Computational approach to characterize causative factors and molecular indicators of chronic wound inflammation

J Immunol. 2014 Feb 15;192(4):1824-34. doi: 10.4049/jimmunol.1302481. Epub 2014 Jan 22.


Chronic inflammation is rapidly becoming recognized as a key contributor to numerous pathologies. Despite detailed investigations, understanding of the molecular mechanisms regulating inflammation is incomplete. Knowledge of such critical regulatory processes and informative indicators of chronic inflammation is necessary for efficacious therapeutic interventions and diagnostic support to clinicians. We used a computational modeling approach to elucidate the critical factors responsible for chronic inflammation and to identify robust molecular indicators of chronic inflammatory conditions. Our kinetic model successfully captured experimentally observed cell and cytokine dynamics for both acute and chronic inflammatory responses. Using sensitivity analysis, we identified macrophage influx and efflux rate modulation as the strongest inducing factor of chronic inflammation for a wide range of scenarios. Moreover, our model predicted that, among all major inflammatory mediators, IL-6, TGF-β, and PDGF may generally be considered the most sensitive and robust indicators of chronic inflammation, which is supported by existing, but limited, experimental evidence.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Computer Simulation*
  • Humans
  • Inflammation / immunology*
  • Interleukin-6 / metabolism
  • Macrophages / immunology
  • Neutrophils / immunology
  • Platelet-Derived Growth Factor / metabolism
  • Transforming Growth Factor beta / metabolism
  • Wounds and Injuries / immunology*


  • IL6 protein, human
  • Interleukin-6
  • Platelet-Derived Growth Factor
  • Transforming Growth Factor beta
  • platelet-derived growth factor A