Can random changes over time effectively predict aging?

New research shows that stochastic variation alone could create aging clocks that correlate with actual biological age.

We all witness aging in different ways – the fraying threads of muscle and memory that come undone as time passes. But not everyone ages in a similar fashion, and while some aging is due to the body’s reduced capacity for repair, some is due to an accumulation of unpredictable, stochastic damages.

Aging is influenced by factors like oxidative stress, environmental exposure, and other biological processes that damage cells over time. This cellular damage increases the risk of age-related conditions such as cardiovascular disease, diabetes, and neurological disorders.

In recent years, researchers have developed aging clocks to measure biological age. One of the earliest, created in 2011, analyzed cytosine phosphate guanine (CpG) islands, which reveal different aspects of health. These advancements have led to the question: Is aging simply the result of random, unpredictable events?

My take on this: Epigenetic drift may sound like a progressive rock concept album from the Seventies, but it refers to the gradual and often age-related changes in DNA methylation patterns that occur over time. Often caused by the imperfect preservation of epigenetic markers over time, this drift can lead to a loss of distinct methylation patterns between genomic regions, which were initially established during early development. Such changes can affect gene expression and are thought to contribute to aging and age-related diseases.

Epigenetic clocks, therefore, seek to map these changes, predicting how close a biological system might be to aging milestones. Across species, epigenetic drift is consistent, with about 30% of the mouse genome showing age-linked epigenetic alterations – a promising foundation for building biological clocks.

A recent study in Nature Aging explored whether random changes in cells, known as stochastic variation, could serve as reliable aging clocks. Researchers found that even small amounts of this random cellular damage could accurately predict age-related changes across different species, including C. elegans worms. In fact, the study successfully linked these variations to biological age in nearly 1,000 independent C. elegans RNA samples.

The findings suggest that as stochastic variation increases, the aging process accelerates. However, a slight reduction in this damage—similar to slowing the breakdown of cells – was shown to slow down aging. The study also demonstrated that these aging clocks could measure the impact of treatments designed to slow biological aging, highlighting their potential for evaluating anti-aging therapies. In the case of C. elegans, the clocks were able to predict both chronological age and the effects of a drug that decelerated biological aging, offering a promising way to track the success of such interventions.

Discover more details about this study HERE .

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