Brain aging may hold the key to predicting Alzheimer’s risk

New study uncovers how advanced brain age, even in cognitively healthy adults, signals a higher risk of Alzheimer's disease and cognitive decline, offering insights into early detection and potential prevention strategies.

Study: Relationship between MRI brain-age heterogeneity, cognition, genetics and Alzheimer’s disease neuropathology. Image Credit: sasirin pamai/Shutterstock.comStudy: Relationship between MRI brain-age heterogeneity, cognition, genetics and Alzheimer’s disease neuropathology. Image Credit: sasirin pamai/Shutterstock.com

In a recent study published in EBiomedicine, a team of researchers investigated how brain aging varies among older adults without any cognitive impairments and explored the link between brain aging, genetic factors, cognitive decline, and Alzheimer’s disease risk.

Background

Brain aging is a concept used to understand how individual brains change with age in comparison to the average changes for the age group. It can be determined using neuroimaging techniques.

Brain health can be estimated using the difference between a person's predicted brain age and their actual age. A brain that appears older than its chronological age could indicate underlying health issues.

Although brain age is typically calculated using various imaging techniques, a wide range of complex processes that vary across individuals contribute to brain aging. Structural and functional changes, such as the loss of gray matter and changes in neural activity, occur as a natural part of aging.

However, advanced brain age during midlife has also been linked to an increased risk of developing dementia in the later years.

Furthermore, neurodegenerative diseases such as Alzheimer's disease have been found to cause deviations from the natural brain aging trajectories.

Despite this growing evidence on brain aging and neurological health, there is a dearth of research on whether advanced brain age in older adults without other cognitive impairments increases the risk of neurodegenerative conditions such as Alzheimer's disease.

About the study

The present study focused on cognitively unimpaired older adults. It investigated whether those with advanced brain age showed any early signs of Alzheimer's disease or other brain changes typically seen in dementia.

The researchers used structural and functional scans of the brains to create two brain age measures for each participant, which were then used to group the participants into three categories — advanced, resilient, or mixed.

The study aimed to understand how these groups differed in cognitive function and brain health. The researchers hypothesized that the individuals in the advanced group would show a greater degree of neurodegeneration and cognitive decline.

The researchers used two datasets for the study. The first set consisted of close to 3,500 participants between the ages of 40 and 85 years, spanning four different studies, including the United Kingdom Biobank.

Structural and functional data of the brain, along with genetic and cognitive data, were collected using resting-state functional magnetic resonance imaging (fMRI). Additionally, the MRI images underwent processing, and various regions of interest were extracted from them.

The second dataset consisted of 867 individuals and the researchers used it to compare brain-age groups. A vector regression model, known as SPARE-BA that predicts brain age using structural and functional MRI was used to estimate the brain age, and the SPARE-BA scores were used to categorize the participants.

Comparisons of image data included white matter hyperintensities, amyloid burden, and other brain markers. Additionally, the researchers administered cognitive tests at baseline and during follow-ups.

Furthermore, genetic data involving Alzheimer's disease-related single nucleotide polymorphisms were analyzed for associations with the brain age groups.

Results

The results showed that individuals with advanced brain age showed greater signs of neurodegeneration and poorer cognitive function than individuals who were categorized as having more resilient brains.

The key findings suggested that structural and functional deficits seen in the brain images were stronger indicators of poor long-term outcomes.

Furthermore, the presence of white matter lesions and increased brain atrophy were significant markers of advanced brain aging. Individuals with advanced brain age showed increased brain shrinkage, reductions in the density of neurites, and higher amyloid burden — all of which were associated with a greater risk of Alzheimer's disease.

Additionally, the study also identified distinct cognitive and genetic patterns among the three groups based on brain age. The resilient group showed better cognitive function and carried a genetic variant associated with protection against Alzheimer's disease.

The individuals in the advanced group showed functional and structural indicators of brain aging, such as atrophy, increased free water diffusion in the brain, and a greater risk of cognitive decline.

The cognitive tests also revealed that the groups with functional deficits, categorized as AFRS (advanced functional brain age and resilient structural brain age), experienced the steepest decline in cognitive performance, including a substantial drop in the cognitive test scores.

On the other hand, individuals with more structural brain age abnormalities showed greater cognitive stability in comparison.

Conclusions

In conclusion, the study highlighted the complexity of brain aging. It showed that advanced brain age characterized by both functional and structural abnormalities was linked to a greater risk of Alzheimer's disease.

Furthermore, the researchers believe that identifying the protective genetic factors among individuals who show resilience to abnormal brain aging could offer new pathways for therapeutic interventions against neurodegenerative diseases.

Journal reference:
Dr. Chinta Sidharthan

Written by

Dr. Chinta Sidharthan

Chinta Sidharthan is a writer based in Bangalore, India. Her academic background is in evolutionary biology and genetics, and she has extensive experience in scientific research, teaching, science writing, and herpetology. Chinta holds a Ph.D. in evolutionary biology from the Indian Institute of Science and is passionate about science education, writing, animals, wildlife, and conservation. For her doctoral research, she explored the origins and diversification of blindsnakes in India, as a part of which she did extensive fieldwork in the jungles of southern India. She has received the Canadian Governor General’s bronze medal and Bangalore University gold medal for academic excellence and published her research in high-impact journals.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Sidharthan, Chinta. (2024, October 24). Brain aging may hold the key to predicting Alzheimer’s risk. News-Medical. Retrieved on November 03, 2024 from https://www.news-medical.net/news/20241024/Brain-aging-may-hold-the-key-to-predicting-Alzheimere28099s-risk.aspx.

  • MLA

    Sidharthan, Chinta. "Brain aging may hold the key to predicting Alzheimer’s risk". News-Medical. 03 November 2024. <https://www.news-medical.net/news/20241024/Brain-aging-may-hold-the-key-to-predicting-Alzheimere28099s-risk.aspx>.

  • Chicago

    Sidharthan, Chinta. "Brain aging may hold the key to predicting Alzheimer’s risk". News-Medical. https://www.news-medical.net/news/20241024/Brain-aging-may-hold-the-key-to-predicting-Alzheimere28099s-risk.aspx. (accessed November 03, 2024).

  • Harvard

    Sidharthan, Chinta. 2024. Brain aging may hold the key to predicting Alzheimer’s risk. News-Medical, viewed 03 November 2024, https://www.news-medical.net/news/20241024/Brain-aging-may-hold-the-key-to-predicting-Alzheimere28099s-risk.aspx.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Researchers aim to transform treatment for sleep disorders in military personnel