Sleep and treatment response in depression: new findings using power spectral analysis

Psychiatry Research 103 Ž2001. 51᎐67

Sleep and treatment response in depression: new findings using power spectral analysis Daniel J. Buysse a,U , Martica Hall a , Amy Begley a , Christine R. Cherry a , Patricia R. Houck a , Stephanie Land b, Hernando Ombao a,c , David J. Kupfer a , Ellen Frank a a

Department of Psychiatry, Uni¨ ersity of Pittsburgh, 3811 O’Hara Street, E-1127 WPIC, Pittsburgh, PA 15213, USA b Department of Biostatistics, Uni¨ ersity of Pittsburgh, 201 North Craig Street, Pittsburgh, PA 15213, USA c Department of Statistics, Uni¨ ersity of Pittsburgh, 3811 O’Hara Street, Pittsburgh, PA 15213, USA Received 30 August 2000; received in revised form 11 May 2001; accepted 31 May 2001

Abstract This study examined quantitative measures of sleep electroencephalogram ŽEEG. and phasic rapid eye movements ŽREM. as correlates of remission and recovery in depressed patients. To address correlates of remission, pre-treatment EEG sleep studies were examined in 130 women outpatients with major depressive disorder treated with interpersonal psychotherapy ŽIPT.. To address correlates of recovery, baseline and post-treatment EEG sleep studies were examined in 23 women who recovered with IPT alone and 23 women who recovered with IPT q fluoxetine. Outcomes included EEG power spectra during non-rapid eye movement ŽNREM. sleep and REM sleep and quantitative REMs. IPT non-remitters had increased phasic REM compared with remitters, but no significant differences in EEG power spectra. IPT q fluoxetine recoverers, but not IPT recoverers, showed increases in phasic REM and REM percentage from baseline to recovery. In NREM sleep, the IPT q fluoxetine group showed a decrease in alpha power from baseline to recovery, while the IPT group showed a slight increase. The number of REMs was a more robust correlate of remission and recovery than modeled quantitative EEG spectra during NREM or REM sleep. Quantitative REMs may provide a more direct measure of brainstem function and dysfunction during REM sleep than quantitative sleep EEG measures. 䊚 2001 Elsevier Science Ireland Ltd. All rights reserved. Keywords: Sleep; Rapid eye movement sleep; Depression; Treatment; Electroencephalogram; Spectral analysis

U

Corresponding author. Tel.: q1-412-624-2246; fax: q1-412-624-2841. E-mail address: [email protected] ŽD.J. Buysse..

0165-1781r01r$ - see front matter 䊚 2001 Elsevier Science Ireland Ltd. All rights reserved. PII: S 0 1 6 5 - 1 7 8 1 Ž 0 1 . 0 0 2 7 0 - 0

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D.J. Buysse et al. r Psychiatry Research 103 (2001) 51᎐67

1. Introduction Findings from several independent samples have indicated a relationship between abnormal sleep at baseline and poor treatment outcome in depression both with pharmacologic treatment Že.g. Kupfer et al., 1981; Rush et al., 1989. and with psychotherapy ŽBuysse et al., 1992a,b; Thase et al., 1996, 1997a,b; Dew et al., 1997; Buysse et al., 1999a.. In recent studies, poor treatment outcomes have been observed among patients who report subjectively poor sleep; who have increased amounts of REM sleep; who have increased numbers of eye movements during REM sleep; or who have an abnormal sleep ‘profile’ comprising poor sleep efficiency, short REM sleep latency and increased numbers of rapid eye movements. Poor response, defined as failure to remit or longer time to remission, has been observed using interpersonal psychotherapy for depression ŽIPT., cognitive-behavior therapy ŽCBT. and combined IPT plus nortriptyline. The relationship between poor sleep and poor outcome has been seen in single-episode and recurrent depression, men and women, and ages from young adulthood to late life. Thus, the relationship between sleep and treatment outcome appears to be a robust one. One of the remaining questions regards the significance of this finding: why should disturbed sleep ᎏ and REM sleep in particular ᎏ be related to poor outcome in depression? One possibility is that sleep disturbance is simply a proxy for greater depression severity. However, the studies cited above have not shown a consistent relationship between degree of sleep disturbance and global severity of depression, as rated by the Hamilton Rating Scale for Depression ŽHRSD.. Other possibilities are suggested by considering the mechanisms involved in the regulation of sleep-wake states, and REM sleep in particular. The appearance of REM sleep is regulated by reciprocal interactions between cholinergic nuclei of the laterodorsal and peduculopontine tegmentum Žwhich show increased firing rates during REM sleep. and noradrenergic and serotonergic nuclei of the locus coeruleus and raphe nuclei Žwhose firing is virtually absent during REM..

Transection experiments demonstrate that these nuclei in the upper pons are necessary and sufficient for the generation of REM sleep. Furthermore, the occurrence of eye movements during REM sleep is controlled almost exclusively by brainstem mechanisms ŽSiegel, 2000.. Although brainstem mechanisms are clearly responsible for the REM sleep state and the appearance of eye movements during REM, functional imaging experiments have consistently shown that widespread areas of the cortex and limbic system are also activated during REM sleep ŽMaquet et al., 1996; Braun et al., 1997; Nofzinger et al., 1997.. Furthermore, the pattern of cortical and limbic activation during REM sleep differs among depressed patients and healthy control subjects ŽNofzinger et al., 1999.. The core symptoms of depression Že.g. low mood, anhedonia, poor concentration . also demonstrate the importance of cortical and limbic dysregulation in depression. Thus, the above observations suggest two additional potential explanations for the relationship between REM sleep disturbances and treatment outcome in depression: namely, that alterations in REM sleep and phasic REM activity are an index of primarily brainstem dysregulation; or of primarily cortical dysregulation. One way to address these competing hypotheses is to compare treatment responders and nonresponders on measures that primarily reflect brainstem activity during REM sleep and on measures that primarily reflect cortical activity. The number of eye movements during REM is an example of the first type of measure. We have previously reported that phasic REM activity was higher among patients who failed to remit with psychotherapy ŽBuysse et al., 1999a.. Power spectral analysis ŽPSA. of the sleep EEG is an example of the second type of measure. PSA is a quantitative method that describes the distribution of EEG power in the frequency domain. It conveys characteristics of the EEG during sleep more fully than traditional visual sleep stage scoring, which assigns a single stage score to REM and four stages to NREM sleep. Previous studies have examined PSA and pharmacologic treatment outcome in depression, but have generally found no differences between treatment re-

D.J. Buysse et al. r Psychiatry Research 103 (2001) 51᎐67

sponders and non-responders ŽLuthringer et al., 1995; van Bemmel et al., 1993, 1995.. In addition to identifying correlates of acute treatment response, EEG sleep studies may also be useful for examining treatment-related changes in neurobiology. Previous studies have indicated that REM sleep and sleep continuity measures, generally show some degree of ‘normalization’ during sustained remission of the acute depressive episode following psychotherapy or pharmacotherapy followed by drug discontinuation Že.g. Thase et al., 1998; Rush et al., 1986; Sitaram et al., 1980; Buysse et al., 1992a,b; Thase et al., 1994.. Furthermore, acute and chronic antidepressant treatment are associated with significant modifications of PSA ŽLuthringer et al., 1996; Hoffmann et al., 1999; Neckelmann et al., 1996; van Bemmel et al., 1995.. However, no studies have reported on changes in PSA of the sleep EEG as a function of psychotherapy treatment. The aims of the current study were: Ž1. To compare phasic REMS and PSA of the EEG during REM and NREM sleep among patients who remitted and who did not remit with psychotherapy treatment. This aim addresses PSA correlates of remission following acute treatment; Ž2. To compare phasic REMS and PSA of the EEG during REM and NREM in a matched subgroup of patients who responded to either psychotherapy alone or combined medicationr psychotherapy treatment. This aim addresses the sleep correlates of recovery with different types of treatment. Because these types of analyses have not been reported, they are primarily descriptive rather than hypothesis-testing.

2. Methods The results reported here are one component of a study investigating the efficacy of three ‘doses’ of interpersonal psychotherapy ŽIPT. as a maintenance treatment for recurrent major depressive disorder ŽMDD. in women ŽMH 49115, E. Frank, Principal Investigator.. The study design involves acute open treatment with IPT until patients recover from the index episode. Patients

53

who fail to remit with IPT as a sole treatment Žsee criteria below. are treated openly with fluoxetine in addition to IPT. After 6 months of sustained remission, patients are deemed to be in recovery. For patients on medication plus IPT, fluoxetine is tapered and discontinued, and patients continue in the protocol. Recovered patients are randomly assigned to weekly, biweekly or monthly maintenance IPT for 2 years. Recurrence rates and time to recurrence constitute the major outcome variables. In order to examine biological correlates of clinical course in these patients, we conduct EEG sleep studies at baseline Žwhile depressed., at recovery Žwhile medication-free. and at the end of maintenance treatment. This report includes analyses on two groups of subjects. Analysis 1 was conducted on baseline sleep studies in patients who remitted Ž n s 73. or did not remit Ž n s 57. with IPT alone. Analysis 2 includes a subset of these patients, specifically, age-matched groups of patients who recovered on IPT alone or on IPT plus fluoxetine Ž n s 23 each.. In the second analysis, sleep measures were analyzed at both baseline Žsymptomatic. and recovery Žasymptomatic. time points. Data from earlier subsets of subjects described in this report have been presented in previous publications ŽBuysse et al., 1998, 1999a,b.. The current report includes additional, more recently studied subjects. 2.1. Patients Subjects were 130 women Žmean age 38.0" 10.3 years. with recurrent MDD without psychotic features who were recruited, studied and treated as outpatients. Patients had to have at least one previous episode of MDD occurring no more than 2.5 years prior to the index episode, with a complete symptomatic remission lasting at least 10 weeks between episodes. Diagnoses were established using either the Schedule for Affective Disorders and Schizophrenia and Research Diagnostic Criteria ŽEndicott and Spitzer, 1978; Spitzer et al., 1978; Endicott and Spitzer, 1978. or the Structured Clinical Interview for DSM-III-R or DSM-IV ŽSpitzer et al., 1992; First et al., 1995.

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D.J. Buysse et al. r Psychiatry Research 103 (2001) 51᎐67

administered by master’s level psychiatric clinicians. All patients were required to meet a severity threshold of a score G 15 on the Hamilton Rating Scale for Depression ŽHRSD. ŽHamilton, 1967. and a score G 7 on the Raskin Scale ŽRaskin et al., 1969.. Mean scores were 18.5" 3.0 on the 17-item HRSD and 8.7" 1.3 on the Raskin Scale. Patients were excluded if they met criteria for any other Axis I diagnosis, except generalized anxiety disorder, panic disorder or eating disorder NOS, or if they met full criteria for antisocial or borderline personality disorder. Patients with some borderline or antisocial features were, however, included. Patients with current or past substance abuserdependence within the previous 3 years were also excluded. In addition, patients were evaluated with a medical history and physical examination in order to verify that they had no acute or unstable medical problems, and were taking no medications that would cause mood or sleep symptoms. Patients had sleep studies only if they maintained a regular sleep-wake schedule with no rotating or night shift work, as determined by self-report andror sleep-wake diaries. Subjective sleep quality at baseline was assessed using the Pittsburgh Sleep Quality Index ŽBuysse et al., 1989.. Finally, patients were free of all psychotropic medications for at least 2 weeks prior to sleep studies Ž4 weeks for fluoxetine, 1 week for antihistamines and alcohol.. 2.2. Treatment protocol All patients were treated initially with interpersonal psychotherapy ŽIPT. ŽKlerman et al., 1984. and no medications until remission of their episode or until a determination of non-response was made. Treatment consisted of weekly IPT sessions with a master’s or doctoral level clinician, trained by a certified IPT trainer ŽCleon Cornes, M.D... Weekly HRSD ratings were performed by a clinician other than the patient’s therapist. Periodic reliability checks have shown an intraclass correlation of 0.94 for the HRSD total score across seven patients and 14 raters. If HRSD scores did not decrease by G 33% within the first 4 weeks, sessions were increased to twice weekly. Remission was defined by the following conjoint

criteria: HRSD score F 7 and Raskin score of F 5 for 3 consecutive weeks; clinical consensus that the patient was in remission; and a minimum of 12 weeks of IPT. In general, patients were treated for 12᎐20 weeks on a weekly basis to reach remission. The decision to treat with fluoxetine was allowed to be somewhat flexible, given that the major focus of this investigation was on maintenance treatment and recurrence, rather than acute treatment. Fluoxetine treatment was initiated when the patient failed to remit within 6 months Ž24 weeks. of weekly IPT. We also used the following supplementary criteria for initiating fluoxetine: failure to show even a modest response to IPT alone Žless than 25% symptom reduction from baseline HRSD by week 6; less than 50% reduction by week 12; or less than 50% symptom reduction after 4 weeks of weekly IPT followed by 4 weeks of twice per week IPT.; or a relapse during continuation treatment, defined as an HRSD score G 15 for 2 consecutive weeks following initial remission. Patients who met these criteria were treated with continued IPT plus open-label fluoxetine, 10᎐60 mg per day. The mean dose of fluoxetine for patients described in this report was 24.8" 13.2 mg Žmedian 20, range 5᎐600.. Clinical status during acute treatment was also monitored weekly with the Beck Depression Rating Scale ŽBeck et al., 1961. and the Global Assessment Scale ŽEndicott et al., 1976.. For analysis 1, ‘remitters’ included only those patients who achieved remission with IPT alone. Non-remitters included patients who failed to achieve remission with IPT alone, or who were treated with fluoxetine ŽFig. 1.. 2.3. EEG sleep studies Three nights of EEG sleep studies were conducted during subjects’ habitual sleep᎐wake times, determined by self-report andror sleep᎐wake diary. Mean data from nights 2 and 3 were used in analyses of visually scored sleep stages, data from night 2 were used for power spectral analysis. To address aim 1, studies were conducted at pretreatment baseline, while subjects were depressed. To address aim 2, we also examined sleep studies at recovery, when patients were

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55

Fig. 1. Study time line and treatment decision tree.

asymptomatic and medication-free. The standard sleep montage consisted of a single channel of EEG ŽC 3 or C 4 referenced to A 1 ᎐A 2 ., bilateral electro-oculograms ŽEOG. referenced to A 1 ᎐A 2 and bipolar sub-mental electromyogram ŽEMG.. High and low frequency filter setting were 100 and 0.3 Hz for the EEG and EOG signals, and 90 and 10 Hz for EMG, and the 60-Hz notch filter was activated. EEG signals were first low-pass filtered with an anti-aliasing filter Ž70 Hz, 24 dBroctave.. Amplified EEG signals ŽGrass model 7P511. were analog-to-digital converted at a sampling rate of 256 Hz with 12-bit resolution. Digital EEG signals were band-limited to 50 Hz by a digital finite impulse response ŽFIR. filter before being decimated from 256 to 128 Hz. Details

regarding procedures for recording, processing and storing data on PCs have been previously described ŽDoman et al., 1995.. Patients were not routinely screened for periodic limb movements or sleep apnea. However, the histories of patients who were obese or who presented with symptoms suggestive of a primary sleep disorder were discussed with the first author, and additional monitoring for apnea and periodic limb movements was ordered if indicated. Patients with an apnea-hypopnea index of ) 10 or a periodic limb movement arousal index of ) 10 were excluded from further participation. Sleep studies were visually scored in 60-s epochs by technologists who maintained high scoring reliability, as indicated by mean kappa values ) 0.60

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D.J. Buysse et al. r Psychiatry Research 103 (2001) 51᎐67

for various sleep stages and percent agreement between 53% Žstage 1. and 98% ŽREM.. In addition, quantitative analyses of sleep data were conducted using period-amplitude analysis for EEG delta activity and a separate computer algorithm for identification of rapid eye movements during REM sleep ŽDoman et al., 1995.. Digitized EEG signals were also analyzed with power spectral analysis. Awake time, identified by visual scoring in 60-s epochs, was excluded from these analyses. Artifact-laden 4-s epochs were identified by an automated routine ŽBrunner et al., 1996. and also excluded from analysis. EEG power densities were then calculated from the 128-Hz signals for consecutive 4-s epochs in 0.25Hz frequency bandwidths using a Fast Fourier Transform ŽFFT. routine. Artifact-free 4-s power density values were used to calculate mean power density for 0.25-Hz bandwidths during NREM and REM sleep across the entire sleep period. Values for adjacent 0.25-Hz bandwidths were then averaged into 1.0-Hz bandwidths for statistical analysis and graphical display. 2.4. Statistical analyses Clinical and sleep measures among comparison groups ŽIPT remitters vs. non-remitters, IPT recoverers vs. IPT q fluoxetine recoverers. were contrasted using t-tests and ␹ 2-tests. As a first step in comparing the EEG sleep among groups, we confirmed our previously reported findings using principal components analysis on 24 sleep variables, representing both visually scored and period-amplitude measures. A detailed explanation of these procedures is provided in Buysse et al. Ž1998.. Briefly, the PCA identified four domains ᎏ slow wave sleep, sleep continuity, REM sleep and REM latencyrdelta ratio ᎏ which together accounted for 70% of the variability in EEG sleep measures. Differences in EEG sleep measures between groups, reported in Buysse et al. Ž1999a,b., were confirmed by performing t-tests on the factor scores for each of these four components. Significant t-tests from the PCA factors were followed up with t-tests of individual variables loading strongly within the specific multivariate domains. These analyses, which included

analyses of phasic REM, were conducted only to confirm our previously reported findings in a subgroup of the current patient population and to serve as a comparison for findings using power spectral analysis. Analysis of EEG power spectra among groups and across time points was conducted using both traditional EEG frequency bands and regression procedures with fixed knot splines described elsewhere ŽCarrier et al., 2001.. Separate analyses were conducted for aim 1 Žpre-treatment data in IPT remitters and non-remitters . and for aim 2 Žpre-treatment and recovery data in IPT recoverers vs. IPT q fluoxetine recoverers.. For both traditional and regression analyses, EEG power data were natural log-transformed in order to stabilize variance across frequencies and subjects. This also reduces the wide variability in power across EEG frequencies. Both types of analyses examined power averaged across all NREM periods and, separately, power across all REM periods. In other words, data were examined in the frequency domain, and not in the time domain. Analyses of traditional EEG frequency bands involved multivariate analyses of variance ŽMANOVA., repeated-measures analyses of variance ŽANOVA. and t-tests for pre-specified EEG bands Ždelta 0.25᎐4.0 Hz, theta 4᎐8 Hz, alpha 8᎐12 Hz, sigma 12᎐16 Hz, beta 16᎐32 Hz.. Analysis for aim 1 used group ŽIPT remitter, IPT nonremitter. as a factor, and analysis for aim 2 used group ŽIPT recoverers vs. IPT q fluoxetine recoverers., time point Žpre-treatment, recovery. and the group= time point interaction as factors. The regression approach has several advantages compared to tests conducted on individual frequency bands. First, it allows a parsimonious, omnibus test among groups or time points for the entire EEG spectrum across multiple frequencies. In other words, it addresses the question, ‘is spectrum A different from spectrum B?’ Second, it accounts for the functional correlation among adjacent frequency bins, whereas t-tests, ANOVAs or MANOVAs assume functional independence of the different measurements. Finally, it permits the simultaneous examination of several main effects and their interactions Že.g. EEG frequency, group, time point..

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This statistical procedure has several steps. First, power density values were log-transformed to normalize variation. Second, the shape of each subject’s power density spectrum was modeled with fixed-knot regression splines, which are piecewise cubic polynomial functions of frequency connected at points called ‘knots’. The number and location of knots used in the models for NREM and REM sleep were determined by application of the spatially adaptive regression splines ŽSARS. method ŽZhou and Shen, 2001.. SARS was applied separately to the log spectra of each subject. Third, the best-fit model for knot location in the entire group of subjects was determined. In order to do this, the parameters for each subject’s model were applied to the entire group of subjects. The best fit for the entire group was determined by selecting the model with the optimal value for the Bayesian Information Criterion ŽBIC.. For NREM analyses, seven splines were selected, and for REM, six were selected. These splines are not directly interpretable in terms of the spectral EEG data, but rather, are a computationally efficient means to reparameterize the piecewise cubic polynomial functions of EEG frequency. In essence, the splines describe the shape of the entire power spectrum curve. Fourth, an error model was selected. Based on Akaike Information Criterion and Bayesian Information Criterion, a model using an unconstrained error structure was selected. Fifth, statistical analyses were conducted on the modeled EEG power spectrum data. Specifically, analyses were conducted on coefficients of the different splines that modeled each group andror each time point. For aim 1, we used the likelihood ratio test on nested models to test for group, frequency and group= frequency interaction. For aim 2, we tested for these effects as well as evaluation point Žbaseline, recovery.. The effects of group and time point on modeled EEG power spectra data for NREM and REM sleep were examined with a mixed-model analysis. This is a linear regression technique that permits both random and fixed parameters, random effects are those specific to each subject and fixed parameters are those associated with the entire population that our sample represents, e.g.

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group and time point. Mixed models were performed with SAS PROC MIXED.

3. Results 3.1. Demographic and clinical findings Baseline demographic and clinical variables for the IPT remitters vs. IPT non-remitters, and for the IPT recoverers vs. IPT q fluoxetine recoverers, are shown in Table 1. As previously reported in a smaller sample ŽBuysse et al., 1998, 1999a., IPT non-remitters had significantly worse subjective sleep quality, measured by the PSQI; worse social functioning, measured by the GAS; and a non-significant trend toward higher severity, measured by the HRSD-17. As previously reported, demographic and clinical measures did not differ among the matched subgroups of IPT recoverers and IPT q fluoxetine recoverers ŽBuysse et al., 1999b.. 3.2. Aim 1: EEG sleep in IPT remitters ¨ s. IPT non-remitters Multivariate analyses of sleep EEG factors confirmed the results reported for a smaller sample in Buysse et al. Ž1999a.. IPT non-remitters had elevated scores on the REM sleep factor compared to IPT responders Žd.f.s 128, t s 2.87, Ps 0.005., but no significant differences on the delta sleep, sleep continuity or REM latencyrdelta ratio factors. Univariate tests of the sleep variables within the REM sleep factor showed significant group differences for several automated measures of phasic REM activity, all of which were higher in the non-remitter group ŽTable 2.. EEG power spectral analysis was first examined using traditional EEG frequency bands ŽTable 3.. No significant differences were noted between IPT remitters and IPT non-remitters for either NREM sleep or REM sleep. Specifically, no significant differences were noted with MANOVA Žusing the five traditional frequency bands. or t-tests on individual frequency bands. EEG power spectra using fixed-knot regression

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Table 1 Clinical and demographic characteristics of study sample Aim 1: IPT remitters vs. IPT non-remitters Variable

IPT remitters Ž n s 73.

IPT non-remitters Ž n s 57.

t

P

Age Age of onset of MDD Duration of current episode Žweeks. Lifetime number of episodes Hamilton Rating Scale for Depression, 17-item Hamilton Rating Scale for Depression, 25-item Pittsburgh Sleep Quality Index global score Global Assessment Scale

37.9 Ž10.3. 24.8 Ž9.0. 27.9 Ž21.8. median s 22.5 8.2 Ž10.8. median s 4 18.1 Ž2.7.

38.3 Ž10.5. 22.3 Ž8.3. 28.1 Ž18.5. median s 28 8.0 Ž9.4. median s 5 19.1 Ž3.3.

0.22 y1.67 0.30

0.82 0.10 0.76

0.71

0.48

1.80

0.07

22.0 Ž3.7.

22.8 Ž4.2.

1.21

0.23

8.1 Ž3.1.

10.3 Ž3.7.

3.4

0.001

55.8 Ž5.5.

53.4 Ž6.3.

y2.28

0.02

IPT q fluoxetine recoverers Ž n s 23. 37.3 Ž9.1. 22.7 Ž8.2. 32.1 Ž23.6.

t

P

0.00 y0.19 0.50

1.00 0.85 0.62

5.4 Ž3.0.

0.37

0.71

18.2 Ž3.1.

0.43

0.67

21.9 Ž4.3.

0.16

0.88

9.6 Ž3.7.

y1.99

0.17

55.5 Ž5.3.

y0.59

0.56

Aim 2: IPT recoverers vs. IPT q fluoxetine recoverers Variable IPT recoverers Ž n s 23. Age 37.3 Ž9.1. Age of onset of MDD 23.1 Ž7.4. Duration of current episode 28.7 Ž22.3. Žweeks. Lifetime number of 5.1 Ž3.0. episodes Hamilton Rating Scale for 17.8 Ž2.3. Depression, 17-item Hamilton Rating Scale for 21.7 Ž3.2. Depression, 25-item Pittsburgh Sleep Quality 7.6 Ž3.7. Index global score Global Assessment Scale 56.4 Ž4.7.

spline models were compared among IPT remitters and IPT non-remitters using mixed-model analysis. These analyses showed no significant group differences during NREM sleep Ž ␹ 2 s 0.62, d.f.s 1, Ps 0.43. or during REM sleep Ž ␹ 2 s 0.11, d.f.s 1, Ps 0.74., indicating that overall EEG power was not different among the two groups ŽFig. 2.. The model includes the group= EEG frequency interaction term to test whether the two groups have different EEG power spectrum profiles, i.e. different distributions of power across EEG frequencies. The interaction term approached significance in NREM sleep Ž ␹ 2 s 11.98,

d.f.s 7, Ps 0.10., with a suggestion of higher power among IPT non-remitters in the theta Ž4᎐8 Hz. and sigma Ž12᎐16 Hz. ranges. However, as indicated above, univariate tests did not reach traditional levels of statistical significance in these two frequency bands. The group= frequency interaction term was not significant for REM sleep spectra Ž ␹ 2 s 5.35, d.f.s 6, Ps 0.50.. 3.3. Aim 2: EEG sleep in IPT reco¨ erers ¨ s. IPT q fluoxetine reco¨ erers These analyses addressed not only group dif-

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Table 2 Sleep EEG measures in remitters and non-remitters e IPT remitters Ž n s 73.

IPT non-remitters Ž n s 57.

t Žd.f.s 128.

P

Factor 1: slow wave sleep Total delta counts-whole night Ž0.5-2 Hz.a Total delta counts-whole night Ž0.5᎐1 Hz.a Total delta counts-whole night Ž1᎐2 Hz.a Total delta counts-whole night Ž2᎐3 Hz.a Average delta countsrmin-whole night Ž0.5᎐2 Hz.b Total delta counts-NREM 1 Ž0.5᎐2 Hz.a Total delta counts-NREM2 Ž0.5᎐2 Hz.a % Stage 1a % Stage 2a % Stage 3r4a

0.04 Ž1.10. 5287 Ž2215. 2128 Ž800. 3159 Ž1613. 951 Ž797. 17.0 Ž6.8. 1980 Ž1022. 1660 Ž822. 4.3 Ž2.7. 60.3 Ž6.4. 9.8 Ž6.9.

y0.03 Ž0.92. 5870 Ž2830. 2347 Ž1061. 3523 Ž1920. 1131 Ž781. 19.3 Ž8.6. 2252 Ž1437. 1968 Ž978. 4.3 Ž2.3. 59.0 Ž8.0. 10.0 Ž8.6.

0.44 ᎐ ᎐ ᎐ ᎐ ᎐ ᎐ ᎐ ᎐ ᎐ ᎐

0.66 ᎐ ᎐ ᎐ ᎐ ᎐ ᎐ ᎐ ᎐ ᎐ ᎐

Factor 2: REM Automated REM counts-whole nighta Average REM counts-whole nightb REM counts REM 1a REM counts REM 2a % REM REM density ŽREM activityrREM min. REM activity Žwhole night total, visually estimated 0᎐8 per 1-min epoch.a Time spent asleep Žmin.

0.28 Ž0.96. 889 Ž535. 8.0 Ž4.2. 123 Ž169. 191 Ž142. 25.6 Ž4.7. 1.2 Ž0.4. 137.1 Ž62.3.

y0.22 Ž0.98. 1150 Ž655. 10.3 Ž5.0. 209 Ž178. 276 Ž177. 26.7 Ž5.0. 1.3 Ž0.4. 144.9 Ž55.9.

2.87 2.56 2.89 3.47 3.24 1.33 0.86 0.91

417.7 Ž48.5.

413.0 Ž49.0.

Factor 3: sleep continuity Sleep efficiency Žtime spent asleeprtotal recording period.c Awake Žmin. Sleep latency Žmin.d Number of REM periods

0.15 Ž1.05. 90.8 Ž5.9.

Factor 4: REM latencyrdelta sleep ratio REM latency minus awake Žmin.a Delta ratiod

0.005 0.01 0.005 0.0007 0.002 0.19 0.39 0.37

y0.55

0.58

y0.12 Ž0.95. 91.0 Ž5.5.

1.50 ᎐

0.14 ᎐

25.0 Ž26.5. 17.5 Ž12.4. 4.1 Ž0.8.

23.6 Ž21.3. 18.1 Ž14.6. 4.0 Ž0.8.

᎐ ᎐ ᎐

᎐ ᎐ ᎐

y0.05 Ž1.03. 67.2 Ž19.8. 1.6 Ž0.8.

0.04 Ž0.98. 70.4 Ž28.0. 1.4 Ž0.6.

y0.48 ᎐ ᎐

0.63 ᎐ ᎐

a

Means and standard deviations reported in the original units. Transformations used in the analyses: SQRTŽ X q 0.5.. LogŽ X q 0.1.. c LogŽ100 y X q 1.. d LogŽ X q 1.. e t-Tests were initially conducted on the four multivariate factors. Post-hoc tests were conducted for individual sleep variables only if the factor scores were significantly different. b

ferences at baseline, but changes between symptomatic and recovered clinical states in the two groups. Both groups were medication-free at each sleep evaluation point; medications had been tapered and discontinued in the IPT q fluoxetine group prior to sleep studies. We have previously reported that these groups differed in their pattern of REM and SWS factor changes from baseline to recovery, i.e. significant group= time in-

teractions ŽBuysse et al., 1999b.. Briefly, the MANOVA on SWS showed a significant group= time interaction effect Ž F s 2.67, d.f.s 8.37, Ps 0.02., with the IPT q fluoxetine group generally showing larger increases in delta activity from baseline to recovery. No univariate measure in the SWS factor showed a significant group= time interaction, and the only variable to show a significant group difference was stage 2% Žlower in

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60

Table 3 EEG power spectral analysis using traditional EEG frequency bands a IPT remitters Ž n s 73.

IPT non-remitters Ž n s 57.

F Žd.f.s 5, 124. or t Žd.f.s 128.

P-value

0.27

31.8 Ž17.5.

MANOVA F s 1.30 0.98

NREM Delta Ž0.25᎐4 Hz. Theta Ž4᎐8 Hz. Alpha Ž8᎐12 Hz. Sigma Ž12᎐16 Hz. Beta Ž16᎐32 Hz.

28.0 Ž11.9. 2.6 Ž1.2. 1.5 Ž1.0. 0.66 Ž0.33.

3.0 Ž1.5. 1.5 Ž1.0. 0.79 Ž0.51.

1.67 0.25 1.30

0.10 0.80 0.20

0.05 Ž0.03.

0.06 Ž0.04.

0.87

0.39 0.54

6.8 Ž4.5.

6.9 Ž3.1.

MANOVA F s 0.81 0.34

1.5 Ž0.6. 0.68 Ž0.42. 0.24 Ž0.16.

1.6 Ž0.7. 0.74 Ž0.60. 0.27 Ž0.18.

0.84 0.13 0.86

0.40 0.90 0.39

0.07 Ž0.04.

0.07 Ž0.06.

0.24

REM Delta Ž0.25᎐4 Hz. Theta Ž4᎐8 Hz. Alpha Ž8᎐12 Hz. Sigma Ž12᎐16 Hz. Beta Ž16᎐32 Hz. a

0.33

0.73

0.81

Ln used in the analyses. Means and standard deviations reported in their original units Ž␮V rH z ..

IPT q fluoxetine group, F s 4.44, d.f.s 1.44, Ps 0.04.. The REM sleep MANOVA also showed a significant group= time interaction effect Ž F s 2.46, d.f.s 7.38, Ps 0.04.. Univariate contrasts showed significant group= time interactions for five of seven variables in the REM factor, indicating increases from baseline to recovery in the IPT q fluoxetine group, but decreases in the IPT alone group. For instance, total automated REM counts increased from baseline to recovery in the IPT q fluoxetine group Ž1043 " 636 to 1416 " 784. but decreased in the IPT alone group Ž940 " 562 to 825 " 450. Žgroup = time interaction, F s 17.42, d.f.s 1.44, Ps 0.0001.. Automated REM counts per minute, REM%, visually scored REM activity and total automated REM counts in the first REM period showed the same direction of changes. EEG power spectral analysis was first examined with MANOVA and repeated-measures ANOVA using traditional EEG frequency bands ŽTable 4.. MANOVAs for NREM sleep showed no significant group, time or group= time interaction effects. ANOVAs showed a significant group= time interaction in the alpha band Ž F s 4.08, d.f.s 1.44,

2

Ps 0.05., but no other significant group= time interactions. MANOVA for the five frequency bands in REM sleep showed a significant group= time interaction, indicating that the two treatment groups had different patterns of change from baseline to recovery. However, none of the ANOVAs for individual frequency bands showed significant group= time interactions. Mixed-model analyses of fixed-knot regression spline models were also used to compare EEG power spectra among IPT recoverers and IPT q fluoxetine recoverers at baseline and remission time points. For NREM sleep, these analyses showed a significant three-way interaction between group, time and frequency Ž ␹ 2 s 36.3, d.f.s 7, Ps 0.0001. ŽFig. 3.. This interaction indicates that the two groups had different EEG power spectra across the two assessment time points. Inspection of Fig. 2 suggests that the IPT group had an increase in alpha power from baseline to remission, whereas the IPT q fluoxetine group showed a decrease. In addition, the IPT q fluoxetine group appeared to show a larger increase in high-frequency beta activity from baseline to remission. As presented above, repeated-

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61

Fig. 2. Natural log-transformed EEG power density profiles for IPT remitters and IPT non-remitters during NREM sleep Župper panel. and REM sleep Žlower panel.. No significant group differences were noted in the overall power density profile, or in traditional frequency bandwidths Žsee text.. Data are shown as 1-Hz means with standard deviations ŽS.D...

measures ANOVAs did show a significant group = time interaction for alpha Ž F s 4.08, d.f.s s 1, 44, Ps 0.05., but not for beta or other traditional frequency bins. The mixed-model analysis for REM sleep also showed a significant group= time = frequency interaction Ž ␹ 2 s 38.0, d.f.s 6, Ps 0.0001.. Examination of Fig. 2 again suggests higher alpha power in the IPT group, and a greater increase in high-

frequency beta power in the IPT q fluoxetine group. As presented above, analyses of traditional EEG frequency bands did not indicate significant differences.

4. Discussion Results from the current analyses confirm and

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62

Table 4 EEG power spectral analysis with MANOVA and repeated-measures ANOVA using traditional EEG frequency bands a IPT recoverers Ž n s 23.

IPT q fluoxetine recoverers Ž n s 23.

NREM

Delta Ž0.25᎐4 Hz. Baseline Remission Theta Ž4᎐8 Hz. Baseline Remission Alpha Ž8᎐12 Hz. Baseline Remission Sigma Ž12᎐16 Hz. Baseline Remission Beta Ž16᎐32 Hz. Baseline Remission

29.6 Ž9.6. 29.7 Ž9.2.

31.1 Ž17.5. 34.8 Ž24.2.

2.8 Ž0.9. 3.0 Ž1.1.

2.9 Ž1.1. 3.0 Ž1.5.

1.6 Ž0.8. 1.6 Ž0.8.

1.3 Ž0.6. 1.3 Ž0.7.

0.71 Ž0.34. 0.78 Ž0.43.

0.78 Ž0.37. 0.79 Ž0.36.

0.06 Ž0.03. 0.06 Ž0.03.

0.06 Ž0.02. 0.06 Ž0.02.

REM

Delta Ž0.25᎐4 Hz. Baseline Remission Theta Ž4᎐8 Hz. Baseline Remission Alpha Ž8᎐12 Hz. Baseline Remission Sigma Ž12᎐16 Hz. Baseline Remission Beta Ž16᎐32 Hz. Baseline Remission a

8.4 Ž7.3. 6.3 Ž2.6.

6.2 Ž1.9. 7.1 Ž3.8.

1.5 Ž0.6. 1.5 Ž0.5.

1.5 Ž0.6. 1.6 Ž0.7.

0.74 Ž0.32. 0.77 Ž0.35.

0.60 Ž0.29. 0.57 Ž0.28.

0.24 Ž0.10. 0.24 Ž0.10.

0.25 Ž0.10. 0.23 Ž0.08.

0.07 Ž0.04. 0.08 Ž0.06.

0.06 Ž0.02. 0.07 Ž0.02.

ANOVA F Žd.f.s 1.44.

P-value

MANOVA F Group s 1.32 Times 0.96 Group= Times 2.49 Groups 0.00 Times 1.21 Group= Times 0.44 Groups 0.02 Times 0.85 Group= Times 1.16 Groups 2.41 Times 0.11 Group= Times 4.08 Groups 0.40 Times 0.97 Group= Times 0.45 Groups 0.27 Times 1.33 Group= Times 0.11

0.28 0.44 0.06 0.97 0.28 0.51 0.88 0.36 0.29 0.13 0.74 0.05 0.53 0.33 0.50 0.60 0.26 0.75

MANOVA F Groups 2.55 Times 3.75 Group= Times 3.27 Groups 0.21 Times 0.43 Group= Times 2.38 Groups 0.02 Times 0.01 Group= Times 0.02 Groups 3.75 Times 0.05 Group= Times 0.79 Groups 0.00 Times 0.73 Group= Time s 1.13 Groups 0.30 Times 3.20 Group= Times 0.37

0.05 0.01 0.02 0.65 0.52 0.13 0.90 0.92 0.89 0.06 0.82 0.38 0.95 0.40 0.29 0.59 0.08 0.55

Ln used in the analyses. Means and standard deviations reported in their original units Ž␮V 2 rH z ..

extend our previous observations regarding EEG sleep correlates of remission and recovery with psychotherapy and combined psychotherapy᎐antidepressant treatment. Prior to treatment, IPT non-remitters had increased phasic REM sleep compared with remitters. However, EEG power

spectral profiles during REM sleep and NREM sleep did not significantly differ among these groups. Patients who recovered with IPT q fluoxetine had an increase in REM sleep percentage and phasic REM activity following successful treatment and discontinuation of fluoxetine, an

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Fig. 3. Natural log-transformed EEG power density profiles for age-matched IPT recoverers and IPT q fluoxetine recoverers during NREM sleep Župper panel. and REM sleep Žlower panel.. The only significant group= assessment time interaction occurred in the alpha bandwidth during NREM sleep, where the IPT group showed a small increase in power from baseline to remission and the IPT q fluoxetine group showed a decrease Ž F s 4.08, Ps 0.05.. Data are shown as 1-Hz means. Standard deviations are not shown, in order to permit clearer viewing of mean values across groups and time points.

effect that was not seen in patients who recovered with IPT alone. Furthermore, patients who recov-

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ered with IPT q fluoxetine tended to have lower alpha power during both REM and NREM sleep and tended to show increased high-frequency beta power following successful treatment. Overall, measures of phasic rapid eye movement activity and REM sleep percentage were more consistent correlates of treatment response than EEG power spectral profiles during either NREM or REM sleep. Our findings differ from those reported by Luthringer and colleagues ŽLuthringer et al., 1995., who found that pharmacotherapy responders had higher relative delta power and lower relative alpha power compared with non-responders. In addition, responders had lower absolute power across all frequency bands. The only similarity to these findings in our own results was the trend for lower absolute power among IPT remitters in the theta Ž4᎐8 Hz. and sigma Ž12᎐16 Hz. ranges. Beyond the fact that Luthringer and colleagues examined pharmacotherapy response while we focused on psychotherapy remission, other methodological differences may account for some differences between these studies. First, our sample included mildly to moderately depressed women outpatients, whereas Luthringer and colleagues studied severely depressed inpatients, including almost equal numbers of men and women. Several investigators have commented on the more severely disrupted EEG sleep patterns of depressed men compared with women Že.g. Armitage et al., 2000a,b. and of inpatients compared with outpatients Že.g. Buysse and Kupfer, 1990; Reynolds et al., 1982.. Other relevant differences include different sample sizes, different criteria for defining remission or response, considering NREM and REM sleep separately or in combined fashion and the use of absolute vs. relative EEG power. Finally, our analyses were based on both traditional band-wise analyses and the profile of the entire EEG frequency spectrum as captured by flexible regression models, whereas Luthringer and colleagues used analyses based on four EEG frequency bands. The differences between remitters and non-remitters in phasic REM activity, but not in NREM or REM EEG power, may be understandable from a neurobiological basis. REM sleep occurs

64

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as the result of integrated activity in pontine ‘REM on’ and ‘REM off’ neuronal groups Žreviewed in Siegel, 2000.. In particular, pontogeniculo-occipital ŽPGO. spikes and phasic eye movements arise from pedunculopontine nuclei ŽSiegel et al., 1984; Shouse and Siegel, 1992. and are stimulated by the application of cholinergic agents to this region ŽBaghdoyan et al., 1987.. Thus, phasic REMs are essentially a brainstem phenomenon. By contrast, the activated, low-voltage EEG pattern of REM sleep results from widespread cholinergic activity in the brainstem reticular formation, thalamic nuclei and basal forebrain, as well as non-cholinergic activity in thalamocortical and cortical neurons ŽSteriade, 2000.. Hippocampal theta activity and EEG activation, two of the hallmarks of the REM sleep state, can both occur when the forebrain is disconnected from the pons ŽOlmstead and Villablanca, 1977.. Moreover, human positron emission tomography studies show activation of medial frontal cortical and limbic system structures during REM sleep ŽMaquet et al., 1996; Nofzinger et al., 1997.. Thus, the EEG characteristics of REM sleep rely on both brainstem and cortical mechanisms. In human sleep studies, including the present study, quantitative eye movement activity provides a relatively direct measure of brainstem activation. On the other hand, EEG signals, even when measured with quantitative techniques such as power spectral analysis, reflect summed cortical activity with little spatial localization. These EEG signals are the end result of integrated activity in brainstem, diencephalic and cortical structures. This suggests that quantitative eye movement data may present a more direct measure of brainstem activation and, in particular cholinergic activation than quantitative EEG measures which are multiply determined. Thus, the increased REM activity seen in IPT treatment non-responders may indicate a dysregulation of brainstem cholinergic and monoaminergic mechanisms not reflected in the more complex activity represented by EEG power. Furthermore, pontine nuclei involved in REM generation are reciprocally connected to limbic structures such as the central nucleus of the amygdala Žreviewed in

Calvo and Simon-Arceo, 1999., suggesting that eye movement activity during REM sleep may also be related to activity in these emotion-regulating centers. Therefore, phasic REM activity may reflect aspects of affective disturbance related to treatment responsiveness. The different patterns of NREM EEG change seen with treatment in IPT recoverers compared with IPT q fluoxetine recoverers is of uncertain significance. The decrease over time in alpha activity in the latter group may represent a persistent effect of prior treatment with fluoxetine. We have previously observed that the number of eye movements, and the percentage of REM sleep, also increased in this group following discontinuation of fluoxetine ŽBuysse et al., 1999b.. Other investigators have noted variable effects of antidepressant treatment on PSA. For instance, chronic treatment with the SSRI antidepressant citalopram was associated with reduced EEG power across all frequencies ŽNeckelmann et al., 1996., fluoxetine was associated with reduced delta amplitude and increased beta amplitude ŽHoffmann et al., 1999. and trazodone was associated with reduced sigma power and a trend toward increased delta power Žvan Bemmel et al., 1995.. There are fewer data regarding the persistence of EEG sleep changes with SSRI antidepressants, and none that we are aware of regarding PSA findings. After a post-fluoxetine drug-free interval of 7 weeks, approximately twice as long as ours, Trivedi et al. Ž1999. found that REM% and REM density were not significantly different from the baseline Žacutely depressed. state. Thus, our studies 4 weeks after discontinuation may have captured patients during a ‘rebound’ phase that would resolve by 7 weeks. The slightly higher amount of theta and alpha activity in IPT recoverers, seen during both NREM and REM sleep ŽFig. 2., may be a marker of differential treatment responsiveness to IPT as opposed to IPT q fluoxetine. However, the fact that this finding was seen in the closely agematched groups of IPT recoverers vs. IPT q fluoxetine recoverers ᎏ but not in the larger group of IPT remitters vs. IPT non-remitters ᎏ casts doubt upon its clinical or prognostic significance as a general predictor. Luthringer et al.

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Ž1995. noted a trend toward reduced absolute EEG power in all bands, including theta and alpha, among pharmacotherapy responders. However, their reference group was pharmacotherapy non-responders, which is likely to be a very different group from patients who recover with IPT. Our regression model and statistical approach to PSA data offer some potential advantages over more traditional approaches. For instance, modeling the EEG data with fixed-knot regression splines allows us to model the entire EEG spectrum, rather than deciding on a priori bands. We have previously observed that age-related EEG changes do not necessarily conform to these traditional bands ŽCarrier et al., 2001.. The regression approach also permits an omnibus test across a large frequency range, to determine whether two PSA profiles differ from each other. We suggest that the regression approach may be a good first step toward analyzing PSA data. Significant differences could then be followed up with targeted univariate tests in bands of interest. The finding of significant differences even when mean differences are small Že.g. Fig. 2. suggests the sensitivity of this approach. Limitations of the current study include: Ž1. The study sample included only women outpatients with mild to moderate severity of depression, and treatment with psychotherapy. These subjects are representative of typical clinical populations, but our findings may not pertain to more severely depressed patients, men, or patients treated with other modalities. Ž2. The study did not involve randomized or blinded treatment assignment. Our findings with regard to aim 2 must be interpreted cautiously, given that the IPT q fluoxetine group experienced sequential, openlabel treatment. Ž3. The study used a single central EEG channel, which does not reflect hemispheric or regional variations in EEG power. Ž4. There was no routine evaluation for sleep disordered breathing. In summary, we found that quantitative measures of eye movement activity during REM sleep are a more robust correlate of remission and recovery in depressed women treated with IPT or IPT q fluoxetine. Quantitative REM measures may be a more accurate indicator of brainstem

65

dysregulation in cholinergic and monoaminergic neuronal systems than EEG activity, which reflects integrated brainstem, cortical and limbic activity. In the future, it will also be important to develop clinical correlates of increased phasic REM activity as a means of prospectively identifying patients at increased risk for treatment nonresponsiveness.

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