Scientists Develop a 'Molecular Clock' to Predict Mammalian Aging and Lifespan
Release time:
2026-05-29
Aging is a gradual process of cellular damage accumulation and functional decline, ultimately leading to the end of life. Yet among individuals of the same chronological age, some remain robust while others suffer from illness — a disparity that fundamentally stems from differences in the pace of aging at the molecular level. For a long time, scientists have sought to create a 'molecular ruler' capable of accurately quantifying these differences, but existing technologies have always had limitations.
On May 27, the journal Nature published a breakthrough study: a team led by Alexander Tyshkovskiy and Vadim Gladyshev at Harvard Medical School has developed a novel 'molecular clock.' By analyzing gene transcriptome data, this clock can not only accurately estimate the molecular age of various mammals but also predict their remaining lifespan. The study, based on analyses of over 11,000 samples spanning 25 tissue types from humans, mice, rats, and rhesus macaques, reveals conserved features of aging across species and provides a powerful new tool for intervention research aimed at slowing aging.
Traditional 'aging clocks' have largely relied on epigenetic modifications, such as DNA methylation — chemical marks that affect gene activity without altering the gene sequence. However, these methods cannot directly reflect changes in the expression of specific genes, akin to 'only looking at the edits in a manual without knowing how the internal parts of a machine actually work,' making the results difficult to interpret.
The new study takes a different approach, focusing on gene transcripts (i.e., the 'working copies' of genes). The team discovered that with age, genes associated with cellular senescence (decline in division capacity), inflammation, and programmed cell death (apoptosis) are generally 'upregulated' (increased activity) across multiple tissues, while genes involved in wound healing, cell differentiation, and extracellular matrix synthesis are 'downregulated' (decreased activity). These patterns are highly conserved across mice, rats, rhesus macaques, and humans, serving as universal 'aging biomarkers' across species.
Based on these biomarkers, the team constructed a multi‑tissue, multi‑species 'molecular clock' model. Validation showed that its accuracy in predicting time of death is comparable to leading second‑generation epigenetic clocks, but with a significant advantage: transcriptomic data can capture real‑time changes in gene activity, like 'instantly monitoring the operating status of a machine' rather than merely recording static 'edits to a manual.' This means it can rapidly evaluate the effects of lifespan‑extending interventions (such as drugs or dietary adjustments) — for instance, whether a given therapy truly slows aging at the molecular level.
In a companion commentary also published in Nature, researchers note that this framework 'can help scientists identify which biological processes are affected by interventions or diseases,' addressing a gap in existing technologies. However, they also caution that the causal relationship between the identified biomarkers and aging remains unclear — are they the 'cause' or the 'effect' of aging? Further clarification is needed.
The road from the laboratory to clinical application is still long. But the advent of this 'molecular clock' has opened a new window for understanding aging and developing targeted longevity strategies. As the researchers themselves put it: 'It not only helps us better understand aging but also brings us one step closer to the goal of healthy aging.'
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