Statistical Correlation and Projection Methods for Improved Information Recovery from Diffusion-Edited NMR Spectra of Biological Samples

详细信息    查看全文

• 作者：Leon M. Smith ; Anthony D. Maher ; Olivier Cloarec ; Mattias Rantalainen ; Huiru Tang ; Paul Elliott ; Jeremiah Stamler ; John C. Lindon ; Elaine Holmes ; Jeremy K. Nicholson
• 刊名：Analytical Chemistry
• 出版年：2007
• 出版时间：August 1, 2007
• 年：2007
• 卷：79
• 期：15
• 页码：5682 - 5689
• 全文大小：369K
• 年卷期：v.79,no.15(August 1, 2007)
• ISSN：1520-6882

文摘

Although NMR spectroscopic techniques coupled withmultivariate statistics can yield much useful informationfor classifying biological samples based on metabolicprofiles, biomarker identification remains a time-consuming and complex procedure involving separation methods,two-dimensional NMR, and other spectroscopic tools. Wepresent a new approach to aid complex biomixtureanalysis that combines diffusion ordered (DO) NMRspectroscopy with statistical total correlation spectroscopy(STOCSY) and demonstrate its application in the characterization of urinary biomarkers and enhanced information recovery from plasma NMR spectra. This methodrelies on calculation and display of the covariance of signalintensities from the various nuclei on the same moleculeacross a series of spectra collected under different pulsedfield gradient conditions that differentially attenuate thesignal intensities according to translational moleculardiffusion rates. We term this statistical diffusion-orderedspectroscopy (S-DOSY). We also have developed a newvisualization tool in which the apparent diffusion coefficients from DO spectra are projected onto a 1D NMRspectrum (diffusion-ordered projection spectroscopy,DOPY). Both methods either alone or in combination havethe potential for general applications to any complexmixture analysis where the sample contains compoundswith a range of diffusion coefficients.