A population-based resource for intergenerational metabolomics analyses in pregnant women and their children: the Generation R Study
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Published:2020-03-23
Issue:4
Volume:16
Page:
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ISSN:1573-3882
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Container-title:Metabolomics
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language:en
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Short-container-title:Metabolomics
Author:
Voerman Ellis, Jaddoe Vincent W. V., Uhl Olaf, Shokry Engy, Horak Jeannie, Felix Janine F., Koletzko Berthold, Gaillard RomyORCID
Abstract
Abstract
Introduction
Adverse exposures in early life may predispose children to cardio-metabolic disease in later life. Metabolomics may serve as a valuable tool to disentangle the metabolic adaptations and mechanisms that potentially underlie these associations.
Objectives
To describe the acquisition, processing and structure of the metabolomics data available in a population-based prospective cohort from early pregnancy onwards and to examine the relationships between metabolite profiles of pregnant women and their children at birth and in childhood.
Methods
In a subset of 994 mothers-child pairs from a prospective population-based cohort study among pregnant women and their children from Rotterdam, the Netherlands, we used LC–MS/MS to determine concentrations of amino acids, non-esterified fatty acids, phospholipids and carnitines in blood serum collected in early pregnancy, at birth (cord blood), and at child’s age 10 years.
Results
Concentrations of diacyl-phosphatidylcholines, acyl-alkyl-phosphatidylcholines, alkyl-lysophosphatidylcholines and sphingomyelines were the highest in early pregnancy, concentrations of amino acids and non-esterified fatty acids were the highest at birth and concentrations of alkyl-lysophosphatidylcholines, free carnitine and acyl-carnitines were the highest at age 10 years. Correlations of individual metabolites between pregnant women and their children at birth and at the age of 10 years were low (range between r = − 0.10 and r = 0.35).
Conclusion
Our results suggest that unique metabolic profiles are present among pregnant women, newborns and school aged children, with limited intergenerational correlations between metabolite profiles. These data will form a valuable resource to address the early metabolic origins of cardio-metabolic disease.
Funder
Erasmus Medisch Centrum Erasmus Universiteit Rotterdam ZonMw European Research Council Hartstichting Diabetes Fonds H2020 European Research Council Bundesministerium für Bildung und Forschung Deutsche Forschungsgemeinschaft
Publisher
Springer Science and Business Media LLC
Subject
Clinical Biochemistry,Biochemistry,Endocrinology, Diabetes and Metabolism
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