From the ‡Shanghai Key Laboratory of Diabetes, Department of Endocrinology & Metabolism, Shanghai Jiao-Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Medical Center of Diabetes, Shanghai Key Clinical Center of Metabolic Diseases, Shanghai Institute for Diabetes, Shanghai, China.
§Department of Obstetrics and Gynecology, Shanghai Clinical Center for Severe Maternal Rescue, Shanghai Jiao-Tong University Affiliated Sixth People's Hospital, Shanghai, China.
Mol Cell Proteomics. 2018 Mar;17(3):431-441. doi: 10.1074/mcp.RA117.000121. Epub 2017 Dec 27.
Although metabolomics are desirable to understand the pathophysiology of gestational diabetes mellitus (GDM), comprehensive metabolomic studies of GDM are rare. We aimed to offer a holistic view of metabolites alteration in GDM patients and investigate the possible multimarker models for GDM diagnosis. Biochemical parameters and perinatal data of 131 GDM cases and 138 controls were collected. Fasting serum samples at 75 g oral glucose tolerance test were used for metabolites by ultra performance liquid chromatography-quadrupole-time of flight-mass spectrometry, ultra performance liquid chromatography-triple triple-quadrupole-mass spectrometry and gas chromatography- time-of- flight mass spectrometry platforms. Significant changes were observed in free fatty acids, bile acids, branched chain amino acids, organic acids, lipids and organooxygen compounds between two groups. In receiver operating characteristic (ROC) analysis, different combinations of candidate biomarkers and metabolites in multimarker models achieved satisfactory discriminative abilities for GDM, with the values of area under the curve (AUC) ranging from 0.721 to 0.751. Model consisting of body mass index (BMI), retinol binding protein 4 (RBP4), n-acetylaspartic acid and C16:1 (cis-7) manifested the best discrimination [AUC 0.751 (95% CI: 0.693-0.809), < 0.001], followed by model consisting of BMI, Cystatin C, acetylaspartic acid and 6,7-diketoLCA [AUC 0.749 (95% CI: 0.691-0.808), < 0.001]. Metabolites alteration reflected disorders of glucose metabolism, lipid metabolism, amino acid metabolism, bile acid metabolism as well as intestinal flora metabolism in GDM state. Multivariate models combining clinical markers and metabolites have the potential to differentiate GDM subjects from healthy controls.
虽然代谢组学有助于了解妊娠期糖尿病（GDM）的病理生理学，但全面的 GDM 代谢组学研究很少。我们旨在提供 GDM 患者代谢物变化的整体视图，并研究 GDM 诊断的可能多标志物模型。收集了 131 例 GDM 病例和 138 例对照的生化参数和围产儿数据。在 75g 口服葡萄糖耐量试验时采集空腹血清样本，用于超高效液相色谱-四极杆飞行时间质谱、超高效液相色谱-三重四极杆质谱和气相色谱-飞行时间质谱平台的代谢物分析。两组之间观察到游离脂肪酸、胆汁酸、支链氨基酸、有机酸、脂质和有机氧化合物有显著变化。在受试者工作特征（ROC）分析中，多标志物模型中候选生物标志物和代谢物的不同组合对 GDM 具有令人满意的判别能力，曲线下面积（AUC）值范围为 0.721 至 0.751。由体重指数（BMI）、视黄醇结合蛋白 4（RBP4）、N-乙酰天冬氨酸和 C16:1（顺-7）组成的模型表现出最佳的判别能力[AUC 0.751（95%CI：0.693-0.809），<0.001]，其次是由 BMI、胱抑素 C、乙酰天冬氨酸和 6,7-二酮基 LCA 组成的模型[AUC 0.749（95%CI：0.691-0.808），<0.001]。代谢物的改变反映了 GDM 状态下葡萄糖代谢、脂质代谢、氨基酸代谢、胆汁酸代谢以及肠道菌群代谢的紊乱。结合临床标志物和代谢物的多变量模型有可能区分 GDM 患者和健康对照者。
