University of Birmingham > Talks@bham > Applied Mathematics Seminar Series > Dynamic modulation of glucose utilisation by glucocorticoid rhythms in health and disease

Dynamic modulation of glucose utilisation by glucocorticoid rhythms in health and disease

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  • UserEder Zavala
  • ClockThursday 31 October 2019, 13:00-14:00
  • HouseNuffield G13.

If you have a question about this talk, please contact Fabian Spill.

Some of the most pressing challenges in healthcare require a dynamic understanding of the cross-talk interactions between endocrine axes. For example, glucocorticoid hormones mediating the stress response are also important for glycemic control and are known to play a role in the development of metabolic conditions such as type 2 diabetes. While high-resolution continuous sampling techniques have revealed circadian and ultradian rhythmicity of stress hormones (e.g., cortisol), little is known about how these rhythms are decoded by peripheral tissues and endocrine organs, or how their dysregulation leads to disease. In particular, the mechanisms by which hypercortisolism can lead to glucose intolerance and insulin resistance are not well understood.

To address this, we propose a mathematical model of glycemic control that accounts for glucocorticoid and insulin antagonism, with an emphasis on the dynamic effects of glucocorticoid pulsatility. The model predicts differential dynamic responses following oral glucose tolerance tests (OGTTs) that depend on ultradian and circadian timing, are modulated by agonists and antagonists of the glucocorticoid receptor, and shows how hypercortisolism disrupts circadian variability in both glucose and insulin responses to OGT Ts. Lastly, we use the model to explore the mechanisms contributing to the development of secondary type 2 diabetes in patients with Cushing’s syndrome. We envisage this class of mathematical models will guide the interpretation of circadian-dependent clinical diagnosis and therapies

This talk is part of the Applied Mathematics Seminar Series series.

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