Project description:This a model from the article: Inclusion of the glucocorticoid receptor in a hypothalamic pituitary adrenal axis model reveals bistability. Gupta S, Aslakson E, Gurbaxani BM, Vernon SD. Theor Biol Med Model 2007 Feb 14;4:8 17300722 , Abstract: BACKGROUND: The body's primary stress management system is the hypothalamic pituitary adrenal (HPA) axis. The HPA axis responds to physical and mental challenge to maintain homeostasis in part by controlling the body's cortisol level. Dysregulation of the HPA axis is implicated in numerous stress-related diseases. RESULTS: We developed a structured model of the HPA axis that includes the glucocorticoid receptor (GR). This model incorporates nonlinear kinetics of pituitary GR synthesis. The nonlinear effect arises from the fact that GR homodimerizes after cortisol activation and induces its own synthesis in the pituitary. This homodimerization makes possible two stable steady states (low and high) and one unstable state of cortisol production resulting in bistability of the HPA axis. In this model, low GR concentration represents the normal steady state, and high GR concentration represents a dysregulated steady state. A short stress in the normal steady state produces a small perturbation in the GR concentration that quickly returns to normal levels. Long, repeated stress produces persistent and high GR concentration that does not return to baseline forcing the HPA axis to an alternate steady state. One consequence of increased steady state GR is reduced steady state cortisol, which has been observed in some stress related disorders such as Chronic Fatigue Syndrome (CFS). CONCLUSION: Inclusion of pituitary GR expression resulted in a biologically plausible model of HPA axis bistability and hypocortisolism. High GR concentration enhanced cortisol negative feedback on the hypothalamus and forced the HPA axis into an alternative, low cortisol state. This model can be used to explore mechanisms underlying disorders of the HPA axis. This model was taken from the CellML repository and automatically converted to SBML. The original model was: Gupta S, Aslakson E, Gurbaxani BM, Vernon SD. (2007) - version=1.0 The original CellML model was created by: Catherine Lloyd c.lloyd@auckland.ac.nz The University of Auckland This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

Project description:Background. Multiple Sclerosis is a chronic inflammatory disease of the central nervous system (CNS) characterized by autoimmune demyelination and subsequent neuro-axonal degeneration. Despite major progress in deciphering MS immunopathogenesis and treating early stages of disease, CNS-confined processes underpinning later progressive form of MS remain elusive, alluding to the poor accessibility to the target organ. We and others have demonstrated the reliability of profiling DNA methylation, a stable epigenetic marker of genome activity, in neuronal nuclei or bulk tissue to capture relevant molecular changes underlying MS neuropathology. In this study, we examined DNA methylation changes occurring in the normal appearing white matter (NAWM) glial cells of MS patients in comparison to white matter (WM) of non-neurological controls (NNC). Results. We profiled DNA methylation in NeuN-negative nuclei of glial cells, isolated from 38 postmortem NAWM specimens of MS patients (n=8) in comparison to WM of NNC individuals (n=14), using Infinium MethylationEPIC BeadChip. We applied reference-free cell type deconvolution to further reduce cellular heterogeneity and identified 1,226 significant (genome-wide adjusted P-value < 0.05) differentially methylated positions (DMPs) between MS patients and controls. Functional annotation of the affected genes uncovered alterations of processes related to cellular motility, cytoskeleton dynamics, metabolic processes, synaptic support, neuroinflammation as well as signaling pathways, such as Rho, Wnt and TGF-β signaling. A fraction of these changes affected genes which displayed transcriptional differences in the brain of MS patients, as reported by publically available transcriptomic data. Gene ontology analysis of differentially methylated genes according to their constitutive cell type-specific expression in glial cells attributed alteration of cytoskeleton rearrangement and extracellular matrix remodelling to all glial cell types, while some processes, including ion transport, Wnt/TGF-β signaling and immune processes were more specifically linked to oligodendrocytes, astrocytes and microglial cells, respectively. Conclusion. Our findings strongly suggest that NAWM glial cells are highly active, even in the absence of lesional insult, collectively exhibiting a multicellular reaction in response to diffuse inflammation.

Project description:This a model from the article: A computer simulation of the hypothalamic-pituitary-adrenal axis. Gonzalez-Heydrich J, Steingard RJ, Kohane I. Proc Annu Symp Comput Appl Med Care 1994;:1010 7949852 , Abstract: This paper describes the construction of a computer model that simulates the hypothalamic-pituitary-adrenal axis (HPA axis) regulation of cortisol production. It is presented to illustrate the process of physiological modeling using standard "off the shelf" technologies. The model simulates components of the HPA axis involved in the continuous secretion and elimination of cortisol, adrenocorticotropin (ACTH), and corticotropin releasing hormone (CRH). The physiological relations of these component pieces were modeled based on the current knowledge of their functioning. Rate constants, half lives, and receptor affinities were assigned values derived from the experimental literature. At its current level of development the model is able to accurately simulate the timing, magnitude and decay of the ACTH and cortisol concentration peaks resulting from the ovine-CRH stimulation test in normal and hypercortisolemic patients. The model will be used to predict the effects of lesions in different components of the HPA axis on the time course of cortisol and ACTH levels. We plan to use the model to explore the experimental conditions required to distinguish mechanisms underlying various disorders of the HPA axis, particularly depression. Efforts are currently underway to validate the model for a large variety of normal and pathological perturbations of the HPA axis. This model was taken from the CellML repository and automatically converted to SBML. The original model was: Gonzalez-Heydrich J, Steingard RJ, Kohane I. (1994) - version02 This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

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Transcriptome analysis of normal-appearing white matter reveals cortisol- and disease-associated gene expression profiles in multiple sclerosis

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