Investigating the metabolic fingerprint of term infants with normal and increased fetal growth
Investigating the metabolic fingerprint of term infants with normal and increased fetal growth
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DOI：
10.1039/c6ra12403h
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发表时间：
2016-01-01
期刊：
影响因子：
3.9
通讯作者：
Zoumpoulakis, P.
中科院分区：
文献类型：
--
作者：
Fotakis, C.;Zoga, M.;Zoumpoulakis, P.
采用核磁共振代谢组学方法来突出产前疾病的代谢变化，并确定可作为大于胎龄 (LGA) 新生儿相关潜在标记物的代谢物。在这项整体研究中，多变量数据分析从核磁共振谱中获取信息，并探讨巨大胎儿的代谢特征。此外，还构建了诊断患有妊娠糖尿病的母亲 (LGA-GDM) 的 LGA 以及未诊断为 GDM 的母亲 (LGA-NGDM) 的 LGA 特征的代谢趋势。从母体和脐带 (UC) 样本中获得的结果表明，与适当孕龄 (AGA) 病例相比，LGA 胎儿存在变化，尤其是氨基酸代谢方面。在母体和 UC 样本的血液中均实现了 LGA-NGDM 与 LGA-GDM 的明确区分。对于母体 LGA 样本的分化，强调了谷氨酰胺和丙氨酸以及四种必需氨基酸（缬氨酸、亮氨酸、异亮氨酸、苏氨酸）的作用，以及甘油和葡萄糖的作用。甘氨酸和组氨酸仅有助于UC样本的分化，前者表征AGA病例，而后者则归因于LGA-GDM和LGA-NGDM病例。有趣的是，UC 和母体 LGA-GDM 样本的特点是 N-乙酰谷氨酸和乙酰乙酸水平增加。 OPLS-DA 模型通过排列测试和 ROC 曲线进行验证。总之，这项研究表明 NMR 代谢组学可以检测与 LGA 产前疾病相关的代谢变化。
An NMR metabolomic approach was employed to highlight the metabolic changes underlying prenatal disorders and determine metabolites that could serve as potential markers in relation to large for gestational age (LGA) newborns. In this holistic study, multivariate data analysis elicited information from the NMR spectra and probed to metabolic signatures of macrosomic fetuses. Moreover, metabolic trends that characterize LGA from mothers diagnosed with gestational diabetes mellitus (LGA-GDM), as well as LGA from mothers not diagnosed with GDM (LGA-NGDM) were framed. Results obtained from maternal and umbilical cord (UC) samples indicated that LGA fetuses present alterations especially in the aminoacid metabolism as compared to Appropriate for Gestational Age (AGA) cases. Clear discrimination of LGA-NGDM from LGA-GDM was achieved both in maternal and in UC samples' blood. The role of glutamine and alanine together with four essential (valine, leucine, isoleucine, threonine) aminoacids, as well as the role of glycerol and glucose is emphasized for the case of maternal LGA samples' differentiation. Glycine and histidine only contributed to the differentiation of UC samples, the former characterized the AGA cases, while the latter was ascribed to both LGA-GDM and LGA-NGDM cases. Interestingly, both UC and maternal LGA-GDM samples were characterized by increased levels of N-acetylglutamic and acetoacetic acids. The OPLS-DA models were validated with permutation testing and ROC curves. In conclusion, this study indicates that NMR metabolomics may enable the detection of metabolic changes associated with LGA prenatal disorders.