In May 2026, Nature published a study in which analysis of more than 11 thousand transcriptomes from 25 tissues of mice, rats, macaques, and humans revealed conserved changes in gene expression during aging. These signatures allow the construction of molecular clocks that predict not only chronological age but also mortality risk with accuracy comparable to second-generation epigenetic clocks.
The main difference from previous approaches is interpretability. Epigenetic clocks measure DNA methylation but do not show which specific genes are working differently. Here, modules are clearly visible: expression of genes related to cellular senescence (CDKN1A, encoding p21), inflammation, and apoptosis increases; expression of genes involved in wound healing, differentiation, and extracellular matrix synthesis decreases. These changes are conserved across species and cell types.
The authors — Alexander Tyshkovsky, Vadim Gladyshev, and colleagues from Harvard Medical School — built models that respond to interventions. Caloric restriction slows the "molecular aging" of mitochondrial and metabolic modules, while chronic diseases accelerate the inflammatory one. Even in cell culture, stress from prolonged passaging or irradiation reproduces the same mortality signatures.
In an accompanying News & Views, João Pedro de Magalhães notes that the markers may help understand which processes a given intervention regulates. However, the question of causality remains open — whether these changes are drivers of aging or merely its consequences. Additional experiments are required.
Imagine a car where instead of a single odometer, individual indicators light up on the dashboard: "brake wear," "cooling problems," "oil leak." Transcriptomic clocks provide exactly such a picture — not overall mileage, but specific "breakdowns" in the body's molecular machinery.
The study shows that aging in mammals has common molecular features despite the huge differences in lifespan. This narrows the range of potential targets for interventions, but at the same time emphasizes that prediction accuracy does not yet equal understanding of the mechanism and the ability to reliably modify it.
