A unifying model of stem cell dynamics explains age-related methylation patterns across mammals

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. A parsimonious model of stem cell dynamics describes how DNA methylation changes arise and propagate with age, unifying diverse epigenetic aging patterns and suggesting that stem cell dynamics are a key driver of aging across mammals.