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In this issue, three studies examine the contribution of stochastic epigenetic changes to DNA methylation clocks. Tarkhov et al., Meyer et al. and Tong et al. take different approaches to addressing this question, and concur that stochasticity is involved in epigenetic aging. The cover, from Meyer et al., shows a Galton board, which is a device used to illustrate concepts of probability and stochasticity. At the top, a series of small balls are released, which follow a random path before landing in bins at the bottom. Over many trials, this stochastic process leads to the formation of a normal distributed shape. A clock is depicted within this shape to illustrate that a completely stochastic process can be used to construct aging clocks, consistent with a role of age-dependent increases in stochastic variation in epigenetic processes.
Artificial intelligence (AI) chatbots offer the potential to enhance many aspects of social care for older adults, but also pose ethical risks. This Comment explores the responsible use of AI chatbots, which recognizes the distinct features of social care provision.
A study in Nature Aging on electronic health records from 1.7 million people in New Zealand reveals that most patients with dementia have a history of hospital-treated infection. In a dementia-free population, individuals with a severe infection were at a threefold-higher risk of dementia even 25 years later.
Aging-related DNA methylation changes are numerous. Their precise measurement has opened new avenues to explore aging-related disease pathology, including the construction of chronological and biological age predictors (termed DNA methylation ‘clocks’). Three studies investigate the substantial stochastic contribution to these epigenetic changes and further our understanding of aging biology, as well as of these predictors.
Small extracellular vesicles (sEVs) derived from the blood of young mice are shown to have the potential to extend lifespan and rejuvenate physiological functions in aged mice. Mechanistically, microRNA (miRNA) cargoes within these sEVs alleviated age-related dysfunction by promoting the expression of PGC1α and enhancing mitochondrial energy metabolism.
Cellular senescence is a hallmark of aging but also a potent tissue remodeling process. Here, Nehme et al. show that modulating poly (ADP-ribose) polymerase 1 can switch cell death into senescence, and that inducing senescence improves recovery from kidney ischemia–reperfusion injury.
In this nationwide administrative register study, individuals diagnosed with infections were three times more likely to be diagnosed with dementia up to 30 years later. Preventing infections might reduce the burden of neurodegenerative conditions.
Moses, Atlan et al. profile the killifish (Nothobranchius furzeri) gonad using single-cell sequencing and reveal that genetic germline depletion induces sexually dimorphic phenotypes, enhancing lifespan in male fish and somatic repair in females.
Circulating factors have an important role in aging. Here the authors show that small extracellular vesicles derived from young plasma rejuvenate whole-body physiology in aged mice, at least in part, by stimulating PGC-1α expression and improving mitochondrial energy metabolism.
Thermogenic beige adipose tissue can enhance energy expenditure and improve metabolism, but its formation declines with age. Park, Hu et al. show that replenishing estrogen can restore cold-induced beige adipogenesis by regulating NAMPT-controlled ER stress.
At single-cell resolution, Tarkhov et al. delineate stochastic and co-regulated components of epigenetic aging, revealing a simultaneous loss of regulation at the epigenetic and transcriptional levels in aging.
Meyer and Schumacher use simulations to show that accumulation of stochastic variation is sufficient to build clocks that can measure both chronological and biological age, sensitive to changes induced by smoking, calorie restriction, parabiosis and reprogramming.
Tong et al. construct simulations using DNA methylation data to quantify what proportion of the predictive accuracy of epigenetic clocks could be explained by stochastic methylation changes, suggesting that stochasticity contributes more toward the accuracy of chronological rather than biological age predictions.