Stochastic Analysis of Human Ovarian Aging and Menopause Timing.

Abstract

Menopause marks a critically important biological event that ends a woman's fertility. It is a result of ovarian aging and depletion of ovarian reserve. While many aspects of these processes are now well understood, the overall dynamic picture remains unclear. Here, we present a novel theoretical framework to analyze human ovarian aging dynamics and menopause timing. Our method is based on stochastic analysis of underlying processes stimulated by observing follicles sequentially transitioning between different stages during ovulation. This allows us to obtain a fully quantitative description of ovarian aging and menopause timing consistent with available experimental observations. Our model accurately predicts the average age of menopause across geographically diverse human populations. Theoretical analysis suggests a universal relation between the initial follicle reserve, the depletion rates, and the threshold that triggers menopause. In addition, it is found that the distributions of menopause times are quite narrow, and it is proposed that this might be a result of a precise regulation due to synchronization of transitions between different stages of follicles. Our theoretical approach not only quantitatively explains the dynamics of human ovarian aging and menopause timing, but also provides important insights into individual variability in ovarian aging. It can be used as a powerful tool for predicting menopause timing and for investigating complex processes of reproductive aging.