Many chronological aging clocks can be found throughout the epigenome: Implications for quantifying biological aging

Epigenetic alterations are a hallmark of aging and age‐related diseases. Computational models using DNA methylation data can create “epigenetic clocks” which are proposed to reflect “biological” aging. Thus, it is important to understand the relationship between predictive clock sites and aging biology. To do this, we examined over 450,000 methylation sites from 9,699 samples. We found ~20% of the measured genomic cytosines can be used to make many different epigenetic clocks whose age prediction performance surpasses that of telomere length. Of these predictive sites, the average methylation change over a lifetime was small (~1.5%) and these sites were under‐represented in canonical regions of epigenetic regulation. There was only a weak association between “accelerated” epigenetic aging and disease. We also compare tissue‐specific and pan‐tissue clock performance. This is critical to applying clocks both to new sample sets in basic research, as well as understanding if clinically available tissues will be feasible samples to evaluate “epigenetic aging” in unavailable tissues (e.g., brain). Despite the reproducible and accurate age predictions from DNA methylation data, these findings suggest they may have limited utility as currently designed in understanding the molecular biology of aging and may not be suitable as surrogate endpoints in studies of anti‐aging interventions. Purpose‐built clocks for specific tissues age ranges or phenotypes may perform better for their specific purpose. However, if purpose‐built clocks are necessary for meaningful predictions, then the utility of clocks and their application in the field needs to be considered in that context. Epigenetic clocks show promise as a biomarker of aging. Our study identifies components of epigenetic clocks critical to understanding their uses and where improvements are still needed. We identified a parabolic trajectory of methylation aging and the extent to which epigenetic clocks are robust to removing the most age‐predictive loci. These data shape our understanding of epigenetic age acceleration and what epigenetic clocks can tell us about the biology of aging.