Abstract

Event Abstract Back to Event A novel strategy for integrating gene expression profiles derived from multiple publicly available datasets highlights novel hub genes and pathways in mouse models of allergic asthma Michela Riba1*, Jose M. Garcia Manteiga1, Berislav Bosniak2, Michelle Epstein2 and Elia Stupka1 1 San Raffaele Scientific Institute, Center for Translational Genomics and Bioinformatics, Italy 2 University of Vienna, Department of Dermatology, Austria There are 30 studies of gene expression profiling of lungs from mice with allergic asthma, which shed new light on the molecular mechanisms of disease, but the experimental designs between them differ. Nevertheless, relevant genes and pathways underlying disease pathogenesis may emerge from the integration of these datasets. From 12 publically available datasets, we selected 6 for meta-­analysis on the basis of the microarray platform and in vivo experimental protocol. Our strategy was to combine a top down pathway­centered and a bottom up gene­centered analyses. The first approach consisted of selecting asthma­specific pathways from a combination of ‘enriched biological terms’ in each individual study. Whereas, secondly, we combined differentially expressed genes from individual datasets to create a gene list. From 22,690 genes and 131 samples, we obtained a core-­network of more than 300 interconnected genes unraveling known (STAT1, JAK2) and unknown hubs (PU.1, CDK1). Additionally, we successfully selected known and unknown disease-­related pathways, such as T­cell activation during an immune response, B­cell mediated immunity, phagocytosis and complement activation. The power of this strategy is the possibility of uncovering key molecules underlying disease pathogenesis utilizing datasets derived from disparate experiments Keywords: Asthma, Gene Expression, Network analysis, Meta-analysis, pathway analysis Conference: 15th International Congress of Immunology (ICI), Milan, Italy, 22 Aug - 27 Aug, 2013. Presentation Type: Abstract Topic: Immune-mediated disease pathogenesis Citation: Riba M, Garcia Manteiga JM, Bosniak B, Epstein M and Stupka E (2013). A novel strategy for integrating gene expression profiles derived from multiple publicly available datasets highlights novel hub genes and pathways in mouse models of allergic asthma. Front. Immunol. Conference Abstract: 15th International Congress of Immunology (ICI). doi: 10.3389/conf.fimmu.2013.02.00881 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 20 Jun 2013; Published Online: 22 Aug 2013. * Correspondence: Dr. Michela Riba, San Raffaele Scientific Institute, Center for Translational Genomics and Bioinformatics, Milano, Italy, riba.michela@hsr.it Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Michela Riba Jose M Garcia Manteiga Berislav Bosniak Michelle Epstein Elia Stupka Google Michela Riba Jose M Garcia Manteiga Berislav Bosniak Michelle Epstein Elia Stupka Google Scholar Michela Riba Jose M Garcia Manteiga Berislav Bosniak Michelle Epstein Elia Stupka PubMed Michela Riba Jose M Garcia Manteiga Berislav Bosniak Michelle Epstein Elia Stupka Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

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