Abstract
One-dimensional 1H nuclear magnetic resonance (1D 1H-NMR) has been used extensively as a metabolic profiling tool for investigating urine and other biological fluids. Under ideal conditions, 1H-NMR peak intensities are directly proportional to metabolite concentrations and thus are useful for class prediction and biomarker discovery. However, many biological, experimental and instrumental variables can affect absolute NMR peak intensities. Normalizing or scaling data to minimize the influence of these variables is a critical step in producing robust, reproducible analyses. Traditionally, analyses of biological fluids have relied on the total spectral area [constant sum (CS)] to normalize individual intensities. This approach can introduce considerable inter-sample variance as changes in any individual metabolite will affect the scaling of all of the observed intensities. To reduce normalization-related variance, we have developed a histogram matching (HM) approach adapted from the field of image processing. We validate our approach using mixtures of synthetic compounds that mimic a biological extract and apply the method to an analysis of urine from rats treated with ethionine. We show that HM is a robust method for normalizing 1H-NMR data and propose it as an alternative to the traditional CS method.
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Acknowledgments
We thank Astra Zeneca for co-funding the BioSysteMetrics Group at Stockholm University and Dr. Frank Dieterle for the source code for the PQN algorithm. We also gratefully acknowledge Ian Lewis, Department of Biochemistry, University of Wisconsin-Madison, for sharing the Semi-Synthetic dataset. The spectra of the synthetic mixtures were collected at the National Magnetic Resonance Facility at Madison (NMRFAM; NIH grants P41 RR02301 and P41 GM GM66326).
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Appendix
Appendix
1.1 Algorithm parameters
1.1.1 Histogram matching
Full spectra are used. N = 60.
1.1.2 Probabilistic quotient normalization
Plant data, used interval 0.02–6.00 ppm. Urine data, used interval 0.02–10.0 ppm, the water peak region (4.65–4.95 ppm) was set to zero.
1.1.3 Normalization to CS
Plant data, used interval 0.02–6.00 ppm. Urine data, used interval 0.02–10.0 ppm, the water peak region (4.65–4.95 ppm) was set to zero.
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Torgrip, R.J.O., Åberg, K.M., Alm, E. et al. A note on normalization of biofluid 1D 1H-NMR data. Metabolomics 4, 114–121 (2008). https://doi.org/10.1007/s11306-007-0102-2
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DOI: https://doi.org/10.1007/s11306-007-0102-2