Park Insung, Kokudo Chihiro, Seol Jaehoon, Ishihara Asuka, Zhang Simeng, Uchizawa Akiko, Osumi Haruka, Miyamoto Ryusuke, Horie Kazumasa, Suzuki Chihiro, Suzuki Yoko, Okura Tomohiro, Diaz Javier, Vogt Kaspar E, Tokuyama Kumpei
International Institute for Integrative Sleep Medicine (WPI-IIIS), University of Tsukuba, Tsukuba, Japan.
Graduate School of Comprehensive Human Science, University of Tsukuba, Tsukuba, Japan.
Front Aging Neurosci. 2022 Dec 6;14:1050648. doi: 10.3389/fnagi.2022.1050648. eCollection 2022.
Traditionally, age-related deterioration of sleep architecture in older individuals has been evaluated by visual scoring of polysomnographic (PSG) recordings with regard to total sleep time and latencies. In the present study, we additionally compared the non-REM sleep (NREM) stage and delta, theta, alpha, and sigma wave stability between young and older subjects to extract features that may explain age-related changes in sleep.
Polysomnographic recordings were performed in 11 healthy older (72.6 ± 2.4 years) and 9 healthy young (23.3 ± 1.1 years) females. In addition to total sleep time, the sleep stage, delta power amplitude, and delta, theta, alpha, and sigma wave stability were evaluated by sleep stage transition analysis and a novel computational method based on a coefficient of variation of the envelope (CVE) analysis, respectively.
In older subjects, total sleep time and slow-wave sleep (SWS) time were shorter whereas wake after sleep onset was longer. The number of SWS episodes was similar between age groups, however, sleep stage transition analysis revealed that SWS was less stable in older individuals. NREM sleep stages in descending order of delta power were: SWS, N2, and N1, and delta power during NREM sleep in older subjects was lower than in young subjects. The CVE of the delta-band is an index of delta wave stability and showed significant differences between age groups. When separately analyzed for each NREM stage, different CVE clusters in NREM were clearly observed between young and older subjects. A lower delta CVE and amplitude were also observed in older subjects compared with young subjects in N2 and SWS. Additionally, lower CVE values in the theta, alpha and sigma bands were also characteristic of older participants.
The present study shows a decrease of SWS stability in older subjects together with a decrease in delta wave amplitude. Interestingly, the decrease in SWS stability coincided with an increase in short-term delta, theta, sigma, and alpha power stability revealed by lower CVE. Loss of electroencephalograms (EEG) variability might be a useful marker of brain age.
传统上，老年人睡眠结构与年龄相关的恶化情况是通过对多导睡眠图（PSG）记录进行视觉评分来评估总睡眠时间和潜伏期。在本研究中，我们还比较了年轻和老年受试者之间的非快速眼动睡眠（NREM）阶段以及δ波、θ波、α波和σ波的稳定性，以提取可能解释与年龄相关的睡眠变化的特征。
对11名健康老年女性（72.6±2.4岁）和9名健康年轻女性（23.3±1.1岁）进行了多导睡眠图记录。除了总睡眠时间外，分别通过睡眠阶段转换分析和一种基于包络变异系数（CVE）分析的新型计算方法，对睡眠阶段、δ波功率幅度以及δ波、θ波、α波和σ波的稳定性进行了评估。
在老年受试者中，总睡眠时间和慢波睡眠（SWS）时间较短，而睡眠开始后的觉醒时间较长。各年龄组之间SWS发作次数相似，然而，睡眠阶段转换分析显示，老年个体的SWS稳定性较差。按δ波功率降序排列的NREM睡眠阶段为：SWS、N2和N1，老年受试者NREM睡眠期间的δ波功率低于年轻受试者。δ频段的CVE是δ波稳定性的一个指标，且在不同年龄组之间存在显著差异。当对每个NREM阶段进行单独分析时，年轻和老年受试者之间在NREM中明显观察到不同的CVE聚类。与年轻受试者相比，老年受试者在N2和SWS阶段的δ波CVE和幅度也较低。此外，老年参与者在θ波、α波和σ波频段的CVE值较低也是其特征。
本研究表明，老年受试者的SWS稳定性降低，同时δ波幅度减小。有趣的是，SWS稳定性的降低与较低的CVE所显示的短期δ波、θ波、σ波和α波功率稳定性增加相一致。脑电图（EEG）变异性的丧失可能是脑年龄的一个有用标志。
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