Crockford Derek J, Holmes Elaine, Lindon John C, Plumb Robert S, Zirah Severine, Bruce Stephen J, Rainville Paul, Stumpf Chris L, Nicholson Jeremy K
Biological Chemistry, Division of Biomedical Sciences, Sir Alexander Fleming Building, Imperial College London, SW7 2AZ, UK.
Anal Chem. 2006 Jan 15;78(2):363-71. doi: 10.1021/ac051444m.
Statistical heterospectroscopy (SHY) is a new statistical paradigm for the coanalysis of multispectroscopic data sets acquired on multiple samples. This method operates through the analysis of the intrinsic covariance between signal intensities in the same and related molecules measured by different techniques across cohorts of samples. The potential of SHY is illustrated using both 600-MHz 1H NMR and UPLC-TOFMS data obtained from control rat urine samples (n = 54) and from a corresponding hydrazine-treated group (n = 58). We show that direct cross-correlation of spectral parameters, viz. chemical shifts from NMR and m/z data from MS, is readily achievable for a variety of metabolites, which leads to improved efficiency of molecular biomarker identification. In addition to structure, higher level biological information can be obtained on metabolic pathway activity and connectivities by examination of different levels of the NMR to MS correlation and anticorrelation matrixes. The SHY approach is of general applicability to complex mixture analysis, if two or more independent spectroscopic data sets are available for any sample cohort. Biological applications of SHY as demonstrated here show promise as a new systems biology tool for biomarker recovery.
统计异谱学（SHY）是一种用于对多个样本上获取的多光谱数据集进行联合分析的新统计范式。该方法通过分析跨样本队列中不同技术测量的相同及相关分子信号强度之间的内在协方差来运作。使用从对照大鼠尿液样本（n = 54）和相应肼处理组（n = 58）获得的600-MHz 1H NMR和UPLC-TOFMS数据说明了SHY的潜力。我们表明，对于多种代谢物，光谱参数的直接互相关，即NMR的化学位移和MS的m/z数据，很容易实现，这提高了分子生物标志物识别的效率。除了结构之外，通过检查NMR与MS相关和反相关矩阵的不同层次，可以获得关于代谢途径活性和连通性的更高层次生物信息。如果任何样本队列有两个或更多独立的光谱数据集，SHY方法普遍适用于复杂混合物分析。此处展示的SHY的生物学应用表明其有望成为一种用于生物标志物恢复的新系统生物学工具。
