Center for Neuroscience Research, Children's National Medical Center, Washington, District of Columbia, USA.
The George Washington University School of Medicine and Health Sciences, Washington, District of Columbia, USA.
Autism Res. 2022 Jun;15(6):1031-1042. doi: 10.1002/aur.2709. Epub 2022 Mar 19.
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.
天使综合征（AS）是一种神经发育障碍，由母本 UBE3A 基因功能丧失突变引起。AS 的特征是智力残疾、言语和运动技能受损、癫痫和睡眠障碍。在 AS 的啮齿动物模型中，从休眠的父本等位基因重新表达功能性神经元 UBE3A 的多种治疗策略已取得成功，现已进入儿童早期临床试验阶段。开发可靠和客观的 AS 生物标志物对于指导当前和未来临床试验的设计和实施至关重要。我们之前的工作通过量化白天的短程脑电图（EEG）来定义 AS 的有前途的生物标志物。在这里，我们想知道夜间睡眠是否更适合检测 AS 的 EEG 生物标志物。我们回顾性分析了来自 12 名 AS 患者的 12 项夜间睡眠研究的 EEG，这些患者的年龄和性别与唐氏综合征和神经典型对照组相匹配，重点关注低频（2-4 Hz）δ 节律和睡眠纺锤波。在整个夜间睡眠期间，AS 患者的 δ EEG 节律均增加，但与清醒相比，夜间睡眠并不能提高检测到 δ 增加的能力。在 AS 患者的 EEG 中，夜间睡眠期间并未可靠地检测到异常的睡眠纺锤波，这表明 δ 节律是一种更可靠的生物标志物。总的来说，我们得出结论，清醒期足以量化 AS 生物标志物的 δ EEG 节律，甚至可能是理想的。
