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Importance of Correlation between Gene Expression Levels: Application to the Type I Interferon Signature in Rheumatoid Arthritis

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  • Frédéric Reynier
  • Fabien Petit
  • Malick Paye
  • Fanny Turrel-Davin
  • Pierre-Emmanuel Imbert
  • Arnaud Hot
  • Bruno Mougin
  • Pierre Miossec

Abstract

Background: The analysis of gene expression data shows that many genes display similarity in their expression profiles suggesting some co-regulation. Here, we investigated the co-expression patterns in gene expression data and proposed a correlation-based research method to stratify individuals. Methodology/Principal Findings: Using blood from rheumatoid arthritis (RA) patients, we investigated the gene expression profiles from whole blood using Affymetrix microarray technology. Co-expressed genes were analyzed by a biclustering method, followed by gene ontology analysis of the relevant biclusters. Taking the type I interferon (IFN) pathway as an example, a classification algorithm was developed from the 102 RA patients and extended to 10 systemic lupus erythematosus (SLE) patients and 100 healthy volunteers to further characterize individuals. We developed a correlation-based algorithm referred to as Classification Algorithm Based on a Biological Signature (CABS), an alternative to other approaches focused specifically on the expression levels. This algorithm applied to the expression of 35 IFN-related genes showed that the IFN signature presented a heterogeneous expression between RA, SLE and healthy controls which could reflect the level of global IFN signature activation. Moreover, the monitoring of the IFN-related genes during the anti-TNF treatment identified changes in type I IFN gene activity induced in RA patients. Conclusions: In conclusion, we have proposed an original method to analyze genes sharing an expression pattern and a biological function showing that the activation levels of a biological signature could be characterized by its overall state of correlation.

Suggested Citation

  • Frédéric Reynier & Fabien Petit & Malick Paye & Fanny Turrel-Davin & Pierre-Emmanuel Imbert & Arnaud Hot & Bruno Mougin & Pierre Miossec, 2011. "Importance of Correlation between Gene Expression Levels: Application to the Type I Interferon Signature in Rheumatoid Arthritis," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-8, October.
    • Handle: RePEc:plo:pone00:0024828
    DOI: 10.1371/journal.pone.0024828
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    References listed on IDEAS

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    1. M. Kathleen Kerr, 2003. "Design Considerations for Efficient and Effective Microarray Studies," Biometrics, The International Biometric Society, vol. 59(4), pages 822-828, December.
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    Cited by:

    1. Emily C Somers & Wenpu Zhao & Emily E Lewis & Lu Wang & Jeffrey J Wing & Baskaran Sundaram & Ella A Kazerooni & W Joseph McCune & Mariana J Kaplan, 2012. "Type I Interferons Are Associated with Subclinical Markers of Cardiovascular Disease in a Cohort of Systemic Lupus Erythematosus Patients," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-8, May.

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