Patient specific modeling of the HPA axis related to clinical diagnosis of depression

Bangsgaard, Elisabeth O.; Ottesen, Johnny T.

doi:10.1016/j.mbs.2016.10.007

Cited by 31 publications

(35 citation statements)

References 43 publications

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“…2) results in two decoupled models describing the acute inflammatory response and the hormone secretion of the HPA axis, respectively. For further details, see Bangsgaard (2016).…”

Section: Integrated Inflammatory Stress Modelmentioning

confidence: 99%

“…The submodel describing the acute inflammatory response is fitted to data of rats receiving different doses of LPS while the submodel describing the HPA axis is fitted to data of humans in order to verify each of the submodels (Bangsgaard 2016). Using these results, the parameters introduced in the ITIS model (1)-(2) were calibrated by hand by comparing output to data.…”

Section: Parameter Selectionmentioning

confidence: 99%

“…By using parameter estimation on four selected parameters, the fit of the ITIS model is improved. The selected parameters are chosen as sensitive parameters, which vary considerably between individuals; for further discussion, see Bangsgaard (2016). The selected parameters δ, d 4 , d 8 and k 15 are among the sensitive ones without being the most sensitive.…”

Section: Parameter Selectionmentioning

confidence: 99%

“…Thus, our choice of selected is not only based on the quantitative sensitivity criteria but also on a qualitative criteria as well. Based on this, the parameter δ describing the circadian phase is chosen as one of the selected parameters, since it is very important for the timing of the circadian peaks for the various curves, despite a rather small quantitative sensitivity compared to most other parameters (Bangsgaard 2016). See Appendix for the complete sensitivity analysis.…”

Section: Parameter Selectionmentioning

confidence: 99%

“…The ITIS model is developed partly by biological reasoning and the parsimonious principle for the mathematical expressions related to data. For further details, see Bangsgaard (2016). The interpretations of the equations in the model are explained in the following.…”

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Integrated Inflammatory Stress (ITIS) Model

et al. 2017

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Integrated Inflammatory Stress (ITIS) ModelBangsgaard, Elisabeth O.; Hjorth, Poul G.; Olufsen, Mette S.; Mehlsen, Jesper; Ottesen, Johnny T. Published in: Bulletin of Mathematical BiologyLink to article, DOI: 10.1007/s11538-017-0293-2 Publication date: 2017 Document VersionPublisher's PDF, also known as Version of record Abstract During the last decade, there has been an increasing interest in the coupling between the acute inflammatory response and the Hypothalamic-Pituitary-Adrenal (HPA) axis. The inflammatory response is activated acutely by pathogen-or damagerelated molecular patterns, whereas the HPA axis maintains a long-term level of the stress hormone cortisol which is also anti-inflammatory. A new integrated model of the interaction between these two subsystems of the inflammatory system is proposed and coined the integrated inflammatory stress (ITIS) model. The coupling mechanisms describing the interactions between the subsystems in the ITIS model are formulated based on biological reasoning and its ability to describe clinical data. The ITIS model is calibrated and validated by simulating various scenarios related to endotoxin (LPS) exposure. The model is capable of reproducing human data of tumor necrosis factor alpha, adrenocorticotropic hormone (ACTH) and cortisol and suggests that repeated LPS injections lead to a deficient response. The ITIS model predicts that the most extensive response to an LPS injection in ACTH and cortisol concentrations is observed in the early hours of the day. A constant activation results in elevated levels of the variables in the model while a prolonged change of the oscillations in ACTH and

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“…2) results in two decoupled models describing the acute inflammatory response and the hormone secretion of the HPA axis, respectively. For further details, see Bangsgaard (2016).…”

Section: Integrated Inflammatory Stress Modelmentioning

confidence: 99%

Section: Parameter Selectionmentioning

confidence: 99%

Section: Parameter Selectionmentioning

confidence: 99%

Section: Parameter Selectionmentioning

confidence: 99%

mentioning

confidence: 99%

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Stability and Hopf bifurcation analysis of a 4‐dimensional hypothalamic‐pituitary‐adrenal axis model with distributed delays

Kaslik

Neamţu

2018

Math Methods in App Sciences

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A 4‐dimensional mathematical model of the hypothalamus‐pituitary‐adrenal axis is investigated, incorporating the influence of the glucocorticoid receptors concentration and general feedback functions. The inclusion of distributed time delays provides a more realistic modeling approach, since the whole past history of the variables is taken into account. The positivity of the solutions and the existence of a positively invariant bounded region are proved. It is shown that the considered 4‐dimensional system has at least 1 equilibrium state, and a detailed local stability and Hopf bifurcation analysis is given. Numerical results reveal the fact that an appropriate choice of the system's parameters leads to the coexistence of 2 asymptotically stable equilibria in the nondelayed case. When the total average time delay of the system is large enough, the coexistence of 2 stable limit cycles is revealed, which successfully model the ultradian rhythm of the hypothalamus‐pituitary‐adrenal axis both in a normal disease‐free situation and in a diseased hypocortisolism state, respectively. Numerical simulations reflect the importance of the theoretical results.

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