How the epigenetic clock works

Biological age often differs significantly from chronological age: one person at the age of 70 may maintain health and stamina comparable to someone much younger, while another at the same age of 70 faces pronounced fragility and multiple age‑related disorders. To detect this difference, epigenetic clocks are used, which measure DNA methylation — chemical changes that do not affect the gene sequence itself but regulate which genes are active and which are turned off. The совокупности of such changes is called the epigenome, and its analysis helps predict health problems and even the risk of death better than chronological age alone.

Until recently, it remained unclear which specific biological processes underlie the accuracy of these tools. The team studied blood samples from 3,227 participants in the Health and Retirement Study in the United States, comparing DNA methylation patterns with gene expression—that is, with how actively genes are transcribed into RNA and participate in protein synthesis. The совокупности of all transcriptional processes in a cell is called the transcriptome.

It turned out that different epigenetic clocks are associated with different biological mechanisms. Some reflect processes related to energy balance and cell growth, while others reflect the activation of immune cells and inflammatory signaling pathways. At the same time, all clocks have common features: they record changes in the immune system, metabolism, and intercellular communication — key aspects of aging.

Based on these data, researchers have developed new tools — transcriptomic aging assessments. The combined approach, which integrates epigenetic and transcriptomic data, provides a more complete picture of a person’s biological state. In some cases, TAGS predicted outcomes such as frailty, walking speed, cardiovascular diseases, diabetes, lung diseases, and even death more accurately than epigenetic clocks alone.

The practical value of the work lies not only in the creation of more accurate predictive tools but also in the fact that it helps researchers choose the appropriate type of clock for specific tasks. For example, some time points may be optimal for studying therapies targeting the immune system, while others may be better suited for evaluating drugs that affect metabolism or slow down the loss of physiological resilience.

According to researchers, uncovering the molecular programs behind these biomarkers increases their interpretability and paves the way for their application in gerontology, epidemiology, and, in the long term, in clinical practice. Now, experts are not just recording biological age — they have a better understanding of which processes in the body determine the rate of aging and the risk of age‑related diseases.