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Predictive metabolomic signatures of end-stage renal disease: A multivariate analysis of population-based data
Biochimie ( IF 3.3 ) Pub Date : 2018-06-15 , DOI: 10.1016/j.biochi.2018.06.009
Robson E. Silva , João L. Baldim , Daniela A. Chagas-Paula , Marisi G. Soares , João H.G. Lago , Reggiani V. Gonçalves , Rômulo D. Novaes

The variability of molecular signatures and predictive low molecular weight markers of chronic kidney disease (CKD) in different populations are poorly understood. Thus, in a large sample with 4763 people we compare the molecular signatures and metabolites with diagnostic relevance in plasma and urine of CKD patients of different geographical origins. From an integrated model based on dynamic networks and multivariate statistics, metabolites with predictive value obtained from targeted and untargeted molecular analysis, interactions between metabolic pathways affected by CKD, and the methodological quality of metabolomic studies were analyzed. The metabolites 3-methylhistidine, citrulline, kynurenine, p-cresol sulfate, urea, and citrate presented consistent expression in all population groups. Only increased kynurenine and p-cresol sulfate in plasma samples obtained acceptable scores as CKD biomarkers, independent of geographic origin. Metabolites such as leucine, alanine, isoleucine, serine, histidine, and citrate were nodal points, indicating that protein metabolism pathways are similarly impaired in Asian, European and North American patients. Based on our integrated model, we show that the metabolome of CKD patients exhibits a strong geographic influence, leading to unique metabolic signatures. Contrary to the likelihood of molecular similarities between geographically distinct populations, metabolic convergences in protein metabolism pathways and the molecules kynurenine and p-cresol sulfate were relevant as general predictors of CKD. In general, the quality assessment indicated that the current evidence is based on research models with variable methodological quality, whose limitations described in this study should be considered in the refinement of molecular approaches.



中文翻译:

终末期肾脏疾病的预测代谢组学特征:基于人群的数据的多变量分析

人们对慢性肾脏病(CKD)在不同人群中的分子特征和预测性低分子量标志物的变异性了解甚少。因此,在一个有4763人的大型样本中,我们比较了不同地理来源的CKD患者血浆和尿液中的分子特征和代谢物具有诊断意义。从基于动态网络和多元统计数据的集成模型中,分析有针对性和无针对性的分子分析获得的具有预测价值的代谢物,CKD影响的代谢途径之间的相互作用以及代谢组学研究的方法学质量。代谢物3-甲基组氨酸,瓜氨酸,犬尿氨酸,硫酸对甲酚,尿素和柠檬酸盐在所有人群中均表达一致。血浆样品中只有增加的犬尿氨酸和对甲酚硫酸盐作为CKD生物标志物获得了可接受的评分,与地理来源无关。亮氨酸,丙氨酸,异亮氨酸,丝氨酸,组氨酸和柠檬酸盐等代谢物是结点,表明在亚洲,欧洲和北美患者中,蛋白质代谢途径也同样受损。基于我们的综合模型,我们表明CKD患者的代谢组表现出强大的地理影响,从而导致独特的代谢特征。与地理上不同人群之间分子相似性的可能性相反,蛋白质代谢途径中的代谢趋同以及分子犬尿氨酸和硫酸对甲酚是CKD的一般预测指标。一般来说,

更新日期:2018-06-15
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