Ketamine's modulation of cerebro-cerebellar circuitry during response inhibition in major depression

Neural correlates of treatment response to ketamine for treatment-resistant depression: A systematic review of MRI-based studies

Treatment-resistant depression (TRD) is defined as patients diagnosed with depression having a history of failure with different antidepressants with an adequate dosage and treatment duration. The NMDA receptor antagonist ketamine rapidly reduces depressive symptoms in TRD. We examined neural correlates of treatment response to ketamine in TRD through a systematic review of brain magnetic resonance imaging (MRI) studies. A comprehensive search in PubMed was performed using "ketamine AND depression AND magnetic resonance." The time span for the database queries was "Start date: 2018/01/01; End date: 2024/05/31." Total 41 original articles comprising 1,396 TRD and 587 healthy controls (HC) were included. Diagnosis of depression was made using the Structured Clinical Interview for DSM Disorders (SCID), the Mini-International Neuropsychiatric Interview (MINI), and/or the clinical assessment by psychiatrists. Patients with affective psychotic disorders were excluded. Most studies applied ketamine [0.5mg/kg racemic ketamine and/or 0.25mg/kg S-ketamine] diluted in 60cc of normal saline via intravenous infusion over 40 min one time, four times, or six times spaced 2-3 days apart over 2 weeks. Clinical outcome was defined as either remission, response, and/or percentage changes of depressive symptoms. Brain MRI of the T2*-weighted imaging (resting-state or task performance), arterial spin labeling, diffusion weighted imaging, and T1-weighted imaging were acquired at baseline and mainly 1-3days after the ketamine administration. Only the study results replicated by ≥ 2 studies and were included in the default-mode, salience, fronto-parietal, subcortical, and limbic networks were regarded as meaningful. Putative brain-based markers of treatment response to ketamine in TRD were found in the structural/functional features of limbic (subgenual ACC, hippocampus, cingulum bundle-hippocampal portion; anhedonia/suicidal ideation), salience (dorsal ACC, insula, cingulum bundle-cingulate gyrus portion; thought rumination/suicidal ideation), fronto-parietal (dorsolateral prefrontal cortex, superior longitudinal fasciculus; anhedonia/suicidal ideation), default-mode (posterior cingulate cortex; thought rumination), and subcortical (striatum; anhedonia/thought rumination) networks. Brain features of limbic, salience, and fronto-parietal networks could be useful in predicting the TRD with better response to ketamine in relief of anhedonia, thought rumination, and suicidal ideation.

Modulation of habenular and nucleus accumbens functional connectivity by ketamine in major depression

INTRODUCTION

Major depressive disorder (MDD) is associated with dysfunctional reward processing, which involves functional circuitry of the habenula (Hb) and nucleus accumbens (NAc). Since ketamine elicits rapid antidepressant and antianhedonic effects in MDD, this study sought to investigate how serial ketamine infusion (SKI) treatment modulates static and dynamic functional connectivity (FC) in Hb and NAc functional networks.

METHODS

MDD participants (n = 58, mean age = 40.7 years, female = 28) received four ketamine infusions (0.5 mg/kg) 2-3 times weekly. Resting-state functional magnetic resonance imaging (fMRI) scans and clinical assessments were collected at baseline and 24 h post-SKI. Static FC (sFC) and dynamic FC variability (dFCv) were calculated from left and right Hb and NAc seeds to all other brain regions. Changes in FC pre-to-post SKI, and correlations with changes with mood and anhedonia were examined. Comparisons of FC between patients and healthy controls (HC) at baseline (n = 55, mean age = 32.6, female = 31), and between HC assessed twice (n = 16) were conducted as follow-up analyses.

RESULTS

Following SKI, significant increases in left Hb-bilateral visual cortex FC, decreases in left Hb-left inferior parietal cortex FC, and decreases in left NAc-right cerebellum FC occurred. Decreased dFCv between left Hb and right precuneus and visual cortex, and decreased dFCv between right NAc and right visual cortex both significantly correlated with improvements in mood ratings. Decreased FC between left Hb and bilateral visual/parietal cortices as well as increased FC between left NAc and right visual/parietal cortices both significantly correlated with improvements in anhedonia. No differences were observed between HC at baseline or over time.

CONCLUSION

Subanesthetic ketamine modulates functional pathways linking the Hb and NAc with visual, parietal, and cerebellar regions in MDD. Overlapping effects between Hb and NAc functional systems were associated with ketamine's therapeutic response.

Prediction of Early Antidepressant Efficacy in Patients with Major Depressive Disorder Based on Multidimensional Features of rs-fMRI and P11 Gene DNA Methylation: Prédiction de l'efficacité précoce d'un antidépresseur chez des patients souffrant du trouble dépressif majeur d'après les caractéristiques multidimensionnelles de la méthylation de l'ADN du gène P11 et de la IRMf-rs

OBJECTIVE

This study established a machine learning model based on the multidimensional data of resting-state functional activity of the brain and P11 gene DNA methylation to predict the early efficacy of antidepressant treatment in patients with major depressive disorder (MDD).

METHODS

A total of 98 Han Chinese MDD were analysed in this study. Patients were divided into 51 responders and 47 nonresponders according to whether the Hamilton Depression Rating Scale-17 items (HAMD-17) reduction rate was ≥50% after 2 weeks of antidepressant treatment. At baseline, the Illumina HiSeq Platform was used to detect the methylation of 74 CpG sites of the P11 gene in peripheral blood samples. Resting-state functional magnetic resonance imaging (rs-fMRI) scan detected the amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) in 116 brain regions. The least absolute shrinkage and selection operator analysis method was used to perform feature reduction and feature selection. Four typical machine learning methods were used to establish support vector machine (SVM), random forest (RF), Naïve Bayes (NB), and logistic regression (LR) prediction models based on different combinations of functional activity of the brain, P11 gene DNA methylation and clinical/demographic features after screening.

RESULTS

The SVM model based on ALFF, ReHo, FC, P11 methylation, and clinical/demographic features showed the best performance, with 95.92% predictive accuracy and 0.9967 area under the receiver operating characteristic curve, which was better than RF, NB, and LR models.

CONCLUSION

The multidimensional data features combining rs-fMRI, DNA methylation, and clinical/demographic features can predict the early antidepressant efficacy in MDD.

Ketamine treatment modulates habenular and nucleus accumbens static and dynamic functional connectivity in major depression

Dysfunctional reward processing in major depressive disorder (MDD) involves functional circuitry of the habenula (Hb) and nucleus accumbens (NAc). Ketamine elicits rapid antidepressant and alleviates anhedonia in MDD. To clarify how ketamine perturbs reward circuitry in MDD, we examined how serial ketamine infusions (SKI) modulate static and dynamic functional connectivity (FC) in Hb and NAc networks. MDD participants (n=58, mean age=40.7 years, female=28) received four ketamine infusions (0.5mg/kg) 2-3 times weekly. Resting-state fMRI scans and clinical assessments were collected at baseline and 24 hours post-SKI completion. Static FC (sFC) and dynamic FC variability (dFCv) were calculated from left and right Hb and NAc seeds to all other brain regions. Paired t-tests examined changes in FC pre-to-post SKI, and correlations were used to determine relationships between FC changes with mood and anhedonia. Following SKI, significant increases in left Hb-bilateral visual cortex FC, decreases in left Hb-left inferior parietal cortex FC, and decreases in left NAc-right cerebellum FC occurred. Decreased dFCv between left Hb and right precuneus and visual cortex, and decreased dFCv between right NAc and right visual cortex both significantly correlated with improvements in Hamilton Depression Rating Scale. Decreased FC between left Hb and bilateral visual/parietal cortices as well as increased FC between left NAc and right visual/parietal cortices both significantly correlated with improvements in anhedonia. Subanesthetic ketamine modulates functional pathways linking the Hb and NAc with visual, parietal, and cerebellar regions. Overlapping effects between Hb and NAc functional systems were associated with ketamine's therapeutic response.

Brain-based correlates of antidepressant response to ketamine: a comprehensive systematic review of neuroimaging studies

Ketamine is an effective antidepressant, but there is substantial variability in patient response and the precise mechanism of action is unclear. Neuroimaging can provide predictive and mechanistic insights, but findings are limited by small sample sizes. This systematic review covers neuroimaging studies investigating baseline (pre-treatment) and longitudinal (post-treatment) biomarkers of responses to ketamine. All modalities were included. We performed searches of five electronic databases (from inception to April 26, 2022). 69 studies were included (with 1751 participants). There was substantial methodological heterogeneity and no well replicated biomarker. However, we found convergence across some significant results, particularly in longitudinal biomarkers. Response to ketamine was associated with post-treatment increases in gamma power in frontoparietal regions in electrophysiological studies, post-treatment increases in functional connectivity within the prefrontal cortex, and post-treatment increases in the functional activation of the striatum. Although a well replicated neuroimaging biomarker of ketamine response was not identified, there are biomarkers that warrant further investigation.

Review: The use of functional magnetic resonance imaging (fMRI) in clinical trials and experimental research studies for depression

Functional magnetic resonance imaging (fMRI) is a non-invasive technique that can be used to examine neural responses with and without the use of a functional task. Indeed, fMRI has been used in clinical trials and pharmacological research studies. In mental health, it has been used to identify brain areas linked to specific symptoms but also has the potential to help identify possible treatment targets. Despite fMRI's many advantages, such findings are rarely the primary outcome measure in clinical trials or research studies. This article reviews fMRI studies in depression that sought to assess the efficacy and mechanism of action of compounds with antidepressant effects. Our search results focused on selective serotonin reuptake inhibitors (SSRIs), the most commonly prescribed treatments for depression and ketamine, a fast-acting antidepressant treatment. Normalization of amygdala hyperactivity in response to negative emotional stimuli was found to underlie successful treatment response to SSRIs as well as ketamine, indicating a potential common pathway for both conventional and fast-acting antidepressants. Ketamine's rapid antidepressant effects make it a particularly useful compound for studying depression with fMRI; its effects on brain activity and connectivity trended toward normalizing the increases and decreases in brain activity and connectivity associated with depression. These findings highlight the considerable promise of fMRI as a tool for identifying treatment targets in depression. However, additional studies with improved methodology and study design are needed before fMRI findings can be translated into meaningful clinical trial outcomes.

Functional MRI markers for treatment-resistant depression: Insights and challenges

Imaging studies of treatment-resistant depression (TRD) have examined brain activity, structure, and metabolite concentrations to identify critical areas of investigation in TRD as well as potential targets for treatment interventions. This chapter provides an overview of the main findings of studies using three imaging modalities: structural magnetic resonance imaging (MRI), functional MRI (fMRI), and magnetic resonance spectroscopy (MRS). Decreased connectivity and metabolite concentrations in frontal brain areas appear to characterize TRD, although results are not consistent across studies. Treatment interventions, including rapid-acting antidepressants and transcranial magnetic stimulation (TMS), have shown some efficacy in reversing these changes while alleviating depressive symptoms. However, comparatively few TRD imaging studies have been conducted, and these studies often have relatively small sample sizes or employ different methods to examine a variety of brain areas, making it difficult to draw firm conclusions from imaging studies about the pathophysiology of TRD. Larger studies with more unified hypotheses, as well as data sharing, could help TRD research and spur better characterization of the illness, providing critical new targets for treatment intervention.

Superior temporal gyrus and cerebellar loops predict nonsuicidal self-injury in major depressive disorder patients by multimodal neuroimaging

In major depressive disorder (MDD) patients, nonsuicidal self-injury (NSSI) is a common comorbidity, and it is important to clarify the underlying neurobiology. Here, we investigated the association of NSSI with brain function and structure in MDD patients. A total of 260 MDD patients and 132 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging and three-dimensional T1-weighted structural scans. NSSI behaviour was assessed through interviews. Voxel-based morphometry analysis (VBM), regional homogeneity analysis (ReHo), functional connectome topology properties and network-based statistics were used to detect the differences in neuroimaging characteristics. Finally, the random forest method was used to evaluate whether these factors could predict NSSI in MDD. Compared with HCs, MDD patients with a history of NSSI showed significant right putamen grey matter volume (GMV), right superior orbital frontal cortex ReHo, left pallidum degree centrality, and putamen-centre function network differences. Compared to MDD subjects without NSSI, those with past NSSI showed significant right superior temporal gyrus (STG) GMV, right lingual gyrus ReHo, sigma and global efficiency, and cerebellum-centre function network differences. The right STG GMV and cerebellum-centre function network were more important than other factors in predicting NSSI behaviour in MDD. MDD patients with a history of NSSI have dysregulated spontaneous brain activity and structure in regions related to emotions, pain regulation, and the somatosensory system. Importantly, right STG GMV and cerebellar loops may play important roles in NSSI in MDD patients.

Intrinsic Connectivity Networks of Glutamate-Mediated Antidepressant Response: A Neuroimaging Review

Conventional monoamine-based pharmacotherapy, considered the first-line treatment for major depressive disorder (MDD), has several challenges, including high rates of non-response. To address these challenges, preclinical and clinical studies have sought to characterize antidepressant response through monoamine-independent mechanisms. One striking example is glutamate, the brain's foremost excitatory neurotransmitter: since the 1990s, studies have consistently reported altered levels of glutamate in MDD, as well as antidepressant effects following molecular targeting of glutamatergic receptors. Therapeutically, this has led to advances in the discovery, testing, and clinical application of a wide array of glutamatergic agents, particularly ketamine. Notably, ketamine has been demonstrated to rapidly improve mood symptoms, unlike monoamine-based interventions, and the neurobiological basis behind this rapid antidepressant response is under active investigation. Advances in brain imaging techniques, including functional magnetic resonance imaging, magnetic resonance spectroscopy, and positron emission tomography, enable the identification of the brain network-based characteristics distinguishing rapid glutamatergic modulation from the effect of slow-acting conventional monoamine-based pharmacology. Here, we review brain imaging studies that examine brain connectivity features associated with rapid antidepressant response in MDD patients treated with glutamatergic pharmacotherapies in contrast with patients treated with slow-acting monoamine-based treatments. Trends in recent brain imaging literature suggest that the activity of brain regions is organized into coherent functionally distinct networks, termed intrinsic connectivity networks (ICNs). We provide an overview of major ICNs implicated in depression and explore how treatment response following glutamatergic modulation alters functional connectivity of limbic, cognitive, and executive nodes within ICNs, with well-characterized anti-anhedonic effects and the enhancement of "top-down" executive control. Alterations within and between the core ICNs could potentially exert downstream effects on the nodes within other brain networks of relevance to MDD that are structurally and functionally interconnected through glutamatergic synapses. Understanding similarities and differences in brain ICNs features underlying treatment response will positively impact the trajectory and outcomes for adults suffering from MDD and will facilitate the development of biomarkers to enable glutamate-based precision therapeutics.

Convergence, preliminary findings and future directions across the four human connectome projects investigating mood and anxiety disorders

In this paper we provide an overview of the rationale, methods, and preliminary results of the four Connectome Studies Related to Human Disease investigating mood and anxiety disorders. The first study, "Dimensional connectomics of anxious misery" (HCP-DAM), characterizes brain-symptom relations of a transdiagnostic sample of anxious misery disorders. The second study, "Human connectome Project for disordered emotional states" (HCP-DES), tests a hypothesis-driven model of brain circuit dysfunction in a sample of untreated young adults with symptoms of depression and anxiety. The third study, "Perturbation of the treatment resistant depression connectome by fast-acting therapies" (HCP-MDD), quantifies alterations of the structural and functional connectome as a result of three fast-acting interventions: electroconvulsive therapy, serial ketamine therapy, and total sleep deprivation. Finally, the fourth study, "Connectomes related to anxiety and depression in adolescents" (HCP-ADA), investigates developmental trajectories of subtypes of anxiety and depression in adolescence. The four projects use comparable and standardized Human Connectome Project magnetic resonance imaging (MRI) protocols, including structural MRI, diffusion-weighted MRI, and both task and resting state functional MRI. All four projects also conducted comprehensive and convergent clinical and neuropsychological assessments, including (but not limited to) demographic information, clinical diagnoses, symptoms of mood and anxiety disorders, negative and positive affect, cognitive function, and exposure to early life stress. The first round of analyses conducted in the four projects offered novel methods to investigate relations between functional connectomes and self-reports in large datasets, identified new functional correlates of symptoms of mood and anxiety disorders, characterized the trajectory of connectome-symptom profiles over time, and quantified the impact of novel treatments on aberrant connectivity. Taken together, the data obtained and reported by the four Connectome Studies Related to Human Disease investigating mood and anxiety disorders describe a rich constellation of convergent biological, clinical, and behavioral phenotypes that span the peak ages for the onset of emotional disorders. These data are being prepared for open sharing with the scientific community following screens for quality by the Connectome Coordinating Facility (CCF). The CCF also plans to release data from all projects that have been pre-processed using identical state-of-the-art pipelines. The resultant dataset will give researchers the opportunity to pool complementary data across the four projects to study circuit dysfunctions that may underlie mood and anxiety disorders, to map cohesive relations among circuits and symptoms, and to probe how these relations change as a function of age and acute interventions. This large and combined dataset may also be ideal for using data-driven analytic approaches to inform neurobiological targets for future clinical trials and interventions focused on clinical or behavioral outcomes.