PLoS ONE (Jan 2014)

The role of inflammation resolution speed in airway smooth muscle mass accumulation in asthma: insight from a theoretical model.

  • Igor L Chernyavsky,
  • Huguette Croisier,
  • Lloyd A C Chapman,
  • Laura S Kimpton,
  • Jonathan E Hiorns,
  • Bindi S Brook,
  • Oliver E Jensen,
  • Charlotte K Billington,
  • Ian P Hall,
  • Simon R Johnson

DOI
https://doi.org/10.1371/journal.pone.0090162
Journal volume & issue
Vol. 9, no. 3
p. e90162

Abstract

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Despite a large amount of in vitro data, the dynamics of airway smooth muscle (ASM) mass increase in the airways of patients with asthma is not well understood. Here, we present a novel mathematical model that describes qualitatively the growth dynamics of ASM cells over short and long terms in the normal and inflammatory environments typically observed in asthma. The degree of ASM accumulation can be explained by an increase in the rate at which ASM cells switch between non-proliferative and proliferative states, driven by episodic inflammatory events. Our model explores the idea that remodelling due to ASM hyperplasia increases with the frequency and magnitude of these inflammatory events, relative to certain sensitivity thresholds. It highlights the importance of inflammation resolution speed by showing that when resolution is slow, even a series of small exacerbation events can result in significant remodelling, which persists after the inflammatory episodes. In addition, we demonstrate how the uncertainty in long-term outcome may be quantified and used to design an optimal low-risk individual anti-proliferative treatment strategy. The model shows that the rate of clearance of ASM proliferation and recruitment factors after an acute inflammatory event is a potentially important, and hitherto unrecognised, target for anti-remodelling therapy in asthma. It also suggests new ways of quantifying inflammation severity that could improve prediction of the extent of ASM accumulation. This ASM growth model should prove useful for designing new experiments or as a building block of more detailed multi-cellular tissue-level models.