Use of metabolomics for the identification and validation of clinical biomarkers for preterm birth: Preterm SAMBA

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dc.contributor.authorCecatti, Jose G.
dc.contributor.authorSouza, Renato T.
dc.contributor.authorSulek, Karolina
dc.contributor.authorCosta, Maria L.
dc.contributor.authorKenny, Louise C.
dc.contributor.authorMcCowan, Lesley M.
dc.contributor.authorPacagnella, Rodolfo C.
dc.contributor.authorVillas-Boas, Silas G.
dc.contributor.authorMayrink, Jussara
dc.contributor.authorPassini, Renato
dc.contributor.authorFranchini, Kleber G.
dc.contributor.authorBaker, Philip N.
dc.contributor.authorParpinelli, Mary A.
dc.contributor.authorCalderon, Iracema M. [UNESP]
dc.contributor.authorCassettari, Bianca F. [UNESP]
dc.contributor.authorVetorazzi, Janete
dc.contributor.authorPfitscher, Lucia
dc.contributor.authorFilho, Edilberto P. Rocha
dc.contributor.authorLeite, Débora F.
dc.contributor.authorFeitosa, Francisco E.
dc.contributor.authorCosta e Silva, Carolina L.
dc.contributor.authorPoston, Lucilla
dc.contributor.authorMyers, Jenny E.
dc.contributor.authorSimpson, Nigel A.B.
dc.contributor.authorWalker, James J.
dc.contributor.authorDekker, Gus A.
dc.contributor.authorRoberts, Claire T.
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)
dc.contributor.institutionLiggins Institute
dc.contributor.institutionIrish Centre for Fetal and Neonatal Translational Research (INFANT)
dc.contributor.institutionFaculty of Medical and Health Sciences
dc.contributor.institutionSchool of Biological Sciences
dc.contributor.institutionLNBio
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionFederal University of Rio Grande do Sul
dc.contributor.institutionUniversidade Federal de Pernambuco (UFPE)
dc.contributor.institutionFederal University of Ceará
dc.contributor.institutionKing's College London and King's Health Partners
dc.contributor.institutionUniversity of Manchester
dc.contributor.institutionUniversity of Leeds
dc.contributor.institutionUniversity of Adelaide
dc.date.accessioned2018-12-11T17:29:12Z
dc.date.available2018-12-11T17:29:12Z
dc.date.issued2016-08-08
dc.description.abstractBackground: Spontaneous preterm birth is a complex syndrome with multiple pathways interactions determining its occurrence, including genetic, immunological, physiologic, biochemical and environmental factors. Despite great worldwide efforts in preterm birth prevention, there are no recent effective therapeutic strategies able to decrease spontaneous preterm birth rates or their consequent neonatal morbidity/mortality. The Preterm SAMBA study will associate metabolomics technologies to identify clinical and metabolite predictors for preterm birth. These innovative and unbiased techniques might be a strategic key to advance spontaneous preterm birth prediction. Methods/design: Preterm SAMBA study consists of a discovery phase to identify biophysical and untargeted metabolomics from blood and hair samples associated with preterm birth, plus a validation phase to evaluate the performance of the predictive modelling. The first phase, a case-control study, will randomly select 100 women who had a spontaneous preterm birth (before 37 weeks) and 100 women who had term birth in the Cork Ireland and Auckland New Zealand cohorts within the SCOPE study, an international consortium aimed to identify potential metabolomic predictors using biophysical data and blood samples collected at 20 weeks of gestation. The validation phase will recruit 1150 Brazilian pregnant women from five participant centres and will collect blood and hair samples at 20 weeks of gestation to evaluate the performance of the algorithm model (sensitivity, specificity, predictive values and likelihood ratios) in predicting spontaneous preterm birth (before 34 weeks, with a secondary analysis of delivery before 37 weeks). Discussion: The Preterm SAMBA study intends to step forward on preterm birth prediction using metabolomics techniques, and accurate protocols for sample collection among multi-ethnic populations. The use of metabolomics in medical science research is innovative and promises to provide solutions for disorders with multiple complex underlying determinants such as spontaneous preterm birth.en
dc.description.affiliationUniversity of Campinas (UNICAMP) School of Medical Sciences Department of Obstetrics and Gynecology, R. Alexander Fleming, 101
dc.description.affiliationUniversity of Auckland Gravida: National Centre for Growth and Development Liggins Institute
dc.description.affiliationUniversity College Cork Irish Centre for Fetal and Neonatal Translational Research (INFANT) Department of Obstetrics and Gynaecology
dc.description.affiliationUniversity of Auckland South Auckland Clinical School Faculty of Medical and Health Sciences
dc.description.affiliationUniversity of Auckland School of Biological Sciences
dc.description.affiliationUniversity of Campinas (UNICAMP) LNBio-Brazilian Biosciences National Laboratory and School of Medical Sciences
dc.description.affiliationSchool of Medical Sciences University of Campinas
dc.description.affiliationLNBio
dc.description.affiliationSchool of Medicine of Botucatu UNESP
dc.description.affiliationSchool of Medicine Federal University of Rio Grande do Sul
dc.description.affiliationSchool of Medicine Federal University of Pernambuco
dc.description.affiliationSchool of Medicine Federal University of Ceará
dc.description.affiliationKing's College London and King's Health Partners
dc.description.affiliationMaternal and Fetal Health Research Centre University of Manchester
dc.description.affiliationUniversity of Leeds
dc.description.affiliationUniversity of Adelaide
dc.description.affiliationUnespSchool of Medicine of Botucatu UNESP
dc.identifierhttp://dx.doi.org/10.1186/s12884-016-1006-9
dc.identifier.citationBMC Pregnancy and Childbirth, v. 16, n. 1, 2016.
dc.identifier.doi10.1186/s12884-016-1006-9
dc.identifier.file2-s2.0-84981273829.pdf
dc.identifier.file2-s2.0-84981273829.pdf
dc.identifier.issn1471-2393
dc.identifier.scopus2-s2.0-84981273829
dc.identifier.urihttp://hdl.handle.net/11449/178189
dc.language.isoeng
dc.relation.ispartofBMC Pregnancy and Childbirth
dc.relation.ispartofsjr1,427
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectBiological biomarker
dc.subjectMass spectrometry
dc.subjectMetabolomics
dc.subjectPrediction
dc.subjectSpontaneous preterm birth
dc.titleUse of metabolomics for the identification and validation of clinical biomarkers for preterm birth: Preterm SAMBAen
dc.typeArtigo

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