Application of a Bayesian deconvolution approach for high-resolution (1)H NMR spectra to assessing the metabolic effects of acute phenobarbital exposure in liver tissue.
Application of a Bayesian deconvolution approach for high-resolution (1)H NMR spectra to assessing the metabolic effects of acute phenobarbital exposure in liver tissue.
复制标题
应用贝叶斯反卷积方法进行高分辨率 (1)H NMR 谱评估急性苯巴比妥暴露对肝组织的代谢影响。
DOI：
10.1021/ac100344m
复制
发表时间：
2010
影响因子：
7.4
通讯作者：
Rubtsov DV
中科院分区：
文献类型：
--
作者：
Rubtsov DV
高分辨率1H NMR光谱学经常用于代谢组学领域，以评估生物流体或组织提取物中发现的代谢物，从而定义描述给定生物过程的代谢谱。在这项研究中，我们的目的是增加基于NMR代谢组学的效用，通过使用先进的贝叶斯建模的时域高分辨率一维NMR自由感应衰减（FID）。传统的非参数分箱的改进是双重的，并与信号处理阶段的分析和自动化的增强分辨率相关联。自动化是通过使用贝叶斯形式主义的所有参数的模型，包括组件的数量。该方法说明了一项研究的早期标志物急性暴露于不同剂量的一个良好的特点，非遗传毒性肝癌，苯巴比妥，在大鼠。结果表明，贝叶斯反卷积产生一个更好的模型的NMR光谱，允许识别代谢浓度的细微变化和减少预期的错误发现率相比，基于“分箱”的方法。这些性质表明，贝叶斯反卷积可以促进生物标志物的发现过程，并提高高分辨率NMR谱的信息提取。
High-resolution1H NMR spectroscopy is frequently used in the field of metabolomics to assess the metabolites found in biofluids or tissue extracts to define a metabolic profile that describes a given biological process. In this study, we aimed to increase the utility of NMR-based metabolomics by using advanced Bayesian modeling of the time-domain high-resolution 1D NMR free induction decay (FID). The improvement over traditional nonparametric binning is twofold and associated with enhanced resolution of the analysis and automation of the signal processing stage. The automation is achieved by using a Bayesian formalism for all parameters of the model including the number of components. The approach is illustrated with a study of early markers of acute exposure to different doses of a well-characterized nongenotoxic hepatocarcinogen, phenobarbital, in rats. The results demonstrate that Bayesian deconvolution produces a better model for the NMR spectra that allows the identification of subtle changes in metabolic concentrations and a decrease in the expected false discovery rate compared with approaches based on “binning”. These properties suggest that Bayesian deconvolution could facilitate the biomarker discovery process and improve information extraction from high-resolution NMR spectra.