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Lawley, S. D.

Publications and source records attributed to Lawley, S. D..

2 recordsLinked to original sources

On modeling ovarian aging and menopause timing

Mathematical modeling of ovarian aging and menopause timing has a long history, dating back a half-century to the models of Nobel Prize winner Robert G. Edwards. More recently, such models have been used to investigate clinical interventions for women, which underscores the importance of scientific rigor in model development and analysis. In this paper, we analyze a recent model published in the biophysics literature. We first correct an error which invalidates claims about menopause age in different populations. We then use stochastic analysis to show how this model is a reparameterization of a prior model and put it in the framework of several prior models, which enables the application of extreme value theory. We prove some general extreme value theory results and use them to obtain detailed estimates of menopause age in this model. In particular, we derive a new expected menopause age formula which is orders of magnitude more accurate than the previous heuristic estimate. We further obtain rigorous analytical estimates of the full menopause age distribution and all its moments. We conclude by using these mathematical results to elucidate the physiological sources of menopause age variability.

physiology↗

Recapitulating Human Ovarian Aging Using Random Walks

Mechanism(s) that control whether individual human primordial ovarian follicles (PFs) remain dormant, or begin to grow, are all but unknown. One of our groups has recently shown that activation of the Integrated Stress Response (ISR) pathway can slow follicular granulosa cell proliferation by activating cell cycle checkpoints. Those data suggest that the ISR is active and fluctuates according to local conditions in dormant PFs. Because cell cycle entry of (pre)granulosa cells is required for PF growth activation (PFGA), we propose that rare ISR checkpoint resolution allows individual PFs to begin to grow. Fluctuating ISR activity within individual PFs can be described by a random process. In this paper, we model ISR activity of individual PFs by one-dimensional random walks (RWs) and monitor the rate at which simulated checkpoint resolution and thus PFGA threshold crossing occurs. We show that that the simultaneous recapitulation of i) the loss of PFs over time within simulated subjects, and ii) the timing of PF depletion in populations of simulated subjects equivalent to the distribution of the human age of natural menopause can be produced using this approach. In the RW model, the probability that individual PFs grow is influenced by regionally fluctuating conditions, that over time manifests in the known pattern of PFGA. Considered at the level of the ovary, randomness appears to be a key, purposeful feature of human ovarian aging.

physiology↗