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Sleep. Sep 1, 2010; 33(9): 1147–1157.
PMCID: PMC2938796

Separating the Contribution of Glucocorticoids and Wakefulness to the Molecular and Electrophysiological Correlates of Sleep Homeostasis


Study Objectives:

The sleep-deprivation–induced changes in delta power, an electroencephalographical correlate of sleep need, and brain transcriptome profiles have importantly contributed to current hypotheses on sleep function. Because sleep deprivation also induces stress, we here determined the contribution of the corticosterone component of the stress response to the electrophysiological and molecular markers of sleep need in mice.




Mouse sleep facility.


C57BL/6J, AKR/J, DBA/2J mice.


Sleep deprivation, adrenalectomy (ADX).

Measurements and Results:

Sleep deprivation elevated corticosterone levels in 3 inbred strains, but this increase was larger in DBA/2J mice; i.e., the strain for which the rebound in delta power after sleep deprivation failed to reach significance. Elimination of the sleep-deprivation–associated corticosterone surge through ADX in DBA/2J mice did not, however, rescue the delta power rebound but did greatly reduce the number of transcripts affected by sleep deprivation. Genes no longer affected by sleep deprivation cover pathways previously implicated in sleep homeostasis, such as lipid, cholesterol (e.g., Ldlr, Hmgcs1, Dhcr7, −24, Fkbp5), energy and carbohydrate metabolism (e.g., Eno3, G6pc3, Mpdu1, Ugdh, Man1b1), protein biosynthesis (e.g., Sgk1, Alad, Fads3, Eif2c2, −3, Mat2a), and some circadian genes (Per1, −3), whereas others, such as Homer1a, remained unchanged. Moreover, several microRNAs were affected both by sleep deprivation and ADX.


Our findings indicate that corticosterone contributes to the sleep-deprivation–induced changes in brain transcriptome that have been attributed to wakefulness per se. The study identified 78 transcripts that respond to sleep loss independent of corticosterone and time of day, among which genes involved in neuroprotection prominently feature, pointing to a molecular pathway directly relevant for sleep function.


Mongrain V; Hernandez SA; Pradervand S; Dorsaz S; Curie T; Hagiwara G; Gip P; Heller HC; Franken P. Separating the contribution of glucocorticoids and wakefulness to the molecular and electrophysiological correlates of sleep homeostasis. SLEEP 2010;33(9):1147-1157.

Keywords: Sleep regulation, corticosterone, neuroprotection, microarray, microRNA

A NEED OR PRESSURE FOR SLEEP ACCUMULATES WHILE AWAKE BUT, BECAUSE THE NEUROPHYSIOLOGICAL FUNCTION OF SLEEP REMAINS ELUSIVE, sleep need is not easily defined or objectively measured. Sleep research has profited much from the use of the electroencephalogram (EEG)-derived variable delta power, as illustrated by its central role in theories concerning sleep function (e.g.1). Delta power, a measure that quantifies the delta oscillations (1-4 Hz) that are characteristic of the non rapid-eye-movement (NREM) sleep EEG, is widely used to index sleep need in mammals.2,3 Using this sleep homeostatic index in a panel of 6 inbred strains of mice, we observed that the rate at which sleep need accumulates during wakefulness varies greatly according to genetic background. Specifically, within this panel of 6, the sleep deprivation-induced increase in delta power is smallest in DBA/2J (D2) and largest in AKR/J (AK) mice.3 Subsequent studies in humans confirmed the importance of genetic factors in sleep homeostasis.4 To gain insight into the genetic pathways underlying the homeostatic regulation of sleep, we and others have searched for molecular correlates of sleep need using microarrays and extensive changes in brain gene expression after sleep deprivation have been reported in both mice and rats.5 Also, these gene-profiling studies have contributed to current hypotheses on sleep function.5

Sleep deprivation-induced brain gene-expression profiles have been found to differ with genetic background as well, and one transcript, Homer1a, is considered to be of particular relevance because the sleep-deprivation–induced expression was smaller in D2 mice, compared with AK mice,4 thus matching the strain differences observed in delta power after sleep deprivation, as discussed above. Moreover, mapping of the delta-power phenotype in recombinant offspring derived from D2 and C57BL/6J (B6) mice yielded a quantitative trait locus centered around Homer1,3,6 suggesting a causal implication of Homer1 in the homeostatic regulation of delta power. Other transcripts implicated in sleep homeostasis, such as clock genes,7 also vary according to genetic background (i.e., we observed large strain differences in the rate at which the expression of the Period1 (Per1) and −2 genes increased in the forebrain over the course of sleep deprivation).8

An unavoidable confound in sleep-deprivation studies is that, besides activating sleep homeostatic processes, sleep deprivation also activates the hypothalamic-pituitary-adrenal (HPA) axis, as evidenced by the surge in circulating levels of glucocorticoids; i.e., corticosterone in rodents9,10 and cortisol in humans.11 Accordingly, stress and differences in stress susceptibility could contribute to the reported strain differences on the effects of sleep deprivation on both delta power and brain gene expression. For some types of stress, a relationship with delta power has been demonstrated, although the directions of change are not consistent. For example, mice selected for high stress susceptibility have been found to show lower delta power,12 whereas social-defeat stress increases delta power in the rat.13 Similarly, in humans, a negative correlation has been reported between rates of endogenous cortisol secretion and delta power,14 whereas the administration of the stress hormone cortisol has been found to increase delta power.15 The stress-related surge in plasma corticosterone, which affects the expression of many genes in the brain,16 including the expression and protein levels of some clock genes,17,18 has never been directly controlled for in studies that have investigated the molecular correlates of sleep homeostasis.

The present study aimed at determining the contribution of the corticosterone component of the stress response to the sleep-wake associated changes in the electrophysiological and molecular correlates of sleep need. We first compared the changes in corticosterone plasma levels after sleep deprivation in the two mouse strains that differed for the increase in delta power after sleep deprivation (i.e., D2 and AK), and in B6 mice, a strain with an intermediate response to sleep deprivation.3 We observed that genotype greatly affected the increase in corticosterone, with D2 mice showing the highest response, suggesting that the reduced increase in EEG delta power after sleep deprivation observed in this strain might be a consequence of a higher stress susceptibility. However, in a second experiment, we found that removing the sleep deprivation–dependent corticosterone increase through adrenalectomy (ADX) did not ‘rescue’ the blunted delta-power response to sleep deprivation in D2 mice. Conversely, in a last experiment of similar design, inactivating the corticosterone component of the HPA axis profoundly diminished the brain transcriptome response to enforced wakefulness.


Animals and Surgery

Adult male mice from 3 inbred strains were used in this study: C57BL/6J (B6), AKR/J (AK), and DBA/2J (D2). Mice were purchased from Jackson Laboratory and maintained under standard animal housing conditions, with free access to food and water, and a 12-hour light/12-hour dark cycle. Age was 12 weeks at the time of the experiment. For the first experiment, 10 B6, 8 AK, and 9 D2 mice were used to assess the corticosterone increase after sleep deprivation ending at ZT6 (Zeitgeber time 6; i.e., 6 h after light onset), and 11 B6, 9 AK, and 9 D2 were used as non-sleep-deprived control animals. Also, 6 B6, 8 AK, and 6 D2 mice were sacrificed at ZT18 to measure basal corticosterone levels after the main active period. For the sleep recording experiment, 16 D2 animals were used (control: n = 16; sham-lesioned: n = 9; ADX: n = 7). For the gene-expression experiment, D2 mice (n = 26: control, n = 7 and 6; sleep deprivation, n = 7 and 6 in sham-lesioned and ADX, respectively) were raised on site, and animals between 8 and 12 weeks were used. Bilateral ADX or sham lesions were performed under deep anesthesia (pentobarbital sodium 65-75 mg/kg or ketamine/xylazine 75 and 10 mg/kg, respectively, intraperitoneal injection). Animals were allowed to recover for a week while supplemented with either saline (gene expression experiment) or corticosterone (sleep and EEG experiment; Sigma, St. Louis, MO; 25 μg/mL in 0.2% ethanol-0.5% NaCl) in drinking water. Mice supplemented with saline were adapted to this before surgery.

Electrode implantation for EEG and electromyography (EMG) recordings was performed as detailed previously.19 Briefly, surgery was carried out under deep pentobarbital sodium anesthesia (65-75 mg/kg, intraperitoneal injection). Two gold-plated screws (diameter 1.1 mm) served as EEG electrodes and were screwed through the skull over the right cerebral hemisphere (frontal: 1.7 mm lateral to midline, 1.5 mm anterior to bregma; parietal: 1.7 mm lateral to midline, 1.0 mm anterior to lambda). Two other screws were implanted at the same coordinates over the left hemisphere as anchor screws. Two gold wires served as electromyography electrodes and were inserted between 2 neck muscles. The EEG and EMG electrodes were soldered to a connector and, together with the anchor screws, were cemented to the skull. Recording leads were connected to a swivel contact, and animals were allowed 10 to 14 days of recovery from surgery and habituation before the experiment.

Corticosterone Measurements

For corticosterone and gene-expression measurements, mice were rapidly killed by cervical dislocation immediately at the end of the sleep deprivation (ZT6) together with their non–sleep-deprived controls. The brain and blood plasma were rapidly collected, frozen on dry ice, and stored at −80°C. The measurements of corticosterone levels of animals undergoing sleep recordings were achieved by radioimmunoassay.9 Briefly, triplicate samples of plasma (10 μL) were heat denatured at 80°C. [3H] corticosterone (Sigma) and corticosterone antiserum (Endocrine Sciences, Agoura Hills, CA) were added to the samples that were incubated overnight. [3H] corticosterone was separated from nonradiolabeled corticosterone using Dextran T70 (Amersham Pharmacia Biotech AB, Uppsala, Sweden) coated charcoal, and quantified in a liquid scintillation counter (Beckman model LS 3801, Brea, CA). Competition binding was assessed against a standard curve of corticosterone (Sigma) ranging from 0.001 to 5 ng/mL and analyzed using a nonlinear least-squares formula and best-fit analysis based on the F distribution. The quantification of corticosterone levels of animals involved in gene-expression assays was performed according to manufacturer instructions using an enzyme immunoassay commercial kit (Assay Designs, Ann Arbor, MI).

EEG Recordings and Analysis

All mice were recorded continuously for 48 hours, of which the first 24 hours served as baseline, followed by 6 hours of sleep deprivation, initiated at ZT0, and 18 hours of recovery sleep. Sleep deprivation was achieved by gentle handling.19 All mice were submitted to the same sleep recording protocol twice; i.e., before and after undergoing ADX or sham lesion. The EEG and EMG signals were amplified, filtered and analog-to-digital converted. Behavioral states (wakefulness, NREM sleep and rapid eye movement (REM) sleep) were visually assigned to 4-second epochs, as previously described.19 The EEG signal of artifact-free epochs was subjected to spectral analysis using discrete Fourier transform to calculate the EEG power density in the delta frequency range (1-4 Hz; i.e., delta power) during NREM sleep. Interindividual differences in the absolute level of delta power were accounted for by expressing delta power as a percentage of the mean delta power in NREM sleep during the last 4 hours of the baseline light period. Delta power was averaged for 8 intervals, to which an equal number NREM sleep epochs contribute (i.e., percentiles) both during the baseline light period and during the 6 hours immediately following sleep deprivation (recovery).

Quantitative PCR

RNA was isolated from forebrain (hindbrain excised) using the RNeasy Lipid Tissue Midi kit and was Dnase-treated (QIAgen, Hombrechtikon, Switzerland). All RNA sample amounts were measured with a NanoDrop ND-1000 spectrophotometer (Thermo Scientific, Wilmington, DE), and the quality of RNA samples was verified on Agilent 2100 bioanalyzer chips (Agilent Technologies, Basel, Switzerland). For each sample, reverse transcription was performed on 0.5 μg of RNA. First, RNA, 0.25 μg random hexamers, and 10μM dNTP mix was incubated for 5 minutes at 65°C for the denaturation step. Then, first-strand buffer, 0.1 M DTT, RNAzin Plus Rnase inhibitor, and SuperScript II reverse transcriptase (Invitrogen, Basel, Switzerland) were added to the denaturation mix and incubated for 10 minutes at 25°C followed by 60 minutes at 42°C.

Quantitative polymerase chain reaction (qPCR) was performed according to Applied Biosystems protocol using a real-time cycler ABI Prism 7700 (Applied Biosystems, Foster City, CA). Briefly, approximately 14 ng of cDNA was used in 10 μL for qPCR with Master Mix reagent (Applied Biosystems) under the following cycling conditions: 95°C for 10 minutes, followed by 40 cycles of 95°C for 15 seconds, and 60°C for 1 minute. The assays, designed at exon-exon junctions, were performed with oligos (sequences provided in Supplementary Table 6 [Supplementary tables and figures are available online only at www.journalsleep.org.]). Primers were purchased from Invitrogen or Microsynth (Balgach, Switzerland) and probes from Eurogentec SA (Seraing, Belgium). Each PCR reaction was done in triplicate. Tbp, GusB, and Rps9 were used as endogenous controls after selection of the most stable control genes using geNorm v3.5 program and relative quantification of mRNA levels was evaluated using the modified ΔΔCt method from qBase v1.3.5 program, as performed previously.6

Statistical Analysis

To assess the differential effects of sleep deprivation on corticosterone secretion in inbred mouse strains, a 2-way analysis of variance (ANOVA) with factors Strain (B6, AK, D2) and Condition (sleep deprivation vs control) was performed. To evaluate the effects of time on corticosterone secretion, a 2-way ANOVA was used with Strain and Time (ZT6 vs ZT18) as factors. The effect of ADX on accumulated difference in NREM sleep time after sleep deprivation was assessed at each time point using 1-way ANOVA with factor Group (control, sham, ADX). The effect of ADX on delta power was tested using a repeated-measures ANOVA with factors Group (sham vs ADX), Condition (control vs sleep deprivation), and Interval (1 to 8). Lastly, the effect of ADX on sleep-deprivation–induced forebrain gene expression was assessed using 2-way ANOVA with factors Group (sham vs ADX) and Condition (control vs sleep deprivation). Significant interactions were decomposed using posthoc t tests, Tukey HSD test, or simple effect analysis (contrasts). Statistical analyses were done using SAS (SAS Institute Inc, Cary, NC) or Statistica (Statsoft Inc, Tulsa, OK). Statistical significance was set to P = 0.05, and results are reported as mean ± SEM.


RNA samples isolated from forebrain were diluted to 300 ng/3μL and independently used to perform the target preparation using the whole transcript sense target labeling protocol procedure (Affymetrix, High Wycombe, UK). Then, 5.5 μg of each fragmented cDNA was end labeled with biotin and hybridized to a GeneChip Mouse Gene 1.0 ST array (Affymetrix), processed, and scanned according to standard procedures. Normalized expression signals were calculated from Affymetrix CEL files using RMA normalization method implemented in the Affymetrix Expression Console software, as in our previous publication.6 RMA processing was performed separately for each animal. All subsequent statistical analyses were performed using R (R Core, 2004, http://www.R-project.org) and Bioconductor packages (http://www.Bioconductor.org). Control and unannotated probe sets were removed, leaving 28,198 probe sets for statistical analysis. Differential hybridized features were identified using Bioconductor package “limma”, as before.6 P values were adjusted for multiple testing with the Benjamini and Hochberg method to control the false discovery rate (FDR).20 We fitted a model with a coefficient for each of the 4 factor combinations (Sham-control, Sham-sleep deprivation, ADX-control, ADX-sleep deprivation) and then extracted the comparisons of interest as contrasts. Functional enrichment analysis was performed using Ingenuity Pathway Analysis Tool (Ingenuity Systems, Inc., Redwood City, CA). MicroRNA (miRNA) targets enrichment analysis was performed using Miranda Mus musculus putative targets (microrna.sanger.ac.uk/cgi-bin/targets/v5/download.pl). Enrichment of putative targets of mmu-miR-29c, −410, −112, −151-3p and −151-5p were tested separately among genes upregulated or downregulated by sleep deprivation (FDR < 0.05) using Fisher exact test.


Genotype Influences the Sleep Deprivation-Induced Corticosterone Surge

To evaluate the effect of genetic background on the corticosterone surge associated with sleep deprivation, corticosterone levels were measured in 3 inbred mouse strains (i.e., B6, D2, and AK). Consistent with previous work,9,10 a 6-hour sleep deprivation increased corticosterone levels in all 3 strains compared with baseline levels (Figure 1A). Across genotypes, significant differences in the corticosterone response to sleep deprivation were noted, and the relative increase was 2- to 3-fold larger for D2 mice compared with B6 and AK mice (Figure 1B). The strain differences in plasma corticosterone levels were specific to the enforced wakefulness because concentrations in the non–sleep-deprivation control groups sampled at the same time of day (ZT6; i.e., 6 hours after light onset) did not differ. Also, sustained periods of spontaneous wakefulness, in the mouse strains used here occurring between ZT12 and ZT18,19 did not increase corticosterone levels in D2 and B6 mice (Figure 1A). Interestingly, in AK mice, which responded the least to sleep deprivation in terms of increased corticosterone levels, similar concentrations were reached after a spontaneous sustained period of wakefulness (i.e., at ZT18 in baseline) compared with after sleep deprivation (Figure 1A).

Figure 1
Corticosterone (CORT) secretion induced by sleep deprivation (SD) in inbred mice. (A) CORT was measured at ZT6 in control condition, at ZT6 after 6 h of SD, and at ZT18 after an extended period of spontaneous wakefulness in AK, B6, and D2 mice. SD induced ...

HPA activity is known to vary with genetic background,12 and, consistent with our findings, D2 mice were reported to be more susceptible to various other stressors, compared with B6 mice.21,22 Our data thus confirm that, in mice, sleep deprivation activates the HPA axis and that genetic factors importantly modulate this effect. The strain differences in the fold increase in corticosterone secretion after sleep deprivation appeared inversely proportional to the rate of increase of the homeostatic sleep pressure reflected by the dynamics of delta power (Figure 1B).3 Indeed, D2 mice showed the lowest delta power rebound and the highest corticosterone surge with sleep deprivation, whereas AK mice showed the reverse and B6 mice had intermediate phenotypes. This raises the possibility that the strain differences in the corticosterone response might have contributed to the strain differences in the expression of delta power during recovery sleep.

Adrenalectomy Does Not Influence the Delta-Power Response to Sleep Deprivation

To determine whether the higher corticosterone increase following sleep deprivation in D2 mice contributed to their blunted delta power rebound, we performed ADX with corticosterone replacement. We contrasted the effects of sleep deprivation on delta power in this group with the sleep-deprivation effects before the surgery in the same mice and to the sleep-deprivation effects in a group of sham-lesioned mice recorded in parallel.

Also in this cohort of D2 mice, the sleep-deprivation–induced rebound in delta power was low compared with previously published data for other strains,19 and the levels reached in both intact controls and the sham-lesioned mice (171% ± 6% and 183% ± 10%, respectively; Figure 2A) were well within the range of values previously reported for this strain (179% ± 14%).19 Although ADX successfully abolished the sleep-deprivation–induced increase in corticosterone secretion (Figure 2B), ADX affected neither the baseline dynamics of delta power nor the increase in delta power after sleep deprivation (178% ± 10%; Figure 2A). Not only delta power during NREM sleep, but also baseline amount and distribution of total sleep time (Supplementary Figure 1) and recovery time spent in NREM sleep following the sleep deprivation (Figure 2C) did not vary across the 3 experimental groups.

Figure 2
Effects of adrenalectomy (ADX) on recovery from sleep deprivation (SD). (A) Delta power time course during the light period of baseline (ZT0-ZT12) or after 6 hours of SD (ZT6-ZT12) in control, sham-lesioned, and ADX mice. Delta power changes during baseline ...

Adrenalectomy Attenuates the Effect of Sleep Deprivation on Period (Per) Gene Expression

The contribution of the increase in corticosterone to the sleep-deprivation–dependent increase in the expression of the clock genes Per1-3 was investigated in a separate set of D2 mice by comparing forebrain expression using qPCR among ADX and sham-operated mice that were either sleep deprived or were allowed to sleep ad lib prior to sacrifice at ZT6. Also in this experiment, sleep deprivation elevated corticosterone in sham-operated mice only (Figure 3, bottom left panel). Similar to previous studies,6,8,23,24 sleep deprivation induced an increase in the expression of the Per genes in the forebrain of sham-operated mice. This increase was strongly attenuated in ADX mice and no longer reached significance levels for Per1 and Per3, whereas the increase in Per2, although still significant, was reduced by approximately 40% (Figure 3, left panels). ANOVA revealed a significant interaction between factors Sleep Deprivation and ADX for Per2 and Per3 expression (Figure 3).

Figure 3
Effect of adrenalectomy (ADX) on sleep deprivation (SD)-induced changes in expression of clock genes and a sleep-related gene. Gene expression was assessed at ZT6 by quantitative polymerase chain reaction (qPCR) in sham-lesioned or ADX D2 mice in control ...

Other clock genes that we evaluated in this qPCR experiment were Npas2 (Neuronal PAS domain protein 2), Rev-Erba (or Nr1d1; nuclear receptor subfamily 1, group D, member 1), and the “clock-controlled” gene Dbp (D site albumin promoter binding protein). The typical sleep-deprivation–dependent decrease in forebrain Dbp levels8,23 was equally observed in ADX mice (Figure 3). Also Rev-Erba mRNA levels were decreased with sleep deprivation, but this decrease was significant in sham-operated mice only. Similarly, a significant increase in Npas2 expression after sleep deprivation was found only in sham mice. Although ANOVA analyses identified a significant interaction between factors Sleep Deprivation and ADX for the transcripts Per2 and −3 only, ADX seemed, in general, to attenuate the sleep-deprivation–induced changes in clock-gene expression.

Finally, we examined the expression of the activity-induced transcript Homer1a, which we previously identified as a core molecular marker of sleep pressure.6 In contrast with the clock genes, Homer1a was not affected by ADX and showed a robust increase in both experimental groups (Figure 3, bottom right panel). Thus, like delta power (see above), Homer1a also proved to be a reliable marker of time spent awake not affected by the corticosterone component of the HPA axis.

Adrenalectomy Reduces the Sleep-Deprivation–Dependent Changes in Brain Transcriptome

In addition to evaluating the aforementioned candidate genes that we and others had previously found to be implicated in the homeostatic regulation of sleep, we performed a transcriptome analysis to quantify for which forebrain transcripts the sleep-deprivation–induced changes in expression were modulated by ADX. Using an FDR of 5%, we identified 1,476 probe sets significantly affected by sleep deprivation in the brain of sham-operated mice, with 634 being increased and 842 being decreased (Figure 4A; Supplementary Table 1). Transcripts increased by sleep deprivation included synaptic plasticity genes (e.g., Homer1, Arc, Bdnf), genes encoding heat-shock proteins (Hsp1, −90, and −40), early response genes (Fos, Egr, Hif), potassium channel subunits (Kcnf1, Kcnq2, Kcnk1), and clock genes (Per1, Per2). Functional clustering of these probes highlights their involvement in transcriptional and in posttranslational processes, in cell cycle regulation, and in cell development (Supplementary Table 2). Among the transcripts decreased by sleep deprivation were RNA-binding proteins (Rbm and Cirbp), adhesion proteins (synaptotagmin [Sytl2, Syt3], Mcam, Cadm4), and regulatory enzymes of neurotransmitters (Maoa, Ache). These transcripts belong to a variety of functional categories, such as lipid, steroid, and cholesterol metabolism; protein synthesis and degradation, and cell-to-cell signaling and interaction (Supplementary Table 2). Many of the brain transcripts that changed their expression after sleep deprivation in the current study have been reported previously, (Supplementary Table 1) demonstrating the reproducibility of these finding in general and the validity of our present findings specifically.

Figure 4
Effect of adrenalectomy (ADX) on sleep deprivation (SD)-induced changes in the forebrain transcriptome. (A) Venn diagram showing the number of transcripts (probe sets) that increased (up) or decreased (down) with SD in sham-lesioned and ADX mice (false ...

Comparison of the ADX and sham-operated mice that were not sleep deprived demonstrated that ADX, per se, did not affect forebrain gene-expression levels; none of the 28,198 probe sets reached the 5% FDR (best adjusted P value 0.33; second best > 0.99). ADX did, however, alter the brain transcriptome response to sleep deprivation; the expression of only 469 transcripts (i.e., 68% fewer compared with shams) was significantly affected by sleep deprivation (FDR < 5 %) in ADX mice, 349 of which overlapped with those changed by sleep deprivation in sham-operated mice (Figure 4A, Supplementary Table 1). The 1,127 probes changed by sleep deprivation in sham animals but not in ADX are part of a variety of functional groups among which are genes coding for heat-shock proteins (Hspa4, Hspd1, Hspe1, Hsp90aa1, Dnaja1, Dnajb4), metabolic enzymes (Pdk4, Gpt2, Dgat2, Hmgcs1, Dhcr7-24, G6pc3, Ugdh), histone and histone-regulatory proteins, (Hdac4, Hdac6, Jhdm1d, H1f0, H2afj, Hist1h4i), and adhesion proteins (Pcdh10, Pcdhb11, Pcdhb13, Pcdhb15, Pcdhb20). To compare, in a quantitative way, the sleep-deprivation–responses between ADX and sham-operated mice, we contrasted the fold-change in the ADX group with that for the sham group for each of the 1,476 probe sets affected by sleep deprivation in sham-operated mice (Figure 4B). We observed that, for the vast majority of probe sets, the absolute sleep-deprivation response was reduced in ADX animals.

To further identify specific probe sets within the 1,476 that respond differently to sleep deprivation in ADX and sham-operated mice, we calculated an FDR for the interaction between the factors Sleep Deprivation and ADX. Since for only 18 probe sets an FDR < 5% was reached, we designed a data-mining approach to select the top affected genes. We used a range of FDR cutoffs to define growing lists of affected probe sets. Then, hierarchical clustering was applied to the gene-expression data for each of these probe-set lists to select a FDR cutoff at which non–sleep-deprived animals would segregate together while separating sleep-deprived ADX and sleep-deprived sham-operated mice (Supplementary Figure 2). The lowest FDR at which such segregation was achieved for the Sleep Deprivation-ADX interaction was 0.23, corresponding here with a nominal P value of 0.04. At this FDR, 260 probes were identified showing an interaction due to attenuation of both the increases and decreases in gene expression after sleep deprivation in ADX mice (Figure 4B and C, Supplementary Table 3). Functional clustering of these probes indicated that they take part in most of the molecular, cellular, and system-development functions modulated by sleep deprivation, including metabolic processes (protein, lipid, and carbohydrate metabolism), cell cycle, cell death, and cellular functioning (see Supplementary Table 2).

For 5 of those 260 transcripts, we verified whether the interaction could be confirmed using qPCR analysis (i.e., Sgk1, Pdk4, Xdh, Mertk, and Ppp1r1a). These genes were chosen to represent the diversity of pathways regulated by corticosterone, with an emphasis on metabolism. For instance, Sgk1, the expression of which is directly affected by corticosterone, is involved in cellular functions such as glucose transport,25 regulation of voltage-gated channels,26 and apoptotic processes.27 Also, Mertk is implicated in apoptosis.28 Pdk4 is an essential component of energy metabolism via its role in carbohydrate and lipid metabolic pathways,29 whereas Xdh is relevant to redox mechanism and response to hypoxia,30 and Ppp1r1a to glycogen metabolism.31 Except for Ppp1r1a, which was the only transcript among these 5 that was decreased by sleep deprivation, qPCR confirmed the interactions found for the microarray results (Figure 5).

Figure 5
Confirmation of the effect of adrenalectomy (ADX) on sleep deprivation (SD)-induced changes of selected transcripts. (A) Group-by-Condition interaction in gene expression in the microarray data was confirmed by quantitative polymerase chain reaction (qPCR) ...

Interestingly, among the 260 transcripts with an interaction, the effect of sleep deprivation was enhanced by ADX for 2 transcripts, contrasting all other transcripts in this list for which ADX reduced the effect of sleep deprivation (Figure 5B, Supplementary Table 3). These 2 transcripts, Ier5 and Midn, are involved in neurogenesis.32,33 Although qPCR analysis could not confirm the interaction for Ier5 (Figure 5B), the sleep-deprivation–induced increase in expression was significant in ADX mice only. This observation is consistent with the fact that corticosterone, besides playing a role as a transcriptional coactivator, can also act as a transcriptional corepressor.16 Similarly, among the probe sets for which a decrease after sleep deprivation was observed in sham-lesioned animals only, as well as the probe sets among which an increase was observed in ADX but not in sham mice (n = 684 and 66, respectively; Figure 4A, Supplementary Table 1), many are likely to be repressed by corticosterone. Conversely, transcripts increased by sleep deprivation in sham-mice only and decreased by sleep deprivation in ADX mice only (n = 443 and 54, respectively; Figure 4A, Supplementary Table 1) are likely to be under the control of corticosterone-mediated transcriptional activation. This indicates that the corticosterone surge not only amplifies the sleep-deprivation–induced decreases and increases in transcription, but may also mask transcripts relevant to sleep homeostasis.

Molecular Correlates of Sleep Homeostasis

The expression of 349 probe sets was significantly affected by sleep deprivation in both sham-lesioned and ADX mice (Figure 4A). As pointed out for Homer1a (see above), molecules modulated by sleep deprivation, independent of the activation of the HPA axis, might be part of the circuitry underlying sleep homeostasis or, at least, be used as molecular markers of sleep pressure, as reflected by the dynamics of delta power. Among these 349 probe sets are immediate/early response genes (Fosl2, Fos, Egr1, 3), specific heat shock protein genes (Hspa1a, Hspa5, Hspa8, Hspb1, Dnajb5, Dnajc3), RNA-binding protein genes (Rbm3, Rbm11, Rbm14), and plasticity and growth-factor genes (Homer1, Arc, Bdnf, Vgf, Vegfa). We verified whether the expression of this set of genes was similarly affected by a spontaneous period of wakefulness under undisturbed baseline conditions (ZT18) because, also under these conditions, delta power is high,3 whereas corticosterone levels are low (Figure 1A). Contrasting ZT18 versus ZT12 baseline data (i.e., just after and before the main period of sustained wakefulness) in D2 mice from our previous microarray study,6 we found that, among the 297 genes that were represented by the 349 probe sets and that were present on both microarray platforms, more than one-quarter (i.e., 78) were similarly affected by sustained spontaneous wakefulness (Supplementary Table 4; Supplementary Figure 3). These 78 genes can be regarded as core molecular components of the sleep homeostatic response, as exemplified by the activity-induced transcript Homer1a.

The functional clusters not covered by the transcripts for which a significant interaction was observed (Supplementary Table 2) are also likely to encompass molecular correlates of sleep pressure independent of corticosterone signaling. These clusters include protein synthesis and folding, RNA posttranscriptional modification, and several molecular pathways, such as endoplasmic reticulum stress pathway, ERK/MAPK signaling, and the Nrf2-mediated oxidative stress response. MiRNAs have been implicated in the posttranscriptional control of cellular proliferation, development, and differentiation.34 Indeed, we observed 10 miRNAs for which the expression changed with sleep deprivation in sham-lesioned mice (Supplementary Table 1), 5 of which increased (miR-410, −212, −29c, −29b-2, and −708) and 5 decreased (let-7e, miR-137, −22, −219-2, and −99a) with sleep deprivation. A recent study in the rat also reported significant changes in let-7e and miR-99a expression after sleep deprivation, but, contrary to our findings, let-7e was increased by sleep deprivation in hippocampus and hypothalamus.35 As in our study, miR-99a was decreased in prefrontal and somatosensory cortex and hypothalamus after sleep deprivation. Corticosterone appears to also target the transcriptional regulation of miRNAs because, of the 10 miRNA transcripts affected by sleep deprivation in sham-operated mice, only 3 reached transcriptome-wide statistical significance in ADX mice (miR-410, −212, and −29c; Supplementary Table 1), one of which, miR-29c, showed a significant interaction (Supplementary Table 3). In addition, we identified 1 miRNA, miR-151, that was increased by sleep deprivation in ADX mice (FDR 0.01 and 0.08 for ADX and sham, respectively). MiRNAs favor translational repression and/or destabilization of target mRNAs,34 and we therefore verified for miR-410, −212, −29c, and −151 whether the potential target transcripts of these miRNAs were among those affected by sleep deprivation. Among the 842 probes significantly decreased with sleep deprivation, we observed a significant enrichment of potential gene targets of miR-29c while among the 634 probes that increased with sleep deprivation, we observed a significant enrichment of potential targets of the 5′ direction of miR-151 and a tendency for enrichment (P = 0.06) of miR-212 targets (Supplementary Table 5). No significant enrichment was found for the potential targets of miR-410. Hence, miRNA function in sleep and wakefulness deserves attention both in the context of sleep homeostasis as well as in corticosterone signaling.


In this study, we demonstrated that the corticosterone response to enforced wakefulness depends on genetic background in mice. Subsequently, using ADX, we aimed at assessing the contribution of the sleep deprivation-associated increase in plasma corticosterone levels to the molecular and electrophysiological response to sleep loss. Our results indicate that corticosterone greatly amplifies the molecular changes in the brain, which previously were attributed to extended wakefulness per se, resulting in a two-thirds reduction in the number of transcripts significantly affected by sleep deprivation. In contrast, delta power, a widely used electrophysiological marker of sleep pressure, proved to reliably follow the sleep-wake distribution independently of the changes in corticosterone under both baseline and sleep-deprivation conditions. The analyses also enabled us to identify 78 transcripts that, similar to delta power, varied with sleep and waking independent of changes in corticosterone.

Adrenalectomy and Delta Power

Abolishing the sleep-deprivation–dependent surge in corticosterone through ADX did not rescue the blunted delta power rebound in D2 mice. Although we cannot rule out other secondary effects of this intervention, this observation suggests that the increase in corticosterone does not contribute to the level of delta power reached after sleep deprivation. This result is consistent with that of a comparable study performed in rats36 and with the observation in mice that the duration of both spontaneous and enforced bouts of wakefulness equally predict delta power in subsequent sleep.3 As shown here, ADX eliminated the stress-induced increase in corticosterone secretion; ADX does, however, not eliminate the endocrine stress response at other levels of the HPA axis, such as elevated CRH (corticotrophin-releasing hormone) and ACTH (adrenocorticotropic hormone) levels that might have contributed to the strain-specific sleep-deprivation–dependent changes in delta power. Although CRH and ACTH tend to modulate sleep duration, in particular that of REM sleep,37,38 the effect of CRH on delta power seems minor.38 Overall, the data indicate that the strain differences in the delta-power rebound after sleep deprivation must be due to other (genetic) factors independent of the corticosterone component of the HPA-mediated stress response.

Adrenalectomy and Clock Genes

Numerous studies point to a close interrelationship between corticosterone signaling and Per expression. Per1 transcription, in particular, has been shown to be directly controlled by corticosterone through glucocorticoid responsive elements (GRE) in its promoter.17 Our present results suggest that most of the sleep-deprivation–dependent increase in Per1 expression is mediated through corticosterone signaling and not related to the increased time spent awake per se. Although Per2 expression seems less affected by stress and corticosterone,39 PER2 protein levels were, nonetheless, found to be modulated by corticosterone,18 and, recently, a functional GRE sequence was also identified for Per2.40 Based on observations made in Npas2 knockout mice24 and Cryptochrome1,2 double- knockout mice41 that showed a reduced and an augmented increase, respectively, in Per2 after sleep deprivation compared with wild-type mice, we concluded that the sleep-deprivation–dependent changes in Per2 were mediated, in part, through the negative feedback loop made up of clock genes that underlie circadian-rhythm generation.7 Therefore, the reduced increase in Per2 expression in ADX mice suggests that sleep deprivation activates both clock-gene and corticosterone-signaling pathways and that both pathways, in turn, affect Per2 expression. These two closely associated pathways are both implicated in metabolism and are essential to cope with and anticipate energy demands.42,43 Because extended wakefulness is thought to represent a metabolic challenge to the brain, the sleep-wake–related changes in Per2 in the forebrain underscore the notion that this molecule plays a role in homeostatic sleep need.7

Although our study focused on the sleep-deprivation–induced changes in corticosterone, it should be noted that HPA activation is only one of several mechanism affecting circulating corticosterone levels. The daily changes observed under undisturbed baseline conditions are controlled by various factors, including suprachiasmatic nucleus output, light, and circadian oscillations intrinsic to the adrenal.44,45 Also, these baseline variations in corticosterone, the amplitude of which approaches those reported here for the effect of sleep deprivation,45 are accompanied by changes in clock-gene expression, and it has been proposed that increases in circulating corticosterone levels set the phase of circadian rhythms in the periphery.44 Given the important role of corticosterone in normal physiology and in gene expression, it is surprising that the absence of circadian changes in corticosterone in ADX mice did not affect the baseline expression of any of the transcripts, at least at this time of day when corticosterone was low in both experimental groups. Because corticosterone was supplemented in the experiment assessing delta power, levels of circulating corticosterone are likely to have followed the drinking rhythm.18

Adrenalectomy and the Brain Transcriptome

Corticosterone can bind and activate mineralocorticoid and glucocorticoid receptors in the brain. Both are highly expressed in forebrain areas such as the hippocampus and amygdala, which are involved in emotional regulation and in learning and memory processes.46 These nuclear receptors, when ligand activated, can initiate transcription by binding to specific DNA sequences in the promoter regions of target genes or, by interacting with other transcription factors, can decrease transcription.16,46 Numerous transcripts in the brain, mainly concerning metabolism and neuronal function,46 are affected by this signaling pathway. The importance of corticosterone in gene regulation is compellingly illustrated by our microarray results because the transcriptional response associated with sleep deprivation in the forebrain was greatly reduced after ADX. Although addressing a different question, the extensive 68% reduction in the number of transcripts affected by sleep deprivation is reminiscent of the 60% decrease in the number of transcripts that maintained circadian rhythmicity in the liver of ADX mice.39 Similarly, we have previously established that 80% of the brain transcripts that were considered to be circadian because expression changed according to time of day were, in fact, sleep-wake driven.6 These studies illustrate the necessity of distinguishing between primary and consequent effects (e.g., sleep loss and corticosterone, or circadian and sleep-wake driven, respectively), especially when the influence of the latter exceeds those of the former.

The Molecular Wiring of Sleep Homeostasis

We assembled an exclusive list of 78 sleep homeostatic transcripts that responded to sleep loss independent of corticosterone and time of day. This list includes an important subset of immediate/activity-dependent genes linked to neuronal plasticity and memory (e.g., Fos, Arc, Egr1, Egr3, Nr4a3),4749 which corroborates the proposed direct involvement of plastic neuronal changes in sleep homeostasis.1 Also, genes associated with the ERK/MAPK pathway of intracellular signaling, which is closely linked to the immediate early gene response, are well represented in the 78 transcripts (e.g., Dusp6, Dusp1, Dusp4, Trib2). Maret et al.6 proposed a neuroprotective function for sleep, based on the role of Homer1a in intracellular calcium homeostasis. Also Npas4 and Nr4a1, which feature among our set of 78, were recently found to be part of a gene program involved in neuroprotection, which is activated upon synaptic activity-induced calcium signaling,50 further supporting such a role for sleep. Moreover, other transcripts on our list, such as Egr1, Fos, and Nr4a3, have also been involved in the molecular neuroprotective response triggered by ischemia,51 as is the case for Hspa5, Xbp1, Hsp90b1, and Stip1, which are responsive to cellular stress and implicated in the unfolded protein response,5254 and Bcl2, a well-known apoptotic mediator.55 Overall, these findings confirm that extended wakefulness activates molecular pathways associated with the preservation of neuronal integrity and the modulation of neuronal connections.

Our list also contains Nfil3 (or E4bp4), which drives circadian gene expression and is a molecular partner of PER2,56 providing additional support for an involvement of specific clock components in homeostatic sleep regulation. Furthermore, in addition to the presence of RNA-binding proteins (Cirbp, Rbm3, Rbm11) in the list of homeostatic transcripts, our miRNA findings confirm a role for RNA posttranscriptional processing in sleep homeostasis.35 Of the 10 miRNAs that changed with sleep deprivation in sham-operated mice, only miR-410, −212, and −29c did so independently of ADX. Thus, as for the entire transcriptome, again a two-third reduction occurred, indicating an important role for corticosterone in miRNA expression, which has not been demonstrated previously in vivo. Importantly, among the miR-212 potential target genes, 5 feature on our list of homeostatic genes (i.e., Npas4, Nfil3, Homer1, Ier5, and Hspa1a). The relevance of miR-212 to sleep homeostasis is a lead we are currently following up on. Thus, in addition to their relevance for circadian rhythms,57,58 our findings, which need to be confirmed using more-specific miRNA extraction protocols, show an additional role for miRNA in sleep regulation directly through sleep homeostasis.


We report on the central relationship between the molecular and physiological markers of sleep need and their response to one component of the stress response in mice. Also, in humans, sleep restriction can increase the level of the glucocorticoid cortisol.11 Our EEG findings suggest that, at least for acute forms of stress, this effect does not have an important impact on the recuperative value of sleep, as indexed by delta power. Glucocorticoids mediate most of the central effects of stress, which is well documented for the hippocampus, where it affects energy metabolism, memory, synaptic plasticity, dendritic morphology, neurogenesis, and neurotoxicity.59,60 Several of these effects, such as the modulation of energy metabolism, the changes in synaptic plasticity, and the changes in mediators of cell death, have also been observed after sleep deprivation, where they have been attributed to sleep loss.5 At the molecular level, our findings support a large contribution of glucocorticoids, especially regarding the general regulation of various metabolic routes, an effect that has not been directly assessed previously. The analyses allowed for the identification of those transcripts that respond to sleep loss independent of glucocorticoids and time of day and suggest that sustained wakefulness activates a neuroprotective signaling pathway likely to be of direct relevance for sleep function.


This was not an industry supported study. The authors have indicated no financial conflicts of interest.


We are thankful to Sabine Dhir, Brice Petit, and Yann Emmenegger for technical help. We also thank Sophie Wicker, Otto Hagenbuchle, and Keith Harshman (Lausanne Genomic Technologies Facility) for the microarray profiling study.

This work was supported by the University of Lausanne, Canton de Vaud (Switzerland), the National Institutes of Health (grant MH67752), the Swiss National Science Foundation (grants 108478 and 111974), and a fellowship from the National Sciences and Engineering Research Council of Canada to VM.


A commentary on this article appears in this issue on page 1131.

Supplementary Figures and Tables for Separating the Contribution of Glucocorticoids and Wakefulness to the Molecular and Electrophysiological Correlates of Sleep Homeostasis

Supplementary Figure 1

Total sleep time observed in control condition (before surgery) and after adrenalectomy (ADX) or sham-lesion in D2 mice. A) Time course of total sleep time (NREM and REM sleep) averaged per hour during the 24h baseline, during sleep deprivation (SD), and 18h of recovery. B) Total sleep time calculated per 12h light or dark period during baseline in the three experimental groups. Time course of total sleep time and total sleep time per 12h did not differ among control (n = 16), ADX (n = 7), and sham-lesioned (n = 9) mice. See Figure 2C for the effect of SD on NREM sleep.

Supplementary Figure 2

2-Hierarchical clustering, using Ward's linkage method, of all 26 individual mice based on a variable number of probe sets displaying a signifcant interaction between the effects of ADX and of SD. This clustering approach was performed to delineate the genes for which the SD effect on expression was altered by ADX. In each graph an increasing FDR significance threshold was used (varying from 0.1 to 0.6; upper left - lower right) to asses the interaction. The lowest FDR threshold with which the Sham-SD, ADX-SD, and control (CT) groups could be separated was 0.23. This cut-off was subsequently used to evaluate probe sets for which a significant interaction between Group (sham vs. ADX) and Condition (CT vs. SD) was found among the 1476 probe sets affected by SD (See Supplementary Table 3). Using this approach, a significant interaction was found for 260 probe sets (see data points marked green in Figure 4B and the heatmap of Figure 4C). Pearson correlation was used as a distance metric for clustering analysis. Hierarchical clustering, using Ward's linkage method, of all 26 individual mice based on a variable number of probe sets displaying a signifcant interaction between the effects of ADX and of SD. This clustering approach was performed to delineate the genes for which the SD effect on expression was altered by ADX. In each graph an increasing FDR significance threshold was used (varying from 0.1 to 0.6; upper left - lower right) to asses the interaction. The lowest FDR threshold with which the Sham-SD, ADX-SD, and control (CT) groups could be separated was 0.23. This cut-off was subsequently used to evaluate probe sets for which a significant interaction between Group (sham vs. ADX) and Condition (CT vs. SD) was found among the 1476 probe sets affected by SD (See Supplementary Table 3). Using this approach, a significant interaction was found for 260 probe sets (see data points marked green in Figure 4B and the heatmap of Figure 4C). Pearson correlation was used as a distance metric for clustering analysis.

Supplementary Figure 3

3-Scatter plot of the fold-change in expression induced by the sleep deprivation (SD) [log(SD/control)] in sham-lesioned animals plotted against the fold-change in expression between ZT18 and ZT12 in DBA/2J mice during baseline conditions [log(ZT18/ZT12)] (analysis of previously published micro-array data from Maret et al., 2007). The 297 gene sequences representing the 349 probe sets that were significantly modified by SD in both sham and ADX mice in the present study (Supplementary Table 1 and Figure 4A) were compared to the Maret et al. (2007) study to verify whether they were equally affected by a comparable extended period of spontaneous wakefulness. Among the 297 genes represented, 78 genes showed a significant and similar change between ZT18 and ZT12 (green symbols, see Supplementary Table 4). The 45 degree line of equality is indicated with a dashed red line.

Supplemental Table 1
Probes significantly affected by sleep deprivation (SD) in sham-operated D2 mice (1476 probe sets). The FDR of 5% for the ANOVA with factor SD was taken to adjust nominal P-values (Adj. P value). The direction indicates whether SD increased (up) or decreased ...
Supplemental Table 2
Functional clustering of probe sets significantly affected by sleep deprivation (SD) in sham-operated D2 mice (Ingenuity Pathways Analysis; Ingenuity Systems). Indicated for each functional cluster are the range of P values based on all 1476 probes significantly ...
Supplemental Table 3
Listing of the 260 probe sets showing Group (sham vs. ADX) by Condition (control vs. SD) interaction (FDR > 0.23; see Supplementary text and Supplementary Figure 1) among the 1476 probes affected by sleep deprivation (SD) (see Supplementary Table ...
Supplemental Table 4
List of the 78 genes showing a significant effect of sleep deprivation (SD) in both sham and ADX mice of the present micro-array and a significant effect of spontaneous wakefulness (from an analysis of the difference between baseline ZT18 and ZT12 micro-array ...
Supplemental Table 5
List of probe sets affected by SD (see Supplementary Table 1) that are considered potential targets of the microRNAs affected by sleep deprivation (SD) in both sham and ADX animals. Target genes among the probe sets that were either decreased (down) or ...
Supplemental Table 6
Sequences of primers and probes used for qPCR.


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