HMN 2026: How Gene activity clocks estimate lifespan across species, matching epigenetic tools

Molecular clocks that can provide accurate estimates of both molecular age and lifespan across multiple mammalian species and tissue types are presented in an article published in Nature this week. An analysis of more than 11,000 human, rodent, and primate samples reveals conserved signatures of aging. This framework may aid the development of targeted interventions to improve longevity.

Aging is characterized by the accumulation of cellular damage and functional decline, eventually leading to death. Individuals with the same chronological age may age differently on a molecular level, and identifying biomarkers associated with these differences has long interested researchers. Existing methods involve analyzing epigenetic modifications (non-genetic alterations) to an individual’s DNA over time, known as their epigenetic clock. However, these clocks can still be difficult to interpret as they do not reflect the activity of specific genes.

Alexander Tyshkovskiy, Vadim Gladyshev and colleagues have analyzed more than 11,000 genetic transcripts (transcriptomic signatures) from more than 25 tissue types from mice, rats, macaques, and humans. Aging-related changes to the transcriptome were conserved across species and cell types, enabling the identification of several biomarkers of mammalian aging.

Genes associated with senescence (the decline of cell division), inflammation and apoptosis (programmed cell death) were upregulated in aging cells. Genes associated with wound healing, cell differentiation and extracellular matrix synthesis were downregulated across species and cell types with chronological aging.

The authors used these data to develop their own multi-tissue and multi-species molecular clocks to both assess chronological age and predict expected mortality. These models were validated using statistical approaches and against existing animal and cellular models of aging. The clocks predicted time to death with accuracy comparable to second-generation epigenetic clocks. The real-time nature of transcriptomes over epigenetic data also enables the efficacy of life-extending interventions to be assessed on a molecular level.

In an accompanying News & Views article, João Pedro de Magalhães notes that the markers identified in this study “could help researchers to pinpoint which processes are modulated by interventions or diseases,” a valuable measure that is not visible through existing methods. However, further research is needed to disentangle exactly how these biomarkers are related to aging and whether they are causative or simply by-products of the process.

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