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

被引:29
作者
Cecatti, Jose G. [1 ]
Souza, Renato T. [1 ]
Sulek, Karolina [2 ]
Costa, Maria L. [1 ]
Kenny, Louise C. [3 ]
McCowan, Lesley M. [4 ]
Pacagnella, Rodolfo C. [1 ]
Villas-Boas, Silas G. [5 ]
Mayrink, Jussara [1 ]
Passini, Renato, Jr. [1 ]
Franchini, Kleber G. [6 ,7 ]
Baker, Philip N. [2 ]
机构
[1] Univ Estadual Campinas, Dept Obstet & Gynecol, Sch Med Sci, UNICAMP, R Alexander Fleming 101, BR-13083881 Campinas, SP, Brazil
[2] Univ Auckland, Liggins Inst, Gravida Natl Ctr Growth & Dev, Auckland, New Zealand
[3] Univ Coll Cork, Dept Obstet & Gynaecol, Irish Ctr Fetal & Neonatal Translat Res INFANT, Cork, Ireland
[4] Univ Auckland, South Auckland Clin Sch, Fac Med & Hlth Sci, Auckland, New Zealand
[5] Univ Auckland, Sch Biol Sci, Auckland, New Zealand
[6] Univ Estadual Campinas, UNICAMP, LNBio Brazilian Biosci Natl Lab, Campinas, SP, Brazil
[7] Univ Estadual Campinas, UNICAMP, Sch Med Sci, Campinas, SP, Brazil
基金
爱尔兰科学基金会;
关键词
Spontaneous preterm birth; Metabolomics; Prediction; Biological biomarker; Mass spectrometry; EARLY-PREGNANCY PREDICTION; ASYMPTOMATIC WOMEN; NULLIPAROUS WOMEN; INCREASED RISK; GLOBAL LEVELS; PREECLAMPSIA; MORTALITY; INFANTS; WEIGHT; MARKER;
D O I
10.1186/s12884-016-1006-9
中图分类号
R71 [妇产科学];
学科分类号
100211 ;
摘要
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.
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页数:9
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