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1-1-2019
The Medial Prefrontal Cortex To Dorsal Raphe Circuit In The
The Medial Prefrontal Cortex To Dorsal Raphe Circuit In The
Antidepressant Action Of Ketamine
Antidepressant Action Of Ketamine
Alexandra Thomas
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Of Ketamine” (2019). Yale Medicine Thesis Digital Library. 3538.
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The Medial Prefrontal Cortex to Dorsal Raphe Circuit in the
Antidepressant Action of Ketamine
A Thesis
Submitted to the
Yale University School of Medicine
in Partial Fulfilment of the Requirements for the
Degree of
Doctor of Medicine
By
Alexandra Moran Thomas
Dissertation Director: Ronald S. Duman, Ph.D.
May 2019
ii
ABSTRACT
Major depressive disorder is a common and debilitating illness for which there is a
notable lack of efficient, effective treatment. While currently available
pharmacotherapies typically take eight weeks to take effect and fail to do so at all for
about a third of patients, the N-methyl-D-aspartate (NMDA) receptor antagonist
ketamine has shown a much more favorable effectiveness profile, including improvements
in symptoms within hours of administration, even for many patients who do not respond
to typical antidepressants. Ketamine, as a modulator of glutamate signaling in the brain,
has a distinct mechanism of action from the serotonin and norepinephrine modulators
that are currently the mainstay of depression treatment. This dissertation seeks to
contribute to the understanding of this unique mechanism, and particularly the brain
circuits affected. Rodent studies have shown that ketamine induces a burst of
glutamatergic activity in the medial prefrontal cortex (mPFC), which is necessary to
produce its antidepressant effect. The downstream targets of this glutamatergic activity
that are relevant to the ketamine antidepressant effect are unclear, but recent research
has suggested a role for the dorsal raphe nucleus (DRN), which contains most of the
brain’s serotonin-producing cells. In this thesis, I first provide a synthesis of the literature
on the mechanism of ketamine’s antidepressant effect and the neural circuits that might
underlie it. I then investigate the projection from the mPFC to the DRN using
optogenetic stimulation of mPFC-originating axon terminals in the DRN, finding that
activation of this pathway produces an antidepressant effect on the forced-swim test
(FST), which measures “behavioral despair” induced by a stressful environment, but not
on other measures of depression-like behavior. I also perform immunohistochemical
studies of the DRN, which indicate that both serotonergic and non-serotonergic cells are
iii
activated by this stimulation. I then find additional support for this behavioral selectivity
using a pharmacological approach: by inhibiting serotonin release during ketamine
administration, I find that DRN activity is needed for the antidepressant effect of
ketamine on the FST but not on other behavioral tests. Finally, I interrogate the
projection from the mPFC to the nucleus accumbens using the same optogenetic
approach as before. These experiments show that activation of the mPFC-to-DRN
pathway produces an antidepressant effect on a particular subset of depression-like
behavior and supports a role for serotonin signaling in the behavior measured by the
FST.
iv
© Alexandra Moran Thomas
All rights reserved.
v
TABLE OF CONTENTS
ACKNOWLEDGEMENTS …………………………………………………………………… vi
LIST OF FIGURES ……………………………………………………………………………
viii
LIST OF ABBREVIATIONS
……………………………………………………………….. ix
CHAPTER 1: The neural and molecular mechanisms of the
antidepressant effect of ketamine
……………………………………………………….
1
1.1. Brain pathology in depression
………………………………………………………………………….. 1
1.2. Mechanism of action of currently available antidepressants ………………………………… 5
1.3. Mechanism of action of ketamine …………………………………………………………………….. 7
1.4. Neural circuits involved in the function of rapid-acting antidepressants
………………. 15
1.5. Aims …………………………………………………………………………………………………………… 17
CHAPTER 2: Optogenetic stimulation of mPFC-originating axon
terminals in the dorsal raphe nucleus produces an antidepressant
effect ……………………………………………………………………………………………………
18
2.1. Introduction ………………………………………………………………………………………………… 18
2.2. Methods ……………………………………………………………………………………………………… 21
2.3. Results ………………………………………………………………………………………………………… 26
2.4. Discussion
……………………………………………………………………………………………………. 36
CHAPTER 3: Inhibition of DRN serotonin release inhibits the
antidepressant effect of ketamine
……………………………………………………..
42
3.1. Introduction ………………………………………………………………………………………………… 42
3.2. Methods ……………………………………………………………………………………………………… 43
3.3. Results ………………………………………………………………………………………………………… 47
3.4. Discussion
……………………………………………………………………………………………………. 52
CHAPTER 4: Optogenetic stimulation of infralimbic-originating
terminals in the nucleus accumbens does not produce an
antidepressant effect
………………………………………………………………………….
55
4.1. Introduction ………………………………………………………………………………………………… 55
4.2. Methods ……………………………………………………………………………………………………… 56
4.3. Results ………………………………………………………………………………………………………… 60
4.4. Discussion
……………………………………………………………………………………………………. 62
CHAPTER 5: Conclusions and future directions
………………………………
65
BIBLIOGRAPHY
…………………………………………………………………………………
70
vi
ACKNOWLEDGEMENTS
I have been fortunate to have many mentors, close friends, and family
members who have supported me on my journey through graduate school.
First among them is my advisor, Ron Duman, who has helped me develop
and execute this dissertation at every step, and whose immense patience and
kindness along the way has modeled for me how a good mentor should be.
Yale as a whole has provided a wonderful environment in which to develop as
a scientist and physician, and particularly the psychiatry department. I have
greatly benefited from the input and expertise of my thesis committee, Ralph
DiLeone, Marina Picciotto, and Alex Kwan; and from the depth and breadth
of knowledge of my oral exam readers, John Krystal, Jane Taylor, and
Angelique Bordey. The leadership and staff of the MD/PhD program has
provided indispensable guidance on this long road, most notably Barbara
Kazmierczak, Jim Jamieson, Cheryl Defilippo, and Sue Sansone; and the
leadership of the MD program and Interdepartmental Neuroscience Program
have been patient and helpful in navigating the transition from medical
school to grad school and back again, especially Nancy Angoff, Michael
O’Brien, Charlie Greer, Carol Russo, and Donna Carranzo. I am also grateful
to the National Institute of Mental Health for the F30 grant that financed a
portion of this work.
My development as a scientist has been influenced by many
collaborators and colleagues. George Aghajanian and Rong-Jian Liu, as well
as Ben Land and Rich Trinko of the DiLeone lab, were wonderful
vii
collaborators when I started my project. Manabu Fuchikami taught me
nearly every technique I used in this project with care and diligence. I have
learned from and gotten vital assistance from many members of the Duman
lab, which made it a great place to go to work everyday: particular thanks to
Kenichi Fukumoto, Brendan Hare, and Taro Kato, who directly contributed
to some of the experiments in this dissertation; as well as Mouna Banasr,
Astrid Becker, Cathy Duman, Jason Dwyer, Tina Franklin, Danielle
Gerhard, Matthew Girgenti, Sri Ghosal, Ashley Lepack, Xiao-Yuan Li,
Georgia Miller, Rose Terwiliger, Manmeet Virdee, and Eric Wohleb.
I have been blessed with an immensely supportive family, who have
always trusted that I would make it to the finish line, even when I doubted it
myself. I remember especially those who passed away during these years
and whose love and encouragement I still carry with me: my uncle Monte
Sliger, stepmom Sandy Thomas, grandmother Bertine Sliger, and especially
my dad, George Thomas. I continue to be uplifted by my mother Janice
Sliger, brother Luke Thomas and his wife Joanie, and the very best family-in-
law: Joan Russo, Donald Burset, Stephanie Burset, and Charlie King.
Finally, the best decision I made during grad school was to marry
Christian Burset, who has picked me up and pulled me through even the
toughest parts of the last five years with his love and patience. I am
especially thankful that our most ambitious collaborative project, our son
Dominic, was completed in perfect form, needing not a single revision, almost
simultaneously with this thesis.
viii
LIST OF FIGURES
Figure 1.1 Mechanisms of synapse loss in depression …………………………..6
Figure 1.2 Signaling pathways involved in the response to rapid-acting
antidepressants …………………………………………………………10
Figure 2.1 Distribution of GFP-labeled ChR2 throughout the brain…………26
Figure 2.2 DRN axon-terminal stimulation produces an antidepressant effect
on the FST ………………………………………………………………28
Figure 2.3 DRN axon-terminal stimulation had no effect on the NSFT, FUST,
or 7-day post-stimulation FST ……………………………………….31
Figure 2.4 Cannula placement and viral expression in the mPFC and
DRN………………………………………………………………………33
Figure 2.5 c-Fos activation is increased in the DRN but not in the ilPFC in
response to DRN axon-terminal stimulation ………………………35
Figure 2.6 Stimulation induces c-Fos expression in non-TPH2-expressing
cells ……………………………………………………………………….36
Figure 3.1 8OH-DPAT blocks the antidepressant effect of ketamine on the
FST ……………………………………………………………………….47
Figure 3.2 Ketamine increases swimming, not climbing, on the FST ……….49
Figure 3.3 8OH-DPAT does not interfere with the effect of ketamine on the
NSFT …………………………………………………………………….50
Figure 3.4 Depression-like behavior is higher in control groups when drugs
are administered by a male experimenter than by a female
experimenter ……………………………………………………………52
Figure 4.1 ChR2 expression in the nucleus accumbens after viral injection
into the mPFC ………………………………………………………….60
Figure 4.2 Stimulation of mPFC-originating NAC axon terminals does not
produce an antidepressant effect ……………………………………62
ix
LIST OF ABBREVIATIONS
8OH-DPAT, 8-hydroxy-n,n-dipropylaminotetralin
AMPAR, α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid
BDNF, brain-derived neurotrophic factor
DBS, deep brain stimulation
DRN, dorsal raphe nucleus
DSM, Diagnostic and Statistical Manual of Mental Disorders
eEf2K, eukaryotic elongation factor-2 kinase
GABAR, l-aminobutyric acid receptor
GSK, glycogen synthase kinase
HNK, hydroxynorketamine; mAchR, muscarinic acetylcholine receptor
LHB, lateral habenula
MDD, Major Depressive Disorder
mGluR, metabotropic glutamate receptor
mPFC, medial prefrontal cortex
MSN, medium spiny neuron
mTORC1, mammalian target of rapamycin complex 1
NAC, nucleus accumbens
NMDAR, N-methyl-D-aspartate receptor
SNRI, selective norepinephrine-reuptake inhibitors
SSRI, selective serotonin-reuptake inhibitors
TrkB, tropomysin receptor kinase B
VDCC, voltage-gated calcium channel
1
CHAPTER 1: The neural and molecular mechanisms of the
antidepressant effect of ketamine
This chapter contains a modified version of material that appeared in the
author’s publication: Alexandra Thomas & Ronald Duman. 2017. Novel
rapid-acting antidepressants: molecular and cellular signaling mechanisms.
Neuronal Signaling, 1(4): 1-10.
1.1. Brain pathology in depression
Major Depressive Disorder (MDD) affects an estimated 5% of the
global population at any given time, and it is the leading cause of disability
worldwide (Ferrari et al., 2013). In addition to the high toll of personal
suffering it exacts, depression drains over $50 billion per year from the US
economy alone in lost work productivity and medical costs (P. S. Wang,
Simon, & Kessler, 2003). Despite the widespread need for effective
treatment, currently available antidepressants often take 6-8 weeks to take
effect, and only one-third of patients respond to their first trial on any given
drug. One-third of depressed patients never get relief from typical
antidepressants, even after multiple trials (Gaynes et al., 2009). Perhaps the
biggest obstacle to the development of better medications has been the lack of
understanding of the molecular mechanisms that underlie antidepressant
2
effects. But several innovations in the past two decades have begun to reveal
answers to this puzzle.
First, the drug ketamine, which had long been used in high doses as an
anesthetic, was found to have a rapid antidepressant effect in low, sub-
anesthetic doses (Berman et al., 2000). It relieves symptoms within hours,
even in many patients who have not responded to typical antidepressants.
Notably, it acts primarily through a different neurotransmitter, glutamate,
than do all currently available antidepressants, which primarily affect the
transmission of serotonin and/or norepinephrine. The discovery of the rapid
antidepressant action of ketamine and a handful of other drugs has spurred a
rethinking of fundamental questions about how antidepressants work, and
especially about the role of glutamatergic signaling in antidepressant
mechanisms. To aid in this reassessment, new tools in neuroscience have
shed light on the intracellular signals and neuronal networks that underlie
the effects of rapid-acting agents.
In order to understand how antidepressants relieve the symptoms of
depression, it is helpful to understand how the brains of depressed people
differ from those who are not depressed. This question has been difficult to
study due to the wide diversity of clinical presentations that meet criteria for
MDD according to the Diagnostic and Statistical Manual of Mental Disorders
(DSM) (American Psychiatric Association, 2013). Derangements in a variety
of biological processes have been imputed to lead to depression, including
inflammation (Iwata, Ota, & Duman, 2012), metabolism (Abdallah et al.,
3
2014), and stress-response pathways (Duman, 2014), and it is possible that
these mechanisms interact in different ways in different subgroups of
patients with MDD. But despite the probable heterogeneity of MDD
mechanisms, there seem to be several common features of the depressed state
that serve as hallmarks of the depressed brain.
Human neuroimaging studies have consistently demonstrated reduced
brain volume in key areas associated with mood regulation, including the
frontal cortex, cingulate cortex, and hippocampus (Arnone, McIntosh,
Ebmeier, Munafò, & Anderson, 2012). Most of the volume reduction occurs in
gray matter, and evidence in both humans and animals suggests that loss of
glia accounts for most of this effect, and reduction in the size of neurons also
plays a role (Rajkowska et al., 1999; Treadway et al., 2015). Reduction in
synapse number in the prefrontal cortex has also been found in postmortem
tissue of depressed subjects and may also contribute to decreased cortical
gray matter volume (Kang et al., 2012). Glial loss may be a consequence of
several aspects of the stress response, including excessive release of
glutamate caused by high levels of corticosteroids, decreased expression of
neurotrophic factors, and increased activation of apoptotic signaling
pathways (Banasr, Dwyer, & Duman, 2011).
Glia are key regulators of glutamate neurotransmission, and their
disruption leads to derangements in glutamatergic signaling that may be
ameliorated by rapid-acting antidepressants. Specifically, glia inactivate
glutamate signaling by sequestering glutamate after it is released into the
4
synapse. With that function compromised, extracellular glutamate levels are
elevated (Krystal, Sanacora, & Duman, 2013). This excess glutamate, if
present at high enough levels, will bind not only to the post-synaptic α-amino-
3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and N-methyl-D-
aspartate (NMDA) receptors that are its primary target, but also to
presynaptic metabotropic glutamate receptors (mGluRs). Activation of these
presynaptic metabotropic receptors inhibits synaptic glutamate release,
which leads to reduced post-synaptic glutamatergic signaling and ultimately
reduced synaptic connectivity (Bonansco et al., 2011). This idea of excess
glutamate leading to reduced connectivity accords well with human
neuroimaging studies, which have found elevated glutamate levels and
reduced functional connectivity in the anterior cingulate cortex (Horn et al.,
2010). In addition, depressed patients have higher levels of activity in
cingulate area 25, which normalizes after successful treatment with deep-
brain stimulation (Mayberg et al., 2005).
Excess extracellular glutamate may also have deleterious effects on
connectivity by activating extrasynaptic NMDA receptors. Stimulation of
these receptors initiates a signaling cascade that may be involved in the
mechanism of rapid-acting antidepressants. Key components include the
phosphorylation of eukaryotic elongation factor-2 (eEF2) and reduction of
brain-derived neurotrophic factor (BDNF) levels, which lead to dendritic
atrophy and dendritic-spine loss (Krystal et al., 2013). Induction of REDD1,
a negative regulator of the mammalian target of rapamycin complex 1
5
(mTORC1) pathway, which is involved in synaptic protein synthesis, has
been reported in postmortem PFC of depressed subjects and in rodent chronic
stress models and may also contribute to loss of synapses (Ota et al., 2014).
The degeneration of dendritic structure is a consistent finding in animal
models of depression and corresponds to human studies showing loss of
synapses and neuronal atrophy in MDD patients (Kang et al., 2012). This
model of glial loss leading to a decrease in connectivity and synaptic function
provides important insights into the mechanism of action of rapid-acting
antidepressants, which ameliorate those same deficits (Figure 1.1).
1.2. Mechanism of action of currently available antidepressants
The research that would eventually lead to the development of the
antidepressants in wide use today began in the 1950s, when it was noted that
drugs that prevented the reuptake of monoamine neurotransmitters had
antidepressant activity, though the exact mechanism remained unclear. As
all of these drugs increased synaptic levels of serotonin, norepinephrine,
dopamine, or some combination of the three, the prevailing hypothesis was
that the increase in monoamine levels was the key to their effectiveness.
Based on this monoamine hypothesis, pharmacologists have been able to
improve upon the monoamine-oxidase inhibitors and tricyclic
6
antidepressants, which were the first monoaminergic antidepressants in use
but which often had burdensome side effects due to their relatively non-
selective binding profile. The first selective serotonin-reuptake inhibitors
(SSRIs) were released in the late 1980s, and they along with selective
norepinephrine-reuptake inhibitors (SNRIs) have remained the first-line
agents in the treatment of depression (López-Muñoz & Alamo, 2009).
Figure 1.1. Mechanisms of synapse loss in depression
Stress-induced loss of glia leads to excess extracellular glutamate, as glia normally
remove glutamate from the synapse after an action potential. Glutamate then binds
to presynaptic metabotropic glutamate receptors (mGluR) to inhibit further synaptic
glutamate release, which would normally promote strengthening of synapses by
binding postsynaptic AMPA receptors (AMPAR). Glutamate binding to extrasynaptic
NMDA receptors (NMDAR) leads to phosphorylation of elongation factor 2 (ElF-2),
which inhibits synthesis of brain-derived neurotrophic factor (BDNF), a key promoter
of synaptic growth. Stress also leads to induction of REDD1, which inhibits the
mammalian target of rapamycin complex 1 (mTORC1). mTORC1 is needed to
promote the translation of synaptic proteins necessary for new dendrite formation.
Each of these pathways contributes to the loss of synapses and dendritic spines seen in
depression.
7
Though the monoamine hypothesis became the basis for most drug-
discovery efforts in the ensuing forty years, it had shortcomings that were
difficult to resolve before advances in the understanding of depression
pathophysiology began to emerge over the past two decades. Notably, the
most frustrating clinical aspect of monoaminergic drugs, the 6-to-8-week-long
delay in the onset of their antidepressant activity, cannot be adequately
explained by the monoamine hypothesis, given that the drugs increase
monoamine availability after a single effective dose (Sanacora, Treccani, &
Popoli, 2012). Clearly, some additional mechanism besides increased
monoamine levels mediates the effectiveness of these drugs. The discovery of
the rapid-acting antidepressant activity of ketamine, a glutamatergic agent,
forced the field to move beyond the monoamine hypothesis to integrate what
is known about deficits of plasticity and connectivity in the depressed brain
and the effect of rapid-acting agents on these pathways.
1.3. Mechanism of action of ketamine
Ketamine, the best-characterized rapid-acting antidepressant, marks a
dramatic improvement over monoaminergic agents not only because of its
speed of onset but because it often relieves symptoms of depression even in
patients who have not responded to other modalities, even including those
who do not respond to electroconvulsive therapy and are considered
treatment-resistant (Ibrahim et al., 2011). However, it does have drawbacks
that limit widespread use. Specifically, it produces dissociative and
psychomimetic side effects in the immediate post-administration period (1 to
8
2 hours) in a substantial proportion of patients (Berman et al., 2000), and it
has abuse potential (especially in higher doses) (Zhang et al., 2014). Even
more concerning, users of frequent, high doses of ketamine suffer cortical
atrophy and neurotoxicity as assessed by MRI (C. Wang, Zheng, Xu, Lam, &
Yew, 2013). In order to harness the impressive antidepressant profile of
ketamine, it is important to understand how it functions in the brain in order
to apply that knowledge to develop new therapies that are safe for
widespread use.
Ketamine is an antagonist of the NMDA receptor, which is an
ionotropic glutamate receptor and one of the most abundant transducers of
glutamate signaling in the brain. Rodent studies have demonstrated that
ketamine induces a transient increase in extracellular glutamate in the
medial prefrontal cortex (mPFC) shortly (30 to 60 minutes) after
administration (Moghaddam, Adams, Verma, & Daly, 1997). Blockade of
AMPA receptors blocks the drug’s antidepressant effect, providing evidence
that glutamate-AMPA activity is necessary to produce the effect (Maeng et
al., 2008). The first challenge in explaining ketamine’s mechanism of action is
reconciling how a drug that blocks a glutamate receptor leads to an increase
in glutamate signaling. The key to this apparent paradox may be the fact
that ketamine preferentially binds to the NMDA receptor when its ion
channel is in the open conformation (Figure 1.2). Interneurons have a
higher tonic firing rate than pyramidal neurons and thus their NMDA
receptors are more likely to have an open channel at any given time, so it is
9
hypothesized that low doses of ketamine preferentially bind to NMDA
receptors on l-aminobutyric acid (GABA) interneurons. Blockade of the
NMDA receptor blocks the function of these inhibitory cells, which in turn
disinhibits the activity of glutamatergic pyramidal cells, whose activity is
tonically inhibited by interneurons (Duman, 2014). This disinhibition
hypothesis explains the observed glutamatergic effects of ketamine, and it
also explains why ketamine does not induce a glutamate burst or an
antidepressant effect at higher doses (Moghaddam et al., 1997): higher
concentrations of ketamine are able to bind to NMDA receptors on both
interneurons and pyramidal neurons, so at higher doses of ketamine NMDA
receptor blockade on pyramidal neurons interferes with the interneuron-
mediated glutamate neurotransmission necessary to achieve an
antidepressant effect.
10
The glutamate burst induced by disinhibition of pyramidal neurons
initiates post-synaptic signaling cascades that affect both local networks in
the prefrontal cortex and a wide range of other brain regions to which the
Figure 2. Signaling pathways involved in the response to rapid-acting
antidepressants
In the GABA interneuron: Ketamine blocks activity of the NMDA receptor (NMDAR),
which prevents GABA release and thus disinhibits the firing of the glutamatergic cell,
resulting in a transient burst of glutamate release. In the postsynaptic cell: The glutamate
burst activates synaptic NMDARs and AMPA receptors (AMPARs). AMPAR activity
triggers the opening of voltage-gated calcium channels (VDCC); the resulting calcium
influx triggers the release of BDNF, which binds to TrkB and induces mammalian
target of rapamycin complex 1 (mTORC1) signaling. SSRIs also increase the
expression of BDNF after chronic administration. Ketamine exerts a pro-growth
effect by blocking extrasynaptic NMDARs, especially those containing the GluN2B
subunit. These receptors activate elongation factor 2 kinase (EF2k), which inhibits
elongation factor 2 (elF-2); their blockade induces brain-derived neurotrophic factor
(BDNF) synthesis and other protein synthesis via ElF-2. mTORC1 promotes protein
synthesis via multiple mechanisms. Protein synthesis is necessary for formation of new
synapses, which enables the plasticity that marks a successful antidepressant response.
11
pyramidal neurons project. The primary target of synaptic glutamate is the
post-synaptic AMPA receptor; if AMPA receptors are inhibited, ketamine’s
antidepressant effect is blocked as well (Maeng et al., 2008). AMPA receptor
activation causes its ion channel to open and depolarizes the post-synaptic
cell. In turn, depolarization leads to the opening of L-type voltage-gated
calcium channels (VDCCs), which promotes the release of brain-derived
neurotrophic factor (BDNF) (Lepack, Fuchikami, Dwyer, Banasr, & Duman,
2014), binding of BDNF to its receptor tropomysin receptor kinase B (TrkB),
and TrkB-mediated activation of the mTORC1 signaling pathway (Jourdi et
al., 2009; N. Li et al., 2010). Each of these molecular signals is necessary for
the antidepressant action of ketamine and ultimately promotes the dendritic-
spine growth and synaptic plasticity that are the hallmarks of ketamine-
induced antidepressant activity.
The signaling cascades that lead to and proceed from BDNF release
and mTORC1 activation are dense and interconnected, as each is involved in
different facets of the regulation of energy metabolism and cellular growth
(Duman & Voleti, 2012) (Figure 1.2). Several important mediators of these
pathways have been identified and their relevance to the antidepressant
effect of ketamine confirmed. Autry and colleagues have shown that
ketamine promotes the induction of BDNF synthesis in hippocampus through
an additional mechanism by preventing the activation of eukaryotic
elongation factor 2 kinase (eEF2K), which normally phosphorylates its target
protein, eukaryotic elongation factor 2 (eEF2), in response to spontaneous
12
synaptic glutamate release (as distinct from action-potential-evoked release)
(Autry et al., 2011). NMDA receptors bind to spontaneously released
glutamate and trigger the activation of eEF2K, so the blockade of NMDA
receptors by ketamine prevents the transmission of this signal. Because
phosphorylated eEF2 inhibits BDNF synthesis, ketamine’s NMDA
antagonism removes this inhibition (Monteggia, Gideons, & Kavalali, 2013).
This effect of NMDA receptor antagonism is distinct from the pyramidal-cell
disinhibition hypothesis, but may represent a complementary mechanism. In
contrast to our lab’s previous studies as well as reports from multiple other
research groups (N. Li et al., 2010; Liu et al., 2017), Autry et al. (2011) and
Zanos et al. (2016) have reported no effect of ketamine on mTORC1 signaling.
This contradiction may be due to multiple factors, including uncontrolled
stress of the animals, species (rat vs. mouse), brain region and dissection, and
tissue preparation (crude homogenates vs. synaptosome-enriched
preparations), that could influence the phosphorylation of mTORC1 signaling
proteins, a process that is dynamic and state-dependent.
Further supporting the idea that ketamine derives at least part of its
antidepressant efficacy by blocking the response to spontaneous glutamate
release, numerous studies have investigated an important role of NMDA
receptors containing the GluN2B subunit, which is selectively activated by
spontaneous glutamate release (in contrast to GluN2A subunits, which
respond to action-potential-evoked glutamate). Pharmacological studies
report that GluN2B-selective antagonists produce rapid antidepressant
13
effects in depressed patients (Preskorn et al., 2015) and in rodent models (N.
Li et al., 2010; Maeng et al., 2008). Using a conditional knockout to remove
the GluN2B subunit selectively from cortical pyramidal neurons, Hall and
colleagues found that GluN2B-selective inhibition produces a robust
antidepressant response that occludes the antidepressant effect of ketamine;
however, these knockout mice also display hyperlocomotor activity making it
difficult to interpret these behavioral findings (Miller et al., 2014). In
addition to activating in response to different patterns of glutamate release,
GluN2B subunits transmit a different set of intracellular signals than do
GluN2A subunits and may be most prevalent at a different part of the
postsynaptic neuron (Hardingham & Bading, 2010). GluN2B-mediated
signals, particularly at extrasynaptic NMDA receptors, appear to act as a
brake on the plasticity-promoting effects of glutamate neurotransmission.
The conditional knockout of GluN2B removes this impediment to BDNF
synthesis and mTORC1 activation in a way that occludes the effects of
ketamine on both of these signaling pathways (Miller et al., 2014). Though
ketamine does not selectively bind to one GluN2 isoform over the other,
inhibition of overactive extrasynaptic NMDARs that contain GluN2B may
have a unique set of behavioral consequences.
Ketamine also interacts with at least one additional facet of the
plasticity-regulating machinery through the glycogen synthase kinase (GSK)
pathway (Figure 1.2). GSK controls the degradation of b-catenin, which is a
necessary substrate for most forms of cellular growth and plasticity,
14
including the formation of new dendritic spines. Phosphorylation of GSK
renders it inactive, thus increasing the availability of b-catenin (Duman &
Voleti, 2012). Ketamine rapidly promotes GSK phosphorylation, and this
activity is necessary for its antidepressant effect (Beurel, Song, & Jope,
2011). The mechanism of this effect is not clear, but it may be a downstream
consequence of BDNF release, which activates Akt, a protein that
phosphorylates GSK; or it may result from mTORC1 activity, which activates
S6 kinase, which also phosphorylates GSK (Duman & Voleti, 2012).
A recent line of research has called into question the conclusion that
NMDA antagonism is the functional mechanism of ketamine at all, based on
the finding that one particular metabolite of racemic (R,S) ketamine, (2R,6R)-
hydroxynorketamine (HNK), is sufficient to produce a robust antidepressant
response, even though it was reported that this metabolite does not show
binding affinity for the NMDA receptor (Zanos et al., 2016). This enantiomer
of HNK does induce a rapid, transient increase in glutamate signaling along
with insertion of AMPA receptors in cell membranes, which racemic
ketamine has previously been shown to do (Wohleb, Gerhard, Thomas, &
Duman, 2016). However, recent evidence from another laboratory indicates
that HNK may in fact act at NMDA receptors, although at higher doses
(Suzuki, Nosyreva, Hunt, Kavalali, & Monteggia, 2017). Nevertheless, even if
HNK acts via NMDA receptors the reduced side effects in rodent models
indicate that it has the potential to be better tolerated by depressed patients
than ketamine itself is.
15
Ketamine has numerous points of interaction with signaling pathways
that lead to increased synaptic plasticity and dendritic spine growth via new
translation of the proteins needed to form new synapses, including the AMPA
receptor subunit GluA1 (Duman, Aghajanian, Sanacora, & Krystal, 2016).
Rodent models of depression induced by chronic stress have shown that loss
of dendritic spines is a key feature of the depressed brain, which ketamine
reverses within 24 hours of administration (N. Li, Liu, Dwyer, Banasr, Lee,
Son, Li, Aghajanian, & Duman, 2011a). Both BDNF release and mTORC1
activation, two of the necessary components of ketamine’s antidepressant
effect, promote synaptogenesis (Duman & Aghajanian, 2012). The restoration
of synaptic plasticity appears to be the critical mechanism on which the many
signaling pathways affected by ketamine converge.
1.4. Neural circuits involved in the function of rapid-acting
antidepressants
As the intracellular signaling pathways activated by antidepressants
come into sharper and more detailed focus, the circuit level effects of
antidepressants are beginning to be understood, thanks to new tools like
optogenetics that enable the manipulation of specific brain circuits. The
mood-regulating parts of the human brain have long been studied as an
interrelated cortical-limbic system, and research efforts have identified
correlates of these areas in non-human primates and rodents(Price &
Drevets, 2009). A key regulator of the limbic system is the mPFC, which
exerts top-down influence over other emotion-related areas. In humans, the