DNA “Chaos” Reveals Secrets of Aging

Researchers Jonathan Chan, Liudmilla Rubbi, and Matteo Pellegrini from the University of California, Los Angeles, have developed a new method to measure changes in DNA that can help predict a person’s biological age. Their study, published in the journal Aging, introduces a metric called methylation entropy, which captures how randomly chemical tags, known as DNA methylation marks, are distributed across the genome over time.

Unlike traditional epigenetic clocks that estimate age based on average DNA methylation levels, this method focuses on the degree of disorder in methylation patterns, offering a new perspective on how aging affects the genome. The researchers found that methylation entropy performed as well as, or better than, existing age prediction models.

To test their approach, the team analyzed DNA from buccal swabs (cheek cells) of 100 individuals ranging in age from 7 to 84. Using targeted bisulfite sequencing, they measured methylation entropy across 3,000 specific regions of the genome. Their findings suggest that increased variability in DNA methylation is closely linked to aging and may provide valuable insights for studying age-related diseases.

Entropy in this context reflects how disordered or varied the methylation patterns are at certain sites on the DNA. The researchers discovered that as people age, the entropy of methylation at many locations changes in a reproducible way. Sometimes it increases, reflecting more random patterns, and sometimes it decreases, showing more uniformity. These shifts are not always tied to how much methylation is happening, which suggests entropy provides new information beyond what traditional methods can offer.

To test how well this new metric could predict age, the team used both statistical and machine learning models. They found that methylation entropy predicted age as accurately as traditional methods, and the best results came from combining entropy with other measurements like average methylation and a method called CHALM. These combined models were able to estimate age with an average error of just five years.

According to the researchers, “[…] methylation entropy is measuring different properties of a locus compared to mean methylation and CHALM, and that loci can become both more or less disordered with age, independently of whether the methylation is increasing or decreasing with age.”

This research supports the growing theory that aging is partly caused by a gradual loss of epigenetic information—the biological “instructions” that help keep our cells working properly. This insight also connects with recent studies suggesting that restoring this lost information might reverse some signs of aging. While more research is needed to study methylation entropy in other tissues, this work points to a more precise and powerful way to measure biological aging, which could influence the future of aging-related treatments and therapies.

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