- Background/Aims: Preterm birth (PTB) and low birth weight (LBW) significantly influence mortality and morbidity of the offspring in early life and also have long-term consequences in later life. A better understanding of the molecular mechanisms of preterm birth could provide new insights regarding putative preventive strategies. Metabolomics provides a powerful analytic tool to readout complex interactions between genetics, environment and health and may serve to identify relevant biomarkers. In this study, the association between 163 targeted maternal blood metabolites and gestational age was investigated in order to find candidate biomarkers for PTB. Methods: Five hundred twenty-three women were included into this observational study. Maternal blood was obtained before delivery. The concentration of 163 maternal serum metabolites was measured by flow injection tandem mass spectrometry. To find putative biomarkers for preterm birth, a three-step analysis was designed: bivariate correlation analysis followed by multivariableBackground/Aims: Preterm birth (PTB) and low birth weight (LBW) significantly influence mortality and morbidity of the offspring in early life and also have long-term consequences in later life. A better understanding of the molecular mechanisms of preterm birth could provide new insights regarding putative preventive strategies. Metabolomics provides a powerful analytic tool to readout complex interactions between genetics, environment and health and may serve to identify relevant biomarkers. In this study, the association between 163 targeted maternal blood metabolites and gestational age was investigated in order to find candidate biomarkers for PTB. Methods: Five hundred twenty-three women were included into this observational study. Maternal blood was obtained before delivery. The concentration of 163 maternal serum metabolites was measured by flow injection tandem mass spectrometry. To find putative biomarkers for preterm birth, a three-step analysis was designed: bivariate correlation analysis followed by multivariable regression analysis and a comparison of mean values among gestational age groups. Results: Bivariate correlation analysis showed that 2 acylcarnitines (C16:2, C2), 1 amino acids (xLeu), 8 diacyl-PCs (PCaaC36:4, PCaaC38:4, PCaaC38:5, PCaaC38:6, PCaaC40:4, PCaaC40:5, PCaaC40:6, PCaaC42:4), and 1 Acylalkyl-PCs (PCaeC40:5) were inversely correlated with gestational age. Multivariable regression analysis confounded for PTB history, maternal body mass index (BMI) before pregnancy, systolic blood pressure at the third trimester, and maternal body weight at the third trimester, showed that the diacyl-PC PCaaC38:6 was the only metabolite inversely correlated with gestational age. Conclusions: Maternal blood concentrations of PCaaC38:6 are independently associated with gestational age. (C) 2016 The Author(s) Published by S. Karger AG, Basel…
