Regulation of the reproductive cycle in adult women is a dual control system involving at least eight hormones produced by the brain and the ovaries. This research project develops and analyzes differential equation models for the number of follicles (eggs) and blood levels of reproductive hormones during a woman's reproductive years from age 20 until menopause. The investigators' models already predict hormone levels that agree with data in the literature for normally cycling women, and the models have other solutions reflecting characteristics of polycystic ovarian syndrome (PCOS), a leading cause of female infertility. Building on this work, the researchers will develop more complex, mechanistic models to describe a woman's cycling throughout her reproductive life and to track the "primordial pool" of follicles with which a woman is born and that continually decreases as she ages. Ad hoc techniques will be devised to estimate model parameters using data sets from multiple age groups. Model simulations will be used to predict and to study age-related and pathological changes in cycling. These include a decrease in serum inhibins, which is one of the earliest signs of reproductive aging, and erratic luteal levels of estrogen and progesterone, which may occur in women in their 40's. Tools from numerical analysis and dynamical systems, e.g., parameter identification methods, sensitivity analysis, stability theory, and bifurcation techniques, will be used to develop and to study these models.
A woman's peak fertility occurs between the ages of 20 and 30. However, in North America and Europe more women are postponing childbearing until their 30's and must deal with the consequences of reduced natural fertility due to a decreasing number of follicles and changes in reproductive hormones. In addition, women with polycystic ovarian syndrome (PCOS) often exhibit hormonal imbalances and insulin insensitivity. A goal of this research project is to model and study the interplay between PCOS, excess androgens, and glucose metabolism. A lifelong model for hormonal control of the female reproductive cycle may be used to predict optimal types, doses, and durations of hormonal therapies for young and aging women. In turn, given the broad consensus that hormone therapies be used at lowest doses for the shortest intervals necessary to achieve specific therapeutic aims, the impact of these modeling studies on women's health should be beneficial. This research also may advance our understanding of several types of increasingly prevalent diseases, including PCOS, infertility in general, diabetes, and other metabolic disorders.
