People who are the same chronological age can experience very different molecular changes as they grow older, according to a new study. The findings suggest that biological aging is a highly individual process shaped by genetics, the environment, daily biological rhythms and other factors.
“Molecular aging is dynamic and unique to each person,” said study co-author Julia Elsayed Mustafa, a computational genomics researcher at King’s College London.
For example, genes involved in the same biological process may become more active in one person but less active in another. The same pattern can occur with metabolites — small molecules produced during the body’s chemical reactions that help regulate health and disease.
These differences may be influenced by genetics, environmental exposures and the body’s daily biological rhythm, also known as the circadian rhythm.
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The study was published in the journal Science. Its results could make it more difficult for scientists to measure aging with a single number or universal biological-age test.
Scientists have developed several “aging clocks” that use molecular markers, such as chemical tags on DNA, to estimate a person’s biological age. These tools can indicate whether someone appears biologically older or younger than their chronological age.
However, the new research suggests that biological aging may be less like a fixed score and more like a collection of changing molecular patterns.
“There is no single number that fully captures the many systems that age at different rates,” said Raghav Sehgal, an associate research fellow at Yale School of Medicine who was not involved in the study.
Tracking molecular aging over time
The researchers followed 335 women between the ages of 32 and 80 for up to eight years. The participants were part of the TwinsUK cohort, a long-term research project that includes identical and fraternal twins, along with extensive health and biological data.
Each participant visited a clinic at least three times between 2009 and 2017. The median time between the first and final visits was six years. At every visit, researchers collected blood samples and measured gene activity and metabolite levels.
“Most aging studies only take snapshots, comparing different people at a single point in time,” Elsayed Mustafa said. “Because this study involved repeated measurements, we could see how gene activity and metabolite levels changed within the same person over time.”
The study used data from the TwinsUK cohort, which includes more than 15,000 identical and fraternal twins from across the United Kingdom.
(Image credit: MesquitaFMS, Getty Images)
The team analyzed more than 16,000 genes and 915 metabolites. Over the study period, 5,061 genes and 181 metabolites changed significantly.
Most of the genes — 5,036 — showed broadly consistent increases or decreases across the participants. A similar pattern was observed for 45 metabolites.
Many of the genes were linked to biological pathways involved in immune function, metabolism and conditions associated with aging, including heart disease and neurodegenerative disorders.
Despite these overall trends, some participants showed molecular changes in the opposite direction. “Even though most people’s genes and metabolites moved in one direction, we found a group that moved in the opposite direction,” said Kerrin Small, a professor of genomics at King’s College London.
Levels of 136 metabolites varied substantially between individuals. A metabolite that increased in one woman could decrease in another, while showing little change in a third participant. The researchers also found that each woman’s overall metabolite profile became less similar to her own earlier profile over time.
What shapes individual aging patterns?
Several factors appear to influence molecular changes during aging. Identical twins generally had more similar gene-expression patterns than fraternal twins, suggesting that genetics plays an important role.
However, aging-related changes were not uniform across immune cell types. Previous research has also suggested that age-related immune changes can vary significantly between people.
The timing of blood collection also mattered. Molecular signals differed depending on the season and time of day when samples were taken. Approximately one-quarter of the genes and metabolites showed seasonal variation, including changes related to energy production and immune activity.
Up to 40% of metabolites varied according to the body’s 24-hour biological clock, highlighting the importance of circadian rhythms when studying aging and health.
The researchers also observed declines in blood levels of per- and polyfluoroalkyl substances, or PFAS. These synthetic compounds, sometimes called “forever chemicals”, have been used in products such as nonstick cookware and food packaging.
The decline may be related to restrictions on PFAS use in the United Kingdom. PFAS levels were also associated with changes in certain genes and metabolites, although the observational study could not prove that the chemicals caused those molecular changes.
Overall, the researchers identified more than 100,000 associations between genes and metabolites. These links demonstrate how closely connected the body’s biological systems are — and how complex the aging process can be.
“I’m not saying that aging is unpredictable, but it is certainly more personal and context-dependent,” Sehgal said.
Understanding individual molecular aging trajectories could eventually help scientists distinguish between changes associated with healthy aging and those linked to disease. However, researchers caution that such applications remain years away.
The study included only women and relied on blood samples, so larger and more diverse studies are needed to determine whether the findings apply to the wider population. The research team plans to track molecular changes for approximately 15 years, extending the current eight-year follow-up period.
In the future, aging assessments may combine broad biological-age scores with personalized measures of immune, metabolic, brain and cardiovascular aging.
Elsayed Mustafa, J.S., et al. (2026). “Longitudinal dynamics of gene expression and metabolomics in aging populations.” Science, 393(6815).
Source: www.livescience.com


