Document Type
Article
Version
Author's Final Manuscript
Publication Title
Mathematical Biosciences
Volume
358
Publication Date
2023
Abstract
A normally functioning menstrual cycle requires significant crosstalk between hormones originating in ovarian and brain tissues. Reproductive hormone dysregulation may cause abnormal function and sometimes infertility. The inherent complexity in this endocrine system is a challenge to identifying mechanisms of cycle disruption, particularly given the large number of unknown parameters in existing mathematical models. We develop a new endocrine model to limit model complexity and use simulated distributions of unknown parameters for model analysis. By employing a comprehensive model evaluation, we identify a collection of mechanisms that differentiate normal and abnormal phenotypes. We also discover an intermediate phenotype—displaying relatively normal hormone levels and cycle dynamics—that is grouped statistically with the irregular phenotype. Results provide insight into how clinical symptoms associated with ovulatory disruption may not be detected through hormone measurements alone.
Citation
Graham, E. J., Elhadad, N. & D. Albers. 2023. "Reduced model for female endocrine dynamics: Validation and functional variations." Mathematical Biosciences 358: 108979.
DOI
https://doi.org/10.1016/j.mbs.2023.108979