DNA Methylation Entropy: A New Way to Track and Predict Aging
04-16-2025"We find that epigenetic clocks based on the entropy of methylation states predict chronological age with similar accuracy as common approaches that are based on methylation levels of individual cytosines."
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BUFFALO, NY — April 16, 2025 — A new research paper was published in Aging (Aging-US) Volume 17, Issue 3, on March 12, 2025, titled “DNA methylation entropy is a biomarker for aging.”
Researchers Jonathan Chan, Liudmilla Rubbi, and Matteo Pellegrini from the University of California, Los Angeles, led a study that discovered a new way to measure changes in DNA that can help predict a person’s age. This method focuses on how random certain chemical tags on DNA become over time. The team compared this new measurement, called methylation entropy, to existing methods and found it performed just as well—or even better. These findings support the idea that changes in our epigenetic information are closely linked to aging and could offer new tools for studying age-related diseases.
The study focused on DNA methylation, a process where chemical marks are added to DNA and help control which genes are turned on or off. Scientists have traditionally measured average methylation levels to estimate biological age using “epigenetic clocks.” This study, however, takes a different approach. The researchers used buccal swabs (cells from inside the cheek) from 100 individuals between ages 7 and 84 and applied targeted bisulfite sequencing techniques to measure methylation entropy across 3,000 regions of the genome.
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.
"[...] 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.
Read the full paper: DOI: https://doi.org/10.18632/aging.206220
Corresponding author: Matteo Pellegrini - matteope@gmail.com
Keywords: aging, entropy, DNA methylation, aging, epigenetics, epigenetic clocks
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