The transition to menopause encompasses a wide ranging set of changes for women. The work we propose offers a unique opportunity to explore the transition and link it with the prior history of a large, well-defined cohort of women. We will study a cohort of women enrolled in the Tremin Trust. They have been providing detailed prospective reports of menstrual and reproductive histories, and information on life-cycle events and health status for up to 30 years. For 150 women, we will collect daily first-morning urine specimens during a 6-month window during each of the five project years. The specimens will be assayed for the principal steroids and gonadotropins involved in regulating ovarian cycles and in signalling reproductive aging. Statistical models will link the women's menstrual, reproductive, and health related histories to the experience of the transition, model the effects of hormonal patterns on menstrual bleeding during the perimenopause, and relate features of the transition to the underlying process of follicular depletion. The proposed work differs from other studies of the menopause in several important respects. First we have access to decades worth of prospectively- reported data. Second, unlike most other studies of the endocrinology of the menopause, we will work with a population- based cohort of women who were all recruited well before the transition. Thus, they are not selected for any aspect of their experience of the transition. Third, we propose to develop and apply new mathematical models that will allow us to link characteristics of the menopausal transition to prior history and underlying biological mechanisms. The work complements, but does not reproduce, the current NIA initiative. The project will give new insight into the patterns and causes of variation in women's experience of the menopausal transition, will yield a better understanding of how individual-level experience gives rise to population-level patterns of reproductive aging, will enrich clinical practice by providing information on how past menstrual patterns are linked to experience throughout the menopausal transition, and will provide a foundation for future epidemiological studies of the health consequences of patterns of reproductive aging. The data set produced in conjunction with this research will provide a rich resource for future investigators.
