Die Untersuchung der Effekte einer einzelnen subanästhetischen Ketamininfusion auf Symptome der Major Depression und ihr Zusammenhang mit neuralen Aktivierungsmustern in Kognitions- und Emotions-assoziierten Gehirnarealen

Background: Major Depressive Disorder (MDD) is still regarded as often difficult to treat due to its large variety in symptoms. Ketamine has demonstrated rapid antidepressant effects, already 24 h after a single subanaesthetic infusion, but is still lacking effective predictors for a positive treatment response. Objectives: The primary goal of this dissertation project was to investigate ketamine’s effect on distinct MDD symptom dimensions (i.e. cognitive, affective and somatic). Furthermore, by applying a working memory (WM) related functional Magnetic Resonance Imaging (fMRI) paradigm, this project focused on the detection of MDD symptom specific response predictors. Methods: We implemented a symptom-based approach by utilizing a three-factor solution of the Beck Depression Inventory (BDI) in a sample of 47 MDD patients 24 hours pre- and post- a single ketamine infusion. Subsequently, we accessed functional activity at baseline in correlation with MDD symptom improvements 24 h post-treatment in a subsample of 16 patients. Since aberrant functional activation in the default mode network (DMN) and the dorsolateral prefrontal cortex (DLPFC) has been associated with dysfunctional cognition-emotion interaction in MDD, we focused on the examination of these brain regions. Results: On the behavioral level our results indicated that ketamine influences MDD symptom dimensions to a different extent, whereby predominantly affecting the cognitive domain. On the neural level, we found evidence that a decreased DMN deactivation and elevated DLPFC activation predicts ketamine’s enhanced effect on cognitive symptoms. Conclusion: Taken together, these findings suggest that ketamine’s antidepressant efficacy is driven by a “pro-cognitive mechanism” that might be substantiated by an elevated capability for “adaptive adjustment” in the described functional networks.Hintergrund: Die Major Depression (MDD) gilt aufgrund ihrer großen Symptomvielfalt noch immer als häufig schwer zu behandeln. Ketamin zeigt bereits 24 h nach einer einzelnen subanästhetischen Infusion eine schnelle antidepressive Wirkung, wobei es weiterhin an wirksamen Prädiktoren für ein positives Ansprechen auf die Behandlung mangelt. Ziel: Das primäre Ziel dieses Dissertationsprojekts bestand darin, die Wirkung von Ketamin auf verschiedene MDD-Symptomdimensionen (d.h. kognitiv, affektiv und somatisch) zu untersuchen. Überdies lag der Fokus des Projektes darauf, durch die Anwendung eines Arbeitsgedächtnis-assoziierten funktionellen Magnetresonanztomographie (fMRT) Paradigmas MDD symptomspezifische Prädiktoren zu ermitteln. Methoden: Wir implementierten einen symptombasierten Ansatz, indem wir eine Drei-Faktoren-Lösung des Beck Depression Inventory (BDI) in einer Stichprobe von 47 MDD-Patienten 24 h prä und post einer einzelnen Ketamin Infusion anwendeten. Anschließend wurde die funktionelle Aktivität zu Studienbeginn im Zusammenhang mit MDD Symptomverbesserungen 24 h nach der Behandlung in einer Teilstichprobe von 16 Patienten untersucht. Weil funktionelle Abweichungen im Default Mode Network (DMN), sowie im Dorsolateralen Präfrontalen Cortex (DLPFC) mit dysfunktionalen Kognitions-Emotions Interaktionen in der Depression assoziiert werden, lag der Fokus unserer Untersuchungen auf diesen Regionen. Ergebnisse: Auf der Verhaltensebene deuten unsere Ergebnisse darauf hin, dass Ketamin MDD-Symptome in unterschiedlichem Ausmaß beeinflusst, wobei es hauptsächlich den kognitiven Bereich betrifft. Auf neuronaler Ebene fanden wir Hinweise darauf, dass eine verringerte DMN Deaktivierung und eine erhöhte DLPFC Aktivierung die verstärkte Wirkung von Ketamin auf kognitive Symptome prädiziert. Schlussfolgerung: Zusammengenommen lassen diese Ergebnisse darauf schliessen, dass die antidepressive Wirkung von Ketamin durch einen „prokognitiven Mechanismus“ getrieben wird, der durch eine erhöhte Fähigkeit zur „adaptiven Anpassung“ in den beschriebenen funktionellen Netzwerken zustande kommen könnte

A symptom-based approach in predicting ECT outcome in depressed patients employing MADRS single items

Establishing symptom-based predictors of electroconvulsive therapy (ECT) outcome seems promising, however, findings concerning the predictive value of distinct depressive symptoms or subtypes are limited; previous factor-analytic approaches based on the Montgomery-Åsberg Depression Rating Scale (MADRS) remained inconclusive, as proposed factors varied across samples. In this naturalistic study, we refrained from these previous factor-analytic approaches and examined the predictive value of MADRS single items and their change during the course of ECT concerning ECT outcome. We used logistic and linear regression models to analyze MADRS data routinely assessed at three time points in 96 depressed psychiatric inpatients over the course of ECT. Mean age was 53 years (SD 14.79), gender ratio was 58:38 (F:M), baseline MADRS score was M = 30.20 (SD 5.42). MADRS single items were strong predictors of ECT response, remission and overall symptom reduction, especially items 1 (apparent sadness), 2 (reported sadness) and 8 (inability to feel), assessing affective symptoms. Strongest effects were found for regression models including item 2 (reported sadness) with up to 80% correct prediction of ECT outcome. ROC analyses were performed to estimate the optimal cut-point for treatment response. MADRS single items during the course of ECT might pose simple, reliable, time- and cost-effective predictors of ECT outcome. More severe affective symptoms of depression at baseline and a stronger reduction of these affective symptoms during the course of ECT seem to be positively associated with ECT outcome. Precise cut-off values for clinical use were proposed. Generally, these findings underline the benefits of a symptom-based approach in depression research and treatment in addition to depression sum-scores and generalized diagnoses

EffECTively Treating Depression: A Pilot Study Examining Manualized Group CBT as Follow-Up Treatment After ECT

Background: There is an urgent need for effective follow-up treatments after acute electroconvulsive therapy (ECT) in depressed patients. Preliminary evidence suggests psychotherapeutic interventions to be a feasible and efficacious follow-up treatment. However, there is a need for research on the long-term usefulness of such psychotherapeutic offers in a naturalistic setting that is more representative of routine clinical practice. Therefore, the aim of the current pilot study was to investigate the effects of a half-open continuous group cognitive behavioral therapy (CBT) with cognitive behavioral analysis system of psychotherapy elements as a follow-up treatment for all ECT patients, regardless of response status after ECT, on reducing depressive symptoms and promoting psychosocial functioning. Method: Group CBT was designed to support patients during the often-difficult transition from inpatient to outpatient treatment. In a non-controlled pilot trial, patients were offered 15weekly sessions of manualized group CBT (called EffECTiv 2.0). The Montgomery-Åsberg Depression Rating Scale was assessed as primary outcome; the Beck Depression Inventory, WHO Quality of Life Questionnaire-BREF, and the Cognitive Emotion Regulation Questionnaire were assessed as secondary outcomes. Measurements took place before individual group start, after individual group end, and 6months after individual group end. Results: During group CBT, Post-ECT symptom reduction was not only maintained but there was a tendency toward a further decrease in depression severity. This reduction could be sustained 6months after end of the group, regardless of response status after ECT treatment. Aspects of quality of life and emotion regulation strategies improved during group CBT, and these improvements were maintained 6months after the end of the group. Conclusion: Even though the interpretability of the results is limited by the small sample and the non-controlled design, they indicate that manualized group CBT with cognitive behavioral analysis system of psychotherapy elements might pose a recommendable follow-up treatment option after acute ECT for depressed patients, regardless of response status after ECT. This approach might not only help to further reduce depressive symptoms and prevent relapse, but also promote long-term psychosocial functioning by improving emotion regulation strategies and psychological quality of life and thus could be considered as a valuable addition to clinical routine after future validation

Predicting Antidepressant Effects of Ketamine: the Role of the Pregenual Anterior Cingulate Cortex as a Multimodal Neuroimaging Biomarker

Background: Growing evidence underscores the utility of ketamine as an effective and rapid-acting treatment option for major depressive disorder (MDD). However, clinical outcomes vary between patients. Predicting successful response may enable personalized treatment decisions and increase clinical efficacy. Methods: We here explored the potential of pregenual anterior cingulate cortex (pgACC) activity to predict antidepressant effects of ketamine in relation to ketamine-induced changes in glutamatergic metabolism. Prior to a single i.v. infusion of ketamine, 24 patients with MDD underwent functional magnetic resonance imaging during an emotional picture-viewing task and magnetic resonance spectroscopy. Changes in depressive symptoms were evaluated using the Beck Depression Inventory measured 24 hours pre- and post-intervention. A subsample of 17 patients underwent a follow-up magnetic resonance spectroscopy scan. Results: Antidepressant efficacy of ketamine was predicted by pgACC activity during emotional stimulation. In addition, pgACC activity was associated with glutamate increase 24 hours after the ketamine infusion, which was in turn related to better clinical outcome. Conclusions: Our results add to the growing literature implicating a key role of the pgACC in mediating antidepressant effects and highlighting its potential as a multimodal neuroimaging biomarker of early treatment response to ketamine. Keywords: antidepressant effects; ketamine; multimodal neuroimaging biomarker; pgACC; pregenual anterior cingulate cortex

Differential Effects of Electroconvulsive Therapy in the Treatment of Major Depressive Disorder

Background/Aims/Methods: Electroconvulsive therapy (ECT) is still one of the most potent treatments in the acute phase of major depressive disorder (MDD) and particularly applied in patients considered treatment resistant. However, despite the frequent and widespread use of ECT for >70 years, the exact neurobiological mechanisms underlying its efficacy remain unclear. The present review aims to describe differential antidepressant and cognitive effects of ECT as well as effects on markers of neural activity and connectivity, neurochemistry, and inflammation that might underlie the treatment response and remission. Results: Region- specific changes in brain function and volume along with changes in concentrations of neurotransmitters and neuroinflammatory cytokines might serve as potential biomarkers for ECT outcomes. Conclusions: However, as current data is not consistent, future longitudinal investigations should combine modalities such as MRI, MR spectroscopy, and peripheral physiological measures to gain a deeper insight into interconnected time- and modality-specific changes in response to ECT

Ketamine specifically reduces cognitive symptoms in depressed patients: An investigation of associated neural activation patterns

Major depressive disorder (MDD) is characterized by heterogeneous cognitive, affective and somatic symptoms. Hence, the investigation of differential treatment effects on these symptoms as well as the identification of symptom specific biomarkers might crucially contribute to the development of individualized treatment strategies. We here aimed to examine symptom specific responses to treatment with ketamine, which repeatedly demonstrated rapid antidepressant effects in severe MDD. Additionally, we investigated working memory (WM) related brain activity associated with changes in distinct symptoms in order to identify specific response predictors. In a sample of 47 MDD patients receiving a single sub-anesthetic dose of ketamine, we applied a three-factor solution of the Beck Depression Inventory (BDI) to detect symptom specific changes 24 h post-infusion. A subsample of 16 patients underwent additional fMRI scanning during an emotional working memory task prior to ketamine treatment. Since functional aberrations in the default mode network (DMN) as well as in the dorsolateral prefrontal cortex (DLPFC) have been associated with impaired cognitive and emotional processing in MDD, we investigated neural activity in these regions. Our results showed that ketamine differentially affects MDD symptoms, with the largest symptom reduction in the cognitive domain. WM related neuroimaging results indicated that a more pronounced effect of ketamine on cognitive symptoms is predicted by lower DMN deactivation and higher DLPFC activation. Findings thereby not only indicate that ketamine's antidepressant efficacy is driven by a pro-cognitive mechanism, but also suggest that this might be mediated by increased potential for adaptive adjustment in the circumscribed brain regions. Keywords: Cognitive symptoms; Default mode network (DMN); Ketamine; Major depression; Working memory (WM); fMRI

Gray matter volume of rostral anterior cingulate cortex predicts rapid antidepressant response to ketamine

Ketamine was recently approved for treatment resistant depression. However, despite its therapeutic potential, about 50% of patients do not show improvement under this therapy. In this prospective two-site study, we investigated baseline brain structural predictors for rapid symptom improvement after a single subanesthetic ketamine infusion. Furthermore, given the preclinical evidence and findings from a pilot study in a clinical population that ketamine induces rapid neuroplasticity, we performed an exploratory investigation of macroscopic changes 24 h post-treatment. T1-weighted MRI brain images from 33 depressed patients were acquired before and 24 h after a single ketamine infusion and analyzed using voxel-based morphometry (VBM). Additionally, we performed a region of interest (ROI)-based analysis of structures that have previously been shown to play a role in the antidepressant effects of ketamine: bilateral hippocampus, nucleus accumbens, anterior cingulate cortex, and thalamus. A whole-brain regression analysis showed that greater baseline volume of the bilateral rostral anterior cingulate cortex (rACC) significantly predicts rapid symptom reduction. The right ACC showed the same association in the ROI analysis, while the other regions yielded no significant results. Exploratory follow-up analyses revealed no volumetric changes 24 h after treatment. This is the first study reporting an association between pretreatment gray matter volume of the bilateral rACC and the rapid antidepressant effects of ketamine. Results are in line with previous investigations, which highlighted the potential of the rACC as a biomarker for response prediction to different antidepressant treatments. Ketamine-induced volumetric changes may be seen at later time points

Aberrant working memory processing in major depression: evidence from multivoxel pattern classification

Major depressive disorder (MDD) is often accompanied by severe impairments in working memory (WM). Neuroimaging studies investigating the mechanisms underlying these impairments have produced conflicting results. It remains unclear whether MDD patients show hyper- or hypoactivity in WM-related brain regions and how potential aberrations in WM processing may contribute to the characteristic dysregulation of cognition–emotion interactions implicated in the maintenance of the disorder. In order to shed light on these questions and to overcome limitations of previous studies, we applied a multivoxel pattern classification approach to investigate brain activity in large samples of MDD patients (N = 57) and matched healthy controls (N = 61) during a WM task that incorporated positive, negative, and neutral stimuli. Results showed that patients can be distinguished from healthy controls with good classification accuracy based on functional activation patterns. ROI analyses based on the classification weight maps showed that during WM, patients had higher activity in the left DLPFC and the dorsal ACC. Furthermore, regions of the default-mode network (DMN) were less deactivated in patients. As no performance differences were observed, we conclude that patients required more effort, indexed by more activity in WM-related regions, to successfully perform the task. This increased effort might be related to difficulties in suppressing task-irrelevant information reflected by reduced deactivation of regions within the DMN. Effects were most pronounced for negative and neutral stimuli, thus pointing toward important implications of aberrations in WM processes in cognition–emotion interactions in MDD