This work was funded in part by grants the National Institute of Environmental Health Sciences, National Institutes of Health (R01 ES028298; PI: J.R.P. and P30 ES020957); Robert J. Sokol, MD Endowed Chair of Molecular Obstetrics and Gynecology (J.R.P.); and the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland (Contracts N01-HD-3-3355, N01-HD-3-3356 and N01-HD-3-3358). S.L.M. was supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health. The authors declare no competing interests.
These data suggest that our sperm epigenetic clocks may have utility as a novel biomarker to predict TTP among couples in the general population and underscore the importance of the male partner for reproductive success.
We observed a 17% lower cumulative probability at 12 months for couples with male partners in the older compared to the younger SEA categories.
Our SEACpG clock had the highest predictive performance with correlation between chronological and predicted age (r = 0.91). In adjusted discrete Cox models, SEACpG was negatively associated with TTP (fecundability odds ratios (FORs)=0.83; 95% CI: 0.76, 0.90; P = 1.2×10-5), indicating a longer TTP with advanced SEACpG. For subsequent birth outcomes, advanced SEACpG was associated with shorter gestational age (n = 192; -2.13 days; 95% CI: -3.67, -0.59; P = 0.007). Current smokers also displayed advanced SEACpG (P < 0.05). Finally, SEACpG showed a strong performance in an independent IVF cohort (n = 173; r = 0.83). SEADMR performance was comparable to SEACpG but with attenuated effect sizes.
This was a population-based prospective cohort study of couples discontinuing contraception to become pregnant recruited from 16 US counties from 2005 to 2009 and followed for up to 12 months.
Sperm DNA methylation from 379 semen samples was assessed via a beadchip array. A state-of-the-art ensemble machine learning algorithm was employed to predict age from the sperm DNA methylation data. SEA was estimated from clocks derived from individual CpGs (SEACpG) and differentially methylated regions (SEADMR). Probability of pregnancy within 1 year was compared by SEA, and discrete-time proportional hazards models were used to evaluate the relations with time-to-pregnancy (TTP) with adjustment for covariates.
Is sperm epigenetic aging (SEA) associated with probability of pregnancy among couples in the general population?
This prospective cohort study consisted primarily of Caucasian men and women, and thus analysis of large diverse cohorts is necessary to confirm the associations between SEA and couple pregnancy success in other races/ethnicities.
The strong relation between chronological age and DNA methylation profiles has enabled the estimation of biological age as epigenetic 'clock' metrics in most somatic tissue. Such clocks in male germ cells are less developed and lack clinical relevance in terms of their utility to predict reproductive outcomes.