Field, SL, Dasgupta, T, Cummings, M et al. (5 more authors) (2015) Bayesian modeling suggests that IL-12 (p40), IL-13 and MCP-1 drive murine cytokine networks in vivo. BMC Systems Biology, 9 (76). ISSN 1752-0509
Abstract
Background Cytokine-hormone network deregulations underpin pathologies ranging from autoimmune disorders to cancer, but our understanding of these networks in physiological/pathophysiological states remains patchy. We employed Bayesian networks to analyze cytokine-hormone interactions in vivo using murine lactation as a dynamic, physiological model system. Results Circulatory levels of estrogen, progesterone, prolactin and twenty-three cytokines were profiled in post partum mice with/without pups. The resultant networks were very robust and assembled about structural hubs, with evidence that interleukin (IL)-12 (p40), IL-13 and monocyte chemoattractant protein (MCP)-1 were the primary drivers of network behavior. Network structural conservation across physiological scenarios coupled with the successful empirical validation of our approach suggested that in silico network perturbations can predict in vivo qualitative responses. In silico perturbation of network components also captured biological features of cytokine interactions (antagonism, synergy, redundancy). Conclusion These findings highlight the potential of network-based approaches in identifying novel cytokine pharmacological targets and in predicting the effects of their exogenous manipulation in inflammatory/immune disorders.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015, Field et al. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
Keywords: | Bayesian network; cytokine; hormone; lactation; mouse |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Inst of Biomed & Clin Sciences (LIBACS) (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Inst of Biomed & Clin Sciences (LIBACS) (Leeds) > Obstetrics & Gynaecology (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 19 Nov 2015 14:52 |
Last Modified: | 12 Feb 2019 13:35 |
Published Version: | http://dx.doi.org/10.1186/s12918-015-0226-3 |
Status: | Published |
Publisher: | BioMed Central |
Identification Number: | 10.1186/s12918-015-0226-3 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:91991 |