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Wang X, Zhang Y, Zheng W, Wang J, Wang Y, Song W, Liang S, Guo C, Ma X, Li G. Dynamic changes and early predictive value of branched-chain amino acids in gestational diabetes mellitus during pregnancy. Front Endocrinol (Lausanne) 2022; 13:1000296. [PMID: 36313758 PMCID: PMC9614652 DOI: 10.3389/fendo.2022.1000296] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 09/20/2022] [Indexed: 11/17/2022] Open
Abstract
OBJECTIVE Branched-chain amino acids (BCAAs) are closely associated with type 2 diabetes mellitus, but their roles in gestational diabetes mellitus (GDM) are still controversial. This study aims to explore the dynamic changes of BCAAs during pregnancy and identify potential early biomarkers for GDM. METHODS This study is a nested case-control study involved 49 women with GDM and 50 age- and body mass index (BMI)-matched healthy pregnant women. The dynamic changes of valine (Val), isoleucine (Ile), and leucine (Leu) were detected in the first (8-12 weeks) and second trimesters (24-28 weeks) by liquid chromatography-mass spectrometry. RESULTS Serum Val, Ile, and Leu were higher in GDM patients than in controls in the first trimester. Compared with the first trimester, the serum Val, Ile, and Leu in GDM patients were decreased in the second trimester. In addition, Val, Ile, and Leu in the first trimester were the risk factors for GDM, and Ile presented a high predictive value for GDM. Ile + age (≥ 35) + BMI (≥ 24) exhibited the highest predictive value for GDM (AUC = 0.902, sensitivity = 93.9%, specificity = 80%). CONCLUSION Maternal serum Ile in the first trimester was a valuable biomarker for GDM. Ile combined with advanced maternal age and overweight may be used for the early prediction of GDM.
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Affiliation(s)
- Xiaoxin Wang
- Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing, China
| | - Ya Zhang
- Department of Genetics, National Research Institute for Family Planning, Beijing, China
- Environmental and Spatial Epidemiology Research Center, National Human Genetic Resources Center, Beijing, China
| | - Wei Zheng
- Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing, China
| | - Jia Wang
- Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing, China
| | - Yuanyuan Wang
- Department of Genetics, National Research Institute for Family Planning, Beijing, China
- Environmental and Spatial Epidemiology Research Center, National Human Genetic Resources Center, Beijing, China
| | - Wei Song
- Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing, China
| | - Shengnan Liang
- Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing, China
| | - Cuimei Guo
- Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing, China
| | - Xu Ma
- Department of Genetics, National Research Institute for Family Planning, Beijing, China
- Environmental and Spatial Epidemiology Research Center, National Human Genetic Resources Center, Beijing, China
- *Correspondence: Xu Ma, ; Guanghui Li,
| | - Guanghui Li
- Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing, China
- *Correspondence: Xu Ma, ; Guanghui Li,
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