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Interleukin-17 as a spatiotemporal bridge from acute to chronic inflammation: Novel insights from computational modeling

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WIRES MECHANISMS OF DISEASE
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WILEY
DOI: 10.1002/wsbm.1599

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acute inflammation; computational modeling; IL-17A

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A systematic review explores the role of interleukin (IL)-17A in acute inflammatory diseases and suggests that it is centrally involved in inflammation propagation. Using biological network analysis and computational methodologies, IL-17A is implicated in the cross-tissue spread of inflammation, partly regulated by neural mechanisms. The study also proposes a possible link between chronic inflammation and IL-17A-mediated acute inflammation, indicating that insights from computational modeling of acute inflammatory diseases may aid in the diagnosis and treatment of chronic inflammation.
A systematic review of several acute inflammatory diseases ranging from sepsis and trauma/hemorrhagic shock to the relevant pathology of the decade, COVID-19, points to the cytokine interleukin (IL)-17A as being centrally involved in the propagation of inflammation. We summarize the role of IL-17A in acute inflammation, leveraging insights made possible by biological network analysis and novel computational methodologies aimed at defining the spatiotemporal spread of inflammation in both experimental animal models and humans. These studies implicate IL-17A in the cross-tissue spread of inflammation, a process that appears to be in part regulated through neural mechanisms. Although acute inflammatory diseases are currently considered distinct from chronic inflammatory pathologies, we suggest that chronic inflammation may represent repeated, cyclical episodes of acute inflammation driven by mechanisms involving IL-17A. Thus, insights from computational modeling of acute inflammatory diseases may improve diagnosis and treatment of chronic inflammation; in turn, therapeutics developed for chronic/autoimmune disease may be of benefit in acute inflammation.This article is categorized under:Immune System Diseases > Computational Models

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