Gaussian binning: a new kernel-based method for processing NMR spectroscopic data for metabolomics

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• 作者：Paul E. Anderson (1)
  Nicholas V. Reo (2)
  Nicholas J. DelRaso (3)
  Travis E. Doom (1)
  Michael L. Raymer (1)
  
• 关键词：Gaussian ; Binning ; Pattern recognition ; Quantification ; Nuclear magnetic resonance
• 刊名：Metabolomics
• 出版年：2008
• 出版时间：September 2008
• 年：2008
• 卷：4
• 期：3
• 页码：261-272
• 全文大小：545KB
• 参考文献：1. Anthony, M. L., Sweatman, B. C., Beddell, C. R., Lindon, J. C., & Nicholson, J. K. (1994). Pattern recognition classification of the site of nephrotoxicity based on metabolic data derived from proton nuclear magnetic resonance spectra of urine. / Molecular Pharmacology, / 46, 199.
  2. Beckwith-Hall, B. M., Holmes, E., Lindon, J. C., Gounarides, J., Vickers, A., Shapiro, M., et al. (2002). NMR-based metabonomic studies on the biochemical effects of commonly used drug carrier vehicles in the rat. / Chemical Research in Toxicology, / 15, 1136. doi:10.1021/tx020020+ . CrossRef
  3. Beckwith-Hall, B. M., Nicholson, J. K., Nicholls, A. W., Foxall, P. J., Lindon, J. C., Connor, S. C., et al. (1998). Nuclear magnetic resonance spectroscopic and principal components analysis investigations into biochemical effects of three model hepatotoxins. / Chemical Research in Toxicology, / 11, 260. doi:10.1021/tx9700679 . CrossRef
  4. Connor, S. C., Gray, R. A., Hodson, M. P., Clayton, N. M., Haselden, J. N., Chessell, I. P., et al. (2007). An NMR-based metabolic profiling study of inflammatory pain using the rat FCA model. / Metabolomics, / 3, 29-9. doi:10.1007/s11306-006-0039-x . CrossRef
  5. Craig, A., Cloarec, O., Holmes, E., Nicholson, J. K., & Lindon, J. C. (2006). Scaling and normalization effects in NMR spectroscopic metabonomic data sets. / Analytical Chemistry, / 78, 2262. doi:10.1021/ac0519312 . CrossRef
  6. Fiehn, O. (2002). Metabolomics–The link between genotypes and phenotypes. / Plant Molecular Biology, / 48, 155-71. doi:10.1023/A:1013713905833 . CrossRef
  7. Gartland, K. P., Beddell, C. R., Lindon, J. C., & Nicholson, J. K. (1991). Application of pattern recognition methods to the analysis and classification of toxicological data derived from proton nuclear magnetic resonance spectroscopy of urine. / Molecular Pharmacology, / 39, 629-42.
  8. Gartland, K. P., Sanins, S. M., Nicholson, J. K., Sweatman, B. C., Beddell, C. R., & Lindon, J. C. (1990). Pattern recognition analysis of high resolution ¹H NMR spectra of urine. A nonlinear mapping approach to the classification of toxicological data. / NMR in Biomedicine, / 3, 166. doi:10.1002/nbm.1940030404 . CrossRef
  9. Griffin, J. L., Williams, H. J., Sang, E., & Nicholson, J. K. (2001). Abnormal lipid profile of dystrophic cardiac tissue as demonstrated by one- and two-dimensional magic-angle spinning (1)H NMR spectroscopy. / Magnetic Resonance in Medicine: Official Journal of the Society of Magnetic Resonance in Medicine/Society of Magnetic Resonance in Medicine, / 46, 249.
  10. Holmes, E., Bonner, F. W., Sweatman, B. C., Lindon, J. C., Beddell, C. R., Rahr, E., et al. (1992). Nuclear magnetic resonance spectroscopy and pattern recognition analysis of the biochemical processes associated with the progression of and recovery from nephrotoxic lesions in the rat induced by mercury(II) chloride and 2-bromoethanamine. / Molecular Pharmacology, / 42, 922.
  11. Holmes, E., Nicholls, A. W., Lindon, J. C., Ramos, S., Spraul, M., Neidig, P., et al. (1998). Development of a model for classification of toxin-induced lesions using ¹H NMR spectroscopy of urine combined with pattern recognition. / NMR in Biomedicine, / 11, 235. doi :10.1002/(SICI)1099-1492(199806/08)11:4/5<235::AID-NBM507>3.0.CO;2-V. CrossRef
  12. Hotelling, H. (1933). Analysis of a complex of statistical variables into principal components. / Journal of Educational Psychology, / 24, 417-41. doi:10.1037/h0071325 . CrossRef
  13. Jolliffe, I. T. (1986). / Principal component analysis. New York: Springer-Verlag.
  14. Lindon, J. C., Holmes, E., & Nicholson, J. K. (2001). Pattern recognition methods and applications in biomedical magnetic resonance. / Progress in Nuclear Magnetic Resonance Spectroscopy, / 39, 1. doi:10.1016/S0079-6565(00)00036-4 . CrossRef
  15. Martens, H., & Naes, T. (1989). / Multivariate calibration. London: Wiley.
  16. Nicholson, J. K., & Wilson, I. D. (1989). High resolution proton magnetic resonance spectroscopy of biological fluids. / Progress in Nuclear Magnetic Resonance Spectroscopy, / 21, 444-01. doi:10.1016/0079-6565(89)80008-1 . CrossRef
  17. Reo, N. V. (2002). NMR-based metabolomics. / Drug and Chemical Toxicology, / 25, 375-82. doi:10.1081/DCT-120014789 . CrossRef
  18. Robertson, D. G., Reily, M. D., Sigler, R. E., Wells, D. F., Paterson, D. A., & Braden, T. K. (2000). Metabonomics: evaluation of nuclear magnetic resonance (NMR) and pattern recognition technology for rapid in vivo screening of liver and kidney toxicants. / Toxicological Sciences, / 57, 326-37. doi:10.1093/toxsci/57.2.326 . CrossRef
  19. Robosky, L. C., Robertson, D. G., Baker, J. D., Rane, S., & Reily, M. D. (2002). In vivo toxicity screening programs using metabonomics. / Combinatorial Chemistry & High Throughput Screening, / 5, 651.
  20. Shockcor, J. P., & Holmes, E. (2002). Metabonomic applications in toxicity screening and disease diagnosis. / Current Topics in Medicinal Chemistry, / 2, 35. doi:10.2174/1568026023394498 . CrossRef
  21. Spraul, M., Neidig, P., Klauck, U., Kessler, P., Holmes, E., Nicholson, J. K., et al. (1994). Automatic reduction of NMR spectroscopic data for statistical and pattern recognition classification of samples. / Journal of Pharmaceutical and Biomedical Analysis, / 12, 1215. doi:10.1016/0731-7085(94)00073-5 . CrossRef
  22. Wang, Y., Holmes, E., Nicholson, J. K., Cloarec, O., Chollet, J., Tanner, M., et al. (2004). Metabonomic investigations in mice infected with / Schistosoma mansoni: An approach for biomarker identification. / Proceedings of the National Academy of Sciences of the USA, / 101, 12676-2681. doi:10.1073/pnas.0404878101 . CrossRef
  23. Waters, N. J., Holmes, E., Waterfield, C. J., Farrant, R. D., & Nicholson, J. K. (2002). NMR and pattern recognition studies on liver extracts and intact livers from rats treated with / α-naphthylisothiocyanate. / Biochemical Pharmacology, / 64, 67-7. doi:10.1016/S0006-2952(02)01016-X . CrossRef
  24. Westrick, M. P., DelRaso, N. J., Raymer, M. L., Anderson, P. E., Mahle, D. A., Neuforth, A. E., et?al. Dose and time response metabonomic analyses of / α-naphthylisothiocyanate toxicity in the rat. / Chemical Research in Toxicology, submitted.
  25. Whitehead, T. L., Monzavi-Karbassi, B., & Kieber-Emmons, T. (2005). ¹H-NMR metabonomics analysis of sera differentiates between mammary tumor-bearing mice and healthy controls. / Metabolomics, / 1, 269-78. doi:10.1007/s11306-005-0006-y . CrossRef
  26. Williams, R. E., Cottrell, L., Jacobsen, M., Bandara, L. R., Kelly, M. D., & Kennedy, S. (2003). ¹H-Nuclear magnetic resonance pattern recognition studies with / N-phenylanthranilic acid in the rat: Time- and dose-related metabolic effects. / Biomarkers, / 8, 472-90. doi:10.1080/13547500310001647030 . CrossRef
  27. Wold, H. (1966). / Estimation of principal components and related models by iterative least squares (1st ed.). New York: Academic Press.
  
• 作者单位：Paul E. Anderson (1)
  Nicholas V. Reo (2)
  Nicholas J. DelRaso (3)
  Travis E. Doom (1)
  Michael L. Raymer (1)
  
  1. Department of Computer Science and Engineering, Wright State University, Dayton, OH, 45435, USA
  2. Department of Biochemistry and Molecular Biology, Boonshoft School of Medicine, Cox Institute, Wright State University, Dayton, OH, 45429, USA
  3. 711 Human Performance Wing, Wright-Patterson AFB, USAF, Dayton, OH, 45433, USA
  
• ISSN：1573-3890

文摘

In many metabolomics studies, NMR spectra are divided into bins of fixed width. This spectral quantification technique, known as uniform binning, is used to reduce the number of variables for pattern recognition techniques and to mitigate effects from variations in peak positions; however, shifts in peaks near the boundaries can cause dramatic quantitative changes in adjacent bins due to non-overlapping boundaries. Here we describe a new Gaussian binning method that incorporates overlapping bins to minimize these effects. A Gaussian kernel weights the signal contribution relative to distance from bin center, and the overlap between bins is controlled by the kernel standard deviation. Sensitivity to peak shift was assessed for a series of test spectra where the offset frequency was incremented in 0.5?Hz steps. For a 4?Hz shift within a bin width of 24?Hz, the error for uniform binning increased by 150%, while the error for Gaussian binning increased by 50%. Further, using a urinary metabolomics data set (from a toxicity study) and principal component analysis (PCA), we showed that the information content in the quantified features was equivalent for Gaussian and uniform binning methods. The separation between groups in the PCA scores plot, measured by the J 2 quality metric, is as good or better for Gaussian binning versus uniform binning. The Gaussian method is shown to be robust in regards to peak shift, while still retaining the information needed by classification and multivariate statistical techniques for NMR-metabolomics data.