Growing evidence implicates the glutamatergic system in the pathogenesis of depression, and receptor antagonists may provide a new generation of compounds for MDD treatment. In particular, the finding that the NMDA antagonist, ketamine, induces a rapid antidepressant response within hours to days has led to research investigating the neural mechanisms producing rapid antidepressant action and makes ketamine a valuable tool to identify biomarkers of depression response and of risk of relapse. The study of biomarkers for understanding the mechanistic actions of ketamine may serve to enhance emerging treatment approaches and provide new breakthroughs for translation of other drug targets.
Recently, the investigators of this trial have begun to offer off-label ketamine infusion treatment to clinical patients with treatment-resistant depression (TRD) and have developed a local treatment protocol for systematic clinical assessment, infusion monitoring and follow-up, which has been well-received and tolerated. The overarching goal of this study is to investigate imaging, gene expression and immune system biomarkers to help determine the underlying mechanisms and predictors for treatment response and relapse in MDD patients receiving ketamine and to compare these with the same biomarkers obtained from patients receiving ECT. The investigators aim to collect data from a sample of 60 patients who will receive serial infusions of ketamine, occurring 2-3 times a week, until they achieve remission or a total of 4 infusions. To study changes during or after ketamine treatment, we will use advanced brain scans that will allow us to measure brain structure, chemistry and function. We will also collect blood samples to measure changes in gene regulation and immune system response at the same time. Patients will also be assessed for basic cognitive function and mood. Brain and blood sample measurements will occur before ketamine infusion, 24 hours after the first infusion, after the 4th or last infusion, and at a final follow-up session approximately 5 weeks after ketamine treatment. We are also including remote mood assessment after treatment to more efficiently track relapse. We will therefore be able to see how changes over time in brain measurements and gene regulation, or immune response relate to improvements and relapse in depressive symptoms.
The investigators will address the following aims:
Aim 1: To use a comprehensive multimodal magnetic resonance imaging (MRI) battery including a) single voxel proton magnetic resonance spectroscopy (1HMRS), b) structural MRI (sMRI), c) arterial spin-labeling (ASL), d) resting state functional MRI (rs-fMRI) and e) diffusion MRI (dMRI) sensitive to different aspects of brain plasticity to isolate neurobiological markers linked with and predictive of ketamine response and subsequent relapse.
Hypothesis 1: Neuroplasticity in cortico-limbic (prefrontal and anterior cingulate cortex and hippocampus) and striatal networks, including changes in glutamate and other brain metabolites, in blood perfusion and in structural and functional connectivity will associate with therapeutic response to ketamine.
Aim 2: To use peripheral blood to measure inflammatory cytokines and their soluble receptors previously linked with depression or treatment outcome for the examination of relationships with ketamine response and subsequent relapse.
Hypothesis 2: Ketamine-induced symptom improvement will associate with altered concentrations of proinflammatory cytokines to indicate modulation of the immune response system.
Aim 3: To conduct transcriptome profiling using peripheral blood samples to identify gene expression correlates of ketamine response.
Hypothesis 3: Gene expression profiles will signal biological pathways underlying therapeutic response to ketamine.
Description of outcome measures:
1. Clinical outcome: The Hamilton Depression Rating Scale
2. Imaging markers: Image analysis will incorporate both standard and custom image analysis software and processing streams to measure changes neurochemistry, and structural and functional plasticity and connectivity occurring across time and in association clinical response. Specifically, outcome measures will include:
1. Structural imaging and connectivity measures: combined volumetric and shape and diffusion metrics obtained from sMRI and dMRI data.
2. Functional connectivity measures: Combined functional imaging measures obtained from resting state functional imaging data
3. Neurochemistry: Brain metabolites including glutamate, choline, and NAA.
4. Gene expression: Gene expression markers obtained from differential expression analyses.
Analyses: General linear mixed models and regression analyses will be used to determine changes across time and in association with clinical response for imaging markers. Weighted Gene Coexpression Network analysis (WGCNA) and Ingenuity Pathways analysis (IPA) will be used to identify functions and pathways associated with identified transcripts.
