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An international team of researchers has identified universal gene-expression patterns linked to aging and mortality that are shared across mice, rats, macaques, and humans, publishing their findings in Nature this week.nature
The study, led by Alexander Tyshkovskiy of Brigham and Women’s Hospital and Harvard Medical School, analyzed more than 11,000 transcriptomes from over 25 tissues in four mammalian species. The researchers found that aging-associated changes to gene activity are conserved across species and cell types, then used those patterns to build molecular “clocks” capable of estimating biological age and predicting expected mortality.sciencemediacentre
“The same genes are associated with aging in, for example, liver and heart in rats and humans,” Tyshkovskiy told Scientific American. The results suggest aging is a “very systemic process,” affecting different tissues, cell types, and species in similar ways, he said.scientificamerican
The team found that genes involved in inflammatory, immune-activation, and cellular stress pathways increased with age, while those tied to mitochondrial energy production and wound healing declined. In humans, the clocks predicted time to death from any cause among participants in a large heart-health study, with accuracy comparable to second-generation epigenetic clocks.nature
The clocks also incorporated data from rodents treated with dozens of genetic, dietary, and pharmacological interventions known to affect aging and lifespan, capturing the effects of measures that accelerated or slowed biological aging.nature
David Sinclair, a prominent aging researcher, praised the work. “They developed transcriptomic clocks that don’t just estimate age, they measure the progressive loss of cellular function and predict biological decline and mortality risk across mammals,” he said.scientificamerican
Unlike earlier epigenetic clocks based on DNA methylation, these transcriptomic clocks directly measure gene activity, potentially offering a more functional readout of the biological processes driving aging. Researchers say the approach could expedite development of anti-aging interventions by providing a faster way to assess whether experimental treatments are truly slowing aging at the molecular level.nature