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A Systems Biology Approach to Blood pp 227–243Cite as

Innate Immunity in Disease: Insights from Mathematical Modeling and Analysis

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Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 844))

Abstract

The acute inflammatory response is a complex defense mechanism that has evolved to respond rapidly to injury, infection, and other disruptions in homeostasis. This robust responsiveness to biological stress likely endows the host with increased fitness, but over-robust or inadequate inflammation predisposes the host to various diseases. Importantly, well-compartmentalized inflammation is generally beneficial, but spillover of inflammation into the blood is a hallmark—and likely also a driver—of self-maintaining inflammation. The blood is also a key entry point and immunological interface for vectors of parasitic diseases, diseases that themselves incite systemic inflammation. The complex role of inflammation in health and disease has made this biological system difficult to understand comprehensively and modulate rationally for therapeutic purposes. Consequently, systems approaches have been applied in order to characterize dynamical properties and identify key control points in inflammation. This process begins with the collection of high-dimensional, experimental, and clinical data, followed by data reduction and data-driven modeling that finally informs mechanistic computational models for analysis, prediction, and rational modulation. These studies have suggested that the overall architecture of the inflammatory response includes a multiscale positive feedback from inflammation → tissue damage → inflammation, which is often inadequately controlled by negative feedback from anti-inflammatory mediators. Given the importance of the blood interface for the inflammatory response, and the accessibility of this compartment both as an immunological sampling reservoir for vectors as well as for diagnosis and therapy, we suggest that any rational efforts at modulating inflammation via the blood compartment must involve computational modeling.

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Abbreviations

ABM:

Agent-based model

AsNOS:

Anopheles stephensi nitric oxide synthase

DAMP:

Damage-associated molecular pattern molecule

DBN:

Dynamic Bayesian Networks

GMM:

Genetically modified mosquito

MODS:

Multiple organ dysfunction syndrome

ODE:

Ordinary differential equations

PCA:

Principal component analysis

RBM:

Rule-based model

sTNFR:

Soluble tumor necrosis factor-α receptor

TNF-α:

Tumor necrosis factor-α

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Acknowledgments

This work was supported in part by the National Institutes of Health grants R01GM67240, P50GM53789, R33HL089082, R01HL080926, R01AI080799, R01HL76157, R01DC008290, and UO1 DK072146; National Institute on Disability and Rehabilitation Research grant H133E070024; a Shared University Research Award from IBM, Inc.; and grants from the Commonwealth of Pennsylvania, the Pittsburgh Life Sciences Greenhouse, and the Pittsburgh Tissue Engineering Initiative/Department of Defense.

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Authors and Affiliations

  1. University of Pittsburgh, 3064 Biomedical Sciences Tower 3, 3501 Fifth Ave., 15213, Pittsburgh, PA, USA

    Nabil Azhar

  2. Department of Surgery, University of Pittsburgh, W944 Biomedical Sciences Tower, 200 Lothrop St., 15213, Pittsburgh, PA, USA

    Yoram Vodovotz PhD

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  1. Nabil Azhar
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Correspondence to Yoram Vodovotz PhD .

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Editors and Affiliations

  1. Departments of Pediatrics and Cell & Molecular Biology, Northwestern University Feinberg School of Medicine and Lurie Children’s Hospital of Chicago, Chicago, Illinois, USA

    Seth Joel Corey

  2. Department of Statistics, Rice University, Houston, Texas, USA

    Marek Kimmel

  3. Northwestern University Comprehensive Cancer Center, Evanston, Illinois, USA

    Joshua N. Leonard

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Azhar, N., Vodovotz, Y. (2014). Innate Immunity in Disease: Insights from Mathematical Modeling and Analysis. In: Corey, S., Kimmel, M., Leonard, J. (eds) A Systems Biology Approach to Blood. Advances in Experimental Medicine and Biology, vol 844. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2095-2_11

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