Genome-wide network analysis reveals the global properties of IFN-beta immediate transcriptional effects in humans

Fernald, G. H., Knott, S., Pachner, A., Caillier, S. J., Narayan, K., Oksenberg, J. R., Mousavi, P., Baranzini, S. E. (April 2007) Genome-wide network analysis reveals the global properties of IFN-beta immediate transcriptional effects in humans. J Immunol, 178 (8). pp. 5076-85. ISSN 0022-1767 (Print)0022-1767

URL: http://www.ncbi.nlm.nih.gov/pubmed/17404290
DOI: 10.4049/​jimmunol.178.8.5076

Abstract

IFN-beta effectively controls clinical exacerbations and magnetic resonance imaging activity in most multiple sclerosis patients. However, its mechanism of action has not been yet fully elucidated. In this study we used DNA microarrays to analyze the longitudinal transcriptional profile of blood cells within a week of IFN-beta administration. Using differential expression and gene ontology analyses we found evidence of a general decrease in the cellular activity of T lymphocytes resembling the endogenous antiviral response of IFNs. In contrast, most of the differentially expressed genes (DEGs) from untreated individuals were involved in cellular physiological processes. We then used mutual information (MI) to build networks of coregulated genes in both treated and untreated individuals. Interestingly, the connectivity distribution (k) of networks generated with high MI values displayed scale-free properties. Conversely, the observed k for networks generated with suboptimal MI values approximated a Poisson distribution, suggesting that MI captures biologically relevant interactions. Gene networks from individuals treated with IFN-beta revealed a tight core of immune- and apoptosis-related genes associated with higher values of MI. In contrast, networks obtained from untreated individuals primarily reflected cellular housekeeping functions. Finally, we trained a neural network to reverse engineer the directionality of the main interactions observed at the biological process level. This is the first study that incorporates network analysis to investigate gene regulation in response to a therapeutic drug in humans. Implications of this method in the creation of personalized models of response to therapy are discussed.

Item Type: Paper
Uncontrolled Keywords: Gene Expression Profiling *Gene Regulatory Networks Humans Interferon-beta/*pharmacology Transcription, Genetic/*drug effects
Subjects: bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > transcription
bioinformatics > genomics and proteomics > analysis and processing > microarray gene expression processing
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function > gene expression
CSHL Authors:
Communities: CSHL labs > Hannon lab
Depositing User: Matt Covey
Date: 15 April 2007
Date Deposited: 18 Mar 2015 15:29
Last Modified: 18 Mar 2015 15:29
Related URLs:
URI: http://repository.cshl.edu/id/eprint/31284

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