Extracellular Vesicles and Epigenetic Aging Clocks in Tissue Aging: An Exosome-Focused Conceptual Framework with a Focus on Skin.

Authors

Zeynep Yaren Dinçer, Kaan Zikşahna, Murat Ihlamur

Published in

The journals of gerontology. Series A, Biological sciences and medical sciences. Jul 17, 2026. Epub Jul 17, 2026.

Abstract

Tissue aging is a multifactorial process characterized by cellular senescence, disrupted intercellular communication, and epigenetic alterations, with skin providing a clinically accessible and biologically informative model system. Exosomes and other extracellular vesicles (EVs) are increasingly recognized as mediators of aging-related signalling, whereas DNA methylation-based aging clocks offer quantitative measures of biological age. In this narrative review, we examine the potential interplay between EV/exosome biology and epigenetic aging clocks across tissue-aging contexts, while using skin aging as a primary focus and illustrative model. We review evidence from studies of keratinocytes, dermal fibroblasts, mesenchymal stromal cells, and aging-associated EV cargo, distinguishing studies with direct DNA methylation age readouts from those reporting indirect epigenetic effects. Current evidence indicates that EVs/exosomes from aged or senescent cells may disseminate pro-aging and inflammatory signals, whereas vesicles from young or regenerative sources may support repair and tissue homeostasis. Nevertheless, direct evidence that EVs alter skin epigenetic clock measures remains scarce. In particular, direct experimental evidence demonstrating that aged-cell-derived EVs or exosomes alter DNA methylation clock readings in human keratinocytes or dermal fibroblasts is currently lacking. We propose that skin serves as a useful model for investigating how extracellular signalling interfaces with epigenetic aging dynamics. Therefore, the proposed exosomal-epigenetic clock feedback-loop framework should be interpreted as a hypothesis-generating conceptual model rather than as a validated mechanistic pathway.

PMID:
42467831
Bibliographic data and abstract were imported from PubMed on 18 Jul 2026.

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