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Analysis of urinary metabolomic profiling for unstable angina pectoris disease based on nuclear magnetic resonance spectroscopy

机译:基于核磁共振波谱分析不稳定型心绞痛疾病的尿代谢组学分析

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摘要

~1H NMR-based urinary metabolic profiling is used for investigating the unstable angina pectoris (UAP) metabolic signatures, in order to find out candidate biomarkers to facilitate medical diagnosis. In this work, 27 urine samples from UAP patients and 20 heatthy controls were used. The metabolic profiles of the samples were analyzed by multivariate statistics analysis, including PCA, PLS-DA and OPLS-DA. The PCA analysis exhibited slight separation with R~2X of 0.681 and Q~2 of 0.251, while the PLS-DA (R~2X = 0.121, R~2Y = 0.931, and Q~2 = 0.661) and the OPLS-DA (R~2X = 0.121, R~2Y = 0.931, Q~2 = 0.653) demonstrated that the model showed good performance. By OPLS-DA, 20 metabolites were identified. A diagnostic model was further constructed using the receiver-operator characteristic (ROC) curves (AUC = 0.953), which exhibited a satisfying sensitivity of 92.6%, specificity of 90% and accuracy of 89.1%. The results demonstrated that the NMR-based metabolomics approach showed good performance in identifying diagnostic urinary biomarkers, providing new insights into the metabolic process related to UAP.
机译:基于1 H NMR的尿液代谢谱用于研究不稳定型心绞痛(UAP)的代谢特征,以便找出候选生物标记物以促进医学诊断。在这项工作中,使用了来自UAP患者的27个尿液样本和20个健康对照。通过多变量统计分析,包括PCA,PLS-DA和OPLS-DA,分析了样品的代谢谱。 PCA分析显示略有分离,R〜2X为0.681,Q〜2为0.251,而PLS-DA(R〜2X = 0.121,R〜2Y = 0.931,Q〜2 = 0.661)和OPLS-DA( R〜2X = 0.121,R〜2Y = 0.931,Q〜2 = 0.653)表明模型表现出良好的性能。通过OPLS-DA,鉴定出20种代谢物。使用接收者-操作者特征(ROC)曲线(AUC = 0.953)进一步构建了诊断模型,该曲线表现出令人满意的灵敏度(92.6%),特异性(90%)和准确度(89.1%)。结果表明,基于NMR的代谢组学方法在识别诊断性尿液生物标志物方面表现出良好的性能,为与UAP相关的代谢过程提供了新的见识。

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  • 来源
    《Molecular BioSystems》 |2015年第12期|3387-3396|共10页
  • 作者单位

    Department of Chemistry, Capital Normal University, Beijing 100048, China,Beijing University of Chinese Medicine, No.11 Beisanhuandonglu, Chaoyang District, Beijing 100029, China;

    Department of Chemistry, Capital Normal University, Beijing 100048, China;

    Beijing University of Chinese Medicine, No.11 Beisanhuandonglu, Chaoyang District, Beijing 100029, China;

    Beijing University of Chinese Medicine, No.11 Beisanhuandonglu, Chaoyang District, Beijing 100029, China;

    Beijing University of Chinese Medicine, No.11 Beisanhuandonglu, Chaoyang District, Beijing 100029, China;

    Beijing University of Chinese Medicine, No.11 Beisanhuandonglu, Chaoyang District, Beijing 100029, China;

    Department of Chemistry, Capital Normal University, Beijing 100048, China;

    Department of Chemistry, Capital Normal University, Beijing 100048, China;

    Beijing University of Chinese Medicine, No.11 Beisanhuandonglu, Chaoyang District, Beijing 100029, China;

    Beijing University of Chinese Medicine, No.11 Beisanhuandonglu, Chaoyang District, Beijing 100029, China;

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