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A Robust and Reproducible Connectome Fingerprint of Ketamine is Highly Associated with the Connectomic Signature of Antidepressants

Chadi G. Abdallah, Kyung-Heup Ahn, Lynnette A. Averill, Samaneh Nemati, Christopher L. Averill, Samar Fouda, Mohini Ranganathan, Peter T Morgan, Deepak C. D’Souza, Daniel H. Mathalon, John H. Krystal, Naomi R. Driesen

medRxiv Preprint Server April 10, 2020 preprint DOI: 10.1101/2020.04.10.20061085 (opens in new tab)

Study at a glance

AI-extracted from the abstract
Characteristics Longitudinal functional magnetic resonance imaging study Randomized
Sample size 265
Population Healthy participants and major depressive disorder patients
Interventions Ketamine Normal saline Sertraline Placebo
Dose subanesthetic dose
Duration 8-week intervention, 1-week post treatment
Topics Ketamine Esketamine
Keywords Dissociative anesthetic Rapid-acting antidepressant Brain connectivity Brain networks Neural networks Brain alterations Brain changes Neural connectivity Depression treatment Mental health treatment Antidepressant therapy Sertraline Therapeutic response Biomarkers Brain biomarker Predictive marker Connectome fingerprint Neural signature
Citations 1
Key findings A ketamine-induced brain connectivity fingerprint, reproducible across three healthy cohorts, predicted later response to sertraline in depressed patients.

Abstract

Over the past decade, various N-Methyl-D-Aspartate modulators have failed in clinical trials, underscoring the challenges of developing novel rapid-acting antidepressants based solely on the receptor or regional targets of ketamine. Thus, identifying the effect of ketamine on the brain circuitry and networks is becoming increasingly critical. In this longitudinal functional magnetic resonance imaging study of data from 265 participants, we used a validated predictive model approach that allows the full assessment of brain functional connectivity, without the need for seed selection or connectivity summaries. First, we identified a connectome fingerprint (CFP) in healthy participants (Cohort A, n=25) during intravenous infusion of a subanesthetic dose of ketamine, compared to normal saline. We then demonstrated the robustness and reproducibility of the discovered Ketamine CFP in two separate healthy samples (Cohort B, n=22; Cohort C, n=18). Finally, we investigated the Ketamine CFP connectivity at 1-week post treatment in major depressive disorder patients randomized to 8 weeks of sertraline or placebo (Cohort D, n=200). We found a significant, robust, and reproducible Ketamine CFP, consistent with reduced connectivity within the primary cortices and within the executive network, but increased connectivity between the executive network and the rest of the brain. Compared to placebo, the Ketamine CFP connectivity changes at 1-week predicted response to sertraline at 8-weeks. In each of Cohort A-C, ketamine significantly increased connectivity in a previously identified Antidepressant CFP. Investigating the brain connectivity networks, we successfully identified a robust and reproducible ketamine biomarker that is related to the mechanisms of antidepressants.

Comparable studies

Other observational and cohort studies on ketamine, most cited first.

Study Year Design Participants
Taming the Ketamine Tiger Volunteers from a prison population 2010 Observational study n = 20
Increased spontaneous MEG signal diversity for psychoactive doses of ketamine, LSD and psilocybin Humans 2017 Observational study
Disruption of Frontal–Parietal Communication by Ketamine, Propofol, and Sevoflurane Surgical patients undergoing induction of anesthesia with intravenous ketamine 2013 Observational cohort n = 30
Do the dissociative side effects of ketamine mediate its antidepressant effects? Treatment-resistant inpatients with major depressive disorder or bipolar disorder 2014 Observational cohort n = 108
Concomitant BDNF and sleep slow wave changes indicate ketamine-induced plasticity in major depressive disorder Patients with treatment-resistant major depressive disorder 2012 Observational cohort n = 30

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