Alzheimer’s dementia risk can be predicted using a new tool

Using demographic information, brain imaging test results and genetic biomarkers, researchers at Washington University School of Medicine in St. Louis have developed an algorithm that can help provide people who volunteer for studies on aging information on the risk everyone faces of developing dementia due to Alzheimer’s disease.

Published September 30 in the Journal of Alzheimer’s and Dementia, the findings – from researchers at the university Knight Alzheimer’s Research Center (Knight ADRC) – can help study participants learn more about their future, in terms of risk of dementia related to Alzheimer’s disease. The research may also potentially help other people determine if they are at risk for a wasting disorder.

“Thousands of adults have volunteered for studies at Alzheimer’s disease research centers across the country,” said the lead researcher. Sarah M. Hartz, MD, Ph.D., associate professor of psychiatry. “They come back and have tests year after year, including PET (positron emission tomography) and MRI scans, blood tests, cognitive tests and lumbar punctures which measure proteins in the cerebrospinal fluid. These studies advance the overall understanding of Alzheimer’s disease, but they give participants relatively little information about their own risk. This algorithm is a way to illuminate this information and let individuals know if they are at significant risk for dementia related to Alzheimer’s disease.

Hartz and Co-Principal Investigator Jessica Mozersky, Ph.D.assistant professor of medicine at the university Bioethics Research Center, examined the various factors that contribute to Alzheimer’s dementia, and they used this information to create an algorithm to estimate an individual’s absolute risk of developing early symptoms of Alzheimer’s disease dementia. They developed the algorithm for use in a clinical trial to find out if they could help volunteers in aging studies at the Knight ADRC better understand what biomarkers of disease they might have, and if researchers could then evaluate the eventual results of the participants.

“We developed the algorithm because study participants wanted more than just a report of whether their test results were normal or abnormal,” Mozersky said. “We have done studies with people who receive results that indicate high amyloid, for example. They tell us: ‘You know what I really want to know? My risk.'”

(Image: Mike Worful/School of Medicine)

The Risk Algorithm website uses demographic information, along with specific test results, to help study volunteers better understand their risk.

Over the years, there have been ethical debates about how much information to disclose to people who take part in such studies, since there is not yet a treatment to prevent or cure Alzheimer’s dementia. Additionally, the ability of various biomarkers to predict the problem in people who show no symptoms of the disease has not been well studied.

“We developed the algorithm so that we could tell participants what is currently known in a meaningful way, and so that the algorithm could be easily updated as new research or data emerges,” Hartz said.

The algorithm, accessible on Knight ADRC’s website at, provides more details for researchers and people who want to know more about Alzheimer’s dementia risk. For example, a 69-year-old woman who went to college and had a relative with Alzheimer’s dementia has about a 6% risk of developing early symptoms of Alzheimer’s dementia within the next five years. . This of course means that she also has a 94% chance of not developing dementia due to Alzheimer’s disease in the next five years.

The algorithm incorporates amyloid PET results and brain hippocampus volumes — a smaller hippocampus often suggests an increased risk of Alzheimer’s dementia-related damage — to show how risk changes when such additional information is known. If this same 69-year-old woman also had a PET scan revealing high levels of amyloid and decreased hippocampal volume, her risk would increase to about 33%.

“Yet age is the greatest demographic risk factor,” Hartz said.

If the woman were 85 instead of 69, her risk of developing dementia from Alzheimer’s disease over the next five years would increase from about 6% to about 32%, even without knowing the biomarker results.

The researchers also looked at a gene known to influence the risk of Alzheimer’s dementia. The risk increases significantly depending on the type of APOE gene a person has. But when the researchers included the APOE genotype in their model, they found it didn’t tell them anything that the data from the imaging tests hadn’t already revealed. This is likely because the brain changes seen in imaging tests occur in part because of the APOE gene.

Hartz and Mozersky are continuing their work to improve the ability to predict Alzheimer’s dementia risk based on these variables. They have grants totaling more than $5 million from the National Institute on Aging to conduct a clinical trial to better understand the impact of providing these risk assessments to people participating in research and to validate their algorithm in samples. more important.

“Researchers are concerned about how this information will affect study participants,” Hartz said. “We want to know how the information might affect them and whether providing this type of information can actually help them.”

Hartz SM, Mozersky J, Schindler SE, Linnenbringer E, Wang J, Gordon BA, Raji CA, Moulder KL, West T, Benzinger TLS, Cruchaga C, Hasenstab JJ, Bierut LJ, Xiong C, Morris JC. A flexible modeling approach for biomarker-based calculation of the absolute risk of Alzheimer’s disease-related dementia. The Journal of Alzheimer’s and Dementia, September 30, 2022.

This work is supported by the National Institute on Aging and the National Cancer Institute of the National Institutes of Health (NIH). Grant numbers include R01 AG065234, P01 AG026276, 5P01 AG003991, P30 AG066444, 1UL1 TR002345, R44 AG059489, R01 AG07094, and U01 AG016976, with additional grants funding Alzheimer’s research centers involved in these studies ( for a complete list, see the paper). Other funding sources include BrightFocus CA2016636, the Gerald and Henrietta Rauenhorst Foundation, and the Alzheimer’s Drug Discovery Foundation.

About Washington University School of Medicine

Medicine WashU is a world leader in academic medicine, including biomedical research, patient care, and educational programs with 2,700 faculty. Its National Institutes of Health (NIH) research funding portfolio is the fourth largest among U.S. medical schools, has grown 54% over the past five years, and with institutional investment, WashU Medicine dedicates more a billion dollars a year for basic and clinical research. innovation and training. Its faculty practice consistently ranks among the top five in the nation, with more than 1,790 faculty physicians practicing at more than 60 sites who are also on the medical staff of Barnes-Jew and St. Louis Children’s hospitals of BJC Healthcare. WashU Medicine has a rich history of MD/PhD training, recently dedicated $100 million in scholarships and curriculum renewal for its medical students, and is home to top-notch training programs in every medical subspecialty as well as physiotherapy, occupational therapy, and audiology and communication sciences.

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