > 15-6 (June 2022) . - p.1031-1042[article] Evaluation of electroencephalography biomarkers for Angelman syndrome during overnight sleep [Texte imprimé et/ou numérique] / Yuval LEVIN, Auteur ; Nishitha S. HOSAMANE, Auteur ; Taylor E. MCNAIR, Auteur ; Shrujana S. KUNNAM, Auteur ; Benjamin D. PHILPOT, Auteur ; Zheng FAN, Auteur ; Michael S. SIDOROV, Auteur . - p.1031-1042.
Langues : Anglais (eng)
in Autism Research > 15-6 (June 2022) . - p.1031-1042
Mots-clés : Angelman Syndrome/complications/diagnosis/genetics Autism Spectrum Disorder Biomarkers Electroencephalography Humans Retrospective Studies Sleep/physiology Angelman syndrome Eeg biomarker delta sleep spindle Medpace, Inc. for EEG analysis. Index. décimale : PER Périodiques Résumé : Angelman syndrome (AS) is a neurodevelopmental disorder caused by loss-of-function mutations in the maternal copy of the UBE3A gene. AS is characterized by intellectual disability, impaired speech and motor skills, epilepsy, and sleep disruptions. Multiple treatment strategies to re-express functional neuronal UBE3A from the dormant paternal allele were successful in rodent models of AS and have now moved to early phase clinical trials in children. Developing reliable and objective AS biomarkers is essential to guide the design and execution of current and future clinical trials. Our prior work quantified short daytime electroencephalograms (EEGs) to define promising biomarkers for AS. Here, we asked whether overnight sleep is better suited to detect AS EEG biomarkers. We retrospectively analyzed EEGs from 12 overnight sleep studies from individuals with AS with age and sex-matched Down syndrome and neurotypical controls, focusing on low frequency (2-4?Hz) delta rhythms and sleep spindles. Delta EEG rhythms were increased in individuals with AS during all stages of overnight sleep, but overnight sleep did not provide additional benefit over wake in the ability to detect increased delta. Abnormal sleep spindles were not reliably detected in EEGs from individuals with AS during overnight sleep, suggesting that delta rhythms represent a more reliable biomarker. Overall, we conclude that periods of wakefulness are sufficient, and perhaps ideal, to quantify delta EEG rhythms for use as AS biomarkers. LAY SUMMARY: Electroencephalography (EEG) is a safe and reliable way of measuring abnormal brain activity in Angelman syndrome. We found that low-frequency "delta" EEG rhythms are increased in individuals with Angelman syndrome during all stages of overnight sleep. Delta rhythms can be used as a tool to measure improvement in future clinical trials. En ligne : http://dx.doi.org/10.1002/aur.2709 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=476