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The Proceedings of the American Thoracic Society 4:85-91 (2007)
© 2007 The American Thoracic Society
doi: 10.1513/pats.200607-139JG
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Towards Systems Biology of Human Pulmonary Fibrosis

Sean M. Studer and Naftali Kaminski

Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania

Correspondence and requests for reprints should be addressed to Naftali Kaminski, M.D., Dorothy P. & Richard P. Simmons Center for Interstitial Lung Disease, Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh Medical Center, NW 628 MUH, 3459 5th Avenue, Pittsburgh, PA 15261. E-mail: kaminskin{at}upmc.edu

ABSTRACT

The integrated effect of multiple pathways, molecules, genetic polymorphisms, environmental stimuli, and possible infection determines the lung phenotype in idiopathic pulmonary fibrosis (IPF), a chronic progressive and often lethal lung disease. Systems biology approaches aim to provide a systemwide view of biological process using computational tools and high-throughput technologies. Although much of the analysis of genome-level transcriptional high-resolution profiles of IPF was reductionist, usually focusing on a single factor in the disease process, there are some studies that implement systems approaches. We discuss these analyses and provide examples of the global analysis of IPF, hypersensitivity pneumonitis, and nonspecific interstitial pneumonia. Detailed quantitative phenotyping and correlation with microarray results as well as high-throughput genotyping should provide us with the datasets to implement systems biology approaches in fibrosis research. Interdisciplinary teams and training of junior investigators in the vocabulary of systems biology should allow us to use these datasets integratively and generate a global model of human pulmonary fibrosis.

Key Words: Cancer Biomedical Informatics Grid, caBIG • idiopathic pulmonary fibrosis • interstitial lung disease • microarrays




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