Heart rate variability in obsessive compulsive disorder in comparison to healthy controls and as predictor of treatment response.

OBJECTIVE: Obsessive compulsive disorder (OCD) has a large impact on the quality of life of patients. It often takes years to get the right diagnosis and to receive treatment. Therefore, biomarkers that could inform the diagnostic process and provide information on response or non-response for first line treatment approaches are urgently needed. The aim of this study was to analyze whether (1) heart rate (HR) and heart rate variability (HRV) markers of the autonomous nervous system could distinguish between healthy controls (HC) and patients suffering from OCD and (2) HRV parameters additionally yield useful information to separate therapy-responders from non-responders. METHODS: A fifteen-minute resting state ECG (electrocardiogram) was recorded from 51 unmedicated OCD patients before treatment and 28 HC. The function of the autonomic nervous system was assessed by using parameters of the HRV. Clinical Global Impression (CGI) scores served as baseline and outcome parameters following three to six months of therapy (cognitive behavioral therapy n = 18, selective-serotonin-reuptake-inhibitor n = 11 or combination n = 22). Differences between patients and HC and responders and non-responders were identified using analysis of covariance (ANCOVAs). Predictive values were calculated following binary regression modelling and receiver operating characteristics (ROC). RESULTS: OCD patients revealed a significantly higher HR in comparison to HC. Although patients were thus characterized by increased sympathetic and decreased parasympathetic tone, treatment responders exhibited a larger High Frequency Power as a marker for increased parasympathetic activity at baseline. ROC-curves for OCD vs HC and R vs NR showed clinically relevant areas under curve (83%, 88% respectively). CONCLUSIONS: These results are in line with findings of increased sympathetic and decreased parasympathetic activity in OCD in comparison to healthy subjects. The findings further provide clinically useful information on treatment response in OCD. SIGNIFICANCE: Results may facilitate the clinical use of electrophysiological markers in OCD.

Altered EEG lagged coherence during rest in obsessive-compulsive disorder.

OBJECTIVE: Functional magnetic resonance imaging (fMRI) studies found alterations of functional connectivity in obsessive compulsive disorder (OCD). However, there is little knowledge about region of interest (ROI) based electroencephalogram (EEG) connectivity, i.e. lagged non-linear and linear coherence in OCD. Goal of this study was to compare these EEG measures during rest and at different vigilance stages between patients and healthy controls (HC). METHODS: A 15 min resting-state EEG was recorded in 30 unmedicated patients and 30 matched HC. Intracortical lagged non-linear coherence of the main EEG-frequency bands within a set of frontal ROIs and within the default mode network (DMN) were computed and compared using intracortical exact low resolution electromagnetic tomography (eLORETA) software. RESULTS: Lagged non-linear but not linear coherence was significantly decreased for patients in comparison to HC for the beta 2 frequency between frontal brain areas but not within the DMN. When analysing separate EEG-vigilance stages, only high vigilance stages yielded decreased frontal phase synchronisation at beta and theta frequencies. CONCLUSIONS: The results underline an altered neuronal communication within frontal brain areas during rest in OCD. SIGNIFICANCE: These findings encourage further research on connectivity measures as possible biomarkers for physiological homogeneous subgroups.

EEG-vigilance regulation during the resting state in obsessive-compulsive disorder.

OBJECTIVE: Obsessive compulsive disorder (OCD) has been associated with disturbed sleep-wake cycles and cortical hypermetabolism. However, it still remains unclear whether OCD is associated with a dysregulation of vigilance (i.e. "brain arousal"). VIGALL (Vigilance Algorithm Leipzig) is an EEG-based tool to assess vigilance dynamics. Aim of this study is to test the hypothesis that during resting state less declines to lower vigilance stages are found in unmedicated patients with OCD (n=30) compared to healthy controls (HCs, n=30). METHODS: Fifteen minutes of resting EEG were recorded; preceding sleep duration, nicotine/caffeine consumption and severity of OCD and depressive symptoms were assessed. RESULTS: Significant differences of EEG-vigilance were found for the factor "group" (OCD vs. HC), factor "time" and interaction "group×time" in a repeated measures ANOVA with increased EEG-vigilance in OCD patients. OCD patients showed significantly fewer transitions between EEG-vigilance stages. CONCLUSIONS: In line with findings of disturbed sleep regulation, OCD is associated with altered EEG-vigilance regulation with a failure of declining toward low vigilance stages during rest. SIGNIFICANCE: These results encourage the use of EEG-vigilance regulation for determining subgroups for e.g. studying treatment response and suggest awareness for possible vigilance effects in neuroimaging studies of OCD.