The effects of self-selected light-dark cycles and social constraints on human sleep and circadian timing: a modeling approach.
ABSTRACT: Why do we go to sleep late and struggle to wake up on time? Historically, light-dark cycles were dictated by the solar day, but now humans can extend light exposure by switching on artificial lights. We use a mathematical model incorporating effects of light, circadian rhythmicity and sleep homeostasis to provide a quantitative theoretical framework to understand effects of modern patterns of light consumption on the human circadian system. The model shows that without artificial light humans wakeup at dawn. Artificial light delays circadian rhythmicity and preferred sleep timing and compromises synchronisation to the solar day when wake-times are not enforced. When wake-times are enforced by social constraints, such as work or school, artificial light induces a mismatch between sleep timing and circadian rhythmicity ('social jet-lag'). The model implies that developmental changes in sleep homeostasis and circadian amplitude make adolescents particularly sensitive to effects of light consumption. The model predicts that ameliorating social jet-lag is more effectively achieved by reducing evening light consumption than by delaying social constraints, particularly in individuals with slow circadian clocks or when imposed wake-times occur after sunrise. These theory-informed predictions may aid design of interventions to prevent and treat circadian rhythm-sleep disorders and social jet-lag.
Project description:Circadian rhythms maintain a 24 h oscillation pattern in metabolic, physiological and behavioral processes in all living organisms. Circadian rhythms are organized as biochemical networks located in hypothalamus and peripheral tissues. Rhythmicity in the expression of circadian clock genes plays a vital role in regulating the process of cell division and DNA damage control. The oncogenic protein, MYC and the tumor suppressor, p53 are directly influenced by the circadian clock. Jet lag and altered sleep/wake schedules prominently affect the expression of molecular clock genes. This study is focused on developing a Petri net model to analyze the impacts of long term jet lag on the circadian clock and its probable role in tumor progression. The results depict that jet lag disrupts the normal rhythmic behavior and expression of the circadian clock proteins. This disruption leads to persistent expression of MYC and suppressed expression of p53. Thus, it is inferred that jet lag altered circadian clock negatively affects the expressions of cell cycle regulatory genes and contribute in uncontrolled proliferation of tumor cells.
Project description:Circadian organization of the mammalian transcriptome is achieved by rhythmic recruitment of key modifiers of chromatin structure and transcriptional and translational processes. These rhythmic processes, together with posttranslational modification, constitute circadian oscillators in the brain and peripheral tissues, which drive rhythms in physiology and behavior, including the sleep-wake cycle. In humans, sleep is normally timed to occur during the biological night, when body temperature is low and melatonin is synthesized. Desynchrony of sleep-wake timing and other circadian rhythms, such as occurs in shift work and jet lag, is associated with disruption of rhythmicity in physiology and endocrinology. However, to what extent mistimed sleep affects the molecular regulators of circadian rhythmicity remains to be established. Here, we show that mistimed sleep leads to a reduction of rhythmic transcripts in the human blood transcriptome from 6.4% at baseline to 1.0% during forced desynchrony of sleep and centrally driven circadian rhythms. Transcripts affected are key regulators of gene expression, including those associated with chromatin modification (methylases and acetylases), transcription (RNA polymerase II), translation (ribosomal proteins, initiation, and elongation factors), temperature-regulated transcription (cold inducible RNA-binding proteins), and core clock genes including CLOCK and ARNTL (BMAL1). We also estimated the separate contribution of sleep and circadian rhythmicity and found that the sleep-wake cycle coordinates the timing of transcription and translation in particular. The data show that mistimed sleep affects molecular processes at the core of circadian rhythm generation and imply that appropriate timing of sleep contributes significantly to the overall temporal organization of the human transcriptome.
Project description:BACKGROUND:The phase and amplitude of rhythms in physiology and behavior are generated by circadian oscillators and entrained to the 24-h day by exposure to the light-dark cycle and feedback from the sleep-wake cycle. The extent to which the phase and amplitude of multiple rhythms are similarly affected during altered timing of light exposure and the sleep-wake cycle has not been fully characterized. METHODOLOGY/PRINCIPAL FINDINGS:We assessed the phase and amplitude of the rhythms of melatonin, core body temperature, cortisol, alertness, performance and sleep after a perturbation of entrainment by a gradual advance of the sleep-wake schedule (10 h in 5 days) and associated light-dark cycle in 14 healthy men. The light-dark cycle consisted either of moderate intensity 'room' light (?90-150 lux) or moderate light supplemented with bright light (?10,000 lux) for 5 to 8 hours following sleep. After the advance of the sleep-wake schedule in moderate light, no significant advance of the melatonin rhythm was observed whereas, after bright light supplementation the phase advance was 8.1 h (SEM 0.7 h). Individual differences in phase shifts correlated across variables. The amplitude of the melatonin rhythm assessed under constant conditions was reduced after moderate light by 54% (17-94%) and after bright light by 52% (range 12-84%), as compared to the amplitude at baseline in the presence of a sleep-wake cycle. Individual differences in amplitude reduction of the melatonin rhythm correlated with the amplitude of body temperature, cortisol and alertness. CONCLUSIONS/SIGNIFICANCE:Alterations in the timing of the sleep-wake cycle and associated bright or moderate light exposure can lead to changes in phase and reduction of circadian amplitude which are consistent across multiple variables but differ between individuals. These data have implications for our understanding of circadian organization and the negative health outcomes associated with shift-work, jet-lag and exposure to artificial light.
Project description:The term "social jet lag" was introduced for defining the conflict between social and biological clocks due to the general practice of shifting weekday risetime on early morning hours. The phase delay of the sleep-wake cycle during adolescence is one of the most remarkable features of the ontogenesis of sleep that is incompatible with early school start times. It was previously proposed that the process of accumulation of sleep pressure during wakefulness is slowing down in post-pubertal teens to allow them to stay awake for a longer period of time thus causing the delay of their bedtime. In order to examine this proposition, we traced the ontogeny of social jet lag using sleep times reported for 160 samples of study participants of different ages as an input to a model of sleep-wake regulatory process. The simulations suggested that a gradual change in just one of the model's parameters, the time constant of wakefulness phase of the sleep-wake regulatory process, might explain the association of the transition between childhood and adulthood with the prolongation of time staying awake, delay of sleep time, and reduction of sleep duration. We concluded that the implication of the sleep-wake regulating model would be of help for understanding precisely how social jet lag varies with age and what are the chronophysiological causes of this variation.
Project description:Sleep is undoubtedly important for human health as insufficient sleep has been associated with a plethora of diseases. Adequate sleep assessment is critical in clinical and research settings, however current sleep assessment protocols fail to account for circadian rhythms, despite the fact that sleep is a well-recognized circadian process. Purpose: The purpose of this study was to determine if circadian parameters, such as chronotype, influence sleep quality in a sleep laboratory setting. Methods: In order to investigate this, twenty participants (10 men and 10 women) aged 18–31 years old had their sleep recorded by electroencephalography in a sleep lab. Participants also complete surveys which provided data on chronotype, social jet lag and subjective sleep quality. Participants were allowed to self-select sleep time for the study, and sleep discrepancy, defined as the difference between reported and experienced mid-sleep, was determined. Results: Interestingly, results indicated a significant correlation between self-reported sleep quality and social jet lag, with those who typically experience more social jet lag being more satisfied with their sleep during the study (r = 0.549, p = 0.012). In addition, when participants were separated into groups based on chronotype, sleep discrepancy and social jet lag, sizeable differences were noted for parameters such as sleep onset latency, number of awakenings, and percent of time spent in REM sleep. Conclusion: These results suggest circadian parameters serve as predictors of both subjective and objective sleep quality, and thus illuminates a necessity for these parameters to be taken into account in the assessment and research of sleep.
Project description:Travel across multiple time zones results in desynchronization of environmental time cues and the sleep-wake schedule from their normal phase relationships with the endogenous circadian system. Circadian misalignment can result in poor neurobehavioral performance, decreased sleep efficiency, and inappropriately timed physiological signals including gastrointestinal activity and hormone release. Frequent and repeated transmeridian travel is associated with long-term cognitive deficits, and rodents experimentally exposed to repeated schedule shifts have increased death rates. One approach to reduce the short-term circadian, sleep-wake, and performance problems is to use mathematical models of the circadian pacemaker to design countermeasures that rapidly shift the circadian pacemaker to align with the new schedule. In this paper, the use of mathematical models to design sleep-wake and countermeasure schedules for improved performance is demonstrated. We present an approach to designing interventions that combines an algorithm for optimal placement of countermeasures with a novel mode of schedule representation. With these methods, rapid circadian resynchrony and the resulting improvement in neurobehavioral performance can be quickly achieved even after moderate to large shifts in the sleep-wake schedule. The key schedule design inputs are endogenous circadian period length, desired sleep-wake schedule, length of intervention, background light level, and countermeasure strength. The new schedule representation facilitates schedule design, simulation studies, and experiment design and significantly decreases the amount of time to design an appropriate intervention. The method presented in this paper has direct implications for designing jet lag, shift-work, and non-24-hour schedules, including scheduling for extreme environments, such as in space, undersea, or in polar regions.
Project description:Daily rhythms in human physiology and behavior are driven by the interplay of circadian rhythms, environmental cycles, and social schedules. Much research has focused on the mechanism and function of circadian rhythms in constant conditions or in idealized light-dark environments. There have been comparatively few studies into how social pressures, such as work and school schedules, affect human activity rhythms day to day and season to season. To address this issue, we analyzed activity on Twitter in >1,500 US counties throughout the 2012-2013 calendar years in 15-min intervals using geographically tagged tweets representing ?0.1% of the total population each day. We find that sustained periods of low Twitter activity are correlated with sufficient sleep as measured by conventional surveys. We show that this nighttime lull in Twitter activity is shifted to later times on weekends relative to weekdays, a phenomenon we term "Twitter social jet lag." The magnitude of this social jet lag varies seasonally and geographically-with the West Coast experiencing less Twitter social jet lag compared to the Central and Eastern US-and is correlated with average commuting schedules and disease risk factors such as obesity. Most counties experience the largest amount of Twitter social jet lag in February and the lowest in June or July. We present evidence that these shifts in weekday activity coincide with relaxed social pressures due to local K-12 school holidays and that the direct seasonal effect of altered day length is comparatively weaker.
Project description:Disturbances of sleep and the underlying circadian rhythm are related to many human diseases, such as obesity, diabetes, cardiovascular disorders, and cognitive impairments. Dysbiosis of the gut microbiome has also been reported to be associated with the pathologies of these diseases. Therefore, we proposed that disturbed sleep may regulate gut microbiota homeostasis. In this study, we mimicked the sleep-wake cycle shift, one typical type of circadian rhythm disturbances in young people, in recruited subjects. We used 16S rRNA gene amplicon sequencing to define microbial taxa from their fecal samples. Although the relative abundances of the microbes were not significantly altered, the functional-profile analysis of gut microbiota revealed functions enriched during the sleep-wake cycle shift. In addition, the microbial networks were quite distinct among baseline, shift, and recovery stages. These results suggest that an acute sleep-wake cycle shift may exert a limited influence on the gut microbiome, mainly including the functional profiles of the microbes and the microbial relationships within the microbial community.IMPORTANCE Circadian rhythm misalignment due to social jet lag, shift work, early morning starts, and delayed bedtimes is becoming common in our modern society. Disturbances of sleep and the underlying circadian rhythms are related to multiple human diseases, such as obesity, diabetes, cardiovascular disorders, and cognitive impairments. Given the crucial role of microbiota in the same pathologies as are caused by sleep disturbance, how the gut microbiota is affected by sleep is of increasing interest. The results of this study indicate that the acute circadian rhythm disturbance caused by sleep-wake shifts affect the human gut microbiota, especially the functional profiles of gut microbes and interactions among them. Further experiments with a longer-time-scale intervention and larger sample size are needed to assess the effects of chronic circadian rhythm disruption on the gut microbiome and to guide possible microbial therapies for clinical intervention in the related diseases.
Project description:Circadian rhythms are internal manifestations of the solar day that permit adaptations to predictable environmental temporal changes. These ~24-h rhythms are controlled by molecular clockworks within the brain that are reset daily to precisely 24?h by exposure to the light-dark cycle. Information from the master clock in the mammalian hypothalamus conveys temporal information to the entire body via humoral and neural communication. A bidirectional relationship exists between mood disorders and circadian rhythms. Mood disorders are often associated with disrupted circadian clock-controlled responses, such as sleep and cortisol secretion, whereas disruption of circadian rhythms via jet lag, night-shift work, or exposure to artificial light at night, can precipitate or exacerbate affective symptoms in susceptible individuals. Evidence suggests strong associations between circadian rhythms and mental health, but only recently have studies begun to discover the direct interactions between the circadian system and mood regulation. This review provides an overview of disrupted circadian rhythms and the relationship to behavioral health and psychiatry. The focus of this review is delineating the role of disruption of circadian rhythms on mood disorders using human night shift studies, as well as jet lag studies to identify links. We also review animal models of disrupted circadian rhythms on affective responses. Lastly, we propose low-cost behavioral and lifestyle changes to improve circadian rhythms and presumably behavioral health.
Project description:Timing of the human sleep-wake cycle is determined by social constraints, biological processes (sleep homeostasis and circadian rhythmicity) and environmental factors, particularly natural and electrical light exposure. To what extent seasonal changes in the light-dark cycle affect sleep timing and how this varies between weekdays and weekends has not been firmly established. We examined sleep and activity patterns during weekdays and weekends in late autumn (standard time, ST) and late spring (daylight saving time, DST), and expressed their timing in relation to three environmental reference points: clock-time, solar noon (SN) which occurs one clock hour later during DST than ST, and the midpoint of accumulated light exposure (50% LE). Observed sleep timing data were compared to simulated data from a mathematical model for the effects of light on the circadian and homeostatic regulation of sleep. A total of 715 days of sleep timing and light exposure were recorded in 19 undergraduates in a repeated-measures observational study. During each three-week assessment, light and activity were monitored, and self-reported bed and wake times were collected. Light exposure was higher in spring than in autumn. 50% LE did not vary across season, but occurred later on weekends compared to weekdays. Relative to clock-time, bedtime, wake-time, mid-sleep, and midpoint of activity were later on weekends but did not differ across seasons. Relative to SN, sleep and activity measures were earlier in spring than in autumn. Relative to 50% LE, only wake-time and mid-sleep were later on weekends, with no seasonal differences. Individual differences in mid-sleep did not correlate with SN but correlated with 50% LE. Individuals with different habitual bedtimes responded similarly to seasonal changes. Model simulations showed that light exposure patterns are sufficient to explain sleep timing in spring but less so in autumn. The findings indicate that during autumn and spring, the timing of sleep associates with actual light exposure rather than sun time as indexed by SN.