Abnormal coherence and sleep composition in children with Angelman syndrome: a retrospective EEG study / Hanna DEN BAKKER in Molecular Autism, 9 (2018)  

Public ISBD [article]  inMolecular Autism > 9 (2018) . - 32p. Titre : Abnormal coherence and sleep composition in children with Angelman syndrome: a retrospective EEG study Type de document : texte imprimé Auteurs : Hanna DEN BAKKER, Auteur ; Michael S. SIDOROV, Auteur ; Zheng FAN, Auteur ; David J. LEE, Auteur ; Lynne M. BIRD, Auteur ; Catherine J. CHU, Auteur ; Benjamin D. PHILPOT, Auteur Article en page(s) : 32p. Langues : Anglais (eng) Mots-clés : Angelman Syndrome/physiopathology  Case-Control Studies  Child  Delta Rhythm  Female  Gamma Rhythm  Humans  Male  Sleep Stages  Angelman syndrome  Biomarker  Coherence  eeg  Spindles  UBE3A Index. décimale : PER Périodiques Résumé : Background: Angelman syndrome (AS) is a neurodevelopmental disorder characterized by intellectual disability, speech and motor impairments, epilepsy, abnormal sleep, and phenotypic overlap with autism. Individuals with AS display characteristic EEG patterns including high-amplitude rhythmic delta waves. Here, we sought to quantitatively explore EEG architecture in AS beyond known spectral power phenotypes. We were motivated by studies of functional connectivity and sleep spindles in autism to study these EEG readouts in children with AS. Methods: We analyzed retrospective wake and sleep EEGs from children with AS (age 4-11) and age-matched neurotypical controls. We assessed long-range and short-range functional connectivity by measuring coherence across multiple frequencies during wake and sleep. We quantified sleep spindles using automated and manual approaches. Results: During wakefulness, children with AS showed enhanced long-range EEG coherence across a wide range of frequencies. During sleep, children with AS showed increased long-range EEG coherence specifically in the gamma band. EEGs from children with AS contained fewer sleep spindles, and these spindles were shorter in duration than their neurotypical counterparts. Conclusions: We demonstrate two quantitative readouts of dysregulated sleep composition in children with AS-gamma coherence and spindles-and describe how functional connectivity patterns may be disrupted during wakefulness. Quantitative EEG phenotypes have potential as biomarkers and readouts of target engagement for future clinical trials and provide clues into how neural circuits are dysregulated in children with AS. En ligne : https://dx.doi.org/10.1186/s13229-018-0214-8 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=371 [article] Abnormal coherence and sleep composition in children with Angelman syndrome: a retrospective EEG study [texte imprimé] / Hanna DEN BAKKER, Auteur ; Michael S. SIDOROV, Auteur ; Zheng FAN, Auteur ; David J. LEE, Auteur ; Lynne M. BIRD, Auteur ; Catherine J. CHU, Auteur ; Benjamin D. PHILPOT, Auteur . - 32p. Langues : Anglais (eng) in Molecular Autism > 9 (2018) . - 32p. Mots-clés : Angelman Syndrome/physiopathology  Case-Control Studies  Child  Delta Rhythm  Female  Gamma Rhythm  Humans  Male  Sleep Stages  Angelman syndrome  Biomarker  Coherence  eeg  Spindles  UBE3A Index. décimale : PER Périodiques Résumé : Background: Angelman syndrome (AS) is a neurodevelopmental disorder characterized by intellectual disability, speech and motor impairments, epilepsy, abnormal sleep, and phenotypic overlap with autism. Individuals with AS display characteristic EEG patterns including high-amplitude rhythmic delta waves. Here, we sought to quantitatively explore EEG architecture in AS beyond known spectral power phenotypes. We were motivated by studies of functional connectivity and sleep spindles in autism to study these EEG readouts in children with AS. Methods: We analyzed retrospective wake and sleep EEGs from children with AS (age 4-11) and age-matched neurotypical controls. We assessed long-range and short-range functional connectivity by measuring coherence across multiple frequencies during wake and sleep. We quantified sleep spindles using automated and manual approaches. Results: During wakefulness, children with AS showed enhanced long-range EEG coherence across a wide range of frequencies. During sleep, children with AS showed increased long-range EEG coherence specifically in the gamma band. EEGs from children with AS contained fewer sleep spindles, and these spindles were shorter in duration than their neurotypical counterparts. Conclusions: We demonstrate two quantitative readouts of dysregulated sleep composition in children with AS-gamma coherence and spindles-and describe how functional connectivity patterns may be disrupted during wakefulness. Quantitative EEG phenotypes have potential as biomarkers and readouts of target engagement for future clinical trials and provide clues into how neural circuits are dysregulated in children with AS. En ligne : https://dx.doi.org/10.1186/s13229-018-0214-8 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=371

Evaluation of electroencephalography biomarkers for Angelman syndrome during overnight sleep / Yuval LEVIN in Autism Research, 15-6 (June 2022)  

Public ISBD [article]  inAutism Research > 15-6 (June 2022) . - p.1031-1042 Titre : Evaluation of electroencephalography biomarkers for Angelman syndrome during overnight sleep Type de document : texte imprimé 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 [article] Evaluation of electroencephalography biomarkers for Angelman syndrome during overnight sleep [texte imprimé] / 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

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