Scientists Create Brain Scan Tool to Predict Aging Speed

A single MRI brain scan can now reveal how fast someone is aging and predict their risk for dementia, chronic diseases, and even death years before symptoms appear, according to researchers who developed a powerful new assessment tool.

The technology, called DunedinPACNI, analyzes brain structure to estimate biological aging rates that often differ dramatically from chronological age.

Using data from over 50,000 brain scans worldwide, scientists at Duke University, Harvard, and the University of Otago demonstrated that people aging faster by this measure faced significantly higher risks for cognitive decline, physical frailty, and mortality. The findings, published in Nature Aging, could help identify individuals who might benefit most from early interventions to slow age-related decline.

Beyond Calendar Age: Measuring True Biological Aging

“The way we age as we get older is quite distinct from how many times we’ve traveled around the sun,” explained Ahmad Hariri, professor of psychology and neuroscience at Duke University. Unlike previous “aging clocks” that compare people of different ages at one time point, this tool measures how the same individuals change over decades.

The breakthrough stems from the unique Dunedin Study, which has followed 1,037 people born in the same year since birth. Researchers tracked 19 biomarkers—including blood pressure, lung function, cholesterol, and even gum recession—across nearly 20 years to create a gold-standard measure of aging speed.

Key findings from the comprehensive analysis include:

• People with faster brain aging scores were 60% more likely to develop dementia
• The fastest agers faced 40% higher mortality risk within several years
• Brain-based predictions worked equally well across different ethnic and socioeconomic groups
• The tool showed excellent reliability when tested multiple times on the same individuals

Using MRI scans collected when Dunedin participants were 45 years old, researchers trained an algorithm to recognize brain patterns associated with rapid aging. The tool analyzes 315 structural brain features, including cortical thickness, gray matter volume, and brain region sizes.

Predicting Health Decades Into the Future

When researchers applied their aging tool to brain scans from other studies, the results were striking. In one analysis of 624 cognitively normal adults, those deemed fast agers at baseline developed memory problems and dementia significantly earlier than slow agers during up to 16 years of follow-up.

“What’s really cool about this is that we’ve captured how fast people are aging using data collected in midlife,” Hariri noted. “And it’s helping us predict diagnosis of dementia among people who are much older.”

The brain-aging measure predicted far more than cognitive decline. People with faster aging scores showed increased physical frailty, reported worse overall health, and faced higher risks for heart attacks, lung disease, and strokes. The fastest agers were 18% more likely to develop chronic diseases within several years compared to average agers.

Importantly, the tool captured social determinants of health, with faster aging scores observed among people with lower education levels and income—reflecting well-established patterns of health inequality.

Global Validation Across Diverse Populations

A critical test came when researchers applied their tool to brain scans from Latin American participants—a population underrepresented in most brain aging research. The results held strong: people with Alzheimer’s disease and frontotemporal dementia showed accelerated aging patterns nearly identical to those seen in North American datasets.

This cross-cultural validation suggests the brain signatures of aging may be universal, transcending geographic and demographic boundaries. The tool performed similarly whether analyzing scans from high-income participants in the UK or diverse populations across Argentina, Chile, Colombia, Mexico, and Peru.

The research addresses urgent global health needs. With people living longer worldwide, the number of adults over 65 is expected to double by 2050, reaching nearly one-fourth of the global population. Alzheimer’s care costs alone could grow from $1.33 trillion in 2020 to over $9 trillion by 2050.

A New Window Into Prevention

Current Alzheimer’s treatments largely fail because they begin after extensive brain damage has occurred. “Drugs can’t resurrect a dying brain,” Hariri observed. The new tool could identify at-risk individuals years or decades earlier, when interventions might still prevent irreversible decline.

The algorithm is freely available to researchers worldwide, potentially accelerating studies of aging causes and anti-aging interventions. Scientists can now measure aging effects in existing brain imaging studies without collecting additional data—unlocking insights from thousands of scans already sitting in research databases.

While more research is needed before clinical applications, the tool represents a significant advance in understanding the brain-body connection in aging. As Hariri concluded, “We really think of it as hopefully being a key new tool in forecasting and predicting risk for diseases, especially Alzheimer’s and related dementias.”