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

by · News-Medical

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.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.

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.

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