Predictors of Response to Ketamine in Treatment Resistant Major Depressive Disorder and Bipolar Disorder

This meta-analysis (2018) examined whether clinical and biological pretreatment variables could predict the treatment response of ketamine for patients with (bipolar) depression, but found that its antidepressant efficacy was highly variable and did not depend on any single predictor, although certain inflammatory biomarkers were associated with a positive response.

Abstract

Objectives: Extant evidence indicates that ketamine exerts rapid antidepressant effects in treatment-resistant depressive (TRD) symptoms as a part of major depressive disorder (MDD) and bipolar disorder (BD). The identification of depressed sub-populations that are more likely to benefit from ketamine treatment remains a priority. In keeping with this view, the present narrative review aims to identify the pretreatment predictors of response to ketamine in TRD as part of MDD and BD.

Method: Electronic search engines PubMed/MEDLINE, ClinicalTrials.gov, and Scopus were searched for relevant articles from inception to January 2018. The search term ketamine was cross-referenced with the terms depression, major depressive disorder, bipolar disorder, predictors, and response and/or remission.

Results: Multiple baseline pretreatment predictors of response were identified, including clinical (i.e., Body Mass Index (BMI), history of suicide, family history of alcohol use disorder), peripheral biochemistry (i.e., adiponectin levels, vitamin B12 levels), polysomnography (abnormalities in delta sleep ratio), neurochemistry (i.e., glutamine/glutamate ratio), neuroimaging (i.e., anterior cingulate cortex activity), genetic variation (i.e., Val66Met BDNF allele), and cognitive functioning (i.e., processing speed). High BMI and a positive family history of alcohol use disorder were the most replicated predictors.

Conclusions: A pheno-biotype of depression more, or less likely, to benefit with ketamine treatment is far from complete. Notwithstanding, metabolic-inflammatory alterations are emerging as possible pretreatment response predictors of depressive symptom improvement, most notably being cognitive impairment. Sophisticated data-driven computational methods that are iterative and agnostic are more likely to provide actionable baseline pretreatment predictive information.”

Authors: Carola Rong, Caroline Park, Joshua D. Rosenblat, Mehala Subramaniapillai, Hannah Zuckerman, Dominika Fus, Yena L. Lee, Zihang Pan, Elisa Brietzke, Rodrigo B. Mansur, Danielle S. Cha, Leanna M. W. Lui & Roger S. McIntyre

Summary

Article

This narrative review aims to identify the pretreatment predictors of response to ketamine in treatment-resistant depressive symptoms as a part of major depressive disorder and bipolar disorder. High BMI and a positive family history of alcohol use disorder were the most replicated predictors.

  1. Introduction

MDD is a highly prevalent, chronic, and disabling disorder that often requires 4 to 8 weeks of treatment before clinically significant improvement in symptoms is observed. This prolongs patient-reported symptoms, increases risk for suicidality, and increases economic costs.

Ketamine is a dissociative anesthetic that antagonizes glutamatergic N-methyl-D-aspartate (NMDA) receptors and has been reported to have rapid-onset antidepressant effects in subpopulations with MDD and bipolar disorder that do not sufficiently respond to conventional antidepressant therapies.

Ketamine’s mechanism of action is not fully characterized, but is hypothesized to involve downstream actions on multiple effector systems, including the monoamine system, the opioid system, the gamma aminobutyric acid (GABA)/glutamate system, signal transduction cascades, cellular proliferation, and neuroplasticity-promoting intracellular cascades.

Ketamine has several potential side effects, including dissociative phenomena, vasomotor effects, and CNS effects. It is important to identify predictors of safety, tolerability, and efficacy in response to IV ketamine to improve therapeutic response prediction and cost-effectiveness analyses.

Herein, we aim to summarize pretreatment clinical and biological predictors of successful response to IV ketamine infusion in adults with TRD.

  1. Methods

An electronic literature search was conducted using the following databases: PubMed/MEDLINE, ClinicalTrials.gov, and Scopus from inception to January 2018. All studies that assessed depression severity using standardized and validated depression rating scales were included in the review.

  1. Results

The original search yielded 582 records, of which 12 were included in the review. Nine studies were included via electronic search, and three studies were included via manual search.

3.2. Clinical Variables

Subjects with a positive family history of alcohol use disorder responded better to ketamine infusion than healthy controls, and the effects lasted for up to four weeks.

A separate post-hoc analysis found that higher pretreatment BMI was associated with greater improvement in total HDRS score at 230-min and one-day post-infusion, but not at seven-days post-infusion. Moreover, individuals without a history of suicide attempts had greater improvement in HDRS score at seven-days post-infusion.

3.3. Peripheral Biomarkers

Machado-Vieira et al. (2017) observed that low pretreatment plasma adiponectin levels predicted rapid response to ketamine and that high levels of pro-inflammatory cytokines were associated with a poor response to conventional antidepressants.

Pretreatment pro-inflammatory cytokines and circulating vitamin B12 levels may moderate response to ketamine, and higher levels of vitamin B12 are positively correlated with the conventional antidepressant response.

3.4. Polysomnography

Slow wave sleep is decreased in individuals with MDD and BD, and low pretreatment DSR predicts a greater improvement in total depressive symptom severity than high pretreatment DSR.

3.5. Neurochemistry Variables

Using proton magnetic resonance spectroscopy, Salvadore et al. (2012) measured levels of neurotransmitters in the ventromedial and dorsomedial/dorsomelateral prefrontal cortex in subjects with MDD before and after IV ketamine treatment.

3.6. Noninvasive Functional Neuroimaging

IV ketamine treatment increased anterior cingulate cortical activity in subjects with MDD compared to healthy controls, which was positively and significantly correlated with a rapid antidepressant response to IV ketamine.

3.7. Genetics

The BDNF Val66Met single nucleotide polymorphism has been reported to be associated with an impaired function of BDNF activity in the human brain and an increased likelihood of response to IV ketamine in individuals with MDD.

3.8. Cognitive Function

Neurocognitive impairment is a highly replicated finding and enduring abnormality in individuals with MDD and BD. Pretreatment cognitive performance may influence the overall treatment response to ketamine, and a separate hypothesis has been proffered that suggests that the pro-cognitive effects of ketamine mediate the anti-suicidal effects of ketamine treatment.

  1. Discussion

There is an urgent need to identify predictors of response to psychotropic medications in subpopulations with mood disorders. The identification of pretreatment predictors may provide clinicians with decision support as it regards the selection and sequencing of ketamine treatment in a cost-effective manner.

Ketamine exerts rapid and robust antidepressant effects in patients with TRD, and pretreatment inflammatory markers may have predictive potential. Moreover, individuals with disturbances in central amino acid neurotransmitters and/or pro-inflammatory cytokines may particularly benefit from ketamine treatment.

Pretreatment predictors of antidepressant treatment response may be identified by analyzing phenotypic and biological variables. This may lead to personalized healthcare and significantly improved clinical outcomes for patients.

The current review has several significant limitations, including small sample sizes, heterogeneity of study designs, and lack of healthy control groups.

Machine learning techniques may be able to predict patient response to ketamine therapy, including improvements in cognitive measures and reward measures. Additionally, studies evaluating ketamine’s effects on workplace functioning may be able to provide additional insight into patient response.

  1. Conclusions

Herein, we identified several putative pretreatments that may predict the antidepressant response to IV ketamine. These variables include BMI and FHP, and indirect evidence suggests metabolic inflammatory alterations and cognitive impairment.

Study details

Compounds studied
Ketamine

Topics studied
Depression Bipolar Disorder

Study characteristics
Meta-Analysis Literature Review