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The application of metabolomics analysis in the research of gestational diabetes mellitus and preeclampsia
Author(s) -
Tan Bing,
Ma Yanan,
Zhang Lei,
Li Ni,
Zhang Jiandong
Publication year - 2020
Publication title -
journal of obstetrics and gynaecology research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.597
H-Index - 50
eISSN - 1447-0756
pISSN - 1341-8076
DOI - 10.1111/jog.14304
Subject(s) - medicine , gestational diabetes , behenic acid , preeclampsia , palmitic acid , diabetes mellitus , metabolomics , lipid profile , endocrinology , pregnancy , gastroenterology , bioinformatics , biochemistry , gestation , fatty acid , biology , genetics
Abstract Aim The aim of the study was to investigate the difference of the serum metabolic profile between gestational diabetes mellitus (GDM) patients and preeclampsia (PE) patients, to establish the disease differentiation model and to find characteristic metabolites, in order to provide a new idea for the occurrence, development and treatment of the disease. Methods Twenty‐nine patients with GDM group and 29 PE group who were examined in Tianjin No. 3 Central Hospital from March 2018 to August 2018 were enrolled as case group, and 29 normal pregnant women were selected as control group. All the serum samples were analyzed by using the ultra‐performance liquid chromatography and mass spectrometry. Based on the multivariate statistical analysis method of pattern recognition, we screened out and identified the differential characteristic metabolites. Results The serum metabolic profile model of GDM group and PE group was successfully constructed. A total of nine characteristic metabolites were screened and identified in this study, including LPC 18:0, LPC 22:6, LPC 16:0, ( S )‐14‐methylhexadecanoic acid, behenic acid, palmitic acid, sphingosine, phytosphingosine and 1,25‐dihydroxyvitamin D3‐26,23‐lactone. Among them, six characteristic metabolites which were LPC 18:0, LPC 22:6, behenic acid, palmitic acid, sphingosine and 1,25‐dihydroxyvitamin D3‐26,23‐lactone all had a significant statistical difference among GDM, PE and normal pregnancy groups ( P < 0.05). Conclusion The construction of metabolic profile discriminant model has a strong ability to differentiate GDM patients from PE pregnant women. The screened characteristic metabolites can early reflect the disorder of lipid, calcium and phosphorus metabolism of patients, and provide reference and help for the discussion of the occurrence, development and treatment of diseases.