Translational Systems Approaches to the Biology of Inflammation and Healing

Abstract

Inflammation is a complex, non-linear process central to many of the diseases that affect both developed and emerging nations. A systems-based understanding of inflammation, coupled to translational applications, is therefore necessary for efficient development of drugs and devices, for streamlining analyses at the level of populations, and for the implementation of personalized medicine. We have carried out an iterative and ongoing program of literature analysis, generation of prospective data, data analysis, and computational modeling in various experimental and clinical inflammatory disease settings. These simulations have been used to gain basic insights into the inflammatory response under baseline, gene-knockout, and drug-treated experimental animals for in silico studies associated with the clinical settings of sepsis, trauma, acute liver failure, and wound healing to create patient-specific simulations in polytrauma, traumatic brain injury, and vocal fold inflammation; and to gain insight into host-pathogen interactions in malaria, necrotizing enterocolitis, and sepsis. These simulations have converged with other systems biology approaches (e.g., functional genomics) to aid in the design of new drugs or devices geared towards modulating inflammation. Since they include both circulating and tissue-level inflammatory mediators, these simulations transcend typical cytokine networks by associating inflammatory processes with tissue/organ impacts via tissue damage/dysfunction. This framework has now allowed us to suggest how to modulate acute inflammation in a rational, individually optimized fashion. This plethora of computational and intertwined experimental/engineering approaches is the cornerstone of Translational Systems Biology approaches for inflammatory diseases.

Keywords::

• Inflammation
• mathematical modeling
• translational research
• systems biology
• computational biology

Acknowledgements

The authors would like to acknowledge the contributions to this work of the following investigators, students, and postdoctoral fellows: Julia Arciero, Arie Baratt, Timothy R. Billiar, Frederick D. Busche, David Carney, Carson Chow, Gilles Clermont, Judy Day, Edwin Dietch, Russell Delude, Joyeeta Dutta-Moscato, James Faeder, Rena Feinman, Ali Ghuma, Mitchell P. Fink, David Hackam, Rukmini Kumar, Claudio Lagoa, Ryan M. Levy, Nicole Li, Maxim Mikheev, Rajaie Namas, Gary Nieman, Patricio Polanco, Ian Price, Jose M. Prince, Juan Carlos Puyana, Angela Reynolds, Beatrice Riviere, Matthew Rosengart, Alexey Solovyev, David L. Steed, Joshua Sullivan, David Swigon, Andres Torres, Jefrey Upperman, Katherine Verdolini, Ivan Yotov, Cordelia Ziraldo, and Sven Zenker. Additionally, several excellent technicians (Derek Barclay, David Gallo, and Binnie Betten) contributed to this work. We would also like to thank Alan Russell and Cliford Brubaker for their unwavering support.

Declaration of interest: Ths work was supported in part by the National Institutes of Health grants R01-GM-67240, P50-GM-53789, R33-HL-089082, R01-HL080926, R01-AI080799, and R01-HL-76157; National Institute on Disability and Rehabilitation Research grant H133E070024; as well as grants from the Commonwealth of Pennsylvania, the Pittsburgh Lifesciences Greenhouse, and the Pittsburgh Tissue Engineering Initiative. Te Pediatric Acute Liver Failure (PALF) Study Group is supported by the NIH-NIDDK UO1-DK072146-05. Dr. Vodovotz is a co-founder of and consultant to Immunetrics, Inc., which has licensed from the University of Pittsburgh the rights to commercialize aspects of the mathematical modeling of infammation. Drs. An and Ermentrout are also consultants to Immunetrics, Inc. The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.