一种分离昼夜节律与非昼夜节律掩蔽效应的新方法,以加强从核心体温估计每日昼夜节律的时间和振幅

Phuc D Nguyen, Claire Dunbar, Hannah Scott, Bastien Lechat, Jack Manners, Gorica Micic, Nicole Lovato, Amy C Reynolds, Leon Lack, Robert Adams, Danny Eckert, Andrew Vakulin, Peter G Catcheside
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引用次数: 0

摘要

昼夜节律紊乱会对睡眠、工作表现和健康产生不利影响。追踪昼夜节律的每日连续变化的一种公认方法是测量核心体温(CBT),并确定每日与昼夜节律相关的 CBT 最低时间(Tmin)。这种方法通常采用余弦模型拟合测量的 CBT 数据,但余弦模型可能无法充分考虑到大量的清醒代谢活动和睡眠对 CBT 的影响,这些活动和影响会混淆和掩盖昼夜节律效应,从而影响与昼夜节律相关的 Tmin 的估计值。这项研究引入了一种新颖的生理学分析方法,用于区分昼夜节律效应和非昼夜节律效应对 CBT 的影响,我们将其与传统的余弦分析方法进行了比较。数据集由 33 名健康参与者组成,他们参加了 39 小时的实验室研究,其中包括最初的一夜睡眠和随后的长时间清醒。CBT数据是通过可食用胶囊以30秒为间隔收集的。我们的设计同时捕捉了基准睡眠期和延长唤醒期(无睡眠)的 CBT,并允许我们使用生理学指导的广义加法模型来模拟睡眠、唤醒和活动的昼夜节律和非昼夜节律效应对 CBT 的影响。我们将模型拟合结果和通过延长唤醒而不睡眠推断出的估计 Tmin 与传统的余弦模型拟合结果进行了比较。与传统余弦模型相比,新模型的 CBT 拟合效果更好(PearsonR 0.90 [95%CI; [0.83 - 0.96] 对 0.81 [0.55-0.93])。我们的方法(0.2 [-0.5,0.3] 小时)比以前的方法(1.4[1.1-1.7] 小时)更好地拟合了从不眠日得出的估计昼夜节律 Tmin 与测量昼夜节律 Tmin 之间的差异。与传统余弦法相比,这种新方法能更好地消除非昼夜节律的影响,包括消除与睡眠有关的偏差,更早地估计昼夜节律Tmin。
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A novel method to separate circadian from non-circadian masking effects in order to enhance daily circadian timing and amplitude estimation from core body temperature
Circadian disruption contributes to adverse effects on sleep, performance, and health. One accepted method to track continuous daily changes in circadian timing is to measure core body temperature (CBT), and establish daily, circadian-related CBT minimum time (Tmin). This method typically applies cosine-model fits to measured CBT data, which may not adequately account for substantial wake metabolic activity and sleep effects on CBT that confound and mask circadian effects, and thus estimates of the circadian-related Tmin. This study introduced a novel physiology-grounded analytic approach to separate circadian from non-circadian effects on CBT, which we compared against traditional cosine-based methods. The dataset comprised 33 healthy participants attending a 39-hour in-laboratory study with an initial overnight sleep followed by an extended wake period. CBT data were collected at 30-second intervals via ingestible capsules. Our design captured CBT during both the baseline sleep period and during extended wake period (without sleep) and allowed us to model the influence of circadian and non-circadian effects of sleep, wake, and activity on CBT using physiology-guided generalized additive models. Model fits and estimated Tmin inferred from extended wake without sleep were compared with traditional cosine-based models fits. Compared to the traditional cosine model, the new model exhibited superior fits to CBT (Pearson R 0.90 [95%CI; [0.83 - 0.96] versus 0.81 [0.55-0.93]). The difference between estimated vs measured circadian Tmin, derived from the day without sleep, was better fit with our method (0.2 [-0.5,0.3] hours) versus previous methods (1.4 [1.1 to 1.7] hours). This new method provides superior demasking of non-circadian influences compared to traditional cosine methods, including the removal of a sleep-related bias towards an earlier estimate of circadian Tmin.
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