Author response: Ketamine induces multiple individually distinct whole-brain functional connectivity signatures Article Swipe

MAKE IMPACT

Flora Moujaes , Jie Lisa Ji , Masih Rahmati , Joshua B. Burt , Charles Schleifer , Brendan Adkinson , Aleksandar Savić , Nicole Santamauro , Zailyn Tamayo , Caroline Diehl , Antonija Kolobaric , Morgan Flynn , Nathalie M. Rieser , Clara Fonteneau , Terry Camarro , Junqian Xu , Youngsun Cho , Grega Repovš , Sarah K. Fineberg , Peter Morgan , Erich Seifritz , Franz X. Vollenweider , John H. Krystal , John D. Murray , Katrin H. Preller , Alan Anticevic · YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.7554/elife.84173.sa2

Full text Figures and data Peer review Side by side Abstract Editor's evaluation eLife digest Introduction Materials and methods Results Discussion Data availability References Article and author information Metrics Abstract Background: Ketamine has emerged as one of the most promising therapies for treatment-resistant depression. However, inter-individual variability in response to ketamine is still not well understood and it is unclear how ketamine's molecular mechanisms connect to its neural and behavioral effects. Methods: We conducted a single-blind placebo-controlled study, with participants blinded to their treatment condition. 40 healthy participants received acute ketamine (initial bolus 0.23 mg/kg, continuous infusion 0.58 mg/kg/hr). We quantified resting-state functional connectivity via data-driven global brain connectivity and related it to individual ketamine-induced symptom variation and cortical gene expression targets. Results: We found that: (i) both the neural and behavioral effects of acute ketamine are multi-dimensional, reflecting robust inter-individual variability; (ii) ketamine's data-driven principal neural gradient effect matched somatostatin (SST) and parvalbumin (PVALB) cortical gene expression patterns in humans, while the mean effect did not; and (iii) behavioral data-driven individual symptom variation mapped onto distinct neural gradients of ketamine, which were resolvable at the single-subject level. Conclusions: These results highlight the importance of considering individual behavioral and neural variation in response to ketamine. They also have implications for the development of individually precise pharmacological biomarkers for treatment selection in psychiatry. Funding: This study was supported by NIH grants DP5OD012109-01 (A.A.), 1U01MH121766 (A.A.), R01MH112746 (J.D.M.), 5R01MH112189 (A.A.), 5R01MH108590 (A.A.), NIAAA grant 2P50AA012870-11 (A.A.); NSF NeuroNex grant 2015276 (J.D.M.); Brain and Behavior Research Foundation Young Investigator Award (A.A.); SFARI Pilot Award (J.D.M., A.A.); Heffter Research Institute (Grant No. 1–190420) (FXV, KHP); Swiss Neuromatrix Foundation (Grant No. 2016–0111) (FXV, KHP); Swiss National Science Foundation under the framework of Neuron Cofund (Grant No. 01EW1908) (KHP); Usona Institute (2015 – 2056) (FXV). Clinical trial number: NCT03842800 Editor's evaluation This paper presents a valuable investigation of the acute effects of ketamine in healthy volunteers using rating scale-based behavioral and resting-state fMRI-based neural measures. It provides solid evidence of inter-individual variability in responses to ketamine along with associations to relevant gene expression markers (somatostatin, parvalbumin) in the brain. https://doi.org/10.7554/eLife.84173.sa0 Decision letter Reviews on Sciety eLife's review process eLife digest Ketamine is a widely used anesthetic as well as a popular illegal recreational drug. Recently, it has also gained attention as a potential treatment for depression, particularly in cases that don't respond to conventional therapies. However, individuals can vary in their response to ketamine. For example, the drug can alter some people's perception, such as seeing objects as larger or small than they are, while other individuals are unaffected. Although a single dose of ketamine was shown to improve depression symptoms in approximately 65% of patients, the treatment does not work for a significant portion of patients. Understanding why ketamine does not work for everyone could help to identify which patients would benefit most from the treatment. Previous studies investigating ketamine as a treatment for depression have typically included a group of individuals given ketamine and a group given a placebo drug. Assuming people respond similarly to ketamine, the responses in each group were averaged and compared to one another. However, this averaging of results may have masked any individual differences in response to ketamine. As a result, Moujaes et al. set out to investigate whether individuals show differences in brain activity and behavior in response to ketamine. Moujaes et al. monitored the brain activity and behavior of 40 healthy individuals that were first given a placebo drug and then ketamine. The results showed that brain activity and behavior varied significantly between individuals after ketamine administration. Genetic analysis revealed that different gene expression patterns paired with differences in ketamine response in individuals – an effect that was hidden when the results were averaged. Ketamine also caused greater differences in brain activity and behavior between individuals than other drugs, such as psychedelics, suggesting ketamine generates a particularly complex response in people. In the future, extending these findings in healthy individuals to those with depression will be crucial for determining whether differences in response to ketamine align with how effective ketamine treatment is for an individual. Introduction Over the last two decades, ketamine has emerged as one of the most promising therapies for treatment-resistant depression (TRD) (Krystal et al., 2019). Robust individual differences in response to ketamine have been observed in both healthy controls and patients with TRD (Murrough et al., 2013; Hack et al., 2021). For example, a single ketamine infusion results in a response rate of around 65% in patients with TRD, while individual differences in baseline molecular effects (e.g. NMDA receptor occupancy) and brain function predict the degree to which an individual experiences specific acute ketamine-induced symptoms (Murrough et al., 2013; Stone et al., 2008; Honey et al., 2008). Despite these findings, an assumption persists within the fMRI pharmacology literature that the behavioral and neural effects of substances like ketamine are uniform across individuals, and that the central tendency can effectively capture such effects. In this study, we challenge this assumption and instead posit that ketamine's effects are multi-dimensional, and that these dimensions will capture individual differences in response to ketamine. Ketamine's effects have been extensively characterised by group studies, which typically involve recruiting a sample of patients, measuring brain activity before and after ketamine infusion, and then averaging the results across the patients (i.e. relying on the power of central tendency) to ascertain ketamine's effects. At subanesthetic doses, ketamine produces transient changes in behavior, perception, and cognition that are comparable to the positive, negative, and cognitive symptoms seen in patients with psychosis-spectrum illness (Krystal et al., 1994). Therefore, ketamine's acute behavioral effects are typically captured using psychosis-related scales such as the Positive and Negative Syndrome Scale (PANSS), as well as cognitive tasks (Anticevic et al., 2012). However, the acute neural effects of subanesthetic of ketamine are less clear. The majority of studies exploring ketamine's neural alterations have used seed-based approaches, which often result in contradictory results and are fundamentally limited by the required a-priori selection of a seed region and an inability to fully capture ketamine's systems-level alterations (Scheidegger et al., 2012; Niesters et al., 2012; Dandash et al., 2015; Grimm et al., 2015; Höflich et al., 2015; Khalili-Mahani et al., 2015; Bonhomme et al., 2016; Wong et al., 2016; Kraguljac et al., 2017; Liebe et al., 2018; Mueller et al., 2018; Fleming et al., 2019; Hack et al., 2021; Cole et al., 2010; Fitzgerald, 2012). For instance, studies have identified both ketamine-induced increases and decreases in thalamo-cortical and hippocampal-cortical activity (Höflich et al., 2015; Hack et al., 2021; Grimm et al., 2015; Khalili-Mahani et al., 2015; Kraguljac et al., 2017). There is evidence that these inconsistencies may stem in part from a failure to account for individual differences in ketamine response. Ketamine has demonstrated dose-dependent individual variability in thalamic functional connectivity in healthy adults, with some individuals showing dose-dependent increases in functional connectivity, and others showing decreases (Hack et al., 2021). A limited number of studies have also characterised ketamine's neural systems-level functional alterations using whole-brain approaches, demonstrating that ketamine results in robust brain-wide effects. For example, ketamine has been shown to increase global brain connectivity (GBC) in the prefrontal cortex (PFC) in healthy controls specifically, and normalize the reduced PFC GBC in patients with major depressive disorder 24 hr post-ketamine (Anticevic et al., 2015; Abdallah et al., 2017; Abdallah et al., 2018). However, this finding failed to replicate in patients with depression 48 hr post-ketamine (Kraus et al., 2020), suggesting a complex relationship between ketamine's acute and delayed effects. In addition to GBC, graph theoretical approaches have demonstrated ketamine induces a shift from a cortical to a subcortically-centred brain state, particularly the basal ganglia and cerebellum (Joules et al., 2015). Meanwhile, a nodal predictive model found ketamine resulted in reduced connectivity within the primary cortices and the executive network, but increased connectivity between the executive network and the rest of brain (Abdallah et al., 2021). Finally, dynamic resting-state functional connectivity showed that ketamine decreased connectivity both within the left visual network and inter-hemispherically between the visual networks (Spies et al., 2019). However, these studies also fail to account for individual differences in response to ketamine. The main limitation of relying on the power of central tendency is that meaningful differences between individual subjects may be lost through the process of averaging. One method that has been used to successfully address this and uncover individual differences in psychiatric research is a principal component analysis (PCA) (Ji et al., 2020; Halai et al., 2017). A PCA is a data-driven method that is able to uncover both group-level and individual-level differences. More specifically, a PCA allows us to test the hypothesis that ketamine's effects are multi-dimensional: if ketamine's effects are uniform then we would expect a PCA to result in one principal component on which all the participants can be mapped; however if there are systemic differences between participants, we would anticipate a PCA to generate multiple principle components. A PCA is also able to capture individual-level differences through an individual's relative positioning along the axes of the principal components (Halai et al., 2017). In order to assess the relative merits of characterizing ketamine's acute effects using a uni-dimensional (i.e. mean-level) or multi-dimensional (i.e. PCA) approach, we will compare which results best relate to ketamine's hypothesized molecular mechanisms. We will focus on the indirect hypothesis, which posits that ketamine first inhibits tonic-firing GABAergic interneurons via NMDAR blockade, leading to a burst of glutamate that drives synaptic plasticity (Gerhard et al., 2020). Specifically, we will test the hypothesis that individual differences in ketamine's neural systems-level effects are associated with SST and PVALB GABAergic interneurons by correlating ketamine's neural effects with SST and PVALB cortical gene expression maps derived from the Allen Human Brain Atlas (AHBA). SST and PVALB genes were selected a-priori based on: (i) the large body of animal literature directly linking SST and PVALB interneurons to ketamine's acute effects (Gerhard et al., 2020; Ng et al., 2018; Picard et al., 2019); (ii) studies showing SST and PVALB interneurons are particularly sensitive to ketamine as a result of their NMDA receptor subunit configuration (Paoletti et al., 2013); (iii) previous research showing that specific cortical regions express different ratios of SST and PVALB interneurons, with SST showing higher expression levels in association relative to sensory regions, while PVALB shows the reverse pattern (Anderson et al., 2020; Hawrylycz et al., 2012); and (iv) studies demonstrating patients with depression show reduced SST or PVALB interneurons in areas such as the hippocampus and PFC (Nowak et al., 2010; Zadrożna et al., 2011; Czeh et al., 2005; Czéh et al., 2015). Given that many different genes show similar spatial patterns in the brain, with the most common pattern explaining approximately 25% of the total gene expression variance (Burt et al., 2018), it is important to note that by relating ketamine's neural effects to SST and PVALB cortical gene expression patterns we do not make any claims regarding gene specificity. Instead, we use the established relationship between ketamine and SST/PVALB interneurons to evaluate the relative merits of assessing ketamine's acute effects using a multi-dimensional vs. uni-dimensional approach. The current study aims to investigate the behavioral and neural effects of acute ketamine administration in 40 healthy controls using a whole-brain data-driven multi-dimensional (PCA) approach. We hypothesize that ketamine will result in multiple neural and behavioral axes of variation, reflecting inter-individual variability in response to ketamine. We further hypothesize that using a multi-dimensional vs. uni-dimensional approach to capture ketamine's acute effects will allow us to more closely relate ketamine's effects to its hypothesized molecular mechanisms, specifically SST and PVALB cortical gene expression maps. In addition, we investigate the extent to which multi-dimensionality is a property specific to ketamine by directly comparing ketamine to two other psychoactive substances that have also shown preliminary clinical efficacy for the treatment of depression, but have very different pharmacological profiles: (i) psilocybin, a preferential 5-HT2A and 5-HT1A agonist; and (ii) LSD, which stimulates a wide range of serotonin and dopamine receptors (Gasser et al., 2014; Carhart-Harris et al., 2016; Pokorny et al., 2016; De Gregorio et al., 2016; Halberstadt and Geyer, 2011; Passie et al., 2008). Finally, we compare the principal behavioral axes to established psychosis literature subscales (e.g. three-factor and five-factor PANSS models), and assess the extent to which the principal behavioral axes captures novel neural variation and individual differences in molecular mechanisms. Materials and methods Key resources table Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional informationSoftware, algorithmQuNexQuNex, Ji et al., 2023Software, algorithmHCP MPPHCP MPP, Glasser et al., 2013Software, algorithmN-BRIDGEN-BRIDGE, Ji et al., 2020Software, algorithmCAB-NPCAB-NP, Ji et al., 2019Software, algorithmRRRRID:SCR_001905Software, algorithmFSLFSLRRID:SCR_002823 Ketamine study participants Request a detailed protocol Healthy participants were recruited from the New Haven area via flyers and online ads. In order to be eligible to receive ketamine, participants were required to meet the following set of criteria, as determined by a detailed telephone interview and an in-person clinical assessment: (i) Age 21–60; (ii) IQ >70 as measured via Wide Range Achievement Test (WRAT-3) and the Wechsler Adult Intelligence Scale (WAIS-III); (iii) intact or corrected-to-normal vision; (iv) weight 86% for a estimated medium effect size (Cohen's d of 0.5). Demographic details can be found in Supplementary file 2. Ketamine study design Request a detailed protocol The protocol was approved by the Yale Human Investigations Committee (ClinicalTrials.gov Identifier: NCT03842800). All subjects provided written informed consent. The study employed a single-blind within-subjects design, with participants blinded to their treatment condition. Placebo was administered during the first neuroimaging scan session, and ketamine (initial bolus 0.23 mg/kg, continuous infusion 0.58 mg/kg/hr) during the second, as residual ketamine effects ruled out counterbalancing of the order. Participants were not informed about the order in which they would receive saline and ketamine, however they were able to correctly identify the ketamine infusion 100% of the time. Cognitive effects were measured using a Spatial Working Memory task completed in the scanner. Subjective effects were measured before and after the scan (180 min post drug administration) using the following scales: (1) Positive and Negative Syndrome Scale (PANSS), (2) Clinician Administered Dissociative States Scale (CADSS), and (3) Beck's Depression Inventory (BDI). Ketamine infusion protocol Request a detailed protocol Participants were instructed to fast for 12 hr prior to the scan and avoid any alcohol or medications 72 hr prior to the scan. As a precaution, blood alcohol content was assessed with an electronic breathalyzer on the morning of the infusion. Prior to entering the scanner, subjects received IV cannulation in each forearm: one IV for the placebo/ketamine infusion and one for blood draws during the scan. In the first scan session, an initial bolus of saline was administered over two minutes prior to collecting BOLD images, followed by a continuous maintenance infusion of saline throughout the remainder of the scan. In the second scan session, an initial bolus of racemic ketamine (0.23 mg/kg) diluted in saline solution was delivered just prior to data acquisition, followed by a continuous infusion of racemic ketamine (0.58 mg/kg/hr) throughout the remainder of the scan. Blood was drawn immediately after the resting-state run, and subsequent gas chromatography-mass spectrometry determined that the group mean serum ketamine concentration at the end of this run was 470 nmol/L. The scan was aborted and the participant removed for evaluation if, at any point, they expressed discomfort related to administration of the drug or placebo, or if they became unresponsive or showed any indications of an adverse reaction. Diazepam was available for anxiety in the event of a particularly negative response, but was never needed. Full neuroimaging protocol details can be found in (Figure 1). Figure 1 with 5 supplements see all Download asset Open asset Neuroimaging protocol. The study employed a single-blind within-subjects design, with participants blinded to their treatment condition. Forty participants received an IV cannulation in each forearm: one IV for the placebo/ketamine infusion and one for blood draws during the scan. Placebo was administered during the first neuroimaging can session, and ketamine (initial bolus 0.23 mg/kg, continuous infusion 0.58 mg/kg/hr) during the second because residual ketamine effects ruled out counterbalancing of the order. Blood was drawn immediately after the resting-state run. Cognitive effects were measured using a Spatial Working Memory task completed in the scanner. Subjective effects were measured 180 min post drug administration using the following scales: (1) Positive and Negative Syndrome Scale (PANSS), (2) Clinician Administered Dissociative States Scale (CADSS), and (3) Beck's Depression Inventory (BDI). Ketamine neuroimaging data acquisition Request a detailed protocol Neural data were collected using a Siemens 3T scanner with with a 32 channel head coil at the Yale Center for Biomedical Imaging. Imaging acquisition parameters were aligned with those of the Human Connectome Project (HCP) (Van Essen et al., 2013). High-resolution T1w and T2w structural images were acquired in 224 AC-PC aligned slices, 0.8 mm isotropic voxels. T1w images were collected with a magnetization-prepared rapid gradient-echo (MP-RAGE) pulse sequence (time repetition (TR)=2400ms, time echo (TE)=2.07ms, flip angle = 8°, field of view = 256 x 256 mm). T2w images were collected with a SCP pulse sequence (TR = 3200ms, TE = 564ms, flip angle = T2 var, field of view = 256 x 256 mm). Resting-state BOLD images were collected with a multi-band accelerated fast gradient-echo, echo-planar sequence (acceleration factor = 6, TR = TE = flip angle = field of view = x = x = aligned to the with mm isotropic voxels. A total of were acquired scan in a scan of a of reverse field maps and were acquired size = mm TR = TE = flip angle = field of view = = and neuroimaging data acquisition Request a detailed protocol assess the extent to which variability is specific to ketamine, we compared the neural effects of ketamine to the neural effects of and For the and we data from two pharmacological neuroimaging et al., 2018; et al., 2020). for the neuroimaging study are in in prior et al., 2018). The use of in was by the Swiss of The study protocol was approved by the Committee of The study employed a fully design with (1) placebo placebo and 1 after with placebo and 1 (2) placebo after with placebo and 1 or (3) after with the 5-HT2A Data were collected for all subjects in a order at different each two For all conditions, the first was administered min before the second and the first neural scan was conducted min after the second with a second scan conducted at min In the study, data from the (1) placebo and (2) placebo were for the neuroimaging study are in in prior et al., 2020). The use of in was by the Swiss of The study was at The study employed a fully Participants at two different 2 received placebo and 1 placebo or The resting-state scan was conducted at time between administration and and min after treatment administration. In the study, data from the and placebo neural conducted at min were Neuroimaging data Request a detailed protocol Neuroimaging data was with the Human Connectome Project (HCP) minimal et al., using the Neuroimaging Ji et al., A of the is as structural images were for and then to the brain in a single through a of and via the and et al., was used to brain-wide and to individual cortical and et al., 2012). were for and as well as for each the and a was along with which were to generate the neural file in the for each individual et al., 2013). BOLD data were by to the of run via in the initial In a was to from cortical BOLD data were to the by from the cortical and aligned to the using et al., 2013). were aligned to the using whole-brain and then the to the portion of the the minimal was et al., 2013). with in were identified if they at one of the following two (Anticevic et al., 2012). was by the across all body in which mm were mean was by the mean of differences in between the current and across all and it by the mean in which x the across the for each were also The as well as the the immediately and immediately following any were from further with more than were a was to the BOLD data to to scanner was used to the variation in BOLD in the and across the as well as These as well as their first to account for delayed were then out of the BOLD time as any in the BOLD to these are not to neural et al., 2018). It be that using global to is in neuroimaging et al., 2017; et al., but it a current see other and approaches at Glasser et al., 2018; et al., 2020). In order to address this we also the mean effect and neural PCA results (Figure Figure In addition, when we compared the results of the neural PCA with and we found that GBC with was significantly with the GBC (Figure In GBC with was not significantly with the GBC Figure This that when a PCA is on results the first captures a of the global that is removed when out Neural data via functional brain-wide Request a detailed protocol All neural data in this study is resting-state We the neural effects of ketamine at multiple levels of network and and were at the the and data were acquired using a derived whole-brain via the Brain

Type

peer-review

Language

en

Landing Page

https://doi.org/10.7554/elife.84173.sa2

OA Status

gold

Related Works

10

OpenAlex ID

https://openalex.org/W4394895791

Raw OpenAlex JSON

OpenAlex ID

https://openalex.org/W4394895791

Canonical identifier for this work in OpenAlex

DOI

https://doi.org/10.7554/elife.84173.sa2

Digital Object Identifier

Title

Author response: Ketamine induces multiple individually distinct whole-brain functional connectivity signatures

Work title

Type

peer-review

OpenAlex work type

Language

en

Primary language

Publication year

2024

Year of publication

Publication date

2024-01-08

Full publication date if available

Authors

Flora Moujaes, Jie Lisa Ji, Masih Rahmati, Joshua B. Burt, Charles Schleifer, Brendan Adkinson, Aleksandar Savić, Nicole Santamauro, Zailyn Tamayo, Caroline Diehl, Antonija Kolobaric, Morgan Flynn, Nathalie M. Rieser, Clara Fonteneau, Terry Camarro, Junqian Xu, Youngsun Cho, Grega Repovš, Sarah K. Fineberg, Peter Morgan, Erich Seifritz, Franz X. Vollenweider, John H. Krystal, John D. Murray, Katrin H. Preller, Alan Anticevic

List of authors in order

Landing page

https://doi.org/10.7554/elife.84173.sa2

Publisher landing page

Open access

Yes

Whether a free full text is available

OA status

gold

Open access status per OpenAlex

OA URL

https://doi.org/10.7554/elife.84173.sa2

Direct OA link when available

Concepts

Ketamine, Neuroscience, Parvalbumin, Functional connectivity, Psychology, Variation (astronomy), Placebo, Medicine, Physics, Pathology, Astrophysics, Alternative medicine

Top concepts (fields/topics) attached by OpenAlex

Cited by

0

Total citation count in OpenAlex

Related works (count)

10

Other works algorithmically related by OpenAlex

Full payload