Wilcock Amy, Begley Paul, Stevens Adam, Whatmore Andrew, Victor Suresh
a Faculty of Medical and Human Sciences , University of Manchester , Manchester , UK .
b Faculty of Medical and Human Sciences , Centre for Endocrinology and Diabetes, Institute of Human Development, The University of Manchester , Manchester , UK .
J Matern Fetal Neonatal Med. 2016 Mar;29(5):758-62. doi: 10.3109/14767058.2015.1017462. Epub 2015 Mar 19.
OBJECTIVE: No single diagnostic investigation is currently available for necrotising enterocolitis (NEC). We implemented a novel, untargeted, exploratory study to determine whether metabolomics can reveal early biomarker(s) of NEC. The effect of gestational age on the metabolome was also investigated. METHODS: Two serum samples were obtained from 12 preterm babies (born <30 weeks gestation) and eight term controls: sample "A" at ≤1 week of age and sample "B" once fully fed. Samples were subjected to gas chromatography-mass spectrometry. Metabolomic data was analysed by principal component analysis (PCA), univariate and network analysis. RESULTS: Sixteen metabolite features significantly differed when B samples were compared between preterm babies who subsequently developed NEC and preterm/term controls (p value <0.05). Of these seven metabolites were linked to up-regulation of IL-1β. Significant differences in 54 metabolite features (p value <0.05) were observed between preterm and term metabolomes. Of these, 12 metabolite features were linked to one network involved in carbohydrate/lipid metabolism (p = 1 × 10(-30)). CONCLUSIONS: Metabolomic differences were observed in preterm babies at risk of NEC. However, sample sizes were insufficient to confidently identify a biomarker. Network modelling of preterm and term metabolomes suggest possible nutritional deficiency and altered pro-insulin action in preterm babies.
目的:目前尚无针对坏死性小肠结肠炎(NEC)的单一诊断性检查方法。我们开展了一项新颖的、非靶向的探索性研究,以确定代谢组学是否能揭示NEC的早期生物标志物。同时还研究了胎龄对代谢组的影响。 方法:从12名早产婴儿(孕周<30周出生)和8名足月儿对照组获取两份血清样本:样本“A”在出生≤1周时采集,样本“B”在完全喂养后采集。样本进行气相色谱-质谱分析。代谢组学数据通过主成分分析(PCA)、单变量分析和网络分析进行分析。 结果:在随后发生NEC的早产婴儿与早产/足月对照组之间比较B样本时,有16个代谢物特征存在显著差异(p值<0.05)。其中7种代谢物与IL-1β的上调有关。在早产和足月代谢组之间观察到54个代谢物特征存在显著差异(p值<0.05)。其中,12个代谢物特征与一个参与碳水化合物/脂质代谢的网络有关(p = 1×10⁻³⁰)。 结论:在有NEC风险的早产婴儿中观察到了代谢组学差异。然而,样本量不足以可靠地鉴定出生物标志物。早产和足月代谢组的网络建模表明早产婴儿可能存在营养缺乏和胰岛素原作用改变的情况。
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