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. 2021 Sep 30;15:749180. doi: 10.3389/fnbeh.2021.749180

A Multiscale View of the Mechanisms Underlying Ketamine’s Antidepressant Effects: An Update on Neuronal Calcium Signaling

Ayako Kawatake-Kuno 1, Toshiya Murai 1,2, Shusaku Uchida 1,*
PMCID: PMC8514675  PMID: 34658809

Abstract

Major depressive disorder (MDD) is a debilitating disease characterized by depressed mood, loss of interest or pleasure, suicidal ideation, and reduced motivation or hopelessness. Despite considerable research, mechanisms underlying MDD remain poorly understood, and current advances in treatment are far from satisfactory. The antidepressant effect of ketamine is among the most important discoveries in psychiatric research over the last half-century. Neurobiological insights into the ketamine’s effects have shed light on the mechanisms underlying antidepressant efficacy. However, mechanisms underlying the rapid and sustained antidepressant effects of ketamine remain controversial. Elucidating such mechanisms is key to identifying new therapeutic targets and developing therapeutic strategies. Accumulating evidence demonstrates the contribution of the glutamatergic pathway, the major excitatory neurotransmitter system in the central nervous system, in MDD pathophysiology and antidepressant effects. The hypothesis of a connection among the calcium signaling cascade stimulated by the glutamatergic system, neural plasticity, and epigenetic regulation of gene transcription is further supported by its associations with ketamine’s antidepressant effects. This review briefly summarizes the potential mechanisms of ketamine’s effects with a specific focus on glutamatergic signaling from a multiscale perspective, including behavioral, cellular, molecular, and epigenetic aspects, to provide a valuable overview of ketamine’s antidepressant effects.

Keywords: ketamine, antidepressant action, neuroplasticity, epigenetics, gene expression, stress, glutamate receptor, calcium signaling

Introduction

Major depressive disorder (MDD) is the leading cause of disability worldwide. Despite considerable research, biological mechanisms underlying MDD pathophysiology remain unclear, with significant unmet needs for treatment. Typical antidepressants, including selective serotonin reuptake inhibitors (SSRIs) and serotonin and noradrenaline reuptake inhibitors, increase monoamine concentration in the synaptic cleft, resulting in antidepressant effects (Berton and Nestler, 2006). However, although increased monoamine concentration in the synapse occurs relatively quickly as an acute pharmacological action, recovery from depression takes several weeks to months in clinical practice (Krishnan and Nestler, 2008). Electroconvulsive therapy (ECT) is also an effective treatment for drug-resistant depression, although achieving clinically meaningful or sustained remission with ECT required at least 1 month (Yamasaki et al., 2020). Such substantial time lags are a major concern since patients with depression are at high risk for suicide. Thus, there is an urgent need to develop antidepressants with rapid onset and sustained effectiveness.

Ketamine, a non-competitive glutamate N-methyl-D-aspartate receptor (NMDAR) antagonist, has gained considerable interest in the neuropsychiatric field. A single administration of ketamine elicits rapid and sustained antidepressant effects for 1–2 weeks in both humans and animals (Berman et al., 2000; Zarate et al., 2006; Li et al., 2010; Autry et al., 2011). This discovery offered new insight into the investigation of a whole new class of agents beyond the monoamine system to treat depression (Chaki, 2017). Esketamine, an enantiomer of (R,S)-ketamine, has been approved by the U.S. Food and Drug Administration (USFDA) for treating patients with treatment-resistant depression. Thus, research on pathophysiology and drug discovery for MDD has transitioned from the monoaminergic to the glutamatergic system. Recently, the importance of multiscale neuroscience to study cross-scale interactions at genetic, molecular, cellular, and macroscale levels of brain circuitry, connectivity, and behavior has been emphasized to establish a comprehensive understanding of neuropsychiatric disease (Van Den Heuvel et al., 2019). This mini-review aims to update the current knowledge regarding ketamine effect on the brain, focusing on the glutamatergic signaling pathway from a multiscale perspective at the behavioral, cellular, molecular, and epigenetic levels.

The Glutamatergic System in Neuroplasticity, Intracellular Signaling, and Gene Expression

Glutamate is the major excitatory neurotransmitter in the brain, and increasing evidence indicates that dysfunction in glutamatergic signaling contributes to MDD pathophysiology (Popoli et al., 2011; Duman and Aghajanian, 2012; Thompson et al., 2015; Duman et al., 2019; Xia et al., 2021). The glutamatergic system is modulated by both ionotropic [NMDARs, α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs), and kainate receptors] and metabotropic glutamate receptors (mGluRs). NMDARs are found throughout the central nervous system and contribute to synaptic calcium (Ca2+) influx, which is required for activity-dependent synaptic plasticity (Koester and Sakmann, 1998; Reid et al., 2001; Ngo-Anh et al., 2005; Bloodgood and Sabatini, 2007; Carter et al., 2007). NMDAR function is tightly linked to AMPAR, which gates sodium and mediates fast excitatory transmission. Increased AMPAR density in the postsynaptic membrane causes NMDAR-dependent long-term potentiation (LTP) (Huganir and Nicoll, 2013). AMPARs can also have several direct effects on synaptic transmission (i.e., LTP) and intracellular signals without the proper functioning of NMDARs. This NMDAR-independent and AMPAR-dependent intracellular signaling pathway is also hypothesized to underlie ketamine’s antidepressant actions (Zanos et al., 2016; Duman et al., 2019; Wei et al., 2021).

Ca2+ influx into the postsynaptic neuron stimulates a signaling-cascade, such as calcium/calmodulin-dependent kinases [CAMKs; e.g., calcium/calmodulin-dependent kinase II (CaMKIIs), eukaryotic elongation factor 2 (eEF2) kinase]. Brain-derived neurotrophic factor (BDNF) and its receptor, neurotrophic receptor tyrosine kinase 2 (TrkB), also plays a key role in synaptic plasticity (Minichiello, 2009). TrkB activation stimulates phospholipase Cγ1 (PLCγ1), which results in CaMK activation (Minichiello, 2009). Calcium-signaling activation further sends its signal toward downstream epigenetic and transcription modulators, such as MEF2, MeCP2, and HDAC5. These pathways modulate gene expression that affects dendritic growth, synaptic development, and neuronal plasticity (Greer and Greenberg, 2008; Graff and Tsai, 2013; Takemoto-Kimura et al., 2017; Uchida and Shumyatsky, 2018a,b; Figure 1). Taken together, calcium-signaling stimulation through NMDARs and/or AMPARs activates multiple downstream nucleocytoplasmic pathways; it induces activity-dependent epigenetic genetic expression, contributing to depression and antidepressant action.

FIGURE 1.

FIGURE 1

Proposed mechanisms of ketamine’s antidepressant action. The binding of ketamine to N-methyl-D-aspartate receptors (NMDARs) on GABAergic interneurons disinhibits glutamatergic neurons, which results in increased synaptic glutamate release. AMPAR activation by glutamate increases brain-derived neurotrophic factor (BDNF) levels. Although the exact source of BDNF is yet to be determined, local release of BDNF is thought to stimulate TrkB receptors. This activation activates intracellular signaling, such as the Ca2+ pathway. Another mechanism is the direct inhibition of NMDAR by ketamine. Inhibiting postsynaptic NMDARs reduces eEF2 via the inactivation of CaMK (eEF2 kinase), which leads to enhanced local protein synthesis of BDNF. Increased intracellular Ca2+ stimulates CaMKs and their downstream targets, including MeCP2, MEF2, and HDAC5. MeCP2, a transcriptional regulator, binds to methylated CpG sites on the genomic region and interacts with other transcription repressors, including HDACs. CaMKII phosphorylates MeCP2, promotes its nuclear export, and increases activity-dependent transcription. MEF2 recruits HDAC5 and removes activating acetyl groups from histones, which results in a silenced or repressed state of transcription. CaMKII phosphorylates HDAC5, which promotes nuclear export and increases activity-dependent transcription. Ketamine is known to increase the phosphorylation of CaMKII, MeCP2, and HDAC5 (see detail in the main text). Thus, ketamine-mediated enhancement of intracellular Ca2+ signaling is linked to epigenetic regulation of transcription, which leads to long-term synaptic plasticity and, consequently, prolonged antidepressant-like effects.

Chronic stress initiates and exacerbates several psychiatric illnesses. Indeed, adverse stressful environments are associated with the pathophysiology of major psychiatric disorders, including mood and anxiety disorders (Mcewen, 2007; Krishnan and Nestler, 2008; Duman and Aghajanian, 2012). There are several evidences demonstrating alterations in the expression and/or function of glutamatergic signaling and its downstream molecules (e.g., NMDARs, AMPARs, CaMKIIs, MEF2, MeCP2, and HDAC5), which is associated with plasticity and behaviors induced by chronic stress, traditional antidepressant drugs, and/or ketamine (Table 1). Moreover, molecular dysregulation associated with glutamatergic system is visible in postmortem brain tissues of patients with MDD (Table 1). Thus, such clinical and preclinical evidences suggest that calcium-signaling is a downstream target of the glutamatergic system in MDD pathophysiology and antidepressant effects.

TABLE 1.

Example evidence indicates alterations in behavior, glutamatergic signaling, and its downstream pathways regarding depression, chronic stress, and antidepressants: translational and multiscale views.

Behaviors
Findings References
Ketamine’s effects on a stress-induced animal model of depression CUMS-induced increase of immobility in TST were reversed 0.5 and 72 h after ketamine treatment in rats Sun et al., 2016
CUS-induced reduction in sucrose preference in SPT was reversed by ketamine 24 h after injection in rats Li et al., 2011
CSDS-induced reduction of social interaction was reversed 24 h after (2R, 6R)-HNK treatment in mice Zanos et al., 2016
CSDS-induced depression-like behaviors were reversed 24 h after (R)-ketamine treatment in mice Yang C. et al., 2018
Ketamine’s effects on pharmacological model of depression Chronic CORT effects on immobility in TST, open-arm exploration in an elevated plus maze and sucrose preference were reversed 24h after ketamine treatment in mice Moda-Sava et al., 2019
Chronic CORT-induced anhedonia in a sucrose preference test was recovered by (2S, 6S)-HNK treatment Zanos et al., 2016
LPS-induced increase of immobility in FST was reversed by (R)- Ketamine, but not (R)- HNK, in mice Yamaguchi et al., 2018
Chronic CORT-induced anhedonia and increased immobility time in FST were improved by (2S, 6S)-HNK, but not (2R, 6R)-HNK Yokoyama et al., 2020
Neuroplasticity
Findings References
MDD patients Postmortem brain of MDD patients showed a lower number of synapses in dlPFC Kang et al., 2012
Meta-analysis of structural imaging studies demonstrated that MDD patients have smaller hippocampus volumes Macqueen and Frodl, 2011
Meta-analysis of imaging showed the structural and functional decline in dmPFC of MDD patients Price and Drevets, 2010
Stress-induced animal model of depression CUS decreases the number and function of spine synapses in the mPFC Li et al., 2011
Reduced spine density in the hippocampus and mPFC of mice susceptible to CUMS and CSDS Abe-Higuchi et al., 2016; Higuchi et al., 2016; Nie et al., 2018; Sakai et al., 2021
Repeated stress impairs glutamatergic transmission in PFC pyramidal neurons Yuen et al., 2012
Ketamine’s effect (S)-ketamine normalized habenula, midline thalamus, and hippocampal connectivity at 48 h in fMRI imaging of stressed rats Gass et al., 2019
Ketamine blocks NMDAR spontaneous activity Autry et al., 2011
Ketamine treatment restores lost spines by chronic CORT exposure and promote generating functional synapses in mice Moda-Sava et al., 2019
Ketamine treatment increases the number and function of spine synapse in rat mPFC Li et al., 2010
(2R,6R)-HNK increased fEPSC slope in SC-CA1 of rats Zanos et al., 2016
(2S,6S)-HNK caused no changes in sEPSC frequency or amplitudes in rat CA1 interneurons (but has antidepressant effect) Chen et al., 2012
Molecular pathway/Intracellular signaling
Molecules Findings References
NMDARs MDD and stress model
A postmortem prefrontal cortex showed increased levels of NR1 in MDD Rodriguez-Munoz et al., 2017
Reduced GluN2A in prefrontal cortex of MDD Beneyto and Meador-Woodruff, 2008
MK801, a NMDAR antagonist, injection reduced immobility in FST Autry et al., 2011
CUS-induced reduction in sucrose preference in SPT was reversed by a selective NR2B antagonist, Ro 25-6981, 24 h after injection in rats Li et al., 2011
Ketamine
Ketamine treatment increases NR1 expression levels in mouse PFC Liu et al., 2011
Ketamine and a high dose of (2R, 6R)-HNK influences NMDAR-mediated eEF2 phosphorylation Autry et al., 2011; Suzuki et al., 2017
(2R, 6R)-HNK do not block NMDAR function Lumsden et al., 2019
AMPARs MDD and stress model
Postmortem cortical tissue from MDD patients showed decreased GluA1 levels Beneyto et al., 2007
Reduced GluA1 level in the hippocampus of stress-susceptible mice AMPAR potentiator drives stress resilience, whereas GluA1 inhibition leads to stress susceptibility Sakai et al., 2021
Ketamine
Ketamine increased the level of GluA1 subunit in the mouse hippocampus Beurel et al., 2016
(2R, 6R)-HNK increased synaptic GluA1 and GluA2 protein expression in the mouse hippocampus Zanos et al., 2016
BDNF/TrkB MDD and stress model
Postmortem brain tissues from the hippocampus and prefrontal cortex in suicide subjects showed reduced expression of BDNF and TrkB Dwivedi et al., 2003
BDNF levels were lower in the anterior cingulate of postmortem brains of subjects with early life adversity and/or died by suicide Youssef et al., 2018
Ketamine
CUMS-induced reduction of the expression of BDNF was reversed 0.5 and 72 h after ketamine treatment in rats Sun et al., 2016
The deletion of BDNF or TrkB in broad forebrain regions of mice blocks ketamine’s antidepressant effects Nosyreva et al., 2013, 2014
Neutralizing a BDNF antibody into the mPFC blocks the behavioral effects of ketamine in FST Lepack et al., 2014
(2R,6R)-HNK increased BDNF protein levels 24 h after injection in mouse hippocampus Zanos et al., 2016
(2S,6S)-HNK increased extracellular BDNF levels in the mouse prefrontal cortex Anderzhanova et al., 2020
CaMKIIs MDD and stress model
A postmortem study showed decreased levels of CAMK2B in the anterior cingulate cortex of MDD Seney et al., 2018
A postmortem prefrontal cortex study showed decreased levels of CAMK2A in MDD Fuchsova et al., 2015
A postmortem prefrontal cortex study showed increased levels of CAMK2A in MDD Tochigi et al., 2008
CaMKIIβ levels in the ventral HPC were lower in mice following CUMS. CaMKIIβ activation reversed depression-like behaviors Sakai et al., 2021
Ketamine
CaMKIIβ activity is increased at 3 days after ketamine injection Kim et al., 2021
MeCP2 MDD and stress model
p-MeCP2 levels decreased in the hippocampus and prefrontal cortex of suicide victims Misztak et al., 2020
MeCP2 complexes determine stress susceptibility and resilience in mice Uchida et al., 2011
Ketamine
p-MeCP2 is required for ketamine-induced metaplasticity and antidepressant effects Kim et al., 2021
MEF2C MDD and stress model
MEF2C is one of the candidate risk genes for MDD Hyde et al., 2016
Ketamine
Ketamine enhances the transcriptional activity of MEF2 in mice hippocampus Choi et al., 2015
HDAC5 MDD and stress model
Increased HDAC5 level in MDD Iga et al., 2007; Hobara et al., 2010
HDAC5 overexpression in the hippocampus disrupts antidepressant-like effect of traditional antidepressant Tsankova et al., 2006
HDAC 4/5 inhibitor induces antidepressant-like behavioral effects in mice Higuchi et al., 2016
Ketamine
Ketamine induces the phosphorylation of HDAC5 at 30 min and 24 h after administration in mice hippocampus Choi et al., 2015

CUMS, chronic unpredictable mild stress; CUS, chronic unpredictable stress; CSDS, chronic social defeat stress; CORT, corticosterone; LPS, lipopolysaccharide; HNK, hydroxynorketamine; MDD, major depressive disorder; SSRI, selective serotonin reuptake inhibitor; FST, forced-swimmed test; SPT, sucrose preference test; TST, tail suspension Test; sEPSC, spontaneous excitatory postsynaptic current; fEPSC, field excitatory postsynaptic current; dlPFC, dorsolateral prefrontal cortex; mPFC, medial prefrontal cortex; dmPFC, dorsomedial prefrontal cortex.

Mechanisms of Ketamine’s Antidepressant Effects: A Multiscale View

Less than one-third of patients with MDD achieve remission using traditional antidepressant pharmacotherapy (Trivedi et al., 2006). Treatment resistance occurs in up to 30% of patients with MDD (Fava, 2003). However, a single subanesthetic dose of ketamine produces a therapeutic response within a few hours that lasts for several days in patients with depression (Berman et al., 2000; Zarate et al., 2006). Intravenous infusion of ketamine results in clinical response and remission in 70 and 30% of treatment-resistant patients with MDD, respectively (Zarate et al., 2006). Additionally, Ketamine reduces suicidal ideation (Krystal et al., 2013). In 2020, esketamine was approved by the USFDA for treating depressive symptoms in adults with MDD having acute suicidal ideation or behavior.

Ketamine elicits robust unwanted side effects, including prepulse-inhibition deficits, cognitive deficits, and schizophrenia-like psychotic symptoms in humans (Lahti et al., 1995; Chan et al., 2013; Giorgetti et al., 2015). Recent preclinical data indicate that ketamine’s enantiomer (R)-ketamine (Hashimoto, 2019; Wei et al., 2021) and its metabolites (2R, 6R)-hydroxynorketamine (HNK) (Zanos et al., 2016) exert antidepressant effects with fewer adverse effects than do ketamine or (S)-ketamine. Since potential mechanisms underlying the rapid antidepressant actions of ketamine and its metabolites have been reviewed elsewhere (Fukumoto et al., 2017; Yang C. et al., 2018; Duman et al., 2019; Krystal et al., 2019; Sial et al., 2020; Highland et al., 2021; Shinohara et al., 2021; Wei et al., 2021; Xia et al., 2021), we review the recent progress in deciphering mechanisms underlying ketamine’s sustained antidepressant effects, with a particular focus on the role of calcium signaling from a multiscale perspective.

Behavioral Effects of Ketamine

Several animal studies have demonstrated antidepressant-like responses to ketamine. A single intraperitoneal injection of ketamine or its metabolites produces rapid (30 min–1 h) and long-lasting (24 h–7 days) antidepressant effects (Autry et al., 2011; Koike et al., 2011; Zhou et al., 2014; Sun et al., 2016; Zanos et al., 2016; Yang C. et al., 2018; Kim et al., 2021). Moreover, such ketamine antidepressant effects have been observed in not only naïve, non-stressed animals but also in animals subjected to adverse stressful life events. Animals exposed to chronic stress show despair-like behavior, anhedonia, anxiety, and/or social avoidance, whereas a single injection of ketamine or its metabolites rapidly reverses these deleterious effects and exerts long-term effects (Li et al., 2011; Zanos et al., 2016; Duman et al., 2019; Wei et al., 2021).

Neurobiological Effects of Ketamine

Neuroimaging studies have shown structural and functional alterations in the hippocampus and dorsomedial prefrontal cortex (dmPFC) of patients with MDD (Price and Drevets, 2010; Macqueen and Frodl, 2011). Human functional magnetic resonance imaging (MRI) studies have demonstrated that a single dose of ketamine ameliorates reductions in functional connectivity in the prefrontal cortex (PFC), which is associated with the alleviation of depressive symptoms (Abdallah et al., 2017). Interestingly, a recent MRI study in animals demonstrated short- and long-term effects of ketamine on distinct brain circuitry. Gass et al. (2019) found in an animal model of depression that ketamine causes a rapid response in the amygdala, anterodorsal hippocampus, and ventral pallidum, which are related to cognitive, sensory, emotional, and reward functions. However, 48 h after administration, ketamine showed a long-term normalization of the habenula, midline thalamus, and hippocampal connectivity. They mediate cognitive flexibility for processing contextual information, distinguish contextual cues in safe versus threatening situations, and modulate fear and emotional responses in non-threatening environments (Gass et al., 2019).

There is increasing evidence suggesting altered neuronal and structural plasticity in animal models of depression as well as in patients with MDD (Duman and Aghajanian, 2012; Kang et al., 2012; Abe-Higuchi et al., 2016; Higuchi et al., 2016; Nie et al., 2018; Uchida et al., 2018; Sakai et al., 2021). Ketamine rapidly increases the number and function of spine synapses. Furthermore, Li et al. found that ketamine increases the number and function of spine synapses in the medial PFC (mPFC) and rapidly reverses synaptic abnormalities caused by chronic stress exposure (Li et al., 2010). Although this evidence suggests an association between ketamine-induced spinogenesis and antidepressant-like behavior, the causal relationship is unclear. However, a recent report by Moda-Sava et al. has addressed this issue. They used a photoactivable proof to selectively reverse ketamine effects on spine formation in the PFC. They found that newly formed spines are necessary for and play a specific role in the sustained antidepressant-like behavior induced by ketamine treatment (Moda-Sava et al., 2019).

Ketamine-Induced Synaptic Plasticity

Brain-derived neurotrophic factor and its receptor TrkB play key roles in synaptic plasticity, stress, and depression (Duman and Monteggia, 2006; Minichiello, 2009; Castren and Monteggia, 2021). A recent report discovered that several antidepressants, including fluoxetine, imipramine, and ketamine, directly bind to TrkB, facilitating BDNF action and plasticity (Casarotto et al., 2021). In addition, increased BDNF-TrkB signaling in rodent frontocortical/hippocampal circuits has been observed following acute treatment with ketamine (Li et al., 2010; Autry et al., 2011).

Clinical evidence suggests that repeated ketamine administration allows cumulative and sustained antidepressant effects and that it is more effective than a single injection in patients with MDD (Aan Het Rot et al., 2010; Murrough et al., 2013; Phillips et al., 2019). The threshold and sensitivity of the persistent increase and decrease of synaptic strength are subject to activity-dependent regulation. This type of plasticity, called “metaplasticity,” is important for stabilizing synaptic strength and preventing LTP saturation and long-term depression, leading to homeostatic alternations of synaptic activation (Bienenstock et al., 1982; Turrigiano et al., 1998; Kavalali and Monteggia, 2020). Notably, a preclinical study suggested that ketamine administration elicits metaplastic effects on LTP modulation and potentially other processes for long term. Kim et al. (2021) reported that, by using slice recordings of the Schaffer collateral-CA1 pathway in the hippocampus, ketamine induces AMPAR-mediated synaptic potentiation. Interestingly, this effect was more than two-fold higher in brain slices of mice that had received ketamine 7 days earlier, suggesting a priming effect of ketamine treatment such that subsequent ketamine augments synaptic potentiation. Further experiments to understand the mechanisms of this metaplasticity will provide critical insight into mechanisms underlying ketamine’s potent and prolonged antidepressant effects.

Ketamine-Induced Ca2+ Signaling Cascades

N-methyl-D-aspartate receptors activate eEF2 via CaMKs (eEF2 kinases) and depress BDNF levels (Scheetz et al., 2000). Ketamine-induced suppression of postsynaptic NMDARs deactivates eEF2 kinase, leading to reduced eEF2 phosphorylation and increased translation of BDNF in the hippocampus (Autry et al., 2011; Suzuki and Monteggia, 2020). This signaling pathway then potentiates synaptic AMPAR responses through the insertion of GluA1/2 subunits (Autry et al., 2011). In contrast, ketamine’s metabolite (2R, 6R)-HNK has NMDAR inhibition-independent antidepressant actions (Zanos et al., 2016; Lumsden et al., 2019), whereas other reports have shown that NMDAR inhibition at a high dose of (2R, 6R)-HNK triggers intracellular signaling via eEF2 (Suzuki et al., 2017).

A transient burst of glutamate via NMDAR blockade on GABAergic interneurons by ketamine activates postsynaptic AMPARs in excitatory neurons. This activation induces depolarization and activation of NMDARs that trigger Ca2+ influx, releasing BDNF (Krystal et al., 2019). Local release of BDNF is thought to activate TrkB on the postsynaptic membrane, stimulating the ERK and PI3K-Akt signaling pathways and mammalian target of rapamycin complex 1 (mTORC1) phosphorylation to promote synapse formation by stimulating synaptic proteins, such as GluA1 and PSD-95, which are required for synaptic plasticity (Cavalleri et al., 2018). Recently, mTORC1 effectors 4E-BP2 and 4-EB2 in excitatory or inhibitory neurons underlie behavioral and neurobiological responses to ketamine (Aguilar-Valles et al., 2021). Ketamine-induced activation of TrkB increases GSK-3β phosphorylation via the ERK signaling pathway, decreasing PSD-95 phosphorylation and internalizing the AMPA GluA1 subunit, which upregulates signaling through the GluA1 to promote synapse formation (Liu et al., 2013; Beurel et al., 2016). Ketamine-dependent changes in dendritic arborization and soma size are abolished by AMPAR antagonists or mTOR complex/signaling inhibitors (Cavalleri et al., 2018). Intracellular molecular signaling cascades stimulated by the glutamatergic pathway may be associated with ketamine-induced structural and synaptic plasticity and its antidepressant effects.

As mentioned earlier, CaMKIIs are major downstream target for the glutamatergic pathway and might be involved in stress and depression. TrkB activation stimulates phospholipase Cγ1 (PLCγ1) and also results in the activation of CaMKs (Minichiello, 2009). Activated CaMKIIs further stimulate MeCP2 phosphorylation (Zhou et al., 2006), allowing the transcription of downstream target genes. A recent study showed that MeCP2 phosphorylation at S421 (p-MeCP2) is essential for the expression of metaplasticity and the sustained, but not acute, antidepressant effects of ketamine (Kim et al., 2021). Hippocampal BDNF protein levels were shown to increase rapidly 30 min after ketamine administration but returned to baseline 3 days after injection. In contrast, hippocampal p-MeCP2 levels increased 3 and 7 days, but not 30 min, after ketamine injection. CaMKIIβ were elevated at 3 days after ketamine injection but returned to baseline at 7 days. These findings indicate that CaMKIIβ plays a role in the intermediary process between BDNF activation and MeCP2 phosphorylation required for the sustained antidepressant effects of ketamine. This hypothesis is also supported, at least in part, by a recent finding that hippocampal CaMKIIβ is downregulated in chronic stress-susceptible mice and that short-term (within 4 days) CaMKIIβ activation ameliorates depression-like behaviors (Sakai et al., 2021).

Epigenetic Regulation of Gene Transcription by Ketamine

The interplay between genetic and environmental factors underlies depression pathophysiology, and epigenetic mechanisms might contribute to these interactions (Nestler et al., 2016; Uchida et al., 2018; Kawatake-Kuno et al., 2021). Although accumulating evidence demonstrated altered epigenetic functioning in animal models of depression and postpartum MDD-patient brains, few studies have used ketamine-induced transcriptome and epigenome analyses to characterize ketamine’s antidepressant effects. Genome-wide transcriptome and epigenome mapping offer a template for several strategies to identify novel drug targets in unbiased ways to develop more effective treatments for MDD (Bagot et al., 2017). Here we summarize how ketamine-induced activation of Ca2+ signal influences epigenetic regulation of gene transcription.

MeCP2, MEF2, and HDAC5 functions are regulated by Ca2+ signaling and are associated with stress and depression (Table 1). As mentioned above, p-MeCP2 is necessary for sustained antidepressant response to ketamine (Kim et al., 2021). MeCP2 is a methylated cytosine reader that impacts chromatin organization with any change in DNA methylation. A previous report showed that chronic stress differentially modulates MeCP2 activity in stress-resilient and -susceptible mice and subsequent epigenetic gene transcription (Uchida et al., 2011). Thus, ketamine-induced enhancement of p-MeCP2 may be associated with the formation of chromatin-remodeling complexes on target genes and, thus, transcription regulation. HDAC5 is a histone deacetylase, and its phosphorylation by CaMKs is associated with transcription repression (Mckinsey et al., 2000). Hippocampal HDAC5 is associated with behavioral response to chronic stress and traditional antidepressants (e.g., imipramine and SSRIs) (Tsankova et al., 2006; Higuchi et al., 2016). A recent study suggested that ketamine rapidly induces HDAC5 phosphorylation and nuclear export through CaMKII-dependent pathways, which leads to enhanced MEF2 transcription that regulates neuronal structural and functional plasticity (Choi et al., 2015). Correspondingly, HDAC5 knockdown occludes the actions of ketamine. Moreover, MeCP2 is considered as a master regulator of metaplasticity (Chen et al., 2012). Ca2+-signal-mediated modulation of MeCP2, HDAC5, and MEF2 functions may be involved in the sustained antidepressant response of ketamine through epigenetic transcription.

Conclusion

This mini-review highlights that the glutamatergic pathway is associated with behavioral, neuroplastic, neurobiological, molecular, and epigenetic effects of ketamine, focusing on Ca2+ signaling wherein its dysfunction is involved in depression pathophysiology according to both clinical and animal studies. Such (reverse) translational implications for bridging the research gap between human depression and animal models will provide a better understanding of how ketamine affects and modulates depression pathophysiology and ultimately contribute to the clinical application of ketamine or the development of related compounds for wide range of psychiatric disorders. Glutamatergic transmission and monoaminergic systems induce rapid biological changes that induce fast antidepressant effects. In contrast, ketamine’s sustained antidepressant actions are likely mediated by intracellular Ca2+ signaling cascades that affect neurobiological processes, including dendritic spine formation, epigenetic modifications, and long-term synaptic plasticity, and consequently, maintain physiological functioning.

In this mini-review, we particularly focused on the hippocampus and prefrontal cortex, key brain regions associated with MDD pathophysiology and ketamine’s antidepressant effect. However, other brain regions were suggested to also be involved in these processes, such as the lateral habenula. Emerging evidence from preclinical and clinical studies identified an important role of the lateral habenula in depression and ketamine’s antidepressant effect through a glutamatergic pathway (Li et al., 2013; Cui et al., 2018a,b, 2019; Yang et al., 2018; Hu, 2019, Hu et al., 2020). In addition, dynamic molecular changes were observed in the nucleus accumbens of animal models of depression and ketamine-treated animals (Bagot et al., 2017). Thus, future studies are warranted to clarify how ketamine impacts neuronal circuit activity and identify underlying molecular and epigenetic mechanisms.

In summary, ketamine has great potential in the development of groundbreaking neuropsychiatric therapies. Our current understanding of depression pathophysiology and ketamine’s action suggests that diverse drug actions converge around Ca2+-signaling-mediated neural plasticity. However, ketamine plays diverse roles in the glutamatergic pathway and other neurotransmitter systems, neurogenesis, inflammation, and even body–brain crosstalk. Furthermore, several studies have suggested the distinct roles of ketamine enantiomers ([S]-ketamine and [R]-ketamine) and their metabolites ([2R,6R]-HNK and [2S,6S]-HNK) in plasticity and behavior (Zanos et al., 2016; Yamaguchi et al., 2018; Hashimoto, 2019; Lumsden et al., 2019; Yokoyama et al., 2020; Highland et al., 2021; Wei et al., 2021). Thus, mechanisms underlying ketamine’s actions remain controversial. Moreover, ketamine effects at the mesoscale of neural architecture and macroscale of neural connectivity, cognition, and behavior are poorly understood. Further investigations at both the multiscale and multisystem levels are necessary to comprehensively understand mechanisms underlying ketamine’s antidepressant effects and develop novel drugs for treating MDD.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Funding

This work was supported by JSPS KAKENHI Grant Numbers JP21K19707 and JP18H02750, by MEXT KAKENHI Grant Number JP21H00198, and by AMED under Grant Numbers JP21ak0101136 and JP21dm0307102h0003.

References

  1. Aan Het Rot M., Collins K. A., Murrough J. W., Perez A. M., Reich D. L., Charney D. S., et al. (2010). Safety and efficacy of repeated-dose intravenous ketamine for treatment-resistant depression. Biol. Psychiatry 67 139–145. 10.1016/j.biopsych.2009.08.038 [DOI] [PubMed] [Google Scholar]
  2. Abdallah C. G., Averill L. A., Collins K. A., Geha P., Schwartz J., Averill C., et al. (2017). Ketamine Treatment and Global Brain Connectivity in Major Depression. Neuropsychopharmacology 42 1210–1219. 10.1038/npp.2016.186 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Abe-Higuchi N., Uchida S., Yamagata H., Higuchi F., Hobara T., Hara K., et al. (2016). Hippocampal Sirtuin 1 Signaling Mediates Depression-like Behavior. Biol. Psychiatry 80 815–826. 10.1016/j.biopsych.2016.01.009 [DOI] [PubMed] [Google Scholar]
  4. Aguilar-Valles A., De Gregorio D., Matta-Camacho E., Eslamizade M. J., Khlaifia A., Skaleka A., et al. (2021). Antidepressant actions of ketamine engage cell-specific translation via eIF4E. Nature 590 315–319. 10.1038/s41586-020-03047-0 [DOI] [PubMed] [Google Scholar]
  5. Anderzhanova E., Hafner K., Genewsky A. J., Soliman A., Pohlmann M. L., Schmidt M. V., et al. (2020). The stress susceptibility factor FKBP51 controls S-ketamine-evoked release of mBDNF in the prefrontal cortex of mice. Neurobiol. Stress 13:100239. 10.1016/j.ynstr.2020.100239 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Autry A. E., Adachi M., Nosyreva E., Na E. S., Los M. F., Cheng P. F., et al. (2011). NMDA receptor blockade at rest triggers rapid behavioural antidepressant responses. Nature 475 91–95. 10.1038/nature10130 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Bagot R. C., Cates H. M., Purushothaman I., Vialou V., Heller E. A., Yieh L., et al. (2017). Ketamine and Imipramine Reverse Transcriptional Signatures of Susceptibility and Induce Resilience-Specific Gene Expression Profiles. Biol. Psychiatry 81 285–295. 10.1016/j.biopsych.2016.06.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Beneyto M., Kristiansen L. V., Oni-Orisan A., Mccullumsmith R. E., Meador-Woodruff J. H. (2007). Abnormal glutamate receptor expression in the medial temporal lobe in schizophrenia and mood disorders. Neuropsychopharmacology 32 1888–1902. 10.1038/sj.npp.1301312 [DOI] [PubMed] [Google Scholar]
  9. Beneyto M., Meador-Woodruff J. H. (2008). Lamina-specific abnormalities of NMDA receptor-associated postsynaptic protein transcripts in the prefrontal cortex in schizophrenia and bipolar disorder. Neuropsychopharmacology 33 2175–2186. 10.1038/sj.npp.1301604 [DOI] [PubMed] [Google Scholar]
  10. Berman R. M., Cappiello A., Anand A., Oren D. A., Heninger G. R., Charney D. S., et al. (2000). Antidepressant effects of ketamine in depressed patients. Biol. Psychiatry 47 351–354. 10.1016/s0006-3223(99)00230-9 [DOI] [PubMed] [Google Scholar]
  11. Berton O., Nestler E. J. (2006). New approaches to antidepressant drug discovery: beyond monoamines. Nat. Rev. Neurosci. 7 137–151. 10.1038/nrn1846 [DOI] [PubMed] [Google Scholar]
  12. Beurel E., Grieco S. F., Amadei C., Downey K., Jope R. S. (2016). Ketamine-induced inhibition of glycogen synthase kinase-3 contributes to the augmentation of alpha-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) receptor signaling. Bipolar. Disord. 18 473–480. 10.1111/bdi.12436 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Bienenstock E. L., Cooper L. N., Munro P. W. (1982). Theory for the development of neuron selectivity: orientation specificity and binocular interaction in visual cortex. J. Neurosci. 2 32–48. 10.1523/JNEUROSCI.02-01-00032.1982 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Bloodgood B. L., Sabatini B. L. (2007). Nonlinear regulation of unitary synaptic signals by CaV(2.3) voltage-sensitive calcium channels located in dendritic spines. Neuron 53 249–260. 10.1016/j.neuron.2006.12.017 [DOI] [PubMed] [Google Scholar]
  15. Carter A. G., Soler-Llavina G. J., Sabatini B. L. (2007). Timing and location of synaptic inputs determine modes of subthreshold integration in striatal medium spiny neurons. J. Neurosci. 27 8967–8977. 10.1523/JNEUROSCI.2798-07.2007 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Casarotto P. C., Girych M., Fred S. M., Kovaleva V., Moliner R., Enkavi G., et al. (2021). Antidepressant drugs act by directly binding to TRKB neurotrophin receptors. Cell 184 1299–1313e1219. 10.1016/j.cell.2021.01.034 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Castren E., Monteggia L. M. (2021). Brain-Derived Neurotrophic Factor Signaling in Depression and Antidepressant Action. Biol. Psychiatry 90 128–136. 10.1016/j.biopsych.2021.05.008 [DOI] [PubMed] [Google Scholar]
  18. Cavalleri L., Merlo Pich E., Millan M. J., Chiamulera C., Kunath T., Spano P. F., et al. (2018). Ketamine enhances structural plasticity in mouse mesencephalic and human iPSC-derived dopaminergic neurons via AMPAR-driven BDNF and mTOR signaling. Mol. Psychiatry 23 812–823. 10.1038/mp.2017.241 [DOI] [PubMed] [Google Scholar]
  19. Chaki S. (2017). Beyond Ketamine: New Approaches to the Development of Safer Antidepressants. Curr. Neuropharmacol. 15 963–976. 10.2174/1570159X15666170221101054 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Chan K. W., Lee T. M., Siu A. M., Wong D. P., Kam C. M., Tsang S. K., et al. (2013). Effects of chronic ketamine use on frontal and medial temporal cognition. Addict. Behav. 38 2128–2132. 10.1016/j.addbeh.2013.01.014 [DOI] [PubMed] [Google Scholar]
  21. Chen S. X., Cherry A., Tari P. K., Podgorski K., Kwong Y. K., Haas K. (2012). The transcription factor MEF2 directs developmental visually driven functional and structural metaplasticity. Cell 151 41–55. 10.1016/j.cell.2012.08.028 [DOI] [PubMed] [Google Scholar]
  22. Choi M., Lee S. H., Wang S. E., Ko S. Y., Song M., Choi J. S., et al. (2015). Ketamine produces antidepressant-like effects through phosphorylation-dependent nuclear export of histone deacetylase 5 (HDAC5) in rats. Proc. Natl. Acad. Sci. U S A 112 15755–15760. 10.1073/pnas.1513913112 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Cui Y., Hu S., Hu H. (2019). Lateral Habenular Burst Firing as a Target of the Rapid Antidepressant Effects of Ketamine. Trends Neurosci. 42 179–191. 10.1016/j.tins.2018.12.002 [DOI] [PubMed] [Google Scholar]
  24. Cui Y., Yang Y., Dong Y., Hu H. (2018a). Decoding Depression: Insights from Glial and Ketamine Regulation of Neuronal Burst Firing in Lateral Habenula. Cold Spr. Harb. Symp. Quant. Biol. 83 141–150. 10.1101/sqb.2018.83.036871 [DOI] [PubMed] [Google Scholar]
  25. Cui Y., Yang Y., Ni Z., Dong Y., Cai G., Foncelle A., et al. (2018b). Astroglial Kir4.1 in the lateral habenula drives neuronal bursts in depression. Nature 554 323–327. 10.1038/nature25752 [DOI] [PubMed] [Google Scholar]
  26. Duman R. S., Aghajanian G. K. (2012). Synaptic dysfunction in depression: potential therapeutic targets. Science 338 68–72. 10.1126/science.1222939 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Duman R. S., Monteggia L. M. (2006). A neurotrophic model for stress-related mood disorders. Biol. Psychiatry 59 1116–1127. 10.1016/j.biopsych.2006.02.013 [DOI] [PubMed] [Google Scholar]
  28. Duman R. S., Shinohara R., Fogaca M. V., Hare B. (2019). Neurobiology of rapid-acting antidepressants: convergent effects on GluA1-synaptic function. Mol. Psychiatry 24 1816–1832. 10.1038/s41380-019-0400-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Dwivedi Y., Rizavi H. S., Conley R. R., Roberts R. C., Tamminga C. A., Pandey G. N. (2003). Altered gene expression of brain-derived neurotrophic factor and receptor tyrosine kinase B in postmortem brain of suicide subjects. Arch. Gen. Psychiatry 60 804–815. 10.1001/archpsyc.60.8.804 [DOI] [PubMed] [Google Scholar]
  30. Fava M. (2003). Diagnosis and definition of treatment-resistant depression. Biol. Psychiatry 53 649–659. 10.1016/s0006-3223(03)00231-2 [DOI] [PubMed] [Google Scholar]
  31. Fuchsova B., Alvarez Julia A., Rizavi H. S., Frasch A. C., Pandey G. N. (2015). Altered expression of neuroplasticity-related genes in the brain of depressed suicides. Neuroscience 299 1–17. 10.1016/j.neuroscience.2015.04.057 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Fukumoto K., Toki H., Iijima M., Hashihayata T., Yamaguchi J. I., Hashimoto K., et al. (2017). Antidepressant Potential of (R)-Ketamine in Rodent Models: Comparison with (S)-Ketamine. J. Pharmacol. Exp. Ther. 361 9–16. 10.1124/jpet.116.239228 [DOI] [PubMed] [Google Scholar]
  33. Gass N., Becker R., Reinwald J., Cosa-Linan A., Sack M., Weber-Fahr W., et al. (2019). Differences between ketamine’s short-term and long-term effects on brain circuitry in depression. Transl. Psychiatry 9:172. 10.1038/s41398-019-0506-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Giorgetti R., Marcotulli D., Tagliabracci A., Schifano F. (2015). Effects of ketamine on psychomotor, sensory and cognitive functions relevant for driving ability. Forensic. Sci. Int. 252 127–142. 10.1016/j.forsciint.2015.04.024 [DOI] [PubMed] [Google Scholar]
  35. Graff J., Tsai L. H. (2013). Histone acetylation: molecular mnemonics on the chromatin. Nat. Rev. Neurosci. 14 97–111. 10.1038/nrn3427 [DOI] [PubMed] [Google Scholar]
  36. Greer P. L., Greenberg M. E. (2008). From synapse to nucleus: calcium-dependent gene transcription in the control of synapse development and function. Neuron 59 846–860. 10.1016/j.neuron.2008.09.002 [DOI] [PubMed] [Google Scholar]
  37. Hashimoto K. (2019). Rapid-acting antidepressant ketamine, its metabolites and other candidates: A historical overview and future perspective. Psychiatry Clin. Neurosci. 73 613–627. 10.1111/pcn.12902 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Highland J. N., Zanos P., Riggs L. M., Georgiou P., Clark S. M., Morris P. J., et al. (2021). Hydroxynorketamines: Pharmacology and Potential Therapeutic Applications. Pharmacol Rev 73 763–791. 10.1124/pharmrev.120.000149 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Higuchi F., Uchida S., Yamagata H., Abe-Higuchi N., Hobara T., Hara K., et al. (2016). Hippocampal MicroRNA-124 Enhances Chronic Stress Resilience in Mice. J. Neurosci. 36 7253–7267. 10.1523/JNEUROSCI.0319-16.2016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Hobara T., Uchida S., Otsuki K., Matsubara T., Funato H., Matsuo K., et al. (2010). Altered gene expression of histone deacetylases in mood disorder patients. J. Psychiatr. Res. 44 263–270. 10.1016/j.jpsychires.2009.08.015 [DOI] [PubMed] [Google Scholar]
  41. Hu H. (2019). Advances in Molecular and Circuitry Mechanisms of Depressive Disorder-A Focus on Lateral Habenula. Adv. Exp. Med. Biol. 1180 135–146. 10.1007/978-981-32-9271-0_7 [DOI] [PubMed] [Google Scholar]
  42. Hu H., Cui Y., Yang Y. (2020). Circuits and functions of the lateral habenula in health and in disease. Nat. Rev. Neurosci. 21 277–295. 10.1038/s41583-020-0292-4 [DOI] [PubMed] [Google Scholar]
  43. Huganir R. L., Nicoll R. A. (2013). AMPARs and synaptic plasticity: the last 25 years. Neuron 80 704–717. 10.1016/j.neuron.2013.10.025 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Hyde C. L., Nagle M. W., Tian C., Chen X., Paciga S. A., Wendland J. R., et al. (2016). Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nat. Genet. 48 1031–1036. 10.1038/ng.3623 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Iga J., Ueno S., Yamauchi K., Numata S., Kinouchi S., Tayoshi-Shibuya S., et al. (2007). Altered HDAC5 and CREB mRNA expressions in the peripheral leukocytes of major depression. Prog. Neuropsychopharmacol. Biol. Psychiatry 31 628–632. 10.1016/j.pnpbp.2006.12.014 [DOI] [PubMed] [Google Scholar]
  46. Kang H. J., Voleti B., Hajszan T., Rajkowska G., Stockmeier C. A., Licznerski P., et al. (2012). Decreased expression of synapse-related genes and loss of synapses in major depressive disorder. Nat. Med. 18 1413–1417. 10.1038/nm.2886 [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Kavalali E. T., Monteggia L. M. (2020). Targeting Homeostatic Synaptic Plasticity for Treatment of Mood Disorders. Neuron 106 715–726. 10.1016/j.neuron.2020.05.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Kawatake-Kuno A., Murai T., Uchida S. (2021). The Molecular Basis of Depression: Implications of Sex-Related Differences in Epigenetic Regulation. Front. Mol. Neurosci. 14:708004. 10.3389/fnmol.2021.708004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Kim J. W., Autry A. E., Na E. S., Adachi M., Bjorkholm C., Kavalali E. T., et al. (2021). Sustained effects of rapidly acting antidepressants require BDNF-dependent MeCP2 phosphorylation. Nat. Neurosci. 2021:8. 10.1038/s41593-021-00868-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Koester H. J., Sakmann B. (1998). Calcium dynamics in single spines during coincident pre- and postsynaptic activity depend on relative timing of back-propagating action potentials and subthreshold excitatory postsynaptic potentials. Proc. Natl. Acad. Sci. U S A 95 9596–9601. 10.1073/pnas.95.16.9596 [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Koike H., Iijima M., Chaki S. (2011). Involvement of AMPA receptor in both the rapid and sustained antidepressant-like effects of ketamine in animal models of depression. Behav. Brain Res. 224 107–111. 10.1016/j.bbr.2011.05.035 [DOI] [PubMed] [Google Scholar]
  52. Krishnan V., Nestler E. J. (2008). The molecular neurobiology of depression. Nature 455 894–902. 10.1038/nature07455 [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Krystal J. H., Abdallah C. G., Sanacora G., Charney D. S., Duman R. S. (2019). Ketamine: A Paradigm Shift for Depression Research and Treatment. Neuron 101 774–778. 10.1016/j.neuron.2019.02.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Krystal J. H., Sanacora G., Duman R. S. (2013). Rapid-acting glutamatergic antidepressants: the path to ketamine and beyond. Biol. Psychiatry 73 1133–1141. 10.1016/j.biopsych.2013.03.026 [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Lahti A. C., Koffel B., Laporte D., Tamminga C. A. (1995). Subanesthetic doses of ketamine stimulate psychosis in schizophrenia. Neuropsychopharmacology 13 9–19. 10.1016/0893-133X(94)00131-I [DOI] [PubMed] [Google Scholar]
  56. Lepack A. E., Fuchikami M., Dwyer J. M., Banasr M., Duman R. S. (2014). BDNF release is required for the behavioral actions of ketamine. Int. J. Neuropsychopharmacol. 18:33. 10.1093/ijnp/pyu033 [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Li K., Zhou T., Liao L., Yang Z., Wong C., Henn F., et al. (2013). betaCaMKII in lateral habenula mediates core symptoms of depression. Science 341 1016–1020. 10.1126/science.1240729 [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Li N., Lee B., Liu R. J., Banasr M., Dwyer J. M., Iwata M., et al. (2010). mTOR-dependent synapse formation underlies the rapid antidepressant effects of NMDA antagonists. Science 329 959–964. 10.1126/science.1190287 [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Li N., Liu R. J., Dwyer J. M., Banasr M., Lee B., Son H., et al. (2011). Glutamate N-methyl-D-aspartate receptor antagonists rapidly reverse behavioral and synaptic deficits caused by chronic stress exposure. Biol. Psychiatry 69 754–761. 10.1016/j.biopsych.2010.12.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Liu F., Paule M. G., Ali S., Wang C. (2011). Ketamine-induced neurotoxicity and changes in gene expression in the developing rat brain. Curr. Neuropharmacol. 9 256–261. 10.2174/157015911795017155 [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Liu R. J., Fuchikami M., Dwyer J. M., Lepack A. E., Duman R. S., Aghajanian G. K. (2013). GSK-3 inhibition potentiates the synaptogenic and antidepressant-like effects of subthreshold doses of ketamine. Neuropsychopharmacology 38 2268–2277. 10.1038/npp.2013.128 [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Lumsden E. W., Troppoli T. A., Myers S. J., Zanos P., Aracava Y., Kehr J., et al. (2019). Antidepressant-relevant concentrations of the ketamine metabolite (2R,6R)-hydroxynorketamine do not block NMDA receptor function. Proc. Natl. Acad. Sci. U S A 116 5160–5169. 10.1073/pnas.1816071116 [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Macqueen G., Frodl T. (2011). The hippocampus in major depression: evidence for the convergence of the bench and bedside in psychiatric research? Mol. Psychiatry 16 252–264. 10.1038/mp.2010.80 [DOI] [PubMed] [Google Scholar]
  64. Mcewen B. S. (2007). Physiology and neurobiology of stress and adaptation: central role of the brain. Physiol. Rev. 87 873–904. 10.1152/physrev.00041.2006 [DOI] [PubMed] [Google Scholar]
  65. Mckinsey T. A., Zhang C. L., Lu J., Olson E. N. (2000). Signal-dependent nuclear export of a histone deacetylase regulates muscle differentiation. Nature 408 106–111. 10.1038/35040593 [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Minichiello L. (2009). TrkB signalling pathways in LTP and learning. Nat. Rev. Neurosci. 10 850–860. 10.1038/nrn2738 [DOI] [PubMed] [Google Scholar]
  67. Misztak P., Panczyszyn-Trzewik P., Nowak G., Sowa-Kucma M. (2020). Epigenetic marks and their relationship with BDNF in the brain of suicide victims. PLoS One 15:e0239335. 10.1371/journal.pone.0239335 [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Moda-Sava R. N., Murdock M. H., Parekh P. K., Fetcho R. N., Huang B. S., Huynh T. N., et al. (2019). Sustained rescue of prefrontal circuit dysfunction by antidepressant-induced spine formation. Science 364:8078. 10.1126/science.aat8078 [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Murrough J. W., Perez A. M., Pillemer S., Stern J., Parides M. K., Aan Het, et al. (2013). Rapid and longer-term antidepressant effects of repeated ketamine infusions in treatment-resistant major depression. Biol. Psychiatry 74 250–256. 10.1016/j.biopsych.2012.06.022 [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Nestler E. J., Pena C. J., Kundakovic M., Mitchell A., Akbarian S. (2016). Epigenetic Basis of Mental Illness. Neuroscientist 22 447–463. 10.1177/1073858415608147 [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Ngo-Anh T. J., Bloodgood B. L., Lin M., Sabatini B. L., Maylie J., Adelman J. P. (2005). SK channels and NMDA receptors form a Ca2+-mediated feedback loop in dendritic spines. Nat. Neurosci. 8 642–649. 10.1038/nn1449 [DOI] [PubMed] [Google Scholar]
  72. Nie X., Kitaoka S., Tanaka K., Segi-Nishida E., Imoto Y., Ogawa A., et al. (2018). The Innate Immune Receptors TLR2/4 Mediate Repeated Social Defeat Stress-Induced Social Avoidance through Prefrontal Microglial Activation. Neuron 99 464–479e467. 10.1016/j.neuron.2018.06.035 [DOI] [PubMed] [Google Scholar]
  73. Nosyreva E., Autry A. E., Kavalali E. T., Monteggia L. M. (2014). Age dependence of the rapid antidepressant and synaptic effects of acute NMDA receptor blockade. Front. Mol. Neurosci. 7:94. 10.3389/fnmol.2014.00094 [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Nosyreva E., Szabla K., Autry A. E., Ryazanov A. G., Monteggia L. M., Kavalali E. T. (2013). Acute suppression of spontaneous neurotransmission drives synaptic potentiation. J. Neurosci. 33 6990–7002. 10.1523/JNEUROSCI.4998-12.2013 [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Phillips J. L., Norris S., Talbot J., Birmingham M., Hatchard T., Ortiz A., et al. (2019). Single, Repeated, and Maintenance Ketamine Infusions for Treatment-Resistant Depression: A Randomized Controlled Trial. Am. J. Psychiatry 176 401–409. 10.1176/appi.ajp.2018.18070834 [DOI] [PubMed] [Google Scholar]
  76. Popoli M., Yan Z., Mcewen B. S., Sanacora G. (2011). The stressed synapse: the impact of stress and glucocorticoids on glutamate transmission. Nat. Rev. Neurosci. 13 22–37. 10.1038/nrn3138 [DOI] [PMC free article] [PubMed] [Google Scholar]
  77. Price J. L., Drevets W. C. (2010). Neurocircuitry of mood disorders. Neuropsychopharmacology 35 192–216. 10.1038/npp.2009.104 [DOI] [PMC free article] [PubMed] [Google Scholar]
  78. Reid C. A., Fabian-Fine R., Fine A. (2001). Postsynaptic calcium transients evoked by activation of individual hippocampal mossy fiber synapses. J. Neurosci. 21 2206–2214. 10.1523/JNEUROSCI.21-07-02206.2001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  79. Rodriguez-Munoz M., Sanchez-Blazquez P., Callado L. F., Meana J. J., Garzon-Nino J. (2017). Schizophrenia and depression, two poles of endocannabinoid system deregulation. Transl. Psychiatry 7:1291. 10.1038/s41398-017-0029-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Sakai Y., Li H., Inaba H., Funayama Y., Ishimori E., Kawatake-Kuno A., et al. (2021). Gene-environment interactions mediate stress susceptibility and resilience through the CaMKIIbeta/TARPgamma-8/AMPAR pathway. iScience 24:102504. 10.1016/j.isci.2021.102504 [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Scheetz A. J., Nairn A. C., Constantine-Paton M. (2000). NMDA receptor-mediated control of protein synthesis at developing synapses. Nat. Neurosci. 3 211–216. 10.1038/72915 [DOI] [PubMed] [Google Scholar]
  82. Seney M. L., Huo Z., Cahill K., French L., Puralewski R., Zhang J., et al. (2018). Opposite Molecular Signatures of Depression in Men and Women. Biol. Psychiatry 84 18–27. 10.1016/j.biopsych.2018.01.017 [DOI] [PMC free article] [PubMed] [Google Scholar]
  83. Shinohara R., Aghajanian G. K., Abdallah C. G. (2021). Neurobiology of the Rapid-Acting Antidepressant Effects of Ketamine: Impact and Opportunities. Biol. Psychiatry 90 85–95. 10.1016/j.biopsych.2020.12.006 [DOI] [PubMed] [Google Scholar]
  84. Sial O. K., Parise E. M., Parise L. F., Gnecco T., Bolanos-Guzman C. A. (2020). Ketamine: The final frontier or another depressing end? Behav. Brain Res. 383:112508. 10.1016/j.bbr.2020.112508 [DOI] [PMC free article] [PubMed] [Google Scholar]
  85. Sun H. L., Zhou Z. Q., Zhang G. F., Yang C., Wang X. M., Shen J. C., et al. (2016). Role of hippocampal p11 in the sustained antidepressant effect of ketamine in the chronic unpredictable mild stress model. Transl. Psychiatry 6:e741. 10.1038/tp.2016.21 [DOI] [PMC free article] [PubMed] [Google Scholar]
  86. Suzuki K., Monteggia L. M. (2020). The role of eEF2 kinase in the rapid antidepressant actions of ketamine. Adv. Pharmacol. 89 79–99. 10.1016/bs.apha.2020.04.005 [DOI] [PubMed] [Google Scholar]
  87. Suzuki K., Nosyreva E., Hunt K. W., Kavalali E. T., Monteggia L. M. (2017). Effects of a ketamine metabolite on synaptic NMDAR function. Nature 546 E1–E3. 10.1038/nature22084 [DOI] [PubMed] [Google Scholar]
  88. Takemoto-Kimura S., Suzuki K., Horigane S. I., Kamijo S., Inoue M., Sakamoto M., et al. (2017). Calmodulin kinases: essential regulators in health and disease. J. Neurochem. 141 808–818. 10.1111/jnc.14020 [DOI] [PubMed] [Google Scholar]
  89. Thompson S. M., Kallarackal A. J., Kvarta M. D., Van Dyke A. M., Legates T. A., Cai X. (2015). An excitatory synapse hypothesis of depression. Trends Neurosci. 38 279–294. 10.1016/j.tins.2015.03.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  90. Tochigi M., Iwamoto K., Bundo M., Sasaki T., Kato N., Kato T. (2008). Gene expression profiling of major depression and suicide in the prefrontal cortex of postmortem brains. Neurosci. Res. 60 184–191. 10.1016/j.neures.2007.10.010 [DOI] [PubMed] [Google Scholar]
  91. Trivedi M. H., Rush A. J., Wisniewski S. R., Nierenberg A. A., Warden D., Ritz L., et al. (2006). Evaluation of outcomes with citalopram for depression using measurement-based care in STARD: implications for clinical practice. Am. J. Psychiatry 163 28–40. 10.1176/appi.ajp.163.1.28 [DOI] [PubMed] [Google Scholar]
  92. Tsankova N. M., Berton O., Renthal W., Kumar A., Neve R. L., Nestler E. J. (2006). Sustained hippocampal chromatin regulation in a mouse model of depression and antidepressant action. Nat. Neurosci. 9 519–525. 10.1038/nn1659 [DOI] [PubMed] [Google Scholar]
  93. Turrigiano G. G., Leslie K. R., Desai N. S., Rutherford L. C., Nelson S. B. (1998). Activity-dependent scaling of quantal amplitude in neocortical neurons. Nature 391 892–896. 10.1038/36103 [DOI] [PubMed] [Google Scholar]
  94. Uchida S., Hara K., Kobayashi A., Otsuki K., Yamagata H., Hobara T., et al. (2011). Epigenetic status of Gdnf in the ventral striatum determines susceptibility and adaptation to daily stressful events. Neuron 69 359–372. 10.1016/j.neuron.2010.12.023 [DOI] [PubMed] [Google Scholar]
  95. Uchida S., Shumyatsky G. P. (2018a). Epigenetic regulation of Fgf1 transcription by CRTC1 and memory enhancement. Brain Res. Bull. 141 3–12. 10.1016/j.brainresbull.2018.02.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  96. Uchida S., Shumyatsky G. P. (2018b). Synaptically Localized Transcriptional Regulators in Memory Formation. Neuroscience 370 4–13. 10.1016/j.neuroscience.2017.07.023 [DOI] [PMC free article] [PubMed] [Google Scholar]
  97. Uchida S., Yamagata H., Seki T., Watanabe Y. (2018). Epigenetic mechanisms of major depression: Targeting neuronal plasticity. Psychiatry Clin. Neurosci. 72 212–227. 10.1111/pcn.12621 [DOI] [PubMed] [Google Scholar]
  98. Van Den Heuvel M. P., Scholtens L. H., Kahn R. S. (2019). Multiscale Neuroscience of Psychiatric Disorders. Biol. Psychiatry 86 512–522. 10.1016/j.biopsych.2019.05.015 [DOI] [PubMed] [Google Scholar]
  99. Wei Y., Chang L., Hashimoto K. (2021). Molecular mechanisms underlying the antidepressant actions of arketamine: beyond the NMDA receptor. Mol. Psychiatry 2021:1. 10.1038/s41380-021-01121-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  100. Xia C. Y., He J., Du L. D., Yan Y., Lian W. W., Xu J. K., et al. (2021). Targeting the dysfunction of glutamate receptors for the development of novel antidepressants. Pharmacol. Ther. 226:107875. 10.1016/j.pharmthera.2021.107875 [DOI] [PubMed] [Google Scholar]
  101. Yamaguchi J. I., Toki H., Qu Y., Yang C., Koike H., Hashimoto K., et al. (2018). (2R,6R)-Hydroxynorketamine is not essential for the antidepressant actions of (R)-ketamine in mice. Neuropsychopharmacology 43 1900–1907. 10.1038/s41386-018-0084-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  102. Yamasaki S., Aso T., Miyata J., Sugihara G., Hazama M., Nemoto K., et al. (2020). Early and late effects of electroconvulsive therapy associated with different temporal lobe structures. Transl. Psychiatry 10:344. 10.1038/s41398-020-01025-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  103. Yang C., Ren Q., Qu Y., Zhang J. C., Ma M., Dong C., et al. (2018). Mechanistic Target of Rapamycin-Independent Antidepressant Effects of (R)-Ketamine in a Social Defeat Stress Model. Biol. Psychiatry 83 18–28. 10.1016/j.biopsych.2017.05.016 [DOI] [PubMed] [Google Scholar]
  104. Yang Y., Cui Y., Sang K., Dong Y., Ni Z., Ma S., et al. (2018). Ketamine blocks bursting in the lateral habenula to rapidly relieve depression. Nature 554 317–322. 10.1038/nature25509 [DOI] [PubMed] [Google Scholar]
  105. Yokoyama R., Higuchi M., Tanabe W., Tsukada S., Naito M., Yamaguchi T., et al. (2020). (S)-norketamine and (2S,6S)-hydroxynorketamine exert potent antidepressant-like effects in a chronic corticosterone-induced mouse model of depression. Pharmacol. Biochem. Behav. 191:172876. 10.1016/j.pbb.2020.172876 [DOI] [PubMed] [Google Scholar]
  106. Youssef M. M., Underwood M. D., Huang Y. Y., Hsiung S. C., Liu Y., Simpson N. R., et al. (2018). Association of BDNF Val66Met Polymorphism and Brain BDNF Levels with Major Depression and Suicide. Int. J. Neuropsychopharmacol. 21 528–538. 10.1093/ijnp/pyy008 [DOI] [PMC free article] [PubMed] [Google Scholar]
  107. Yuen E. Y., Wei J., Liu W., Zhong P., Li X., Yan Z. (2012). Repeated stress causes cognitive impairment by suppressing glutamate receptor expression and function in prefrontal cortex. Neuron 73 962–977. 10.1016/j.neuron.2011.12.033 [DOI] [PMC free article] [PubMed] [Google Scholar]
  108. Zanos P., Moaddel R., Morris P. J., Georgiou P., Fischell J., Elmer G. I., et al. (2016). NMDAR inhibition-independent antidepressant actions of ketamine metabolites. Nature 533 481–486. 10.1038/nature17998 [DOI] [PMC free article] [PubMed] [Google Scholar]
  109. Zarate C. A., Jr., Singh J. B., Carlson P. J., Brutsche N. E., Ameli R., Luckenbaugh D. A., et al. (2006). A randomized trial of an N-methyl-D-aspartate antagonist in treatment-resistant major depression. Arch. Gen. Psychiatry 63 856–864. 10.1001/archpsyc.63.8.856 [DOI] [PubMed] [Google Scholar]
  110. Zhou W., Wang N., Yang C., Li X. M., Zhou Z. Q., Yang J. J. (2014). Ketamine-induced antidepressant effects are associated with AMPA receptors-mediated upregulation of mTOR and BDNF in rat hippocampus and prefrontal cortex. Eur. Psychiatry 29 419–423. 10.1016/j.eurpsy.2013.10.005 [DOI] [PubMed] [Google Scholar]
  111. Zhou Z., Hong E. J., Cohen S., Zhao W. N., Ho H. Y., Schmidt L., et al. (2006). Brain-specific phosphorylation of MeCP2 regulates activity-dependent Bdnf transcription, dendritic growth, and spine maturation. Neuron 52 255–269. 10.1016/j.neuron.2006.09.037 [DOI] [PMC free article] [PubMed] [Google Scholar]

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