In late 2021 a Russian-born billionaire named Yuri Milner gathered some of the most celebrated scientific minds of our time at his lavish US$100-million-dollar mansion in California. The topic of conversation was reversing aging. Could our cells be reprogrammed into a younger state? And, perhaps most importantly for the aging billionaire, how quickly could this technology be developed?
The unusual event resulted in the development of Altos Labs, a biotech startup with aspirations to produce an anti-aging treatment that can extend human life. By the next year Altos Labs had amassed around $3 billion dollars in funding, with figures including Jeff Bezos dropping cash into the fund.
One of the key research areas Altos Lab is focusing on is reversing aging by removing the epigenetic markers that accumulate on cells as time passes. Based on the landmark findings of Shinya Yamanaka in 2006, the idea is that four key proteins can be used to send a cell back to its embryonic state, essentially removing all biomarkers of aging.
A new study from a team of biologists and epidemiologists at UC San Diego is calling into question this core foundation of much anti-aging research. The findings suggest a focus on reversing epigenetic markers may be the wrong approach for trying to reverse aging, and a competing hypothesis around the relationship between aging and DNA mutations may be a better approach.
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Paywalled Paper:
Somatic mutation as an explanation for epigenetic aging
DNA methylation marks have recently been used to build models known as epigenetic clocks, which predict calendar age. As methylation of cytosine promotes C-to-T mutations, we hypothesized that the methylation changes observed with age should reflect the accrual of somatic mutations, and the two should yield analogous aging estimates. In an analysis of multimodal data from 9,331 human individuals, we found that CpG mutations indeed coincide with changes in methylation, not only at the mutated site but with pervasive remodeling of the methylome out to ±10 kilobases. This one-to-many mapping allows mutation-based predictions of age that agree with epigenetic clocks, including which individuals are aging more rapidly or slowly than expected. Moreover, genomic loci where mutations accumulate with age also tend to have methylation patterns that are especially predictive of age. These results suggest a close coupling between the accumulation of sporadic somatic mutations and the widespread changes in methylation observed over the course of life.