TY - JOUR
T1 - Use of metabolomics for the identification and validation of clinical biomarkers for preterm birth
T2 - Preterm SAMBA
AU - Cecatti, Jose G.
AU - Souza, Renato T.
AU - Sulek, Karolina
AU - Costa, Maria L.
AU - Kenny, Louise C.
AU - McCowan, Lesley M.
AU - Pacagnella, Rodolfo C.
AU - Villas-Boas, Silas G.
AU - Mayrink, Jussara
AU - Passini, Renato
AU - Franchini, Kleber G.
AU - Baker, Philip N.
AU - Parpinelli, Mary A.
AU - Calderon, Iracema M.
AU - Cassettari, Bianca F.
AU - Vetorazzi, Janete
AU - Pfitscher, Lucia
AU - Filho, Edilberto P.Rocha
AU - Leite, Débora F.
AU - Feitosa, Francisco E.
AU - Costa e Silva, Carolina L.
AU - Poston, Lucilla
AU - Myers, Jenny E.
AU - Simpson, Nigel A.B.
AU - Walker, James J.
AU - Dekker, Gus A.
AU - Roberts, Claire T.
AU - for the Preterm SAMBA and SCOPE study groups
N1 - Funding Information:
This was one of the two big studies selected for sponsoring from the research call “Grand Challenges Brazil: Reducing the burden of preterm birth” number 05/2013 jointly issued by the Brazilian National Research Council (CNPq) and the Bill and Melinda Gates Foundation (Award 401636/2013-5). The funders played no role at all in the study design, writing the manuscript nor in the decision to submit the manuscript for publication. LC Kenny is supported by a Science Foundation Ireland Program Grant for INFANT (12/ RC/2272). The SCOPE database is provided and maintained by MedSciNet AB (http://medscinet.com). The New Zealand SCOPE study was funded by the New Enterprise Research Fund, Foundation for Research Science and Technology; Health Research Council (04/198); Evelyn Bond Fund, Auckland District Health Board Charitable Trust. The Irish SCOPE study was funded by the Health Research Board of Ireland (CSA/2007/2; http://www.hrb.ie).
Publisher Copyright:
© 2016 The Author(s).
PY - 2016/8/8
Y1 - 2016/8/8
N2 - 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.
AB - 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.
KW - Biological biomarker
KW - Mass spectrometry
KW - Metabolomics
KW - Prediction
KW - Spontaneous preterm birth
UR - http://www.scopus.com/inward/record.url?scp=84981273829&partnerID=8YFLogxK
U2 - 10.1186/s12884-016-1006-9
DO - 10.1186/s12884-016-1006-9
M3 - Journal article
C2 - 27503110
AN - SCOPUS:84981273829
SN - 1471-2393
VL - 16
JO - BMC Pregnancy and Childbirth
JF - BMC Pregnancy and Childbirth
IS - 1
M1 - 212
ER -