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Brain, Behavior, and Immunity xxx (2016) xxx–xxx
Contents lists available at ScienceDirect
Brain, Behavior, and Immunity
journal homepage: www.elsevier .com/locate /ybrbi
Full-length Article
Repeating patterns of sleep restriction and recovery: Do we get
usedto it?
http://dx.doi.org/10.1016/j.bbi.2016.06.0010889-1591/� 2016
Elsevier Inc. All rights reserved.
⇑ Corresponding author.E-mail address: [email protected]
(M. Haack).
Please cite this article in press as: Simpson, N.S., et al.
Repeating patterns of sleep restriction and recovery: Do we get
used to it?. Brain Behav. I(2016),
http://dx.doi.org/10.1016/j.bbi.2016.06.001
Norah S. Simpson a, Moussa Diolombi b, Jennifer Scott-Sutherland
b, Huan Yang b, Vrushank Bhatt b,Shiva Gautamb, Janet Mullington b,
Monika Haack b,⇑aDepartment of Psychiatry and Behavioral Sciences,
401 Quarry Rd., Stanford University School of Medicine, Stanford,
CA, United StatesbDepartment of Neurology, Beth Israel Deaconess
Medical Center/Harvard Medical School, DANA-727, 330 Brookline
Ave., Boston, MA 02215, United States
a r t i c l e i n f o a b s t r a c t
Article history:Received 4 April 2016Received in revised form 18
May 2016Accepted 2 June 2016Available online xxxx
Keywords:Sleep
restrictionStressInflammationCortisolSubjective
Despite its prevalence in modern society, little is known about
the long-term impact of restricting sleepduring the week and
‘catching up’ on weekends. This common sleep pattern was
experimentally modeledwith three weeks of 5 nights of sleep
restricted to 4 h followed by two nights of 8-h recovery sleep. In
anintra-individual design, 14 healthy adults completed both the
sleep restriction and an 8-h control condi-tion, and the subjective
impact and the effects on physiological markers of stress
(cortisol, the inflamma-tory marker IL-6, glucocorticoid receptor
sensitivity) were assessed. Sleep restriction was not perceivedto
be subjectively stressful and some degree of resilience or
resistance to the effects of sleep restrictionwas observed in
subjective domains. In contrast, physiological stress response
systems remain activatedwith repeated exposures to sleep
restriction and limited recovery opportunity. Morning IL-6
expressionin monocytes was significantly increased during week 2
and 3 of sleep restriction, and remainedincreased after recovery
sleep in week 2 (p < 0.05) and week 3 (p < 0.09). Serum
cortisol showed a signif-icantly dysregulated 24 h-rhythm during
weeks 1, 2, and 3 of sleep restriction, with elevated
morningcortisol, and decreased cortisol in the second half of the
night. Glucocorticoid sensitivity of monocyteswas increased, rather
than decreased, during the sleep restriction and sleep recovery
portion of eachweek. These results suggest a disrupted interplay
between the hypothalamic-pituitary-adrenal andinflammatory systems
in the context of repeated exposure to sleep restriction and
recovery. The observeddissociation between subjective and
physiological responses may help explain why many
individualscontinue with the behavior pattern of restricting and
recovering sleep over long time periods, despitea cumulative
deleterious physiological effect.
� 2016 Elsevier Inc. All rights reserved.
1. Introduction
Patterns of restricting sleep during the week and ‘catching
up’over the weekend are prevalent in modern society (Hansen et
al.,2005; Monk et al., 2000; National Sleep Foundation, 2010;
Tsuiand Wing, 2009; Wing et al., 2009). These sleep patterns are
notcommonly thought of as deleterious; however, there is
limitedempirical evidence to support this belief. Given the wealth
of accu-mulated evidence that insufficient sleep is associated with
ele-vated health risks (e.g., cardiovascular disorders (Grandner et
al.,2013), metabolic disorders (Knutson et al., 2007), and chronic
painconditions (Finan et al., 2013)), gaining a better
understanding ofthe impact of these common sleep patterns is
essential.
Sleep loss can be conceptualized a physiological stressor,
withboth subjective (psychological) and physiological
effects(described further below). The multiple systems involved in
thephysiologic stress response are homeostatic and tightly
inter-related (Almawi et al., 1996; de Kloet, 2000) and include
thesympatho-adrenal, the hypothalamic-pituitary-adrenal (HPA),
aswell as the inflammatory system. Inflammatory cytokines serveas
chemical messengers and are negatively controlled by cortisol,a
glucocorticoid (GC) that is the main output hormone of theHPA axis
(reviewed in Chrousos, 2009). Impaired GC sensitivityhas been
reported in response to various acute and chronic stres-sors
(Herman et al., 1995; Miller et al., 2002; Stark et al., 2001),and
GC sensitivity is one possible mechanism by which observedincreases
in inflammatory markers can be explained.
The HPA system is perhaps the most studied stress
responsesystem, and is known to typically habituate when faced
withrepeated or ongoing stressors (Grissom and Bhatnagar,
2009).
mmun.
http://dx.doi.org/10.1016/j.bbi.2016.06.001mailto:[email protected]://dx.doi.org/10.1016/j.bbi.2016.06.001http://www.sciencedirect.com/science/journal/08891591http://www.elsevier.com/locate/ybrbihttp://dx.doi.org/10.1016/j.bbi.2016.06.001
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2 N.S. Simpson et al. / Brain, Behavior, and Immunity xxx (2016)
xxx–xxx
However, sleep loss is a unique stressor because it is a
biologicalresource necessary for regulation of multiple
physiological sys-tems, including the stress response system
(Hamilton et al.,2007; McEwen, 2006). Further, in extreme cases,
sleep is necessaryfor survival itself (Everson et al., 1989;
Montagna et al., 1995). Noprior research has examined whether
humans can adapt to chronicpatterns of insufficient sleep and
limited recovery, or studied theimpact of this common real-world
pattern on stress-response sys-tems. As described below, the impact
of single episodes of sleeploss and (to a lesser extent) recovery
sleep has been tested, how-ever it remains unknown whether these
results remain true whenpatterns of restricted sleep and recovery
become chronic.
Within single episodes of experimental sleep loss,
subjectiveratings of sleepiness, positive mood, and self-reported
physicalfunctioning appear to show response stabilization, or
acclimation.For example, subjective experiences of pain (Haack
andMullington, 2005) and sleepiness (Van Dongen et al., 2003)
stabi-lize after a few days of sleep restriction or sleep
deprivation (ordeteriorate more slowly), despite ongoing sleep
loss. On a physio-logical level, multiple markers of the stress
system have beenfound to increase following a single episode of
sleep loss, includingcortisol (Balbo et al., 2009; Guyon et al.,
2014) and the inflamma-tory marker interleukin [IL]-6 (Haack et
al., 2007; Irwin et al.,2006; Pejovic et al., 2013; van Leeuwen et
al., 2009; Vgontzaset al., 2004). Although habituation to acute
stressors is a key fea-ture of the HPA system (Grissom and
Bhatnagar, 2009), it isunknown whether this classic pattern of
habituation can beapplied to the physiological stress of repeated
exposures to sleeploss with limited recovery sleep, given that
sleep loss is a uniquephysiological stressor.
Little is known about the impact of repeated episodes of
sleeploss or the role of recovery sleep. To our knowledge, the
currentstudy protocol tests the longest model of chronic sleep
restrictionto date. Everson and colleagues have conducted studies
of repeatedexposure to sleep loss and recovery in an animal model,
and havedocumented changes in metabolic indices (weight, food
intake),and pathological organ and bone changes (Everson and
Szabo,2009, 2011). Recovery from sleep loss has been rarely
studied,but using a five night sleep restriction/two night recovery
protocol,van Leeuwen and colleagues showed that IL-6 mRNA
levelsremained elevated after two nights of recovery sleep
(vanLeeuwen et al., 2009). These data provide preliminary support
that‘catching-up’ on sleep over the weekend might be insufficient
torestore stress-response systems, and contribute to
ongoingresponses to repeated exposure to sleep loss over time.
These lim-ited data highlight a critical gap in our understanding
of conse-quences of insufficient sleep, as it is the real-world
experiencesof repeated episodes of sleep loss and limited recovery
sleep thatare most likely to have a long term impact on health.
This study modeled real-world sleep-wake patterns of
sleeprestriction and recovery in the laboratory environment to
investi-gate effects on multiple stress systemmarkers, using an
intensifiedmodel of sleep restricted to four hours of sleep on
weekdays andextended to eight hours on weekends. This amplification
of themagnitude of difference between weekdays/weekends was
chosenin part due to the aim of assessing the impact of these
patternsunder highly controlled experimental conditions that can be
main-tained for a period of weeks, rather than the months or years
thatadults often will maintain these milder patterns of sleep
restrictionand recovery in the real world.
Based on previous research, we hypothesized that there wouldbe a
response stabilization or habituation across repeated episodesof
sleep loss in subjective domains, but poor habituation and
anincomplete recovery in physiological domains. If true, these
find-ings could help explain why patterns of inadequate sleep
persist,namely, because there would be no perceived negative impact
of
Please cite this article in press as: Simpson, N.S., et al.
Repeating patterns of s(2016),
http://dx.doi.org/10.1016/j.bbi.2016.06.001
these behavior patterns. Additionally, this study was
specificallydesigned to extend previous research demonstrating that
sleep lossresults in increases in serum or plasma IL-6 (Haack et
al., 2007;Irwin et al., 2006; Pejovic et al., 2013; van Leeuwen et
al., 2009;Vgontzas et al., 2004) by focusing on monocytes, and
whetherthe expected increased expression of inflammatory
mediatorscan be explained by changes in the sensitivity of
monocytes tocortisol.
2. Methods
2.1. Experimental model
The hypothesis was tested using a sleep restriction
conditionconsisting of three weeks of a repeating pattern of five
nights ofsleep restricted to 4 h/night (0300–0700 h) followed by
two nightsof recovery sleep with 8 h/night (2300–0700 h). This
model wasdesigned to mirror commonly observed patterns of
moderatelyrestricting on weeknights and recovering sleep on weekend
nightsthat often occur in the general population for periods of
months oryears (National Sleep Foundation, 2010), albeit with an
amplifiedsleep restriction pattern on weeknights (see Fig. 1). This
amplifiedsleep restriction period was designed to maximize the
potentialthat the effects of what are often much longer periods of
mildersleep restriction and recovery that occur in the real world
couldbe captured in a relatively short three-week in-laboratory
experi-mental protocol. The sleep control condition consisted of
threeweeks with a nightly sleep opportunity of 8 h. In an
intra-individual randomized balanced design, participants
underwenttwo 25-day in-hospital stays (restricted sleep condition
and sleepcontrol condition) separated by more than two months. Each
25-day stay started with an adaptation and a baseline day,
followedby three weeks of either the repeated exposure to sleep
restric-tion/recovery or control sleep, and ended with an
additional nightof full sleep (totaling 25 days).
2.2. Participants
This study was approved by the Institutional Review Board forthe
Protection of Human Subjects at the Beth Israel DeaconessMedical
Center (BIDMC). Participants were recruited via commu-nity
advertisements. Seventeen healthy young women and menwere studied.
Fourteen participants completed both 25-day-in-hospital conditions;
three participants could only complete oneof the two
25-day-in-hospital conditions due to change in work/family-related
requirements (see Fig. 2).
Participants were between the ages of 18–35 years, had a
bodymass index (BMI) between 18.5 and 30 kg/m2, a daily sleep
dura-tion between 7 and 9 h (verified by sleep diary data over a
2-week period), began their habitual sleep period within one hourof
11 pm (to ensure normal entrainment) and had blood chemistrylevels
within the normal range. Female participants were eligible ifthey
had regular menstrual cycles and no significant discomfortduring
pre-menses/menses. Exclusion criteria included presenceor past
history of major medical problems, psychiatric disordersor sleep
disorders. Additional exclusion criterion included
preg-nant/nursing status, regular medication use other than oral
contra-ceptives, and donation of blood or platelets three month
prior to orin-between study stays.
2.3. Study protocol
2.3.1. Screening & randomizationParticipants were initially
screened over two visits to the hospi-
tal and were evaluated by a study physician for the
exclusion
leep restriction and recovery: Do we get used to it?. Brain
Behav. Immun.
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1 2 3 8 10 15 17 22 24
Time of D
ay
23
01
03
05
07
09
11
13
15
17
19
21
Week 1 Week 2 Week 3 Day
Participant arrival/discharge Sleep period (8h or 4h)
Heavy recording days (blood, urine, PSG)
IL-6 expression. in monocytes, GC sensitivity
Fig. 1. Study protocol: Repeated exposure to sleep
restriction-recovery patterns. In the control condition,
participants had a sleep opportunity of 8 h every day.
N.S. Simpson et al. / Brain, Behavior, and Immunity xxx (2016)
xxx–xxx 3
criteria described above. Two weeks before entering each
25-dayin-hospital stay, participants were asked to follow the study
sleepschedule (11 pm–7 am), which was verified by sleep log data.
Theweek prior to the second 25-day visit, blood tests used at the
initialscreening were repeated to ensure values are in the normal
range.Participants were randomized to the order of experimental
condi-tions (sleep restriction or control) on the first day of the
first 25-day hospital stay. An independent statistician prepared
envelopeswith randomization codes, one of which was opened by a
seniorstaff member prior the first hospital stay.
2.3.2. Research environmentDuring the two 25-day in-hospital
stays (Fig. 1), participants
stayed in a private or semi-private room in the Clinical
ResearchCenter (CRC) at BIDMC. Intensive physiological recordings
wereconducted on seven out of the 25 days: on the baseline night,
everyfifth day of restricted/control sleep and every second night
ofrecovery/control sleep in each of the three weeks. These
intensivemeasurement periods included PSG recordings and frequent
bloodsampling though an intravenous catheter across 24 h.
Subjectivewell-being assessments were also collected on
computerizedvisual analog scales every four hours throughout waking
periods.
During the sleep restriction nights, the sleep opportunity
wasfrom 0300 to 0700 h; however, participants had to remain in
bedin a semi-supine position during the wakeful nighttime
periods(2300–0300 h) in order to limit differences in postural and
phys-ical activity inputs across all study nights and conditions.
Lightlevels were less than 40 lx during wakeful nighttime
periods(2300–0300 h). During daytime periods (0700–2300 h),
partici-pants had access to both artificial and natural light
sources.Throughout both 25-day stays, participants were maintained
ona balanced diet (NA+ and K+ controlled) and regimented
fluidintake in order to maintain body weight/composition
throughoutthe study. Meals and fluids were served at standardized
hours. Toprevent sedentary conditions and maintain constant
activitylevels, participants had scheduled walks (5–10 min each)
withinthe CRC every other hour throughout the daytime periods ofthe
protocol (between 0700 and 2300 h). On non-intensiverecording days,
participants had an additional longer walk ofapproximately 30 min
that could take place outdoors. Participantswere also encouraged to
follow their pre-study exercise habits
Please cite this article in press as: Simpson, N.S., et al.
Repeating patterns of s(2016),
http://dx.doi.org/10.1016/j.bbi.2016.06.001
through an opportunity on the non-intensive recording days
tovisit the hospital gym facilities. Room temperature was
adjustedto each participant’s comfort level during the first two
adaptationdays, and the same daytime temperature was kept
throughoutthe remaining days of the protocol. Nighttime
temperature(2300–0700 h) was set 2 �C lower than daytime
temperature. Par-ticipants were allowed to have visitors during
daytime periods, aswell as have access to email and phone, in order
to minimize dis-ruptions to their social networks and prevent
social isolation.During all waking periods a research assistant
accompanied par-ticipants in order to ensure adherence to the study
protocol andprocedures, as well as to engage participants in social
activitiessuch as board/video games or talking, as needed.
2.3.3. Measurements2.3.3.1. Polysomnographic recording (PSG).
Sleep was recorded usingthe Embla system N7000 (Medcare US,
Buffalo) on seven intensiverecording days of each 25-day study run
(at baseline, every fifthand seventh day of each of the three
weeks). The PSG montage fol-lowed standard criteria and sleep
electroencephalography wasmanually stage-scored on a 30 s epoch
basis (American Academyof Sleep Medicine, 2007). All recordings
were scored by the samesleep technician.
2.3.3.2. Blood sampling. On the seven intensive recording days
ofeach 25-day study run, blood was drawn at 2-hourly intervalsusing
an indwelling 20-gauge forearm catheter. During sleepopportunities,
a long line was attached to the catheter and bloodcollection was
performed from an adjacent anti-chamber withoutdisrupting the
participant’s sleep. The total amount of blood takenover each
25-day protocol did not exceed 550 ml.
2.4. Stress response system measures
2.4.1. CortisolCortisol was measured in serum collected every
two hours on
the seven intensive recording days using an
electrochemilumines-cence immunoassay (ECLIA, Labcorp.com).
According to thecompany, intra-run and inter-run precision are 1.2%
and 1.6%,respectively.
leep restriction and recovery: Do we get used to it?. Brain
Behav. Immun.
http://dx.doi.org/10.1016/j.bbi.2016.06.001
-
Slee
py
(0-1
00 u
nits
) Ef
fort
to d
o an
ythi
ng
(0-1
00 u
nits
) St
ress
ed
(0-1
00 u
nits
)
Day
Repeated exposure of restricted sleep Control sleep
Fig. 2. Ratings of ‘Sleepy’, ‘Effort to do anything’, and
‘Stressed’ across therepeated exposure to sleep
restriction-recovery patterns. Data present estimatedmean ± SEM
based on mixed model analysis. *p < 0.05 between conditions.
4 N.S. Simpson et al. / Brain, Behavior, and Immunity xxx (2016)
xxx–xxx
Please cite this article in press as: Simpson, N.S., et al.
Repeating patterns of s(2016),
http://dx.doi.org/10.1016/j.bbi.2016.06.001
2.4.2. Stimulated IL-6Stimulated IL-6 was measured in vitro as
the capacity of mono-
cytes to express IL-6, using the 1130 h blood sample on each of
theseven intensive recording days. Whole blood was stimulated
withlipopolysaccharide (LPS) from Escherichia coli 0127-B8 (LPS 100
pg/ml, Sigma-Aldrich), and then brefeldin A (10 lg/ml,
Sigma-Aldrich)was added to the sample, which was incubated for 4 h
at 37 �C in a5% CO2 atmosphere. Following fixation and
permeabilization pro-cedures (IntraprepTM Permeabilization reagents
[Beckman Coulter]),fluorescence-conjugated antibodies were added
(CD14 APC, CD45KrO [both Beckman Coulter], IL-6 PE [BD Bioscience])
and samplesincubated for 15 min at room temperature in the dark.
Sampleswere vortexed, washed with phosphate-buffered saline
solution(PBS 1X, Sigma Aldrich), and stored at 2–8 �C in the dark
after re-suspension in 500 ul of PBS containing 0.5% formaldehyde.
Prepa-rations were analyzed within 24 h using a GalliosTM flow
cytometer(Beckmann-Coulter) at the Flow Cytometry Core at BIDMC,
and100,000 events were acquired. Percentage of IL6-positive
mono-cytes (LPS-stimulated and spontaneous) were quantified
usingKaluza� Flow Analysis software (Beckmann Coulter).
2.4.3. Unstimulated IL-6The same procedures were applied to a
whole blood sample
that was not stimulated with LPS.
2.4.4. Glucocorticoid (GC) sensitivity of
monocytesGlucocorticoid (GC) sensitivity of monocytes was
determined
by the capacity of the synthetic glucocorticoid
dexamethasone(DEX) to suppress IL-6 expression in monocytes, using
the 1130 hblood sample on each of the seven intensive recordings
days.Whole blood was stimulated with LPS (see above), and then
differ-ent concentrations of DEX (25, 50, 100, 200, and 400 nM;
Sigma-Aldrich) as well as brefeldin A were added to the samples,
whichthen underwent the same procedures as described above. For
sta-tistical purposes, IL-6 suppression curves were calculated
aschange from monocytic IL-6 expression without DEX. In
addition,area under the curve (AUC) was computed for each IL-6
suppres-sion curve according to methods described by Pruessner and
col-leagues (Pruessner et al., 2003). For this analysis, samples
withdifferent DEX concentrations were first calculated as change
frombaseline (i.e., sample without DEX), and then computed as
AUC.
2.4.5. Subjective measuresSubjective measures were assessed
every four hours during the
waking periods of the protocol. Participants were asked to rate
theintensity of various well-being items using computerized
visualanalogue scales (AsWin, programmed by Martin Rivers &
Associ-ates). The VAS set used in the current study contained items
fromthe Deactivation Activation Check List (Thayer, 1978) and
scaleshave been used in our previous studies (Haack and
Mullington,2005; Haack et al., 2009). The test battery required
approximatelyfive minutes per administration. Ratings of ‘Sleepy’,
‘Effort to doanything’, and ‘Stressed’ were aggregated across the
daytime peri-ods of each study day for statistical analysis.
2.5. Statistics
Linear mixed models were used to analyze the data, with
condi-tion (repeated sleep restriction vs. control sleep) and study
day(baseline, fifth and seventh day of each of the three weeks) as
fixedfactors, and participants and participants � day as random
factors.For variables that were also repeated within a study day
(e.g.,cortisol measured every two hours, IL-6 suppression measured
atvarious concentrations of DEX at each recording day), time
ofday/concentration were also entered as additional fixed
factors.The baseline day was used as a covariate in order to
account for
leep restriction and recovery: Do we get used to it?. Brain
Behav. Immun.
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N.S. Simpson et al. / Brain, Behavior, and Immunity xxx (2016)
xxx–xxx 5
differences at study start. Accordingly, data in graphs are
depictedas estimated means from mixed model analysis. Since
baseline daywas used as covariate, interpretation of the
interaction as well asmain condition effects is considered
appropriate and are presentedif significant. Physiological stress
outcome measures were: (1)serum cortisol assessed every two hours
during intensive record-ing days, (2) IL-6 positive monocytes
(LPS-stimulated and unstim-ulated), assessed once per intensive
recording day at 11:30 h, and(3) GC sensitivity of monocytes,
measured as IL-6 suppressioncurves at various doses of DEX once per
intensive recording dayat 11:30 h, and calculated as AUC (Pruessner
et al., 2003). Subjec-tive outcome measures were ratings of
‘Sleepy’, ‘Effort to do any-thing’, and ‘Stressed’, which were
aggregated to a single daytimemean (0700–2300) across each of the
seven intensive recordingdays.
3. Results
Of the 17 participants randomized, 14 completed both
sleeprestriction and sleep-control laboratory stays. Table 1
presentsbaseline characteristics of the participants who were
randomizedand are included in analyses. On average, there were144 ±
23 days (4.8 ± 0.8 months) between laboratory stays. Dataand
statistical analyses are described below; Supplemental Table
1presents summary data from subjective and physiological
stressmarkers across repeated patterns of sleep restriction
andrecovery.
3.1. Subjective well-being responses
Fig. 2 presents the subjective well-being responses to
therepeated exposure of sleep restriction-recovery patterns.
Mixedmodel revealed a significant condition effect (p < 0.05)
for rat-ings of ‘Sleepy’ and ‘Effort to do anything’, but not for
‘Stressed’.Values for ‘Sleepy’ and ‘Effort to do anything’
significantlyincreased during the sleep restriction days of each
week, andalmost completely returned to baseline values during
intermit-tent recovery sleep nights (no significant difference
comparedto baseline). When comparing ratings of ‘Sleepy’ across
consec-utive weeks in the sleep restriction group, mixed model
analy-ses indicated a significant week effect. Ratings
wereprogressively lower from week to week, indicating that the
sub-jective experience of feeling sleepy habituated across
therepeated exposure of sleep restriction-recovery patterns.
Simi-larly, ratings of ‘Effort to do anything’ trended towards a
signif-icant week effect (p < 0.07), indicating that the
subjectiveexperience of ‘Effort to do anything’ somewhat habituates
tothe repeated exposure of sleep restriction-recovery
patterns.Ratings of ‘Stressed’ did not show any significant
increasesbetween sleep restriction periods.
Table 1Participant characteristics.
Controlsleep
Restrictedsleep
N* 16 15Sex Female/Male 8/8 7/8Age (yrs) Mean ± SEM 24.9 ± 1.1
24.9 ± 1.2Screening BMI (kg/m2) Mean ± SEM 24.8 ± 0.8 24.6 ±
0.7Habitual sleep duration (h)** Mean ± SEM 8.1 ± 0.2 8.4 ± 0.1
* 14 of the participants completed both 25-day stays (control
sleep and restrictedsleep; 3 participants completed only 1 stay.**
Based on 10–14 day recording period through diary.
Please cite this article in press as: Simpson, N.S., et al.
Repeating patterns of s(2016),
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3.2. Physiological stress responses
3.2.1. Diurnal cortisol rhythmFig. 3 presents daily serum
cortisol levels across the repeated
exposure to sleep restriction and recovery patterns. Mixed
modelanalysis indicated a significant interaction effect between
condi-tion by day by time of day. As seen in Fig. 3, cortisol
levels areincreasingly dysregulated across repeated exposure to
sleeprestriction, as indicated by the increasing number of
significanttime point differences in Fig. 3. Most consistently,
fasted cortisollevels shortly after awakening (0730) are
increasingly higher dur-ing the repeated sleep restriction exposure
compared to controlsleep participants, as indicated by a
significant week effect inmixed model analysis (Fig. 4). Though not
significantly different,morning cortisol levels did not completely
return to baseline levelsafter two nights with an 8 h sleep
opportunity (see Fig. 4).
3.2.2. IL-6 positive monocytesFig. 5a presents the percentage of
LPS-stimulated IL-6 positive
monocytes throughout the repeated exposure to sleep
restrictionand recovery. Mixed model analysis indicated a
significant condi-tion effect. Compared to the control sleep
condition, values weresignificantly higher during the second and
third week of sleeprestriction. Values remained higher after two
nights of recoverysleep following the second week (p < 0.05) and
third week(p = 0.09) of restricted sleep. Fig. 5b presents
percentage of non-stimulated IL-6 positive monocytes. Mixed model
analysis indi-cated a significant condition effect. When compared
to the controlsleep condition, non-stimulated IL-6 levels were
significantlyhigher during the first sleep restriction week (p <
0.05) and trendedto be higher during the second and third sleep
restriction week(both p = 0.06). Levels stayed significantly higher
after two nightsof recovery sleep following the first sleep
restriction exposure(p < 0.05) and trended to be higher after
the second sleep restric-tion exposure (p = 0.07).
3.2.3. Glucocorticoid (GC) sensitivity of monocytesFig. 6
presents the GC sensitivity determined by the ability of
dexamethasone (DEX) to suppress IL-6 expression in
monocytesacross repeated exposure to sleep restriction-recovery
patterns.Mixed model analysis indicated a significant interaction
effectbetween condition and day. While GC sensitivity was not
signifi-cantly affected during the first sleep restriction
exposure, it wassignificantly higher during the second and third
sleep restrictionexposures when compared to control sleep. GC
sensitivity trendedto remain higher after two nights of recovery
sleep following thethird exposure to restricted sleep (p <
0.06). Fig. 7 depicts the areaunder the curve (AUC) for the IL-6
suppression curves. Mixedmodel analyses revealed a significant
condition effect, due tohigher GC sensitivity throughout the three
weeks of sleeprestriction-recovery exposure, when compared to
control sleep.
4. Discussion
This study, to the best of our knowledge, provides the first
evi-dence for the impact of real-world sleep patterns of sleep
restric-tion and recovery on stress response systems. Consistent
withour hypotheses, repeated episodes of restricted sleep and
recoverywere not experienced as subjectively stressful. While they
wereperceived more generally as ‘burdensome’ (as reflected by
increas-ing subjective symptoms of sleepiness and effort),
participants’subjective responses acclimated to repeated exposure
to sleeprestriction and tended to fully recover after two nights of
full sleep.In contrast, the physiological stress response systems
assessed(cortisol and inflammatory) showed increased activity and
did
leep restriction and recovery: Do we get used to it?. Brain
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Week 1 5th day of sleep restriction 2nd day of recovery
sleepBaseline
Cor
tisol
(ug/
dL) *
Week 25th day of sleep restriction 2nd day of recovery sleep
*
*
Repeated exposureof restricted sleepControl sleep
Week 35th day of sleep restriction 2nd day of recovery sleep
Time (hours) Time (hours)
*
*
*
*
Fig. 3. Diurnal cortisol rhythms across the repeated exposure
sleep restriction-recovery patterns. Data present mean ± SEM. *p
< 0.05 between conditions.
6 N.S. Simpson et al. / Brain, Behavior, and Immunity xxx (2016)
xxx–xxx
not habituate or fully recover when repeatedly exposed to
thissleep restriction-recovery pattern. Further, the observed
increasedGC sensitivity of monocytes suggests that there was a
disruptedinterplay between the HPA and inflammatory system. The
fact thatthese escalating physiological responses were dissociated
fromsubjective impact suggests one reason that these behavior
patternspersist despite accumulating physiological costs. Plainly
stated, ifthe person does not ‘feel’ an accumulated negative impact
of thesesleep patterns, there is no internal motivation to change
thebehavior.
The current study furthers previous research that
experimen-tally modeled ‘catching up’ after a single week of sleep
restrictionis insufficient to restore the homeostasis of the
inflammatoryresponse system (van Leeuwen et al., 2009) by
demonstrating thatwhen repeatedly exposed to such sleep
restriction-recovery peri-ods, LPS-stimulated IL-6 positive
monocytes increase and do notappear to habituate to the repeated
exposure to sleep restriction,and two nights of recovery sleep do
not normalize levels. IL-6expression in unstimulated monocytes were
also significantly ele-vated during the first week of sleep
restriction followed by sleep
Please cite this article in press as: Simpson, N.S., et al.
Repeating patterns of s(2016),
http://dx.doi.org/10.1016/j.bbi.2016.06.001
recovery (paralleling Irwin et al., 2015b), and tended to remain
ele-vated while these sleep patterns continue. These findings
indicatethat even in the absence of an exogenous activation of
innateimmune components (e.g., LPS), monocytes spontaneously
pro-duce more IL-6 in response to sleep loss, do not habituate
withthe repeated exposure to sleep loss, and do not fully recover
evenafter a limited opportunity for recovery sleep.
These findings contrast, at least to some extent, to the
recentmeta-analytic finding that sleep disruption, rather than
habituallyshort sleep durations and experimentally modeled sleep
loss arenot associated with increased IL-6 (Irwin et al., 2015a).
However,this meta-analysis also demonstrates the variability in
IL-6 find-ings, which is likely introduced, at least in part, by
the level ofexperimental control in each study, including as the
impact of foodcomposition, timing of meal intake relative to blood
draws, andwhether the participants were resting quietly in a seated
periodprior to blood sample collection. Perhaps more importantly,
thereported IL-6 results may be more closely tied to the range of
mag-nitudes and durations of sleep loss examined across studies.
Thecurrent study is the first that closely models the chronicity
of
leep restriction and recovery: Do we get used to it?. Brain
Behav. Immun.
http://dx.doi.org/10.1016/j.bbi.2016.06.001
-
Week 1 Week 2 Week 3
Cor
tisol
730
am (u
g/dL
, ser
um)
* * *
12
14
16
18
20
3 8 10 15 17 22 24Study Day
Repeated exposureof restricted sleepControl sleep
Fig. 4. Cortisol levels after awakening across repeated sleep
restriction-recoverypatterns. Data present estimated mean ± SEM
based on mixed model analysis.*p < 0.05 between conditions.
* * *
Week 1 Week 2 Week 3
IL-6
pos
itive
mon
ocyt
es (%
) LP
S-st
imul
ated
Repeated exposure of restricted sleep Control sleep
(a)
IL-6
pos
itive
mon
ocyt
es (%
) un
stim
ulat
ed
20
30
40
50
60
70
3 8 10 15 17 22 24
* *
Week 1 Week 2 Week 3 (b)
-2
0
2
4
6
8
10
3 8 10 15 17 22 24 Day
Fig. 5. IL-6 positive monocytes assessed in (a) LPS-stimulated
and (b) unstimulatedwhole blood across repeated exposure to sleep
restriction-recovery patterns. Datapresent estimated mean ± SEM
based on mixed model analysis. *p < 0.05 betweenconditions.
N.S. Simpson et al. / Brain, Behavior, and Immunity xxx (2016)
xxx–xxx 7
real-world patterns of sleep loss, is designed to take a more
mech-anistic approach by investigating whether changes in the
sensitiv-ity of monocytes to the counter-inflammatory signal
cortisol maybe responsible for increased IL-6 expression, and is
highly con-trolled, leaving little room for confounds from
experimentalfactors.
Sleep loss appears to be a somewhat unique physical stressor,
inthat the HPA response to sleep loss compared to other stressors
ismild (Balbo et al., 2010; Guyon et al., 2014; Meerlo et al.,
2008).Additionally results from this study demonstrates that
chronicsleep loss does not produce the typical pattern of
habituation withrepeat exposure with respect to HPA (Grissom and
Bhatnagar,2009) and IL-6 responses (the latter when measured on a
cellularlevel (McInnis et al., 2015)). While it is adaptive for the
HPA axisto habituate to non-harmful stressors, sleep is a necessary
biolog-ical resource (Everson and Szabo, 2009; Hamilton et al.,
2007;McEwen, 2006), so habituation to chronic sleep loss may be
harm-ful rather than adaptive. While the changes in HPA axis
functioningobserved in the current study are small, as they have
been in pre-vious studies of experimental sleep loss, there may be
a cumulativeeffect after months and potentially years of
insufficient sleep. Addi-tionally, there is increasing evidence
that small changes in inflam-matory and stress mediators are
present in a variety of diseases,including cardiovascular,
metabolic, neurodegenerative diseases,as well as some forms of
cancer and pain conditions, which pro-vides further support for the
importance of the small changesobserved in the current study
(Medzhitov, 2010).
One possible explanation for the observed increase IL-6 is
thatIL-6 producing monocytes became less sensitive to the
counter-inflammatory signal of cortisol (i.e., glucocorticoid
sensitivitydecreased). Stress-induced activation of the HPA and
inflammatorysystems is metabolically costly, with potential
deleterious effects ifthese systems are overactive. Therefore,
while it is adaptive for theHPA axis to habituate to non-harmful
stressors, in this context itmay be harmful to adjust to the stress
of chronic sleep loss giventhat sleep is a necessary biological
resource (Everson and Szabo,
Please cite this article in press as: Simpson, N.S., et al.
Repeating patterns of s(2016),
http://dx.doi.org/10.1016/j.bbi.2016.06.001
2009) and, more globally, sleep is thought to be required to
ade-quately adapt to a stressor (Hamilton et al., 2007;
McEwen,2006). The process of habituation to repeated stress is, in
part, reg-ulated by cortisol negative feedback mechanisms, as
demonstratedby inhibited habituation with blockage of the GC
receptor(reviewed in Grissom and Bhatnagar, 2009). HPA and
inflammatorysystems are tightly regulated, and the GC cortisol is
crucial for theappropriate termination of every stress response via
inhibition ofmonocytes and other immune cell populations in the
productionof transcription factors (such as NF-kB) and downstream
inflam-matory cytokines, such as IL-6. However, in parallel to this
IL-6increase, we also observed an increase in GC sensitivity; one
thatdid not appear to be sufficient to prevent IL-6 production by
mono-cytes. Previous research has found contrasting results
wheredecreased GC sensitivity is observed (along with increasing
inflam-mation) under condition of chronic stress (e.g., Cohen et
al., 2012);it is challenging to expand upon the discussion of how
the mecha-nisms differ between those studies and ours without
additionalresearch. However this phenomenon of increased IL-6
productiondespite increased GC sensitivity observed in the current
study
leep restriction and recovery: Do we get used to it?. Brain
Behav. Immun.
http://dx.doi.org/10.1016/j.bbi.2016.06.001
-
Repeated exposure of restricted sleep Control sleep
DEX concentration (nM) 0 25 50 100 200 400
DEX concentration (nM) 0 25 50 100 200 400
DEX concentration (nM) 0 25 50 100 200 400
Week 1
Week 2
Week 3
5th day of sleep restriction 2nd day of recovery sleep
Baseline
5th day of sleep restriction 2nd day of recovery sleep
5th day of sleep restriction 2nd day of recovery sleep
0 25 50 100 200 400 0 25 50 100 200 400
0 25 50 100 200 400 0 25 50 100 200 400
P
-
* *
* *
* *
Week 1 Week 2 Week 3
IL-6
sup
pres
sion
by
dexa
met
haso
ne (A
UC
)G
C s
ensi
tivity
Lower
Higher-200
-180
-160
-140
-120
-100
-80
-60
-40
-20
0
3 8 10 15 17 22 24
Day
Repeated exposure to restricted sleepControl sleep
Fig. 7. GC sensitivity calculated as AUC of IL-6 suppression.
Higher IL-6 suppressionby DEX indicates higher GC sensitivity. Data
present estimated mean ± SEM basedon mixed model analysis.*p <
0.05 between conditions.
N.S. Simpson et al. / Brain, Behavior, and Immunity xxx (2016)
xxx–xxx 9
during the week and eight hours on weekends) was utilized.
Theextent to which patterns of stress responses will change if
milderpatterns of restricted sleep and recovery were carried out
for alonger period of time, (e.g., years or decades), as are often
experi-enced in real life, will need to be addressed in future
studies.
5. Conclusion
To our knowledge, this is the first study that has used an
in-laboratory design to model patterns of repeated sleep
restrictionand recovery that are prevalent in modern society. It is
also amongthe first that begins to map out a mechanistic path of
multiplestress responses systems in the context of experimental
sleep lossin humans. Despite habituation in subjective domains,
weobserved that physiological stress systems show patterns of
con-tinued elevated responses across repeated cycles of sleep
restric-tion, even with limited opportunities for recovery sleep.
Thecurrent study provides preliminary, yet powerful evidence thatwe
cannot fully adjust to patterns of restricted sleep loss
andrecovery. Despite accumulating physiological impact, if the
subjec-tive experience to these sleep patterns is one of
habituation, it caneasily be seen why obtaining insufficient sleep
on a chronic basis isexperienced as benign and why motivation to
change these behav-ior patterns remains low. The growing awareness
of chronic low-grade inflammation as a basis for increasing rates
of cardiovascu-lar, metabolic, pain or mood related disorders
(Medzhitov, 2010)suggests that these patterns of insufficient sleep
may pose a signif-icant health risk. Given its high prevalence in
modern society, theimpact of these patterns of chronically
restricted sleep with limitedrecovery on long-term health cannot be
ignored.
Acknowledgments
This work was funded by Grants R01 HL 105544 from theNational
Heart, Lung, and Blood Institute, and Grants UL1RR02758 and
M01-RR-01032 from the National Center for
Please cite this article in press as: Simpson, N.S., et al.
Repeating patterns of s(2016),
http://dx.doi.org/10.1016/j.bbi.2016.06.001
Research Resources to the Harvard Clinical and
TranslationalScience Center.
Appendix A. Supplementary data
Supplementary data associated with this article can be found,
inthe online version, at
http://dx.doi.org/10.1016/j.bbi.2016.06.001.
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Repeating patterns of sleep restriction and recovery: Do we get
used �to it?1 Introduction2 Methods2.1 Experimental model2.2
Participants2.3 Study protocol2.3.1 Screening &
randomization2.3.2 Research environment2.3.3 Measurements2.3.3.1
Polysomnographic recording (PSG)2.3.3.2 Blood sampling
2.4 Stress response system measures2.4.1 Cortisol2.4.2
Stimulated IL-62.4.3 Unstimulated IL-62.4.4 Glucocorticoid (GC)
sensitivity of monocytes2.4.5 Subjective measures
2.5 Statistics
3 Results3.1 Subjective well-being responses3.2 Physiological
stress responses3.2.1 Diurnal cortisol rhythm3.2.2 IL-6 positive
monocytes3.2.3 Glucocorticoid (GC) sensitivity of monocytes
4 Discussion5 ConclusionAcknowledgmentsAppendix A Supplementary
dataReferences