Summary: A new study reveals that the brain age gap — the difference between a brain’s biological age and chronological age — may influence how risk factors like diabetes and high blood pressure affect cognitive function. Using machine learning to analyze brain scans from over 1,400 older adults, researchers found that a greater brain age gap was linked to poorer thinking and memory skills.
This effect was especially significant in people with markers of cerebrovascular disease. The findings suggest that the brain age gap could serve as a useful biomarker for predicting cognitive decline in adults with elevated health risks.
The difference between the brain’s predicted age and actual chronological age, called a brain age gap, may influence the relationship between cognitive impairment risk factors, like high blood pressure and diabetes, and a person’s cognitive performance, also known as thinking and memory skills, according to a study published June 18, 2025, online in Neurology.
Advances in neuroimaging have led to the development of machine learning tools, trained on brain scans, that can help detect differences in how people’s brains age and predict a brain’s biological age.
“As we get older, our brains change, with less brain volume and fewer blood vessels that support brain tissue, and diseases can worsen these changes, profoundly affecting brain health,” said study author Saima Hilal, MD, PhD, of the National University of Singapore.
“Such signs of brain aging can be seen on brain scans, showing if a person’s brain looks older than their actual age. Our study found that having more risk factors for cognitive impairment is associated with poorer cognitive performance, with the brain age gap playing a key role in this connection. This effect was more noticeable in people with cerebrovascular disease.”
The study included 1,437 people without dementia who had an average age of 66. Of those, 60% had no cognitive impairment.
Participants’ medical histories were gathered through questionnaires, interviews and medication review. They also had physical examinations, laboratory tests and brain scans.
To measure risk factors for cognitive impairment, researchers calculated a score for each participant based on the following risk factors: age, ethnicity, education, past and current smoking status, body mass index, depressive symptoms, high blood pressure, diabetes, high cholesterol and stroke. Higher scores indicated a greater likelihood of cognitive impairment.
To measure thinking and memory skills, or cognitive performance, participants took tests for executive function, attention, language, memory, visuoconstruction, which involves the ability to copy a drawing or build a model, and visuomotor speed, which is how quickly it takes someone to process visual information and turn it into action.
Researchers found higher cognitive impairment risk factor scores were consistently associated with poorer cognitive performance, especially for visuoconstruction and visuomotor speed.
Using machine learning, researchers developed a brain age prediction model to review participants’ brain scans and determine the predicted biological brain age of each participant.
Researchers then subtracted a person’s chronological brain age from their predicted brain age to calculate their brain age gap. A positive brain age gap implied accelerated brain aging.
Researchers also used brain scans to look for markers of cerebrovascular disease, such as microbleeds and infarcts, areas of dead tissue due to lack of blood supply. They compared people with high and low amounts of markers.
Researchers found in people with a high amount of these cerebrovascular disease markers, the brain age gap influenced how cognitive impairment risk factors affected thinking and memory skills, especially in areas like executive function and language.
They found the proportion of mediation, or how much the relationship between cognitive impairment risk factors and thinking memory skills was affected by the brain age gap, was 20% overall, 34% for executive function and 27% for language.
“The brain age gap may be a helpful biomarker in determining a person’s risk of cognitive decline,” said Hilal.
“Our findings suggest that accelerated brain aging may serve as an important factor linking cognitive impairment risk factors to thinking and memory skills in adults with cerebrovascular conditions.”
A limitation of the study was that it looked only at Southeast Asian people, so the results may not be the same for other populations.
Researchers were also unable to examine the effects of exercise, diet and genetic markers for Alzheimer’s disease on brain structure and cognition because data were not available for all participants.
Funding: The study was supported by the National University of Singapore, the Singapore National Medical Research Council and the Singapore Ministry of Education.
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