Sleep EEG recordings in depressive disorders

Journal

oJA//ective

Disorders,

9 (1985)

47-53

47

Elsevier

JAD 00300

Sleep EEG Recordings M. Kerkhofs’, ’

Department

G. Hoffmann’,

in Depressive

V. De Martelaere

of Psychiatry Sleep Unit, Erasmus

Hospital,

Disorders

2, P. Linkowski’

and J. Mendlewicz’

Universrty Clrnics of Brussels and .’ I. R. B. H. N. Facult_p of Medium,

Free

Universgy of Brussels. Brussels (Belgrum)

(Received 17 August, 1984) (Revised, received 13 November. 1984 (Accepted 20 November, 1984)

Summary Sleep polygraphic recordings were performed during 3 consecutive nights in a sample of 43 affectively ill inpatients. The patients were classified as major (n = 36) or minor depressive disorder (n = 7) according to the Research Diagnostic Criteria. Among the 36 patients with a major depressive disorder, 14 were in remission at the time of the sleep investigation. A two-way analysis of variance was performed to assess night and diagnostic effect on sleep variables. Shortening of REM latency was observed in depressed patients with major depressive disorder when compared to major depressive disorder patients in remission. Depressed patients with major depressive disorder also showed higher REM activity and REM density values than patients with minor depressive disorder. According to the linear discriminant analysis, sleep variables were able to correctly classify 68% of the patients.

Key words:

Depressive disorders - REM sleep - Sleep EEG

Introduction Sleep polygraphic recordings in depressed patients have shown disturbances in sleep continuity, sleep architecture and REM sleep. Depressed patients have a longer sleep latency, a greater number of stage shifts, more awake time during the night, early morning awakening, less delta sleep than normal subjects (Kupfer et al. 1978; Chen

This work was supported by grants from the FRSM and The Association of Mental Health Research. Correspondence to: M. Kerkhofs, Department of Psychiatry Sleep Unit, Hopital Erasme, University of Brussels, Route de Lennik 808, 1070 Brussels, Belgium. 01650327/85/$03.30

0 1985 Elsevier Science Publishers

1979; Duncan et al. 1979; Gillin et al. 1979, 1980). Although discrepant findings have been reported for REM time in depression (Chen 1979) shortening of REM latency has been described as a specific marker both for primary depression (Kupfer et al. 1978; Akiskal et al. 1982) and endogenous depression (Feinberg et al. 1982; Rush et al. 1982). Shortening of REM latency has also been inversely correlated with severity of depression (Coble et al. 1981) and plasma cortisol levels after dexamethasone (Mendlewicz et al. 1984).I Increased Dhasic \ activity during REM sleep particularly during the first REM period, has been observed in primary depression as compared to secondary depression (Kupfer et al. 1978) and normals (Gillin et al.

B.V. (Biomedical

Division)

48

1981). Environmental changes and stress may also affect REM sleep and night by night variability has been reported for sleep variables in psychiatric patients (Kupfer and Foster 1978). Although nonsignificant night by night variations have been shown in primary depressed inpatients, a shortening of REM latency during the second recording night of outpatients with secondary depression has been reported by Coble et al. (1976) and by Reynolds et al. (1983) for older patients with major depression. The purpose of the present study was to investigate sleep variables across 3 successive nights of recording in a sample of well characterized affectively ill patients studied during a depressive episode and in remission. Methods

Forty-three patients aged 19-60 years consecutively admitted in the sleep unit of our department of psychiatry for a depressive episode were included in this study, after giving their informed consent. Thirty-six patients met the Research Diagnostic Criteria (Spitzer et al. 1978) for a primary major depressive disorder (MDD) and 7 patients had minor depressive disorder (mDD). Severity of depression was evaluated with the Hamilton Rating Scale for Depression (NIMH 24-Item Form)(Hamilton 1968). All the patients were free of drugs for at least 2 weeks before the sleep recordings. Obese patients or patients with somatic

TABLE

Sleep

After one accommodation night, sleep was recorded during 3 consecutive nights. Ordinary conditions of lighting. temperature and sound proofing were maintained. Patients were not allowed to take naps during the day. Night technicians applied electrodes between 21.30 h and 23.00 h. Patients went to sleep at their usual time and awoke spontaneously. The electroencephalogram (EEG). electromyogram (EMG) and electrooculogram (EOG) were recorded on a polygraph (Mingograph Siemens) at the rate of 15 mm/s. For the EEG, occipital, central and frontal leads were used. For the EMG. the electrodes were placed on the point of the chin and for the EOG. the electrodes were applied to the upper and lower canthi. Sleep analysis was made following the criteria of Rechtschaffen and Kales (1968) by an experienced reader, blind to the diagnostic category of the patient. The sleep variables studied

1

CLINICAL

CHARACTERISTICS

Diagnosis (RDC) Number

disorders were not included in the study as well as patients who had used neuroleptics, MAO inhibitors or lithium salts in the last 3 months. Among the 36 patients with a MDD. 22 were investigated during a depressed phase (Hamilton score above 20) of whom 19 were endogenous and 3 non-endogenous, while 14 patients showed a remission during the 2 weeks wash-out period preceding the investigation (MDR, Hamilton score below 10). The clinical characteristics of our sample are illustrated in Table 1.

of patients

OF AFFECTIVELY

ILL PATIENTS

M~JCXdepressive disorder

Major depressive disorder in remission

Minor depressive disorder

(MDD)

(MDR)

(mDD)

22 (19 endogenous) (3 non-endogenous)

14

I

M&S

12

3

4

Females

10

11

3

Age range (yr) XkSD Hamilton xiSD

23-60

24659

19-59

41 f 10

43ill

3x*13

rating 35ilh

x*

1

21+

2

49 TABLE

2

EEG SLEEP VARIABLES

Sleep continuity 1. Time In Bed (TIB) (min): 2. Sleep Onset Latency (SOL) (mm): 3. Sleep Period Time (SPT) (min): 4. Total Sleep Time (TST) (min): 5. Number of Awakenings: 6. Length of Awakenings (min): 7. Number of Stage Shifts: 8. Sleep Efficiency Index (SEI):

time from the lights out until standing up. time from lights out until the appearance of the first 20 s of stage 1. TIB - (SOL+ time awake before standing up). SPT - awake time during the night. NA LA NSS ratio of TST to TIB X 100.

Sleep urchrtecture 1. Minutes of each stage of sleep. 2. Percentage of each stage of sleep expressed REM 1. 2. 3. 4. 5. 6. 7.

sleep REM latency I (RL I): REM latency II (RL II): REM activity (RA): REM REM REM REM

activity I and II: density (RD): density I and II: activity/TST:

as a ratio to TST.

minutes from the first stage 1 until the first REM epoch. minutes from the first stage 2 until the first REM epoch. each 40-s period of REM sleep is scored on a O-8 point scale for the REM patterns: REM activity value is determined by the sum of scores for the whole night. value of REM activity for the first and the second half of the WT. respectively. ratio of REM activity to the total duration of REM sleep. value of REM density for the first and the second half of the SPT, respectively. ratio of RA to TST.

were grouped into sleep continuity, sleep architecture and REM sleep as illustrated in Table 2. Statistics

Two-way analysis of variance was performed on each sleep variable to assess night and diagnostic effects. Contrasts between diagnosis of MDD and mDD and between diagnosis of MDD and MDR were evaluated by a z-test. A pooled variance estimate was used in the denominator of t, except when the Fisher’s statistic between the variances led to the conclusion that the homogeneity of variance assumption was not respected. In this case a separate variance estimate was used. Linear discriminant analyses were performed between the 3 diagnostic groups. The variables introduced first were all the sleep variables except the percentage of sleep stages. In a second analysis the variables introduced were the REM latency and the REM density. For every patient, the variables of all successive nights were analysed. A case is thus defined by the set of values observed for each variable, per patient and per night. A stepwise

method was used. The stepwise selection criterion was Rao’s V generalized distance. The efficiency of the discriminant function so selected was further investigated by using the discriminating variables to classify the nights into the 3 diagnostic groups. All these computations were performed with the use of the SPSS (Statistical Package for the Social Sciences) programs (Nie et al. 1975). Chi-square tests were used to compare distributions of REM latency. Results The two-way analysis of variance did not show any significant night effect on sleep variables in our depressed patients. However, a trend to a shortening of REM latency from the first to the second and third night was observed in patients with MDD and in patients with mDD, but not in patients in remission (MDR). This difference did not reach statistical significance (P = 0.092) (Table 3). There was a diagnostic effect for the SOL (P = O.OOl), REM latency II (P = 0.029) REM

50 TABLE REM

3 LATENCY

Nights

VALUES

IN DEPRESSED

PATIENTS

ACROSS

3 SUCCESSIVE

NIGHTS

OF RECORDING

Diagnosis MDD

(n = 22)

MDR

(n = 14)

mDD

RL I

RLI

RL II

RL II

1

91.8 + 23.3

84.6+ 21.4

2

45.3&

7.8

41.8?

7.6

98.6 + 20.6

Y3.Oi 19.6

3

50.9f

9.2

45.9+

8.7

102.6 I 21.4

100.9 k 20.9

(n = 7) RL II

RLI

X~SEM

TABLE

104

+22.1

101.7&22

8x.5+11.9

84.8 + 10.8

65.5+

59.7+

6.8

58.7 _t 22.7

6.6

58.1 ? 22.6

4

SLEEP VARIABLES

IN DEPRESSED

Sleep variables

PATIENTS

MDD

(57 nights/

22 patients)

MDR

(31 nights/

14 patients)

mDD

(17 nights/

7 patients

ANOVA (P)

X*SEM

(I) Sleep continuity TIB (min)

456.8

+

8.6

436.6

SOL (min)

29.5

k

3.5

24.2

i 15.26

SPT (min)

427.9

i

7.9

411.5

+ 15.1

422.4

f 14.7

NS

TST (min)

349.8

+ 10.9

358.5

f 16.63

379.2

+ 16.9

NS

?

3.4

479.4

NA

23.7

?

2.3

16.7

+

2.4

20.6

TA (min)

78.1

+ 10.8

53.4

i

9.7

43.24*

~tr 9.5

135.8

NSS

183.5

SE1

76.8

*

2.08

k 12.8

81.8

*

2.2

* 10.71

78.1

f 10.11

k

6.69

42.1

f

7.87

191.42+

& 12.78

NS

k

0.0002

56.9

*

164.9

8.54

3.15

NS

6.9

NS

+ 15.7

0.013

k

2.07

NS

100.22 f

9.32

53.94 +

7.44

78.7

(2) Sleep archttecture Time of stage awake (min)

107.7

1

57.7

2

161.37+

3

27.7

+

2.6

24.92 f

2.91

34.06 k

4.82

NS NS NS NS

4

23.7

+

3.7

21.47 *

4.06

35.67 +

7.33

NS

REM

73.02 k

4.88

72.51 k

5.44

61.47 *

6.6

NS

% stage A

32.9

*

3.62

24.8

& 3.84

28.41 f

3.57

1

16.8

+

1.68

12.37?

1.08

14.12*

1.92

NS NS

2

46.63 +

1.94

53

f

2.21

49.49*

3.18

NS

3

7.84+

0.71

f

0.82

8.24+

1.16

NS

6.44+

0.97

6.11 f

1.27

10.24k

1.95

20.69*

1.19

20.07 +

1.26

16.12k

1.67

NS NS

4 REM

6.9

3.86 12

188.27 + 15.23

(3) REM sleep RL I (min)

63.56 +

9.63

RL II (min)

58.31f

8.9

RA

87.15 k 11.9

102.12 i 12.5

7.45

0.037

98.71 + 12.25

68.17*

72

+

7.2

0.018

61.22?

8.93

32.05 +

6.46

0.019

RD

1.05&

0.11

0.885

0.14

0.47*

0.09

0.023

RAI

40.08 +

7.99

24.87+

5.5

7.88+

2.62

0.041

RA II

47.07?

6.69

36.35*

5.1

1.01*

0.14

0.74+

0.17

0.37*

RD II

1.11 i

0.11

0.94*

0.14

0.57+

0.12

NS

RA/TST

0.24*

0.03

0.19+

0.04

0.07*

0.01

0.018

RDI

25.94i

6

NS

0.09

0.047

51

activity (P = 0.024) REM density (P = 0.026) REM activity I (P = 0.046) and REM activity/ TST (P = 0.022). The interaction night/diagnosis was never significant. A one-way analysis of variance was then performed to compare the 3 groups of patients. As illustrated in Table 4, a diagnostic effect was observed for the above variables but also for the NSS (Number of Stage Shifts) (P = 0.013) and for REM latency I (P = 0.037). The analysis of contrasts showed that, when compared to patients with a MDR, patients with a MDD had significantly more stage shifts (P = 0.004), shorter REM latency I (P = 0.017) and shorter REM latency II (P = 0.010). A longer sleep onset latency was observed in patients with mDD than in patients with a MDD. When compared to patients with mDD patients with a MDD had higher REM activity (P = 0.001) REM density (P = 0.006) REM activity I (P = O.OOl), and REM activity/TST (P = 0.001). A linear discriminant analysis between the 3 diagnostic groups was then performed. All sleep variables except percentage of each stage were introduced as variables. Two discriminant functions were derived. The following variables: sleep onset latency, REM activity, stage 3 and 4, REM latency II, time awake, number of stage shifts were retained by the stepwise linear discriminant analysis. Table 5 shows the classification obtained. Seventy one cases (variable per patient and per night) (68%) were correctly classified; 42 cases (74%) were correctly classified in the group of patients

>, 10 20 30 LO 50 60 70 80 90 100 110 120 > REM

Fig. 1. Distribution

of REM latency

TABLE

5

CLASSIFICATION OF CASES BY THE TWO DISCRIMINANT FUNCTIONS USING ALL SLEEP VARIABLES Diagnosis

Discriminant

function

MDD

MDR

mDD

MDD MDR mDD

42 12 6

10 19 1

5 0 10

TABLE

II values in patients

Total

57 31 17

6

CLASSIFICATION OF CASES BY TWO DISCRIMINANT FUNCTIONS USING REM LATENCY II AND REM DENSITY Diagnosis

MDD MDR mDD

Discriminant

function

MDD

MDR

mDD

42 16 4

2 5 0

13 10 13

classification

Total

57 31 17

with MDD, 19 (61%) in the group of patients with MDR and 10 (59%) in the group of patients with mDD. A second discriminant analysis was performed using REM latency II and REM density only. Table 5 shows that these two variables are sufficient to classify 74% of cases in the group of patients with MDD. However, only 16% of cases in the group of patients with a MDR were cor-

>,I020 30 40 50 60 70 80 90100110120, LATENCY

classification

(min)

with a MDD (0) and in patients

with a MDR (8)

52 rectly classified. Figure 1 illustrates the distributions of nights for various values of REM latency II in the group of patients with MDD and MDR. These two distributions are significantly different (x2 = 23.3, df= 1, P = 0.05) and shorter REM latencies are more often found in the group of depressed patients with a major depression (MDD) than in remission (MDR). Discussion

Our data suggest that sleep EEG variables are generally stable across successive nights of recording in our sample of depressed patients. However, a trend toward shortening of REM latency during the two last nights was observed mainly in the depressed patients but not in patients in remission, suggesting the presence of accommodation effects in our depressed patients. Similar results were reported by Coble et al. (1976) in secondary depressed outpatients recorded during two consecutive nights. Furthermore our data show specific REM sleep anomalies in patients with major depressive disorder, characterized by a shortening of REM latency and increased REM activity and REM density, confirming previous studies of Kupfer et al. (1978) and Gillin et al. (1979, 1981). According to Schultz et al. (1979) REM latency tends to normalise during remission from depression. We also report almost normal values for REM latency in patients in recent remission from depression although these patients had not been studied during a depressive episode. We did not observe any difference in the amount of slow wave sleep between the groups of patients. We have also shown that sleep EEG variables can correctly classify 68% of cases in our sample. However, the discriminant function using REM latency II and REM density alone could correctly classify only 57% of all cases. This drop in the accuracy of the classification was mainly due to the lack of recognition of patients in remission using REM variables alone, indicating the utility of sleep continuity variables in the discrimination of patients in remission from depressed patients. Although our 3 groups of patients were of similar age, it is important that age be considered in further sleep studies since Ulrich et al. (1980) and Gillin et al. (1981) have described changes

with age in sleep variables. Our data also raise the question of the number of nights of recording needed to obtain reproducible sleep data in depressed patients, particularly in the case of REM variables. Our findings need to be confirmed on large samples of affectively ill patients including agematched non-psychiatric controls, to assess the influence of other factors potentially affecting sleep EEG such as age, past depressive episodes, family history of affective illness and previous treatment with psychotropic drugs. Acknowledgements

We thank Mrs. M. Remy and Mrs. M. De Tremerie for technical assistance and Mrs. M. Desmedt for secretarial assistance. References

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