Wu Zhenghong, Jin Lei, Zheng Wenyi, Zhang Chenxi, Zhang Liwen, Chen Yaping, Guan Junhua, Fei He
Department of Obstetrics and Gynaecology, The Fifth People's Hospital of Shanghai, School of Medicine, Fudan University, Shanghai, People's Republic of China.
Department of Obstetrics and Gynecology, Fengcheng Hospital, Shanghai, People's Republic of China.
Biochem Biophys Res Commun. 2018 Feb 5;496(2):679-685. doi: 10.1016/j.bbrc.2018.01.096. Epub 2018 Jan 17.
A missed abortion (MA) is an in-utero death of the embryo or fetus before the 20th week of gestation with retained products of conception. In order to discover novel biomarkers for MA, a H NMR spectroscopy-based metabolomics approach was applied to detect human MA serum metabolic profiles. Serum samples were obtained from patients with MA (n = 15) and healthy controls (n = 9) for study. The NOESYPR1D spectrum combined with multi-variate pattern recognition analysis was used to cluster the groups and establish a disease-specific metabolites phenotype. Principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) models were capable of distinguishing MA patients from healthy subjects. The results revealed that 24 metabolites altered in MA patients compared with the control population. Metabolomic pathway analysis demonstrated that alanine, aspartate and glutamate metabolism, citrate cycle (TCA cycle), taurine and hypotaurine metabolism were significantly altered in MA. The results indicated that serum NMR-based metabolomic profiling method is sensitive and specific enough to distinguish MA and from healthy controls, this method could be developed as a clinically useful diagnostic tool for MA. The finding from the MA serum metabolic profiling shed a new light on further understanding of MA disease mechanisms.
稽留流产（MA）是指妊娠20周前胚胎或胎儿在宫内死亡且妊娠产物稽留宫腔。为发现稽留流产的新型生物标志物，采用基于核磁共振氢谱（¹H NMR）的代谢组学方法检测人类稽留流产血清代谢谱。从稽留流产患者（n = 15）和健康对照者（n = 9）获取血清样本进行研究。利用核欧沃豪斯效应光谱（NOESYPR1D）谱结合多变量模式识别分析对各组进行聚类，并建立疾病特异性代谢物表型。主成分分析（PCA）和正交偏最小二乘判别分析（OPLS - DA）模型能够区分稽留流产患者和健康受试者。结果显示，与对照组相比，稽留流产患者中有24种代谢物发生改变。代谢途径分析表明，丙氨酸、天冬氨酸和谷氨酸代谢、柠檬酸循环（三羧酸循环，TCA循环）、牛磺酸和亚牛磺酸代谢在稽留流产中显著改变。结果表明，基于血清核磁共振的代谢组学分析方法足够灵敏和特异，能够区分稽留流产患者和健康对照者，该方法可开发成为稽留流产临床有用的诊断工具。稽留流产血清代谢组分析结果为进一步理解稽留流产疾病机制提供了新线索。
