Mathematical Modelling of Endocrine Systems

• Published in: Trends in endocrinology and metabolism Vol. 30; no. 4; pp. 244 - 257
• Main Authors: Zavala, Eder, Wedgwood, Kyle C.A., Voliotis, Margaritis, Tabak, Joël, Spiga, Francesca, Lightman, Stafford L., Tsaneva-Atanasova, Krasimira
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01-04-2019; Elsevier Science Pub. Co
• Subjects: Chronotherapy; Circadian Rhythm - physiology; circadian rhythms; Endocrine System - metabolism; hormone dynamics; Hormones - metabolism; Humans; hybrid systems; Hypothalamo-Hypophyseal System - metabolism; Models, Theoretical; regulatory networks; ultradian oscillations; Ultradian Rhythm - physiology; chronotherapy; hybrid systems; regulatory networks; hormone dynamics; circadian rhythms; ultradian oscillations
• ISSN: 1043-2760; 1879-3061
• DOI: 10.1016/j.tem.2019.01.008

Hormone rhythms are ubiquitous and essential to sustain normal physiological functions. Combined mathematical modelling and experimental approaches have shown that these rhythms result from regulatory processes occurring at multiple levels of organisation and require continuous dynamic equilibration, particularly in response to stimuli. We review how such an interdisciplinary approach has been successfully applied to unravel complex regulatory mechanisms in the metabolic, stress, and reproductive axes. We discuss how this strategy is likely to be instrumental for making progress in emerging areas such as chronobiology and network physiology. Ultimately, we envisage that the insight provided by mathematical models could lead to novel experimental tools able to continuously adapt parameters to gradual physiological changes and the design of clinical interventions to restore normal endocrine function.
Combining appropriate mathematical models with carefully designed experiments offers great potential to understand complex endocrine regulation at multiple levels of organisation.
Understanding the mechanisms underlying coordinated, rhythmic insulin secretion requires novel mathematical and computational methods that consider the pancreatic islet as a network of beta cells.
Mathematical models, in combination with experimental physiology, have uncovered the mechanisms by which glucocorticoid hormones exhibit normal ultradian pulsatility and respond rapidly to stressors, including during inflammation.
Supported by optogenetic experiments, a hypothalamic neural network comprising kisspeptin secretory neurons has been postulated as driving pulsatile GnRH dynamics involved in the regulation of the reproductive cycle.
The dynamic clamp, a hybrid system integrating electrophysiological measurements with mathematical modelling, enables the interactive manipulation of key parameters in real time.