School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China; School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China.
Department of Endocrinology, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China.
Free Radic Biol Med. 2023 Nov 20;209(Pt 1):9-17. doi: 10.1016/j.freeradbiomed.2023.10.014. Epub 2023 Oct 6.
Evidence from longitudinal studies is crucial to enhance our understanding of the role of metabolites in the progression of gestational diabetes mellitus (GDM). Herein, a longitudinal untargeted metabolomic study was conducted to reveal the metabolomic profiles and biomarkers associated with the progression of GDM, and characterize the changing patterns of metabolites.
We collected serum samples at three trimesters from 30 patients with GDM and 30 healthy Chinese pregnant women with pre-pregnancy BMI, age, and parity matched, and untargeted metabolomic analysis was performed, followed by machine learning approaches that integrated bootstrap and LASSO. Cluster analysis was conducted to elucidate the patterns of metabolite changes. Pathway analyses were conducted to gain insights into the underlying pathways involved.
A total of 32 metabolites, mainly belonging to amino acid and its derivatives, were significantly associated with GDM across three trimesters, and were clustered into three distinct patterns. Metabolites belonging to phosphatidylcholines, lysophosphatidylcholines, lysophosphatidic acids, and lysophosphatidylethanolamines were consistently upregulated, and 2,3-Dihydroxypropyl dihydrogen phosphate was downregulated in GDM group. Amino acid-related, glycerophospholipid, and vitamin B6 metabolism were enriched in multiple trimesters. The levels of allantoic acid, which was positively correlated with blood glucose, was consistently higher in GDM patients and exhibited good discriminatory ability for GDM in the early and mid-pregnancy.
We identified and characterized distinct patterns of metabolites associated with GDM throughout pregnancy, and found that allantoic acid was a potential biomarker for early diagnosis of GDM.
来自纵向研究的证据对于加深我们对代谢物在妊娠期糖尿病（GDM）进展中的作用的理解至关重要。在此，我们进行了一项纵向非靶向代谢组学研究，以揭示与 GDM 进展相关的代谢组学特征和生物标志物，并描述代谢物变化的模式。
我们收集了 30 名 GDM 患者和 30 名具有匹配孕前 BMI、年龄和产次的健康中国孕妇在三个孕期的血清样本，并进行了非靶向代谢组学分析，然后采用集成 bootstrap 和 LASSO 的机器学习方法。我们进行聚类分析以阐明代谢物变化的模式。我们进行了途径分析以深入了解涉及的潜在途径。
共有 32 种代谢物主要属于氨基酸及其衍生物，与整个孕期的 GDM 显著相关，并聚类为三个不同的模式。属于磷脂酰胆碱、溶血磷脂酰胆碱、溶血磷脂酸和溶血磷脂酰乙醇胺的代谢物持续上调，而 2,3-二羟丙基二氢磷酸在 GDM 组中下调。氨基酸相关、甘油磷脂和维生素 B6 代谢在多个孕期中都有富集。与血糖呈正相关的尿囊酸水平在 GDM 患者中一直较高，并且在孕早期和孕中期对 GDM 具有良好的鉴别能力。
我们确定并描述了与整个孕期 GDM 相关的不同代谢物模式，发现尿囊酸是 GDM 早期诊断的潜在生物标志物。
