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A module-based analytical strategy to identify novel disease-associated genes shows an inhibitory role for interleukin 7 Receptor in allergic inflammation
Unit for Clinical Systems Biology, Department of Pediatrics, University of Gothenburg, Gothenburg, Sweden.
Department of Immunology, Sahlgrenska Academy, Gothenburg, Sweden.
Department of Experimental Medicine, Lund University, Lund, Sweden.
Department of Immunology, Sahlgrenska Academy, Gothenburg, Sweden.
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2009 (English)In: BMC Systems Biology, ISSN 1752-0509, Vol. 3, no 19Article in journal (Refereed) Published
Abstract [en]

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.

CONCLUSION: We propose that a module-based analytical strategy is generally applicable to find novel genes in complex diseases.

Place, publisher, year, edition, pages
BioMed Central, 2009. Vol. 3, no 19
National Category
Medical and Health Sciences
URN: urn:nbn:se:liu:diva-98573DOI: 10.1186/1752-0509-3-19ISI: 000264392600001PubMedID: 19216740OAI: diva2:654984
Available from: 2013-10-09 Created: 2013-10-09 Last updated: 2014-10-01Bibliographically approved

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