Neurobiology of Sleep and Circadian Rhythms最新文献

Sleep is regulated by a homeostatic and a circadian process. Together these two processes determine most aspects of sleep and related variables like sleepiness and alertness. The two processes are known to be able to work independently, but also to both influence sleep and sleep related variables in an additive or more complex manner. The question remains whether the two processes are directly influencing each other.

The present review summarizes evidence from behavioural and electroencephalographic determined sleep, electrophysiology, gene knock out mouse models, and mathematical modelling to explore whether sleep homeostasis can influence circadian clock functioning and vice versa.

There is a multitude of data available showing parallel action or influence of sleep homeostatic mechanisms and the circadian clock on several objective and subjective variables related to sleep and alertness. However, the evidence of a direct influence of the circadian clock on sleep homeostatic mechanisms is sparse and more research is needed, particularly applying longer sleep deprivations that include a second night.

The strongest evidence of an influence of sleep homeostatic mechanisms on clock functioning comes from sleep deprivation experiments, demonstrating an attenuation of phase shifts of the circadian rhythm to light pulses when sleep homeostatic pressure is increased. The data suggest that the circadian clock is less susceptible to light when sleep pressure is high.

The available data indicate that a strong central clock will induce periods of deep sleep, which in turn will strengthen clock function. Both are therefore important for health and wellbeing. Weakening of one will also hamper functioning of the other. Shift work and jet lag are situations where one tries to adapt to zeitgebers in a condition where sleep is compromised. Adaptation to zeitgebers may be improved by introducing nap schedules to reduce sleep pressure, and through that increasing clock susceptibility to light.

The central aim of this study was to investigate hormones as a predictor of individual vulnerability or resiliency on emotion processing tasks following one night of sleep restriction. The restriction group was instructed to sleep 3 a.m.–7 a.m. (13 men, 13 women in follicular phase, 10 women in luteal phase of menstrual cycle), and a control group slept 11 p.m.–7 a.m. (12 men, 12 follicular women, 12 luteal women). Sleep from home was verified with actigraphy. Saliva samples were collected on the evening prior to restriction, and in the morning and afternoon following restriction, to measure testosterone, estradiol, and progesterone. In the laboratory, event-related potentials (ERPs) were recorded during presentation of images and faces to index neural processing of emotional stimuli. Compared to controls, sleep-restricted participants had a larger amplitude Late Positive Potential (LPP) ERP to positive vs neutral images, reflecting greater motivated attention towards positive stimuli. Sleep-restricted participants were also less accurate categorizing sad faces and exhibited a larger N170 to sad faces, reflecting greater neural reactivity. Sleep-restricted luteal women were less accurate categorizing all images compared to control luteal women, and progesterone was related to several outcomes. Morning testosterone in men was lower in the sleep-restricted group compared to controls; lower testosterone was associated with lower accuracy to positive images, a greater difference between positive vs neutral LPP amplitude, and lower accuracy to sad and fearful faces. In summary, women higher in progesterone and men lower in testosterone were more vulnerable to the effects of sleep restriction on emotion processing tasks. This study highlights a role for sex and sex hormones in understanding individual differences in vulnerability to sleep loss.

Heart rate variability (HRV) is a reliable technique to evaluate autonomic activity and shows marked changes across a night of sleep. Previous nighttime sleep findings report changes in HRV during non-rapid eye movement sleep (NREM), which have been associated with cardiovascular health benefits. Daytime sleep, however, has been linked with both positive and negative cardiovascular outcomes. Yet, no studies have directly compared HRV profiles during an ecologically-valid daytime nap in healthy, well-rested adults to that of nighttime sleep. Using a within-subjects design, 32 people took a daytime nap and slept overnight in the lab at least one week apart; both sleep sessions had polysomnography, including electrocardiography (ECG), recorded. We measured inter-beat intervals (RR), total power (TP), low frequency power (LF; .04–.15 Hz), and high frequency power (HF; .15–.40 Hz) components of HRV during NREM and rapid eye movement (REM) sleep. Compared to the nap, we found longer RR intervals and decreased heart rate during the night for both Stage 2 and SWS and increased TP, LF and HF power during nighttime Stage 2 sleep only; however, no differences in the LFHF ratio or normalized HF power were found between the nap and the night. Also, no differences in REM sleep between the nap and night were detected. Similar relationships emerged when comparing the nap to one cycle of nighttime sleep. These findings suggest that longer daytime naps, with both SWS and REM, may provide similar cardiovascular benefits as nocturnal sleep. In light of the on-going debate surrounding the health benefits and/or risks associated with napping, these results suggest that longer daytime naps in young, healthy adults may support cardiac down-regulation similar to nighttime sleep. In addition, napping paradigms may serve as tools to explore sleep-related changes in autonomic activity in both healthy and at-risk populations.

The mammalian circadian and sleep-wake systems are closely aligned through their coordinated regulation of daily activity patterns. Although they differ in their anatomical organization and physiological processes, they utilize overlapping regulatory mechanisms that include an assortment of proteins and molecules interacting within the extracellular space. These extracellular factors include proteases that interact with soluble proteins, membrane-attached receptors and the extracellular matrix; and cell adhesion molecules that can form complex scaffolds connecting adjacent neurons, astrocytes and their respective intracellular cytoskeletal elements. Astrocytes also participate in the dynamic regulation of both systems through modulating neuronal appositions, the extracellular space and/or through release of gliotransmitters that can further contribute to the extracellular signaling processes. Together, these extracellular elements create a system that integrates rapid neurotransmitter signaling across longer time scales and thereby adjust neuronal signaling to reflect the daily fluctuations fundamental to both systems. Here we review what is known about these extracellular processes, focusing specifically on areas of overlap between the two systems. We also highlight questions that still need to be addressed. Although we know many of the extracellular players, far more research is needed to understand the mechanisms through which they modulate the circadian and sleep-wake systems.

Millions of people worldwide are required to work when their physiology is tuned for sleep. By forcing wakefulness out of the body’s normal schedule, shift workers face numerous adverse health consequences, including gastrointestinal problems, sleep problems, and higher rates of some diseases, including cancers. Recent studies have developed protocols to simulate shift work in rodents with the intention of assessing the effects of night-shift work on subsequent sleep (Grønli et al., 2017). These studies have already provided important contributions to the understanding of the metabolic consequences of shift work (Arble et al., 2015; Marti et al., 2016; Opperhuizen et al., 2015) and sleep-wake-specific impacts of night-shift work (Grønli et al., 2017). However, our understanding of the causal mechanisms underlying night-shift-related sleep disturbances is limited. In order to advance toward a mechanistic understanding of sleep disruption in shift work, we model these data with two different approaches. First we apply a simple homeostatic model to quantify differences in the rates at which sleep need, as measured by slow wave activity during slow wave sleep (SWS) rises and falls. Second, we develop a simple and novel mathematical model of rodent sleep and use it to investigate the timing of sleep in a simulated shift work protocol (Grønli et al., 2017). This mathematical framework includes the circadian and homeostatic processes of the two-process model, but additionally incorporates a stochastic process to model the polyphasic nature of rodent sleep. By changing only the time at which the rodents are forced to be awake, the model reproduces some key experimental results from the previous study, including correct proportions of time spent in each stage of sleep as a function of circadian time and the differences in total wake time and SWS bout durations in the rodents representing night-shift workers and those representing day-shift workers. Importantly, the model allows for deeper insight into circadian and homeostatic influences on sleep timing, as it demonstrates that the differences in SWS bout duration between rodents in the two shifts is largely a circadian effect. Our study shows the importance of mathematical modeling in uncovering mechanisms behind shift work sleep disturbances and it begins to lay a foundation for future mathematical modeling of sleep in rodents.

Many women experience sleep problems during pregnancy. This includes difficulty initiating and maintaining sleep due to physiologic changes that occur as pregnancy progresses, as well as increased symptoms of sleep-disordered breathing (SDB). Growing evidence indicates that sleep deficiency alters glucose metabolism and increases risk of diabetes. Poor sleep may exacerbate the progressive increase in insulin resistance that normally occurs during pregnancy, thus contributing to the development of maternal hyperglycemia. Here, we critically review evidence that exposure to short sleep duration or SDB during pregnancy is associated with gestational diabetes mellitus (GDM). Several studies have found that the frequency of GDM is higher in women exposed to short sleep compared with longer sleep durations. Despite mixed evidence regarding whether symptoms of SDB (e.g., frequent snoring) are associated with GDM after adjusting for BMI or obesity, it has been shown that clinically-diagnosed SDB is prospectively associated with GDM. There are multiple mechanisms that may link sleep deprivation and SDB with insulin resistance, including increased levels of oxidative stress, inflammation, sympathetic activity, and cortisol. Despite emerging evidence that sleep deficiency and SDB are associated with increased risk of GDM, it has yet to be demonstrated that improving sleep in pregnant women (e.g., by extending sleep duration or treating SDB) protects against the development of hyperglycemia. If a causal relationship can be established, behavioral therapies for improving sleep can potentially be used to reduce the risk and burden of GDM.

The effects of feeding behavior and diet composition, as well as their possible interactions, on daily (clock) gene expression rhythms have mainly been studied in the liver, and to a lesser degree in white adipose tissue (WAT), but hardly in other metabolic tissues such as skeletal muscle (SM) and brown adipose tissues (BAT). We therefore subjected male Wistar rats to a regular chow or free choice high-fat-high sugar (fcHFHS) diet in combination with time restricted feeding (TRF) to either the light or dark phase. In SM, all tested clock genes lost their rhythmic expression in the chow light fed group. In the fcHFHS light fed group rhythmic expression for some, but not all, clock genes was maintained, but shifted by several hours. In BAT the daily rhythmicity of clock genes was maintained for the light fed groups, but expression patterns were shifted as compared with ad libitum and dark fed groups, whilst the fcHFHS diet made the rhythmicity of clock genes become more pronounced. Most of the metabolic genes in BAT tissue tested did not show any rhythmic expression in either the chow or fcHFHS groups. In SM Pdk4 and Ucp3 were phase-shifted, but remained rhythmically expressed in the chow light fed groups. Rhythmic expression was lost for Ucp3 whilst on the fcHFHS diet during the light phase. In summary, both feeding at the wrong time of day and diet composition disturb the peripheral clocks in SM and BAT, but to different degrees and thereby result in a further desynchronization between metabolically active tissues such as SM, BAT, WAT and liver.

Chronic insufficient sleep is a major societal problem and is associated with increased risk of metabolic disease. Hypothalamic inflammation contributes to hyperphagia and weight gain in diet-induced obesity, but insufficient sleep-induced neuroinflammation has yet to be examined in relation to metabolic function. We therefore fragmented sleep of adult male C57BL/6 J mice for 18 h daily for 9 days to determine whether sleep disruption elicits inflammatory responses in brain regions that regulate energy balance and whether this relates to glycemic control. To additionally test the hypothesis that exposure to multiple inflammatory factors exacerbates metabolic outcomes, responses were compared in mice exposed to sleep fragmentation (SF), high-fat diet (HFD), both SF and HFD, or control conditions. Three or 9 days of high-fat feeding reduced glucose tolerance but SF alone did not. Transient loss of body mass in SF mice may have affected outcomes. Comparisons of pro-inflammatory cytokine concentrations among central and peripheral metabolic tissues indicate that patterns of liver interleukin-1β concentrations best reflects observed changes in glucose tolerance. However, we demonstrate that SF rapidly and potently increases Iba1 immunoreactivity (-ir), a marker of microglia. After 9 days of manipulations, Iba1-ir remains elevated only in mice exposed to both SF and HFD, indicating a novel interaction between sleep and diet on microglial activation that warrants further investigation.

Objectives

To investigate the acute benefits of breaking up prolonged sitting with light-intensity physical activity on (i) glucose metabolism under conditions of sleep restriction, and (ii) cognitive deficits associated with sleep restriction.

Methods

This counterbalanced, crossover trial consisted of two five-day (5 night) experimental conditions separated by a two-week washout period. On the first night, participants were given a 9-h sleep opportunity to allow the collection of steady-state baseline measures the following day. This was followed by three consecutive nights of sleep restriction (5-h sleep opportunity). In the sitting condition (SIT), participants remained seated between 1000 and 1800 h. In the physical activity condition (ACT), participants completed 3-min bouts of light-intensity walking every 30 min on a motorised treadmill between 1000 and 1800 h. At all other times, in both conditions, participants remained seated, except when walking to the dining room or to use the bathroom (max distance = 32 m). Six physically inactive, healthy males were randomised to one of two trial orders, 1) SIT then ACT, or 2) ACT then SIT. Continuous measures of interstitial glucose were measured at 5-min intervals. A cognitive and subjective test battery was administered every two hours during wake periods. Analyses were conducted using a series of linear mixed-effect ANOVAs.

Results

No differences in interstitial glucose concentration or cognitive performance were observed between the SIT condition and the ACT condition. Participants reported higher levels of sleepiness, and felt less alert in the SIT condition compared with the ACT condition.

Conclusions

There were no observable benefits of breaking up prolonged sitting on glucose metabolism under conditions of sleep restriction. These findings have implications for behaviour change interventions. Future studies will need to include larger, less homogenous study populations and appropriate control conditions (i.e., 8–9 h sleep opportunities).

Daytime light exposure has been reported to impact or have no influence on energy metabolism in humans. Further, whether inter-individual differences in wake, sleep, 24 h energy expenditure, and RQ during circadian entrainment and circadian misalignment are stable across repeated 24 h assessments is largely unknown. We present data from two studies: Study 1 of 15 participants (7 females) exposed to three light exposure conditions: continuous typical room ~100 lx warm white light, continuous ~750 lx warm white light, and alternating hourly ~750 lx warm white and blue-enriched white light on three separate days in a randomized order; and Study 2 of 14 participants (8 females) during circadian misalignment induced by a simulated night shift protocol. Participants were healthy, free of medical disorders, medications, and illicit drugs. Participants maintained a consistent 8 h per night sleep schedule for one week as an outpatient prior to the study verified by wrist actigraphy, sleep diaries, and call-ins to a time stamped recorder. Participants consumed an outpatient energy balance research diet for three days prior to the study. The inpatient protocol for both studies consisted of an initial sleep disorder screening night. For study 1, this was followed by three standard days with 16 h scheduled wakefulness and 8 h scheduled nighttime sleep. For Study 2, it was followed by 16 h scheduled wake and 8 h scheduled sleep at habitual bedtime followed by three night shifts with 8 h scheduled daytime sleep. Energy expenditure was measured using whole-room indirect calorimetry. Constant posture bedrest conditions were maintained to control for energy expenditure associated with activity and the baseline energy balance diet was continued with the same exact meals across days to control for thermic effects of food. No significant impact of light exposure was observed on metabolic outcomes in response to daytime light exposure. Inter-individual variability in energy expenditure was systematic and ranged from substantial to almost perfect consistency during both nighttime sleep and circadian misalignment. Findings show robust and stable trait-like individual differences in whole body 24 h, waking, and sleep energy expenditure, 24 h respiratory quotient—an index of a fat and carbohydrate oxidation—during repeated assessments under entrained conditions, and also in 24 h and sleep energy expenditure during repeated days of circadian misalignment.