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A network-based analysis of systemic inflammation in humans

Nature volume 437, pages 1032–1037 (2005)Cite this article

A Corrigendum to this article was published on 01 December 2005

Abstract

Oligonucleotide and complementary DNA microarrays are being used to subclassify histologically similar tumours, monitor disease progress, and individualize treatment regimens1,2,3,4,5. However, extracting new biological insight from high-throughput genomic studies of human diseases is a challenge, limited by difficulties in recognizing and evaluating relevant biological processes from huge quantities of experimental data. Here we present a structured network knowledge-base approach to analyse genome-wide transcriptional responses in the context of known functional interrelationships among proteins, small molecules and phenotypes. This approach was used to analyse changes in blood leukocyte gene expression patterns in human subjects receiving an inflammatory stimulus (bacterial endotoxin). We explore the known genome-wide interaction network to identify significant functional modules perturbed in response to this stimulus. Our analysis reveals that the human blood leukocyte response to acute systemic inflammation includes the transient dysregulation of leukocyte bioenergetics and modulation of translational machinery. These findings provide insight into the regulation of global leukocyte activities as they relate to innate immune system tolerance and increased susceptibility to infection in humans.

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Figure 1: Gene expression profiles of circulating leukocytes in response to bacterial endotoxin infusion.
Figure 2: Pathway analysis of representative genes involved in innate immunity.
Figure 3: Network representation of the biological processes underlying the temporal response of blood leukocytes to in vivo endotoxin administration.

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Acknowledgements

We thank S. M. Coyle for clinical assistance, and J. Wilhelmy, A. Kumar, S. MacMillan and A. Abouhamze for technical assistance. This work was supported by an Injury and the Host Response to Inflammation Large Scale Collaborative Research Program Award from the National Institute of General Medical Sciences (to R.G.T.).

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Author notes

  1. Steve E. Calvano and Wenzhong Xiao: *These authors contributed equally to this work

Authors and Affiliations

  1. Department of Surgery, UMDNJ-Robert Wood Johnson Medical School, New Jersey, 08903, New Brunswick, USA

    Steve E. Calvano & Stephen F. Lowry

  2. Stanford Genome Technology Center, California, 94304, Palo Alto, USA

    Wenzhong Xiao, Michael N. Mindrinos & Ronald W. Davis

  3. Ingenuity Systems Inc, California, 94043, Mountain View, USA

    Daniel R. Richards, Ramon M. Felciano, Raymond J. Cho & Richard O. Chen

  4. Departments of Molecular Genetics and Microbiology, University of Florida College of Medicine, Florida, 32610, Gainesville, USA

    Henry V. Baker

  5. Department of Surgery, University of Florida College of Medicine, Florida, 32610, Gainesville, USA

    Henry V. Baker, S. Kevin Tschoeke & Lyle L. Moldawer

  6. Department of Surgery, Washington University in St Louis, Missouri, 63110, St Louis, USA

    Bernard H. Brownstein & J. Perren Cobb

  7. Department of Surgery, University of Rochester School of Medicine, New York, 14642, Rochester, USA

    Carol Miller-Graziano

  8. Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Massachusetts, 02114, Boston, USA

    Ronald G. Tompkins

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Consortia

Inflammation and Host Response to Injury Large Scale Collaborative Research Program

Corresponding author

Correspondence to Ronald W. Davis.

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Competing interests

D.R.R., R.M.F., R.J.C. and R.O.C. are employees of Ingenuity Systems Inc.

Additional information

Lists of participants and affiliations appear at the end of the paper

Supplementary information

Supplementary Methods 1

This file includes methods and results of the verification experiment (Adobe Acrobat File, 22KB) (PDF 21 kb)

Supplementary Methods 2

This file includes additional methods of the knowledge-base network analysis (Adobe Acrobat File, 2.0MB) (PDF 2079 kb)

Supplementary Figure 1

This figure shows gene-gene interactions surrounding RELA captured in the observed human interactome. (Adobe Acrobat File, 1.8MB) (PDF 1831 kb)

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Calvano, S., Xiao, W., Richards, D. et al. A network-based analysis of systemic inflammation in humans. Nature 437, 1032–1037 (2005). https://doi.org/10.1038/nature03985

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