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Modeling the circadian regulation of HPA axis activity
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Rao, Rohit T.. Modeling the circadian regulation of HPA axis activity. Retrieved from https://doi.org/doi:10.7282/t3-5btj-0d28

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TitleModeling the circadian regulation of HPA axis activity
NameRao, Rohit T. (author); Androulakis, Ioannis P (chair); Ramachandran, Rohit (internal member); Roth, Charles (internal member); Jusko, William J (outside member); Rutgers University; School of Graduate Studies
Date Created2018
Other Date2018-10 (degree)
SubjectChemical and Biochemical Engineering, Glucocorticoids, Hypothalamic-pituitary-adrenal axis
Extent1 online resource (160 pages : illustrations)
DescriptionThe hypothalamic-pituitary-adrenal (HPA) axis constitutes the primary physiological stress response mechanism, with cortisol (corticosterone in rodents) being the major effector molecule of the HPA axis, mediating an array of metabolic and immune-modulatory functions. The circadian dynamics of the mediators of HPA axis are considered to significantly modulate their functional characteristics and demonstrate remarkable plasticity. This is observed in pathological conditions where circadian disruption is often associated with disease etiology, as in the case of chronic inflammatory conditions such as rheumatoid arthritis, as well as in physiological conditions, where the presence of significant sex differences in numerous aspects of the HPA axis, including both basal circadian activity as well as in its response to physiological stressors is well established. It is widely suggested that the mechanisms that dictate the rhythmic properties of the HPA network might also contribute to its functioning in both physiological and pathological conditions. For example, the sex differences in the circadian dynamics of the HPA axis are thought to contribute to the observed sex disparity in the development of a variety of autoimmune and infectious diseases. Moreover, an understanding of these underlying mechanisms is critical to development of pharmacological approaches that can appropriately treat HPA axis disorders. Mathematical modeling provides a promising approach to study physiological feedback systems such as the HPA axis, and enables the evaluation of the feasibility of hypotheses, by providing a phenomenological framework for explaining empirical observations as well as making testable predictions. In this work we develop semi-mechanistic mathematical models of the HPA axis to understand the critical regulatory mechanisms that contribute to its functioning in health and disease. In the first aim we develop a mathematical model for the progression of collagen-induced arthritis that evaluates the effect of chronic elevation on the proinflammatory cytokines on the circadian dynamics of corticosterone and important markers of disease activity such as paw edema, thus emphasizing the importance of accounting for circadian rhythms in models of chronic inflammation. Subsequently, we study how differences in the regulatory features of the HPA network might lead to basal variability, with a focus on sex-specific and individual differences in its activity. In doing so, we predict that the host can employ diverse regulatory mechanisms to maintain glucocorticoid circadian rhythms within strict physiological bounds, ultimately resulting in the existence of trade-offs between multiple functional characteristics of the HPA axis. Furthermore, we characterize specific chronic stress-induced allostatic adaptations in the regulatory dynamics of the HPA axis. Finally, through mathematical modeling, we determine how an understanding of the circadian dynamics of the HPA axis could be leveraged for the design of chronotherapeutic dosing regimens to minimize the incidence of adverse effects associated with chronic glucocorticoid therapy.
NotePh.D.
NoteIncludes bibliographical references
Noteby Rohit T. Rao
Genretheses, ETD doctoral
Persistent URLhttps://doi.org/doi:10.7282/t3-5btj-0d28
Languageeng
CollectionSchool of Graduate Studies Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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