Glucocorticoids and CBG during pregnancy in mammals: diversity, pattern, and function.

Pregnancy is one of the defining characteristics of placental mammals. Key in the growth and development of the fetus during pregnancy are the dynamics of glucocorticoids (GCs) and their binding protein,corticosteroid-binding globulin (CBG), which determines how much of the GCs are free and biologically active. Out of more than 5000 species of placental mammals in 19 different orders, our understanding of the dynamics of maternal GCs and CBG during pregnancy is largely limited to the detailed study of 3 groups - sheep, laboratory rodents, and humans. The assumption is often made that what we see in these few species applies to the rest. To examine this generality, we compared patterns of maternal GCs over pregnancy from all placental mammals where data is available: in the blood of 13 species from 5 different orders and in metabolites in excreta in an additional 20 species from 9 orders. We found that maternal free GCs increase by late pregnancy in most taxa. This increase is achieved by either an increase in total GC secretion or a decrease in CBG. A major exception is found in the even-toed ungulates (sheep, cows, etc.) where maternal GCs and CBG remain stable, but where the fetal adrenals mature in late pregnancy and produce the majority of their own GCs. We conclude that patterns of change in maternal GCs and CBG during pregnancy are species-specific but are alternative means to the same end: increased fetal exposure to GCs in late pregnancy, which is essential for development.

Model-based therapeutic correction of hypothalamic-pituitary-adrenal axis dysfunction.

The hypothalamic-pituitary-adrenal (HPA) axis is a major system maintaining body homeostasis by regulating the neuroendocrine and sympathetic nervous systems as well modulating immune function. Recent work has shown that the complex dynamics of this system accommodate several stable steady states, one of which corresponds to the hypocortisol state observed in patients with chronic fatigue syndrome (CFS). At present these dynamics are not formally considered in the development of treatment strategies. Here we use model-based predictive control (MPC) methodology to estimate robust treatment courses for displacing the HPA axis from an abnormal hypocortisol steady state back to a healthy cortisol level. This approach was applied to a recent model of HPA axis dynamics incorporating glucocorticoid receptor kinetics. A candidate treatment that displays robust properties in the face of significant biological variability and measurement uncertainty requires that cortisol be further suppressed for a short period until adrenocorticotropic hormone levels exceed 30% of baseline. Treatment may then be discontinued, and the HPA axis will naturally progress to a stable attractor defined by normal hormone levels. Suppression of biologically available cortisol may be achieved through the use of binding proteins such as CBG and certain metabolizing enzymes, thus offering possible avenues for deployment in a clinical setting. Treatment strategies can therefore be designed that maximally exploit system dynamics to provide a robust response to treatment and ensure a positive outcome over a wide range of conditions. Perhaps most importantly, a treatment course involving further reduction in cortisol, even transient, is quite counterintuitive and challenges the conventional strategy of supplementing cortisol levels, an approach based on steady-state reasoning.