4.7 Article

LC-MS-Based Metabolomics Identification of Novel Biomarkers of Chorioamnionitis and Its Associated Perinatal Neurological Damage

Journal

JOURNAL OF PROTEOME RESEARCH
Volume 14, Issue 3, Pages 1432-1444

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/pr501087x

Keywords

metabolomics; metabolic fingerprinting; chorioamnionitis; amniotic fluid; perinatal neurological damage; perinatology; biomarkers

Funding

  1. Spanish Ministry of Economy and Competitiveness [MINECO- CTQ2011-23562]
  2. Institute of Health Carlos III [PI09/02179]

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Chorioamnionitis is a complication of pregnancy associated with significant maternal and perinatal long-term adverse outcomes. We apply high-throughput amniotic fluid (AF) metabolomics analysis for better understanding the pathophysiological mechanism of chorioamnionitis and its associated perinatal neurological injury and to provide meaningful information about new potential biomarkers. AF samples (n = 40) were collected from women at risk of chorioamnionits. Detailed clinical information on each pregnancy was obtained from obstetrical and neonatal medical examination. Liquid chromatography (LC)/mass spectrometry (MS) followed by data alignment and filtration as well as univariate and multivariate statistical analysis was performed. Statistically significant differences were found in 60 masses in positive and 115 in negative ionization mode obtained with LC/quadrupole time-of-flight MS (LC-QTOF-MS) between women with and without chorioamnionitis. Identified compounds were mainly related to glycerophospholipids and sphingolipids metabolism. From them, LPE(16:0)/LPE(P-16:0) and especially lactosylceramides emerged as the best biomarker candidates. Sulfocholic acid, trioxocholenoic acids, and LPC(18:2) were particularly increased in women with chorioamnionitis whose newborns developed perinatal brain damage. Therefore, we propose LPE(16:0)/LPE(P-16:0) and lactosylceramides as biomarkers for chorioamnionitis as well as LPC(18:2), trioxocholenoic acid, and sulfocholic acid for its associated perinatal brain damage. Metabolomics fingerprinting of AF enables the prediction of pregnancy-related disorders and the development of new diagnostics strategies.

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