A large-scale multi-omics study maps why the epigenetic clock captures different aspects of aging and shows how gene expression scores sharpen the interpretation.
Research: How the epigenetic clock ticks: Unpacking the black box by deciphering the biological pathways and transcriptomic signatures of accelerated aging. Image credit: Lightspring / Shutterstock
In a recent study published in the journal npj agingA group of researchers identified biological pathways and gene expression signatures associated with the widely used epigenetic clock and assessed how the Transcriptome Aging Gene Score (TAGS) is associated with aging-related health outcomes.
background
Why do some people remain healthier than others despite being the same age? This difference may be due to biological aging rather than chronological age.
Scientists use epigenetic clocks to measure the rate at which the human body ages. Epigenetic clocks can predict health risks more accurately than chronological age, but the biological processes underlying their predictions remain unclear. These clocks measure age-related DNA methylation patterns that may be related to gene activity.
Examining the relationship between epigenetic clocks and gene activity may improve our understanding of their biological interpretation.
About research
The researchers analyzed data from participants enrolled in the HRS venous blood study, focusing on participants for whom both DNAm and RNA-seq data were available. Of the 4,018 participants with DNAm results, 3,227 were studied as complete transcriptome and covariate data were available.
To develop and internally evaluate the transcriptome score, the analyzed samples were randomly divided into two sets. One is 80% of the total sample, one is 20% of the total sample, and one is the holdout test set. In this study, we analyzed five epigenetic clocks: Horvath, Hannum, PhenoAge, GrimAge, and DunedinPACE.
Using the training dataset, the researchers performed differential gene expression (DGE) analysis to identify genes whose expression levels were associated with each epigenetic age-acceleration indicator.
The resulting gene list was analyzed using GSEA to identify biological pathways associated with each clock. This analysis also addressed similarities and differences in shared and specific pathways among the five clocks.
Finally, the researchers developed TAGS from differentially expressed genes (DEGs) and evaluated the relationship between epigenetic age acceleration indicators and multiple aging-related health outcomes in a holdout test dataset.
In this study, we assessed the transferability of transcriptome scores by comparing them with parental epigenetic clocks and available disease-related outcomes across three external datasets.
Research results
The analysis revealed significant differences in the molecular signatures expressed by the five epigenetic clocks. The number of DEGs varied considerably, from 49 in the Horvath clock to 3,204 in DunedinPACE. These differences did not correspond to the number of CpGs in each clock. This indicates that a larger clock does not necessarily capture more gene expression changes.
There are no DEGs shared by all five clocks, and DunedinPACE has the highest proportion of unique DEGs, suggesting that each clock captures different processes in biological aging. The greatest overlap in DEGs was observed between second and third generation clocks, especially GrimAge, PhenoAge, and DunedinPACE.
Further analysis showed that the biological pathways associated with the clock were also markedly different. DunedinPACE had the most associated pathways, while Horvath had the least. Although there were no Reactome biological pathways common to all clocks, several immune-related pathways such as neutrophil degranulation, innate immune system signaling, and immune system signaling were shared by Hannum, PhenoAge, GrimAge, and DunedinPACE.
Additionally, pathways associated with antibacterial activity were observed in a subset of clocks. Analysis of each clock revealed distinct biological pathways enriched with genes. The Horvath clock was associated with pathways involved in metabolism and signal transduction, while the Hannum clock was associated with homeostasis and vascular wall processes.
The GrimAge clock is associated with interferon signaling, whereas the PhenoAge clock is associated with cellular aging pathways, and the DunedinPACE clock is associated with various biological pathways such as protein metabolism, immune signaling, nervous system development, and cellular respiration.
Examining a broader range of gene ontology (GO) biological processes reveals greater overlap between clocks than individual pathways. This analysis revealed four major functional themes: metabolic and macromolecular processes, developmental processes, immune system function, and regulatory and signaling pathways. This indicates that although clocks have distinct molecular features, they share some broad biological processes associated with aging.
The researchers then developed TAGS for each clock and tested their associations with aging-related outcomes. Each TAGS score was positively correlated with its corresponding epigenetic clock, with the strongest correlation observed for DunedinPACE. In some cases, TAGS showed greater associations with aging-related measures than the original epigenetic clock.
Stronger associations were found for mortality, frailty, ADL, walking speed, heart problems, diabetes, lung problems, telomere length, and interleukin-6. TAGS was not a significant predictor of psychological problems, but its associations with grip strength, cognitive performance, and interleukin-10 were mixed.
Validation in external datasets yielded comparable but variable correlations with parental epigenetic clocks and associations with disease-related outcomes, providing preliminary support for the transmissibility of transcriptome scores.
conclusion
This study shows that known epigenetic clocks are not a single universal aging mechanism but is associated with a variety of biological pathways, and that measures of epigenetic acceleration of aging are associated with gene expression patterns in the blood, helping to elucidate the biological interpretation of clocks.
TAGS complemented existing epigenetic clocks and in some cases showed stronger associations with aging-related diseases, physical function, and mortality. Because the analysis used blood samples primarily from older Caucasian adults and the TAGS test used holdout samples from the same cohort, further validation in a diverse, independent population is required before clinical use.
These results make the epigenetic clock more biologically interpretable and support its application in aging research and future validation studies.
Reference magazines:
- Arpawong, T. E., Cole, S., Badhesha, H., Kim, J. K., Beam, C. R., Klopack, E. T., Siegmund, K., Thyagarajan, B., and Crimmins, E. M. (2026). How the epigenetic clock ticks: Unpacking the black box by deciphering the biological pathways and transcriptomic signatures of accelerated aging. npj aging. Doi: 10.1038/s41514-026-00446-x, https://www.nature.com/articles/s41514-026-00446-x
