Human Epigenetic Aging is Logarithmic with Time Across the Entire Lifespan
It is well established that organisms undergo epigenetic changes both during development and aging. Developmental changes have been extensively studied to characterize the differentiation of stem cells into diverse lineages. Epigenetic changes during aging have been characterized by multiple epigenetic clocks, that allow the prediction of chronological age based on methylation status. Despite their accuracy and utility, epigenetic age biomarkers leave many questions about epigenetic aging unanswered. Specifically, they do not permit the unbiased characterization of non-linear epigenetic aging trends across entire life spans, a critical question underlying this field of research. Here we a provide an integrated framework to address this question. Our model, inspired from evolutionary models, is able to account for acceleration/deceleration in epigenetic changes by fitting an individuals model age, the epigenetic age, which is related to chronological age in a non-linear fashion. We have devised a two stage procedure leveraging these model ages to infer aging trends over the entire lifespan of a population. Application of this procedure to real data measured across broad age ranges, from before birth to old age, and from two tissue types, suggests a universal logarithmic trend characterizes epigenetic aging across entire lifespans. This observation may have important implications for the development and application of future, more accurate, aging biomarkers.