Use of Metabolomics for the Identification and Validation of Clinical Biomarkers for Preterm Birth
José Guilherme Cecatti from the Universidade Estadual de Campinas in Brazil will develop a predictive algorithm to identify early in pregnancy those at increased risk of preterm birth so that if possible they can be treated. There are likely to be many causes of preterm birth, and it is a major cause of both short and long term life-threatening complications for infants. They will use existing data from 6,000 pregnancies that resulted in both term and preterm births, and perform three complementary mass spectrometry-based methods on blood taken early (around 15 weeks) in those pregnancies to identify a panel of biomarkers that can predict preterm birth. This will be combined with sociodemographic and physical data including economic status and age to generate a predictive algorithm. They will then evaluate this algorithm in a cohort of 1,150 low risk pregnant Brazilian women for its ability to identify those that go on to give birth prematurely.