Abstract
The purpose of the study is to investigate the metabolic characteristics of placental tissue in patients diagnosed with gestational diabetes mellitus (GDM). Ultra-performance liquid chromatography-mass spectrometry (UPLC-MS/MS) was employed to qualitatively and quantitatively analyze the metabolites in placental tissues obtained from 25 healthy pregnant women and 25 pregnant women diagnosed with GDM. Multilevel statistical methods are applied to process intricate metabolomics data. Meanwhile, we applied machine learning techniques to identify biomarkers that could potentially predict the risk of long-term complications in patients with GDM as well as their offspring. We identified 1902 annotated metabolites, out of which 212 metabolites exhibited significant differences in GDM placentas. In addition, the study identifies a set of risk biomarkers that effectively predict the likelihood of long-term complications in both pregnant women with GDM and their offspring. The accuracy of this panel was measured by the area under the receiver operating characteristic curve (ROC), which was found to be 0.992 and 0.960 in the training and validation sets, respectively. This study enhances our understanding of GDM pathogenesis through metabolomics. Furthermore, the panel of risk markers identified could prove to be a valuable tool in predicting potential long-term complications for both GDM patients and their offspring.
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References
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Acknowledgements
We would like to thank Dr Yuting Xiang for his technical assistance. We would also like to thank all the staff at the Department of Obstetrics and Gynaecology, Huizhou First Maternal and Child Health Care Hospital, and we are grateful to Wuhan Metware Biotechnology Co., Ltd for assisting in metabolomics detection and bioinformatics analysis. Meanwhile, we would also like to thank all the staff of the Medical Ethics Committee of Huizhou First Maternal and Child Health Care Hospital for their support in overseeing this study. Finally, we thank all the tissue donors and their families who generously donated samples to the Clinical Biobanking Centre.
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This study was conducted in accordance with the guidelines of the Declaration of Helsinki and was approved by the Hospital Ethics Committee of Huizhou First Maternal and Child Health Hospital (number: 2020055). Each participant signed an informed consent form in accordance with relevant regulations. This study followed the STROBE reporting guidelines.
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Jiang, Z., Ye, X., Cao, D. et al. Association of Placental Tissue Metabolite Levels with Gestational Diabetes Mellitus: a Metabolomics Study. Reprod. Sci. 31, 569–578 (2024). https://doi.org/10.1007/s43032-023-01353-2
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DOI: https://doi.org/10.1007/s43032-023-01353-2