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CALL FOR PAPERS
Metabolic Syndrome
1Department of Neurobiology and Physiology and 2Center for Sleep and Circadian Biology, Northwestern University, Evanston; and 3Department of Endocrinology, Evanston Northwestern Hospital, Evanston, Illinois
Submitted 29 April 2005 ; accepted in final form 5 November 2005
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ABSTRACT |
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 TOP ABSTRACT MATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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obesity; sleep time; locomotor activity; sleep fragmentation; circadian rhythms; energy metabolism
In rats, chronic total sleep deprivation (TSD) leads to pronounced changes in energy regulation, including increased food intake, progressive weight loss, elevated sympathetic activation, hyperthermia, and low thyroid hormone levels (4, 13). More recent studies have demonstrated effects of sleep deprivation on the levels of particular hormones and neuropeptides involved in metabolism. Short-term sleep deprivation in rats increases plasma ghrelin concentrations (5). Prolonged TSD results in decreased growth hormone (IGF-1) prolactin, and leptin concentrations (14).
While it is clear that sleep loss results in adjustments in energy metabolism, limited data are available on how changes in energy metabolism affect sleep-wake patterns. Behavioral studies have shown that in mice, a high-fat diet leads to increases in non-rapid eye movement (NREM) sleep time (20) whereas in rats, food deprivation results in decreased sleep time (10, 27) or a more fragmented sleep pattern (6). In rats, the refeeding period following food deprivation is accompanied by elevated sleep time (39), possibly depending on the nutritional content of the food (27). Satiety-inducing agents, such as cholecystokinin and insulin, increase sleep time in rodents (29). Acute leptin administration has been shown to decrease rapid eye movement (REM) sleep and increase NREM sleep time in rats (42). Furthermore, substances, such as histamine and orexin/hypocretin, which are synthesized in and/or have receptor sites in the hypothalamus, have important roles in the control of both feeding and sleep-wake patterns (38, 41, 47, 52).
The effect of sleep deprivation on leptin and the ability of leptin to modulate sleep-wake patterns is of particular interest because this anorectic hormone, which is produced in adipose cells, serves a critical function as a signal of adiposity and satiety to the hypothalamus (3, 33) and may represent an important mechanistic link between sleep and metabolic regulation. The ob/ob mouse is a genetic model of leptin deficiency resulting from a spontaneous mutation in the gene (ob) encoding leptin (18, 56). These mice exhibit hyperphagia and early-onset obesity, as well as hallmarks of the metabolic syndrome including hyperglycemia, insulin resistance, and dyslipidemia. To explore the possible relationship between leptin deficiency and sleep-wake regulatory processes, we characterized the sleep-wake phenotype in ob/ob mice. Here, we report that genetic leptin deficiency in ob/ob mice results in altered sleep-wake organization under baseline conditions, affects the capacity to recover from sleep deprivation, and impairs the diurnal rhythms of sleep-wake states and locomotor activity.
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MATERIALS AND METHODS |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Surgical procedures. At 12 wk of age, ob/ob (48.7 ± 1.7 g) and WT (28.1 ± 1.5 g) mice were anesthetized with an intraperitoneal injection of ketamine (80 mg/kg) and xylazine (9 mg/kg). An incision was made on the scalp to expose the skull. To record EEG waveforms, stainless steel screws (Small Parts, Miami Lakes, FL) were placed in two bilaterally predrilled holes in the skull. The first screw was located 1 mm anterior to bregma and 2 mm lateral to the central suture, and the second was positioned 1 mm anterior to lambda and 2.5 mm lateral to the central suture. To record electromyographic (EMG) activity, the exposed ends of two stainless steel Teflon-coated wires (0.002 in. in diameter, Medwire, Mt. Vernon, VA) were bilaterally inserted into the nuchal muscles in the dorsal neck region. All electrodes were connected to a plastic 1 x 4 pin grid array connector (Plastics One, Roanoke, VA) that was secured to the skull using VetBond and cyanoacrylamide resin. Following implantation of the electrodes, a 1-cm incision was made in the right hind quarter region, and a transducer (1.6 g; model PDT-4000; E-mitter by Mini-Mitter) was implanted in the peritoneal cavity to record body temperature. A minimum of 14 days was allowed before beginning data collection.
Sleep recording and data analysis. Following the recovery period, WT (n = 9) and ob/ob (n = 8) mice were housed individually in cylindrical (diameter, 10 in.) sleep recording cages and placed into light (12:12-h light-dark cycle; lights on 0600), temperature (23–24°C), and sound-controlled recording chambers with free access to food and water. EEG/EMG data were collected using a wire tether/commutator system (Plastics One, Roanoke, VA), which allowed animals unrestricted movement about the cage. After 7 days of acclimation to the recording environment, EEG/EMG waveforms were collected for 48 h starting at lights on. At the time of recording, ob/ob mice weighed 59.7 ± 1.7 g and WT mice weighed 30.1 ± 1.2 g. EEG signals were amplified 10,000 times with –6 dB/oct high-pass and low-pass filters set at 1 and 30 Hz, respectively. EMG signals were amplified 5,000 times with high- and low-pass filtered at 30 and 100 Hz. Both signals were digitized at 100 Hz/channel by an analog-to-digital converter (model DT-01EZ; Data Translation, Marlboro, MA) and stored on an IBM-compatible personal computer, using specialized software for acquiring and processing sleep data in rodents (Multilevel, Actimetrics, Evanston, IL).
After the baseline recording, animals were sleep deprived for 6 h during the last half of the light phase (1200–1800) by a gentle handling procedure. To keep an animal awake, an experimenter observed the EEG/EMG recordings for signs of sleep, and then used a progression of stimuli (cage tapping, cage shaking, gentle contact) to awaken the animal. At the beginning of dark onset (1800), sleep deprivation was terminated and EEG/EMG waveforms were recorded for an 18-h uninterrupted recovery sleep period.
With the use of a custom-designed software package (SleepReport, Actimetrics, Evanston, IL), EEG and EMG recordings were divided into 10-s epochs and scored via visual inspection as either wake (low-voltage, high-frequency EEG and high-amplitude EMG), NREM sleep (high-voltage, low-frequency EEG, and low-amplitude EMG), or REM sleep (low-amplitude EEG constituted mainly by theta wave activity and EMG atonia). SleepReport software was used for postscoring analysis, which allowed the determination of sleep structure parameters, including sleep amount, distribution, and consolidation, as well as EEG spectral analysis. The distribution of sleep/wake parameters was quantified by determining the ratio of sleep/wake amounts between the 12:12-h light-dark periods (light-to-dark ratio). Sleep architecture was further examined by comparing WT and ob/ob mice on the number of arousals from sleep (NREM or REM sleep interrupted by a 10-s epoch of wakefulness) stage shifts (number of transitions between 10-s epochs of wake, NREM, and REM), sleep-wake bouts (at least 2 consecutive epochs, 20 s, of wake, NREM, or REM) and the average duration (minutes) of sleep-wake bouts. For quantitative analysis of the EEG signal, each 10-s scoring epoch was divided into five 2-s intervals and subjected to fast Fourier transformation, which included a range of 1–25 Hz with a frequency resolution of 0.5 Hz. For all epochs of NREM sleep, the EEG power in the delta (1–4 Hz), theta (4–8 Hz), and sigma (11–15 Hz) frequency ranges were calculated. Because absolute power density values can show substantial interindividual variability, to analyze the time course of EEG power in each frequency band, the power values were normalized and expressed as a percentage of the individual 24-h mean.
Body temperature monitoring. Body temperature was measured simultaneously with EEG/EMG recordings. Body temperature measurements were taken from a transducer surgically implanted in the peritoneal cavity (1.6 g; model PDT-4000; E-Mitter). These biotelemetry transducers were precalibrated to an accuracy of 0.1°C. The transducers were powered by an inductive solenoid coil and output signals were captured by a radiofrequency receiver that was located beneath each mouse cage. Body temperature was sampled every 10 s and analyzed at the end of the experiment with a custom designed software package (Multilevel, Actimetrics, Evanston, IL). Problems with transmitter recordings occurred in two of the nine WT mice, and these animals were removed from the analyses of body temperature data.
Locomotor activity monitoring. At 6 wk of age, 5 male ob/ob (36.7 ± 1.3 g) and 5 age-matched WT mice (25.0 ± 1.2 g) were individually housed in cages with free access to a running wheel. Animals were maintained on a 12:12-h light-dark cycle (lights on 0600) with food and water available ad libitum. After 2 wk of acclimation to the recording environment and running wheels, activity patterns were recorded using Chronobiology Kit software (Stanford Software Systems, Stanford, CA). Data from the second week of recording, when animals were 9–10 wk of age, were selected for analysis. The animal weights at the beginning of wheel running recordings were ob/ob (43.7.2 ± 1.8 g) and WT (26.9 ± 1.1 g).
For each day of recording, activity counts were accumulated for consecutive 6-min intervals, as well as for the 12-h light phase, 12-h dark phase, and overall 24-h period using ClockLab software (Actimetrics, Evanston, IL). Activity counts in each of these intervals were averaged over the 7 days of recording in each ob/ob and WT mouse to reduce variability within the samples.
Statistical analysis. Repeated-measures ANOVA was used in instances where genotype (WT vs. ob/ob), time (12:12-h light-dark phases, or 2-h intervals), and genotype x time effects were examined. ANOVA was applied to analyze data from baseline and sleep deprivation recordings, as well as locomotor activity profiles. In a few instances, Student's t-tests were used to make simple between- and within-genotype comparisons. Significance levels were set at P < 0.05 for all comparisons. Statistical analyses were performed using Statistica (StatSoft, Tulsa, OK).
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RESULTS |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Quantitative analysis of NREM EEG waveforms. We analyzed EEG activity during NREM sleep by determining the average power density in the delta (1–4 Hz), theta (4–8 Hz), and sigma (11–15 Hz) frequency bands under baseline sleep conditions (Table 1). There were no genotype differences in delta [F(1,15) = 0.4, P > 0.05], theta [F(1,15) = 1.9, P > 0.05], or sigma [F(1,15) = 0.4, P > 0.05] power. There was an overall time effect in which delta power [time main effect, F(1,15) = 8.5, P < 0.01] and theta power [time main effect, F(1,15) = 31.5, P < 0.001] were elevated during the 12-h dark compared to 12-h light phase.
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In ob/ob mice, individual sleep-wake cycles were less consolidated, as indicated by a high level of sleep fragmentation (Table 2). Ob/ob mice had more arousals from sleep [genotype main effect, F(1,15) = 18.9, P < 0.001; genotype x time interaction, F(1,15) = 4.4, P < 0.05] and stage shifts [genotype main effect, F(1,15) = 22.6, P < 0.001] compared with WT mice. In addition, the number of individual wake bouts [genotype main effect, F(1,15) = 14.9, P < 0.01] and NREM bouts [genotype main effect, F(1,15)= 127.8, P < 0.001] was higher in ob/ob mice. On the other hand, the average duration of individual wake bouts [genotype main effect, F(1,15) = 8.2, P < 0.01; genotype x time interaction, F(1,15) = 7.0, P < 0.05] and NREM bouts [genotype main effect, F(1,15) = 9.5, P < 0.01] was shorter in ob/ob mice (Table 2). These data indicate that ob/ob mice fell asleep more frequently but were unable to maintain individual sleep episodes for the same duration as WT mice, reflective of alterations in sleep architecture in ob/ob mice. There were no genotype differences in REM bout number [F(1,15) = 0.01, P > 0.05] or REM bout duration [F(1,15) = 0.91, P > 0.05].
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Recovery from 6-h sleep deprivation. The recovery response following sleep deprivation was first assessed separately in each genotype by comparing sleep during the 18-h recovery period (1800 to 1200) to sleep during the previous day's corresponding baseline period. The recovery period began at dark onset and consisted of the 12-h dark phase and the 6-h light phase, as indicated in Fig. 3. In WT mice, NREM sleep time was significantly elevated during the first 6 h of the recovery period, as well as during hours 9 and 10 of recovery [condition x time interaction, F(8,40) = 11.5, P < 0.001], (Fig. 3). A decrease in NREM sleep time was noted in the last 2 h of the light phase of the recovery period commonly referred to as a negative rebound. Similarly, REM sleep was increased during the first 6 h of the recovery period and remained nonsignificantly elevated during the following 4 h [condition x time interaction, F(8,40) = 4.5, P < 0.001], (Fig. 3). NREM delta power was significantly increased during the first 2 h of recovery [paired t-test, t(5) = 5.7, P < 0.001], indicating an increase in the intensity of NREM sleep (Fig. 3). In ob/ob mice, the rebound in both NREM [condition x time interaction, F(8,56) = 5.0, P < 0.001] and REM sleep [condition x time interaction, F(8,56) = 2.2, P < 0.05] was restricted to the first 4 h of the recovery period and to the last 2 h of the dark phase of the recovery period (Fig. 3). NREM delta power was significantly increased in the first 2 h of recovery sleep [paired t-test, t(7) = 6.1, P < 0.001].
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We examined changes in NREM sleep bout number and duration between the first 12 h of recovery sleep and the corresponding baseline period (Table 4). NREM recovery sleep in WT mice was primarily due to an increase in NREM bout number, whereas in ob/ob mice, the recovery was due to an increase in average NREM bout duration. We did not perform a bout analysis for REM sleep because the low amount of REM sleep in WT mice during the dark-phase baseline recording precluded an accurate analysis of bout duration.
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DISCUSSION |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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The amount of slow-wave activity in the EEG during NREM sleep, called NREM delta (1–4 Hz) power, is used as a quantitative measure of sleep intensity and homeostatic sleep drive (7). In WT animals under baseline conditions, NREM delta power reached a peak at light onset, decreased across the light phase as sleep drive dissipated and was elevated during the dark phase in association with accumulating sleep drive (Fig. 2). Even though ob/ob mice had normal levels of absolute NREM delta power (Table 1), they exhibited less diurnal variation in normalized NREM delta power across the 24 h (Fig. 2), consistent with the possibility that they were unable to accumulate and dissipate sleep drive normally. It may be that this attenuated diurnal rhythm resulted from ob/ob mice sleeping more in the dark phase, therefore, dissipating sleep drive more evenly throughout the 24-h period. Similarly, the increase in NREM sleep fragmentation during the light phase could have prevented the normal dissipation of sleep drive. It may also be that ob/ob mice have a more fundamental deficit in their circadian regulatory system, as discussed in later paragraphs.
In response to sleep deprivation, both WT and ob/ob mice generated a compensatory increase in NREM and REM sleep time, as well as NREM delta power (Fig. 3), indicating the basic mechanisms involved in generating the sleep homeostatic response were intact in ob/ob mice. It should be noted that the NREM and REM rebound in ob/ob mice was shorter in duration and smaller in magnitude compared with WT animals. Because ob/ob mice already had higher levels of baseline sleep time during the dark phase compared with WT mice, they may have been unable to generate the same magnitude of recovery response, referred to as a ceiling effect. Nonetheless, in the current sleep deprivation paradigm, ob/ob mice did not make up for lost sleep time to the same extent as WT mice. Another genotype difference emerged for NREM recovery sleep in that WT mice primarily increased NREM bout number, whereas ob/ob mice clearly increased NREM bout duration, another indication that ob/ob mice have an intact homeostatic response to sleep deprivation. The lack of increase in NREM bout duration during recovery in WT mice is probably due to large variability in this measure during baseline sleep, since sleep time is low during the active phase in WT mice.
Our data are consistent with findings in rats harboring a mutation in the leptin receptor, the obese Zucker rat (9, 26). In these animals, baseline NREM sleep time was increased, and the diurnal sleep rhythm was flattened, although these results should be interpreted cautiously because lean Zucker rats were not used as controls (9). A later study demonstrated that during a brief 6-h recording period, the obese Zucker rats had normal sleep amounts but an increase in sleep fragmentation compared with lean control rats (26). Despite some methodological limitations, these data parallel our findings in the ob/ob mouse and provide another example of altered sleep-wake patterns in the context of impaired leptin signaling.
The data from our study indicate that leptin deficiency, or some physiological consequence of leptin deficiency, has a negative impact on many aspects of sleep regulation in rodents. An important function of hormonal signals of metabolic status, such as leptin, may be to coordinate long-term energy homeostasis with multiple physiological processes, including the regulation of sleep architecture and sleep amount. More generally, an important function of such peripheral signals may be to modulate sleep to put the animal in an optimal state for anabolic or catabolic processes to be carried out. In support of this hypothesis is the finding that when food availability is restricted to the light phase, rats readjust their sleep-wake cycle so that they are awake more in the light and sleep more in the dark phase, therefore, maintaining temporal alignment between metabolic processes and sleep-wake state (36).
Previous studies have shown that changes in energy balance influence sleep-wake patterns. Studies utilizing high-fat feeding and food restriction paradigms have shown that changes in energy consumption affect sleep-wake patterns (10, 20, 27). Also, hormones that are secreted in response to acute changes in energy status, such as cholecystokinin, ghrelin, and insulin have demonstrated effects on sleep-wake patterns, particularly NREM sleep time and NREM sleep intensity (29). Hyperinsulinemia is a component of the metabolic phenotype in ob/ob mice. Considering that ob/ob mice are both hyperphagic and hyperinsulinemic, their increased sleep time may represent increased postprandial sleep. An interesting future experiment will be to test the effects of insulin-sensitizing agents on sleep-wake patters in ob/ob mice.
The metabolic deficits in ob/ob mice include alterations in hypothalamic neurotransmitters involved in the control of feeding behavior and energy expenditure, which have also been shown to be involved in the control of sleep-wake states, such as histamine (38, 41) and orexin/hypocretin (24, 47, 52). The concentrations of hypothalamic histamine and the expression level of prepro-orexin mRNA are reduced in ob/ob mice (19, 53), and the administration of leptin can increase histamine turnover in mice and prepro-orexin mRNA levels in rats (54, 55). Interestingly, orexin knockout (28, 51) and histidine decarboxylase-deficient mice (31) have increased levels of sleep fragmentation. Therefore, one mechanism by which leptin is linked to sleep-wake pathways could involve interactions with histamine and orexin neurons, particularly since leptin receptors have been identified in regions of the hypothalamus where histamine and orexin/hypocretin are synthesized (16, 40). An interesting future experiment will be to determine whether leptin replacement is able to correct the sleep-wake deficits in ob/ob mice.
The brain stem contains cholinergic and serotonergic nuclei important for the balance of sleep-wake states and integration with respiratory and metabolic function. Ob/ob mice have decreased levels of M2 muscarinic receptor protein in the brain and brain stem (12). Injections of the anticholinesterase agent, neostigmine, into the pontine reticular nucleus yields differential effects in WT and ob/ob mice on sleep time and respiratory control (12). Because the serotonergic system has been implicated in the control of feeding and energy expenditure, the raphé nucleus may represent another important brain region where sleep-wake and metabolic regulatory signals intersect. Leptin receptor immunoreactivity has been identified in the dorsal raphé nucleus, and ob/ob mice have decreased levels of serotonin transporter mRNA in dorsal raphé neurons (8). In combination, these findings present a number of candidate anatomical sites that may have important roles in coordinating sleep and metabolic activity.
Recent studies have shown that adipose cells release a number of adipokines, including TNF-
and IL-6, and levels of these are high in obesity (22). There is substantial evidence that TNF- and possibly IL-6, as well as other cytokines, influence sleep-wake patterns (29). Therefore, it is possible that the changes in sleep in ob/ob mice are a response to an inflammatory component of obesity.
There are few data on the circadian rhythms of ob/ob mice with regard to behavioral, physiological, or molecular parameters (17, 37). In the current study, we found that the diurnal distribution of NREM sleep was slightly attenuated but that the rhythm of REM sleep and NREM delta power are notably altered in ob/ob mice (Figs. 1 and 2). Ob/ob mice had reduced activity levels and a pronounced flattening of the locomotor activity rhythm (Fig. 4). Taken together, these results indicate that in ob/ob mice the output rhythmic signals to a variety of physiological systems are attenuated with respect to the amplitude of the signals.
While the circadian system provides an important signal for the propensity and organization of sleep-wake states (7), recent data have emerged to suggest that circadian processes are also critically involved in energy homeostasis. For example, mice harboring a mutation in the circadian clock gene (Clock) develop obesity, hyperphagia, symptoms of the metabolic syndrome and alterations in the regulation of hypothalamic neuropeptides involved in metabolic signaling (50). In addition, environmentally induced disruption of the normal circadian alignment to the light-dark cycle, as occurs in shift workers, has been associated with increased body mass index, insulin resistance, and cardiovascular disease (11, 21). Interestingly, in an in vitro preparation, leptin administration had direct effects on circadian pacemaker cells, suprachiasmatic nuclei (SCN), and induced-phase shifts in the oscillation of these neurons (34). Future studies will be needed to determine whether ob/ob mice have a primary deficit in the function of the circadian pacemaker in the SCN and/or in central and peripheral circadian clock gene regulation. It will also be important to determine whether various rhythms in behavioral (i.e., feeding, activity), physiological (i.e., circulating hormones, hypothalamic neuropeptides, body temperature) and molecular (i.e., circadian clock genes) systems are misaligned in ob/ob mice.
In the current study, we found that ob/ob mice have a lower body temperature in all sleep-wake states across all periods of the light-dark cycle compared with WT animals. While ob/ob mice did show the expected reduction in body temperature in NREM and REM sleep compared with wakefulness, the magnitude of the decrease was smaller than in WT mice. Because of the close interaction between body temperature and sleep-wake regulation, it is possible that thermoregulatory deficits in ob/ob mice (48) contribute, at least in part, to the disruption of their sleep-wake organization. In addition, ob/ob mice exhibit reduced baseline ventilation and an impaired hypercapnic ventilatory response during both wakefulness and sleep (23, 30). The respiratory changes during sleep in ob/ob mice are not likely to result from sleep apnea because there is no indication of upper airway closure in these mice (30). Therefore, the most notable feature of sleep in the ob/ob mice, increased sleep fragmentation, could result from the inability to regulate blood gas levels and the subsequent arousal responses to relieve CO2 retention. These findings suggest that the ob/ob mouse represents a valuable animal model for studying the relationship between obesity, respiratory control, and sleep.
In summary, clinical and experimental studies have shown that chronic sleep loss is associated with impaired metabolic function. One question still to be examined in genetic animal models is whether sleep disruption (i.e., altered sleep architecture, diurnal rhythmicity, or sleep amount) precedes or is a response to the onset of metabolic disruption. It would not be surprising that sleep and metabolic processes act reciprocally on each other in the context of disease states such as obesity, diabetes, and the metabolic syndrome. There are a number of ways in which leptin deficiency could lead to alterations in sleep patterns ranging from direct interactions with sleep-related nuclei to indirect pathways via changes in hormone levels or circadian regulation. Animal models of leptin dysregulation, such as ob/ob and db/db (leptin receptor mutation) mice will be valuable in clarifying the mechanisms and pathways by which leptin is involved in complex behaviors, such as sleep and feeding.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
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REFERENCES |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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