Dataset Information

An in silico modeling approach to understanding the dynamics of sarcoidosis.

ABSTRACT:

Background

Sarcoidosis is a polygenic disease with diverse phenotypic presentations characterized by an abnormal antigen-mediated Th1 type immune response. At present, progress towards understanding sarcoidosis disease mechanisms and the development of novel treatments is limited by constraints attendant to conducting human research in a rare disease in the absence of relevant animal models. We sought to develop a computational model to enhance our understanding of the pathological mechanisms of and predict potential treatments of sarcoidosis.

Methodology/results

Based upon the literature, we developed a computational model of known interactions between essential immune cells (antigen-presenting macrophages, effector and regulatory T cells) and cytokine mediators (IL-2, TNF?, IFN?) of granulomatous inflammation during sarcoidosis. The dynamics of these interactions are described by a set of ordinary differential equations. The model predicts bistable switching behavior which is consistent with normal (self-limited) and "sarcoidosis-like" (sustained) activation of the inflammatory components of the system following a single antigen challenge. By perturbing the influence of model components using inhibitors of the cytokine mediators, distinct clinically relevant disease phenotypes were represented. Finally, the model was shown to be useful for pre-clinical testing of therapies based upon molecular targets and dose-effect relationships.

Conclusions/significance

Our work illustrates a dynamic computer simulation of granulomatous inflammation scenarios that is useful for the investigation of disease mechanisms and for pre-clinical therapeutic testing. In lieu of relevant in vitro or animal surrogates, our model may provide for the screening of potential therapies for specific sarcoidosis disease phenotypes in advance of expensive clinical trials.

SUBMITTER: Aguda BD

PROVIDER: S-EPMC3103504 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

An in silico modeling approach to understanding the dynamics of sarcoidosis.

Aguda Baltazar D BD Marsh Clay B CB Thacker Michael M Crouser Elliott D ED

PloS one 20110527 5

<h4>Background</h4>Sarcoidosis is a polygenic disease with diverse phenotypic presentations characterized by an abnormal antigen-mediated Th1 type immune response. At present, progress towards understanding sarcoidosis disease mechanisms and the development of novel treatments is limited by constraints attendant to conducting human research in a rare disease in the absence of relevant animal models. We sought to develop a computational model to enhance our understanding of the pathological mecha ...[more]

PMID: 21637752

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Dataset Information

An in silico modeling approach to understanding the dynamics of sarcoidosis.

Background

Methodology/results

Conclusions/significance

Publications

An in silico modeling approach to understanding the dynamics of sarcoidosis.

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