Your browser doesn't support javascript.
loading
Use of metabolomics for the identification and validation of clinical biomarkers for preterm birth: Preterm SAMBA.
Cecatti, Jose G; Souza, Renato T; Sulek, Karolina; Costa, Maria L; Kenny, Louise C; McCowan, Lesley M; Pacagnella, Rodolfo C; Villas-Boas, Silas G; Mayrink, Jussara; Passini, Renato; Franchini, Kleber G; Baker, Philip N.
Affiliation
  • Cecatti JG; Department of Obstetrics and Gynecology, University of Campinas (UNICAMP) School of Medical Sciences, R. Alexander Fleming, 101, Campinas, SP,, 13083-881, Brazil. cecatti@unicamp.br.
  • Souza RT; Department of Obstetrics and Gynecology, University of Campinas (UNICAMP) School of Medical Sciences, R. Alexander Fleming, 101, Campinas, SP,, 13083-881, Brazil.
  • Sulek K; Gravida: National Centre for Growth & Development, Liggins Institute, University of Auckland, Auckland, New Zealand.
  • Costa ML; Department of Obstetrics and Gynecology, University of Campinas (UNICAMP) School of Medical Sciences, R. Alexander Fleming, 101, Campinas, SP,, 13083-881, Brazil.
  • Kenny LC; Irish Centre for Fetal and Neonatal Translational Research (INFANT), Department of Obstetrics and Gynaecology, University College Cork, Cork, Ireland.
  • McCowan LM; South Auckland Clinical School, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.
  • Pacagnella RC; Department of Obstetrics and Gynecology, University of Campinas (UNICAMP) School of Medical Sciences, R. Alexander Fleming, 101, Campinas, SP,, 13083-881, Brazil.
  • Villas-Boas SG; School of Biological Sciences, University of Auckland, Auckland, New Zealand.
  • Mayrink J; Department of Obstetrics and Gynecology, University of Campinas (UNICAMP) School of Medical Sciences, R. Alexander Fleming, 101, Campinas, SP,, 13083-881, Brazil.
  • Passini R; Department of Obstetrics and Gynecology, University of Campinas (UNICAMP) School of Medical Sciences, R. Alexander Fleming, 101, Campinas, SP,, 13083-881, Brazil.
  • Franchini KG; LNBio-Brazilian Biosciences National Laboratory and School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil.
  • Baker PN; Gravida: National Centre for Growth & Development, Liggins Institute, University of Auckland, Auckland, New Zealand.
BMC Pregnancy Childbirth ; 16(1): 212, 2016 08 08.
Article in En | MEDLINE | ID: mdl-27503110
ABSTRACT

BACKGROUND:

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.
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Pregnancy Trimester, Second / Prenatal Diagnosis / Algorithms / Premature Birth / Metabolomics Type of study: Diagnostic_studies / Etiology_studies / Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans / Newborn / Pregnancy Country/Region as subject: America do sul / Brasil / Europa / Oceania Language: En Journal: BMC Pregnancy Childbirth Journal subject: OBSTETRICIA Year: 2016 Type: Article Affiliation country: Brazil

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Pregnancy Trimester, Second / Prenatal Diagnosis / Algorithms / Premature Birth / Metabolomics Type of study: Diagnostic_studies / Etiology_studies / Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans / Newborn / Pregnancy Country/Region as subject: America do sul / Brasil / Europa / Oceania Language: En Journal: BMC Pregnancy Childbirth Journal subject: OBSTETRICIA Year: 2016 Type: Article Affiliation country: Brazil