Sperm epigenetic diagnostic to inform couples time to pregnancy

SUMMARY This application is for an STTR phase I project aimed at developing a sperm-specific test to predict the time it takes for couples to conceive. Infertility is one of the most common reproductive health disorders, affecting 17% of couples in the U.S. Notably, infertility has historically been treated as a female issue; however, around half of all infertility cases are partially or completely attributed to male factors. Clinical male infertility is typically ascertained based on semen-quality reference values established by the World Health Organization (WHO) criteria; however, these criteria are poor predictors of reproductive success, raising questions about the significance and reliability of conventional methods for evaluating male fertility. Despite significant advances in understanding the molecular characteristics of semen, measures of male fertility have remained unchanged for decades. Therefore, the development of novel biomarkers of male reproductive health is vital to improving reproductive clinical care. Spermatogenesis requires dynamic reprogramming of the epigenome to enable the progression from diploid spermatogonia to haploid mature spermatozoa. We propose that the robust epigenetic reprogramming during spermatogenesis provides a final opportunity for sperm to “epigenetically match” with their internal factors (e.g., genetics) and external factors (e.g., environment) prior to conception. In recent years, epigenetic clocks, which estimate biological age, have been developed as novel biomarkers for phenotypes such as cancer and mortality. Importantly, our group was the first to develop a sperm-specific epigenetic clock, which has been associated with couples’ pregnancy outcomes and validated in an independent infertility cohort. This application will leverage our machine learning pipeline and extant sperm methylation data, along with reproductive outcome data from 1,825 couples from both the general population and infertility cohorts, to further optimize and validate a new sperm epigenetic clock that predicts reproductive outcomes. The research proposed in this application will optimize and validate our prediction models across three distinct cohorts, demonstrating the feasibility of our product as a potential male fertility diagnostic tool to inform clinical decision-making and support the management of couples seeking to achieve pregnancy in both clinical and non-clinical samples.