A Computational Systems Biology View on the Role of the Menstrual Cycle in Endocrine Health and Disease.

In the era of personalized and precision medicine, sex is an important biological variable that needs to be taken into account in biomedical research. However, the role of the menstrual cycle has long been neglected because it requires clinical studies that are large, time-consuming, and expensive. A computational systems biology approach is a fundamentally different but powerful framework that explains how architectural features of the hormonal system, including feedback loops and cross-talk mechanisms, give rise to emergent behavior on the system level. Nevertheless, systems biology models that are centered around the menstrual cycle are still scarce. A major challenge both in medical research and from a modeling point of view is the large intra- and inter-individual variability in cycle length. In fact, the hypothalamic-pituitary-ovarian (HPO) axis, which is responsible for the regulation of the menstrual cycle, interacts with many of the other hormonal systems that are involved in, for example, the regulation of stress, energy balance, and glucose homeostasis. These interactions and their age-related changes need to be considered when exploring normal and pathological conditions since many endocrine diseases go along with disruptions in multiple hormonal axes. This paper focuses on the HPO axis and its interactions with the hypothalamic-pituitary-adrenal axis and glucose-insulin metabolism in both health and disease. It briefly summarizes the biomedical knowledge about the individual sub-systems and their cross-talk mechanisms and provides an overview of mathematical modeling approaches and opportunities in this field.