代谢谱分析确定了与产后从妊娠糖尿病发展为糖尿病前期相关的潜在生物标志物。

IF 2.2 4区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL
Lenan Liu, Qian Yang, Panyuan Shen, Junsong Wang, Qi Zheng, Guoying Zhang, Bai Jin
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引用次数: 0

摘要

本研究旨在确定预测有妊娠糖尿病(GDM)病史的妇女发展为糖尿病前期的潜在代谢生物标志物。我们在产后六周至六个月期间对有 GDM 病史的妇女进行了 2 小时 75 克口服葡萄糖耐量试验,根据试验结果建立了糖尿病前期组(42 人)和对照组(40 人),并收集了她们的临床数据和生化试验结果。我们采用超高效液相色谱-四极杆飞行时间质谱法(UHPLC-Q-TOF-MS/MS)对受试者空腹和加餐后 2 小时的血浆代谢组学进行了分析。我们发现,与对照组相比,糖尿病前期组年龄较大,孕期负荷后 2 小时血糖水平较高。代谢组学分析确定了组间 164 种不同的代谢物。与对照组相比,糖尿病前期组有 15 种代谢物在两个时间点上呈现出一致的变化趋势,包括 3 种增加的代谢物和 12 种减少的代谢物。通过建立一个从 GDM 向糖尿病前期发展的预测模型,我们发现将三种临床标记物结合在一起得出的曲线下面积(AUC)为 0.71(95% 置信区间 [CI],0.60-0.82)。我们还评估了 15 种代谢物在空腹(AUC,0.98;95% CI,0.94-1.00)和负荷后 2 小时(AUC,0.99;95% CI,0.97-1.00)时间点区分受试者产后糖尿病前期和正常糖耐量的鉴别力。代谢途径分析表明,能量代谢和支链氨基酸在产后早期有 GDM 病史的妇女发生糖尿病前期的过程中发挥了作用。总之,这项研究确定了与产后早期从 GDM 发展为糖尿病前期相关的潜在代谢生物标志物和途径。由 15 种代谢物组成的小组在区分产后糖尿病前期和正常糖耐量方面显示出良好的鉴别力。这些研究结果提供了对这一转变的潜在病理生理学的见解,并表明了开发一种代谢分析测试的可行性,该测试可用于早期识别GDM后出现糖尿病前期的高风险妇女。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Metabolic profiling identifies potential biomarkers associated with progression from gestational diabetes mellitus to prediabetes postpartum.

The current study aims to identify potential metabolic biomarkers that predict the progression to prediabetes in women with a history of gestational diabetes mellitus (GDM). We constructed a prediabetes group ( n = 42) and a control group ( n = 40) based on a2-hour 75 g oral glucose tolerance test for women with a history of GDM from six weeks to six months postpartum, and collected their clinical data and biochemical test results. We performed the plasma metabolomics analysis of the subjects at the fasting and 2-hour post-load time points by using ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS/MS). We found that the prediabetes group was older and had higher 2-hour post-load glucose levels during pregnancy than the control group. The metabolomic analysis identified 164 differential metabolites between the groups. Compared with the control group, 15 metabolites in the prediabetes group exhibited consistent change trends at both time points, including three increased and 12 decreased metabolites. By building a prediction model of the progression from GDM to prediabetes, we found a combination of three clinical markers yielded an area under thecurve (AUC) of 0.71 (95% confidence interval [CI], 0.60-0.82). We also assessed the discriminative power of the panel of 15 metabolites for distinguishing between postpartum prediabetes and normal glucose tolerance of the subjects at the fasting (AUC, 0.98; 95% CI, 0.94-1.00) and 2-hour post-load (AUC, 0.99; 95% CI, 0.97-1.00) time points. The metabolic pathway analysis indicated that energy metabolism and branched-chain amino acids played a role in the development of prediabetes in women with a history of GDM during early postpartum. In conclusion, this study identified potential metabolic biomarkers and pathways associated with the progression from GDM to prediabetes in the early postpartum period. A panel of 15 metabolites showed promising discriminative power for distinguishing between postpartum prediabetes and normal glucose tolerance. These findings provide insights into the underlying pathophysiology of this transition and suggest the feasibility of developing a metabolic profiling test for the early identification of women at high risk of prediabetes following GDM.

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来源期刊
Journal of Biomedical Research
Journal of Biomedical Research MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
4.60
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0.00%
发文量
69
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