Aging illustration via clocks in the brain

People with an older biological age than their chronological age may be more at risk for dementia. (© svetazi - stock.adobe.com)

Biological Aging Isn’t Fixed, and a New Study Shows Why That Changes Everything About Predicting Longevity

In A Nutshell

  • A 24-year study of nearly 700 adults found that how fast biological age accelerates over time is linked to higher mortality risk, adding predictive power beyond a single measurement alone.
  • Researchers used seven DNA-based “epigenetic clocks” to track biological aging across multiple time points, finding that the combined picture of where someone started and how quickly they changed told a more complete story than any one reading.
  • Newer clocks built to predict death or physical decline outperformed older clocks originally designed just to estimate calendar age from DNA patterns.
  • The findings point toward a future where tracking the trajectory of biological aging, not just a snapshot, could help identify who is aging faster and whether interventions are having any effect.

A birthday tells the world how many years someone has been alive. But deep inside every cell, a different kind of clock is ticking, one that measures how quickly the body is actually wearing down. Now, a study spanning nearly a quarter century has found that it’s not just the reading on that internal clock that matters. It’s how fast the clock is speeding up.

Researchers tracking hundreds of adults in Italy found that people whose biological aging sped up over time tended to face higher risks of death, especially when researchers looked at both their starting point and how that changed over time. Two people who appear to be aging at the same rate right now could have very different futures depending on whether one of them is quietly accelerating while the other holds steady.

A single reading is just a snapshot. Watching how that reading shifts over time is more like a movie, and the movie tells a far more useful story.

Published in Nature Aging, these findings matter a great deal for the growing field of anti-aging science. If biological aging isn’t a fixed path but something that shifts in response to health changes, environment, and lifestyle, then tracking those shifts could become a powerful tool for identifying who needs help and could help researchers figure out whether treatments are actually working.

Hourglass with a DNA double helix and flowing sand, a symbolic representation of genetics, time, and the biological aging process. Ideal for science and health concepts.
How fast the sands in your biological hourglass fall may actually dictate how soon you’ll die better than your birthdate. (© Anjar Stock – stock.adobe.com)

Biological Aging Tracked Over 24 Years

The study drew on data from the InCHIANTI study, a long-running research project focused on aging among people living in two towns near Florence, Italy. Researchers analyzed 699 adults whose DNA had been sampled at two or three points over the study period, which began between 1998 and 2000. The average age at the start was 63, and about 56 percent of participants were female.

Over those years, 396 of the 699 participants died, giving the research team a large number of cases to analyze. The median follow-up time was 21.5 years.

To measure biological aging, the team used seven different tools known as epigenetic clocks. These analyze chemical tags on DNA to estimate how old the body actually is, regardless of the calendar. Some of these clocks were designed in the early 2010s to simply match a person’s real age. Newer versions were built to predict death or to capture the speed of physical decline based on changes in health markers over time.

When the researchers looked only at a single starting measurement of biological age, nearly all seven clocks showed a link to mortality risk. People who appeared biologically older than their actual age were more likely to die during the follow-up period. That finding was consistent with previous research and wasn’t surprising on its own.

The real discovery came when the team examined how those clock readings changed over time. When both the starting biological age and the rate of change were included in the same statistical model, the predictions became much more accurate. For several of the clocks, the speed of biological aging proved to be a strong, independent predictor of death, meaning it added new information that couldn’t be captured by a single reading alone.

Results held up even after adjusting for age, sex, and heart health factors like smoking, physical activity, body mass index, cholesterol, blood pressure, and blood sugar.

Not All Biological Clocks Are Created Equal

One of the more revealing findings was that not all biological aging tools performed equally well. Newer clocks, those built to predict mortality or to track physical decline, outperformed the older ones that were originally designed just to estimate calendar age from DNA patterns.

The researchers offered a straightforward explanation: the earliest clocks were trained to match calendar age, which can actually mask the deviations from expected aging that carry the most important health information. Newer clocks, by contrast, were built with health outcomes or physical decline as their targets, making them better at spotting danger.

Among the newer clocks, the second-generation ones appeared to have a slight edge in sorting people into the correct risk categories. The researchers suggested this might be because the latest generation of clocks was developed using data from younger adults and may not fully capture aging patterns in older populations.

Tracking biological aging and risk
(Infographic generated by StudyFinds)

How Fast Biological Age Changes Over Time

Perhaps the most important takeaway from the study is a conceptual one. Biological age is not locked in at birth. The data showed that these clocks shift over time in ways that likely reflect changes in health. Some people’s clocks sped up. Others maintained a steadier pace. And those different paths mapped onto different survival outcomes.

Individual paths were fairly linear for most participants, following a consistent course over time, with only a few people showing dramatic swings. But the rate at which different clocks ticked varied. Some clocks appeared to accelerate with advancing age, suggesting that certain aspects of biological aging may compound over time.

When the team broke participants into younger and older groups, the link between a single starting measurement and death was weaker in the older group for some clocks, while the connection between the rate of change and death remained consistent across both age groups. For older adults in particular, tracking changes over time may be more informative than a one-time reading.

The study’s authors pointed to several important next steps. Future research, they argued, should examine whether treatments that slow the rate of biological aging, through lifestyle changes, medications, or other strategies, can translate into longer, healthier lives. They also called for the development of clocks specifically designed to capture change over time, rather than being adapted from tools built for single measurements.

A curious puzzle surfaced across all seven clocks: biological age increased by less than one year for every calendar year that passed. The reasons remain unclear, but this could reflect quirks in how the clocks were built, or it might mean that some aspects of aging simply aren’t captured by DNA-based measurements.

What the study makes clear is that a single snapshot of biological age, while useful, misses part of the picture. Biological aging is a process in motion, and watching where that process is headed, not just where it started, offers a more honest look at what the future may hold. For a field racing to extend how long people live in good health, that distinction is worth taking seriously.


Paper Notes

Limitations

All participants in this study were of European ancestry from two towns in Italy, which limits how broadly the findings can be applied to other populations. The researchers noted that an important goal of future research is to develop and test epigenetic clocks in highly diverse populations and verify that their values and changes over time predict health outcomes across races and sex. The sample size of 699 participants, while sufficient to detect significant associations, limited the ability to make finer comparisons between different clock models. Additionally, DNA methylation data were only available from adulthood, so it was not possible to assess how early-life exposures might have shaped initial biological age trajectories. The study also acknowledged that longitudinal trajectories may be affected by a statistical phenomenon known as regression to the mean, and that the moderate negative correlation between baseline measurements and longitudinal changes may partially reflect this effect. Finally, the study focused exclusively on mortality as an outcome, and the authors noted that expanding to other outcomes such as disability and disease burden will be important.

Funding and Disclosures

The work was supported by the Intramural Research Program of the National Institute on Aging. Daniel W. Belsky is a fellow of the CIFAR Child Brain Development Network. The research utilized computational resources of the NIH HPC Biowulf cluster. Steve Horvath and Ake Tzu-Hui Lu are named inventors on patent applications related to epigenetic clocks owned by the Regents of the University of California. Horvath is a founder and paid consultant of the nonprofit Epigenetic Clock Development Foundation, which licenses these patents. Belsky is an inventor of the DunedinPACE epigenetic clock, a Duke University and University of Otago invention licensed to TruDiagnostic, and he is consulting CSO and SAB chair of BellSant and an SAB member of the Hooke Clinic. The other authors declared no competing interests.

Publication Details

Title: Longitudinal changes in epigenetic clocks predict survival in the InCHIANTI cohort

Authors: Pei-Lun Kuo, Ann Zenobia Moore, Toshiko Tanaka, Daniel W. Belsky, Ake Tzu-Hui Lu, Steve Horvath, Stefania Bandinelli, and Luigi Ferrucci

Journal: Nature Aging, Volume 6, March 2026, pages 534–540

DOI: 10.1038/s43587-026-01066-6

Affiliations: National Institute on Aging, National Institutes of Health (Kuo, Moore, Tanaka, Ferrucci); Robert N Butler Columbia Aging Center and Department of Epidemiology, Mailman School of Public Health, Columbia University (Belsky); Altos Labs, San Diego (Lu, Horvath); Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles (Horvath); Geriatric Unit, Local Health Unit Tuscany Centre, Florence, Italy (Bandinelli). Kuo and Moore contributed equally as co-first authors.

Received: September 27, 2024. Accepted: January 6, 2026. Published online: March 13, 2026.

Disclaimer: This study was conducted in a specific population — adults of European ancestry living in two towns in Tuscany, Italy — which limits how broadly the findings apply to people of other backgrounds. The research tracked mortality as its primary outcome and did not test any anti-aging treatments or interventions. All participants were adults, so the study could not account for how early-life factors may have shaped their biological aging trajectories. As with all observational research, the findings show associations, not causes.

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