A Canadian/U.S. research team has reported a novel approach to stimulating recovery from chronic stress disorders. Details of the therapeutic model, which exploits the natural dynamics of the body's "fight or flight" system, are published January 23 in the open-access journal PLoS Computational Biology. In contrast to conventional time-invariant therapy, the researchers propose a well-directed therapeutic push delivered according to an optimal treatment schedule.
The hypothalamic, pituitary, adrenal (HPA) axis constitutes one of the body's major control systems, serving to maintain body homeostasis with hormone feedback regulatory loops. If the HPA axis is driven very far from its natural homeostatic rest point, it may be unable to fully recover the healthy physiologic state. Under such conditions, the HPA axis dysfunction may become chronic. HPA axis dysfunction has been characterized in disorders including Chronic Fatigue Syndrome (CFS), depression, post- traumatic stress disorder and Alzheimer disease.
The research team, consisting of Drs. Amos Ben-Zvi, Suzanne D. Vernon, and Gordon Broderick, used a relatively simple mathematical description of the HPA axis to show how the complex dynamical behavior of this system could accommodate multiple stable resting states; some corresponding to chronic loss of function characterized by low cortisol, a hormone that modulates immune function. A robust treatment strategy was designed to take advantage of the body's existing homeostatic mechanism, using a short-duration intervention to assist the HPA axis in re-asserting homeostasis about a healthy equilibrium. Akin to pulling back a slingshot, temporarily reducing the bioavailability of cortisol pharmacologically causes the HPA axis to overcompensate and launch itself back into a correct regulatory regime.
The Centers for Disease Control and Prevention (CDC) in Atlanta, Georgia estimates that between 1 and 4 million Americans suffer from CFS, and only half have consulted a physician for their illness. The CDC and DePaul University have estimated CFS costs the US economy approximately $30 billion each year in health care and lost productivity.
The researchers propose a theoretical, single intervention therapeutic model that is counter-intuitive and challenges the conventional time-invariant approach to many therapies. Validation of this model will require clinical collaboration.
PLEASE ADD THIS LINK TO THE PUBLISHED ARTICLE IN ONLINE VERSIONS OF YOUR REPORT: http://dx.plos.org/10.1371/journal.pcbi.1000273 (link will go live on Friday, January 23)
CITATION: Ben-Zvi A, Vernon SD, Broderick G (2009) Model-Based Therapeutic Correction of Hypothalamic-Pituitary-Adrenal Axis Dysfunction. PLoS Comput Biol 5(1): e1000273. doi:10.1371/journal.pcbi.1000273
Disclaimer
This press release refers to an upcoming article in PLoS Computational Biology. The release is provided by the article authors. Any opinions expressed in this release or article are the personal views of the journal staff and/or article contributors, and do not necessarily represent the views or policies of PLoS. PLoS expressly disclaims any and all warranties and liability in connection with the information found in the releases and articles and your use of such information.
About PLoS Computational Biology
PLoS Computational Biology (www.ploscompbiol.org) features works of exceptional significance that further our understanding of living systems at all scales through the application of computational methods. All works published in PLoS Computational Biology are open access. Everything is immediately available subject only to the condition that the original authorship and source are properly attributed. Copyright is retained by the authors. The Public Library of Science uses the Creative Commons Attribution License.
About the Public Library of Science
The Public Library of Science (PLoS) is a non-profit organization of scientists and physicians committed to making the world's scientific and medical literature a freely available public resource. For more information, visit http://www.plos.org.
PLEASE MENTION THE OPEN ACCESS JOURNAL PLoS COMPUTATIONAL BIOLOGY (www.ploscompbiol.org) AS THE SOURCE FOR THIS ARTICLE AND PROVIDE A LINK TO THE FREELY AVAILABLE TEXT. THANK YOU.
PLoS Computational Biology is an open-access, peer-reviewed journal published weekly by the Public Library of Science (PLoS) as the official journal of the International Society for Computational Biology (ISCB).
Journal
PLoS Computational Biology