Cargando…

Serum Metabolites as an Indicator of Developing Gestational Diabetes Mellitus Later in the Pregnancy: A Prospective Cohort of a Chinese Population

OBJECTIVE: Gestational diabetes mellitus (GDM) is a common metabolic disorder with onset during pregnancy. However, the etiology and pathogenesis of GDM have not been fully elucidated. In this study, we used a metabolomics approach to investigate the relationship between maternal serum metabolites a...

Descripción completa

Detalles Bibliográficos
Autores principales: Tian, Mengyuan, Ma, Shujuan, You, Yiping, Long, Sisi, Zhang, Jiayue, Guo, Chuhao, Wang, Xiaolei, Tan, Hongzhuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7884125/
https://www.ncbi.nlm.nih.gov/pubmed/33628838
http://dx.doi.org/10.1155/2021/8885954
_version_ 1783651345951096832
author Tian, Mengyuan
Ma, Shujuan
You, Yiping
Long, Sisi
Zhang, Jiayue
Guo, Chuhao
Wang, Xiaolei
Tan, Hongzhuan
author_facet Tian, Mengyuan
Ma, Shujuan
You, Yiping
Long, Sisi
Zhang, Jiayue
Guo, Chuhao
Wang, Xiaolei
Tan, Hongzhuan
author_sort Tian, Mengyuan
collection PubMed
description OBJECTIVE: Gestational diabetes mellitus (GDM) is a common metabolic disorder with onset during pregnancy. However, the etiology and pathogenesis of GDM have not been fully elucidated. In this study, we used a metabolomics approach to investigate the relationship between maternal serum metabolites and GDM in early pregnancy. METHODS: A nested case-control study was performed. To establish an early pregnancy cohort, pregnant women in early pregnancy (10‐13(+6) weeks) were recruited. In total, 51 patients with GDM and 51 healthy controls were included. Serum samples were analyzed using an untargeted high-performance liquid chromatography mass spectrometry metabolomics approach. The relationships between metabolites and GDM were analyzed by an orthogonal partial least-squares discriminant analysis. Differential metabolites were evaluated using a KEGG pathway analysis. RESULTS: A total of 44 differential metabolites were identified between GDM cases and healthy controls during early pregnancy. Of these, 26 significant metabolites were obtained in early pregnancy after false discovery rate (FDR < 0.1) correction. In the GDM group, the levels of L-pyroglutamic acid, L-glutamic acid, phenylacetic acid, pantothenic acid, and xanthine were significantly higher and the levels of 1,5-anhydro-D-glucitol, calcitriol, and 4-oxoproline were significantly lower than those in the control group. These metabolites were involved in multiple metabolic pathways, including those for amino acid, carbohydrate, lipid, energy, nucleotide, cofactor, and vitamin metabolism. CONCLUSIONS: We identified significant differentially expressed metabolites associated with the risk of GDM, providing insight into the mechanisms underlying GDM in early pregnancy and candidate predictive markers.
format Online
Article
Text
id pubmed-7884125
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-78841252021-02-23 Serum Metabolites as an Indicator of Developing Gestational Diabetes Mellitus Later in the Pregnancy: A Prospective Cohort of a Chinese Population Tian, Mengyuan Ma, Shujuan You, Yiping Long, Sisi Zhang, Jiayue Guo, Chuhao Wang, Xiaolei Tan, Hongzhuan J Diabetes Res Research Article OBJECTIVE: Gestational diabetes mellitus (GDM) is a common metabolic disorder with onset during pregnancy. However, the etiology and pathogenesis of GDM have not been fully elucidated. In this study, we used a metabolomics approach to investigate the relationship between maternal serum metabolites and GDM in early pregnancy. METHODS: A nested case-control study was performed. To establish an early pregnancy cohort, pregnant women in early pregnancy (10‐13(+6) weeks) were recruited. In total, 51 patients with GDM and 51 healthy controls were included. Serum samples were analyzed using an untargeted high-performance liquid chromatography mass spectrometry metabolomics approach. The relationships between metabolites and GDM were analyzed by an orthogonal partial least-squares discriminant analysis. Differential metabolites were evaluated using a KEGG pathway analysis. RESULTS: A total of 44 differential metabolites were identified between GDM cases and healthy controls during early pregnancy. Of these, 26 significant metabolites were obtained in early pregnancy after false discovery rate (FDR < 0.1) correction. In the GDM group, the levels of L-pyroglutamic acid, L-glutamic acid, phenylacetic acid, pantothenic acid, and xanthine were significantly higher and the levels of 1,5-anhydro-D-glucitol, calcitriol, and 4-oxoproline were significantly lower than those in the control group. These metabolites were involved in multiple metabolic pathways, including those for amino acid, carbohydrate, lipid, energy, nucleotide, cofactor, and vitamin metabolism. CONCLUSIONS: We identified significant differentially expressed metabolites associated with the risk of GDM, providing insight into the mechanisms underlying GDM in early pregnancy and candidate predictive markers. Hindawi 2021-02-05 /pmc/articles/PMC7884125/ /pubmed/33628838 http://dx.doi.org/10.1155/2021/8885954 Text en Copyright © 2021 Mengyuan Tian et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Tian, Mengyuan
Ma, Shujuan
You, Yiping
Long, Sisi
Zhang, Jiayue
Guo, Chuhao
Wang, Xiaolei
Tan, Hongzhuan
Serum Metabolites as an Indicator of Developing Gestational Diabetes Mellitus Later in the Pregnancy: A Prospective Cohort of a Chinese Population
title Serum Metabolites as an Indicator of Developing Gestational Diabetes Mellitus Later in the Pregnancy: A Prospective Cohort of a Chinese Population
title_full Serum Metabolites as an Indicator of Developing Gestational Diabetes Mellitus Later in the Pregnancy: A Prospective Cohort of a Chinese Population
title_fullStr Serum Metabolites as an Indicator of Developing Gestational Diabetes Mellitus Later in the Pregnancy: A Prospective Cohort of a Chinese Population
title_full_unstemmed Serum Metabolites as an Indicator of Developing Gestational Diabetes Mellitus Later in the Pregnancy: A Prospective Cohort of a Chinese Population
title_short Serum Metabolites as an Indicator of Developing Gestational Diabetes Mellitus Later in the Pregnancy: A Prospective Cohort of a Chinese Population
title_sort serum metabolites as an indicator of developing gestational diabetes mellitus later in the pregnancy: a prospective cohort of a chinese population
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7884125/
https://www.ncbi.nlm.nih.gov/pubmed/33628838
http://dx.doi.org/10.1155/2021/8885954
work_keys_str_mv AT tianmengyuan serummetabolitesasanindicatorofdevelopinggestationaldiabetesmellituslaterinthepregnancyaprospectivecohortofachinesepopulation
AT mashujuan serummetabolitesasanindicatorofdevelopinggestationaldiabetesmellituslaterinthepregnancyaprospectivecohortofachinesepopulation
AT youyiping serummetabolitesasanindicatorofdevelopinggestationaldiabetesmellituslaterinthepregnancyaprospectivecohortofachinesepopulation
AT longsisi serummetabolitesasanindicatorofdevelopinggestationaldiabetesmellituslaterinthepregnancyaprospectivecohortofachinesepopulation
AT zhangjiayue serummetabolitesasanindicatorofdevelopinggestationaldiabetesmellituslaterinthepregnancyaprospectivecohortofachinesepopulation
AT guochuhao serummetabolitesasanindicatorofdevelopinggestationaldiabetesmellituslaterinthepregnancyaprospectivecohortofachinesepopulation
AT wangxiaolei serummetabolitesasanindicatorofdevelopinggestationaldiabetesmellituslaterinthepregnancyaprospectivecohortofachinesepopulation
AT tanhongzhuan serummetabolitesasanindicatorofdevelopinggestationaldiabetesmellituslaterinthepregnancyaprospectivecohortofachinesepopulation