New findings on how ketamine acts against depression
The discovery that the anaesthetic ketamine can help people with severe depression has raised hopes of finding new treatment options for the disease. Researchers at Karolinska Institutet have now identified novel mechanistic insights of how the drug exerts its antidepressant effect. The findings have been published in the journal Molecular Psychiatry.
According to the World Health Organization, depression is a leading cause of disability worldwide and the disease affects more than 360 million people every year.
The risk of suffering is affected by both genetics and environmental factors. The most commonly prescribed antidepressants, such as SSRIs, affect nerve signalling via monoamines in the brain.
However, it can take a long time for these drugs to help, and over 30 percent of sufferers experience no relief at all.
The need for new types of antidepressants with faster action and wider effect is therefore considerable.
An important breakthrough is the anaesthetic ketamine, which has been registered for some years in the form of a nasal spray for the treatment of intractable depression.
Relieves depressive symptoms quickly
Unlike classic antidepressants, ketamine affects the nerve signalling that occurs via the glutamate system, but it is unclear exactly how the antidepressant effect is mediated. When the medicine has an effect, it relieves depressive symptoms and suicidal thoughts very quickly.
However, ketamine can cause unwanted side effects such as hallucinations and delusions and there may be a risk of abuse so alternative medicines are needed.
The researchers want to better understand how ketamine works in order to find substances that can have the same rapid effect but without the side effects.
Explains ketamine’s effects
In a new study, researchers at Karolinska Institutet have further investigated the molecular mechanisms underlying ketamine’s antidepressant effects. Using experiments on both cells and mice, the researchers were able to show that ketamine reduced so-called presynaptic activity and the persistent release of the neurotransmitter glutamate.
“Elevated glutamate release has been linked to stress, depression and other mood disorders, so lowered glutamate levels may explain some of the effects of ketamine,” says Per Svenningsson, professor at the Department of Clinical Neuroscience, Karolinska Institutet, and the study’s last author.
When nerve signals are transmitted, the transmission from one neuron to the next occurs via synapses, a small gap where the two neurons meet.
The researchers were able to see that ketamine directly stimulated AMPA receptors, which sit postsynaptically, that is, the part of the nerve cell that receives signals and this leads to the increased release of the neurotransmitter adenosine which inhibits presynaptic glutamate release.
The effects of ketamine could be counteracted by the researchers inhibiting presynaptic adenosine A1 receptors.
“This suggests that the antidepressant action of ketamine can be regulated by a feedback mechanism. It is new knowledge that can explain some of the rapid effects of ketamine,” says Per Svenningsson.
In collaboration with Rockefeller University, the same research group has also recently reported on the disease mechanism in depression.
The findings, also published in the journal Molecular Psychiatry, show how the molecule p11 plays an important role in the onset of depression by affecting cells sitting on the surface of the brain cavity, ependymal cells, and the flow of cerebrospinal fluid.
Advancing the understanding and treatment of psychiatric disorders is a principal goal of neuroscientists. As mental disorders are the leading cause of disabilities worldwide, it is concerning that there are few effective therapeutics on the market due to the lack of knowledge regarding pathophysiology. In particular, the main treatment for major depressive disorders are antidepressants, which target the monoaminergic system and include selective serotonin reuptake inhibitors (SSRIs). However, these drugs take six weeks on average before symptom relief and many individuals are unaffected by them.
Ketamine, a synthetic analogue of PCP, has recently taken the spotlight as a novel, fast-acting antidepressant. The benefits of ketamine include a one-time, low-dose IV infusion, where symptoms are alleviated within hours and which lasts for up to two weeks in patients with depression. Even more compelling is that this regimen affects patients with treatment-resistant depression, meaning those who do not respond to current antidepressants. These effects are especially important in helping individuals with depression who may be experiencing suicidal ideation because of ketamine’s fast-acting nature and it is the only treatment effective for treatment resistant patients.
However, there are many downsides to the use of ketamine as an antidepressant, especially with long-term or repeated use. For example, ketamine is an illicit drug with high abuse potential, commonly known as the party drug “Special K.” Therefore, close clinical monitoring of the use of this drug is necessary. In regards to neuroscience research in the past decade, it has been demonstrated that chronic, low-dose ketamine has been used to study learning and memory deficits in a rodent model of schizophrenia. The biochemical data from these animals reveal a change in a specific type of neuron in the brain that is important for network activity underlying normal cognitive functioning. This begs the question: Can ketamine work as an antidepressant without producing cognitive deficits associated long-term use?
In order to address this question, we need to understand the molecular mechanisms that ketamine is utilizing to produce these beneficial antidepressant effects. Although researchers do not know exactly how ketamine works, we know that it is in a different way than current antidepressants on the market. There is no clear answer yet, but researchers have produced some promising results. Using ketamine to deepen our understanding of depression will advance the field of neuroscience and ultimately lead to a more effective treatment for the disorder.
(Image caption: Mutations in the GABA-A receptor cause a temporary imbalance between GABA signaling (yellow) and glutamate signaling (blue) in the brain. Homeostatic down regulation of glutamate signaling rebalances the system at a lower level and can lead to depression. Treatment with ketamine restores both GABA and glutamate levels to normal. Credit: Penn State University)
New research demonstrates the effectiveness of ketamine to treat depression in a mouse model of the disease and brings together two hypotheses for the cause of depression. The research, led by Bernhard Lüscher, professor of biology and of biochemistry and molecular biology at Penn State University, is in press and was published in the September 15, 2016 print edition of the journal Biological Psychiatry.
“Depression is the second most expensive health problem that we face worldwide, but this fact is not very well known because there is a stigma attached to depression and people don’t like to talk about it,” said Lüscher. “About 17 percent of Americans will be treated for depression at some point in their lives, but there are limited treatment options and about one-third of patients do not respond to these treatments.”
Lüscher and his colleagues generated a mouse model for depression by introducing a mutation into a gene that codes for one of the subunits of a receptor for GABA – the second most abundant chemical used by nerve cells in the brain to communicate. GABA functions mainly to reduce the activity of nerve cells. The receptor mutation results in a reduction in GABA signaling of about 15 to 20 percent and mimics reductions in GABA signaling seen in patients with depression. The mice that have the mutation exhibit traits associated with depression, such as reduced pleasure seeking, and they become normal again following treatment with antidepressant medications.
“You can think of GABA as acting like the brakes of a car – its function is to slow activity in nerve cells,” said Lüscher. “Its counterpart is glutamate, another signaling chemical in the brain that acts as the accelerator of nerve-cell activity. When we reduced the function of GABA in our mice, we were surprised to see that the level of glutamate was also reduced. This result suggests that the brain has mechanisms that maintain a balance between the brakes and the accelerator to prevent brain activity from going out of control, a state we refer to as homeostasis.”
The researchers treated the mice with low doses of ketamine, an experimental antidepressant drug known to act by transiently blocking a major class of glutamate receptors in nerve cells. “Treatment with ketamine not only normalized the behavior and brought glutamate receptor levels back up to normal in our mice, but GABA function also was restored,” said Lüscher. Importantly, the effects of ketamine were only observed in mice with the receptor mutation where nerve signaling was defective, and not in normal mice. “Our results bring together the hypothesis that depression results from deficits in GABA signaling and the hypothesis that depression results from deficits in glutamate signaling. We showed that the depression-like behavior in our mice results from the reduction of both GABA and glutamate, and importantly, that both can be restored with a single dose of ketamine.”
The researchers plan to use their mouse model to better understand how ketamine functions to develop safer alternatives. “Ketamine has many advantages over currently used antidepressant medications,” said Lüscher. “It acts quickly and has long lasting effects, but it is addictive and can induce psychosis, so we hope to use our model to better understand how ketamine works biochemically. We can then begin to develop ketamine-like drugs without the unwanted side effects.”
Statistical model defines ketamine anesthesia’s effects on the brain
Neuroscientists at MIT and Massachusetts General Hospital have developed a statistical framework that rigorously describes the brain state changes that patients experience under ketamine-induced anesthesia.
By developing the first statistical model to finely characterize how ketamine anesthesia affects the brain, a team of researchers at MIT’s Picower Institute for Learning and Memory and Massachusetts General Hospital have laid new groundwork for three advances: understanding how ketamine induces anesthesia; monitoring the unconsciousness of patients in surgery; and applying a new method of analyzing brain activity.
Based on brain rhythm measurements from nine human and two animal subjects, the new model published in PLOS Computational Biology defines the distinct, characteristic states of brain activity that occur during ketamine-induced anesthesia, including how long each lasts. It also tracks patterns of how the states switch from one to the next. The “beta-hidden Markov model” therefore provides anesthesiologists, neuroscientists, and data scientists alike with a principled guide to how ketamine anesthesia affects the brain and what patients will experience.
In parallel work the lab of senior author Emery N. Brown, an anesthesiologist at MGH and Edward Hood Taplin Professor of Computational Neuroscience at MIT, has developed statistical analyses to characterize brain activity under propofol anesthesia, but as the new study makes clear, ketamine produces entirely different effects. Efforts to better understand the drug and to improve patient outcomes therefore depend on having a ketamine-specific model.
“Now we have an extremely solid statistical stake in the ground regarding ketamine and its dynamics,” said Brown, a professor in MIT’s Department of Brain and Cognitive Sciences and Institute for Medical Engineering & Science, as well as at Harvard Medical School.
Making a model
After colleagues at MGH showed alternating patterns of high-frequency gamma rhythms and very low-frequency delta rhythms in patients under ketamine anesthesia, Brown’s team, led by graduate student Indie Garwood and postdoc Sourish Chakravarty set out to conduct a rigorous analysis. Chakravarty suggested to Garwood that a hidden Markov model might fit the data well because it is suited to describing systems that switch among discrete states.
(Image caption: A multitaper spectrogram of 120 seconds of readings from a human patient under ketamine anesthesia shows distinct bands of high power (warmer colors) at high “gamma” frequencies and very low “delta” frequencies)
To conduct the analysis, Garwood and the team gathered data from two main sources. One set of measurements came from forehead-mounted EEGs on nine surgical patients who volunteered to undergo ketamine-induced anesthesia for a period of time before undergoing surgery with additional anesthetic drugs. The other came from electrodes implanted in the frontal cortex of two animals in the lab of Earl Miller, Picower Professor of Neuroscience at MIT.
Analysis of the readings with the hidden Markov model, using a beta distribution as an observation model, not only captured and characterized the previously observed alternations between gamma and delta rhythms, but a few other more subtle states that mixed the two rhythms.
Importantly, the model showed that the various states move through a characteristic order and defined how long each state lasts. Garwood said understanding these patterns allows for making predictions much in the same way that a new driver can learn to predict traffic lights. For instance, learning that lights change from green to yellow to red and that the yellow light only lasts a few seconds can help a new driver predict what to do when coming to an intersection. Similarly, anesthesiologists monitoring rhythms in a patient can use the findings to ensure that brain states are changing as they should, or make adjustments if they are not.
Characterizing the patterns of brain states and their transitions will also help neuroscientists better understand how ketamine acts in the brain, Brown added. As researchers create computational models of the underlying brain circuits and their response to the drug, he said, the new findings will give them important constraints. For instance, for a model to be valid, it should not only produce alternating gamma and slow rhythm states but also the more subtle ones. It should produce each state for the proper duration and yield state transitions in the proper order.
“Lacking this model was preventing some of our other work from going forward in a rigorous way,” Garwood said. “Developing this method allowed us to get that quantitative description that we need to be able to understand what’s going on and what sort of neural activity is generating these states.”
New ideas
As neuroscientists learn more about how ketamine induces unconsciousness from such efforts, one major implication is already apparent, Brown said. Whereas propofol causes brain activity to become dominated by very low-frequency rhythms, ketamine includes periods of high power in high frequency rhythms. Those two very different means of achieving unconsciousness seems to suggest that consciousness is a state that can be lost in multiple ways, Brown said.
“I can make you unconscious by making your brain hyperactive in some sense, or I can make you unconscious by slowing it down,” he said. “The more general concept is there’s a dynamic—we can’t define it precisely—which is associated with you being conscious and as soon as you move away from that dynamic by being too fast or too slow, or too discoordinated or hypercoordinated, you can be unconscious.”
In addition to considering that hypothesis, the team is looking at several new projects including measuring ketamine’s effects across wider areas of the brain and measuring the effects as subjects awaken from anesthesia.
Developing systems that can monitor unconsciousness under ketamine anesthesia in a clinical setting will require developing versions of the model that can run in real-time, the authors added. Right now, the system can only be applied to data post-hoc.
