Researchers at Hebrew University leveraged a deep learning network to analyze DNA methylation patterns, achieving a time series age (defined as postnatal time) with median accuracy for individuals under 50 years, ranging from 1.36 to 1.7 years. result This work will be published in the journal Cell Report.
Utilizing ultra-depth sequences from over 300 blood samples of healthy individuals, the research indicates that age-dependent methylation changes happen in a probabilistic or coordinated block-like fashion across clusters of CPG sites. Image credit: Ochana et al., doi: 10.1016/j.celrep.2025.115958.
“We observe that our DNA leaves measurable marks over time,” commented Professor Tommy Kaplan from Hebrew University.
“Our model interprets these marks with remarkable precision.”
“The essence lies in how our DNA evolves through a process known as methylation – the chemical tagging of DNA by methyl groups (CH)3.
“By focusing on two vital regions of the human genome, our team successfully decoded these changes at the level of individual molecules, employing deep learning to generate accurate age estimations.”
In this research, Professor Kaplan and his team examined blood samples from over 300 healthy subjects and analyzed data from a decade-long study of the Jerusalem Perinatal Study.
The model developed by the team showed consistent performance across various factors, including smoking, weight, gender, and diverse indicators of biological aging.
In addition to potential medical applications, this technique could transform forensic science by enabling experts to estimate the age of suspects based on DNA traces.
“This provides us with a new perspective on cellular aging,” stated Yuval Dor, a professor at Hebrew University.
“It’s a striking example of the intersection between biology and artificial intelligence.”
Researchers found new patterns in DNA alterations over time, suggesting that cells encode both mature and tuned bursts, akin to biological clocks.
“It’s not solely about knowing your age,” explained Professor Ruth Shemmer of Hebrew University.
“It’s about comprehending how cells and molecules keep track of time.”
“This research could redefine our approach to health, aging, and identity,” added the scientist.
“From assisting physicians in treatment based on an individual’s biological timeline to equipping forensic investigators with advanced tools for crime-solving, the capability to decipher age from DNA paves the way for groundbreaking advancements in science, medicine, and law.”
“Moreover, it enhances our understanding of the aging process and brings us closer to unraveling our body’s internal clock.”
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Bracha-Lea Ochana et al. Time is encoded by changes in methylation at clustered CPG sites. Cell Report Published online on July 14th, 2025. doi:10.1016/j.celrep.2025.115958
Source: www.sci.news
