Your brain could be 'older' than your age—and it's easier than ever to find out

National Geographic

16-07-2025

Two groundbreaking studies show that measuring how fast your brain is aging could transform how we predict and prevent disease—even before symptoms appear. Illustration by OsakaWayne Studios, Getty Images
Is your brain aging faster than your chronological age? New research shows it could raise your risk of death and dementia significantly—and offers promise for early intervention.
Old age comes for everyone, but how fast it happens—and how healthy you remain when it does—can vary dramatically.
Groundbreaking new research makes it easier than ever to determine how fast your brain is aging—and shows that having an 'old" brain raises your risk of death by a striking 182 percent over about 15 years compared to people whose brains are aging normally.
In the first of two recent studies, Stanford University scientists found that people with biologically younger organs had a significantly reduced risk of developing diseases compared to those with older organs. This was particularly true for the brain: in addition to raising your risk of death, having an older brain increased the risk of dementia threefold.
(When does old age begin? Science says later than you might think.)
The Stanford research team made these discoveries using a blood test based on protein biomarkers, which helped them estimate the biological age of specific organs in the body—a measure that, unlike your chronological age, captures the true condition of your organs.
But they're not the only ones making breakthroughs on this front.
In a complementary study, researchers at Duke University and the University of Otago in New Zealand show that a single MRI scan—technology already common in hospitals—can be used to predict biological brain aging with surprising accuracy.
Together, these studies could revolutionize how scientists and doctors predict and prevent chronic diseases long before they arise.
'Instead of treating each disease one by one after people get them, we want to approach medicine a completely different way and intervene while people are still young and before age-related diseases have developed,' says Terrie Moffitt, co-author of the Duke/Otago study and a professor of psychology and neuroscience at Duke University School of Medicine. Biological age vs. chronological age
Scientists have long distinguished between chronological age—the number of years you've been alive—and biological age. Even the rest of us might notice a difference at high school reunions: one former classmate is training for their fourth triathlon while another is struggling with hip pain and memory issues.
It helps to differentiate between biological and chronological age by thinking of a car's odometer reading versus the year the car was made. 'While many people may be driving cars built in 2010, some have put many more miles on their engine than others,' explains Ahmad Hariri, professor of psychology and neuroscience at Duke University and a lead author of the Duke/Otago study.
(Just one pregnancy can add months to your biological age.)
And just as individual car parts wear out differently, so do different organs in the body. 'Biological age indicates the health and state of an organ by reflecting how well it's functioning, how much it's declining, and how likely it is to develop disease,' explains Tony Wyss-Coray, professor of neurology and lead author of the Stanford study. Your skin, for instance, may be biologically younger than your chronological age, while your heart could be aging faster.
Each organ's longevity is shaped by a mix of genetics, lifestyle, stress, disease history, and environmental exposures. These factors help explain why some people remain biologically young despite the age on their driver's license while others age prematurely and face higher risks for conditions like dementia, heart disease, and diabetes.
To pinpoint biological age, scientists have developed various 'aging clocks' that rely on biomarkers—measurable signs of biological function at the cellular or systemic level. Commonly used biomarkers include DNA methylation (a chemical process that 'tags' parts of your DNA based on exposure or stress) and gene expression.
Though each aging clock serves specific purposes, all aim to enhance our understanding of aging. Unlocking how biological age affects your health
One major benefit of a well-designed aging clock is revealing why certain organs age faster—and how keeping them young can boost longevity and quality of life.
For example, the Stanford study, published July 9 in Nature Medicine, assessed the biological aging of 11 major organ systems—including the brain, heart, and kidneys—and shows clear links between biological age and health outcomes. Specifically, older organs predicted disease while biologically younger ones were protective.
To reach these conclusions, Wyss-Coray and his team analyzed more than 3,000 proteins in blood samples from over 45,000 human subjects. Using machine learning, they developed an algorithm with the data to estimate the biological age of each organ system—all from a single blood sample.
Each 'organ clock,' as Wyss-Coray calls them, shows how much older or younger an organ is compared to a person's chronological age. "What is fascinating from our research is that people with older organs were shown to be more likely to develop disease in these organs," he explains.
For example, the blood protein data showed that an abnormally aged heart predicted higher risk of atrial fibrillation and heart failure; aged lungs were linked to increased COPD risk; and an aged brain dramatically raised the person's likelihood of dementia. In fact, someone with a biologically old brain was roughly 12 times likelier to develop Alzheimer's over the next decade compared to peers with biologically young brains.
Conversely, biologically younger brains and hearts were linked to increased longevity. Most striking, the study found that having a "young" brain lowers your risk of death by as much as 40 percent.
(How a 102-year-old neurologist keeps his brain sharp.)
While the study had limitations—including a primarily white cohort and a limited protein panel—it shows that protein levels, unlike genetic data, can change over time.
This opens the door to more personalized medical interventions. If doctors can determine which organs are aging rapidly, they may be able to slow—or even reverse—that decline with targeted treatment.
While Stanford's test has been patented and licensed to a biotechnology company in hopes of eventually making it clinically useful, it may be years before it's widely available in hospitals and medical practices.
By contrast, the Duke/Otago study uses MRI technology that's already common in many clinical settings. Published July 1 in Nature Aging, the study centers on DunedinPACNI—an algorithm-based biomarker the team developed that estimates how quickly a person is aging using standard brain scans called MRIs.
'From a single brain scan, researchers can now estimate how fast you're aging to predict risk for disease,' says Ethan Whitman, a lead author of the study and a clinical psychology Ph.D. candidate at Duke University.
The algorithm was developed using more than 50,000 brain MRIs across four datasets and longitudinal data from the famed Dunedin study—a rare cohort of 1,037 individuals born in 1972–1973 in New Zealand and followed for decades after.
(How old are you, really? The answer is written on your face.)
This aging clock identifies key structural markers—such as cortical thinning, hippocampal shrinkage (changes that have been linked to memory loss and dementia), and other region-specific atrophy patterns—to estimate brain deterioration and cognitive decline. Critically, it does so by isolating biological aging from generational influences.
'Most aging clocks are based on comparisons between young and old people, which can confuse aging with generational exposures like cigarette smoke or leaded gasoline,' explains Whitman. 'Because our study participants were all born in the same year, we could focus on biological aging alone.'
Even better, the tool accomplishes all this more quickly and accurately than earlier, less-accessible measures.
Such findings could be a game changer for clinical trials and doctors working to detect brain-related diseases earlier. 'DunedinPACNI could be used as a measuring tool in clinical trials or as a screening tool to help doctors identify patients at highest risk of cognitive decline,' Hariri says. Indeed, a sister measure of the algorithm, known as DunedinPACE, has already predicted disease risk in populations across the U.S., U.K., and Latin America—even before symptoms appeared.
For now, the tool remains a relative measure—comparing individuals to others in the same dataset—but reference norms are under development for broader use.
Together, these studies mark a leap forward for personalized medicine.
Though the studies were conducted independently, the two research teams reviewed and praised each other's work. Kristine Yaffe, director of the Center for Population Brain Health at the University of California, San Francisco, who was not involved with either study, also reviewed both studies and calls them high-quality, large-scale, and highly complementary.
(How personalized medicine is transforming your health care.)
Wyss-Coray describes the Duke/Otago research as 'a very powerful approach to build better models, to gain more biological insight, and to make better predictions of health and disease.'
Whitman, in turn, calls the Stanford research 'an excellent study that advances our understanding of aging and how to measure it.'
But it's the combination of both approaches that may offer the greatest promise.
'By using both types of measures, you can identify a person's broad risk for chronic diseases and also detect uniquely increased risk for organ-specific diseases—it's like knowing not just how fast your car is going, but which parts might be wearing out the soonest,' explains Hariri.
"It's exciting to foresee a future where a simple drop of blood or an MRI scan could help guide personalized interventions (such as lifestyle changes or medications) and track their effectiveness over time,' echoes Wyss-Coray.
And that matters because no single measurement 'can tell the full story,' Whitman says. 'The clinicians of the future will need several tools that each offer unique insights into how we're aging and how we can stay healthier, longer.'