For years, epigenetic clocks have promised to reveal whether a person is aging faster or slower than the calendar suggests. Now, a new study is showing that these widely used biological-age tests are not all measuring the same thing. Instead, each clock appears to capture a different combination of molecular processes linked to aging, including immune activity, metabolism, cellular growth and inflammation.
The findings, reported in npj Aging, offer one of the clearest examinations yet of what happens beneath the surface of epigenetic aging measurements. Researchers led by T. Em Arpawong of the USC Leonard Davis School of Gerontology analyzed blood samples from 3,227 participants in the U.S. Health and Retirement Study. They compared five commonly used epigenetic clocks with patterns of gene expression, seeking to identify the biological pathways that make the clocks useful predictors of health and survival.
Epigenetic clocks estimate biological age by examining DNA methylation, a chemical modification attached to DNA. Methyl groups can influence whether genes are more or less active without changing the underlying genetic sequence. As people age, methylation patterns shift across the genome. Some changes are associated with the passage of time, while others appear to reflect disease, stress, inflammation, lifestyle or changes in the proportions of different cell types found in blood.
A clock converts these methylation patterns into a numerical estimate. The result is often compared with a person’s chronological age to produce an acceleration or deceleration score. Someone whose biological-age estimate is higher than expected may be experiencing molecular changes associated with poorer health, while a lower estimate may indicate a more favorable aging profile. Yet the number itself does not directly measure the age of every cell in the body, nor does it provide a single, universal readout of aging. It is a statistical biomarker built from molecular patterns.
That distinction has been central to the field’s rapid growth. Earlier studies showed that some epigenetic clocks can predict frailty, chronic disease and mortality more effectively than chronological age alone. But the biological reasons for their predictive power have remained difficult to decipher. A clock might be responding to immune-cell changes, altered metabolism, inflammation or other processes without revealing which of those mechanisms is most important.
To investigate that hidden biology, the USC-led team examined gene expression alongside DNA methylation. Gene expression describes how frequently information in DNA is copied into RNA, which can then be used to produce proteins. The complete collection of RNA transcripts being produced in a cell or tissue at a given moment is known as the transcriptome. Unlike DNA methylation, which records regulatory marks on the genome, transcriptomic data provide a more immediate view of which biological programs are active.
The comparison revealed striking differences between the five clocks. Each one was linked to a distinctive set of biological pathways. Some were associated more strongly with energy balance and cellular growth, while others reflected immune-cell activation or inflammatory signaling. The clocks were therefore not interchangeable molecular thermometers. They overlapped in several broad themes, particularly immune-system changes, metabolism and communication between cells, but each emphasized a different biological profile of aging.
Those shared themes are significant because they represent core features of biological aging. The immune system often becomes less coordinated with age, responding less effectively to new threats while maintaining higher levels of chronic, low-grade inflammation. Metabolic regulation can also deteriorate, affecting how cells process nutrients and generate energy. At the same time, communication among cells may become disrupted, weakening tissue repair and the body’s ability to maintain physiological stability.
The researchers then used the combined methylation and gene-expression analysis to create a new class of biomarkers called transcriptomic aging gene scores, or TAGS. Rather than relying only on methylation marks, these scores summarize the activity of genes associated with aging-related pathways. In the study, adding TAGS to existing epigenetic measurements produced a clearer picture of biological health and, in several analyses, improved predictions of frailty, walking speed, heart disease, diabetes, lung disease and mortality.
The results do not mean that gene-expression scores will immediately replace epigenetic clocks, or that either type of test can determine an individual’s future with certainty. The study was based on statistical associations in blood samples, and blood is only one tissue in the body. Gene activity and methylation can also be influenced by temporary illness, medications, smoking, obesity, immune-cell composition and other factors. More research will be needed to test how well the findings apply across populations, tissues and clinical settings, and whether changing a clock score through treatment actually improves health.
The practical implication is that researchers may need to choose aging biomarkers according to the question they are asking. A clock connected strongly with immune pathways could be useful for evaluating an anti-inflammatory or immune-modulating therapy. Another may be more informative for research on metabolic health, cellular resilience or interventions designed to preserve physical function. Combining epigenetic and transcriptomic measurements could also help distinguish a general aging signal from the specific biological process driving an individual’s risk.
By linking methylation patterns to active gene programs, the study begins to open the black box surrounding biological-age clocks. Its central message is that “biological age” is not one hidden number waiting to be discovered. It is a collection of interacting processes, and different clocks illuminate different parts of that system. As these tools move closer to potential clinical use, understanding what they measure may be just as important as knowing how accurately they predict disease or death.
Subject of Research: People
Article Title: How epigenetic clocks tick: unpacking the black box by deciphering biological pathways and transcriptomic signatures of accelerated aging
News Publication Date: 20-Jul-2026
Web References: https://www.nature.com/articles/s41514-026-00446-x; https://gero.usc.edu/faculty/arpawong/
References: npj Aging. DOI: 10.1038/s41514-026-00446-x
Keywords: Epigenetic clocks, biological aging, DNA methylation, epigenetics, gene expression, transcriptomics, transcriptomic aging gene scores, biomarkers, aging research, mortality, frailty, inflammation, metabolism, genomics
