The study, “Lipids uniquely alter the secondary structure and toxicity of amyloid beta 1-42 aggregates,” by Dmitry Kurouski, Ph.D., and research assistants Kiryl Zhaliazka and Mikhail Matyeyenka, was supported by a $1.5 million Maximizing Investigators’ Research Award from the National Institutes of Health. It was published in FEBS Journal — the journal of the Federation of European Biochemical Societies.
“The study found that certain lipids can increase the toxicity of amyloid beta peptides, which are thought to play a role in the development of Alzheimer’s disease,” said Kurouski, an assistant professor and primary investigator for the study, Bryan-College Station. “Specifically, we discovered that the interaction between amyloid beta and lipids can cause the formation of small, toxic clusters called oligomers.”
Researchers have discovered how a molecule found in green tea breaks apart tangles of the protein tau, a hallmark of Alzheimer’s disease. Based on this finding, the team identified other molecules that can also untangle tau and may be better drug candidates than the green tea molecule. Results from the NIA-funded study, published in Nature Communications, suggest that this approach may one day provide an effective strategy for treating Alzheimer’s.
In Alzheimer’s, tau abnormally sticks together in fibrous tangles that spread between brain cells, leading to cell death. The molecule epigallocatechin gallate (EGCG) — the one found in green tea — is known to untangle these tau fibers. However, EGCG is not on its own an effective Alzheimer’s treatment because it cannot easily penetrate the brain and binds to many proteins other than tau, weakening its effect. Therefore, researchers wanted to find molecules that replicate the effects of EGCG but have better drug properties for treating Alzheimer’s.
New electrical method triggers and analyzes dynamics of brain protein that underlie many neurodegenerative diseases
Scientists are not yet clear on how the tau protein changes from a benign protein essential for normal function in our brains into the toxic neurofibrillary tangles that are a signature of Alzheimer’s and other neurodegenerative diseases.
But a new method developed by researchers at UC Santa Barbara gives the ability to control and follow in real time the process by which it happens. The technique employs a novel use of low voltage electricity as a surrogate for the natural signals that trigger the protein to fold and assemble, both for its normal function in the brain and in the runaway process leading to often fatal disease.
“This method provides scientists a new means to trigger and simultaneously observe the dynamic changes in the protein as it transitions from good to bad,” said Daniel E. Morse, Distinguished Professor Emeritus of Biochemistry and Molecular Genetics, and senior author of a paper that appears in the Journal of Biological Chemistry.
“The method should be widely useful to identify molecules and conditions that direct different trajectories of assembly in a number of different but related amyloid diseases,” stated Eloise Masqulier, lead author of the interdisciplinary team of students, researchers and faculty from molecular biology, chemistry and engineering including Esther Taxon, Sheng-Ping Liang, Yahya Al Sabeh, Lior Sepunaru and Michael J. Gordon.
New research from the Institute of Psychiatry, Psychology & Neuroscience (IoPPN) at King’s College London has established a blood-based test that could be used to predict the risk of Alzheimer’s disease up to 3.5 years before clinical diagnosis.
The study, published in the journal Brain, supports the idea that components in the human blood can modulate the formation of new brain cells, a process termed neurogenesis. Neurogenesis occurs in an important part of the brain called the hippocampus that is involved in learning and memory.
While Alzheimer’s disease affects the formation of new brain cells in the hippocampus during the early stages of the disease, previous studies have only been able to study neurogenesis in its later stages through autopsies.
To understand the early changes, researchers collected blood samples over several years from 56 individuals with Mild Cognitive Impairment (MCI), a condition where someone will begin to experience a worsening of their memory or cognitive ability. While not everyone experiencing MCI goes on to develop Alzheimer’s disease, those with the condition progress to a diagnosis at a much higher rate than the wider population. Of the 56 participants in the study, 36 went on to receive a diagnosis of Alzheimer’s disease.
The sport of orienteering, which draws on athleticism, navigational skills and memory, could be useful as an intervention or preventive measure to fight cognitive decline related to dementia, according to new research from McMaster University.
Researchers hypothesized that the physical and cognitive demands of orienteering, which integrates exercise with navigation, may stimulate parts of the brain that our ancient ancestors used for hunting and gathering. The brain evolved thousands of years ago to adapt to the harsh environment by creating new neural pathways.
Those same brain functions are not as necessary for survival today due to modern conveniences such as GPS apps and readily available food. Researchers suggest it is a case of “use it or lose it.”
“Modern life may lack the specific cognitive and physical challenges the brain needs to thrive,” says Jennifer Heisz, Canada Research Chair in Brain Health and Aging at McMaster University, who supervised the research. “In the absence of active navigation, we risk losing that neural architecture.”
Heisz points to Alzheimer’s disease, in which losing the ability to find one’s way is among the earliest symptoms, affecting half of all afflicted individuals, even in the mildest stage of the disease.
In the study, published in the journal PLoS ONE, researchers surveyed healthy adults, ranging in age from 18 to 87 with varying degrees of orienteering expertise (none, intermediate, advanced and elite).
The U.S. Food and Drug Administration (FDA) recently granted approval to Lecanemab, the first Alzheimer’s disease treatment to win approval since the largely failed rollout of Aduhelm two years ago. Sold under the brand name Leqembi, the new drug shows promise, but experts say making the treatment available to patients at academic medical centers like Cedars-Sinai will take time.
“The clinical data on Leqembi is solid and shows moderately less decline for those participants who received the drug compared to those who did not in the Phase III study,” said Sarah Kremen, MD, who leads the Alzheimer’s Disease Clinical Trial Program at Cedars-Sinai. “But before making this treatment available to patients, we have to take steps to ensure that we’re giving the drug as safely as possible to patients who will face the least risk and receive the greatest benefit—a critical process that takes time.”
What did clinical trials show about Leqembi’s benefits?
The data showed that the treatment can pull amyloid—a protein that forms plaques and disrupts brain function—out of the brain in a significant way. Patients receiving Leqembi during clinical trials also showed slowing in decline on tests of memory and functional ability. Leqembi also seems to decrease accumulation of tau protein, which forms tangles inside neurons of Alzheimer’s patients, particularly in the memory centers of the brain. It’s important to recognize that while these results are exciting, this medication does not reverse cognitive decline, it only slows it down.
The human brain holds many clues about a person’s long-term health — in fact, research shows that a person’s brain age is a more useful and accurate predictor of health risks and future disease than their birth date. Now, a new artificial intelligence (AI) model that analyzes magnetic resonance imaging (MRI) brain scans developed by USC researchers could be used to accurately capture cognitive decline linked to neurodegenerative diseases like Alzheimer’s much earlier than previous methods.
Brain aging is considered a reliable biomarker for neurodegenerative disease risk. Such risk increases when a person’s brain exhibits features that appear “older” than expected for someone of that person’s age. By tapping into the deep learning capability of the team’s novel AI model to analyze the scans, the researchers can detect subtle brain anatomy markers that are otherwise very difficult to detect and that correlate with cognitive decline. Their findings, published on Tuesday, January 2, in the journal Proceedings of the National Academy of Sciences, offer an unprecedented glimpse into human cognition.
“Our study harnesses the power of deep learning to identify areas of the brain that are aging in ways that reflect a cognitive decline that may lead to Alzheimer’s,” said Andrei Irimia, assistant professor of gerontology, biomedical engineering, quantitative & computational biology and neuroscience at the USC Leonard Davis School of Gerontology and corresponding author of the study.
A growing pile of evidence indicates that the tens of trillions of microbes that normally live in our intestines — the so-called gut microbiome — have far-reaching effects on how our bodies function. Members of this microbial community produce vitamins, help us digest food, prevent the overgrowth of harmful bacteria and regulate the immune system, among other benefits. Now, a new study suggests that the gut microbiome also plays a key role in the health of our brains, according to researchers from Washington University School of Medicine in St. Louis.
The study, in mice, found that gut bacteria — partly by producing compounds such as short chain fatty acids — affect the behavior of immune cells throughout the body, including ones in the brain that can damage brain tissue and exacerbate neurodegeneration in conditions such as Alzheimer’s disease. The findings, published Jan. 13 in the journal Science, open up the possibility of reshaping the gut microbiome as a way to prevent or treat neurodegeneration.
“We gave young mice antibiotics for just a week, and we saw a permanent change in their gut microbiomes, their immune responses, and how much neurodegeneration related to a protein called tau they experienced with age,” said senior author David M. Holtzman, MD, the Barbara Burton and Reuben M. Morriss III Distinguished Professor of Neurology. “What’s exciting is that manipulating the gut microbiome could be a way to have an effect on the brain without putting anything directly into the brain.”
Evidence is accumulating that the gut microbiomes in people with Alzheimer’s disease can differ from those of healthy people. But it isn’t clear whether these differences are the cause or the result of the disease — or both — and what effect altering the microbiome might have on the course of the disease.
Seasonal affective disorder (SAD) is a type of depression that comes and goes with the seasons. It usually starts in the late fall and early winter and goes away during the spring and summer. Some people do have episodes of depression that start in the spring or summer, but that is a lot less common. Symptoms of SAD may include:
Feeling hopeless, worthless, and irritable
Loss of interest or pleasure in activities you used to enjoy
SAD is more common in women, young people, and those who live far from the equator. You are also more likely to have SAD if you or your family members have depression.
The exact causes of SAD are unknown. Researchers have found that people with SAD may have an imbalance of serotonin, a brain chemical that affects your mood. Their bodies also make too much melatonin, a hormone that regulates sleep, and not enough vitamin D.
The main treatment for SAD is light therapy. The idea behind light therapy is to replace the sunshine that you miss during the fall and winter months. You sit in front of a light therapy box every morning to get daily exposure to bright, artificial light. But some people with SAD do not respond to light therapy alone. Antidepressant medicines and talk therapy can reduce SAD symptoms, either alone or combined with light therapy.
I want to add a note from personal experience to this discussion. I took care of my aunt who suffered and died from Alzheimer’s Disease for the last six years of her life. We had always been close and spoke nearly daily on the phone for the years prior to her being diagnosed with the disease One of the things we had discussed was her getting ‘depressed’ in the winter time when the days got short. As I was acquainted with SAD, I feared that she might suffer far more in the winter when it combined with her Alzheimer’s Disease. So, I bought some full spectrum lights for her apartment. These are used in light therapy and unlike regular lights which give a yellow glow, they broadcast the entire spectrum of light – replicating sunlight. So, my aunt was able to have the equivalent of summer daylight in her home during winter’s darkest hours. She never sank into a depression in the years I took care of her. So, light therapy can be effective.
A Cornell-led collaboration used machine learning to pinpoint the most accurate means, and timelines, for anticipating the advancement of Alzheimer’s disease in people who are either cognitively normal or experiencing mild cognitive impairment.
The modeling showed that predicting the future decline into dementia for individuals with mild cognitive impairment is easier and more accurate than it is for cognitively normal, or asymptomatic, individuals. At the same time, the researchers found that the predictions for cognitively normal subjects is less accurate for longer time horizons, but for individuals with mild cognitive impairment, the opposite is true.
The modeling also demonstrated that magnetic resonance imaging (MRI) is a useful prognostic tool for people in both stages, whereas tools that track molecular biomarkers, such as positron emission tomography (PET) scans, are more useful for people experiencing mild cognitive impairment.
Alzheimer’s disease can take years, sometimes decades, to progress before a person exhibits symptoms. Once diagnosed, some individuals decline rapidly but others can live with mild symptoms for years, which makes forecasting the rate of the disease’s advancement a challenge.
“When we can confidently say someone has dementia, it is too late. A lot of damage has already happened to the brain, and it’s irreversible damage,” said senior author Mert Sabuncu, associate professor of electrical and computer engineering in the College of Engineering and of electrical engineering in radiology at Weill Cornell Medicine.
“We really need to be able to catch Alzheimer’s disease early on,” Sabuncu said, “and be able to tell who’s going to progress fast and who’s going to progress slower, so that we can stratify the different risk groups and be able to deploy whatever treatment options we have.”
An estimated 6.2 million Americans ages 65 and older are living with Alzheimer’s disease. The national Alzheimer’s Association predicts that number to grow to 13.8 million by 2060, barring the development of medical breakthroughs that would prevent, slow or cure the debilitating disease.
Scientists may be one step closer to such a breakthrough thanks to a first-of-its-kind computer model that successfully simulated a clinical trial evaluating the efficacy of multiple treatments for Alzheimer’s disease (AD).
“We’re calling this a virtual clinical trial, because we used real, de-identified patient data to simulate health outcomes,” said Wenrui Hao, associate professor of mathematics at Penn State, who is lead author and principal investigator on the study published in the September issue of the journal PLoS Computational Biology. “What we found aligns almost exactly with findings in prior clinical trials, but because we were using a virtual simulation, we had the added benefit of directly comparing the efficacy of different drugs over longer trial periods.”
Using clinical and biomarker data, the researchers built a computational causal model to run virtual trials on the FDA-approved treatment aducanumab, as well as another promising therapy under evaluation, donanemab. The two drugs are some of the first treatments designed to work directly on what may cause the disease, instead of just treating the symptoms.
Most people are surprised to learn that early signs of serious medical conditions affecting your body can be detected in the eyes. Heart disease, diabetes, cancer, high blood pressure, multiple sclerosis, autoimmune diseases, sexually transmitted diseases, and even Alzheimer’s disease can be detected in the eye. That’s because the blood vessels and nerves in our eyes are reflective of the state of the rest of the body. A routine eye exam can do more than save your eyesight, it can also save your life.
Take for example Barbara Krupar, a 65-year-old retiree from Ohio who went to her ophthalmologist after experiencing some disturbing changes in her vision. When Nicole Bajic, MD, examined her, she detected possible early warning signs of a stroke, and recommended Barbara go to the emergency room immediately to have her head and neck imaged. The ER physician determined that the carotid artery in her neck was 85 percent blocked. She was at imminent risk of suffering a stroke. The exam likely saved her life.
New research from the University of Cincinnati bolsters a hypothesis that Alzheimer’s disease is caused by a decline in levels of a specific protein, contrary to a prevailing theory that has been recently called into question.
UC researchers led by Alberto Espay, MD, and Andrea Sturchio, MD, in collaboration with the Karolinska Institute in Sweden, published the research on Oct. 4 in the Journal of Alzheimer’s Disease.
Questioning the dominant hypothesis
The research is focused on a protein called amyloid-beta. The protein normally carries out its functions in the brain in a form that is soluble, meaning dissolvable in water, but it sometimes hardens into clumps, known as amyloid plaques.
People with dementia often lose their ability to communicate verbally with loved ones in later stages of the disease. But a Northwestern Medicine study, in collaboration with Institute for Therapy through the Arts (ITA), shows how that gap can be bridged with a new music intervention.
In the intervention — developed at ITA and called “Musical Bridges to Memory” — a live ensemble plays music from a patient’s youth such as songs from the musicals “Oklahoma” or “The Sound of Music.” This creates an emotional connection between a patient and their caregiver by allowing them to interact with the music together via singing, dancing and playing simple instruments, the study authors said.
The program also enhanced patients’ social engagement and reduced neuropsychiatric symptoms such as agitation, anxiety and depression in both patients and caregivers.
More than 6 million people in the U.S. have Alzheimer’s disease.
The study is unusual because it targeted patients with dementia and their caregivers, said lead study author Dr. Borna Bonakdarpour. Most prior studies using music for dementia patients have focused only on the patients.
The dementia disorder Alzheimer’s disease has a symptom-free course of 15 to 20 years before the first clinical symptoms emerge. Using an immuno-infrared sensor developed in Bochum, a research team is able to identify signs of Alzheimer’s disease in the blood up to 17 years before the first clinical symptoms appear. The sensor detects the misfolding of the protein biomarker amyloid-beta. As the disease progresses, this misfolding causes characteristic deposits in the brain, so-called plaques.
“Our goal is to determine the risk of developing Alzheimer’s dementia at a later stage with a simple blood test even before the toxic plaques can form in the brain, in order to ensure that a therapy can be initiated in time,” says Professor Klaus Gerwert, founding director of the Centre for Protein Diagnostics (PRODI) at Ruhr-Universität Bochum. His team cooperated for the study with a group at the German Cancer Research Centre in Heidelberg (DKFZ) headed by Professor Hermann Brenner.
The team published the results obtained with the immuno-infrared sensor in the journal “Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association” on 19 July 2022. This study is supported by a comparative study published in the same journal on 2 March 2022, in which the researchers used complementary single-molecule array (SIMOA) technology.
New research by Georgia State University’s TReNDS Center may lead to early diagnosis of devastating conditions such as Alzheimer’s disease, schizophrenia and autism—in time to help prevent and more easily treat these disorders. In a new study published in Scientific Reports a team of seven scientists from Georgia State built a sophisticated computer program that was able to comb through massive amounts of brain imaging data and discover novel patterns linked to mental health conditions. The brain imaging data came from scans using functional magnetic resonance imaging (fMRI), which measures dynamic brain activity by detecting tiny changes in blood flow.
“We built artificial intelligence models to interpret the large amounts of information from fMRI,” said Sergey Plis, associate professor of computer science and neuroscience at Georgia State, and lead author on the study.
He compared this kind of dynamic imaging to a movie—as opposed to a snapshot such as an x-ray or, the more common structural MRI—and noted “the available data is so much larger, so much richer than a blood test or a regular MRI. But that’s the challenge—that huge amount of data is hard to interpret.”