Model-based therapeutic correction of hypothalamic-pituitary-adrenal axis dysfunction
Open accessAbstract
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.
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Regulatory interactions between entities were drawn from the Pathway Studio knowledge database, a repository extracted from the published scientific literature using the MedScan natural language processing engine.
“Regulatory interactions (edges) between these entities were drawn from the Pathway Studio (Elsevier, Amsterdam NL) knowledge database, a repository extracted from the published scientific literature using the MedScan34 natural language processing engine.”
From Leveraging Prior Knowledge of Endocrine Immune Regulation in the Therapeutically-relevant Phenotyping of Women with Chronic Fatigue Syndrome (2019) · cites this paper as [34]
The Introduction and Methods describe an HPA-axis model and model-based treatment, not a Pathway Studio knowledge database. Searches for Pathway Studio, MedScan, and literature-extracted regulatory interactions found no passage in our copy addressing the claim. Page numbers were not available. (LLM, conf=0.78)
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Kim, L. U., Chou, T., & D'Orsogna, M. R. (2016) · Biophysical Journal · doi:10.1016/j.bpj.2015.11.2545
Thakurdesai, P. A., Deshpande, P., Desai, N., Mathad, P., Rani, S., & RAJE, D. V. (2025) · Pharmacognosy Journal · doi:10.5530/pj.2024.16.202
Soucy, J. R., & Koppes, R. A. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-16110-0.00002-9
- Authors
- Ben-Zvi, A., Vernon, S. D., & Broderick, G.
- Affiliations
- Solve ME/CFS Initiative (US)
- University of Alberta (CA)
- Corresponding author
- Broderick, Gordon
- Venue
- PLoS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2009-01-23
- Volume
- 5
- Issue
- 1
- Pages
- e1000273
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- PMC
- PMC2613527
- OpenAlex
- W2038872111
- Cited by
- 56
- References
- 46
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2023: 2 · 2022: 1 · 2021: 5 · 2020: 6 · 2019: 1 · 2018: 5 · 2017: 1 · 2016: 5 · 2015: 3 · 2014: 4 · 2013: 6 · 2012: 7
- FWCI
- 1.78
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- NSUWorks (Nova Southeastern University) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- University of Alberta
- Centers for Disease Control and Prevention
- Natural Sciences and Engineering Research Council of Canada
- Topics
- Life Sciences › Neuroscience › Behavioral Neuroscience › Stress Responses and Cortisol
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Adrenal Hormones and Disorders
- Physical Sciences › Engineering › Control and Systems Engineering › Advanced Control Systems Optimization
- Keywords
- hypothalamic-pituitary-adrenal axis, chronic fatigue syndrome, model predictive control, cortisol suppression, ACTH, corticosteroid-binding globulin, robust control, biological variation
- MeSH terms
- Adrenal Insufficiency, Adrenocorticotropic Hormone, Dose-Response Relationship, Drug, Humans, Hydrocortisone, Hypothalamo-Hypophyseal System, Models, Biological, Pituitary-Adrenal System, Receptors, Glucocorticoid, Transcortin, Fatigue Syndrome, Chronic, Feedback, Physiological, Systems Biology
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