Why is there an oversupply of human ovarian follicles?†

Women are born with hundreds of thousands to over a million primordial ovarian follicles (PFs) in their ovarian reserve. However, only a few hundred PFs will ever ovulate and produce a mature egg. Why are hundreds of thousands of PFs endowed around the time of birth when far fewer follicles are required for ongoing ovarian endocrine function and only a few hundred will survive to ovulate? Recent experimental, bioinformatics, and mathematical analyses support the hypothesis that PF growth activation (PFGA) is inherently stochastic. In this paper, we propose that the oversupply of PFs at birth enables a simple stochastic PFGA mechanism to yield a steady supply of growing follicles that lasts for several decades. Assuming stochastic PFGA, we apply extreme value theory to histological PF count data to show that the supply of growing follicles is remarkably robust to a variety of perturbations and that the timing of ovarian function cessation (age of natural menopause) is surprisingly tightly controlled. Though stochasticity is often viewed as an obstacle in physiology and PF oversupply has been called wasteful, this analysis suggests that stochastic PFGA and PF oversupply function together to ensure robust and reliable female reproductive aging. Mathematical extreme value theory analysis of human primordial follicle numbers over time supports the hypothesis that the large endowment of primordial follicles at birth enables a simple stochastic PFGA mechanism to yield a steady supply of growing follicles that lasts for several decades.

Automated summary

Women are born with a large number of primordial ovarian follicles (PFs), but only a few of them will ever ovulate. Recent analysis suggests that PF growth activation (PFGA) is stochastic, and the oversupply of PFs at birth enables a steady supply of growing follicles. Extreme value theory analysis supports the hypothesis that the large endowment of primordial follicles ensures robust and reliable female reproductive aging.