Sperm epigenetic clock predicts pregnancy outcomes in the general population

We developed two novel sperm epigenetic clocks by applying Super Learner, an ensemble machine learning algorithm, to predict age from sperm EPIC array DNA methylation data via individual CpG sites and differentially methylated regions (DMRs). Overall, our cox model showed that one-year increase in our developed sperm epigenetic age (SEA) was associated with up to 15% reduction in couples time-to-pregnancy (TTP). A population-based prospective design involving participants that were enrolled in the Longitudinal Investigation of Fertility and the Environment (LIFE) Study. It sought to determine the association between sperm epigenetic age (SEA) with time-to-pregnancy (TTP) among couples (n =379) trying for pregnancy.