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

New study reveals how advanced brain age, even in cognitively healthy adults, signals higher risk of Alzheimer’s disease and cognitive decline, providing insight into early detection and potential prevention strategies.

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

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

Background

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

Brain health can be estimated by the difference between a person’s predicted brain age and their actual age. A brain that appears older than its chronological age may indicate underlying health problems.

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

However, advanced brain aging during middle age has also been associated with an increased risk of developing dementia in later years.

Furthermore, neurodegenerative diseases such as Alzheimer’s have been found to cause abnormalities in the brain’s natural aging pathways.

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

About the study

The current study focused on cognitively healthy elderly people. It examined whether people with advanced brain age showed early signs of Alzheimer’s disease or other brain changes commonly associated with dementia.

The researchers used structural and functional scans of the brain to create two measures of brain age 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 group consisted of almost 3,500 participants between 40 and 85 years old, spread across 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). In addition, the MRI images were processed and several areas of interest were extracted.

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

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

In addition, genetic data regarding 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 categorized as having more resilient brains.

Key findings suggested that structural and functional deficits seen on 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, a decrease in neurite density and a higher amyloid burden – all of which were associated with a greater risk of Alzheimer’s disease.

Furthermore, the study also identified different 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 showed that the groups with functional deficits, categorized as AFRS (advanced functional brain age and resilient structural brain age), experienced the strongest declines in cognitive performance, including a substantial decline in cognitive test scores.

On the other hand, individuals with more structural abnormalities in brain age 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 associated with a greater risk of Alzheimer’s disease.

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