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  • ISSN 1674-8301
  • CN 32-1810/R
Volume 35 Issue 5
Sep.  2021
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Liu Liping, Liu Lenan, Wang Junsong, Zheng Qi, Jin Bai, Sun Lizhou. Differentiation of gestational diabetes mellitus by nuclear magnetic resonance-based metabolic plasma analysis[J]. The Journal of Biomedical Research, 2021, 35(5): 351-360. DOI: 10.7555/JBR.35.20200191
Citation: Liu Liping, Liu Lenan, Wang Junsong, Zheng Qi, Jin Bai, Sun Lizhou. Differentiation of gestational diabetes mellitus by nuclear magnetic resonance-based metabolic plasma analysis[J]. The Journal of Biomedical Research, 2021, 35(5): 351-360. DOI: 10.7555/JBR.35.20200191
shu

Differentiation of gestational diabetes mellitus by nuclear magnetic resonance-based metabolic plasma analysis

  • 1.

    Department of Obstetrics, the First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China

  • 2.

    Center for Molecular Metabolism, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China

More Information
  • Corresponding author:

    Lizhou Sun and Bai Jin, Department of Obstetrics, the First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu 210029, China. Tels: +86-13605171213 and +86-13913850147, E-mails: sunlizhoudoc@163.com and jinbai1018@yeah.net

  • Received Date: November 20, 2020
  • Revised Date: December 15, 2020
  • Accepted Date: December 20, 2020
  • Available Online: January 28, 2021
    Graphical Abstract
    • Abstract
  • This study aimed to investigate the metabolic profile of gestational diabetes mellitus (GDM) at both antepartum and postpartum periods. Seventy pregnant women were divided into three groups: the normal glucose-tolerant group (NGT, n=35), the abnormal glucose-tolerant groups without insulin therapy (A1GDM, n=24) or with insulin therapy (A2GDM, n=11). Metabolic profiles of the plasma were acquired by proton nuclear magnetic resonance (1H-NMR) spectroscopy and analyzed by multivariate statistical data analysis. The relationship between demographic parameters and the potential metabolite biomarkers was further explored. Group antepartum or postpartum showed similar metabolic trends. Compare with those of the NGT group, the levels of 2-hydroxybutyrate, lysine, acetate, glutamine, succinate, tyrosine, formate, and all three BCAAs (leucine, valine, isoleucine) in the A2GDM group were increased dramatically, and the levels of lysine, acetate, and formate in the A1GDM group were elevated significantly. The dramatically decreased levels of 3-methyl-2-oxovalerate and methanol were observed both in the A1GDM group and A2GDM group. Compare to the A1GDM group, the branched-chain amino acids (BCAAs) of leucine, valine, and isoleucine were increased dramatically in the A2GDM group. The levels of aromatic amino acids (AAAs), tyrosine and phenylalanine, were significantly increased in GDM women, consistent with the severity of GDM. Interference of amino acid metabolism and disturbance in energy metabolism occurred in women with different grades of GDM. Metabolic profiles could reflect the severity of GDM. Plasma BCAA concentrations showing strong positive correlations with weight and pre-delivery BMI. This study provides a new perspective to understand the pathogenesis and etiology of GDM, which may help the clinical management and treatment of GDM.
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    • References (34)
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