eMB: Collaborative Research: Stochasticity in ovarian aging and biotechnologies for menopause delay

This project aims to (1) advance the understanding of ovarian aging and (2) optimize technologies designed to delay when ovaries "run out of eggs" and stop functioning (menopause). A key hypothesis underpinning both of these aims is that mathematical and statistical theories of randomness can unlock longstanding mysteries surrounding ovarian function and cessation of function. In one example, even though women are born with around one million primordial follicles (the basic reproductive units that contain eggs), they will only ovulate a few hundred eggs during adulthood. For this reason, ovaries in mammals are sometimes called "wasteful." By developing mathematical models and theories that are closely integrated with biological experiments, this project seeks to explain this and other perplexing features of ovarian biology. In addition, menopause presents women with a number of challenging symptoms and health consequences. Cardiovascular health, bone density, muscle mass, body fat composition, and other measures all worsen as menopause approaches. This has led to a recent surge of interest and investment in pharmacological biotechnologies which aim to delay menopause. However, there is currently no theory to predict how such interventions will affect menopause timing. This project aims to develop such a theory, which will be guided, modified, and validated by biological experiments. Mathematically, this proposal seeks to develop extreme value theory for random variables which are not independent and identically distributed (iid). Such a theory would constitute a major advance in stochastics theory and find immediate application in a wide range of areas of science. Extreme value theory deals with extreme events in the tails of probability distributions. Such statistical "outliers" are critical to ovarian biology because the lifespan of ovarian health depends on the last few tenths of a percent of primordial follicles to growth activate. While there are classical results for the iid case, extreme value theory for non-iid random variables is severely limited. Biologically, the proposal contains innovative approaches to address a very long-standing problem in the field: how are individual dormant primordial follicles selected for growth activation while the majority remain dormant over long periods of time? If validated, the hypotheses of this proposal would transform our understanding of ovarian aging, including the landmark stages of the menopausal transition, and menopause. Though stochasticity is often viewed as an obstacle in physiology, this work can help us to determine how random processes function to ensure robust, reliable female reproductive aging. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.