Posts Tagged ‘psychiatry’

by Rachel Metz

There are about 45 million people in the US alone with a mental illness, and those illnesses and their courses of treatment can vary tremendously. But there is something most of those people have in common: a smartphone.

A startup founded in Palo Alto, California, by a trio of doctors, including the former director of the US National Institute of Mental Health, is trying to prove that our obsession with the technology in our pockets can help treat some of today’s most intractable medical problems: depression, schizophrenia, bipolar disorder, post-traumatic stress disorder, and substance abuse.

Mindstrong Health is using a smartphone app to collect measures of people’s cognition and emotional health as indicated by how they use their phones. Once a patient installs Mindstrong’s app, it monitors things like the way the person types, taps, and scrolls while using other apps. This data is encrypted and analyzed remotely using machine learning, and the results are shared with the patient and the patient’s medical provider.

The seemingly mundane minutiae of how you interact with your phone offers surprisingly important clues to your mental health, according to Mindstrong’s research—revealing, for example, a relapse of depression. With details gleaned from the app, Mindstrong says, a patient’s doctor or other care manager gets an alert when something may be amiss and can then check in with the patient by sending a message through the app (patients, too, can use it to message their care provider).

For years now, countless companies have offered everything from app-based therapy to games that help with mood and anxiety to efforts to track smartphone activities or voice and speech for signs of depression. But Mindstrong is different, because it’s considering how users’ physical interactions with the phones—not what they do, but how they do it—can point to signs of mental illness. That may lead to far more accurate ways to track these problems over time. If Mindstrong’s method works, it could be the first that manages to turn the technology in your pocket into the key to helping patients with a wide range of chronic brain disorders—and may even lead to ways to diagnose them before they start.

Digital fingerprints
Before starting Mindstrong, Paul Dagum, its founder and CEO, paid for two Bay Area–based studies to figure out whether there might be a systemic measure of cognitive ability—or disability—hidden in how we use our phones. One hundred and fifty research subjects came into a clinic and underwent a standardized neurocognitive assessment that tested things like episodic memory (how you remember events) and executive function (mental skills that include the ability to control impulses, manage time, and focus on a task)—the kinds of high-order brain functions that are weakened in people with mental illnesses.

The assessment included neuropsychological tests that have been used for decades, like a so-called timed trail-­tracing test, where you have to connect scattered letters and numbers in the proper order—a way to measure how well people can shift between tasks. People who have a brain disorder that weakens their attention may have a harder time with this.

Subjects went home with an app that measured the ways they touched their phone’s display (swipes, taps, and keyboard typing), which Dagum hoped would be an unobtrusive way to log these same kinds of behavior on a smartphone. For the next year, it ran in the background, gathering data and sending it to a remote server. Then the subjects came back for another round of neurocognitive tests.

As it turns out, the behaviors the researchers measured can tell you a lot. “There were signals in there that were measuring, correlating—predicting, in fact, not just correlating with—the neurocognitive function measures that the neuropsychologist had taken,” Dagum says.

For instance, memory problems, which are common hallmarks of brain disorders, can be spotted by looking at things including how rapidly you type and what errors you make (such as how frequently you delete characters), as well as by how fast you scroll down a list of contacts. (Mindstrong can first determine your baseline by looking at how you use your handset and combining those characteristics with general measures.) Even when you’re just using the smartphone’s keyboard, Dagum says, you’re switching your attention from one task to another all the time—for example, when you’re inserting punctuation into a sentence.

He became convinced the connections presented a new way to investigate human cognition and behavior over time, in a way that simply isn’t possible with typical treatment like regularly visiting a therapist or getting a new medication, taking it for a month, and then checking back in with a doctor. Brain-disorder treatment has stalled in part because doctors simply don’t know that someone’s having trouble until it’s well advanced; Dagum believes Mindstrong can figure it out much sooner and keep an eye on it 24 hours a day.

In 2016, Dagum visited Verily, Alphabet’s life sciences company, where he pitched his work to a group including Tom Insel, a psychiatrist who had spent 13 years as director of the National Institute of Mental Health before he joined Verily in 2015.

Verily was trying to figure out how to use phones to learn about depression or other mental health conditions. But Insel says that at first, what Dagum presented—more a concept than a show of actual data—didn’t seem like a big deal. “The bells didn’t go off about what he had done,” he says.

Over several meetings, however, Insel realized that Dagum could do something he believed nobody in the field of mental health had yet been able to accomplish. He had figured out smartphone signals that correlated strongly with a person’s cognitive performance—the kind of thing usually possible only through those lengthy lab tests. What’s more, he was collecting these signals for days, weeks, and months on end, making it possible, in essence, to look at a person’s brain function continuously and objectively. “It’s like having a continuous glucose monitor in the world of diabetes,” Insel says.

Why should anyone believe that what Mindstrong is doing can actually work? Dagum says that thousands of people are using the app, and the company now has five years of clinical study data to confirm its science and technology. It is continuing to perform numerous studies, and this past March it began working with patients and doctors in clinics.

In its current form, the Mindstrong app that patients see is fairly sparse. There’s a graph that updates daily with five different signals collected from your smartphone swipes and taps. Four of these signals are measures of cognition that are tightly tied to mood disorders (such as the ability to make goal-based decisions), and the other measures emotions. There’s also an option to chat with a clinician.

For now, Insel says, the company is working mainly with seriously ill people who are at risk of relapse for problems like depression, schizophrenia, and substance abuse. “This is meant for the most severely disabled people, who are really needing some innovation,” he says. “There are people who are high utilizers of health care and they’re not getting the benefits, so we’ve got to figure out some way to get them something that works better.” Actually predicting that a patient is headed toward a downward spiral is a harder task, but Dagum believes that having more people using the app over time will help cement patterns in the data.

There are thorny issues to consider, of course. Privacy, for one: while Mindstrong says it protects users’ data, collecting such data at all could be a scary prospect for many of the people it aims to help. Companies may be interested in, say, including it as part of an employee wellness plan, but most of us wouldn’t want our employers anywhere near our mental health data, no matter how well protected it may be.

Spotting problems before they start
A study in the works at the University of Michigan is looking at whether Mindstrong may be beneficial for people who do not have a mental illness but do have a high risk for depression and suicide. Led by Srijan Sen, a professor of psychiatry and neuroscience, the study tracks the moods of first-year doctors across the country—a group that is known to experience intense stress, frequent sleep deprivation, and very high rates of depression.

Participants log their mood each day and wear a Fitbit activity tracker to log sleep, activity, and heart-rate data. About 1,500 of the 2,000 participants also let a Mindstrong keyboard app run on their smartphones to collect data about the ways they type and figure out how their cognition changes throughout the year.

Sen hypothesizes that people’s memory patterns and thinking speed change in subtle ways before they realize they’re depressed. But he says he doesn’t know how long that lag will be, or what cognitive patterns will be predictive of depression.

Insel also believes Mindstrong may lead to more precise diagnoses than today’s often broadly defined mental health disorders. Right now, for instance, two people with a diagnosis of major depressive disorder might share just one of numerous symptoms: they could both feel depressed, but one might feel like sleeping all the time, while the other is hardly sleeping at all. We don’t know how many different illnesses are in the category of depression, Insel says. But over time Mindstrong may be able to use patient data to find out. The company is exploring how learning more about these distinctions might make it possible to tailor drug prescriptions for more effective treatment.

Insel says it’s not yet known if there are specific digital markers of, say, auditory hallucinations that someone with schizophrenia might experience, and the company is still working on how to predict future problems like post-traumatic stress disorder. But he is confident that the phone will be the key to figuring it out discreetly. “We want to be able to do this in a way that just fits into somebody’s regular life,” he says.



How and why human-unique characteristics such as highly social behavior, languages and complex culture have evolved is a long-standing question. A research team led by Tohoku University in Japan has revealed the evolution of a gene related to such human-unique psychiatric traits.

PhD candidate Daiki Sato and Professor Masakado Kawata have discovered SLC18A1 (VMAT1), which encodes vesicular monoamine transporter 1, as one of the genes evolved through natural selection in the human lineage. VMAT1 is mainly involved in the transport of neurochemicals, such as serotonin and dopamine in the body, and its malfunction leads to various psychiatric disorders. VMAT1 has variants consisting of two different amino acids, threonine (136Thr) and isoleucine (136Ile), at site 136.

Several studies have shown that these variants are associated with psychiatric disorders, including schizophrenia, bipolar disorder, anxiety, and neuroticism (a personality trait). It has been known that individuals with 136Thr tend to be more anxious and more depressed and have higher neuroticism scores. They showed that other mammals have 136Asn at this site but 136Thr had been favored over 136Asn during human evolution. Moreover, the 136Ile variant had originated nearly at the Out-of-Africa migration, and then, both 136Thr and 136Ile variants have been positively maintained by natural selection in non-African populations.

The study by Sato and Kawata indicates that natural selection has possibly shaped our psychiatric traits and maintained its diversity. The results provide two important implications for human psychiatric evolution. First, through positive selection, the evolution from Asn to Thr at site 136 on SLC18A1 was favored by natural selection during the evolution from ancestral primates to humans, although individuals with 136Thr are more anxious and have more depressed minds.

Second, they showed that the two variants of 136Thr and 136Ile have been maintained by natural selection using several population genetic methods. Any form of natural selection that maintains genetic diversity within populations is called “balancing selection”. Individual differences in psychiatric traits can be observed in any human population, and some personality traits are also found in non-human primates. This suggests the possibility that a part of genetic diversity associated with personality traits and/or psychiatric disorders are maintained by balancing selection, although such selective pressure is often weak and difficult to detect.


By Alan Mozes

People with attention-deficit/hyperactivity disorder (ADHD) may be more than twice as likely to develop an early onset form of Parkinson’s, new research warns.

What’s more, among “those ADHD patients who had a record of being treated with amphetamine-like drugs — especially Ritalin [methylphenidate] — the risk dramatically increased, to between eight- to nine-fold,” said senior study author Glen Hanson.

But his team did not prove that ADHD or its medications actually caused Parkinson’s risk to rise, and one ADHD expert noted that the absolute risk of developing Parkinson’s remains very small.

For the study, researchers analyzed nearly 200,000 Utah residents. All had been born between 1950 and 1992, with Parkinson’s onset tracked up until the age of 60.

Prior to any Parkinson’s diagnosis, roughly 32,000 had been diagnosed with ADHD.

Hanson, a professor of pharmacology and toxicology at the University of Utah, said that ADHD patients were found to be “2.4 times more likely to develop Parkinson’s disease-like disorders prior to the age of 50 to 60 years,” compared with those with no history of ADHD. That finding held up even after accounting for a number of influential factors, including smoking, drug and alcohol abuse, and other psychiatric disorders.

“Although we cannot accurately say how much time elapsed between ADHD and [a] Parkinson’s-like disorder diagnosis, it was probably between 20 to 50 years,” he said.

As to what might explain the link, Hanson said that both ADHD and most forms of Parkinson’s source back to a “functional disorder of central nervous system dopamine pathways.”

In addition, Hanson said that “the drugs used to treat ADHD apparently work because of their profound effects on the activity of these dopamine pathways.” Theoretically, the treatment itself might trigger a metabolic disturbance, promoting dopamine pathway degeneration and, ultimately, Parkinson’s, he explained.

Still, Hanson pointed out that, for now, “we are not able to determine if the increased risk associated with stimulant use is due to the presence of the drug or the severity of the ADHD,” given that those treated with ADHD drugs tend to have more severe forms of the disorder.

And while demonstrating “a very strong association” between ADHD and Parkinson’s risk, the findings are preliminary, the study authors added.

Also, the absolute risk of developing Parkinson’s remained low, even in the most pessimistic scenario.

For example, the findings suggest that the risk of developing early onset Parkinson’s before the age of 50 would be eight or nine people out of every 100,000 with ADHD. This compares with one or two out of every 100,000 among those with no history of ADHD, the researchers said.

But the scientists noted that the results should raise eyebrows, because Parkinson’s primarily strikes people over the age of 60. Given the age range of those tracked so far in the study, Hanson said that his team was not yet able to ascertain Parkinson’s risk among ADHD patients after the age of 60.

Hanson also pointed out that because ADHD was only first diagnosed in the 1960s, only about 1.5 percent of the people in the study had an ADHD diagnosis, despite current estimates that peg ADHD prevalence at 10 percent. That suggests that the current findings may underestimate the scope of the problem.

“Clearly, there are some critical questions left to be answered concerning what is the full impact of this increased risk,” Hanson said.

Dr. Andrew Adesman is chief of developmental and behavioral pediatrics at Cohen Children’s Medical Center of New York with Northwell Health in New York City. He was not involved with the study and said the findings “surprised” him.

But, “we need to keep in mind that this study needs to be replicated and that the incidence of these conditions was very low, even among those with ADHD,” Adesman said. “The reality is that this would not affect 99.99 percent of individuals with ADHD.”

Meanwhile, Adesman said, “given that this study needs to be replicated, given that it is unclear whether ADHD medications further increase the risks of Parkinson’s, and given the very low risk in an absolute sense, I believe individuals with ADHD should not be hesitant to pursue or continue medical treatment for their ADHD.”

The report was published online Sept. 12 in the journal Neuropsychopharmacology.

Glen Hanson, DDS, Ph.D., vice dean and professor, pharmacology, School of Dentistry, University of Utah, Salt Lake City; Andrew Adesman, M.D., chief, developmental and behavioral pediatrics, Steven & Alexandra Cohen Children’s Medical Center of New York, Northwell Health, New York City; Sept. 12, 2018, Neuropsychopharmacology, online

A new study using machine learning has identified brain-based dimensions of mental health disorders, an advance towards much-needed biomarkers to more accurately diagnose and treat patients. A team at Penn Medicine led by Theodore D. Satterthwaite, MD, an assistant professor in the department of Psychiatry, mapped abnormalities in brain networks to four dimensions of psychopathology: mood, psychosis, fear, and disruptive externalizing behavior. The research is published in Nature Communications this week.

Currently, psychiatry relies on patient reporting and physician observations alone for clinical decision making, while other branches of medicine have incorporated biomarkers to aid in diagnosis, determination of prognosis, and selection of treatment for patients. While previous studies using standard clinical diagnostic categories have found evidence for brain abnormalities, the high level of diversity within disorders and comorbidity between disorders has limited how this kind of research may lead to improvements in clinical care.

“Psychiatry is behind the rest of medicine when it comes to diagnosing illness,” said Satterthwaite. “For example, when a patient comes in to see a doctor with most problems, in addition to talking to the patient, the physician will recommend lab tests and imaging studies to help diagnose their condition. Right now, that is not how things work in psychiatry. In most cases, all psychiatric diagnoses rely on just talking to the patient. One of the reasons for this is that we don’t understand how abnormalities in the brain lead to psychiatric symptoms. This research effort aims to link mental health issues and their associated brain network abnormalities to psychiatric symptoms using a data-driven approach.”

To uncover the brain networks associated with psychiatric disorders, the team studied a large sample of adolescents and young adults (999 participants, ages 8 to 22). All participants completed both functional MRI scans and a comprehensive evaluation of psychiatric symptoms as part of the Philadelphia Neurodevelopmental Cohort (PNC), an effort lead by Raquel E. Gur, MD, Ph.D., professor of Psychiatry, Neurology, and Radiology, that was funded by the National Institute of Mental Health. The brain and symptom data were then jointly analyzed using a machine learning method called sparse canonical correlation analysis.

This analysis revealed patterns of changes in brain networks that were strongly related to psychiatric symptoms. In particular, the findings highlighted four distinct dimensions of psychopathology—mood, psychosis, fear, and disruptive behavior—all of which were associated with a distinct pattern of abnormal connectivity across the brain.

The researchers found that each brain-guided dimension contained symptoms from several different clinical diagnostic categories. For example, the mood dimension was comprised of symptoms from three categories, e.g. depression (feeling sad), mania (irritability), and obsessive-compulsive disorder (recurrent thoughts of self-harm). Similarly, the disruptive externalizing behavior dimension was driven primarily by symptoms of both Attention Deficit Hyperactivity Disorder(ADHD) and Oppositional Defiant Disorder (ODD), but also included the irritability item from the depression domain. These findings suggest that when both brain and symptomatic data are taken into consideration, psychiatric symptoms do not neatly fall into established categories. Instead, groups of symptoms emerge from diverse clinical domains to form dimensions that are linked to specific patterns of abnormal connectivity in the brain.

“In addition to these specific brain patterns in each dimension, we also found common brain connectivity abnormalities that are shared across dimensions,” said Cedric Xia, a MD-Ph.D. candidate and the paper’s lead author. “Specifically, a pair of brain networks called default mode network and frontal-parietal network, whose connections usually grow apart during brain development, become abnormally integrated in all dimensions.”

These two brain networks have long intrigued psychiatrists and neuroscientists because of their crucial role in complex mental processes such as self-control, memory, and social interactions. The findings in this study support the theory that many types of psychiatric illness are related to abnormalities of brain development.

The team also examined how psychopathology differed across age and sex. They found that patterns associated with both mood and psychosis became significantly more prominent with age. Additionally, brain connectivity patterns linked to mood and fear were both stronger in female participants than males.

“This study shows that we can start to use the brain to guide our understanding of psychiatric disorders in a way that’s fundamentally different than grouping symptoms into clinical diagnostic categories. By moving away from clinical labels developed decades ago, perhaps we can let the biology speak for itself,” said Satterthwaite. “Our ultimate hope is that understanding the biology of mental illnesses will allow us to develop better treatments for our patients.”

More information: Cedric Huchuan Xia et al, Linked dimensions of psychopathology and connectivity in functional brain networks, Nature Communications (2018). DOI: 10.1038/s41467-018-05317-y


Young people suffering from treatment-resistant depression (TRD) showed a significant reduction of their symptoms after being administered ketamine injections, according to a study published in the Journal of Child and Adolescent Psychopharmacology.

Researchers from the University of Minnesota (UM) and the nonprofit Mayo Clinic found that ketamine caused an average decrease of 42 percent on the Children’s Depression Rating Scale (CDRS)—the most widely used rating scale in research trials for assessing the severity of depression and change in depressive symptoms among adolescents.

Ketamine is perhaps best known for being a popular recreational drug and a useful medical anesthetic, but a growing body of research is indicating that the compound could be an effective treatment for depression. Several recent studies have shown that even a single dose in adults can lead to rapid reductions in depressive symptoms. However, relatively little research has been conducted into ketamine’s antidepressant effects in adolescents.

“Adolescence is a very important time for studying depression, first because depression often starts during these years, and second because it is an important time for brain development,” Kathryn Cullen, from the Department of Psychiatry at UM, told Newsweek.

“When adolescent depression persists without successful treatment, it can interfere with achieving important developmental milestones. Finding the right treatment is critical to allow the restoration of healthy brain development and prevent negative outcomes like chronic depression, disability and suicide.”

Unfortunately, about 40 percent of adolescents do not respond to their first intervention and only half of nonresponders respond to the second treatment, according to the researchers.

“Standard antidepressant treatments do not work for everyone and take weeks to months to take effect, a time period when patients are at risk for continued suffering and suicide attempts,” Cullen said. “The field is in need of new treatment options. Ketamine has a very different mechanism of action than standard treatments.”

The latest study involved 13 young people ages 12 to 18 who had failed two previous trials of antidepressants. During a two-week period, the researchers gave them six ketamine infusions.

They found that the treatment was well tolerated, with the participants showing an average decrease in CDRS scores of 42.5 percent. Five of the participants met the criteria for clinical response and remission. Of these, three were still in remission after six weeks, while the remaining two relapsed within two weeks.

According to the scientists, the results demonstrate the potential role for ketamine in treating adolescents with TRD. However, they note that the study was limited by its small sample size, so future research will be needed to confirm these results.

“The purpose of our study was to investigate the effects of ketamine for TRD in younger patients for whom this indication for ketamine administration is not well studied,” Mark Roback, a professor of pediatrics at the University of Minnesota, told Newsweek.

“I think our results show promise for this population, however this study is just a beginning. The study serves to point out the need for further, rigorous, study designed to answer the many questions that remain about ketamine for TRD, such as optimal dosing and route of administration, dosing interval and treatment length, and long-term effects—just to name a few.”

James Stone, a clinical senior lecturer from the Institute of Psychiatry, Psychology and Neuroscience at King’s College London, who was not involved in the study, told Newsweek that there is “a lot of potential for the use of ketamine as a second or third line antidepressant where other treatments have failed.”

“Although ketamine is potentially a huge breakthrough in the treatment of depression, we still don’t know about the long-term safety, or about how to keep people well from depression without requiring regular ketamine dosing,” Stone added. “Further studies are needed to address these questions.”

Researchers believe that large cells called nucleus gigantocellularis neurons, pictured here, modulate blood flow by releasing nitric oxide.

There is no shortage of wonders that our central nervous system produces—from thought and language to movement to the five senses. All of those dazzling traits, however, depend on an underappreciated deep brain mechanism that Donald Pfaff, head of the Laboratory of Neurobiology and Behavior at The Rockefeller University, calls generalized arousal, or GA for short. GA is what wakes us up in the morning and keeps us aware and in touch with ourselves and our environment throughout our conscious hours.

“It’s so fundamental that we don’t pay attention to it,” says Pfaff, “and yet it’s so important that we should.”

Pfaff and his team of researchers certainly do. Now, in a series of experiments involving a particular type of brain cell, they have advanced our understanding of the roots of consciousness. Their work may potentially prove relevant in the study of some psychiatric diseases.

The big cells in the black box

The findings, published this month in Proceedings of the National Academy of Sciences, shed light on an area of the brainstem that is so little understood the first author of the paper, Inna Tabansky, a research associate in Pfaff’s lab, calls it “the black box.” That term is certainly simpler than its actual name—the nucleus gigantocellularis (NGC), which is part of a structure called the medullary reticular formation.

In her work, using mice, Tabansky focused on a subtype of extremely large neurons in the NGC with links to virtually the entire nervous system, including the thalamus, where neurons can activate the entire cerebral cortex. “If you just look at the morphology of NGC neurons, you know they’re important,” Pfaff says. “It’s just a question of what they’re important for. I think they’re essential for the initiation of any behavior.”

To discover what role the NGC neurons might play in GA, Tabansky and her colleagues, including Joel Stern, a visiting professor in the Pfaff lab, began by identifying the genes that these neurons express. They used a technique known as “retro-TRAP,” developed in the lab of Rockefeller scientist Jeffrey Friedman.

To Tabansky’s surprise, the NGC neurons were found to express the gene for an enzyme, endothelial nitric oxide synthase (eNOS), which produces nitric oxide, which in turn relaxes blood vessels, increasing the flow of oxygenated blood to tissue. (No other neurons in the brain are known to produce eNOS.) They also discovered that the eNOS-expressing NGC neurons are located close to blood vessels.

In Pfaff’s view, the neurons are so critical for the normal functions of the central nervous system that they have evolved the ability to control their own blood supply directly. ‘“We’re pretty sure that if these neurons need more oxygen and glucose, they will release nitric oxide into these nearby blood vessels in order to get it,” he says.

The circumstances that would prompt such a response were the subject of further experiments. The scientists found evidence that changes in the environment, such as the introduction of novel scents, activated eNOS in the NGC neurons and produced increased amounts of nitric oxide in mice.

“There is some low level of production when the animal is in a familiar setting,” says Tabansky, “which is what you expect as they maintain arousal. But it is vastly increased when the animal is adapting to a new environment.” This activation of the NGC neurons supports the case for their central role in arousal, Tabansky says.

From cells to psychiatry

Going forward, Tabansky says she’s interested in exploring if their findings might help fill a gap in the understanding of certain disorders, such as bipolar disorder, suicidality, and ADHD. Some genetic research has implicated a role for the neurons she studied in these diseases, but the mechanism behind this link is not known.

“By showing that this gene and its associated pathways have a particular role, at least in the rodent brain, that relates to a fundamental function of the nervous system, is a hint about how this gene can cause psychiatric disease,” she says. “It’s very preliminary, and there is a lot more work to be done, but it potentially opens a new way to study how this gene can alter an individual’s psychology.”

A study by scientists of the German Center for Neurodegenerative Diseases (DZNE) points to a novel potential approach against Alzheimer’s disease. In studies in mice, the researchers were able to show that blocking a particular receptor located on astrocytes normalized brain function and improved memory performance. Astrocytes are star-shaped, non-neuronal cells involved in the regulation of brain activity and blood flow. The findings are published in the Journal of Experimental Medicine (JEM).

Alzheimer’s disease is a common and currently incurable brain disorder leading to dementia, whose mechanisms remain incompletely understood. The disease appears to be sustained by a combination of factors that include pathological changes in blood flow, neuroinflammation and detrimental changes in brain cell activity.

“The brain contains different types of cells including neurons and astrocytes”, explains Dr. Nicole Reichenbach, a postdoc researcher at the DZNE and first author of the paper published in JEM. “Astrocytes support brain function and shape the communication between neurons, called synaptic transmission, by releasing a variety of messenger proteins. They also provide metabolic and structural support and contribute to the regulation of blood flow in the brain.”

Glitches in network activity

Similar to neurons, astrocytes are organized into functional networks that may involve thousands of cells. “For normal brain function, it is crucial that networks of brain cells coordinate their firing rates. It’s like in a symphony orchestra where the instruments have to be correctly tuned and the musicians have to stay in synchrony in order to play the right melody”, says Professor Gabor Petzold, a research group leader at the DZNE and supervisor of the current study. “Interestingly, one of the main jobs of astrocytes is very similar to this: to keep neurons healthy and to help maintain neuronal network function. However, in Alzheimer’s disease, there is aberrant activity of these networks. Many cells are hyperactive, including neurons and astrocytes. Hence, understanding the role of astrocytes, and targeting such network dysfunctions, holds a strong potential for treating Alzheimer’s.”

Astrocyte-targeted treatment alleviated memory impairment

Petzold and colleagues tested this approach in an experimental study involving mice. Due to a genetic disposition, these rodents exhibited certain symptoms of Alzheimer’s similar to those that manifest in humans with the disease. In the brain, this included pathological deposits of proteins known as “Amyloid-beta plaques” and aberrant network activity. In addition, the mice showed impaired learning ability and memory.

In their study, the DZNE scientists targeted a cell membrane receptor called P2Y1R, which is predominately expressed by astrocytes. Previous experiments by Petzold and colleagues had revealed that activation of this receptor triggers cellular hyperactivity in mouse models of Alzheimer’s. Therefore, the researchers treated groups of mice with different P2Y1R antagonists. These chemical compounds can bind to the receptor, thus switching it off. The treatment lasted for several weeks.

“We found that long-term treatment with these drugs normalized the brain’s network activity. Furthermore, the mice’s learning ability and memory greatly improved”, Petzold says. On the other hand, in a control group of wild type mice this treatment had no significant effect on astrocyte activity. “This indicates that P2Y1R inhibition acts quite specifically. It does not dampen network activity when pathological hyperactivity is absent.”

New approaches for research and therapies?

Petzold summarizes: “This is an experimental study that is currently not directly applicable to human patients. However, our results suggest that astrocytes, as important safeguards of neuronal health and normal network function, may hold the potential for novel treatment options in Alzheimer’s disease.” In future studies, the scientists intend to identify additional novel pathways in astrocytes and other cells as potential drug targets.

Reichenbach, N., Delekate, A., Breithausen, B., Keppler, K., Poll, S., Schulte, T., . . . Petzold, G. C. (2018). P2Y1 receptor blockade normalizes network dysfunction and cognition in an Alzheimer’s disease model. The Journal of Experimental Medicine. doi:10.1084/jem.20171487