Elizabeth B. Klerman

Comparisons of the variability of three markers of the human circadian pacemaker

A circadian pacemaker within the central nervous system regulates the approximately 24-h physiologic rhythms in sleep cycles, hormone secretion, and other physiologic functions. Because the pacemaker cannot be examined directly in humans, markers of pacemaker function must be used to study the pacemaker and its response to environmental stimuli. Core body temperature (CBT), plasma cortisol, and plasma melatonin are three marker variables frequently used to estimate the phase of the human pacemaker. Measurements of circadian phase using markers can contain variability due to the circadian pacemaker itself, the intrinsic variability of the marker relative to the pacemaker, the method of analysis of the marker, and the marker assay. For this report, we compared the mathematical variability of a number of methods of identifying circadian phase from CBT, plasma cortisol, and plasma melatonin data collected in a protocol in which pacemaker variability was minimized using low light levels and regular timing of both the light pattern and the rest/activity schedule. We hoped to assess the relative variabilities of the different physiological markers and the analysis methods. Methods were based on the crossing of an absolute threshold, on the crossing of a relative threshold, or on fitting a curve to all data points. All methods of calculating circadian phase from plasma melatonin data were less variable than those calculated using CBT or cortisol data. The standard deviation for the phase estimates using CBT data was 0.78 h, using cortisol data was 0.65 h, and for the eight analysis methods using melatonin data was 0.23 to 0.35 h. While the variability for these markers might be different for other subject populations and/or less stringent study conditions, assessment of the intrinsic variability of the different calculations of circadian phase can be applied to allow inference of the statistical significance of phase and phase shift calculations, as well as estimation of sample size or statistical power for the number of subjects within an experimental protocol.

Do plasma melatonin concentrations decline with age

PURPOSE Numerous reports that secretion of the putative sleep-promoting hormone melatonin declines with age have led to suggestions that melatonin replacement therapy be used to treat sleep problems in older patients. We sought to reassess whether the endogenous circadian rhythm of plasma melatonin concentration changes with age in healthy drug-free adults. METHODS We analyzed the amplitude of plasma melatonin profiles during a constant routine in 34 healthy drug-free older subjects (20 women and 14 men, aged 65 to 81 years) and compared them with 98 healthy drug-free young men (aged 18 to 30 years). RESULTS We could detect no significant difference between a healthy and drug-free group of older men and women as compared to one of young men in the endogenous circadian amplitude of the plasma melatonin rhythm, as described by mean 24-hour average melatonin concentration (70 pmol/liter vs 73 pmol/liter, P = 0.97), or the duration (9.3 hours vs 9.1 hours, P = 0.43), mean (162 pmol/liter vs 161 pmol/liter, P = 0.63), or integrated area (85,800 pmol x min/liter vs 86,700 pmol x min/liter, P = 0.66) of the nocturnal peak of plasma melatonin. CONCLUSION These results do not support the hypothesis that reduction of plasma melatonin concentration is a general characteristic of healthy aging. Should melatonin replacement therapy or melatonin supplementation prove to be clinically useful, we recommend that an assessment of endogenous melatonin be carried out before such treatment is used in older patients.

Melatonin agonist tasimelteon (VEC-162) for transient insomnia after sleep-time shift: two randomised controlled multicentre trials

BACKGROUND Circadian rhythm sleep disorders are common causes of insomnia for millions of individuals. We did a phase II study to establish efficacy and physiological mechanism, and a phase III study to confirm efficacy of the melatonin agonist tasimelteon (VEC-162) for treatment of transient insomnia associated with shifted sleep and wake time. METHODS We undertook phase II and phase III randomised, double-blind, placebo-controlled, parallel-group studies. In a phase II study, 39 healthy individuals from two US sites were randomly assigned to tasimelteon (10 [n=9], 20 [n=8], 50 [n=7], or 100 mg [n=7]) or placebo (n=8). We monitored individuals for 7 nights: 3 at baseline, 3 after a 5-h advance of sleep-wake schedule with treatment before sleep, and 1 after treatment; we measured plasma melatonin concentration for circadian phase assessment. In a phase III study, 411 healthy individuals from 19 US sites, who had transient insomnia induced in a sleep clinic by a 5-h advance of the sleep-wake schedule and a first-night effect in a sleep clinic, were given tasimelteon (20 [n=100], 50 [n=102], or 100 mg [n=106]) or placebo (n=103) 30 min before bedtime. Prespecified primary efficacy outcomes were polysomnographic sleep efficiency (phase II study), latency to persistent sleep (phase III study), and circadian phase shifting (phase II study). Analysis was by intention to treat. Safety was assessed in both studies. These trials are registered with ClinicalTrials.gov, numbers NCT00490945 and NCT00291187. FINDINGS In the phase II study, tasimelteon reduced sleep latency and increased sleep efficiency compared with placebo. The shift in plasma melatonin rhythm to an earlier hour was dose dependent. In the phase III study, tasimelteon improved sleep latency, sleep efficiency, and wake after sleep onset (ie, sleep maintenance). The frequency of adverse events was similar between tasimelteon and placebo. INTERPRETATION After an abrupt advance in sleep time, tasimelteon improved sleep initiation and maintenance concurrently with a shift in endogenous circadian rhythms. Tasimelteon may have therapeutic potential for transient insomnia in circadian rhythm sleep disorders.

Uncovering Residual Effects of Chronic Sleep Loss on Human Performance

The cumulative effects of chronic sleep loss may be overcome at certain times of day, but the residual effects of sleep deprivation profoundly degrade performance and may thereby compromise safety. More Than Beauty Sleep: Long Days Hamper Performance We all know the dangers of driving when tired; indeed, being awake for 24 hours straight can impair our abilities as much as a blood alcohol level of 0.10%. But all too often these real effects of too little sleep are dismissed with a laugh—or accepted. A careful dissection of the effects of short-term and long-term sleep restriction by Cohen et al. now shows that the situation is even worse than we thought. When chronic sleep loss is superimposed on the natural low-performance periods of our body’s 24-hour rhythm, reaction times slow to about 10 times normal, even if we got a good night’s sleep the night before—a truly hazardous situation. Because our circadian rhythms and sleep-wake cycles are usually intertwined, it has been difficult to dissect precisely their individual influences on how well we function. To independently determine the effects of circadian rhythm and those of acute and chronic sleep loss, the authors completely controlled the schedules of nine healthy volunteers for 38 days. For 21 of these days, the volunteers slept 10 hours out of every ~43-hour cycle, equivalent to about 5.6 hours of sleep per night. On this schedule, the subjects’ circadian rhythm, acute sleep deprivation (which they experienced during each of their long days), and chronic sleep restriction (which got worse and worse as the experiment went on) were all decoupled. By frequently giving the subjects a set of behavioral tests that measured reaction time, the authors were able to discern which factor had the most effect and when. Some of the results could be predicted from our own experience. For a few hours after waking from a 10-hour sleep, subjects’ performance was always normal, but it deteriorated as the ~33-hour waking day went on. But there was an additional effect of chronic sleep restriction. As the weeks of the experiment went by and the subjects’ sleep debt increased, their performance deteriorated to a greater extent each day, although it was still within normal limits just after they woke up. What was surprising was the very large effect of the circadian rhythm. When the subjects’ independently cycling internal clock was at its lowest point in the late night, it always extended reaction times, but its influence was considerably larger when the individual was experiencing acute or, especially, chronic sleep deprivation. Even more surprising was that when the internal clock was at its highest point in the late afternoon, reaction times were relatively normal despite substantial acute and chronic sleep loss. This leads to a dangerous situation in which individuals may not realize that they have a severe chronic sleep debt and a high vulnerability to sudden sleepiness a few hours later into the night. These findings translate into a warning for employers. Workers who need to remain awake for extended periods of time cannot maintain normal performance—and may not be aware of this vulnerability—if they are suffering from chronic sleep loss, especially if they are working at times during which their circadian rhythms are at a nadir. Sleep loss leads to profound performance decrements. Yet many individuals believe they adapt to chronic sleep loss or that recovery requires only a single extended sleep episode. To evaluate this, we designed a protocol whereby the durations of sleep and wake episodes were increased to 10 and 32.85 hours, respectively, to yield a reduced sleep-to-wake ratio of 1:3.3. These sleep and wake episodes were distributed across all circadian phases, enabling measurement of the effects of acute and chronic sleep loss at different times of the circadian day and night. Despite recurrent acute and substantial chronic sleep loss, 10-hour sleep opportunities consistently restored vigilance task performance during the first several hours of wakefulness. However, chronic sleep loss markedly increased the rate of deterioration in performance across wakefulness, particularly during the circadian “night.” Thus, extended wake during the circadian night reveals the cumulative detrimental effects of chronic sleep loss on performance, with potential adverse health and safety consequences.

Photic Resetting of the Human Circadian Pacemaker in the Absence of Conscious Vision

Ocular light exposure patterns are the primary stimuli for entraining the human circadian system to the local 24-h day. Many totally blind persons cannot use these stimuli and, therefore, have circadian rhythms that are not entrained. However, a few otherwise totally blind persons retain the ability to suppress plasma melatonin concentrations after ocular light exposure, probably using a neural pathway that includes the site of the human circadian pacemaker, suggesting that light information is reaching this site. To test definitively whether ocular light exposure could affect the circadian pacemaker of some blind persons and whether melatonin suppression in response to bright light correlates with light-induced phase shifts of the circadian system, the authors performed experiments with 5 totally blind volunteers using a protocol known to induce phase shifts of the circadian pacemaker in sighted individuals. In the 2 blind individuals who maintained light-induced melatonin suppression, the circadian system was shifted by appropriately timed bright-light stimuli. These data demonstrate that light can affect the circadian pacemaker of some totally blind individuals— either by altering the phase of the circadian pacemaker or by affecting its amplitude. They are consistent with data from animal studies demonstrating that there are different neural pathways and retinal cells that relay photic information to the brain: one for conscious light perception and the other for non-image-forming functions.

Clinical Aspects of Human Circadian Rhythms

Circadian rhythmicity can be important in the pathophysiology, diagnosis, and treatment of clinical disease. Due to the difficulties in conducting the necessary experimental work, it remains unknown whether ~24-h changes in pathophysiology or symptoms of many diseases are causally linked to endogenous circadian rhythms or to other diurnal factors that change across the day, such as changes in posture, activity, sleep or wake state, or metabolic changes associated with feeding or fasting. Until the physiology is accurately known, appropriate treatment cannot be designed. This review includes an overview of clinical disorders that are caused or affected by circadian or diurnal rhythms. The clinical side effects of disruption of circadian rhythmicity, such as in shiftwork, including the public health implications of the disrupted alertness and performance, are also discussed.

Age-Related Reduction in the Maximal Capacity for Sleep—Implications for Insomnia

Sleep changes markedly across the life span and complaints about insomnia are prevalent in older people [1]. Whether age-related alterations in sleep are due to modifications in social factors, circadian physiology, homeostatic drive, or the ability to sleep remains unresolved. We assessed habitual sleep duration at home and then quantified daytime sleep propensity, sleep duration, and sleep structure in an inpatient protocol that included extended sleep opportunities covering 2/3 of the circadian cycle (12 hr at night and 4 hr in the afternoon) for 3-7 days in 18 older and 35 younger healthy men and women. At baseline, older subjects had less daytime sleep propensity than did younger subjects. Total daily sleep duration, which was initially longer than habitual sleep duration, declined during the experiment to asymptotic values that were 1.5 hr shorter in older (7.4 +/- 0.4 SEM, hour) than in younger subjects (8.9 +/- 0.4). Rapid-eye-movement sleep and non-rapid-eye-movement sleep contributed about equally to this reduction. Thus, in the absence of social and circadian constraints, both daytime sleep propensity and the maximal capacity for sleep are reduced in older people. These data have important implications for understanding age-related insomnia.

Circadian Phase Resetting in Older People by Ocular Bright Light Exposure

Abstract Background Aging is associated with frequent complaints about earlier bedtimes and waketimes. These changes in sleep timing are associated with an earlier timing of multiple endogenous rhythms, including core body temperature (CBT) and plasma melatonin, driven by the circadian pacemaker. One possible cause of the age-related shift of endogenous circadian rhythms and the timing of sleep relative to clock time is a change in the phase-shifting capacity of the circadian pacemaker in response to the environmental light-dark cycle, the principal synchronizer of the human circadian system. Methods We studied the response of the circadian system of 24 older men and women and 23 young men to scheduled exposure to ocular bright light stimuli. Light stimuli were 5 hours in duration, administered for 3 consecutive days at an illuminance of ˜10,000 lux. Light stimuli were scheduled 1.5 or 3.5 hours after the CBT nadir to induce shifts of endogenous circadian pacemaker to an earlier hour (phase advances) or were scheduled 1.5 hours before the CBT nadir to induce shifts to a later hour (phase delays). The rhythms of CBT and plasma melatonin assessed under constant conditions served as markers of circadian phase. Results Bright light stimuli elicited robust responses of the circadian timing system in older people; both phase advances and phase delays were induced. The magnitude of the phase delays did not differ significantly between older and younger individuals, but the phase advances were significantly attenuated in older people. Conclusions The attenuated response to light stimuli that induce phase advances does not explain the advanced phase of the circadian pacemaker in older people. The maintained responsiveness of the circadian pacemaker to light implies that scheduled bright light exposure can be used to treat circadian phase disturbances in older people.

Linear Demasking Techniques Are Unreliable for Estimating the Circadian Phase of Ambulatory Temperature Data

Clinical investigators often use ambulatory temperature monitoring to assess the endogenous phase and amplitude of an individuals circadian pacemaker for diagnostic and research purposes. However, an individuals daily schedule includes changes in levels of activity, in posture, and in sleep-wake state, all of which are known to have masking or evoked effects on core body temperature (CBT) data. To compensate for or to correct these masking effects, many investigators have developed “demasking” techniques to extract the underlying circadian phase and amplitude data. However, the validity of these methods is uncertain. Therefore, the authors tested a variety of analytic methods on two different ambulatory data sets from two different studies in which the endogenous circadian pacemaker was not synchronized to the sleep-wake schedule. In both studies, circadian phase estimates calculated from CBT collected when each subject was ambulatory (i.e., free to perform usual daily activities) were compared to those calculated during the same study when the same subjects activities were controlled. In the first study, 24 sighted young and older subjects living on a 28-h scheduled “day” protocol were studied for approximately 21 to 25 cycles of 28-h each. In the second study, a blind man whose endogenous circadian rhythms were not synchronized to the 24-h day despite his maintenance of a regular 24-h sleep-wake schedule was studied for more than 80 consecutive 24-h days. During both studies, the relative phase of the endogenous (circadian) and evoked (scheduled activity-rest) components of the ambulatory temperature data changed progressively and relatively slowly, enabling analysis of the CBT rhythm at nearly all phase relationships between the two components. The analyses of the ambulatory temperature data demonstrate that the masking of the CBT rhythm evoked by changes in activity levels, posture, or sleep-wake state associated with the evoked schedule of activity and rest can significantly obscure the endogenous circadian component of the signal, the object of study. In addition, the masking effect of these evoked responses on temperature depends on the circadian phase at which they occur. These nonlinear interactions between circadian phase and sleep-wake schedule render ambulatory temperature data unreliable for the assessment of endogenous circadian phase. Even when proposed algebraic demasking techniques are used in an attempt to reveal the endogenous temperature rhythm, the phase estimates remain severely compromised.

Review: On Mathematical Modeling of Circadian Rhythms, Performance, and Alertness

Mathematical models of neurobehavioral performance and alertness have both basic science and practical applications. These models can be especially useful in predicting the effect of different sleep-wake schedules on human neurobehavioral objective performance and subjective alertness under many conditions. Several relevant models currently exist in the literature. In principle, the development and refinement of any mathematical model should be based on an explicit modeling methodology, such as the Box modeling paradigm, that formally defines the model structure and calculates the set of parameters. While most mathematical models of neurobehavioral performance and alertness include homeostatic, circadian, and sleep inertia components and their interactions, there may be fundamental differences in the equations included in these models. In part, these may be due to differences in the assumptions of the underlying physiology. Because the choice of model equations can have a dramatic influence on the results, it is necessary to consider these differences in assumptions when examining the results from a model and when comparing results across models. This article presents principles of mathematical modeling and examples of how such procedures can be applied to the development and refinement of mathematical models of neurobehavioral performance and alertness. This article also presents several methods of testing and comparing these models, suggests different uses of the models, and discusses problems with current models.