People who are the exact same chronological age can undergo very different molecular changes as they grow older, a new study finds.
“Molecular aging is dynamic and unique to each person,” said study co-author Julia El-Sayed Moustafa, a computational genomics researcher at King’s College London. Even if you and your friend were born the same day, the activity of some of your genes might ramp up while the same genes in your friend dial down. The same is true for metabolites, which are small molecules produced during the body’s chemical processes essential for health.
Genetics, environmental exposures and daily biological rhythms may help to explain some of those differences, the researchers say.
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The findings, published Thursday (Sept. 3) in the journal Science, may complicate efforts to capture aging with a single metric. For example, “biological age” scores estimate the body’s true cellular and physical health, judging how much “older” it is than your chronological age. Scientists have developed “aging clocks” that use molecular markers, such as chemical tags on DNA, to estimate biological age.
But this new study suggests that “biological aging is less like a fixed score and more like a changing set of molecular trajectories,” said Raghav Sehgal, an associate research scientist at the Yale School of Medicine who was not involved in the new research. “No single number can fully capture the many systems that age at different rates,” he told Live Science in an email.
More than a snapshot
In the study, researchers followed 335 women ages 32 to 80 from the long-running TwinsUK cohort for eight years. The cohort includes identical and fraternal twin pairs, along with detailed health and biological data gathered to investigate how genetics and environment can influence health.
Each woman had at least three clinic visits between 2009 and 2017, with a median of six years between their first and last visits. At each visit, researchers took blood samples and measured gene activity and levels of metabolites.
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“Most aging studies take only a ‘snapshot,’ comparing different people at one point in time,” El-Sayed Moustafa said. “In this study, we have multiple measurements, so we can see how gene activity and metabolite levels change over time within the same person.”
The study pulled data from the TwinsUK cohort, which in total includes over 15,000 identical and fraternal twins from across the U.K. (This is a stock image.)
(Image credit: MesquitaFMS via Getty Images)
Of more than 16,000 genes and 915 metabolites analyzed, 5,061 genes and 181 metabolites changed significantly over time. Of those genes, the vast majority — 5,036 — showed a consistent increase or decrease across the group. The same was true of 45 metabolites.
Many of these genes were involved in pathways linked to immune function, metabolism and age-related conditions, including heart disease and neurodegenerative disorders.
That said, “even when most people’s genes or metabolites moved in one direction, we still found groups moving the opposite way,” said study co-author Kerrin Small, a professor of genomics at King’s College London. So even if, on average, certain genes’ activity trended in the same direction, there were individuals who broke from the pattern.
Among 136 metabolites, for example, the levels changed from person to person. A metabolite that increased in one woman could fall in another, while some showed little change over time. One consistent pattern was that each woman’s overall metabolite profile also became less similar to her earlier profile.
What might shape those changes?
Several factors appeared to shape these molecular changes. Identical twins tended to have more similar gene-expression patterns than fraternal twins did, suggesting that genetics plays a strong role. Different immune cell types also showed distinct patterns of gene activity with age, suggesting age-related changes in the immune system are not uniform.
The molecular signals also varied with the time of day and season in which the blood samples were collected. About a quarter of the genes and metabolites showed seasonal shifts, including changes linked to energy production and immune activity, while up to 40% of the metabolites varied with the body’s 24-hour internal clock.
The researchers also found an unexpected decline in blood levels of per- and polyfluoroalkyl substances (PFAS), including PFOA and PFOS. Often called “forever chemicals,” PFAS are synthetic compounds used in a variety of products, such as nonstick cookware and food packaging. Their decline in the study was likely due to restrictions on their use in the U.K., the study authors suspect. Blood levels of PFAS were also associated with changes in some genes and metabolites, although the study could not show that the chemicals themselves caused those changes.
The team found more than 100,000 associations between genes and metabolites, suggesting that changes in certain genes go hand-in-hand with changes in specific metabolites. This highlights how interconnected the body’s biological processes are and how complex aging really is.
“I would not call aging unpredictable, but it is certainly more individualized and context-dependent,” Sehgal said. Understanding these individual trajectories could one day help researchers distinguish healthy aging from molecular changes linked to disease, but that application is still a long way off.
The study was observational, included only women and relied solely on blood samples, so larger and more diverse studies are still needed to see whether these patterns hold in broader populations. The researchers now plan to track molecular changes over about 15 years, up from eight in the current study. In the future, Sehgal suggested, aging assessments could combine broad, biological-age scores with more personalized measures of immune, metabolic, brain and cardiovascular aging.
El-Sayed Moustafa, J. S., Ramisch, A., Raza, Y. N., Leday, G. G., Jiao, Y., Wang, D., Stevens, M., Roberts, A. L., Tomlinson, M., Yan, X., Ing-Simmons, E., Wadge, S., Abdalla, M., Falchi, M., Holmes, C. C., Menni, C., Nicholson, G., McCarthy, M. I., Dermitzakis, E. T., … Small, K. S. (2026). Longitudinal Dynamics of gene expression and metabolomics in an aging population cohort. Science, 393(6815). https://doi.org/10.1126/science.aed6452