Depriving mice of sleep also deprives of food

Both sleep-wake behavior and circadian rhythms are tightly coupled to energy metabolism and food intake. Altered feeding times in mice are known to entrain clock-gene rhythms in brain and liver and sleep-deprived humans tend to eat more and gain weight. Previous observations in mice showing that sleep deprivation (SD) changes clock-gene expression might thus relate to altered food intake and not to the loss of sleep per se. Whether SD affects food intake in the mouse and how this might affect clock-gene expression is, however, unknown. We therefore quantified i) the cortical expression of the clock genes Per1, Per2, Dbp, and Cry1 in mice that had access to food or not during a 6h SD, and ii) food intake during baseline, SD, and recovery sleep. We found that food deprivation did not modify the SD-incurred clock-gene changes in the cortex. Moreover, we discovered that although food intake during SD did not differ from baseline, mice lost weight and increased food intake during subsequent recovery. We conclude that SD is associated with food deprivation and that the resulting energy deficit might contribute to the effects of SD that are commonly interpreted as a response to sleep loss.

Hugin+ neurons provide a link between sleep homeostat and circadian clock neurons

Sleep is controlled by homeostatic mechanisms, which drive sleep after wakefulness, and a circadian clock, which confers the 24-h rhythm of sleep. These processes interact with each other to control the timing of sleep in a daily cycle as well as following sleep deprivation. However, the mechanisms by which they interact are poorly understood. We show here that hugin+ neurons, previously identified as neurons that function downstream of the clock to regulate rhythms of locomotor activity, are also targets of the sleep homeostat. Sleep deprivation decreases activity of hugin+ neurons, likely to suppress circadian-driven activity during recovery sleep, and ablation of hugin+ neurons promotes sleep increases generated by activation of the homeostatic sleep locus, the dorsal fan-shaped body (dFB). Also, mutations in peptides produced by the hugin+ locus increase recovery sleep following deprivation. Transsynaptic mapping reveals that hugin+ neurons feed back onto central clock neurons, which also show decreased activity upon sleep loss, in a Hugin peptide–dependent fashion. We propose that hugin+ neurons integrate circadian and sleep signals to modulate circadian circuitry and regulate the timing of sleep.

P041 The Impact of Simulated Night Shifts on Executive Functioning

Nightwork is associated with fatigue, decreased sleep quality, and impairments in cognitive function. While attentional tasks have been widely investigated, there are limited data on more complex tasks, such as executive functioning during nightwork. Workers often need to rapidly shift between tasks, adapting to new and complex situations. The aim of this study was to investigate the impact of nightwork on executive functioning. Healthy, non-shift working individuals (N=8; 5F, 24.8±5.0y) participated in a 7-day live-in laboratory study. Participants underwent an 8h TIB baseline sleep, followed by 4 consecutive simulated nightshifts with 7h TIB sleep during the day and an 8h TIB recovery sleep. Participants were assessed for executive function at 2000h, 2200h, 0100h and 0400h. Executive functioning was assessed with a mental flexibility switching task where a 3D rotation and math task were displayed simultaneously with an arrow indicating which task to complete in a random order. Resulting throughput data were analysed using linear mixed models. There was a main effect of time of night (F(3,77)=4.81,p=.004) on throughput such that there was a speed accuracy trade off over the night shift with slower switching ability later in the shift. There was also a main effect of nightshift (F(2,77)=54.33,p<.001) where participants’ performance improved on the task with each nightshift. This study suggests executive functioning is impaired on nightshift with worse performance at 0400h. Task improvements over consecutive nightshifts may have been due to learning or acclimation to nightwork. Understanding complex task performance on nightshift is important for tailoring countermeasures.

P007 Eating in alignment with the circadian clock: A strategy to reduce the metabolic impact of nightwork

Nightwork disrupts circadian rhythms and impairs glucose metabolism, increasing the risk for type 2 diabetes. We investigated eliminating or reducing the amount of food consumed during simulated nightwork as a countermeasure to reduce the impact of circadian disruption on glucose metabolism. N=52 healthy, non-shiftworking participants (24.4±4.9 years; 26 Females; BMI 23.8±2.5kg/m2) underwent a 7-day laboratory protocol with an 8h TIB baseline sleep, followed by 4 simulated nightshifts with 7h TIB daytime sleep and an 8h TIB recovery sleep in groups of 4 participants. Each group was randomly assigned to a meal-at-midnight (n=17, 30% energy requirements), snack-at-midnight (n=16, 10% energy requirements) or no-eating-at-midnight (n=19) condition. Total 24h energy and macronutrient intake were constant across conditions. Standard oral glucose tolerance tests (OGTT) were conducted on day2 (baseline), and day7 (recovery). Plasma was sampled at -15, 0, 15, 30, 60, 90, 120, 150 mins, assayed for glucose and insulin. Area under the curve (AUC) was the calculated. Mixed model analyses of glucose AUC found a condition-by-day interaction (p<0.001). Glucose responses to OGTT did not change with nightwork in the no-eating-at-midnight condition (p=0.219) but worsened in the meal-at-midnight (p<0.001) and snack-at-midnight (p=0.022) conditions. Insulin AUC was different by condition (p=0.047). Insulin was highest after nightwork in the no-eating-at-midnight compared to meal-at-midnight (p=0.014) but not snack-at-midnight (p=0.345). Glucose tolerance was impaired by eating-at-midnight, associated with a lower than expected insulin response. Further work is required to determine the effect of meal or snack composition as a strategy to mitigate adverse metabolic effects of nightwork.

Evaluation of Sleep Architecture Using 24-hour Polysomnography in Patients Recovering from Critical Illness in an Intensive Care Unit and High Dependency Unit: A Longitudinal, Prospective, and Observational Study

Background and objective The sleep architecture of critically ill patients being treated in Intensive Care Units (ICU) and High Dependency Units (HDU) is frequently unsettled and inadequate both qualitatively and quantitatively. The study aimed to investigate and elucidate factors influencing sleep architecture and quality in ICU and HDU in a limited resource setting with financial constraints, lacking human resources and technology for routine monitoring of noise, light and sleep promotion strategies in ICU. Methods The study was longitudinal, prospective, hospital-based, analytic, and observational. Insomnia Severity Index (ISI) and the Epworth Sleepiness Scale (ESS) pre hospitalisation scores were recorded. Patients underwent 24-hour polysomnography (PSG) with the simultaneous monitoring of noise and light in their environments. Patients stabilised in ICU were transferred to HDU, where the 24-hour PSG with the simultaneous monitoring of noise and light in their environments was repeated. Following PSG, the Richards-Campbell Sleep Questionnaire (RCSQ) was employed to rate patients’ sleep in both the ICU and HDU. Results Of 46 screened patients, 26 patients were treated in the ICU and then transferred to the HDU. The mean (SD) of the study population’s mean (SD) age was 35.96 (11.6) years with a predominantly male population (53.2% (n=14)). The mean (SD) of the ISI and ESS scores were 6.88 (2.58) and 4.92 (1.99), respectively. The comparative analysis of PSG data recording from the ICU and HDU showed a statistically significant reduction in N1, N2 and an increase in N3 stages of sleep (p<0.05). Mean (SD) of RCSQ in the ICU and the HDU were 54.65 (7.70) and 60.19 (10.85) (p-value = 0.04) respectively. The disease severity (APACHE II) has a weak correlation with the arousal index but failed to reach statistical significance (coeff= 0.347, p= 0.083). Conclusion Sleep in ICU is disturbed and persisting during the recovery period in critically ill. However, during recovery, sleep architecture shows signs of restoration.

Interindividual differences in attentional vulnerability moderate cognitive performance during sleep restriction and subsequent recovery in healthy young men

We investigated whether interindividual attentional vulnerability moderates performance on domain-specific cognitive tasks during sleep restriction (SR) and subsequent recovery sleep. Fifteen healthy men (M ± SD, 22.3 ± 2.8 years) were exposed to three nights of baseline, five nights of 5-h time in bed SR, and two nights of recovery sleep. Participants completed tasks assessing working memory, visuospatial processing, and processing speed approximately every two hours during wake. Analyses examined performance across SR and recovery (linear predictor day or quadratic predictor day2) moderated by attentional vulnerability per participant (difference between mean psychomotor vigilance task lapses after the fifth SR night versus the last baseline night). For significant interactions between day/day2 and vulnerability, we investigated the effect of day/day2 at 1 SD below (less vulnerable level) and above (more vulnerable level) the mean of attentional vulnerability (N = 15 in all analyses). Working memory accuracy and speed on the Fractal 2-Back and visuospatial processing speed and efficiency on the Line Orientation Task improved across the entire study at the less vulnerable level (mean − 1SD) but not the more vulnerable level (mean + 1SD). Therefore, vulnerability to attentional lapses after SR is a marker of susceptibility to working memory and visuospatial processing impairment during SR and subsequent recovery.

Assessment of effects of total sleep deprivation and subsequent recovery sleep: a methodological strategy feasible without sleep laboratory

Background Sleep is critical for maintaining homeostasis in bodily and neurobehavioral functions. This homeostasis can be disturbed by sleep interruption and restored to normal by subsequent recovery sleep. Most research regarding recovery sleep (RS) effects has been conducted in specialized sleep laboratories, whereas small, less-well equipped research units may lack the possibilities to run studies in this area. Hence, the aims of the present study were to develop and validate an experimental protocol, which allows a thorough assessment of at-home recovery sleep after sleep deprivation. Methods The experimental protocol, comprising one night of baseline sleep (BL) at home, one night of monitored total sleep deprivation and a subsequent recovery night at home, was tested in a sample of 30 healthy participants. Subjects’ fatigue and alertness were assessed prior to and after each night. Sleep at home (BL, RS) was objectively assessed using portable polysomnography. To check whether our at-home sleep assessments yielded results that are comparable to those conducted in sleep laboratories, we compared the sleep data assessed in our study with sleep data assessed in laboratory studies. Results Sleep parameters assessed during RS exhibited changes as expected (prolonged total sleep time, better sleep efficiency, slow wave sleep rebound). Sleep parameters of BL and RS were in line with parameters assessed in previous studies examining sleep in a laboratory setting. Fatigue normalized after one night of RS; alertness partly recovered. Conclusions Our results suggest a successful implementation of our new experimental protocol, emphasizing it as a useful tool for future studies on RS outside of well-equipped sleep laboratories.

Estradiol influences adenosinergic signaling and nonrapid eye movement sleep need in adult female rats

Gonadal steroids and gender are risk factors for sleep disruptions and insomnia in women. However, the relationship between ovarian steroids and sleep is poorly understood. In rodent models, estradiol (E2) suppresses sleep in females suggesting that E2 may reduce homeostatic sleep need. The current study investigates whether E2 decreases sleep need and the potential mechanisms that govern E2 suppression of sleep. Our previous findings suggest that the median preoptic nucleus (MnPO) is a key nexus for E2 action on sleep. Using behavioral, neurochemical, and pharmacological approaches, we tested whether (1) E2 influenced the sleep homeostat and (2) E2 influenced adenosine signaling in the MnPO of adult female rats. In both unrestricted baseline sleep and recovery sleep from 6-h sleep deprivation, E2 significantly reduced nonrapid eye movement (NREM) sleep-delta power, NREM-slow wave activity (NREM-SWA, 0.5–4.0 Hz), and NREM-delta energy suggesting that E2 decreases homeostatic sleep need. However, coordinated with E2-induced changes in physiological markers of homeostatic sleep was a marked increase in MnPO extracellular adenosine (a molecular marker of homeostatic sleep need) during unrestricted and recovery sleep in E2-treated but not oil control animals. While these results seemed contradictory, systemically administered E2 blocked the ability of CGS-21680 (adenosine A2A receptor agonist) microinjected into the MnPO to increase NREM sleep suggesting that E2 may block adenosine signaling. Together, these findings provide evidence that E2 may attenuate the local effects of the A2A receptors in the MnPO, which in turn may underlie estrogenic suppression of sleep behavior as well as changes in homeostatic sleep need.

Genetic Markers of Differential Vulnerability to Sleep Loss in Adults

In this review, we discuss reports of genotype-dependent interindividual differences in phenotypic neurobehavioral responses to total sleep deprivation or sleep restriction. We highlight the importance of using the candidate gene approach to further elucidate differential resilience and vulnerability to sleep deprivation in humans, although we acknowledge that other omics techniques and genome-wide association studies can also offer insights into biomarkers of such vulnerability. Specifically, we discuss polymorphisms in adenosinergic genes (ADA and ADORA2A), core circadian clock genes (BHLHE41/DEC2 and PER3), genes related to cognitive development and functioning (BDNF and COMT), dopaminergic genes (DRD2 and DAT), and immune and clearance genes (AQP4, DQB1*0602, and TNFα) as potential genetic indicators of differential vulnerability to deficits induced by sleep loss. Additionally, we review the efficacy of several countermeasures for the neurobehavioral impairments induced by sleep loss, including banking sleep, recovery sleep, caffeine, and naps. The discovery of reliable, novel genetic markers of differential vulnerability to sleep loss has critical implications for future research involving predictors, countermeasures, and treatments in the field of sleep and circadian science.