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dc.contributor.authorEmwas, Abdul-Hamid M.
dc.contributor.authorLuchinat, Claudio
dc.contributor.authorTurano, Paola
dc.contributor.authorTenori, Leonardo
dc.contributor.authorRoy, Raja
dc.contributor.authorSalek, Reza M.
dc.contributor.authorRyan, Danielle
dc.contributor.authorMerzaban, Jasmeen
dc.contributor.authorKaddurah-Daouk, Rima
dc.contributor.authorZeri, Ana Carolina
dc.contributor.authorNagana Gowda, G. A.
dc.contributor.authorRaftery, Daniel
dc.contributor.authorWang, Yulan
dc.contributor.authorBrennan, Lorraine
dc.contributor.authorWishart, David S.
dc.date.accessioned2014-12-10T06:57:22Z
dc.date.available2014-12-10T06:57:22Z
dc.date.issued2014-11-21
dc.identifier.citationStandardizing the experimental conditions for using urine in NMR-based metabolomic studies with a particular focus on diagnostic studies: a review 2014 Metabolomics
dc.identifier.issn1573-3882
dc.identifier.issn1573-3890
dc.identifier.pmid26109927
dc.identifier.doi10.1007/s11306-014-0746-7
dc.identifier.urihttp://hdl.handle.net/10754/337011
dc.description.abstractThe metabolic composition of human biofluids can provide important diagnostic and prognostic information. Among the biofluids most commonly analyzed in metabolomic studies, urine appears to be particularly useful. It is abundant, readily available, easily stored and can be collected by simple, noninvasive techniques. Moreover, given its chemical complexity, urine is particularly rich in potential disease biomarkers. This makes it an ideal biofluid for detecting or monitoring disease processes. Among the metabolomic tools available for urine analysis, NMR spectroscopy has proven to be particularly well-suited, because the technique is highly reproducible and requires minimal sample handling. As it permits the identification and quantification of a wide range of compounds, independent of their chemical properties, NMR spectroscopy has been frequently used to detect or discover disease fingerprints and biomarkers in urine. Although protocols for NMR data acquisition and processing have been standardized, no consensus on protocols for urine sample selection, collection, storage and preparation in NMR-based metabolomic studies have been developed. This lack of consensus may be leading to spurious biomarkers being reported and may account for a general lack of reproducibility between laboratories. Here, we review a large number of published studies on NMR-based urine metabolic profiling with the aim of identifying key variables that may affect the results of metabolomics studies. From this survey, we identify a number of issues that require either standardization or careful accounting in experimental design and provide some recommendations for urine collection, sample preparation and data acquisition.
dc.language.isoen
dc.publisherSpringer Nature
dc.relation.urlhttp://link.springer.com/10.1007/s11306-014-0746-7
dc.rightsThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
dc.subjectNMR
dc.subjectMetabolomics
dc.subjectMetabonomics
dc.subjectMetabolites profiling
dc.subjectUrine
dc.subjectBiomarker
dc.subjectHuman diseases
dc.subjectStandardization
dc.subjectDiagnosis
dc.subjectRecommendations
dc.titleStandardizing the experimental conditions for using urine in NMR-based metabolomic studies with a particular focus on diagnostic studies: a review
dc.typeArticle
dc.contributor.departmentAdvanced Nanofabrication, Imaging and Characterization Core Lab
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Division
dc.contributor.departmentBioscience Program
dc.contributor.departmentNMR
dc.identifier.journalMetabolomics
dc.identifier.pmcidPMC4475544
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionCentro Risonanze Magnetiche – CERM, University of Florence, Florence, Italy
dc.contributor.institutionFiorGen Foundation, 50019, Sesto Fiorentino, Florence, Italy
dc.contributor.institutionCentre of Biomedical Research, Formerly known as Centre of Biomedical Magnetic Resonance, Sanjay Gandhi Post-Graduate Institute of Medical Sciences Campus, Lucknow, India
dc.contributor.institutionDepartment of Biochemistry & Cambridge Systems Biology Centre, University of Cambridge, Cambridge, UK
dc.contributor.institutionEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, CB10 1SD, UK
dc.contributor.institutionSchool of Agricultural and Wine Sciences, Charles Sturt University, Wagga Wagga, Australia
dc.contributor.institutionPharmacometabolomics Center, School of Medicine, Duke University, Durham, USA
dc.contributor.institutionBrazilian Biosciences National Laboratory, LNBio, Campinas, SP, Brazil
dc.contributor.institutionDepartment of Anethesiology and Pain Medicine, Northwest Metabolomics Research Center, University of Washington, 850 Republican St., Seattle, WA, 98109, USA
dc.contributor.institutionWuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Beijing, China
dc.contributor.institutionInstitute of Food and Health and Conway Institute, School of Agriculture & Food Science, Dublin 4, Ireland
dc.contributor.institutionDepartment of Computing Science, University of Alberta, Edmonton, Alberta, Canada
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)
kaust.personEmwas, Abdul-Hamid M.
kaust.personMerzaban, Jasmeen S.
refterms.dateFOA2018-06-13T16:07:41Z
dc.date.published-online2014-11-21
dc.date.published-print2015-08


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