نوار مغزی REM منتج از خواب مشتق شده به عنوان یک نشانگر برای پاسخ به درمان در افسردگی - مطالعه ناتورالیستی بعد از داروهای ضد افسردگی

Objective To evaluate whether prefrontal cordance in theta frequency band derived from REM sleep EEG after the first week of antidepressant medication could characterize the treatment response after 4 weeks of therapy in depressed patients. Method 20 in-patients (15 females, 5 males) with a depressive episode and 20 healthy matched controls were recruited into 4-week, open label, case–control study. Patients were treated with various antidepressants. No significant differences in age (responders (mean ± SD): 45 ± 22) years; non-responders: 49 ± 12 years), medication or Hamilton Depression Rating Scale (HAM-D) score (responders: 23.8 ± 4.5; non-responders 24.5 ± 7.6) at inclusion into the study were found between responders and non-responders. Response to treatment was defined as a ≥50% reduction of HAM-D score at the end of four weeks of active medication. Sleep EEG of patients was recorded after the first and the fourth week of medication. Cordance was computed for prefrontal EEG channels in theta frequency band during tonic REM sleep. Results The group of 8 responders had significantly higher prefrontal theta cordance in relation to the group of 12 non-responders after the first week of antidepressant medication. This finding was significant also when controlling for age, gender and number of previous depressive episodes (F1,15 = 6.025, P = .027). Furthermore, prefrontal cordance of all patients showed significant positive correlation (r = 0.52; P = .019) with the improvement of HAM-D score between the inclusion week and fourth week of medication. Conclusions The results suggest that prefrontal cordance derived from REM sleep EEG could provide a biomarker for the response to antidepressant treatment in depressed patients.

The lifetime prevalence of major depressive disorder (MDD) in United States is 16.6% (Kessler et al., 2005). Unfortunately, approximately 50% of patients with MDD do not respond to initial treatment (Trivedi et al., 2006 and Zajecka, 2003) and it takes usually 4 weeks to evaluate whether a patient responded to therapy (Gelenberg and Chesen, 2000 and Souery et al., 2007). It is therefore of great interest to find biomarkers which could characterize treatment outcome in much shorter time. Several biomarkers that have the potential to maximize treatment effects and minimize adverse reactions emerged from academic research. Previous studies have discovered genetic (Kirchheiner et al., 2004 and Uhr et al., 2008) and systemic markers such as quantification of proteins, lipids and carbohydrates as well as measures from neuroimaging, endocrinology and sleep-electroencephalography (EEG) (Dresler et al., 2014 and Holsboer, 2008). However, biomarkers are still not used in daily psychiatric practice and the initial medication is tested for several weeks on a trial-and-error basis. A further possibility to improve this situation is offered by quantitative electroencephalography (QEEG) obtained from awake patients (Leuchter et al., 2010). Among others, cordance (Leuchter et al., 1994) is a promising candidate to characterize the treatment response. Cordance correlates with regional brain activity by combining information from the absolute and relative EEG spectral power. It was shown that cordance computed for theta (4–8 Hz) frequency band has a positive correlation with cerebral perfusion (Leuchter et al., 1999). Depressed patients compared to controls were found to have significantly higher theta cordance in the prefrontal midline region (Cook et al., 2014). Furthermore, prefrontal theta cordance was reported to be a promising correlator of antidepressant treatment outcome. In several studies, responders showed a significant decrease in prefrontal theta cordance as measured during wakefulness after the first week of therapy when compared to baseline, irrespective of investigated medication (Bares et al., 2010, Bares et al., 2008, Bares et al., 2007 and Cook et al., 2005 and Cook et al., 2002). However, the waking state is characterized by a wide variance of sub-states ranging from alert over relaxed wakefulness to drowsy-awake. These sub-states are composed of heterogenous EEG characteristics and they differ in function as indicated by fMRI (Olbrich et al., 2009). Therefore, measuring a more homogenous state of consciousness has the potential to increase the discrimination power of cordance. Tonic rapid eye movement (REM) sleep is such a homogenous state and can be characterized by objective and clear-cut criteria (American Academy of Sleep Medicine (2009)); lack of rapid eye movements, muscle atonia and a low-amplitude EEG with mixed frequencies. Prefrontal theta cordance may reflect activity of prefrontal cortex and anterior cingulate cortex (ACC) (Asada et al., 1999), which both seem to be crucial in MDD (Drevets, 2000 and Drevets, 1999). Particularly increased rostral ACC (rACC) activity at baseline was shown to be a marker of antidepressant treatment response backed by the emerging evidence indicating that the rACC represents one of the main ‘hubs’ within the default network, an intrinsically organized functional network that has been associated with a variety of self-referential processes like brooding (Pizzagalli, 2011). During REM sleep, the ACC activity level is maximal, whereas the surrounding frontal cortex activity is minimal (Braun et al., 1997 and Hobson and Pace-Schott, 2002). Furthermore, during REM sleep, ACC has prominent oscillatory activity in the theta frequency band (Nishida et al., 2004) marking an ideal frequency band to be detected by the prefrontal theta cordance. Therefore, the aim of this study was to measure the prefrontal theta cordance during tonic REM sleep. We hypothesized that at the end of the first week of antidepressant treatment, absolute prefrontal theta cordance values could differ between responders compared to non-responders.

Eight of the 20 patients responded to antidepressant treatment. Responders had a significantly lower final HAM-D score after 4 weeks than non-responders (P < .001). There were no significant differences between the groups in other clinical and demographic characteristics ( Table 1). Use of medication with (e.g. escitalopram) ( Gursky and Krahn, 2000) and without (trimipramine, mirtazapine and bupropione) ( Nofzinger et al., 1995, Schmid et al., 2006 and Sonntag et al., 1996) REM sleep-suppressing effects was balanced between responders and non-responders. To avoid withdrawal effect, none of the responders but one of the non-responders had low unchanged dosages of an anxiolytic medication (Lorazepam 1.0 mg/d). Table 1. Demographic, clinical, conventional and quantitative EEG sleep parameters of responders, non-responders and healthy controls after one week of antidepressant medication. Responders (N = 8) Non-responders (N = 12) Comparison subjects for responders (N = 8) Comparison subjects for non-responders (N = 12) Analysis Ratio Ratio Ratio Ratio pa Gender (Female: Male) 7: 1 8: 4 7: 1 8: 4 ns Diagnose (Recurrent Affective Disorder: First Episode) 6: 2 10: 2 ns Antidepressant medication (REM-suppressing: REM-not-suppressing) 6: 2 8: 4 ns Mean (SD) Mean (SD) Mean (SD) Mean (SD) pb Age (years) 45.2 (22.1) 49.1 (12.6) 44.9 (21.6) 49.0 (12.8) ns Previous depressive episodes 3.1 (3.4) 2.7 (2.8) 0 (0) 0 (0) ns HAM-D at inclusion 23.8 (4.5) 24.5 (7.6) ns HAM-D at week 1 19.0 (7.6) 23.1 (6.7) ns HAM-D at week 4 6.1 (5.0) 20.2 (5.7) <0.001 Sleep continuity (minutes) pb pc pd Sleep onset latencye 1.30 (0.23) 1.13 (0.54) 0.92 (0.19) 1.00 (0.33) ns 0.003 ns Total sleep time 428.7 (24.4) 404.1 (49.2) 438.6(25.7) 427.0(46.3) ns ns ns Sleep period time 463.5 (10.0) 464.7(19.3) 466.1(25.2) 466.2(22.2) ns ns ns Sleep efficiencyf 89.6 (5.3) 84.3 (10.2) 91.2 (5.1) 89.4 (10.2) ns ns ns Sleep architecture (minutes) REM latencye 2.16 (0.53) 2.11 (0.42) 1.93 (0.13) 1.90 (0.33) ns ns ns REM duration 65.0 (56.8) 48.1 (24.9) 87.1 (23.3) 91.88 (21.3) ns ns <0.001 Stage 1 sleep duration 58.1 (17.3) 55.1 (24.3) 41.1 (10.8) 46.7 (22.1) ns 0.034 ns Stage 2 sleep duration 233.5 (41.6) 220.7 (55.7) 224.3 (28.9) 223.6 (43.1) ns ns ns Slow wave sleep latencye 1.43 (0.14) 1.51 (0.27) 1.54 (0.14) 1.56 (0.24) ns ns ns Slow wave sleep duration 71.0 (38.2) 79.2 (58.4) 85.0 (45.9) 63.5 (36.7) ns ns ns Rapid eye movement density 1.79 (1.28) 3.02 (1.78) 1.49 (0.74) 1.86 (0.93) ns ns ns Absolute prefrontal power in theta (4–8 Hz) band (μV²)e,g 0.51 (0.23) 0.51 (0.21) 0.53 (0.21) 0.47 (0.21) ns ns ns Relative prefrontal power in theta (4–8 Hz) bande,g,h 11.4 (6.1) 9.0 (4.3) 12.4 (2.8) 10.1 (5.5) ns ns ns Responders fulfilled criterion of decreased HAM-D score of at least 50%. a Fisher Exact test, two-tailed, between responders and non-responders. b T test, two-tailed, unpaired, between responders and non-responders. c T test, two-tailed, unpaired, between responders and matched healthy controls. d T test, two-tailed, unpaired, between non-responders and matched healthy controls. e Logarithm (base 10) transformed data prior to analysis. f Sleep efficiency is the ratio of sleep to time spent in bed showed as percentage. g The mean value from 2 prefrontal electrodes (Fp1, Fp2) in theta frequency band. h Percentage of total power in 0.5–20 Hz frequency range.