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Department of Psychiatry and Behavioural Sciences, Stanford University, Palo Alto, CA 94304, USA
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(Received 19 January 2004;
accepted after revision 21 April 2004;
first published online 23 April 2004)
Corresponding author E. Mignot: Department of Psychiatry and Behavioural Sciences, Stanford University, Palo Alto, CA 94304, USA. Email: mignot{at}stanford.edu
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Introduction |
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The hypocretinergic system is difficult to study in humans. Hypocretin-1 is only consistently found in brain tissue and cerebrospinal fluid (CSF). Squirrel monkeys (Saimiri sciureus) are small, diurnal (day-active), New World primates that, like humans, exhibit long, consolidated wake and sleep bouts (Richter, 1968; Wexler & Moore-Ede, 1985; Edgar et al. 1993). Based on studies in humans who lack hypocretin (narcoleptics; Dantz et al. 1994; Broughton et al. 1998) and our own examination of hypocretin in squirrel monkeys (Zeitzer et al. 2003), we have hypothesized that hypocretin is critically involved in consolidating wakefulness into a single extended period in humans and squirrel monkeys. Other mammals, including cats, dogs, mice and rats, do not consolidate wake (polyphasic, having relatively short periods of interspersed wake and sleep) and are therefore imperfect models of human sleep–wake physiology. Another advantage of the squirrel monkey lies in the fact that CSF is readily obtainable from the cerebellomedullary cistern (cisterna magna). There is good temporal concordance between concentrations of cisternal hypocretin-1 and dialysate hypocretin-1 from both the hypothalamus and medial thalamus (Fujiki et al. 2001; Yoshida et al. 2001). In contrast, collection of CSF in humans is typically limited to lumbar sampling. The relationship between brain release of hypocretin-1 and lumbar CSF concentrations of hypocretin-1 is confounded by an extensive temporal delay (Di Chiro et al. 1976), dampening of diurnal fluctuations (Salomon et al. 2003) and the presence of hypocretin-containing nerve endings in the spinal cord (van den Pol, 1999).
We have reported that cisternal CSF concentrations of hypocretin-1 in squirrel monkeys have a robust daily oscillation, with a peak late in the waking day and a nadir just around typical waketime, as theorized for a circadian alertness signal (Zeitzer et al. 2003). In animals in which wake has been extended past usual bedtime, hypocretin-1 concentrations stay elevated (Yoshida et al. 2001; Zeitzer et al. 2003; Pedrazzoli et al. 2004). This implies that hypocretin-1 secretion can be driven or modulated by homeostatic mechanisms (i.e. those dependent on the immediate history of sleep and wake). An alternative explanation is that the elevated hypocretin-1 concentrations observed during wake extension are due to a difference in activity (high locomotion during wake versus low locomotion during sleep).
Anatomical evidence supports a role of endogenous hypocretin in regulating motor activity (Peyron et al. 1998; Moore et al. 2001; Krout et al. 2003; Baldo et al. 2003). Intracerebroventricular injection of exogenous hypocretin-1 in rats increases locomotor activity (Ida et al. 1999; Hagan et al. 1999; Piper et al. 2000), though it is not well understood whether this is a direct induction of locomotion or if it is secondary to increased body temperature (Yoshimichi et al. 2001) or wakefulness (España et al. 2002). Wakefulness in association with spontaneous movements causes a greater induction of c-fos in cat hypocretin-containing neurones than quiet wakefulness (Torterolo et al. 2003). Forced locomotion also increases CSF hypocretin in both dogs (Wu et al. 2002) and rats (Martins et al. 2002), though this manipulation causes sleep deprivation in these species, an intervention that increases CSF hypocretin (Fujiki et al. 2001; Zeitzer et al. 2003). In this study, we have used squirrel monkeys to study the effects of increased and decreased locomotion throughout the day, independent of sleep deprivation.
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Methods |
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Squirrel monkeys (Saimiri sciureus sciureus) were housed indoors in groups of six (cage dimensions: 2.1 x 2.4 x 2.0 m) and exposed to a 12 h light : 12 h dark cycle (lights on at 07.00 h, supplemented with artificial lighting 07.00–19.00 h to ensure 12 h of light per day). Animals had ad libitum access to food (New World Primate Diet 5040; PMI Nutrition International Inc., Brentwood MO, USA) and water; food was replenished daily at 10.00 h except on experimental days, when it was done at 07.00 h. All husbandry and experimental procedures were reviewed and approved by the Stanford University Administrative Panel on Laboratory Animal Care (IACUC).
General protocol
Using a percutaneous cisternal tap, we collected CSF samples from a group of 10 adult female squirrel monkeys (9–10 years old, body weight 686–902 g). Samples were collected at 10.00, 13.00, 16.00 and 19.00 h, both under baseline conditions (no intervention) and after restricting activity for 3, 6, 9 or 12 h (i.e. 07.00–10.00 h, 07.00–13.00 h, 07.00–16.00 h or 07.00–19.00 h, respectively). Samples were also collected twice at 10.00 h after an extended period of environmental enrichment from 07.00 to 10.00 h, and once at 10.00 h after an extended period of forced locomotion from 07.00 to 10.00 h. There were at least 2 weeks between each CSF collection. Animals maintained weight during the study period and exhibited no negative indications following CSF collection. Post-procedure analgesia was available and would have been prescribed by the veterinary staff had they or we deemed it necessary. All samples were assayed in duplicate for hypocretin-1 and cortisol.
Activity manipulation
Four conditions were used: baseline, restricted, enriched or forced. Baseline refers to normal activity, a situation in their standard home cage without investigator contact before CSF collection. Under restricted activity conditions, monkeys were placed in a small transport cage (46 x 46 x 46 cm) that limited movement (10 monkeys in two cages, 5 in each). The monkeys were monitored remotely using a video camera. Before the start of this experiment, monkeys had been exposed many times to the small activity restriction cages, since they were used to hold the monkeys for short periods of time for routine management procedures (e.g. transport between colony rooms). Investigator contact was limited to few, brief interventions to check on the monkeys, adjust monitoring equipment, or to ensure reduced movement. The monkeys typically clung to the sides of the cage or sat on the cage floor. No sleep was evident. Food and water were available ad libitum. Under enriched activity conditions, monkeys lived in their standard home cage and every 20–40 min, an investigator would add or subtract an enrichment variable comprised of the following: opening/closing the barn doors (exposure to outdoors), adding extra horizontal or vertical perching, hanging wire rope or rubber bungees from the cage top, hanging a circular wire rope with sliding plastic pieces attached, hanging a reflective mirror sheet outside the cage, shaking a metal board (loud noise), or giving a board with food boxes attached and openings in the board to access the food (standard chow). In preliminary experiments, monkeys were exposed to these enriching variables one at a time and the manipulations were all found to increase activity in some, but not all, monkeys at a given time. Monkeys were remotely monitored with a video camera such that when a decline in their activity was observed, an environmental variable was changed. The final activity condition was forced locomotion. This condition is similar to a procedure we have used previously to extend wakefulness in this species (Zeitzer et al. 2003), although more intensive. In brief, between 07.00 and 10.00 h, a single investigator (J.M.Z.) remained in the cage and would rattle the perch upon which the monkeys were resting. When the monkeys came to rest on a second perch, that perch would be rattled, and so on. In this way, the investigator forced locomotion for approximately 15 out of every 30 min.
Activity monitoring
In order to objectively quantify locomotor activity, all monkeys wore an actigraph (Actiwatch-64, MiniMitter, Bend, OR, USA) attached to their collar. An actigraph is a small (17 g) device capable of detecting movement through the use of an accelerometer. Actigraphy data were analysed using Sleepwatch software (v. 2.82, Cambridge Neurotechnology, Cambridge, UK). Activity measurement was unsuccessful in 11 of 110 collection intervals (one baseline collection {at 13.00 h}, eight transport cage collections {one at 13.00 h, three at 16.00 h, and four at 19.00 h}, two forced locomotion collections). Data from all other collections (n= 99) were used in subsequent analyses.
CSF collection
Cisternal CSF was collected from anaesthetized monkeys using a siliconized syringe (Lyons et al. 1999; Zeitzer et al. 2003). Anaesthesia was induced by intrasaphenous injection of 10.0 mg kg–1 ketamine hydrochloride with 0.5 mg kg–1 diazepam, and supplemented as needed with an intramuscular injection of 5.0 mg kg–1 ketamine hydrochloride. CSF (200 µl) was collected and placed in a siliconized tube on ice. Within 1 h of collection, CSF samples were placed in a –80°C freezer. CSF was successfully obtained in all but one instance (1 monkey in the forced locomotion condition).
Assays
We used 25 µl of squirrel monkey CSF, diluted with 75 µl of RIA buffer, to measure hypocretin-1 using a commercially available radioimmunoassay and a custom hypocretin-1 antibody provided by Dr Shahrad Taheri and Dr Ling Lin (detection limit = 100 pg ml–1, 5% intra-assay variability, Phoenix Pharmaceuticals, Belmont, CA, USA). CsFn (10 µl) was diluted with 50 µl of RIA buffer and assayed for cortisol using a commercially available radioimmunoassay (Diagnostic Products Inc., Los Angeles, CA, USA). All samples were assayed in duplicate.
Statistics
Data were analysed using Microsoft Excel (v. 10.2614.2625) using Student's paired t test or analysis of variance (ANOVA), as appropriate. Correlated (dependent) ANOVA were done with the java script available at http://faculty.vassar.edu/lowry/anova1u.html. Data from the two enriched activity conditions were combined within monkey before statistical analysis. Percent data were log transformed before averaging. Unless otherwise noted, all data are presented as means ±S.E.M.
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Results |
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The restricted activity condition robustly diminished locomotor activity as compared to baseline at all time points examined (Fig. 1). In comparing the restricted activity condition to baseline, there was an 81.0 ± 2.58% decrease in locomotor activity between 07.00 and 10.00 h before the 10.00 h CSF collection, a 75.3 ± 6.65% decrease in locomotor activity between 07.00 and 13.00 h before the 13.00 h CSF collection, an 86.8 ± 4.81% decrease in locomotor activity between 07.00 and 16.00 h before the 16.00 h CSF collection, and a 92.4 ± 2.81% decrease in locomotor activity between 07.00 and 19.00 h before the 19.00 h CSF collection. Despite the large difference in locomotor activity that we were able to induce, there was no difference in cisternal CSF hypocretin-1 concentrations after the restricted activity conditions as compared to time-matched baseline values (Fig. 2, left panel).
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We examined whether a long duration stay in a transportation cage caused an activation of the hypothalamic–pituitary–adrenal (HPA) axis, as measured by changes in CSF cortisol. Under baseline conditions, CSF cortisol concentrations exhibited the expected daily variation, being highest near wake time and declining throughout the day. In all CSF samplings that were preceded by an extended stay in the transport cage, CSF cortisol concentrations were significantly increased by 112 ± 12% (Fig. 2, right panel). The magnitude of the increase in cortisol observed was similar across the four time points and durations (single-factor ANOVA, d.f. = 39, P= 0.76).
Effect of elevated locomotor activity on CSF hypocretin-1 and cortisol concentrations
We next examined the effects of enhancing motor activity on CSF hypocretin-1 and cortisol concentrations at 10.00 h. Results are illustrated in Fig. 3. The restricted, enriched, forced and baseline conditions produced both different absolute amounts and overall patterns of locomotion between 07.00 and 10.00 h. Under baseline conditions, locomotor activity gradually increased between 07.00 and 10.00 h (685 ± 56.6 arbitrary units {a.u.}), as previously reported (Fig. 1, top panel). In contrast, monkeys in the restricted activity condition showed relatively little locomotion between 07.00 and 10.00 h (118 ± 11.8 a.u., 81.2 ± 2.54% less than baseline). Enriched conditions (962 ± 42.3 a.u., 45.2 ± 9.68% above baseline) evoked a pattern of activity similar to baseline with the addition of an initial burst of locomotion. Finally, the forced locomotion condition increased activity significantly (1721 ± 201 a.u., 161 ± 40.1% above baseline), with especially elevated bursts during the time of investigator interaction. Overall, average locomotor activity in each condition was significantly different from each other (ANOVA, d.f. = 47, P < 0.001; post hoc student's paired t tests, P < 0.005).
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As is evident in Fig. 3, the different activity conditions also evoked different cortisol responses. Cortisol concentrations at 10.00 h were 37.46 ± 3.029 µg dl–1 (restricted), 21.93 ± 2.155 µg dl–1 (baseline), 22.78 ± 1.740 µg dl–1 (enhanced) and 43.02 ± 2.147 µg·dl–1 (forced). Statistical analysis indicated a significant effect of condition (ANOVA, d.f. = 48, P < 0.001) with post hoc analysis indicating that cortisol concentrations observed in the restricted and forced conditions were each significantly higher than those observed in the baseline and enriched conditions (Student's paired t tests, P < 0.02). Cortisol concentrations were not significantly different in restricted versus forced locomotion conditions (Student's paired t tests, P > 0.18). There was no significant linear correlation between CSF cortisol and hypocretin-1 concentrations (r =–0.07, P= 0.68, Pearson moment coefficient).
We further refined our analysis by examining the relationship between hypocretin-1 and the specific activity patterns observed within each condition in each monkey. By studying only the 10.00 h time point, we avoid a ceiling or basement effect in the hypocretin-1 data (Zeitzer et al. 2003). Activity data in the restricted, enhanced and forced locomotion conditions were changed into percentage change from baseline in order to account for intermonkey variability in basal locomotor rate. Hypocretin-1 concentrations were similarly normalized. Average locomotor activity between 07.00 and 10.00 h was highly correlated with the relative hypocretin-1 concentrations obtained at 10.00 h (Pearson moment correlation, r= 0.58, P < 0.001). The variation in the pattern of locomotion observed in the enriched activity condition (Fig. 3B) also enabled us to examine which part of the locomotor activity best reflected the change in hypocretin-1 concentrations (i.e. are hypocretin-1 concentrations reflecting proximal or distal bursting in activity, or the middle nadir; see Fig. 3B). We examined the relationship between the relative change in hypocretin-1 concentration obtained in the 20 cisternal CSF samples and the average locomotor activity before the CSF collection in the enriched condition. Using a dependent, sequential correlation analysis, we examined all correlations between hypocretin-1 concentrations and up to 11 h of prior locomotor activity data. We repeated this analysis after excluding up to 3 h of locomotor data, in 15 min increments, proximal to the CSF collection. These analyses indicated that the best correlation between the hypocretin-1 and locomotor data occurred when locomotor data from 45 to 77 min before obtaining CSF were integrated. Significant (P < 0.05) data were also obtained when locomotor data were integrated between 45 and up to 83 min. In other words, excluding the locomotion occurring 45 min before obtaining the CSF sample and integrating the next 30 min of locomotor data yielded the best correlation. When this was extended to data from all conditions, and locomotor data were normalized to baseline conditions, the Pearson moment correlation was similarly significant (r > 0.54, P < 0.001). We did a 
-square analysis of these data, comparing the observed distribution of hypocretin-1 values with the assumption of a random distribution of hypocretin-1 values. Such analysis indicated that hypocretin-1 was non-randomly distributed (2= 8.58, d.f. = 3, P < 0.04) with respect to locomotion. This indicates a significant impact of locomotion on hypocretin-1.
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Discussion |
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Further evidence for lack of a robust interaction of activity with hypocretin was demonstrated using conditions aimed at stimulating locomotion in squirrel monkeys. Despite robust increases in locomotion after enriched and forced activity, hypocretin-1 did not increase significantly. A trend toward increasing hypocretin-1 concentrations was, however, noticed when comparing reduced, baseline, enriched and forced locomotion conditions, suggesting a modulating effect. Hypocretin-1 concentrations were significantly lower in restricted versus elevated activity conditions, substantiating this observation. When locomotion increased above baseline, hypocretin-1 concentrations were significantly above baseline. In contrast, however, when locomotion was lower than baseline, hypocretin-1 concentrations were distributed randomly, being both higher and lower than baseline. This suggests that increased locomotion may enhance hypocretin secretion while reduced activity has less effect. In addition, the magnitude of the change induced by locomotion was small in comparison to the diurnal change that occurs independent of locomotion. In the restricted activity condition, concentrations increased by 711 ± 69.6 pmol l–1 between 10.00 and 19.00 h (Fig. 2). This can be attributed mostly, if not solely, to a diurnal mechanism, probably controlled by a suprachiasmatic nucleus-dependent mechanism (Zhang et al. 2004). In contrast, we observed a change of only 221 ± 109 pmol l–1 in response to a 161% increase in locomotion in the forced activity condition. The diurnal change is therefore approximately three times larger than that induced by almost constant activity. Thus, while locomotion does not appear necessary for the expression of the daytime fluctuation in CSF hypocretin-1, increased locomotion probably modulates hypocretin-1 concentrations independent of sleep.
The consolidation of wakefulness into a single episode in the absence of external stimulation is unique to humans and some New World monkeys. In rodents, and to a lesser degree cats and dogs, sleep and wake are normally fragmented throughout the 24 h day, with a strong nocturnal or diurnal preference. It has been hypothesized that the hypocretin system is important for the consolidation of wakefulness into a single daily episode (Broughton et al. 1998; Dantz et al. 1994; Zeitzer et al. 2003), owing to its ability to increase wakefulness late in the day. In this model, hypocretin would represent the basis of the proposed circadian alertness signal (Edgar et al. 1993; Dijk & Czeisler, 1994). The ‘circadian alertness signal’ rises late in the waking day to offset the increasing homeostatic pressure for sleep, thereby aiding in the consolidation of wake into a single, elongated segment. Given the difference in consolidation patterns and the proposed role of hypocretin, however, one would anticipate a large difference in hypocretin regulation between wake-consolidating and polyphasic species. In fact, the daily pattern of CSF hypocretin-1 concentrations is surprisingly similar in rats and monkeys (cf. Fujiki et al. 2001 and Zeitzer et al. 2003). Others have found that hypocretin-1 is significantly affected by the concomitants of wake, such as feeding, locomotion and stress (Sakurai et al. 1998; Zhu et al. 2002; Stricker-Krongrad & Beck, 2002; Wu et al. 2002; Martins et al. 2002; España et al. 2002; Baldo et al. 2003; Diano et al. 2003; Yamanaka et al. 2003). We have not found a robust effect of these factors on hypocretin-1 in the squirrel monkey (present study; Zeitzer et al. 2003; J. M. Zeitzer & E. Mignot, unpublished observations). For example, in the squirrel monkey the change in hypocretin-1 observed during sleep deprivation is not dependent on a change in cortisol (Zeitzer et al. 2003). A possible explanation may be that in all polyphasic species it is impossible to study these factors without disturbing sleep. Differences in the methods used to measure ‘hypocretin activity’ (e.g. c-fos staining, RNA versus protein measurements) may also play a role (e.g. hypocretin release may be increased locally but not globally by a stressful stimulus). Alternatively, the daily rhythm of hypocretin-1 is more strongly modified by exogenous and endogenous factors that require wakefulness in polyphasic animals. This may possibly lead to a sleep–wake structure that is more sensitive to external stimuli in polyphasic animals (i.e. the stronger the presence of these factors, the greater the length of the wake bout). In wake-consolidating squirrel monkeys, and by extension humans, there is also an underlying daily variation of cisternal CSF hypocretin-1 (Salomon et al. 2003). However, in the squirrel monkey, unlike the situation in polyphasic mammals, CSF hypocretin-1 is not strongly influenced by stress and only slightly influenced by locomotion. Wake-consolidating mammals may not need an exogenous or endogenous ‘reason’ to be remain awake continuously for extended periods of time (up to 16 h). Given additional evidence from humans who have dysfunctional hypocretin systems (i.e. narcoleptics), and the data accrued from our experiments in squirrel monkeys, hypocretin-1 probably provides a wake-promoting signal that peaks in the evening hours and is lowest at wake time, enabling hypocretin-1 to help offset the homeostatic drive for sleep that builds up throughout the day. It may be that the evolutionary leap that has occurred in species able to consolidate wakefulness into a single, continuous daily bout is that the hypocretin systems of these species are no longer dependent upon exogenous factors or that the hypocretin system is sufficient in and of itself to allow wakefulness.
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