Dynamic balance of pro- and anti-inflammatory signals controls disease and limits pathology.

Autor: Cicchese JM; Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA., Evans S; Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI, USA., Hult C; Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA.; Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI, USA., Joslyn LR; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA., Wessler T; Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA.; Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI, USA., Millar JA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA., Marino S; Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI, USA., Cilfone NA; Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA., Mattila JT; Department of Infectious Diseases and Microbiology, University of Pittsburgh, Pittsburgh, PA, USA., Linderman JJ; Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA., Kirschner DE; Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI, USA.
Jazyk: angličtina
Zdroj: Immunological reviews [Immunol Rev] 2018 Sep; Vol. 285 (1), pp. 147-167.
DOI: 10.1111/imr.12671
Abstrakt: Immune responses to pathogens are complex and not well understood in many diseases, and this is especially true for infections by persistent pathogens. One mechanism that allows for long-term control of infection while also preventing an over-zealous inflammatory response from causing extensive tissue damage is for the immune system to balance pro- and anti-inflammatory cells and signals. This balance is dynamic and the immune system responds to cues from both host and pathogen, maintaining a steady state across multiple scales through continuous feedback. Identifying the signals, cells, cytokines, and other immune response factors that mediate this balance over time has been difficult using traditional research strategies. Computational modeling studies based on data from traditional systems can identify how this balance contributes to immunity. Here we provide evidence from both experimental and mathematical/computational studies to support the concept of a dynamic balance operating during persistent and other infection scenarios. We focus mainly on tuberculosis, currently the leading cause of death due to infectious disease in the world, and also provide evidence for other infections. A better understanding of the dynamically balanced immune response can help shape treatment strategies that utilize both drugs and host-directed therapies.
(© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)
Databáze: MEDLINE
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