The serotonin transporter promoter polymorphism (5-HTTLPR) affects the relation between antidepressant serum concentrations and effectiveness in major depression.

INTRODUCTION: Both the serotonin transporter promotor polymorphism (5-HTTLPR) and serum concentrations of SSRIs have been shown to affect response to SSRIs. Results, however, are inconsistent. The aim of this study was to investigate whether remission or response to SSRIs is influenced by an interaction of 5-HTTLPR and SSRI serum concentrations. METHODS: 49 patients with major depression and SSRI treatment were genotyped for the 5-HTTLPR locus including the rs25531. Drug serum concentrations and depression severity were measured weekly. RESULTS: Logistic regression analysis revealed a significant association between 5-HTTLPR, SSRI serum concentrations and response to treatment. A favourable treatment outcome correlated with SSRI serum concentration in 5-HTTLPR-L(A) allele carriers (r² = 34.3 %; p = 0.001), but not in S/L(G)-allele carriers (p = 0.31). DISCUSSION: In the group of L(A) allele carriers, those MDD patients with a high antidepressant serum concentrations responded better to treatment than patients with a low serum concentration. We conclude that the 5-HTTLPR might affect reponse to SRRI subject to serum concentrations. If replicated this might be a starting point for prospective clinical trials.

Subchronic effects of olanzapine on sleep EEG in schizophrenic patients with predominantly negative symptoms.

BACKGROUND: It is well known that sleep disturbance is an integral symptom of schizophrenia. In recent studies, a deficit of delta sleep has been observed in schizophrenic patients. Antipsychotic drugs with serotonin (5-HT2) receptor-antagonistic properties are considered to have delta sleep promoting effects. We have investigated the effects of subchronic olanzapine treatment on sleep EEG in schizophrenic patients. METHODS: The effects of administration of olanzapine (15 to 20 mg) on sleep were studied for four weeks in 10 male, drug-free patients suffering from schizophrenia with predominantly negative symptoms. Conventional sleep EEG parameters were investigated at baseline and after treatment with olanzapine for four weeks. Additionally, spectral power analysis of the EEG signal in distinct frequency bands was computed for different sleep stages. Psychopathology (PANSS, HAMD-17, HAMA) and side effects were assessed weekly. RESULTS: All patients improved, as measured by PANSS global scores. Compared to baseline, there was a significant improvement of parameters of sleep efficiency and an increase of delta sleep as well as REM sleep. Regarding spectral power values, no significant differences between baseline and treatment conditions were found. CONCLUSIONS: Sleep improvement was due to parameters of sleep efficiency and delta sleep, which may be related to serotonin antagonistic properties of olanzapine.

Interrater reliability between scorers from eight European sleep laboratories in subjects with different sleep disorders.

Interrater variability of sleep stage scorings is a well-known phenomenon. The SIESTA project offered the opportunity to analyse interrater reliability (IRR) between experienced scorers from eight European sleep laboratories within a large sample of patients with different (sleep) disorders: depression, general anxiety disorder with and without non-organic insomnia, Parkinson's disease, period limb movements in sleep and sleep apnoea. The results were based on 196 recordings from 98 patients (73 males: 52.3 +/- 12.1 years and 25 females: 49.5 +/- 11.9 years) for which two independent expert scorings from two different laboratories were available. Cohen's kappa was used to evaluate the IRR on the basis of epochs and intraclass correlation was used to analyse the agreement on quantitative sleep parameters. The overall level of agreement when five different stages were distinguished was kappa = 0.6816 (76.8%), which in terms of kappa reflects a 'substantial' agreement (Landis and Koch, 1977). For different groups of patients kappa values varied from 0.6138 (Parkinson's disease) to 0.8176 (generalized anxiety disorder). With regard to (sleep) stages, the IRR was highest for rapid eye movement (REM), followed by Wake, slow-wave sleep (SWS), non-rapid eye movement 2 (NREM2) and NREM1. The results of regression analysis showed that age and sex only had a statistically significant effect on kappa when the (sleep) stages are considered separately. For NREM2 and SWS a statistically significant decrease of IRR with age has been observed and the IRR for SWS was lower for males than for females. These variations of IRR most probably reflect changes of the sleep electroencephalography (EEG) with age and gender.

The automatic recognition of REM sleep: a challenge and some answers.

Automatic sleep staging has remained a constant challenge over the years due to scientific and economic reasons. Rapid eye movement (REM) sleep recognition is a most critical subtask for these procedures. Because the physiological meaning of REM sleep is still an open question and the identification depends on the coordinated behavior of three biological signals, the present definition still has to be considered preliminary and arbitrary to some extent. Three neural network-based algorithms for automatic REM sleep recognition are reviewed herein. All of them rely on a single EEG channel as input signal, but differ in the preprocessing method. The results are encouraging but might be improved with respect to the interrater concordance rate. Applying nonlinear measures could not reduce the errors in our study. Other biological parameters are discussed that might help to improve the results.

Neural net classification of REM sleep based on spectral measures as compared to nonlinear measures.

In various studies the implementation of nonlinear and nonconventional measures has significantly improved EEG (electroencephalogram) analyses as compared to using conventional parameters alone. A neural network algorithm well approved in our laboratory for the automatic recognition of rapid eye movement (REM) sleep was investigated in this regard. Originally based on a broad range of spectral power inputs, we additionally supplied the nonlinear measures of the largest Lyapunov exponent and correlation dimension as well as the nonconventional stochastic measures of spectral entropy and entropy of amplitudes. No improvement in the detection of REM sleep could be achieved by the inclusion of the new measures. The accuracy of the classification was significantly worse, however, when supplied with these variables alone. In view of results demonstrating the efficiency of nonconventional measures in EEG analysis, the benefit appears to depend on the nature of the problem.

Limbic activity in slow wave sleep in a healthy subject with alpha-delta sleep.

All-night electroencephalographic (EEG) activity was recorded in a healthy subject with known alpha-delta sleep. Recordings were made from all 19 of the 10/20 system electrode sites, and low resolution electromagnetic tomography (LORETA) was used to estimate intracerebral current densities. Sleep stages were compared within classical frequency bands by statistical parametric mapping (SPM). With the onset of sleep, occipital alpha abated. With increasing depth of sleep, alpha power increased in a region comprising the left frontal lobe, the anterior and parietal cingulum, and the anterior and medial right front lobe. In slow wave sleep (SWS), frontal alpha power was much greater than in wakefulness. The maximum of frontal alpha power of SWS was localised symmetrically in the left and right anterior cingulum. The observed alpha activity was different from the occipital alpha characteristic of wakefulness; it was a distinct activity of separate origin. The anterior limbic lobes seemed to play an active part in SWS in this healthy volunteer with an alpha-delta sleep pattern.

Macrostructural EEG characterization based on nonparametric change point segmentation: application to sleep analysis.

In the present investigation a new methodology for macrostructural EEG characterization based on automatic segmentation has been applied to sleep analysis. A nonparametric statistical approach for EEG segmentation was chosen, because it minimizes the need for a priori information about a signal. The method provides the detection of change-points i.e. boundaries between quasi-stationary EEG segments based on the EEG characteristics within four fundamental frequency bands (delta, theta, alpha and beta). Polysomnographic data of 18 healthy subjects were analyzed. Our findings show that nonparametric change-point segmentation in combination with cluster analysis enables us to obtain a clear picture of the hierarchical macrostructural organization of sleep, which is impossible to deduce from the unsegmented EEG data. Analysis of correlations between classically defined sleep stages and piecewise stationary power step functions reveals that three basic patterns can be distinguished: SWS (stage III/stage IV), stage II and stage I/REM. In accordance with correlation analyses, cluster detection shows that the cyclic sleep patterns during the course of the night become clearly observable by implementation of only three classes. Since the described methodology is based on a minimum of a priori assumptions, it may be useful for the development of a new sleep classification standard, which goes beyond the established Rechtschaffen and Kales scheme.

Human sleep EEG under the influence of pulsed radio frequency electromagnetic fields. Results from polysomnographies using submaximal high power flux densities.

Former exploratory investigations of sleep alterations due to global system for mobile communications (GSM) signals have shown a hypnotic and REM-suppressive effect under field exposure. This effect was observed in a first study using a power flux density of 0.5 W/m(2), and the same trend occurred in a second study with a power flux density of 0.2 W/m(2). For the present study, we applied a submaximal power flux density of 50 W/m(2). To investigate putative effects of radio frequency electromagnetic fields (EMFs) of cellular GSM phones on human sleep EEG pattern, all-night polysomnographies of 20 healthy male subjects both with and without exposure to a circularly polarized EMF (900 MHz, pulsed with a frequency of 217 Hz, pulse duration 577 microseconds) were recorded. The results showed no significant effect of the field application either on conventional sleep parameters or on sleep EEG power spectra.

Alterations of continuous MEG measures during mental activities.

In a pilot study, we investigated the topography of 11 continuous MEG measures for the eyes-opened and eyes-closed condition together with three simple mental tasks (mental arithmetic, visual imagery, word generation). One-minute recordings for each condition from 16 right-handed subjects were analyzed. The electrophysiological measures consisted of 6 spectral band measures together with spectral edge frequency and spectral entropy, plus the time-domain-based entropy of amplitudes (ENA) and the nonlinear measures correlation dimension D2 and Lyapunov exponent L1. In summary, our results indicate a pronounced task-dependent difference between the anterior and the posterior region, but no lateralization effects. Although the nonlinear measures ranged in the middle field with respect to the number of significant contrasts, they were the only ones to be partially successful in discriminating the mental tasks from each other. The most efficient measure turned out to be the ENA. Under mental activation the ENA was larger than in both no task conditions (eyes opened and eyes closed). This finding reflects lower variations of the maximum amplitude during performance of mental tasks than during no task states.

Nonlinear analysis of continuous ECG during sleep I. Reconstruction.

In recent years evidence has accumulated that ECG signals are of a nonlinear nature. It has been recognized that strictly periodic cardiac rhythms are not accompanied by healthy conditions but, on the contrary, by pathological states. Therefore, the application of methods from nonlinear system theory for the analysis of ECG signals has gained increasing interest. Crucial for the application of nonlinear methods is the reconstruction (embedding) of the time series in a phase space with appropriate dimension. In this study continuous ECG signals of 12 healthy subjects recorded during different sleep stages were analysed. Proper embedding dimension was determined by application of two techniques the false nearest neighbours method and the saturation of the correlation dimension. Results for the ECG signals were compared with findings for simulated data (quasiperiodic dynamics, Lorenz data, white noise) and for phase randomized surrogates. Findings obtained with the two approaches suggest that embedding dimensions from 6 to 8 may be regarded as suitable for the topologically proper reconstruction of ECG signals.

Nonlinear analysis of continuous ECG during sleep II. Dynamical measures.

The hypothesis that cardiac rhythms are associated with chaotic dynamics implicating a healthy flexibility has motivated the investigation of continuous ECG with methods of nonlinear system theory. Sleep is known to be associated with modulations of the sympathetic and parasympathetic control of cardiac dynamics. Thus, the differentiation of ECG signals recorded during different sleep stages can serve to determine the usefulness of nonlinear measures in discriminating ECG states in general. For this purpose the following six nonlinear measures were implemented: correlation dimension D2, Lyapunov exponent L1. Kolmogorov entropy K2, as well as three measures derived from the analysis of unstable periodic orbits. Results of this study show that continuous ECG signals can be differentiated from linear stochastic surrogates by each of the nonlinear measures. The most significant finding with respect to the sleep-related differentiation of ECG signals is an increase in dominant chaoticity assessed by L1 and a reduction in the degrees of freedom estimated by D2 during REM sleep compared to slow wave sleep. Our findings suggest that the increase in dominant chaoticity during REM sleep with regard to time-continuous nonlinear analysis is comparable to an increased heart rate variability. The reduction in the correlation dimension may be interpreted as an expression of the withdrawal of respiratory influences during REM sleep.

A replication study on P300 single trial analysis in schizophrenia: confirmation of a reduced number of 'true positive' P300 waves.

A single trial analysis of event-related potentials (auditory odd-ball paradigm) of 20 schizophrenics was performed in comparison to matched healthy controls. The purpose of the study was to test the hypothesis that in schizophrenia the well-known P300 amplitude reduction of averaged event-related potentials is due to fewer elicited single trial P300 waves. The results of the present study support this finding of our previous exploratory investigation and point to the view that schizophrenics reveal basal disturbances in information processing due to inadequately elicited electrophysiological responses to target stimuli.

EEG analysis with nonlinear deterministic and stochastic methods: a combined strategy.

We describe nonlinear deterministic versus stochastic methodology, their applications to EEG research and the neurophysiological background underlying both approaches. Nonlinear methods are based on the concept of attractors in phase space. This concept on the one hand incorporates the idea of an autonomous (stationary) system, on the other hand implicates the investigation of a long time evolution. It is an unresolved problem in nonlinear EEG research that nonlinear methods per se give no feedback about the stationarity aspect. Hence, we introduce a combined strategy utilizing both stochastic and nonlinear deterministic methods. We propose, in a first step to segment the EEG time series into piecewise quasi-stationary epochs by means of nonparametric change point analysis. Subsequently, nonlinear measures can be estimated with higher confidence for the segmented epochs fulfilling the stationarity condition.

The benefit from whole body acupuncture in major depression.

BACKGROUND: In a single-blind placebo-controlled study design we investigated the efficacy of acupuncture additionally applied to drug treatment in major depression. METHODS: We randomly included 70 inpatients with a major depressive episode in three different treatment groups: verum acupuncture, placebo acupuncture and a control group. All three groups were pharmacologically treated with the antidepressant mianserin. The verum group received acupuncture at specific points considered effective in the treatment of depression. The placebo group was treated with acupuncture at non-specific locations and the control group received pharmacological treatment plus clinical management. Acupuncture was applied three times a week over a period of 4 weeks. Psychopathology was rated by judges blind to verum/placebo conditions twice a week over 8 weeks. RESULTS: Patients who experienced acupuncture improved slightly more than patients treated with mianserin alone. CONCLUSIONS: Additionally applied acupuncture improved the course of depression more than pharmacological treatment with mianserin alone. However, we could not detect any differences between placebo and verum acupuncture.

Increased bioavailability of oral melatonin after fluvoxamine coadministration.

BACKGROUND: Fluvoxamine, a selective serotonin reuptake inhibitor, is known to elevate melatonin serum concentrations. It has not been clear whether these effects might be attributed to an increased melatonin production or to an decreased elimination of melatonin. The latter hypothesis was tested by this study. METHODS: Five healthy male volunteers (one CYP2D6 poor metabolizer) received 5 mg melatonin either with or without coadministration of 50 mg fluvoxamine. Serum concentrations of melatonin and fluvoxamine were assessed from 0 to 28 hours after melatonin intake. RESULTS: Coadministration of fluvoxamine, on average, led to an 17-fold higher (P < .05) area under concentration-time curve (AUC) and a 12-fold higher (P < .01) serum peak concentration (Cmax) of melatonin. The terminal elimination half-life was not significantly affected. The AUC and Cmax of fluvoxamine were about three times higher and the half-life was about two times higher in the poor metabolizer. There was a correlation (r = 0.63; P < .01) between the melatonin and fluvoxamine serum concentrations. The poor metabolizer was found to have a more pronounced and longer-lasting effect of fluvoxamine on the pharmacokinetics of melatonin. CONCLUSION: This study showed an increase in the bioavailability of oral melatonin by coadministration of fluvoxamine. The effects of fluvoxamine on the melatonin serum concentrations in patients with depression might therefore be caused by inhibition of the elimination of melatonin and not attributable to an increased production of melatonin.

Electrophysiological evidence for an inverse benzodiazepine receptor agonist in panic disorder.

Inverse agonists of the GABA(A) receptor clearly decrease the amplitudes of the spontaneous EEG in the beta-frequency range. Therefore, we tested the hypothesis that panic patients exhibit a reduction of the EEG's spectral power in the beta-frequency band. Ten unmedicated patients with panic disorder and agoraphobia according to DSM-III-R criteria and 10 matched controls were investigated under baseline conditions, after hyperventilation and 30 min after hyperventilation. EEG recordings from the position Pz and Cz were performed under eyes closed conditions. At baseline conditions the patients suffering from panic disorder depicted a reduced beta-power reaching statistically significance for lead position Pz. Immediately after hyperventilation for both channels we observed a decreased beta-power. After hyperventilation we observed the same situation as under baseline conditions. Taken together, our results point to the view that in panic disorder an endogenous inverse agonist of the GABA(A)-benzodiazepine receptor could be hypothesized.