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Research · Aging clocks

New aging clock reads gene activity, not DNA

LongevityWatch editors · August 7, 2026 · 1 min

Measuring biological age is hard. The best-known methods look at chemical marks on DNA. But researchers have now built a clock that reads gene activity directly, and it may be better at predicting what interventions actually do to aging.

A team of researchers published Pasta, a transcriptomic clock. Where epigenetic clocks measure methylation, chemical tags on DNA, this clock reads the transcriptome: the collection of active RNA molecules that shows which genes are operating in a cell at any given moment. These are two distinct layers of biological information.

Why gene activity matters here

Gene activity responds more quickly to change than methylation patterns do. That makes a transcriptomic clock potentially more sensitive to short-term interventions, such as drugs or dietary adjustments. Pasta was specifically designed to detect whether a given compound or change in gene expression shifts a cell’s biological age.

According to the researchers, Pasta performs well at predicting the age-related effects of various compounds and genetic modifications. It could offer a practical tool for testing longevity interventions without waiting years for health outcomes.

What remains uncertain

Transcriptomic clocks are a relatively new area. The open question is whether gene activity patterns are meaningful predictors of health outcomes in humans, or whether they primarily capture a laboratory signal. Epigenetic clocks have been more extensively validated in large human cohorts. Pasta is promising as a research instrument, but its clinical applicability still needs to be established.

For the longevity field, the emergence of new types of biological age clocks is significant regardless. Each clock measures something different, and combining multiple methods may eventually give a more complete picture of how quickly someone is aging biologically.

Read the original article

Search terms: transcriptomic aging clock, gene expression biological age, RNA biomarkers intervention analysis

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