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Normal pregnancy-induced amino acid metabolic stress in a longitudinal cohort of pregnant women: novel insights generated from UPLC-QTOFMS-based urine metabolomic study

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Abstract

Introduction

The maternal body often faces unique physiological challenges in amino acid metabolism due to the continuous requirement of nutrients and substrates for fetal development and additional energy stores for labor and lactation during pregnancy.

Objective

The aims of the present study is to find out the metabolites involved in amino acid metabolism in a large longitudinal healthy pregnant cohort and provide baseline data for future studies of pregnancy and disease from in utero environmental stress factors.

Method

We conducted a UPLC-QTOFMS based-urine metabolomics study to investigate the dynamic amino acid metabolic profiles and pathways of 232 healthy pregnant women in their first, second and third trimesters. After multivariate classification to select the metabolites with the strongest contributions to dynamic alterations in normal pregnancy, we applied the method of standard deviation step (SDSD) down for statistical significance analysis to enhance the value of metabolites in clinical practice.

Results

Kynurenic acid, an endogenous antagonist of N-methyl-d-aspartate receptors, increased significantly in middle pregnancy. l-aspartyl-4-phosphate, a potential marker for lower tolerance against fatigue of human body, decreased significantly in the third trimester. Cysteinylglycine, a pyrolysis product of glutathione, significantly increased in late pregnancy. These findings presented a novel insight into normal pregnancy-related regulation of the generation of excitatory neurotransmitter receptor antagonists, maternal fatigue, oxidative stress and so on.

Conclusion

This normal pregnancy related amino acid metabolic profile as well as the pathways information might be valuable to explore the complex mechanisms of physiological metabolic challenge in amino acid metabolism with the potential capacity to generate a novel hypothesis, which in turn could provide an ideal start for a large-scale epidemiological study of women who subsequently develop diseases, e.g., gestational depression.

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Funding

This work was supported by the National Natural Science Foundation of China (21437002, 81372959, 81402649), the R&D Special Fund for Public Welfare Industry (Environment) (201309048), and the Fundamental Research Funds for the Central Universities, HUST (2016YXZD043).

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Authors and Affiliations

  1. Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People’s Republic of China

    Mu Wang, Han Li, Wei Xia, Yang Peng, Yuanyuan Li, Bing Xu & Shunqing Xu

  2. Beijing Institute of Radiation Medicine, Beijing, People’s Republic of China

    Qiande Liang, Jie Li, Zengchun Ma & Yue Gao

Authors
  1. Mu Wang
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  2. Qiande Liang
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  3. Han Li
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  4. Wei Xia
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  5. Jie Li
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  6. Yang Peng
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  7. Yuanyuan Li
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  8. Zengchun Ma
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  9. Bing Xu
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  10. Yue Gao
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  11. Shunqing Xu
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Corresponding authors

Correspondence to Yue Gao or Shunqing Xu.

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Conflict of interest

The authors declare no conflict of interest.

Ethical approval

All procedures performed in this study were in accordance with the ethical standards of the Ethics Committees of the Tongji Medical College, Huazhong University of Science and Technology, and the Study Hospital of the Maternal and Child Health Hospital of Wuhan City in China, as well as with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Written informed consent was obtained from all individual participants included in the study.

Additional information

Shunqing Xu is the primary corresponding author.

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Wang, M., Liang, Q., Li, H. et al. Normal pregnancy-induced amino acid metabolic stress in a longitudinal cohort of pregnant women: novel insights generated from UPLC-QTOFMS-based urine metabolomic study. Metabolomics 12, 131 (2016). https://doi.org/10.1007/s11306-016-1067-9

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  • DOI: https://doi.org/10.1007/s11306-016-1067-9

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