Tag Archives: Alzheimer’s risk

The ‘tipping point’ toward 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.

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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.

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What to Know About the Recently Approved Alzheimer’s Drug – Cedars-Sinai

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.”

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Kremen, director of the Neurobehavior Program in the Jona Goldrich Center for Alzheimer’s and Memory Disorders, sat down with the Cedars-Sinai Newsroom to explain the risks and benefits of Leqembi and what interested patients can expect that process to include.

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.

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AI-powered analysis accurately reflects risk of cognitive decline and Alzheimer’s disease based on brain age

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.

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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.

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Machine learning gives nuanced view of Alzheimer’s stages

 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.

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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.

The team’s paper, “Machine Learning Based Multi-Modal Prediction of Future Decline Toward Alzheimer’s Disease: An Empirical Study,” published Nov. 16 in PLOS ONE. The lead author is Batuhan Karaman, a doctoral student in the field of electrical and computer engineering.

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.”

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Two Alzheimer’s drugs tested head-to-head in first-ever virtual clinical trial

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).

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“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.

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Decreased proteins, not amyloid plaques, tied to Alzheimer’s disease – Study

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.

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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.

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SuperAger brains contain ‘super neurons’ – NW

·  SuperAger neurons are even larger than those in individuals 20 to 30 years younger
·  These neurons do not have tau tangles that are a hallmark of Alzheimer’s
·  Larger neurons in the brain’s memory region are a biological signature of SuperAging trajectory

Neurons in an area of the brain responsible for memory (known as the entorhinal cortex) were significantly larger in SuperAgers compared to cognitively average peers, individuals with early-stage Alzheimer’s disease and even individuals 20 to 30 years younger than SuperAgers — who are aged 80 years and older, reports a new Northwestern Medicine study.

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These neurons did not harbor tau tangles, a signature hallmark of Alzheimer’s disease.

“The remarkable observation that SuperAgers showed larger neurons than their younger peers may imply that large cells were present from birth and are maintained structurally throughout their lives,” said lead author Tamar Gefen, an assistant professor of psychiatry and behavioral sciences at Northwestern University Feinberg School of Medicine. “We conclude that larger neurons are a biological signature of the SuperAging trajectory.”  

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Alzheimer’s detection up to 17 years in advance

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.

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“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.

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Dynamic mental illness indicators caught by advanced AI in brain imaging

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.

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“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.”

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Loss of smell linked to Alzheimer’s cognitive impairment and biomarkers

Decline in sense of smell is connected to faster buildup of Alzheimer’s disease-related pathology seen in brain scans, according to new research focused on older adults who live outside of nursing homes. The findings provide additional evidence that loss of smell (known as anosmia) is a key early sign of Alzheimer’s-related cognitive impairment and the accumulation of associated harmful proteins, such as amyloid-beta and tau. The research, led by NIA scientists, was published in the Journal of Alzheimer’s Disease.

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Decline in sense of smell had previously been confirmed as an early warning sign for Alzheimer’s in both human and animal studies, but its connection to the uptick of dementia-related brain imaging biomarkers over time had not been as closely studied in larger populations of older adults. For this study, the team tracked 364 participants from the Baltimore Longitudinal Study of Aging (BLSA) over an average period of about 2.5 years. The NIA-led BLSA is the longest running study of healthy aging in America.

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Glucose Levels at Age 35 Associated with Alzheimer’s – BUSM

Living your best life at 35, ignoring cholesterol and glucose levels, may impact your chances of getting Alzheimer’s disease (AD) later in life. According to Boston University School of Medicine (BUSM) researchers, lower HDL (high-density cholesterol) and high triglyceride levels measured in blood as early as age 35 are associated with a higher incidence of AD several decades later in life. They also found that high blood glucose measured between ages 51-60 is associated with risk of AD in the future.

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“While our findings confirm other studies that linked cholesterol and glucose levels measured in blood with future risk of Alzheimer’s disease, we have shown for the first time that these associations extend much earlier in life than previously thought,” explains senior author Lindsay A. Farrer, PhD, chief of biomedical genetics.

The researchers believe that although high LDL has been consistently associated with AD risk in many previous studies, the link between HDL and AD was inconclusive, perhaps because most studies examining these relationships were conducted in persons who were 55 years and older at baseline. 

This study was conducted using data obtained from participants of the Framingham Heart Study who were examined in approximately four-year intervals throughout most of their adult lives. Correlations of AD with multiple known risk factors for cardiovascular disease and diabetes (including HDL, LDL, triglycerides, glucose, blood pressure, smoking, and body mass index) were measured at each exam and during three age periods during adulthood (35-50, 51-60, 61-70).

The researchers found that lower HDL (the good cholesterol) is predictive of AD in early (35-50 years) and middle (51-60 years) adulthood and that high glucose in the blood (a precursor of diabetes) during mid-adulthood is also predictive of AD “These findings show for the first time that cardiovascular risk factors, including HDL which has not been consistently reported as a strong risk factor for AD, contribute to future risk of AD starting as early as age 35,” says first and corresponding author Xiaoling Zhang, MD, PhD, assistant professor of medicine.

According to the researchers, careful management of these factors starting in early adulthood can lower one’s risk of cardiovascular disease and diabetes, as well as Alzheimer’s. “Intervention targeting cholesterol and glucose management starting in early adulthood can help maximize cognitive health in later life,” adds Farrer.

Farrer also points out, “the unique design and mission of the Framingham Heart Study, which is a multi-generation, community-based, prospective study of health that began in 1948, allowed us to link Alzheimer’s to risk factors for heart disease and diabetes measured much earlier in life than possible in most other studies of cognitive decline and dementia.”

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If a Family Member Has Alzheimer’s Disease, Will I Have It, Too? – NIH

If you are asking this question, I share your concern. My family has five cases of Alzheimer’s/dementia on both sides, including a grandparent, a parent, two aunts and a cousin.

Learning about your family health history may help you know if you are at increased risk for certain diseases or medical conditions, like Alzheimer’s disease.

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Blood test can predict presence of beta-amyloid in the brain

Scientists have demonstrated that a new blood test can accurately predict the presence of beta-amyloid plaques in the brain, according to a new study funded in part by NIA. Published in Neurology, the study analyzed the ability of a blood test to predict the presence of Alzheimer’s disease-associated protein beta-amyloid in the brain. The new blood test, which performs comparably to existing brain scan- or spinal tap-based tests, could lower costs and expand the availability of diagnostic studies for Alzheimer’s disease.

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Alzheimer’s is characterized by the buildup of a protein called beta-amyloid, which forms sticky plaques on the brain and can cause brain cells to die. Testing for the presence of these amyloid plaques on the brain is an important part of Alzheimer’s diagnosis and research. For people experiencing memory problems, checking for amyloid in the brain helps health care providers determine whether Alzheimer’s is the potential cause. It also can help doctors determine which patients will respond to drugs that target amyloid. For people without any signs of dementia, the presence of amyloid plaques on the brain may help researchers enroll participants in clinical trials for treatments to prevent or delay the onset of cognitive symptoms.

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Cataract surgery may lower dementia risk

  • An observational study of more than 3,000 adults aged 65 years or older has uncovered a link between cataract surgery and a reduced risk of developing dementia, including Alzheimer’s disease.
  • The researchers say the results support the connection between sensory impairments, such as vision loss, and a higher risk for dementia.
  • The scientists also believe there is a link between blue light and the development of dementia.

More than 55 million peopleTrusted Source worldwide live with dementia — a syndrome that causes a decline in cognitive functions such as memory, language, and comprehension.

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Alzheimer’s disease is the most common form of dementia, accounting for 60–80% of all people who have dementia. Scientists have carried out much research over the years examining the causes of Alzheimer’s; however, they remain unclear.

Researchers from the University of Washington School of Medicine in Seattle now say they have uncovered a link between cataract surgery and a lowered risk for developing dementia in older adults, including Alzheimer’s disease.

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Greater Exposure to Estrogen May Protect Women’s Brain Regions Vulnerable to Alzheimer’s

The drop in estrogen levels that occurs with menopause brings declines in the volumes of “gray matter,” the cellular matter of the brain, in key brain regions that are also affected in Alzheimer’s disease. But a new study from Weill Cornell Medicine researchers, in collaboration with the University of Arizona, suggests that greater cumulative exposure to estrogen in life, for example from having had more children or from having taken menopause hormone therapy, may counter this brain-shrinking effect.

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The findings, reported Nov. 3 in Neurology, come from an analysis of personal histories, MRI scans and cognitive tests on 99 women in their late 40s to late 50s. The researchers confirmed an earlier finding linking menopause to lower gray matter volume (GMV) in brain areas that are vulnerable to Alzheimer’s. But they also linked indicators of higher overall estrogen exposure, such as a longer span of reproductive years (menarche to menopause), more children and the use of menopause hormone therapy and hormonal contraceptives, to higher GMV in some of these brain areas.

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What Are the Signs and Symptoms of Alzheimer’s?

Memory problems are often one of the first signs of Alzheimer’s. Symptoms vary from person to person, and may include problems with:

  • Word-finding, or having more trouble coming up with words than other people the same age.
  • Vision and spatial issues, like awareness of the space around them.
  • Impaired reasoning or judgment, which can impact decisions.

Other symptoms may be changes in the person’s behavior, including:

  • Taking longer to complete normal daily tasks.
  • Repeating questions.
  • Trouble handling money and paying bills.
  • Wandering and getting lost.
  • Losing things or misplacing them in odd places.
  • Mood and personality changes.
  • Increased anxiety and/or aggression.

How Is Alzheimer’s Diagnosed and Treated?

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