Significance of this project resides in the magnitude and scope of Chronic Fatigue Syndrome (CFS) as a growing public health concern and in the inadequacy of current acute illness research models for resolving complex disorders affecting multiple regulatory systems in the body. This illness cuts across race, gender and socioeconomic status to affect a wide segment of society with costs to the US economy estimated at $9 billion in lost productivity and up to $24 billion dollars in health care expenditures annually. Moreover complications and co-morbidity can be severe, including cardiovascular illness and cancer, raising the stakes even further. Research has shown that immune, endocrine and nervous systems are all affected. Though these systems function in close collaboration CFS continues to be studied using a traditional piece-by-piece approach focusing on the failure of individual neuroendocrine and immune components. Hypothesis: We hypothesize that CFS results not only from component failure but perhaps more importantly from a significant deterioration of regulatory function linking these components. We will test regulatory fitness by using an exercise challenge to stimulate stress response and its modulation of the nervous, endocrine and immune systems. Objectives: The objective of this study is to improve our understanding of CFS pathogenesis in three ways: (i) by using broad-scale molecular profiling to create a comprehensive assessment of status in several of the body's regulatory systems, ii) by using information theory to integrate this disparate data into a single interpretable map describing the interactions between these physiologic systems and iii) by using novel elements of network theory to study the structure of these signaling networks and isolate alterations in the """"""""wiring"""""""" that might be specific to CFS. Embedded in these maps we will also have captured the dynamic response of the overarching homeostatic control to exercise stress. This quantitative knowledge of the rates and directions with which biological information is disseminated through the neuroendocrine immune networks will be used as a basis for simulating response to treatment. Indeed computer simulations of neuroendocrineimmune response will be used to perform computer-aided design of candidate clinical trials in much the same way simulations have been used to train flight crews. By simulating CFS as an altered but stable control program treatment courses can be designed that exploit the new homeostatic rules to redirect the system as a whole to normal resting state and a normal pattern of response to activity.
By analyzing the flow of information through regulatory networks we have a foundation for identifying complementary mechanisms that could be harnessed to restore normal network function. We will be estimating dynamic interaction between genes, hormones, neuropeptides and cytokines as well as the population response in a number of individual cell types. This will allow an integrated dynamic model of the neuro-endocrine-immune axes, which can serve as a basis for estimating theoretically optimal intervention strategies and dosage schedules using elements and concepts from model-based predictive control MPC theory.
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