Rostral anterior cingulate glutamate predicts response to subcallosal deep brain stimulation for resistant depression

Treatment response of venlafaxine induced alterations of gut microbiota and metabolites in a mouse model of depression

Antidepressants remain the first-line treatment for depression. However, the factors influencing medication response are still unclear. Accumulating evidence implicates an association between alterations in gut microbiota and antidepressant response. Therefore, the aim of this study is to investigate the role of the gut microbiota-brain axis in the treatment response of venlafaxine. After chronic social defeat stress and venlafaxine treatment, mice were divided into responders and non-responders groups. We compared the composition of gut microbiota using 16 S ribosomal RNA sequencing. Meanwhile, we quantified metabolomic alterations in serum and hippocampus, as well as hippocampal neurotransmitter levels using liquid chromatography-mass spectrometry. We found that the abundances of 29 amplicon sequence variants (ASVs) were significantly altered between the responders and non-responders groups. These ASVs belonged to 8 different families, particularly Muribaculaceae. Additionally, we identified 38 and 39 differential metabolites in serum and hippocampus between the responders and non-responders groups, respectively. Lipid, amino acid, and purine metabolisms were enriched in both serum and hippocampus. In hippocampus, the concentrations of tryptophan, phenylalanine, gamma-aminobutyric acid, glutamic acid, and glutamine were increased, while the level of succinic acid was decreased in the responders group, compared with the non-responders group. Our findings suggest that the gut microbiota may play a role in the antidepressant effect of venlafaxine by modulating metabolic processes in the central and peripheral tissues. This provides a novel microbial and metabolic framework for understanding the impact of the gut microbiota-brain axis on antidepressant response.

Deep Brain Stimulation of the Medial Forebrain Bundle for Treatment-Resistant Depression: A Systematic Review Focused on the Long-Term Antidepressive Effect

OBJECTIVE

Major depression affects millions of people worldwide and has important social and economic consequences. Since up to 30% of patients do not respond to several lines of antidepressive drugs, deep brain stimulation (DBS) has been evaluated for the management of treatment-resistant depression (TRD). The superolateral branch of the medial forebrain bundle (slMFB) appears as a "hypothesis-driven target" because of its role in the reward-seeking system, which is dysfunctional in depression. Although initial results of slMFB-DBS from open-label studies were promising and characterized by a rapid clinical response, long-term outcomes of neurostimulation for TRD deserve particular attention. Therefore, we performed a systematic review focused on the long-term outcome of slMFB-DBS.

MATERIALS AND METHODS

A literature search using Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria was conducted to identify all studies reporting changes in depression scores after one-year follow-up and beyond. Patient, disease, surgical, and outcome data were extracted for statistical analysis. The Montgomery-Åsberg Depression Rating Scale (ΔMADRS) was used as the clinical outcome, defined as percentage reduction from baseline to follow-up evaluation. Responders' and remitters' rates were also calculated.

RESULTS

From 56 studies screened for review, six studies comprising 34 patients met the inclusion criteria and were analyzed. After one year of active stimulation, ΔMADRS was 60.7% ± 4%; responders' and remitters' rates were 83.8% and 61.5%, respectively. At the last follow-up, four to five years after the implantation, ΔMADRS reached 74.7% ± 4.6%. The most common side effects were stimulation related and reversible with parameter adjustments.

CONCLUSIONS

slMFB-DBS appears to have a strong antidepressive effect that increases over the years. Nevertheless, to date, the overall number of patients receiving implantations is limited, and the slMFB-DBS surgical technique seems to have an important impact on the clinical outcome. Further multicentric studies in a larger population are needed to confirm slMFB-DBS clinical outcomes.

Deep brain stimulation for refractory major depressive disorder: a comprehensive review

Deep brain stimulation (DBS) has emerged as a promising treatment for select patients with refractory major depressive disorder (MDD). The clinical effectiveness of DBS for MDD has been demonstrated in meta-analyses, open-label studies, and a few controlled studies. However, randomized controlled trials have yielded mixed outcomes, highlighting challenges that must be addressed prior to widespread adoption of DBS for MDD. These challenges include tracking MDD symptoms objectively to evaluate the clinical effectiveness of DBS with sensitivity and specificity, identifying the patient population that is most likely to benefit from DBS, selecting the optimal patient-specific surgical target and stimulation parameters, and understanding the mechanisms underpinning the therapeutic benefits of DBS in the context of MDD pathophysiology. In this review, we provide an overview of the latest clinical evidence of MDD DBS effectiveness and the recent technological advancements that could transform our understanding of MDD pathophysiology, improve the clinical outcomes for MDD DBS, and establish a path forward to develop more effective neuromodulation therapies to alleviate depressive symptoms.

Multimodal imaging measures in the prediction of clinical response to deep brain stimulation for refractory depression: A machine learning approach

OBJECTIVES

This study compared machine learning models using unimodal imaging measures and combined multi-modal imaging measures for deep brain stimulation (DBS) outcome prediction in treatment resistant depression (TRD).

METHODS

Regional brain glucose metabolism (CMRGlu), cerebral blood flow (CBF), and grey matter volume (GMV) were measured at baseline using 18F-fluorodeoxy glucose (18F-FDG) positron emission tomography (PET), arterial spin labelling (ASL) magnetic resonance imaging (MRI), and T1-weighted MRI, respectively, in 19 patients with TRD receiving subcallosal cingulate (SCC)-DBS. Responders (n = 9) were defined by a 50% reduction in HAMD-17 at 6 months from the baseline. Using an atlas-based approach, values of each measure were determined for pre-selected brain regions. OneR feature selection algorithm and the naïve Bayes model was used for classification. Leave-out-one cross validation was used for classifier evaluation.

RESULTS

The performance accuracy of the CMRGlu classification model (84%) was greater than CBF (74%) or GMV (74%) models. The classification model using the three image modalities together led to a similar accuracy (84%0 compared to the CMRGlu classification model.

CONCLUSIONS

CMRGlu imaging measures may be useful for the development of multivariate prediction models for SCC-DBS studies for TRD. The future of multivariate methods for multimodal imaging may rest on the selection of complementing features and the developing better models.Clinical Trial Registration: ClinicalTrials.gov (#NCT01983904).

The Glutamatergic System in Treatment-Resistant Depression and Comparative Effectiveness of Ketamine and Esketamine: Role of Inflammation?

The glutamatergic system is the primary excitatory pathway within the CNS and is responsible for cognition, memory, learning, emotion, and mood. Because of its significant importance in widespread nervous system function, it is tightly regulated through multiple mechanisms, such as glutamate recycling, microglial interactions, and inflammatory pathways. Imbalance within the glutamatergic system has been implicated in a wide range of pathological conditions including neurodegenerative conditions, neuromuscular conditions, and mood disorders including depression. Major depressive disorder (MDD) is the most common mood disorder worldwide, has a high prevalence rate, and afflicts approximately 280 million people. While there are numerous treatments for the disease, 30-40% of patients are unresponsive to treatment and deemed treatment resistant; approximately another third experience only partial improvement (World Health Organization, Depression fact sheet [Internet], 2020). Esketamine, the S-enantiomer of ketamine, was approved by the Food and Drug Administration for treatment-resistant depression (TRD) in 2019 and has offered new hope to patients. It is the first treatment targeting the glutamatergic system through a complex mechanism. Numerous studies have implicated imbalance in the glutamatergic system in depression and treatment resistance. Esketamine and ketamine principally work through inhibition of the NMDA receptor, though more recent studies have implicated numerous other mechanisms mediating the antidepressant efficacy of these agents. These mechanisms include increase in brain-derived neurotrophic factor (BDNF), activation of mammalian target of the rapamycin complex (mTORC), and reduction in inflammation. Esketamine and ketamine have been shown to decrease inflammation in numerous ways principally through reducing pro-inflammatory cytokines (e.g., TNF-α, IL-6) (Loix et al., Acta Anaesthesiol Belg 62(1):47-58, 2011; Chen et al., Psychiatry Res 269:207-11, 2018; Kopra et al., J Psychopharmacol 35(8):934-45, 2021). This anti-inflammatory effect has also been shown to be involved in the antidepressive properties of both ketamine and esketamine (Chen et al., Psychiatry Res 269:207-11, 2018; Kopra et al., J Psychopharmacol 35(8):934-45, 2021).

Acute effects of ketamine on the pregenual anterior cingulate: linking spontaneous activation, functional connectivity, and glutamate metabolism

Ketamine exerts its rapid antidepressant effects via modulation of the glutamatergic system. While numerous imaging studies have investigated the effects of ketamine on a functional macroscopic brain level, it remains unclear how altered glutamate metabolism and changes in brain function are linked. To shed light on this topic we here conducted a multimodal imaging study in healthy volunteers (N = 23) using resting state fMRI and proton (¹H) magnetic resonance spectroscopy (MRS) to investigate linkage between metabolic and functional brain changes induced by ketamine. Subjects were investigated before and during an intravenous ketamine infusion. The MRS voxel was placed in the pregenual anterior cingulate cortex (pgACC), as this region has been repeatedly shown to be involved in ketamine's effects. Our results showed functional connectivity changes from the pgACC to the right frontal pole and anterior mid cingulate cortex (aMCC). Absolute glutamate and glutamine concentrations in the pgACC did not differ significantly from baseline. However, we found that stronger pgACC activation during ketamine was linked to lower glutamine concentration in this region. Furthermore, reduced functional connectivity between pgACC and aMCC was related to increased pgACC activation and reduced glutamine. Our results thereby demonstrate how multimodal investigations in a single brain region could help to advance our understanding of the association between metabolic and functional changes.

A connectomic analysis of deep brain stimulation for treatment-resistant depression

OBJECTIVE

Deep brain stimulation (DBS) has been used as a treatment of last resort for treatment-resistant depression (TRD) for more than a decade. Many DBS targets have been proposed and tested clinically, but the underlying circuit mechanisms remain unclear. Uncovering white matter tracts (WMT) activated by DBS targets may provide crucial information about the circuit substrates mediating DBS efficacy in ameliorating TRD.

METHODS

We performed probabilistic tractography using diffusion magnetic resonance imaging datas from 100 healthy volunteers in Human Connectome Project datasets to analyze the structural connectivity patterns of stimulation targeting currently-used DBS target for TRD. We generated mean and binary fiber distribution maps and calculated the numbers of WMT streamlines in the dataset.

RESULTS

Probabilistic tracking results revealed that activation of distinct DBS targets demonstrated modulation of overlapping but considerably distinct pathways. DBS targets were categorized into 4 groups: Cortical, Striatal, Thalamic, and Medial Forebrain Bundle according to their main modulated WMT and brain areas. Our data also revealed that Brodmann area 10 and amygdala are hub structures that are associated with all DBS targets.

CONCLUSIONS

Our results together suggest that the distinct mechanism of DBS targets implies individualized target selection and formulation in the future of DBS treatment for TRD. The modulation of Brodmann area 10 and amygdala may be critical for the efficacy of DBS-mediated treatment of TRD.

The anatomy of pain and suffering in the brain and its clinical implications

Pain is an unpleasant sensory and emotional experience associated with actual or potential tissue damage. Chronic pain, with a prevalence of 20-30 % is the major cause of human suffering worldwide, because effective, specific and safe therapies have yet to be developed. It is unevenly distributed among sexes, with women experiencing more pain and suffering. Chronic pain can be anatomically and phenomenologically dissected into three separable but interacting pathways, a lateral 'painfulness' pathway, a medial 'suffering' pathway and a descending pain inhibitory pathway. One may have pain(fullness) without suffering and suffering without pain(fullness). Pain sensation leads to suffering via a cognitive, emotional and autonomic processing, and is expressed as anger, fear, frustration, anxiety and depression. The medial pathway overlaps with the salience and stress networks, explaining that behavioural relevance or meaning determines the suffering associated with painfulness. Genetic and epigenetic influences trigger chronic neuroinflammatory changes which are involved in transitioning from acute to chronic pain. Based on the concept of the Bayesian brain, pain (and suffering) can be regarded as the consequence of an imbalance between the two ascending and the descending pain inhibitory pathways under control of the reward system. The therapeutic clinical implications of this simple pain model are obvious. After categorizing the working mechanisms of each of the available treatments (pain killers, psychopharmacology, psychotherapy, neuromodulation, psychosurgery, spinal cord stimulation) to 1 or more of the 3 pathways, a rational combination can be proposed of activating the descending pain inhibitory pathway in combination with inhibition of the medial and lateral pathway, so as to rebalance the pain (and suffering) pathways.

Advanced Imaging in Psychiatric Neurosurgery: Toward Personalized Treatment

OBJECTIVES

Our aim is to review several recent landmark studies discussing the application of advanced neuroimaging to guide target selection in deep brain stimulation (DBS) for psychiatric disorders.

MATERIALS AND METHODS

We performed a PubMed literature search of articles related to psychiatric neurosurgery, DBS, diffusion tensor imaging, probabilistic tractography, functional magnetic resonance imaging (MRI), and blood oxygen level-dependent activation. Relevant articles were included in the review.

RESULTS

Recent advances in neuroimaging, namely the use of diffusion tensor imaging, probabilistic tractography, functional MRI, and Positron emission tomography have provided higher resolution depictions of structural and functional connectivity between regions of interest. Applying these imaging modalities to DBS has increased understanding of the mechanism of action of DBS from the single structure to network level, allowed for new DBS targets to be discovered, and allowed for individualized DBS targeting for psychiatric indications.

CONCLUSIONS

Advanced neuroimaging techniques may be especially important to guide personalized DBS targeting in psychiatric disorders such as treatment-resistant depression and obsessive-compulsive disorder where symptom profiles and underlying disordered circuitry are more heterogeneous. These articles suggest that advanced imaging can help to further individualize and optimize DBS, a promising next step in improving its efficacy.

Recruitment Challenges for Studies of Deep Brain Stimulation for Treatment-Resistant Depression

INTRODUCTION

Deep brain stimulation (DBS) is currently an investigational treatment for treatment-resistant depression (TRD). There is a need for more DBS trials to strengthen existing evidence of its efficacy for both regulatory and clinical reasons. Recruitment for DBS trials remains challenging due to unproven efficacy in sham-controlled DBS trials, invasive nature of the intervention and stringent eligibility criteria in patient selection. Here, we examined the referral patterns and reasons for exclusion of subjects in our DBS trial.

METHODS

Data were collected from all patients who expressed interest in participating in a DBS study involving subcallosal cingulate region from 2014 to 2016. Referral sources were categorized as either self-referral or professional referral. Evaluation for eligibility was performed in three stages; initial contact, brief telephone assessment, and in-person psychiatric evaluation. The reasons for exclusion were documented. Descriptive and inferential statistics were used for analysis.

RESULTS

Of the 225 patients who contacted us initially, 22 (9.2%) underwent DBS surgery. Self-referral was higher than the referral from professionals (72% versus 28%, P<0.0001). However, the acceptance rate for surgery was higher among the professional referrals than from self-referrals (40% versus 15%, P=0.03). The common reasons for exclusion were self-withdrawal (38.4%), residing out of province or country (26.1%) and psychiatric/medical comorbidity (21.7%).

CONCLUSION

These findings provide insight into DBS candidacy for future TRD trials. It suggests a need for comprehensive recruitment strategies including active engagement of patients and professionals throughout trials, and effective referral communication with education to optimize recruitment for future DBS trials.