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dc.contributor.authorPapa, Eli
dc.contributor.authorDocktor, Michael
dc.contributor.authorSmillie, Christopher
dc.contributor.authorWeber, Sarah
dc.contributor.authorPreheim, Sarah Pacocha
dc.contributor.authorGevers, Dirk
dc.contributor.authorGiannoukos, Georgia
dc.contributor.authorCiulla, Dawn
dc.contributor.authorTabbaa, Diana
dc.contributor.authorIngram, Jay
dc.contributor.authorSchauer, David B.
dc.contributor.authorWard, Doyle V.
dc.contributor.authorKorzenik, Joshua R.
dc.contributor.authorXavier, Ramnik J.
dc.contributor.authorBousvaros, Athos
dc.contributor.authorAlm, Eric J.
dc.date.accessioned2012-08-29T18:04:42Z
dc.date.available2012-08-29T18:04:42Z
dc.date.issued2012-06
dc.date.submitted2012-03
dc.identifier.issn1932-6203
dc.identifier.urihttp://hdl.handle.net/1721.1/72428
dc.description.abstractBackground: Pediatric inflammatory bowel disease (IBD) is challenging to diagnose because of the non-specificity of symptoms; an unequivocal diagnosis can only be made using colonoscopy, which clinicians are reluctant to recommend for children. Diagnosis of pediatric IBD is therefore frequently delayed, leading to inappropriate treatment plans and poor outcomes. We investigated the use of 16S rRNA sequencing of fecal samples and new analytical methods to assess differences in the microbiota of children with IBD and other gastrointestinal disorders. Methodology/Principal Findings: We applied synthetic learning in microbial ecology (SLiME) analysis to 16S sequencing data obtained from i) published surveys of microbiota diversity in IBD and ii) fecal samples from 91 children and young adults who were treated in the gastroenterology program of Children’s Hospital (Boston, USA). The developed method accurately distinguished control samples from those of patients with IBD; the area under the receiver-operating-characteristic curve (AUC) value was 0.83 (corresponding to 80.3% sensitivity and 69.7% specificity at a set threshold). The accuracy was maintained among data sets collected by different sampling and sequencing methods. The method identified taxa associated with disease states and distinguished patients with Crohn’s disease from those with ulcerative colitis with reasonable accuracy. The findings were validated using samples from an additional group of 68 patients; the validation test identified patients with IBD with an AUC value of 0.84 (e.g. 92% sensitivity, 58.5% specificity). Conclusions/Significance: Microbiome-based diagnostics can distinguish pediatric patients with IBD from patients with similar symptoms. Although this test can not replace endoscopy and histological examination as diagnostic tools, classification based on microbial diversity is an effective complementary technique for IBD detection in pediatric patients.en_US
dc.description.sponsorshipNatural Sciences and Engineering Research Council of Canada (Award NSERC PGS D)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (1-R21-A1084032-01A1)en_US
dc.language.isoen_US
dc.publisherPublic Library of Scienceen_US
dc.relation.isversionofhttp://dx.doi.org/10.1371/journal.pone.0039242en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/2.5/en_US
dc.sourcePLoSen_US
dc.titleNon-Invasive Mapping of the Gastrointestinal Microbiota Identifies Children with Inflammatory Bowel Diseaseen_US
dc.typeArticleen_US
dc.identifier.citationPapa, Eliseo et al. “Non-Invasive Mapping of the Gastrointestinal Microbiota Identifies Children with Inflammatory Bowel Disease.” Ed. Jacques Ravel. PLoS ONE 7.6 (2012): e39242.en_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technologyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computational and Systems Biology Programen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Division of Comparative Medicineen_US
dc.contributor.approverAlm, Eric J.
dc.contributor.mitauthorPapa, Eli
dc.contributor.mitauthorSmillie, Christopher
dc.contributor.mitauthorWeber, Sarah
dc.contributor.mitauthorPreheim, Sarah Pacocha
dc.contributor.mitauthorSchauer, David B.
dc.contributor.mitauthorAlm, Eric J.
dc.relation.journalPLoS ONEen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsPapa, Eliseo; Docktor, Michael; Smillie, Christopher; Weber, Sarah; Preheim, Sarah P.; Gevers, Dirk; Giannoukos, Georgia; Ciulla, Dawn; Tabbaa, Diana; Ingram, Jay; Schauer, David B.; Ward, Doyle V.; Korzenik, Joshua R.; Xavier, Ramnik J.; Bousvaros, Athos; Alm, Eric J.en
dc.identifier.orcidhttps://orcid.org/0000-0001-8294-9364
dc.identifier.orcidhttps://orcid.org/0000-0002-8202-5222
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


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