title: An integrative analysis of gene expression and molecular interaction data to identify dys-regulated sub-networks in inflammatory bowel disease.
abstract: BACKGROUND
  Inflammatory bowel disease (IBD) consists of two main disease-subtypes, Crohn's disease (CD) and ulcerative colitis (UC); these subtypes share overlapping genetic and clinical features. Genome-wide microarray data enable unbiased documentation of alterations in gene expression that may be disease-specific. As genetic diseases are believed to be caused by genetic alterations affecting the function of signalling pathways, module-centric optimisation algorithms, whose aim is to identify sub-networks that are dys-regulated in disease, are emerging as promising approaches.
  
  
  RESULTS
  In order to account for the topological structure of molecular interaction networks, we developed an optimisation algorithm that integrates databases of known molecular interactions with gene expression data; such integration enables identification of differentially regulated network modules. We verified the performance of our algorithm by testing it on simulated networks; we then applied the same method to study experimental data derived from microarray analysis of CD and UC biopsies and human interactome databases. This analysis allowed the extraction of dys-regulated subnetworks under different experimental conditions (inflamed and uninflamed tissues in CD and UC). Optimisation was performed to highlight differentially expressed network modules that may be common or specific to the disease subtype.
  
  
  CONCLUSIONS
  We show that the selected subnetworks include genes and pathways of known relevance for IBD; in particular, the solutions found highlight cross-talk among enriched pathways, mainly the JAK/STAT signalling pathway and the EGF receptor signalling pathway. In addition, integration of gene expression with molecular interaction data highlights nodes that, although not being differentially expressed, interact with differentially expressed nodes and are part of pathways that are relevant to IBD. The method proposed here may help identifying dys-regulated sub-networks that are common in different diseases and sub-networks whose dys-regulation is specific to a particular disease.
authors.affiliation: Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, OX3 9DS Oxford, UK. Daniele.Muraro@ndm.ox.ac.uk.
authors.forename: Daniele
authors.initials: D
authors.lastname: Muraro
authors.affiliation: Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, OX3 9DS Oxford, UK. Alison.Simmons@ndm.ox.ac.uk.
authors.forename: Alison
authors.initials: A
authors.lastname: Simmons
mesh_terms: D000465:Algorithms; D003093:Colitis, Ulcerative / Q000175:diagnosis* / Q000235:genetics*; D003424:Crohn Disease / Q000175:diagnosis* / Q000235:genetics*; D030541:Databases, Genetic; D066246:ErbB Receptors / Q000235:genetics / Q000378:metabolism; D019143:Evolution, Molecular; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D056726:Genetic Association Studies; D006801:Humans; D053613:Janus Kinase 1 / Q000235:genetics / Q000378:metabolism; D020935:MAP Kinase Signaling System; D008958:Models, Molecular; D050791:STAT Transcription Factors / Q000235:genetics / Q000378:metabolism; D015398:Signal Transduction
chemical_list: D050791:STAT Transcription Factors; D066246:ErbB Receptors; D053613:Janus Kinase 1