title: A module-based analytical strategy to identify novel disease-associated genes shows an inhibitory role for interleukin 7 Receptor in allergic inflammation.
abstract: BACKGROUND
  The identification of novel genes by high-throughput studies of complex diseases is complicated by the large number of potential genes. However, since disease-associated genes tend to interact, one solution is to arrange them in modules based on co-expression data and known gene interactions. The hypothesis of this study was that such a module could be a) found and validated in allergic disease and b) used to find and validate one ore more novel disease-associated genes.
  
  
  RESULTS
  To test these hypotheses integrated analysis of a large number of gene expression microarray experiments from different forms of allergy was performed. This led to the identification of an experimentally validated reference gene that was used to construct a module of co-expressed and interacting genes. This module was validated in an independent material, by replicating the expression changes in allergen-challenged CD4+ cells. Moreover, the changes were reversed following treatment with corticosteroids. The module contained several novel disease-associated genes, of which the one with the highest number of interactions with known disease genes, IL7R, was selected for further validation. The expression levels of IL7R in allergen challenged CD4+ cells decreased following challenge but increased after treatment. This suggested an inhibitory role, which was confirmed by functional studies.
  
  
  CONCLUSIONS
  We propose that a module-based analytical strategy is generally applicable to find novel genes in complex diseases.
authors.affiliation: Unit for Clinical Systems Biology, Department of Pediatrics, University of Gothenburg, Gothenburg, Sweden. reza.mobini@pediat.gu.se
authors.forename: Reza
authors.initials: R
authors.lastname: Mobini
authors.forename: Bengt A
authors.initials: BA
authors.lastname: Andersson
authors.forename: Jonas
authors.initials: J
authors.lastname: Erjefält
authors.forename: Mirjana
authors.initials: M
authors.lastname: Hahn-Zoric
authors.forename: Michael A
authors.initials: MA
authors.lastname: Langston
authors.forename: Andy D
authors.initials: AD
authors.lastname: Perkins
authors.forename: Lars Olaf
authors.initials: LO
authors.lastname: Cardell
authors.forename: Mikael
authors.initials: M
authors.lastname: Benson
mesh_terms: D000305:Adrenal Cortex Hormones / Q000494:pharmacology; D015496:CD4-Positive T-Lymphocytes / Q000378:metabolism; D050990:GATA3 Transcription Factor / Q000378:metabolism; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation / Q000187:drug effects / Q000235:genetics*; D006801:Humans; D006967:Hypersensitivity / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D020395:Receptors, Interleukin-7; D018709:Statistics, Nonparametric
chemical_list: D000305:Adrenal Cortex Hormones; D050990:GATA3 Transcription Factor; C494749:GATA3 protein, human; D020395:Receptors, Interleukin-7