Estimation of parameters for a mathematical model of growth hormone secretion

Model informed quantification of the feed-forward stimulation of growth hormone by growth hormone-releasing hormone

Aims

Growth hormone (GH) secretion is pulsatile and secretion varies highly between individuals. To understand and ultimately predict GH secretion, it is important to first delineate and quantify the interaction and variability in the biological processes underlying stimulated GH secretion. This study reports on the development of a population nonlinear mixed effects model for GH stimulation, incorporating individual GH kinetics and the stimulation of GH by GH‐releasing hormone (GHRH).

Methods

Literature data on the systemic circulation, the median eminence, and the anterior pituitary were included as system parameters in the model. Population parameters were estimated on data from 8 healthy normal weight and 16 obese women who received a 33 μg recombinant human GH dose. The next day, a bolus injection of 100 μg GHRH was given to stimulate GH secretion.

Results

The GH kinetics were best described with the addition of 2 distribution compartments with a bodyweight dependent clearance (increasing linearly from 24.7 L/h for a 60‐kg subject to 32.1 L/h for a 100‐kg subject). The model described the data adequately with high parameter precision and significant interindividual variability on the GH clearance and distribution volume. Additionally, high variability in the amount of secreted GH, driven by GHRH receptor activation, was identified (coefficient of variation = 90%).

Conclusion

The stimulation of GH by GHRH was quantified and significant interindividual variability was identified on multiple parameters. This model sets the stage for further development of by inclusion of additional physiological components to quantify GH secretion in humans.

Thyrotropin secretion patterns in health and disease

Thyroid hormones are extremely important for metabolism, development, and growth during the lifetime. The hypothalamo-pituitary-thyroid axis is precisely regulated for these purposes. Much of our knowledge of this hormonal axis is derived from experiments in animals and mutations in man. This review examines the hypothalamo-pituitary-thyroid axis particularly in relation to the regulated 24-hour serum TSH concentration profiles in physiological and pathophysiological conditions, including obesity, primary hypothyroidism, pituitary diseases, psychiatric disorders, and selected neurological diseases. Diurnal TSH rhythms can be analyzed with novel and precise techniques, eg, operator-independent deconvolution and approximate entropy. These approaches provide indirect insight in the regulatory components in pathophysiological conditions.

Motivations and methods for analyzing pulsatile hormone secretion

Endocrine glands communicate with remote target cells via a mixture of continuous and intermittent signal exchange. Continuous signaling allows slowly varying control, whereas intermittency permits large rapid adjustments. The control systems that mediate such homeostatic corrections operate in a species-, gender-, age-, and context-selective fashion. Significant progress has been made in understanding mechanisms of adaptive interglandular signaling in vivo. Principal goals are to understand the physiological origins, significance, and mechanisms of pulsatile hormone secretion. Key analytical issues are: 1) to quantify the number, size, shape, and uniformity of pulses, nonpulsatile (basal) secretion, and elimination kinetics; 2) to evaluate regulation of the axis as a whole; and 3) to reconstruct dose-response interactions without disrupting hormone connections. This review will focus on the motivations driving and the methodologies used for such analyses.

Mathematical modelling in neuroendocrinology

In neuroendocrinology, mathematical modelling is about formalising our understanding of the behaviour of the complex biological systems with which we deal. Formulating our explanations mathematically ensures their logical consistency, and makes them open to structured analysis; it is a stringent test of their intellectual coherence. In addition, however, modellers are seeking to extend our understanding in new ways, by seeking novel, simple explanations for complex behaviour. Here we discuss some styles of modelling as they have been applied to neuroendocrine systems, and discuss some of their strengths and limitations.

Modelling the hypothalamic control of growth hormone secretion

Here, we construct a mathematical model of the hypothalamic systems that control the secretion of growth hormone (GH). The work extends a recent model of the pituitary GH system, adding representations of the hypothalamic GH-releasing hormone (GHRH) and somatostatin neurones, each modelled as a single synchronised unit. An unpatterned stochastic input drives the GHRH neurones generating pulses of GHRH release that trigger GH pulses. Delayed feedback from GH results in increased somatostatin release, which inhibits both GH secretion and GHRH release, producing an overall pattern of 3-h pulses of GH secretion that is very similar to the secretory profile observed in male rats. Rather than directly stimulating somatostatin release, GH feedback triggers a priming effect, increasing releasable stores of somatostatin. Varying this priming effect to reduce the effect of GH can reproduce the less pulsatile form of GH release observed in the female rat. The model behaviour is tested by comparison with experimental observations with a range of different experimental protocols involving GHRH injections and somatostatin and GH infusion.