Abstract
DNA methylation data has been used to make "epigenetic clocks" which attempt to measure chronological and biological aging. These models rely on data derived from bisulfite-based measurements, which exploit a semi-selective deamination and a genomic reference to determine methylation states. We found that non-methylation factors lead to "pseudomethylation" signals that are both confounding of epigenetic clocks and uniquely age predictive. We also failed to predict age using human genotyping arrays, but found that epigenetic clocks were overrepresented near genomic regions whose methylation state is dependent upon sequence variants. Quantifying these covariates in aging studies will be critical to building better clocks and designing appropriate studies of epigenetic aging.