A unifying model of stem cell dynamics explains age-related methylation patterns across mammals.
basic_science · Level V
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- Record sourced from PubMed, PMID 42156953.
- Also identified by DOI 10.1038/s43587-026-01125-y.
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Abstract
DNA methylation changes are reliable biomarkers of aging, but the driving mechanisms remain poorly understood. Here we present SCARLET (Stem Cells and Age-ReLated Epigenetic Trajectories), a parsimonious mathematical model that describes how methylation changes in blood arise and propagate through hematopoietic stem cell divisions. Using a large human cohort, we demonstrate that seemingly distinct age-related methylation patterns can be explained by a unifying mechanistic model. We show that SCARLET captures known drivers of epigenetic aging, with accelerated individuals showing reduced ratios of stem cell pool size to division rate (N/s). Applying SCARLET to methylation data from 11 mammalian species reveals that N/s scales with maximum lifespan, suggesting that evolutionary adjustments to stem cell dynamics, rather than epigenetic maintenance efficiency, drive the previously observed relationship between methylation rates and lifespan. Our findings provide a quantitative framework for understanding epigenetic aging and suggest that stem cell dynamics may be a key driver of aging across mammals.