4.5 Article

Evaluation of electroencephalography biomarkers for Angelman syndrome during overnight sleep

Journal

AUTISM RESEARCH
Volume 15, Issue 6, Pages 1031-1042

Publisher

WILEY
DOI: 10.1002/aur.2709

Keywords

Angelman syndrome; biomarker; delta; EEG; sleep; spindle

Funding

  1. Angelman Syndrome Alliance
  2. Eunice Kennedy Shriver National Institute of Child Health and Human Development [R01HD093771, 5P50HD103573]
  3. George Washington University Health Services Scholarship

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Angelman syndrome (AS) is a neurodevelopmental disorder caused by maternal UBE3A gene mutations, resulting in intellectual disability and other symptoms. Research shows increased low-frequency delta EEG rhythms in AS patients during overnight sleep, suggesting its potential as a biomarker for future clinical trials. Abnormal sleep spindles were not reliably detected during overnight sleep, indicating that delta rhythms may be a more reliable marker for AS.
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.

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