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dc.contributor.authorMcGeachie, Michael Jen_US
dc.contributor.authorDahlin, Amberen_US
dc.contributor.authorQiu, Weiliangen_US
dc.contributor.authorCroteau-Chonka, Damien Cen_US
dc.contributor.authorSavage, Jessicaen_US
dc.contributor.authorWu, Ann Chenen_US
dc.contributor.authorWan, Emily Sen_US
dc.contributor.authorSordillo, Joanne Een_US
dc.contributor.authorAl-Garawi, Amalen_US
dc.contributor.authorMartinez, Fernando Den_US
dc.contributor.authorStrunk, Robert Cen_US
dc.contributor.authorLemanske, Robert Fen_US
dc.contributor.authorLiu, Andrew Hen_US
dc.contributor.authorRaby, Benjamin Aen_US
dc.contributor.authorWeiss, Scotten_US
dc.contributor.authorClish, Clary Ben_US
dc.contributor.authorLasky-Su, Jessica Aen_US
dc.date.accessioned2015-10-01T14:55:21Z
dc.date.issued2015en_US
dc.identifier.citationMcGeachie, M. J., A. Dahlin, W. Qiu, D. C. Croteau-Chonka, J. Savage, A. C. Wu, E. S. Wan, et al. 2015. “The metabolomics of asthma control: a promising link between genetics and disease.” Immunity, Inflammation and Disease 3 (3): 224-238. doi:10.1002/iid3.61. http://dx.doi.org/10.1002/iid3.61.en
dc.identifier.issn2050-4527en
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:22856848
dc.description.abstractShort-acting β agonists (e.g., albuterol) are the most commonly used medications for asthma, a disease that affects over 300 million people in the world. Metabolomic profiling of asthmatics taking β agonists presents a new and promising resource for identifying the molecular determinants of asthma control. The objective is to identify novel genetic and biochemical predictors of asthma control using an integrative “omics” approach. We generated lipidomic data by liquid chromatography tandem mass spectrometry (LC-MS), ­ using plasma samples from 20 individuals with asthma. The outcome of interest was a binary indicator of asthma control defined by the use of albuterol inhalers in the preceding week. We integrated metabolomic data with genome-wide genotype, gene expression, and methylation data of this cohort to identify genomic and molecular indicators of asthma control. A Conditional Gaussian Bayesian Network (CGBN) was generated using the strongest predictors from each of these analyses. Integrative and metabolic pathway over-representation analyses (ORA) identified enrichment of known biological pathways within the strongest molecular determinants. Of the 64 metabolites measured, 32 had known identities. The CGBN model based on four SNPs (rs9522789, rs7147228, rs2701423, rs759582) and two metabolites—monoHETE_0863 and sphingosine-1-phosphate (S1P) could predict asthma control with an AUC of 95%. Integrative ORA identified 17 significantly enriched pathways related to cellular immune response, interferon signaling, and cytokine-related signaling, for which arachidonic acid, PGE2 and S1P, in addition to six genes (CHN1, PRKCE, GNA12, OASL, OAS1, and IFIT3) appeared to drive the pathway results. Of these predictors, S1P, GNA12, and PRKCE were enriched in the results from integrative and metabolic ORAs. Through an integrative analysis of metabolomic, genomic, and methylation data from a small cohort of asthmatics, we implicate altered metabolic pathways, related to sphingolipid metabolism, in asthma control. These results provide insight into the pathophysiology of asthma control.en
dc.language.isoen_USen
dc.publisherJohn Wiley & Sons, Ltden
dc.relation.isversionofdoi:10.1002/iid3.61en
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC4578522/pdf/en
dash.licenseLAAen_US
dc.subjectAlbuterolen
dc.subjectasthmaen
dc.subjectepigeneticsen
dc.subjectgeneticsen
dc.subjectmetabolomicsen
dc.titleThe metabolomics of asthma control: a promising link between genetics and diseaseen
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden
dc.relation.journalImmunity, Inflammation and Diseaseen
dash.depositing.authorMcGeachie, Michael Jen_US
dc.date.available2015-10-01T14:55:21Z
dc.identifier.doi10.1002/iid3.61*
dash.authorsorderedfalse
dash.contributor.affiliatedCroteau-Chonka, Damien
dash.contributor.affiliatedWan, Emily
dash.contributor.affiliatedAl-Garawi, Amal
dash.contributor.affiliatedSavage, Jessica
dash.contributor.affiliatedSordillo, Joanne
dash.contributor.affiliatedWu, Ann
dash.contributor.affiliatedRaby, Benjamin
dash.contributor.affiliatedMcGeachie, Michael
dash.contributor.affiliatedWeiss, Scott
dash.contributor.affiliatedDahlin, Amber
dash.contributor.affiliatedSu, Jessica
dash.contributor.affiliatedQiu, Weiliang


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