Tag: Alzheimer’s disease

Music Activates Regions of the Brain Spared by Alzheimer’s Disease

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Ever get chills listening to a particularly moving piece of music? You can thank the salience network of the brain for that emotional joint. Surprisingly, this region also remains an island of remembrance that is spared from the ravages of Alzheimer’s disease. Researchers at the University of Utah Health are looking to this region of the brain to develop music-based treatments to help alleviate anxiety in patients with dementia. Their research will appear in the April online issue of The Journal of Prevention of Alzheimer’s Disease.

“People with dementia are confronted by a world that is unfamiliar to them, which causes disorientation and anxiety” said Jeff Anderson, M.D., Ph.D., associate professor in Radiology at U of U Health and contributing author on the study.“We believe music will tap into the salience network of the brain that is still relatively functioning.”

Previous work demonstrated the effect of a personalized music program on mood for dementia patients. This study set out to examine a mechanism that activates the attentional network in the salience region of the brain. The results offer a new way to approach anxiety, depression and agitation in patients with dementia. Activation of neighboring regions of the brain may also offer opportunities to delay the continued decline caused by the disease.

For three weeks, the researchers helped participants select meaningful songs and trained the patient and caregiver on how to use a portable media player loaded with the self-selected collection of music.

“When you put headphones on dementia patients and play familiar music, they come alive,” said Jace King, a graduate student in the Brain Network Lab and first author on the paper. “Music is like an anchor, grounding the patient back in reality.”

Using a functional MRI, the researchers scanned the patients to image the regions of the brain that lit up when they listened to 20-second clips of music versus silence. The researchers played eight clips of music from the patient’s music collection, eight clips of the same music played in reverse and eight blocks of silence. The researchers compared the images from each scan.

The researchers found that music activates the brain, causing whole regions to communicate. By listening to the personal soundtrack, the visual network, the salience network, the executive network and the cerebellar and corticocerebellar network pairs all showed significantly higher functional connectivity.

“This is objective evidence from brain imaging that shows personally meaningful music is an alternative route for communicating with patients who have Alzheimer’s disease,” said Norman Foster, M.D., Director of the Center for Alzheimer’s Care at U of U Health and senior author on the paper.“Language and visual memory pathways are damaged early as the disease progresses, but personalized music programs can activate the brain, especially for patients who are losing contact with their environment.”

However, these results are by no means conclusive. The researchers note the small sample size (17 participants) for this study. In addition, the study only included a single imaging session for each patient. It is remains unclear whether the effects identified in this study persist beyond a brief period of stimulation or whether other areas of memory or mood are enhanced by changes in neural activation and connectivity for the long term.

“In our society, the diagnoses of dementia are snowballing and are taxing resources to the max,” Anderson said. “No one says playing music will be a cure for Alzheimer’s disease, but it might make the symptoms more manageable, decrease the cost of care and improve a patient’s quality of life.”

https://www.technologynetworks.com/neuroscience/news/music-activation-of-salience-network-could-alleviate-anxiety-in-alzheimers-disease-300268?utm_campaign=Newsletter_TN_BreakingScienceNews&utm_source=hs_email&utm_medium=email&utm_content=62522460&_hsenc=p2ANqtz-9ihWyFIxhX4_ZqRqTTeOrNwa0ZHtTKERWsL_8k0sb5boN7jUkYGkdh9HwUwTgNxQfBVCpLL2CkwNk4uJpbMDlvKJPNJw&_hsmi=62522460

Laboratory mouse studies suggest that long-term, low dose caffeine worsens anxiety and emotional and cognitive flexibility in people with Alzheimer’s disease, while providing only little benefit to learning and memory.

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The study simulated long-term consumption of three cups of coffee a day.

It is well known that memory problems are the hallmarks of Alzheimer’s disease. However, this dementia is also characterized by neuro-psychiatric symptoms, which may be strongly present already in the first stages of the disorder. Known as Behavioural and Psychological Symptoms of Dementia (BPSD), this array of symptoms — including anxiety, apathy, depression, hallucinations, paranoia and sundowning (or late-day confusion) — are manifested in different manners depending on the individual patient, and are considered the strongest source of distress for patients and caregivers.


Coffee and caffeine: good or bad for dementia?

Caffeine has recently been suggested as a strategy to prevent dementia, both in patients with Alzheimer’s disease and in normal ageing processes. This is due to its action in blocking molecules — adenosine receptors — which may cause dysfunctions and diseases in old age. However, there is some evidence that once cognitive and neuro-psychiatric symptoms develop, caffeine may exert opposite effects.

To investigate this further, researchers from Spain and Sweden conducted a study with normal ageing mice and familial Alzheimer’s models. The research, published in Frontiers in Pharmacology, was conducted from the onset of the disease up to more advanced stages, as well as in healthy age-matched mice.

“The mice develop Alzheimer’s disease in a very close manner to human patients with early-onset form of the disease,” explains first author Raquel Baeta-Corral, from Universitat Autònoma de Barcelona, Spain. “They not only exhibit the typical cognitive problems but also a number of BPSD-like symptoms. This makes them a valuable model to address whether the benefits of caffeine will be able to compensate its putative negative effects.”

“We had previously demonstrated the importance of the adenosine A1 receptor as the cause of some of caffeine’s adverse effects,” explains Dr. Björn Johansson, a researcher and physician at the Karolinska University Hospital, Sweden.

“In this study, we simulated a long oral treatment with a very low dose of caffeine (0.3 mg/mL) — equivalent to three cups of coffee a day for a human — to answer a question which is relevant for patients with Alzheimer’s, but also for the ageing population in general, and that in people would take years to be solved since we would need to wait until the patients were aged.”

Worsened Alzheimer’s symptoms outweigh cognition benefits

The results indicate that caffeine alters the behavior of healthy mice and worsens the neuropsychiatric symptoms of mice with Alzheimer’s disease. The researchers discovered significant effects in the majority of the study variables — and especially in relation to neophobia (a fear of everything new), anxiety-related behaviors, and emotional and cognitive flexibility.

In mice with Alzheimer’s disease, the increase in neophobia and anxiety-related behaviours exacerbates their BPSD-like profile. Learning and memory, strongly influenced by anxiety, got little benefit from caffeine.

“Our observations of adverse caffeine effects in an Alzheimer’s disease model, together with previous clinical observations, suggest that an exacerbation of BPSD-like symptoms may partly interfere with the beneficial cognitive effects of caffeine. These results are relevant when coffee-derived new potential treatments for dementia are to be devised and tested,” says Dr. Lydia Giménez-Llort, researcher from the INc-UAB Department of Psychiatry and Legal Medicine, Universitat Autònoma de Barcelona, and lead researcher of the project.

The results of the study form part of the PhD thesis of Raquel Baeta-Corral, first author of the article, and are the product of a research led by Lydia Giménez-Llort, Director of the Medical Psychology Unit, Department of Psychiatry and Legal Medicine and researcher at the UAB Institute of Neuroscience, together with Dr Björn Johansson, Researcher at the Department of Molecular Medicine and Surgery, Karolinska Institutet and the Department of Geriatrics, Karolinska University Hospital, Sweden, under the framework of the Health Research Fund project of the Institute of Health Carlos III.

Long-term caffeine worsens symptoms associated with Alzheimer’s disease

AI can spot signs of Alzheimer’s disease before people do

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by Emily Mullin

When David Graham wakes up in the morning, the flat white box that’s Velcroed to the wall of his room in Robbie’s Place, an assisted living facility in Marlborough, Massachusetts, begins recording his every movement.

It knows when he gets out of bed, gets dressed, walks to his window, or goes to the bathroom. It can tell if he’s sleeping or has fallen. It does this by using low-power wireless signals to map his gait speed, sleep patterns, location, and even breathing pattern. All that information gets uploaded to the cloud, where machine-learning algorithms find patterns in the thousands of movements he makes every day.

The rectangular boxes are part of an experiment to help researchers track and understand the symptoms of Alzheimer’s.

It’s not always obvious when patients are in the early stages of the disease. Alterations in the brain can cause subtle changes in behavior and sleep patterns years before people start experiencing confusion and memory loss. Researchers think artificial intelligence could recognize these changes early and identify patients at risk of developing the most severe forms of the disease.

Spotting the first indications of Alzheimer’s years before any obvious symptoms come on could help pinpoint people most likely to benefit from experimental drugs and allow family members to plan for eventual care. Devices equipped with such algorithms could be installed in people’s homes or in long-term care facilities to monitor those at risk. For patients who already have a diagnosis, such technology could help doctors make adjustments in their care.

Drug companies, too, are interested in using machine-learning algorithms, in their case to search through medical records for the patients most likely to benefit from experimental drugs. Once people are in a study, AI might be able to tell investigators whether the drug is addressing their symptoms.

Currently, there’s no easy way to diagnose Alzheimer’s. No single test exists, and brain scans alone can’t determine whether someone has the disease. Instead, physicians have to look at a variety of factors, including a patient’s medical history and observations reported by family members or health-care workers. So machine learning could pick up on patterns that otherwise would easily be missed.


David Graham, one of Vahia’s patients, has one of the AI-powered devices in his room at Robbie’s Place, an assisted living facility in Marlborough, Massachusetts.

Graham, unlike the four other patients with such devices in their rooms, hasn’t been diagnosed with Alzheimer’s. But researchers are monitoring his movements and comparing them with patterns seen in patients who doctors suspect have the disease.

Dina Katabi and her team at MIT’s Computer Science and Artificial Intelligence Laboratory initially developed the device as a fall detector for older people. But they soon realized it had far more uses. If it could pick up on a fall, they thought, it must also be able to recognize other movements, like pacing and wandering, which can be signs of Alzheimer’s.

Katabi says their intention was to monitor people without needing them to put on a wearable tracking device every day. “This is completely passive. A patient doesn’t need to put sensors on their body or do anything specific, and it’s far less intrusive than a video camera,” she says.

How it works

Graham hardly notices the white box hanging in his sunlit, tidy room. He’s most aware of it on days when Ipsit Vahia makes his rounds and tells him about the data it’s collecting. Vahia is a geriatric psychiatrist at McLean Hospital and Harvard Medical School, and he and the technology’s inventors at MIT are running a small pilot study of the device.

Graham looks forward to these visits. During a recent one, he was surprised when Vahia told him he was waking up at night. The device was able to detect it, though Graham didn’t know he was doing it.

The device’s wireless radio signal, only a thousandth as powerful as wi-fi, reflects off everything in a 30-foot radius, including human bodies. Every movement—even the slightest ones, like breathing—causes a change in the reflected signal.

Katabi and her team developed machine-learning algorithms that analyze all these minute reflections. They trained the system to recognize simple motions like walking and falling, and more complex movements like those associated with sleep disturbances. “As you teach it more and more, the machine learns, and the next time it sees a pattern, even if it’s too complex for a human to abstract that pattern, the machine recognizes that pattern,” Katabi says.

Over time, the device creates large readouts of data that show patterns of behavior. The AI is designed to pick out deviations from those patterns that might signify things like agitation, depression, and sleep disturbances. It could also pick up whether a person is repeating certain behaviors during the day. These are all classic symptoms of Alzheimer’s.

“If you can catch these deviations early, you will be able to anticipate them and help manage them,” Vahia says.

In a patient with an Alzheimer’s diagnosis, Vahia and Katabi were able to tell that she was waking up at 2 a.m. and wandering around her room. They also noticed that she would pace more after certain family members visited. After confirming that behavior with a nurse, Vahia adjusted the patient’s dose of a drug used to prevent agitation.


Ipsit Vahia and Dina Katabi are testing an AI-powered device that Katabi’s lab built to monitor the behaviors of people with Alzheimer’s as well as those at risk of developing the disease.

Brain changes

AI is also finding use in helping physicians detect early signs of Alzheimer’s in the brain and understand how those physical changes unfold in different people. “When a radiologist reads a scan, it’s impossible to tell whether a person will progress to Alzheimer’s disease,” says Pedro Rosa-Neto, a neurologist at McGill University in Montreal.

Rosa-Neto and his colleague Sulantha Mathotaarachchi developed an algorithm that analyzed hundreds of positron-emission tomography (PET) scans from people who had been deemed at risk of developing Alzheimer’s. From medical records, the researchers knew which of these patients had gone on to develop the disease within two years of a scan, but they wanted to see if the AI system could identify them just by picking up patterns in the images.

Sure enough, the algorithm was able to spot patterns in clumps of amyloid—a protein often associated with the disease—in certain regions of the brain. Even trained radiologists would have had trouble noticing these issues on a brain scan. From the patterns, it was able to detect with 84 percent accuracy which patients ended up with Alzheimer’s.

Machine learning is also helping doctors predict the severity of the disease in different patients. Duke University physician and scientist P. Murali Doraiswamy is using machine learning to figure out what stage of the disease patients are in and whether their condition is likely to worsen.

“We’ve been seeing Alzheimer’s as a one-size-fits all problem,” says Doraiswamy. But people with Alzheimer’s don’t all experience the same symptoms, and some might get worse faster than others. Doctors have no idea which patients will remain stable for a while or which will quickly get sicker. “So we thought maybe the best way to solve this problem was to let a machine do it,” he says.

He worked with Dragan Gamberger, an artificial-intelligence expert at the Rudjer Boskovic Institute in Croatia, to develop a machine-learning algorithm that sorted through brain scans and medical records from 562 patients who had mild cognitive impairment at the beginning of a five-year period.

Two distinct groups emerged: those whose cognition declined significantly and those whose symptoms changed little or not at all over the five years. The system was able to pick up changes in the loss of brain tissue over time.

A third group was somewhere in the middle, between mild cognitive impairment and advanced Alzheimer’s. “We don’t know why these clusters exist yet,” Doraiswamy says.

Clinical trials

From 2002 to 2012, 99 percent of investigational Alzheimer’s drugs failed in clinical trials. One reason is that no one knows exactly what causes the disease. But another reason is that it is difficult to identify the patients most likely to benefit from specific drugs.

AI systems could help design better trials. “Once we have those people together with common genes, characteristics, and imaging scans, that’s going to make it much easier to test drugs,” says Marilyn Miller, who directs AI research in Alzheimer’s at the National Institute on Aging, part of the US National Institutes of Health.

Then, once patients are enrolled in a study, researchers could continuously monitor them to see if they’re benefiting from the medication.

“One of the biggest challenges in Alzheimer’s drug development is we haven’t had a good way of parsing out the right population to test the drug on,” says Vaibhav Narayan, a researcher on Johnson & Johnson’s neuroscience team.

He says machine-learning algorithms will greatly speed the process of recruiting patients for drug studies. And if AI can pick out which patients are most likely to get worse more quickly, it will be easier for investigators to tell if a drug is having any benefit.

That way, if doctors like Vahia notice signs of Alzheimer’s in a person like Graham, they can quickly get him signed up for a clinical trial in hopes of curbing the devastating effects that would otherwise come years later.

Miller thinks AI could be used to diagnose and predict Alzheimer’s in patients in as soon as five years from now. But she says it’ll require a lot of data to make sure the algorithms are accurate and reliable. Graham, for one, is doing his part to help out.

https://www.technologyreview.com/s/609236/ai-can-spot-signs-of-alzheimers-before-your-family-does/

A simple score may be able to determine the personal risk of developing Alzheimer’s disease

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For the first time, an international team of scientists, led by researchers at University of California San Diego School of Medicine, have determined that an Alzheimer’s disease (AD) polygenic risk score can be used to correctly identify adults with mild cognitive impairment (MCI) who were only in their 50s. MCI is considered a precursor to AD.

Findings were published in the February 27 online edition of Molecular Psychiatry.

The AD polygenic risk score was created from genome-wide association studies of AD with a combination of genes weighted according to the association of single nucleotide polymorphisms (SNPs) with AD. SNPs are variations of a single nucleotide or DNA-building block that occur at a specific position in the genome. There is some SNP variation in genomic information in all humans, which affects individual susceptibility to disease.

“Current studies of the AD polygenic risk score typically occur in adults in their 70s, but the AD pathological process begins decades before the onset of dementia,” said William S. Kremen, PhD, professor of psychiatry and co-director of the Center for Behavior Genetics of Aging at UC San Diego School of Medicine. “By focusing on a younger population with cognitive impairment, we may be better able to identify patients for critical early interventions and clinical trials.”

Kremen and team found that someone with an AD polygenic risk score in the upper quartile was 2.5 to 3 times more likely to have MCI than someone with a score in the lowest quartile. Signs of MCI may include difficulty with word recall, forgetting appointments, or often losing personal belongings. The type of MCI most associated with memory loss is called amnestic MCI.

According to the National Institute on Aging, more people with MCI than those without it go on to develop Alzheimer’s. Approximately eight of every 10 persons who fit the definition of amnestic MCI develop Alzheimer’s disease within seven years.

“Our research team found that the polygenic score could differentiate individuals with mild cognitive impairment from those who were cognitively normal,” said Kremen. “We also noticed that for study participants who had cognitive deficits other than memory problems, diabetes was three-fold more likely.”

Kremen added that while this test is not yet available to primary care physicians, it may be an important tool to aid researchers in predicting MCI and AD, and, eventually, reducing the number of future cases.

“The Alzheimer’s Association and others have modeled how the impact of delaying the onset of AD by five years could reduce the number of cases by nearly 50 percent by 2050. We want to do what we can to make this projection a reality,” said Kremen.

Data for this study were collected from 1,329 men who participated in the Vietnam Era Twin Study of Aging (VESTA.). VESTA constitutes a national sample comparable to U.S. men in their age range with respect to health and lifestyle characteristics. Approximately 90 percent of subjects in this analysis were in their 50s. Diagnosis of AD was based on the Jak-Bondi actuarial/neuropsychological approach.

This article has been republished from materials provided by UCSD. Note: material may have been edited for length and content. For further information, please contact the cited source.

Reference: Logue, M. W., Panizzon, M. S., Elman, J. A., Gillespie, N. A., Hatton, S. N., Gustavson, D. E., … Kremen, W. S. (2018). Use of an Alzheimer’s disease polygenic risk score to identify mild cognitive impairment in adults in their 50s. Molecular Psychiatry, 1. https://doi.org/10.1038/s41380-018-0030-8

How flashing lights and pink noise might banish Alzheimer’s, improve memory and more

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Illustration by Paweł Jońca

by Helen Thomson

In March 2015, Li-Huei Tsai set up a tiny disco for some of the mice in her laboratory. For an hour each day, she placed them in a box lit only by a flickering strobe. The mice — which had been engineered to produce plaques of the peptide amyloid-β in the brain, a hallmark of Alzheimer’s disease — crawled about curiously. When Tsai later dissected them, those that had been to the mini dance parties had significantly lower levels of plaque than mice that had spent the same time in the dark.

Tsai, a neuroscientist at Massachusetts Institute of Technology (MIT) in Cambridge, says she checked the result; then checked it again. “For the longest time, I didn’t believe it,” she says. Her team had managed to clear amyloid from part of the brain with a flickering light. The strobe was tuned to 40 hertz and was designed to manipulate the rodents’ brainwaves, triggering a host of biological effects that eliminated the plaque-forming proteins. Although promising findings in mouse models of Alzheimer’s disease have been notoriously difficult to replicate in humans, the experiment offered some tantalizing possibilities. “The result was so mind-boggling and so robust, it took a while for the idea to sink in, but we knew we needed to work out a way of trying out the same thing in humans,” Tsai says.

Scientists identified the waves of electrical activity that constantly ripple through the brain almost 100 years ago, but they have struggled to assign these oscillations a definitive role in behaviour or brain function. Studies have strongly linked brainwaves to memory consolidation during sleep, and implicated them in processing sensory inputs and even coordinating consciousness. Yet not everyone is convinced that brainwaves are all that meaningful. “Right now we really don’t know what they do,” says Michael Shadlen, a neuroscientist at Columbia University in New York City.

Now, a growing body of evidence, including Tsai’s findings, hint at a meaningful connection to neurological disorders such as Alzheimer’s and Parkinson’s diseases. The work offers the possibility of forestalling or even reversing the damage caused by such conditions without using a drug. More than two dozen clinical trials are aiming to modulate brainwaves in some way — some with flickering lights or rhythmic sounds, but most through the direct application of electrical currents to the brain or scalp. They aim to treat everything from insomnia to schizophrenia and premenstrual dysphoric disorder.

Tsai’s study was the first glimpse of a cellular response to brainwave manipulation. “Her results were a really big surprise,” says Walter Koroshetz, director of the US National Institute of Neurological Disorders and Stroke in Bethesda, Maryland. “It’s a novel observation that would be really interesting to pursue.”


A powerful wave

Brainwaves were first noticed by German psychiatrist Hans Berger. In 1929, he published a paper describing the repeating waves of current he observed when he placed electrodes on people’s scalps. It was the world’s first electroencephalogram (EEG) recording — but nobody took much notice. Berger was a controversial figure who had spent much of his career trying to identify the physiological basis of psychic phenomena. It was only after his colleagues began to confirm the results several years later that Berger’s invention was recognized as a window into brain activity.

Neurons communicate using electrical impulses created by the flow of ions into and out of each cell. Although a single firing neuron cannot be picked up through the electrodes of an EEG, when a group of neurons fires again and again in synchrony, it shows up as oscillating electrical ripples that sweep through the brain.

Those of the highest frequency are gamma waves, which range from 25 to 140 hertz. People often show a lot of this kind of activity when they are at peak concentration. At the other end of the scale are delta waves, which have the lowest frequency — around 0.5 to 4 hertz. These tend to occur in deep sleep (see ‘Rhythms of the mind’).

At any point in time, one type of brainwave tends to dominate, although other bands are always present to some extent. Scientists have long wondered what purpose, if any, this hum of activity serves, and some clues have emerged over the past three decades. For instance, in 1994, discoveries in mice indicated that the distinct patterns of oscillatory activity during sleep mirrored those during a previous learning exercise. Scientists suggested that these waves could be helping to solidify memories.

Brainwaves also seem to influence conscious perception. Randolph Helfrich at the University of California, Berkeley, and his colleagues devised a way to enhance or reduce gamma oscillations of around 40 hertz using a non-invasive technique called transcranial alternating current stimulation (tACS). By tweaking these oscillations, they were able to influence whether a person perceived a video of moving dots as travelling vertically or horizontally.

The oscillations also provide a potential mechanism for how the brain creates a coherent experience from the chaotic symphony of stimuli hitting the senses at any one time, a puzzle known as the ‘binding problem’. By synchronizing the firing rates of neurons responding to the same event, brainwaves might ensure that the all of the relevant information relating to one object arrives at the correct area of the brain at exactly the right time. Coordinating these signals is the key to perception, says Robert Knight, a cognitive neuroscientist at the University of California, Berkeley, “You can’t just pray that they will self-organize.”


Healthy oscillations

But these oscillations can become disrupted in certain disorders. In Parkinson’s disease, for example, the brain generally starts to show an increase in beta waves in the motor regions as body movement becomes impaired. In a healthy brain, beta waves are suppressed just before a body movement. But in Parkinson’s disease, neurons seem to get stuck in a synchronized pattern of activity. This leads to rigidity and movement difficulties. Peter Brown, who studies Parkinson’s disease at the University of Oxford, UK, says that current treatments for the symptoms of the disease — deep-brain stimulation and the drug levodopa — might work by reducing beta waves.

People with Alzheimer’s disease show a reduction in gamma oscillations5. So Tsai and others wondered whether gamma-wave activity could be restored, and whether this would have any effect on the disease.

They started by using optogenetics, in which brain cells are engineered to respond directly to a flash of light. In 2009, Tsai’s team, in collaboration with Christopher Moore, also at MIT at the time, demonstrated for the first time that it is possible to use the technique to drive gamma oscillations in a specific part of the mouse brain6.

Tsai and her colleagues subsequently found that tinkering with the oscillations sets in motion a host of biological events. It initiates changes in gene expression that cause microglia — immune cells in the brain — to change shape. The cells essentially go into scavenger mode, enabling them to better dispose of harmful clutter in the brain, such as amyloid-β. Koroshetz says that the link to neuroimmunity is new and striking. “The role of immune cells like microglia in the brain is incredibly important and poorly understood, and is one of the hottest areas for research now,” he says.

If the technique was to have any therapeutic relevance, however, Tsai and her colleagues had to find a less-invasive way of manipulating brainwaves. Flashing lights at specific frequencies has been shown to influence oscillations in some parts of the brain, so the researchers turned to strobe lights. They started by exposing young mice with a propensity for amyloid build-up to flickering LED lights for one hour. This created a drop in free-floating amyloid, but it was temporary, lasting less than 24 hours, and restricted to the visual cortex.

To achieve a longer-lasting effect on animals with amyloid plaques, they repeated the experiment for an hour a day over the course of a week, this time using older mice in which plaques had begun to form. Twenty-four hours after the end of the experiment, these animals showed a 67% reduction in plaque in the visual cortex compared with controls. The team also found that the technique reduced tau protein, another hallmark of Alzheimer’s disease.

Alzheimer’s plaques tend to have their earliest negative impacts on the hippocampus, however, not the visual cortex. To elicit oscillations where they are needed, Tsai and her colleagues are investigating other techniques. Playing rodents a 40-hertz noise, for example, seems to cause a decrease in amyloid in the hippocampus — perhaps because the hippo-campus sits closer to the auditory cortex than to the visual cortex.

Tsai and her colleague Ed Boyden, a neuro-scientist at MIT, have now formed a company, Cognito Therapeutics in Cambridge, to test similar treatments in humans. Last year, they started a safety trial, which involves testing a flickering light device, worn like a pair of glasses, on 12 people with Alzheimer’s.

Caveats abound. The mouse model of Alzheimer’s disease is not a perfect reflection of the disorder, and many therapies that have shown promise in rodents have failed in humans. “I used to tell people — if you’re going to get Alzheimer’s, first become a mouse,” says Thomas Insel, a neuroscientist and psychiatrist who led the US National Institute of Mental Health in Bethesda, Maryland, from 2002 until 2015.

Others are also looking to test how manipulating brainwaves might help people with Alzheimer’s disease. “We thought Tsai’s study was outstanding,” says Emiliano Santarnecchi at Harvard Medical School in Boston, Massachusetts. His team had already been using tACS to stimulate the brain, and he wondered whether it might elicit stronger effects than a flashing strobe. “This kind of stimulation can target areas of the brain more specifically than sensory stimulation can — after seeing Tsai’s results, it was a no-brainer that we should try it in Alzheimer’s patients.”

His team has begun an early clinical trial in which ten people with Alzheimer’s disease receive tACS for one hour daily for two weeks. A second trial, in collaboration with Boyden and Tsai, will look for signals of activated microglia and levels of tau protein. Results are expected from both trials by the end of the year.

Knight says that Tsai’s animal studies clearly show that oscillations have an effect on cellular metabolism — but whether the same effect will be seen in humans is another matter. “In the end, it’s data that will win out,” he says.

The studies may reveal risks, too. Gamma oscillations are the type most likely to induce seizures in people with photosensitive epilepsy, says Dora Hermes, a neuroscientist at Stanford University in California. She recalls a famous episode of a Japanese cartoon that featured flickering red and blue lights, which induced seizures in some viewers. “So many people watched that episode that there were almost 700 extra visits to the emergency department that day.”

A brain boost

Nevertheless, there is clearly a growing excitement around treating neurological diseases using neuromodulation, rather than pharmaceuticals. “There’s pretty good evidence that by changing neural-circuit activity we can get improvements in Parkinson’s, chronic pain, obsessive–compulsive disorder and depression,” says Insel. This is important, he says, because so far, pharmaceutical treatments for neurological disease have suffered from a lack of specificity. Koroshetz adds that funding institutes are eager for treatments that are innovative, non-invasive and quickly translatable to people.

Since publishing their mouse paper, Boyden says, he has had a deluge of requests from researchers wanting to use the same technique to treat other conditions. But there are a lot of details to work out. “We need to figure out what is the most effective, non-invasive way of manipulating oscillations in different parts of the brain,” he says. “Perhaps it is using light, but maybe it’s a smart pillow or a headband that could target these oscillations using electricity or sound.” One of the simplest methods that scientists have found is neurofeedback, which has shown some success in treating a range of conditions, including anxiety, depression and attention-deficit hyperactivity disorder. People who use this technique are taught to control their brainwaves by measuring them with an EEG and getting feedback in the form of visual or audio cues.

Phyllis Zee, a neurologist at Northwestern University in Chicago, Illinois, and her colleagues delivered pulses of ‘pink noise’ — audio frequencies that together sound a bit like a waterfall — to healthy older adults while they slept. They were particularly interested in eliciting the delta oscillations that characterize deep sleep. This aspect of sleep decreases with age, and is associated with a decreased ability to consolidate memories.

So far, her team has found that stimulation increased the amplitude of the slow waves, and was associated with a 25–30% improvement in recall of word pairs learnt the night before, compared with a fake treatment7. Her team is midway through a clinical trial to see whether longer-term acoustic stimulation might help people with mild cognitive impairment.

Although relatively safe, these kinds of technologies do have limitations. Neurofeedback is easy to learn, for instance, but it can take time to have an effect, and the results are often short-lived. In experiments that use magnetic or acoustic stimulation, it is difficult to know precisely what area of the brain is being affected. “The field of external brain stimulation is a little weak at the moment,” says Knight. Many approaches, he says, are open loop, meaning that they don’t track the effect of the modulation using an EEG. Closed loop, he says, would be more practical. Some experiments, such as Zee’s and those involving neuro-feedback, already do this. “I think the field is turning a corner,” Knight says. “It’s attracting some serious research.”

In addition to potentially leading to treatments, these studies could break open the field of neural oscillations in general, helping to link them more firmly to behaviour and how the brain works as a whole.

Shadlen says he is open to the idea that oscillations play a part in human behaviour and consciousness. But for now, he remains unconvinced that they are directly responsible for these phenomena — referring to the many roles people ascribe to them as “magical incantations”. He says he fully accepts that these brain rhythms are signatures of important brain processes, “but to posit the idea that synchronous spikes of activity are meaningful, that by suddenly wiggling inputs at a specific frequency, it suddenly elevates activity onto our conscious awareness? That requires more explanation.”

Whatever their role, Tsai mostly wants to discipline brainwaves and harness them against disease. Cognito Therapeutics has just received approval for a second, larger trial, which will look at whether the therapy has any effect on Alzheimer’s disease symptoms. Meanwhile, Tsai’s team is focusing on understanding more about the downstream biological effects and how to better target the hippocampus with non-invasive technologies.

For Tsai, the work is personal. Her grandmother, who raised her, was affected by dementia. “Her confused face made a deep imprint in my mind,” Tsai says. “This is the biggest challenge of our lifetime, and I will give it all I have.”

https://www.nature.com/articles/d41586-018-02391-6

Anxiety may be an early indicator of Alzheimer’s disease

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lzheimer’s disease is a neurodegenerative condition that causes the decline of cognitive function and the inability to carry out daily life activities. Past studies have suggested depression and other neuropsychiatric symptoms may be predictors of AD’s progression during its “preclinical” phase, during which time brain deposits of fibrillar amyloid and pathological tau accumulate in a patient’s brain. This phase can occur more than a decade before a patient’s onset of mild cognitive impairment. Investigators at Brigham and Women’s Hospital examined the association of brain amyloid beta and longitudinal measures of depression and depressive symptoms in cognitively normal, older adults. Their findings, published today by The American Journal of Psychiatry, suggest that higher levels of amyloid beta may be associated with increasing symptoms of anxiety in these individuals. These results support the theory that neuropsychiatric symptoms could be an early indicator of AD.

“Rather than just looking at depression as a total score, we looked at specific symptoms such as anxiety. When compared to other symptoms of depression such as sadness or loss of interest, anxiety symptoms increased over time in those with higher amyloid beta levels in the brain,” said first author Nancy Donovan, MD, a geriatric psychiatrist at Brigham and Women’s Hospital. “This suggests that anxiety symptoms could be a manifestation of Alzheimer’s disease prior to the onset of cognitive impairment. If further research substantiates anxiety as an early indicator, it would be important for not only identifying people early on with the disease, but also, treating it and potentially slowing or preventing the disease process early on.” As anxiety is common in older people, rising anxiety symptoms may prove to be most useful as a risk marker in older adults with other genetic, biological or clinical indicators of high AD risk.

Researchers derived data from the Harvard Aging Brain Study, an observational study of older adult volunteers aimed at defining neurobiological and clinical changes in early Alzheimer’s disease. The participants included 270 community dwelling, cognitively normal men and women, between 62 and 90 years old, with no active psychiatric disorders. Individuals also underwent baseline imaging scans commonly used in studies of Alzheimer’s disease, and annual assessments with the 30-item Geriatric Depression Scale (GDS), an assessment used to detect depression in older adults.

The team calculated total GDS scores as well as scores for three clusters symptoms of depression: apathy-anhedonia, dysphoria, and anxiety. These scores were looked at over a span of five years.

From their research, the team found that higher brain amyloid beta burden was associated with increasing anxiety symptoms over time in cognitively normal older adults. The results suggest that worsening anxious-depressive symptoms may be an early predictor of elevated amyloid beta levels – and, in turn AD — and provide support for the hypothesis that emerging neuropsychiatric symptoms represent an early manifestation of preclinical Alzheimer’s disease.

Donovan notes further longitudinal follow-up is needed to determine whether these escalating depressive symptoms give rise to clinical depression and dementia stages of Alzheimer’s disease over time.

Paper cited: Donovan et al. “Longitudinal Association of Amyloid Beta and Anxious-Depressive Symptoms in Cognitively Normal Older Adults” The American Journal of Psychiatry DOI: 10.1176/appi.ajp.2017.17040442

Examining the eye to spot early signs of Alzheimer’s disease

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Last year, doctors of optometry detected more than 320,000 cases of diabetes. Imagine if they could make the same impact when it comes to exposing early signs of Alzheimer’s disease.

November is National Alzheimer’s Disease Awareness Month. An estimated 5.4 million Americans are affected by Alzheimer’s disease, according to the Centers for Disease Control and Prevention (CDC). Projections put the number at 13.8 million by 2050.

Maryke Nijhuis Neiberg, O.D., associate professor in the School of Optometry at Massachusetts College of Pharmacy and Heath Sciences, in Worcester, Massachusetts, considers this an unrealized patient education opportunity for doctors of optometry.

“The earlier diagnoses give doctors and patients a better chance at managing the progressive brain disease and preserving the patient’s quality of life,” Dr. Neiberg says. “There has been some increase in Alzheimer’s awareness over the years, particularly in the eye community, but not enough yet.

“Alzheimer’s is a significant future public health issue,” she adds. “It is still a terminal disease.”

Early intervention

Much of the research on Alzheimer’s disease seeks to slow the disease’s progression. For instance, a study in Biological Psychiatry on Nov. 6 by researchers at the University of Iowa and the University of Texas Southwestern Medical Center in Dallas reports that there may be a new treatment that can slow the depression and cognitive decline associated with Alzheimer’s disease, without affecting amyloid plaque deposits or reactive glia in rats.

Among the early signs of Alzheimer’s, the researchers say, are anxiety, depression and irritability-long before the devastating effects of memory loss.

“Thus, P7C3 compounds may form the basis for a new class of neuroprotective drugs for mitigating the symptoms in patients with Alzheimer’s disease by preserving neuronal cell survival, irrespective of other pathological events,” researchers say. “P7C3 compounds represent a novel route to treating depression, and new-onset depression in elderly patients may herald the development of Alzheimer’s disease with later cognitive impairments to follow.”

Another study in JAMA Ophthalmology in September by researchers at Stanford University and Veterans Affairs Palo Alto Health Care System linked visual impairment and cognition in older adults and also stressed the “potential importance” of vision screening in identifying these patients’ eye disease and cognitive deficits. The AOA strongly recommends comprehensive eye examinations and stresses the limitations of screenings.

Optometry’s role

According to the CDC:

The rate of Alzheimer’s jumped 50 percent between 1999 and 2014.

Americans fear losing their mental capacity more than losing their physical abilities.

More than $230 billion is estimated to be spent in 2017 on providing health care, long-term care, hospice plus unpaid care for relatives with Alzheimer’s and other dementias.

More large-scale research on Alzheimer’s needs to be done, but progress is being made. Dr. Neiberg pointed to research linking optical coherence tomography (OCT) of the macula to Alzheimer’s and Parkinson’s diseases.

“With the advent of OCT, we now know that the retinal ganglion cell layer thins and that the optic nerve cup-to-disc ratio increases in size, not unlike glaucoma,” Dr. Neiberg says. “Alzheimer’s produces visual field defects that are easily confused with glaucoma. What we need is large-scale research to determine how much of the normal tension glaucoma we diagnose and treat is ultimately related to Alzheimer’s disease.”

She adds, “The early perceptual changes that occur in early Alzheimer’s are startling and measurable. One of the earliest signs is a decline in the Benton Visual Retention Test, a test of visual memory. This test requires the duplication of shapes on paper with a pencil, and is scored.

“Research has shown that this test is able to predict high risk for Alzheimer’s 15 years before diagnosis,” she says. “It’s a simple test many developmental and pediatric optometrists already have on their shelves. If we combine that test and the ocular findings we see, we have a very strong indication that something is indeed amiss. Armed with this information, the patient can then consult with their primary care physician, initiate lifestyle modification and request a referral if necessary.”

There is no cure for Alzheimer’s disease. But doctors of optometry can engage patients in conversation about Alzheimer’s disease and how they can manage their own risk factors, including:

Smoking
Mid-life obesity
Sedentary lifestyle
High-cholesterol diet|
Vascular disease (i.e., diabetes and hypertension)

“Lifestyle modification and early access to medication, which can delay the progression of dementia, might be enough to keep the disease at bay for longer,” Dr. Neiberg says. “We should include the Alzheimer’s disease connection when we educate our patients about lifestyle diseases.”

https://finchannel.com/society/health-beauty/69483-doctors-of-optometry-can-spot-early-signs-of-alzheimer-s-disease

n Alzheimer’s, Excess Tau Protein Damages Brain’s GPS and may be responsible for wandering

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Grid cell from the entorhinal cortex (EC) of the mouse brain, firing repeatedly and uniformly in a grid-like pattern. When a mouse moves through its environment, grid cells are activated, with each cell representing a specific location. This creates a triangular coordinate system that allows for spatial navigation. The accumulation of tau protein in the brain of a mouse model of Alzheimer’s disease was shown to disrupt the function of grid cells, causing problems with navigation. The findings explain why Alzheimer’s patients tend to wander and get lost. Source: Lab of Karen Duff, PhD, Columbia University Medical Center

Columbia University Medical Center (CUMC) researchers have discovered that the spatial disorientation that leads to wandering in many Alzheimer’s disease patients is caused by the accumulation of tau protein in navigational nerve cells in the brain. The findings, in mice, could lead to early diagnostic tests for Alzheimer’s and highlight novel targets for treating this common and troubling symptom.

The study was published online today in the journal Neuron.

An estimated three out of five people with Alzheimer’s disease wander and get lost, usually beginning in the early stages of the disease, leaving them vulnerable to injury. Researchers suspect that these problems originate in an area of the brain known as the entorhinal cortex (EC). The EC plays a key role in memory and navigation and is among the first brain structures affected by the buildup of neurofibrillary tangles that are largely composed of tau, a hallmark of Alzheimer’s disease. “Until now, no one has been able to show how tau pathology might lead to navigational difficulties,” said co-study leader Karen E. Duff, PhD, professor of pathology & cell biology (in psychiatry and in the Taub Institute for Research on Alzheimer’s Disease and the Aging Brain) at Columbia.

Dr. Duff and her colleagues focused their investigations on excitatory grid cells, a type of nerve cell in the EC that fires in response to movement through space, creating a grid-like internal map of a person’s environment. The researchers made electrophysiological recordings of the grid cells of older mice—including mice engineered to express tau in the EC (EC-tau mice) and normal controls—as they navigated different environments. Spatial cognitive tasks revealed that the EC-tau mice performed significantly worse compared to the controls, suggesting that tau alters grid cell function and contributes to spatial learning and memory deficits, according to co-study leader Abid Hussaini, PhD, assistant professor of neurobiology (in pathology & cell biology and the Taub Institute).

Detailed histopathological analysis of the mouse brains revealed that only the excitatory cells, but not the inhibitory cells, were killed or compromised by pathological tau, which probably resulted in the grid cells firing less. “It appears that tau pathology spared the inhibitory cells, disturbing the balance between excitatory and inhibitory cells and misaligning the animals’ grid fields,” said co-first author Hongjun Fu, PhD, associate research scientist in the Taub Institute, who led the immunohistological and behavior studies.

“This study clearly shows that tau pathology, beginning in the entorhinal cortex, can lead to deficits in grid cell firing and underlies the deterioration of spatial cognition that we see in human Alzheimer’s disease,” said Eric Kandel, MD, Nobel laureate, University Professor, and Kavli Professor of Brain Science at Columbia. “This is a classic advance in our understanding of the early stages of Alzheimer’s disease.”

“This study is the first to show a link between grid cells and Alzheimer’s disease,” said Edvard E. Moser, Nobel laureate and head of the Kavli Institute for Systems Neuroscience at Norwegian University of Science and Technology. “These findings will be crucial for future attempts to understand the development of early Alzheimer’s disease symptoms, including the tendency to wander and get lost.”

The findings raise the possibility that spatial disorientation could be treated by correcting this imbalance through transcranial stimulation, deep-brain stimulation, or light-based therapy.

“We have a lot to learn about grid cells and how they are affected by Alzheimer’s disease,” said Gustavo A. Rodriguez, PhD, a postdoctoral research scientist in the Taub Institute and a co-author of the paper. “We don’t yet know what percentage of healthy grid cells are needed for proper navigation or whether this system is rescuable once it has been compromised.”

“In the meantime,” said Dr. Duff, “our findings suggest that it may be possible to develop navigation-based cognitive tests for diagnosing Alzheimer’s disease in its initial stages. And if we can diagnose the disease early, we can start to give therapeutics earlier, when they may have a greater impact.”

The study is titled, “Tau Pathology Induces Excitatory Neuron Loss, Grid Cell Dysfunction and Spatial Memory Deficits Reminiscent of Early Alzheimer’s Disease.” The other contributors are Mathieu Herman, Sheina Emrani, Eden Nahmani, Geoffrey Barrett, Helen Y. Figueroa, and Eliana Goldberg.

The study was supported by grants from National Institutes of Health (R01NS074874 and R01AG050425) and the Alzheimer’s Association (2015-NIRG-341570).

http://newsroom.cumc.columbia.edu/blog/2017/01/19/in-alzheimers-excess-tau-protein-damages-brains-gps/

Having a socially interactive job helps protect from Alzheimer’s disease.

On By A.P.In Alzheimer's disease, brainLeave a comment

By Patrick Foster

Lawyers, teachers and doctors have a better chance of fighting off the effects of Alzheimer’s disease, because of the complex nature of their jobs, scientists reported this week.

Researchers found that people whose jobs combined complex thinking with social engagement with others – such as social workers and engineers – were better protected against the onset of Alzheimer’s, compared to those in manual work.

The study came as another report suggested that people with a poor diet could protect themselves against cognitive decline by adopting a mentally stimulating lifestyle.

Both pieces of research, published at the international conference of the Alzheimer’s Association, in Toronto, examined the impact of complex thinking on the onset of the disease.

In the first study, carried out by scientists at the Alzheimer’s Disease Research Centre, in Wisconsin, researchers examined white matter hyperintensities (WMHs) – white spots that appear on brain scans and are associated with Alzheimer’s – in 284 late-middle-aged patients considered at risk of contracting the disease.

They found that people who worked primarily with other people, as opposed to with “things or data”, were less likely to be affected by brain damage indicated by WMHs.

While lawyers, social workers, teachers and doctors were best protected, those who enjoyed the least protection included shelf-stackers, machine operators and labourers.

Elizabeth Boots, a researcher on the project, said: “These findings indicate that participants with higher occupational complexity are able to withstand pathology associated with Alzheimer’s and cerebrovascular disease and perform at a similar cognitive level as their peers.

“This association is primarily driven by work with people, rather than data or things. These analyses underscore the importance of social engagement in the work setting for building resilience to Alzheimer’s disease.”

The second study, carried out by Baycrest Health Sciences, in Toronto, examined the diet of 351 older adults.

Researchers found that those who had a traditional Western diet of red and processed meat, white bread, potatoes and sweets were more likely to experience cognitive decline.

However, those who adhered to such a diet but who had a mentally stimulating lifestyle enjoyed some protection from such decline.

Dr Matthew Parrott, one member of the team, said: “Our results show the role higher educational attainment, mentally stimulating work and social engagement can play in protecting your brain from cognitive decline, counteracting some negative effects of an unhealthy diet.

“This adds to the growing body of evidence showing how various lifestyle factors may combine to increase or protect against vulnerability to Alzheimer’s disease.”

Other research put forward at the convention included a study showing that digital brain training exercises can help stave of Alzheimer’s, and another paper that suggested that some newly-identified genes may also increase resilience to the disease.

Maria C. Carrillo, the chief science officer at the Alzheimer’s Association, said: “These new data add to a growing body of research that suggests more stimulating lifestyles, including more complex work environments with other people, are associated with better cognitive outcomes in later life.

“As each new study emerges, we further understand just how powerful cognitive reserve can be in protecting the brain from disease. Formal education and complex occupation could potentially do more than just slow cognitive decline – they may actually help compensate for the cognitive damage done by bad diet and small vessel disease in the brain.

“It is becoming increasingly clear that in addition to searching for pharmacological treatments, we need to address lifestyle factors to better treat and ultimately prevent Alzheimer’s and other dementias.”

http://www.telegraph.co.uk/news/2016/07/24/stressful-job-it-might-help-you-fight-off-alzheimers/

New treatment protocol shows promise of improving cognition in patients with Alzheimer’s disease

On By A.P.In Alzheimer's disease, DementiaLeave a comment

Ten patients with early Alzheimer’s disease or its precursors showed improvement in memory after treatment with Metabolic Enhancement for NeuroDegeneration (MEND), a programmatic and personalized therapy protocol.

Researchers described results from the small trial, which used quantitative MRI and neuropsychological testing of participants before and after treatment, in the study published online in Aging.

“ The magnitude of the improvement is unprecedented,” researchers wrote, “providing additional objective evidence that this programmatic approach to cognitive decline is highly effective.”

Before starting the program, the 10 participants had well-defined mild cognitive impairment, subjective cognitive impairment, or had been diagnosed with Alzheimer’s disease. Their subsequent treatment consisted of a complex, 36-point therapeutic personalized program that included comprehensive changes in diet, brain stimulation, exercise, optimization of sleep, specific pharmaceuticals and vitamins, and multiple additional steps that affect brain chemistry.

Researcher Dale Bredesen, MD, a professor at the Buck Institute for Research on Aging and at the Easton Laboratories for Neurodegenerative Disease Research at UCLA, Los Angeles, believes the protocol’s broader-based approach is key to its apparent success in reversing cognitive decline.

“Imagine having a roof with 36 holes in it, and your drug patched one hole very well — the drug may have worked, a single ‘hole’ may have been fixed, but you still have 35 other leaks, and so the underlying process may not be affected much,” Dr. Bredesen said. “We think addressing multiple targets within the molecular network may be additive, or even synergistic, and that such a combinatorial approach may enhance drug candidate performance as well.”

Tests showed some participants “going from abnormal to normal,” Dr. Bredesen said.

In Aging , researchers describe the impact of MEND on all 10 patients, including:
•A 66-year-old man whose neuropsychological testing was compatible with a diagnosis of mild cognitive impairment. After 10 months on the MEND protocol, his hippocampal volume increased from the 17 th percentile for his age to the 75 th percentile, with an associated absolute increase in volume of nearly 12%.
•A 69-year-old entrepreneur with 11 years of progressive memory loss. After 22 months on the protocol, he showed marked improvements in all categories of neuropsychological testing, with long-term recall increasing from the 3 rd to 84 th percentile.
•A 49-year-old woman in the early stages of cognitive decline who, after 9 months on the protocol, no longer showed evidence on quantitative neuropsychological testing of cognitive decline.

Plans for larger studies are under way.

“Even though we see the far-reaching implications of this success,” Dr. Bredesen said, “we also realize that this is a very small study that needs to be replicated in larger numbers at various sites.”

http://www.psychcongress.com/article/mend-protocol-reverses-memory-loss-alzheimer%E2%80%99s-disease-27858