Drawing networks of rejection - a systems biological approach to the identification of candidate genes in heart transplantation

Martin Cadeiras, Manuel von Bayern, Anshu Sinha, Khurram Shahzad, Farhana Latif, Wei Keat Lim, Hernan Grenett, Esteban Tabak, Tod Klingler, Andrea Califano, Mario C. Deng

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

Technological development led to an increased interest in systems biological approaches to characterize disease mechanisms and candidate genes relevant to specific diseases. We suggested that the human peripheral blood mononuclear cells (PBMC) network can be delineated by cellular reconstruction to guide identification of candidate genes. Based on 285 microarrays (7370 genes) from 98 heart transplant patients enrolled in the Cardiac Allograft Rejection Gene Expression Observational study, we used an information-theoretic, reverse-engineering algorithm called ARACNe (algorithm for the reconstruction of accurate cellular networks) and chromatin immunoprecipitation assay to reconstruct and validate a putative gene PBMC interaction network. We focused our analysis on transcription factor (TF) genes and developed a priority score to incorporate aspects of network dynamics and information from published literature to supervise gene discovery. ARACNe generated a cellular network and predicted interactions for each TF during rejection and quiescence. Genes ranked highest by priority score included those related to apoptosis, humoural and cellular immune response such as GA binding protein transcription factor (GABP), nuclear factor of κ light polypeptide gene enhancer in B-cells (NFκB), Fas (TNFRSF6)-associated via death domain (FADD) and c-AMP response element binding protein. We used the TF CREB to validate our network. ARACNe predicted 29 putative first-neighbour genes of CREB. Eleven of these (37%) were previously reported. Out of the 18 unknown predicted interactions, 14 primers were identified and 11 could be immunoprecipitated (78.6%). Overall, 75% (n= 22) inferred CREB targets were validated, a significantly higher fraction than randomly expected (P < 0.001, Fisher's exact test). Our results confirm the accuracy of ARACNe to reconstruct the PBMC transcriptional network and show the utility of systems biological approaches to identify possible molecular targets and biomarkers.

Original languageEnglish (US)
Pages (from-to)949-956
Number of pages8
JournalJournal of Cellular and Molecular Medicine
Volume15
Issue number4
DOIs
StatePublished - Apr 1 2011
Externally publishedYes

Keywords

  • Candidate gene
  • Cardiac transplant
  • Cellular networks
  • Gene expression
  • Rejection
  • Systems biology

ASJC Scopus subject areas

  • Molecular Medicine
  • Cell Biology

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    Cadeiras, M., von Bayern, M., Sinha, A., Shahzad, K., Latif, F., Lim, W. K., Grenett, H., Tabak, E., Klingler, T., Califano, A., & Deng, M. C. (2011). Drawing networks of rejection - a systems biological approach to the identification of candidate genes in heart transplantation. Journal of Cellular and Molecular Medicine, 15(4), 949-956. https://doi.org/10.1111/j.1582-4934.2010.01092.x