Preterm neonatal urinary renal developmental and acute kidney injury metabolomic profiling: an exploratory study.
Preterm neonatal urinary renal developmental and acute kidney injury metabolomic profiling: an exploratory study.
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DOI：
10.1007/s00467-016-3439-9
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发表时间：
2017-01
期刊：
影响因子：
--
通讯作者：
Sumner S
中科院分区：
文献类型：
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作者：
Mercier K;McRitchie S;Pathmasiri W;Novokhatny A;Koralkar R;Askenazi D;Brophy PD;Sumner S
AKI 分期已在成人和儿童人群中制定，但对于新生儿人群尚不存在。利用代谢组学来揭示早产儿正常和 AKI 相关肾功能的生物标志物。该研究由 20 名被诊断为 AKI 的早产儿组成，他们的胎龄和性别与 20 名未诊断为 AKI 的婴儿进行了匹配。使用广谱核磁共振代谢组学分析早产新生儿出生后第 2 天收集的尿液样本。使用多变量分析方法来鉴定区分 AKI 和非 AKI 的代谢物谱，并鉴定与患有和不患有 AKI 的婴儿的胎龄相关的代谢组学特征。 AKI 和非 AKI 概况之间存在明显区别。先前确定的两种 AKI 生物标志物：马尿酸和高香草酸，可区分 AKI 和非 AKI。通路分析揭示了与胆碱神经元、胰腺β细胞的产前尼古丁暴露以及双甲脒诱导的胰岛素分泌抑制的相似性。此外，还注意到 pH 值差异。 pH 值和代谢物均被发现与 AKI 相关；然而，只有代谢型是 AKI 的重要预测因子。与胎龄唯一相关的非 AKI 组的途径包括氨酰基-t-RNA 生物合成，而 AKI 组的途径在丙酮酸代谢中产生了潜在的代谢物变化。代谢组学能够区分有或没有 AKI 诊断的新生儿的尿液特征，并且代谢发育特征与胎龄相关。需要在更大的队列中进行进一步的研究来验证这些结果。
AKI staging has been developed in the adult and pediatric populations, but these do not yet exist for the neonatal population. Metabolomics was utilized to uncover biomarkers of normal and AKI associated renal function in preterm infants. The study was comprised of 20 preterm infants with an AKI diagnosis who were matched by gestational age and gender to 20 infants without an AKI diagnosis. Urine samples from pre-term newborn infants collected on day 2 of life were analyzed using broad spectrum NMR-metabolomics. Multivariate analysis methods were used to identify metabolite profiles that differentiated AKI and no AKI, and to identify a metabolomics profile correlating with gestational age in infants with and without AKI. There was a clear distinction between the AKI and no-AKI profiles. Two previously identified biomarkers of AKI, hippurate and homovanillate, differentiated AKI and no-AKI. Pathway analysis revealed similarities to cholingeric neurons, prenatal nicotine exposure on pancreatic β cells, and Amitraz-induced inhibition of insulin secretion. Additionally, a pH difference was noted. Both pH and the metabolites were found to be associated of AKI; however, only the metabotype was a significant predictor of AKI. Pathways for the no-AKI group that were uniquely correlated to gestational age included aminoacyl-t-RNA biosynthesis, whereas pathways in the AKI group yielded potential metabolite changes in pyruvate metabolism. Metabolomics was able to differentiate the urinary profiles of neonates with and without an AKI diagnosis and metabolic developmental profiles were correlated with gestational age. Further studies in larger cohorts are needed to validate these results.