The identification of novel biomarkers of renal toxicity using automatic data reduction techniques and PCA of proton NMR spectra of urine
The identification of novel biomarkers of renal toxicity using automatic data reduction techniques and PCA of proton NMR spectra of urine
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DOI：
10.1016/s0169-7439(98)00110-5
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发表时间：
1998-12-14
影响因子：
3.9
通讯作者：
Connelly, J
中科院分区：
文献类型：
--
作者：
Holmes, E;Nicholson, JK;Connelly, J
药物引起的毒性病变的早期检测在制药行业是相当重要的。许多药物和毒素在尿谱中产生与病变部位或机制相关的生化扰动的特征性模式。生物流体的H-1核磁共振（NMR）波谱已被证明是表征此类病变的有用技术。我们在此提出了一种有效的方法来分析和分类从不同肾毒素（肾小球，乳头状和近端肾管）处理的大鼠获得的复杂尿液核磁共振光谱，该方法基于随后PCA自动生成的光谱描述符。采用600 MHz H-1核磁共振光谱进行尿液分析，并通过肾脏组织学检查确认肾脏病变部位。前三个pc的图显示了尿液样本的明显聚类，反映了肾脏内毒性的部位。对特征向量的问询表明，核磁共振光谱区域对类分离的贡献最大。这些区域在代谢物谱中进行了视觉检查，并定义了表征组织特异性病变的“标记”代谢物组。这些研究表明，在多变量技术（如主成分分析（PCA））之后对光谱进行自动数据缩减是筛选器官或组织特异性化学诱导病变生物标志物的可靠方法。(C) 1998 Elsevier Science B.V.版权所有
Early detection of drug-induced toxic lesions is of considerable importance in the pharmaceutical industry. Many drugs and toxins produce characteristic patterns of biochemical perturbations in the urinary profile related to the site or mechanism of the lesion. H-1 nuclear magnetic resonance (NMR) spectroscopy of biofluids has been shown to be a useful technique for characterising such lesions. We present here an efficient approach to the analysis and classification of complex urine NMR spectra obtained from rats treated with various nephrotoxins (glomerular, papillary and proximal tubular) based on the automatic generation of descriptors for the spectra with subsequent PCA. Urinalysis was performed using 600 MHz H-1 NMR spectroscopy and the site of renal lesion was confirmed by renal histology. A plot of the first three PCs showed distinct clustering of urine samples reflecting the site of toxicity within the kidney. Interrogation of the eigenvectors showed which NMR spectral regions contributed most to the separation of classes. These regions were examined visually for perturbations in metabolite profile and sets of 'marker' metabolites that characterised tissue-specific lesions were defined. These studies have shown that automatic data reduction of the spectra followed by multivariate techniques such as principal components analysis (PCA) is a reliable method for screening for biomarkers of organ or tissue-specific chemically-induced lesions. (C) 1998 Elsevier Science B.V. All rights reserved.