Hong Zhen, Huang Lan, Zhou Qinwen, Wu Yulin, Lin Xiaoping, Wei Yuanhuan, Wei Qinzhi, Deng Guifang, Zhang Zheqing
Department of Nutrition and Food Hygiene, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China.
Department of Food Safety and Health Research Center, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China.
Clin Nutr. 2025 May;48:90-100. doi: 10.1016/j.clnu.2025.03.008. Epub 2025 Mar 25.
BACKGROUND & AIMS: Gestational diabetes mellitus (GDM) is a prevalent pregnancy complication associated with adverse short-term and long-term health outcomes for both mother and child. This study aimed to investigate the association between plasma amino acid concentrations and the incidence of GDM from 2019 to 2021.
Plasma levels of 37 amino acids were precisely measured using triple quadrupole mass spectrometry. The principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models identified metabolic differences between GDM and non-GDM groups. Conditional logistic regression, generalized linear model, and quantile g-computation were employed to assess the associations between individual or combined amino acids and GDM risk/blood glucose levels. The discriminatory power of various factors associated with the risk of GDM was evaluated using the area under the receiver operating characteristic curve (AUC-ROC).
A total of 969 pregnant women were included in this case-control study. OPLS-DA model identified 16 biomarkers that differentiated the GDM and non-GDM groups. After adjusting for potential covariates and correcting for multiple testing, conditional logistic regression analysis revealed that certain key amino acids, such as valine and isoleucine, were positively associated with the incidence of GDM, while glycine and serine were negatively associated with GDM risk (OR = 0.753-1.671, P = <0.001-0.001). Generalized linear model analysis showed that specific amino acids, including alpha-aminoadipic acid and arginine, were positively associated with blood glucose levels, while glycine and serine were negatively associated (β = -0.211-0.365, P = <0.001-0.045). Additionally, mixtures of the identified amino acids were significantly associated with an increased risk of GDM (P < 0.001). The combination of selected amino acids showed the highest ability to identify GDM in comparison with traditional risk factors and specific amino acids (AUC-ROC = 0.761, 95 % CI: 0.729-0.792). The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified two metabolic pathways related to GDM risk: "Glycine, Serine, and Threonine Metabolism" and "Arginine biosynthesis".
The overall amino acid profile, rather than disturbances in specific amino acids, may serve as a more important prevention or therapeutic target for GDM.
妊娠期糖尿病（GDM）是一种常见的妊娠并发症，与母婴不良的短期和长期健康结局相关。本研究旨在调查2019年至2021年血浆氨基酸浓度与GDM发病率之间的关联。
使用三重四极杆质谱法精确测量37种氨基酸的血浆水平。主成分分析（PCA）和正交偏最小二乘法判别分析（OPLS-DA）模型确定了GDM组和非GDM组之间的代谢差异。采用条件逻辑回归、广义线性模型和分位数g计算来评估单个或组合氨基酸与GDM风险/血糖水平之间的关联。使用受试者工作特征曲线下面积（AUC-ROC）评估与GDM风险相关的各种因素的判别能力。
本病例对照研究共纳入969名孕妇。OPLS-DA模型确定了16种区分GDM组和非GDM组的生物标志物。在调整潜在协变量并校正多重检验后，条件逻辑回归分析显示，某些关键氨基酸，如缬氨酸和异亮氨酸，与GDM发病率呈正相关，而甘氨酸和丝氨酸与GDM风险呈负相关（OR = 0.753 - 1.671，P = <0.001 - 0.001）。广义线性模型分析表明，特定氨基酸，包括α-氨基己二酸和精氨酸，与血糖水平呈正相关，而甘氨酸和丝氨酸呈负相关（β = -0.211 - 0.365，P = <0.001 - 0.045）。此外，所鉴定氨基酸的混合物与GDM风险增加显著相关（P < 0.001）。与传统风险因素和特定氨基酸相比，所选氨基酸的组合显示出最高的识别GDM的能力（AUC-ROC = 0.761，95% CI：0.729 - 0.792）。京都基因与基因组百科全书（KEGG）分析确定了两条与GDM风险相关的代谢途径：“甘氨酸、丝氨酸和苏氨酸代谢”和“精氨酸生物合成”。
整体氨基酸谱，而非特定氨基酸的紊乱，可能是GDM更重要的预防或治疗靶点。
