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Sleep disturbances are prominent correlates of acute mood episodes and inadequate recovery in bipolar disorder (BD), yet the mechanistic relationship between sleep physiology and mood remains poorly understood. Using a series of pre-sleep mood inductions and overnight sleep recording, this study examined the relationship between overnight mood regulation and a marker of sleep intensity (non-rapid eye movement sleep slow wave activity; NREM SWA) during the interepisode phase of BD.
Adults with interepisode BD type 1 (BD; n=20) and healthy adult controls (CTL; n=23) slept in the laboratory for a screening night, a neutral mood induction night (baseline), a happy mood induction night, and a sad mood induction night. NREM SWA (0.75–4.75Hz) was derived from overnight sleep EEG recordings. Overnight mood regulation was evaluated using an affect grid pleasantness rating post-mood induction (pre-sleep) and the next morning.
Overnight mood regulation did not differ between groups following the sad or happy inductions. SWA did not significantly change for either group on the sad induction night compared to baseline. In BD only, SWA on the sad night was related to impaired overnight negative mood regulation. On the happy induction night, SWA increased relative to baseline in both groups, though SWA was not related to overnight mood regulation for either group.
These findings indicate that SWA disruption may play a role in sustaining negative mood state from the previous night in interepisode BD. However, positive mood state could enhance SWA in bipolar patients and healthy adults.
Bipolar disorder (BD) is characterized by mood regulation impairment, oscillating between persistently elevated or irritable mood and sustained periods of depressed mood (APA, 2013). Even between episodes, individuals with BD remain seriously symptomatic (Joffe et al., 2004) and exhibit significant mood lability (Aas et al., 2014). Though sleep disturbances are among the most prominent correlates of mood episodes and inadequate recovery in BD (Harvey, 2008), it remains unclear how specific aspects of sleep physiology may relate to negative and positive mood dysregulation.
Disrupted sleep homeostasis is a hypothesized contributor to sleep and mood impairments in affective disorders (Borbely and Wirz-Justice, 1982). Sleep homeostasis is a physiological sleep regulatory process defined by increasing pressure to sleep during extended wakefulness, followed by dissipating sleep intensity across the sleep period (Borbely et al., 2016). The amount of slow wave activity (SWA; EEG power density 0.75–4.75 Hz) during non-rapid eye movement (NREM) sleep is the best-characterized marker of sleep intensity (Borbely et al., 2016). The S-deficiency hypothesis of depression proposes that deficient build-up of sleep pressure and reduced sleep intensity (SWA) may produce or sustain depressed mood (Borbely and Wirz-Justice, 1982). In accord with this hypothesis, SWA deficits and reduced visually-staged slow wave sleep (SWS; NREM stage 3 and 4) are generally observed in unipolar depression relative to controls (See Armitage, 2007 for review). Moreover, selective slow-wave sleep deprivation can have an antidepressant effect among unipolar depressed patients (Cheng et al., 2015, Landsness et al., 2011), which may be due to a “resetting” of waking sleep pressure and greater SWA rebound the next night (Landsness et al., 2011). While the precise mechanisms linking SWA and depressed mood remain to be delineated, research suggests that increased sleep intensity may facilitate cortical plasticity in brain regions supporting a host of cognitive-affective processes implicated in affective disorders (Huber et al., 2008, Tononi, 2009).
SWA has been less extensively studied in BD. Only one study in bipolar depression (n = 8 per group) has measured SWA, reporting no differences relative to matched controls (Mendelson et al., 1987). However, studies assessing visually-staged sleep indicate lower SWS in bipolar depression relative to healthy adults, at levels akin to unipolar depression (Asaad et al., 2016, Fossion et al., 1998, Gillin et al., 1979, Linkowski et al., 1986). While no studies to date have selectively deprived slow-wave sleep in bipolar depression, sleep deprivation also has antidepressant effects in bipolar depression and can induce (hypo)mania in a subset of cases (Benedetti and Colombo, 2011). SWS deficits in (hypo)mania may be comparable to depression (Asaad et al., 2016, Linkowski et al., 1986), though findings are inconsistent (Hudson et al., 1988). While altered SWS has not been observed in interepisode BD (Eidelman et al., 2010, Knowles et al., 1986, Sitaram et al., 1982), one study reported that higher baseline SWS predicted greater mania symptom severity at 3-month follow-up (Eidelman et al., 2010).
Overall, there is some support for SWS deficits in bipolar depression and (hypo)mania. This raises the possibility that BD patients, like their unipolar depressed counterparts, may be vulnerable to mood-related changes in sleep intensity. Initial prospective findings in interepisode BD, along with the well-documented antidepressant response to sleep deprivation, suggest that altered sleep intensity could play a role in generating or sustaining mood disturbance in BD. However, whether waking mood affects sleep intensity remains unclear. Initial experimental work in healthy adults suggests that pre-sleep affect may alter slow wave sleep (Talamini et al., 2013). Among those with affective disorders, who are more vulnerable to mood regulation impairments, it is important to disambiguate whether acute change in waking mood produces SWA deficits and/or whether deficient SWA maintains mood disturbances overnight. The interepisode phase of BD provides unique opportunity to experimentally probe such relationships.
The aim of the present study was to examine whether adults with interepisode BD experience experimentally-induced mood disruptions in SWA, and whether deficient SWA is related to impaired overnight mood regulation. This study involved further analysis of an existing dataset (Eidelman et al., 2010, Talbot et al., 2009). Adults with interepisode BD and healthy adult controls spent 4 nights in the sleep laboratory: 1 screening night, 1 neutral (baseline) mood induction night, 1 negative (sad) mood induction night, and 1 positive (happy) mood induction night. The first aim was to assess whether interepisode bipolar patients and healthy adults exhibited an overnight reduction in negative and positive mood following the sad and happy mood inductions, respectively. Due to documented mood regulation deficits in interepisode BD (e.g., Aas et al., 2014), it was hypothesized that the bipolar group would exhibit a smaller overnight change in mood. The second aim was to evaluate the effects of the sad and happy mood inductions on SWA relative to baseline. Based on evidence of reduced SWA in depression and (hypo)mania, we predicted that SWA would be lower after both mood inductions relative to baseline in the bipolar group, but not in the control group. The final aim was to assess associations between SWA and overnight changes in mood on the sad and happy induction nights. We predicted that lower SWA would be associated with impaired overnight mood regulation in bipolar patients.
Participants included: 20 adults with interepisode DSM-IV-TR bipolar disorder type I (BD) and 23 healthy adult controls (CTL) with no history of psychiatric or sleep disorders. Participants were drawn from a larger protocol, results from which have been described in previous reports (e.g., Eidelman et al., 2010, Talbot et al., 2009). All procedures contributing to this work comply with the ethical standards of relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. Inclusion criteria for all participants were: (a) negative for narcolepsy, sleep apnea (AHI>5), restless leg syndrome or periodic limb movement disorder (PLMA>15) on the basis of polysomnography; (b) met criteria for interepisode symptom cutoffs based on prior research (Chengappa et al., 2003; Thompson et al., 2005): a score of ≤7 on the Young Mania Rating Scale (YMRS; Young et al., 1978) and a score of ≤ 11 on the Inventory of Depressive Symptomatology–Clinician Rated (ISD-C; Rush et al., 1996); (c) had no history of severe head trauma, stroke, neurological disease, or severe medical illness. BD were included if they: (a) met DSM–IV–TR bipolar I disorder (American Psychiatric Association, 2000); (b) did not meet criteria for substance or alcohol abuse or dependence in the past 3 months; (c) were under the care of a psychiatrist. CTL could not meet DSM–IV–TR criteria for any lifetime Axis I disorder.
In order to be included in the present analysis, participants had to meet criteria for BD type I, and complete the baseline (neutral mood induction) and at least one mood induction (sad or happy) sleep recording. From the original sample (BD n=28; CTL n=28), 4 BD participants had BD type II. Additional participants were excluded on the basis of poor quality sleep recording/excessive EEG artifact on the baseline night (BD=2; CTL=4) or both mood induction nights (BD=2, CTL=1). For the sad induction night, additional participants were lost to dropout (BD=1) or poor quality recordings (BD=2; CTL=2), leading to a total of 17 BD and 21 CTL participants for sad night analyses. Similarly, for the happy induction night additional participants were lost to dropout (BD=1; CTL=1) or poor quality recordings (BD=3; CTL=1), leading to a total of 16 BD and 21 CTL participants for happy night analyses.
DSM-IV-TR Axis I diagnoses were confirmed using the SCID.
Current symptoms of mania were measured using the 11-item, clinician rated Young Mania Rating Scale (YMRS; Young et al., 1978). Current symptoms of depression were assessed using the 30-item, clinician-rated Inventory of Depressive Symptomatology (IDS-C; Rush et al., 1996). YMRS (≤7) and IDS-C (≤ 11) scores were used to confirm current interepisode status (i.e., neither currently manic nor depressed) for both groups.
BD course characteristics were assessed using a validated charting procedure (National Institute of Mental Health retrospective Life-Charting Methodology; Denicoff et al., 1997, Leverich and Post, 1997). Age of BD onset, illness duration, and the number of lifetime manic and depressive episodes were derived.
Medication name and dosage were recorded at each visit. Medication effects were examined using an approach developed for neuroimaging research (Phillips et al., 2008a). Each medication was re-categorized by medication class, and dose was categorized as 0(no medication), 1(low), or 2(high) based on published parameters and chlorpromazine-equivalent mean effective daily doses (Davis and Chen, 2004, Sackeim, 2001). A composite measure of medication load was created for each participant by summing across dosage strength codes and classes (Almeida et al., 2009).
The DSISD is a semi-structured interview that assesses research diagnostic criteria for sleep disorders; it has good reliability and validity (Edinger, 2009).
Sleep was recorded using overnight PSG with a Compumedics 802 Siesta system (Compumedics, Charlotte, NC). PSG involves the continuous and simultaneous recording of EEG, electrooculogram (EOG), and electromyogram (EMG) to score sleep. Recording channels included four EEG derivations (C3/A2, C4/A1, O1/A2, O2/A1), two EOG leads, and two submental EMG sensors. On the first overnight visit, heart rate, blood oxygen, nasal and oral air flow, thoracic and abdominal effort, and leg motion were monitored. PSG data were staged in 30-second epochs using standard Rechtscaffen & Kales criteria (Rechtschaffen, 1968).
Sleep EEG analyses were performed offline in MATLAB R2011b (Mathworks, Natick, MA) and EEGLAB11 (http://sccn.ucsd.edu/eeglab/). Power spectral analysis was carried out in accordance with published methods (van der Helm et al., 2011). EEG channels were re-referenced to the average of the left and right mastoid (A1, A2), run through high-pass (0.5Hz) and low-pass (55Hz) Finite Impulse Response (FIR) filtering, and split into 5-second epochs. EEG recordings were visually inspected for 5-second epochs containing muscle, cardiac and eye-movement artifacts; artifact-laden epochs were manually rejected. Power spectral density (μV2/Hz) was calculated using a Fast Fourier Transform (FFT) on each hamming-windowed 5-second epoch at 128Hz, yielding a frequency resolution of 0.2Hz. FFT results were sorted according to sleep stage and averaged across NREM (stages 2–4). NREM SWA was defined as integrated power in the 0.75–4.75 Hz range. Relative SWA (expressed as a percentage) was derived by dividing SWA by the integrated power of the entire spectrum. For each night, values ±3.0 standard deviations were Winsorized (<1% of all data). Relative SWA derived from the central EEG derivation C4 was used for hypothesis testing.
The affect grid (Russell et al., 1989) is a self-report rating of pleasure on the horizontal axis (–4=extremely unpleasant, 0=neutral, 4=extremely pleasant) and arousal on the vertical axis (–4=extremely low arousal, 0=neutral, 4=extremely high arousal); it has adequate reliability and validity (Russell et al., 1989).
The mood induction technique was adapted from well-validated procedures (Albersnagel, 1988, Eich et al., 1994, Stein et al., 2000, Williams et al., 2002) that combine continuous music with autobiographical recall. For the happy and sad mood inductions, participants were told that they would listen to a selection of music to assist them in developing a happy (or sad) mood, and then were then instructed to try hard to develop an intense mood state by concentrating on ideas and images that make them feel happy (or sad). For the neutral induction, participants were asked to focus on neutral topics (e.g., directions to a familiar place or the layout of furniture at home) while listening to the classical music. See Supplemental Methods regarding music selection.
At the first laboratory visit, participants completed written informed consent. Participants were then administered the SCID, DSISD, YMRS, IDS-C, and life chart to assess diagnostic status, symptom severity, and clinical course. Eligible participants were provided with an instruction sheet for the day prior to subsequent overnight lab visits; these included: (1) restrict caffeine intake to <2 cups coffee (or equivalent) before noon and (2) refrain from taking over-the-counter medications.
For all overnight visits, participants arrived at the laboratory 2 hours prior to their habitual bedtime. Overnight visit eligibility was then assessed by a clinician, including compliance with overnight instructions, medication use, and interepisode status using the YMRS and IDS-C. If YMRS or IDS-C scores exceeded interepisode cut-offs, a safety assessment was completed before the participant was sent home (without completing the overnight). Overnight visits were each approximately 2 weeks apart; some participants did not complete all visits (see Supplemental Procedures for details).
At the first overnight, participants underwent full clinical polysomnography to assess for sleep disorders (e.g., sleep apnea, PLMD). At the three subsequent overnight visits, mood inductions were administered. A neutral mood induction was administered at the second overnight visit, and then the order of the happy and sad inductions was counterbalanced between the third and fourth overnight visits. In order to reduce demand effects, participants were told that they were engaging in two different experiments at these visits, a music study and a sleep study.
At each mood induction overnight visit (neutral, sad, happy), PSG equipment was first attached, followed by the mood induction administration in a private room. During mood inductions, participants rated their current affect, pleasure, and arousal at baseline, and every 5 minutes thereafter, using a computerized version of the Affect Grid. The neutral mood induction was 15 minutes for all participants and there was no mood cut-off at the end. Affect Grid mood thresholds of at least −3 (pleasure) for the sad induction and +3 (pleasure) for the happy induction were set based on previous methods (Eich et al., 1994). Mood inductions ended at these thresholds, or at 40 minutes after the start of the induction. The final Affect Grid of the mood induction was used as the pre-sleep (post-induction) measure. Immediately after the mood induction, participants were escorted to the laboratory bedroom and allowed to sleep. Participants were awakened at the time they requested (approx. 9:00am at the latest). To mitigate the effects of sleep inertia upon morning mood reports, participants completed the Affect Grid roughly 20 minutes after awakening. Participants were debriefed at the end of their last visit.
Analyses were conducted in SPSS 20.0 (IBM Corporation, Somers, NY, 2012). Affect Grid pleasantness ratings were used to evaluate mood just prior to each mood induction (pre-induction), at the end of each mood induction (post-induction) and the morning following the mood induction (morning). A 2 (Group; BD vs. CTL) × 3 (Time; pre-induction, post-induction, morning) repeated-measures analysis of variance (ANOVA) was conducted for each the sad and happy mood inductions. Overnight mood change was evaluated using a difference score (morning – post-induction affect grid pleasantness rating).
The effect of pre-sleep sad and happy mood inductions on SWA was examined using a series of 2 (Night; neutral vs. sad or happy mood induction) × 2 (Group; BD vs. CTL) repeated-measures ANOVA models. The neutral mood induction was used as a baseline night. As a few individuals did not complete both the happy and sad mood induction overnights, separate ANOVAs compared each mood induction (sad, happy) to baseline, to maximize statistical power.
In each group, spearman’s rho correlation analyses evaluated whether SWA on the sad or happy mood induction nights was associated with overnight mood change (morning – post-induction affect grid pleasantness ratings) that same night.
On an exploratory basis, we conducted an analysis with sleep architecture variables paralleling the main sleep aims. Exploratory spearman rho correlations were also conducted to examine effects of illness course characteristics (see Supplemental Results), pre-sleep arousal, and medication load on SWA. The significance level was set at p<0.05 (two-sided) for all analyses.
The two groups did not significantly differ on any sociodemographic characteristics (Table 1). While BD exhibited significantly higher baseline manic and depressive symptoms (ps<0.05), scores were well below established interepisode cut-offs. Baseline (neutral induction night) bedtime and sleep duration sleep did not significantly differ between groups, though waketime was later in BD than CTL (p<0.05). Spearman correlation analyses assessed whether age, sex, depressive or manic symptoms scores were meaningfully associated with any mood or sleep EEG outcomes. No significant correlations emerged; therefore, these variables were not included as covariates in subsequent analyses.
There was neither a significant main effect of Group, F(1,36)=2.61, p=0.115, nor a significant Group X Time interaction effect, F(1,36)=0.44, p=0.513, on affect grid mood ratings across the sad mood induction overnight (Figure 1a). However, there was a significant main effect of Time, F(1, 36)=92.70, p<0.001. Posthoc paired samples t-tests confirmed a significant increase in negative mood from pre- to post-mood induction, t(36)=9.68, p<0.001, and a significant overnight decrease in negative mood from post-induction to morning, t(36)=−8.15, p<0.001.
Figure 2a illustrates SWA means on the baseline and sad mood induction overnights. There were no significant effects SWA across Group, F(1,36)=2.27, p=0.140, Night, F(1,36)=1.13 p=0.295, or Group X Night, F(1,36)=0.42, p=0.520.
Sad mood induction night SWA positively correlated with overnight mood change on the affect grid (r=0.56, p=0.018; Figure 3a) in BD such that higher SWA was related to greater improvement in negative mood; this association was not observed in CTL (r=0.34, p=0.143; Figure 3b).
There was neither a significant main effect of Group, F(1, 41)=0.32, p=0.575, nor a significant Group X Time interaction effect, F(1,35)=0.92, p=0.343, on mood ratings across the happy mood induction overnight (Figure 1b). There was a significant main effect of Time, F(1, 35)=27.61, p<0.001. Posthoc paired samples t-tests confirmed a significant increase in positive mood from pre- to post-mood induction, t(36)=−4.79, p<0.001, and a significant overnight reduction in positive mood from post-induction to morning, t(36)=4.80, p<0.001.
Figure 2b shows SWA on the baseline and happy mood induction overnights. There was a significant main effect of Night, F(1,35)=5.64, p=0.023, whereby SWA increased on the happy mood induction night relative to baseline in both groups. Effects of Group, F(1,35)=0.00, p=0.996, and Group X Night, F(1,35)=1.25, p=0.271, were non-significant.
Table 2 reports results from repeated measures ANOVAs evaluating sleep architecture variables (TST, TWT, N1, N2, SWS, REM) on the neutral vs. happy or sad induction nights. Baseline night means differ slightly between the sad and happy mood induction nights since a few individuals did not participate in both mood nights and a repeated measures analysis of variance excludes a participant if there is missing data on any of the observation points. Baseline sleep architecture has been described in previous reports from the full sample (Eidelman et al., 2010, Talbot et al., 2009). There were no significant effects of Group, Night or Group X Night for TST, N1, N2, or SWS (all p>0.05). There was a Group effect for TWT, such that BD had greater TWT than CTL at baseline relative to both the sad night and happy nights (both p<0.05). There was a main effect of Night for sad night REM sleep relative to baseline, such that both groups had greater REM relative to baseline (p<.05). Sleep architecture variables did not correlate with overnight mood change on the sad or happy nights (all p>0.05) with the exception of SWS. Paralleling SWA findings, sad night SWS was positively correlated with overnight negative mood change in BD (r=0.61, p=0.009), but not CTL (r=−0.27, p=0.259).
No significant differences were observed between BD and CTL on post-induction affect grid arousal ratings for the sad (−1.41 vs. −1.55; t(35)=−0.23, p=0.822) and happy mood induction nights (−0.81 vs. −0.33; t(35)=−0.61, p=0.543). Post-induction arousal ratings did not correlate with SWA on the mood induction nights for either group (ps>0.05).
In BD, medication load did not significantly differ between baseline versus the sad (4.29 vs. 4.12; F(1,16)=1.31, p=0.269) and happy mood induction nights (4.44 vs. 4.38; F(1,15)=0.14, p=0.718). Medication load and SWA were not significantly correlated on the baseline and sad mood induction nights (ps>0.05). Higher medication load correlated with lower happy night SWA at a trend level (r=−0.45, p=0.083).
This study tested relationships between overnight mood regulation impairment, sleep intensity (indexed by SWA), and interepisode BD diagnosis. Findings included that: (1) overnight mood regulation in interepisode BD did not significantly differ from healthy adults, (2) inducing a positive mood state prior to sleep increased SWA relative to baseline across all participants, and (3) lower SWA was associated with attenuated overnight regulation of negative mood, but not positive mood, in bipolar patients.
Taking findings from the sad mood induction first, the prediction that the bipolar group would exhibit impaired overnight mood regulation was not supported. Both the bipolar and control groups exhibited intact overnight mood regulation, with negative mood prior to sleep generally regularizing to a neutral rating by the morning. This is consistent with previous research indicating that negative mood typically improves overnight in healthy adults (Cartwright et al., 2003, Cartwright et al., 1998). Impaired mood regulation in interepisode BD might only be evident after shorter spans of time during waking hours, though to our knowledge this question has not yet been systematically investigated. The present findings indicate that overnight mood regulation capabilities in interepisode BD may generally be comparable to healthy adults.
The sad mood induction did not have differential effects on SWA across the two groups. However, lower SWA on the sad mood induction night was related to attenuated overnight improvement in negative mood for bipolar patients only. This coheres with predictions of the S-deficiency hypothesis (Borbély, 1982), which proposes that deficient SWA may sustain depressed mood. Exploratory sleep architecture analyses further support this notion; lower sad night SWS also correlated with impaired overnight negative mood regulation in BD. A lack of correlation with REM sleep and other NREM stages suggest a specific role for sleep intensity (SWA/SWS) in overnight regulation of negative mood, consistent with prior reports (Cheng et al., 2015). These results raise the possibility that slow-wave deficits in BD might sustain negative mood overnight.
Predictions for the happy mood induction night were generally not supported. On average, positive mood state prior to sleep decreased to a neutral rating by morning for both groups, thus the bipolar group did not exhibit impaired overnight mood regulation relative to controls. Also contrary to our hypothesis, both groups exhibited increased SWA following the happy mood induction. Positive affect has previously been observed to be beneficial for sleep quality and efficiency in some studies (Ong et al., 2013, Steptoe et al., 2008), though this is the first study to our knowledge that has explored the effects of positive mood on SWA. Finally, there was not a significant association between SWA and overnight change in positive mood. The absence of a statistically significant relationship between SWA and overnight change in positive mood, in the presence of both positive mood-induced SWA changes and a reduction in positive mood from night to morning, raises the possibility that SWA may not be driving overnight change in positive mood. Perhaps overnight changes in positive versus negative mood are driven by different sleep-wake regulatory mechanisms. Tightly controlled forced desynchrony and constant routine protocols have determined that there is a circadian pattern in positive affect (Boivin et al., 1997, Murray et al., 2002), while there is less evidence for a clear 24-hr rhythm in negative affect (Boivin et al., 1997). Thus, overnight change in positive mood may primarily be modulated by circadian, rather than homeostatic, factors.
Overall, these results may indicate differing associations between mood state and SWA. Though sad mood did not induce changes in SWA, lower SWA correlated with attenuated overnight improvement in negative mood in BD, adding to existing literature supporting the relevance of sleep homeostatic mechanisms for negative mood regulation. There was greater inter-individual variation in sad night SWA among BD (Figure 3a–b). Inter-individual differences in vulnerability to SWA disruption, and its impact on negative mood, may be linked to genetic susceptibility to affective disorders. For example, PER3 polymorphisms more prevalent in affective disorders are also related to inter-individual differences in homeostatic sleep pressure (Artioli et al., 2007, Dallaspezia et al., 2016). Conversely, the happy mood induction led to increased SWA relative to baseline in both groups, but SWA was uncorrelated with overnight change in positive mood. Effects of positive mood on central and peripheral physiology (Admon and Pizzagalli, 2015, Shiota et al., 2011) may acutely bolster SWA, separate from circadian mechanisms proposed to govern 24-hr fluctuation in positive mood. Relevant to depression, and other psychiatric conditions with SWA deficiencies (e.g., schizophrenia; Hoffmann et al., 2000), increasing pre-sleep positive mood may be means of enhancing SWA, as an alternative to sleep deprivation. However, further work is necessary to delineate the potentially distinct physiological mechanisms underpinning links between negative and positive mood with SWA.
While a key strength of this study is its unique combination of experimental mood manipulation with repeated within-subject PSG sleep assessments in BD, several limitations merit consideration. Only central sleep EEG derivations were analyzed. SWA deficits can be more pronounced in prefrontal and frontal areas (Plante et al., 2012, Werth et al., 1997), thus future studies of sleep in BD would benefit from utilizing hdEEG to explore topographic hypotheses. Sex differences in SWA are sometimes observed in unipolar depression, with some reports observing greater SWA in females (e.g., Plante et al., 2012). While sex differences in SWA were not observed here, this may be due to the predominantly female sample and resulting lack of power to detect sex effects. Prior sleep and wakefulness also impact SWA (Borbély and Achermann, 2000). As this study was not initially designed to assess SWA, participants were not instructed to keep a regular sleep-wake schedule before sleep monitoring; future studies should address this design limitation. This was a medicated sample of bipolar participants. Though medication load was not significantly associated with overnight mood change, medication could be affecting sleep physiology. Because this study was conducted across a span of several months, an unmedicated sample would be unfeasible and unsafe. More broadly, research on severe mental illness would be seriously hindered and lack generalizability if done in only medication-free samples (Phillips et al., 2008b). The present findings remain clinically important given that the vast majority of BD patients are medicated.
In summary, the present findings provide preliminary support for a relationship between mood and sleep intensity(indexed by SWA) in interepisode BD. Lower SWA was associated with impaired overnight regulation of pre-sleep negative mood in BD, but not in controls. Pre-sleep positive mood increased SWA in both groups relative to baseline, though SWA was not related to overnight change in positive mood. The present findings suggest a potential interplay between mood and sleep intensity that may carry relevance for the management of mood dysregulation and sleep-wake disturbances in interepisode BD.
Financial Support: This research was supported by National Institute of Mental Health (A.S., grant numbers K01MH111953, T32MH089919, T32MH018269), (A.H., R34MH080958), (M.W., R01MH9353).
Conflict of Interest: None