Researchers from UCLA and an international consortium have created mathematical models that use DNA methylation levels to accurately estimate the age of tissues in 185 mammalian species, from mice to whales. These "pan-mammalian clocks" work with high accuracy (r > 0,96) and show that a species' maximum lifespan correlates with the nature of epigenetic marks formed as early as the embryonic development period.
The discovery is important precisely now: it provides a tool for comparing aging processes across species and for testing interventions in models where direct experiments on humans are impossible. At the same time, it casts doubt on the notion of aging as the random accumulation of damage — the data point to an evolutionarily conserved program linked to development.
Back in 2013, Steve Horvath proposed the first epigenetic clocks for humans. The new work relies on a database of more than 15 thousand tissue samples from 348 species, collected by nearly two hundred scientists. Papers in Science and Nature Aging (2023) show that methylation at certain DNA sites changes predictably with age in all mammals, and that profiles associated with a species' maximum lifespan differ from those reflecting individual mortality risk.
The study's strength is its scale and reproducibility: the clocks predict age even in long-lived species and correlate with mortality risk in humans and mice. The weakness is that there is still no evidence that intervening in these marks actually extends life in humans; data on the effects of caloric restriction or mutations in the somatotropic axis are preliminary and require further verification. The researchers note patent interests: Horvath and colleagues are affiliated with the Epigenetic Clock Development Foundation and have filed applications for methylation array technology.
Imagine a relief map: in long-lived species, methylation forms distinct "peaks and valleys" shaped over long periods of development; in short-lived ones, it is a flat landscape where cells quickly pass through maturation stages. This analogy helps explain why epigenetic clocks capture not only chronological age but also evolutionary differences in life strategies.
The work shows that aging in mammals is a continuation of developmental programs, not merely wear and tear. It remains an open question how far these conserved mechanisms can be modulated without disrupting other processes, and what ethical frameworks will be required when translating such findings into clinical practice.
