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Phenotyping human blood plasma by 1H-NMR: a robust protocol based on metabolite spiking and its evaluation in breast cancer

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Abstract

This study reports an accurate assignment of the resonance signals present in 1H-NMR spectra of human blood plasma. Hereto, blood plasma was spiked with 32 different metabolites in relevant concentrations since reported chemical shift values show quite some variability depending on the biofluid under study and the applied experimental measuring conditions. The resulting information was used to rationally divide the 1H-NMR spectrum in 110 well-defined integration regions for application in metabolomics. A case–control dataset of 53 breast cancer patients and 52 controls was investigated in order to demonstrate the proof of principle. After removal of noisy variables, i.e. variables exceeding a premised threshold for the coefficient of variation, the groups could be discriminated by OPLS-DA multivariate statistics with a sensitivity and specificity of 83 and 94 %, respectively. In addition, the classification was validated in a small but independent cohort. The proposed methodology might pave the way towards a better understanding of disturbances in disease-related biochemical pathways and so, to the clinical relevance of study findings.

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Abbreviations

1H:

Proton

BMI:

Body mass index

CPMG:

Carr-Purcell-Meiboom-Gill

ChEBI:

Chemical Entities of Biological Interest

D2O:

Deuterium oxide

DCIS:

Ductal carcinoma in situ

DModX:

Distance to model

ER:

Estrogen receptor

GC:

Gas chromatography

IDA:

Invasive ductal adenocarcinoma

ILA:

Invasive lobular adenocarcinoma

IUPAC-IUB:

Nomenclature committee of the international union of biochemistry

LC:

Liquid chromatography

MHz:

Megahertz

MS:

Mass spectrometry

NMR:

Nuclear magnetic resonance

OPLS-DA:

Orthogonal partial least squares-discriminant analysis

PCA:

Principal component analysis

ppm:

Parts per million

PR:

Progesterone receptor

RF:

Radio frequency

S/N:

Signal-to-noise ratio

TSP:

Trimethylsilyl-2,2,3,3-tetradeuteropropionic acid

References

  • Beckonert, O., Keun, H. C., Ebbels, T. M., Bundy, J., Holmes, E., Lindon, J. C., et al. (2007). Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Nature Protocols, 2(11), 2692–2703.

    Article  CAS  PubMed  Google Scholar 

  • Chang, D., Weljie, A., & Newton, J. (2007). Leveraging latent information in NMR spectra for robust predictive models. Pacific Symposium on Biocomputing, 12, 115–126.

    Google Scholar 

  • 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(7), 2262–2267.

    Article  CAS  PubMed  Google Scholar 

  • Engelke, U. F., Liebrand-van Sambeek, M. L., de Jong, J. G., Leroy, J. G., Morava, E., Smeitink, J. A., et al. (2004). N-acetylated metabolites in urine: proton nuclear magnetic resonance spectroscopic study on patients with inborn errors of metabolism. Clinical Chemistry, 50(1), 58–66.

    Article  CAS  PubMed  Google Scholar 

  • Fiehn, O. (2002). Metabolomics–the link between genotypes and phenotypes. Plant Molecular Biology, 48(1–2), 155–171.

    Article  CAS  PubMed  Google Scholar 

  • Garcia, E., Andrews, C., Hua, J., Kim, H. L., Sukumaran, D. K., Szyperski, T., et al. (2011). Diagnosis of early stage ovarian cancer by 1H-NMR metabonomics of serum explored by use of a microflow NMR probe. Journal of Proteome Research, 10(4), 1765–1771.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • German, J. B., Hammock, B. D., & Watkins, S. M. (2005). Metabolomics: Building on a century of biochemistry to guide human health. Metabolomics, 1(1), 3–9.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Kohl, S. M., Klein, M. S., Hochrein, J., Oefner, P. J., Spang, R., & Gronwald, W. (2012). State-of-the art data normalization methods improve NMR-based metabolomic analysis. Metabolomics, 8(Suppl 1), 146–160.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Lindon, J. C., & Nicholson, J. K. (2008). Spectroscopic and statistical techniques for information recovery in metabonomics and metabolomics. Annual Review of Analytical Chemistry (Palo Alto Calif), 1, 45–69.

    Article  CAS  Google Scholar 

  • Markley, J. L., Ulrich, E. L., Berman, H. M., Henrick, K., Nakamura, H., & Akutsu, H. (2008). BioMagResBank (BMRB) as a partner in the Worldwide Protein Data Bank (wwPDB): New policies affecting biomolecular NMR depositions. Journal of Biomolecular NMR, 40(3), 153–155.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Nicholson, J. K., Lindon, J. C., & Holmes, E. (1999). ‘Metabonomics’: Understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica, 29(11), 1181–1189.

    Article  CAS  PubMed  Google Scholar 

  • Nicholson, J. K., & Wilson, I. D. (2003). Opinion: Understanding ‘global’ systems biology: Metabonomics and the continuum of metabolism. Nature Reviews Drug Discovery, 2(8), 668–676.

    Article  CAS  PubMed  Google Scholar 

  • O’Connell, T. M. (2012). Recent advances in metabolomics in oncology. Bioanalysis, 4(4), 431–451.

    Article  PubMed  Google Scholar 

  • Oostendorp, M., Engelke, U. F., Willemsen, M. A., & Wevers, R. A. (2006). Diagnosing inborn errors of lipid metabolism with proton nuclear magnetic resonance spectroscopy. Clinical Chemistry, 52(7), 1395–1405.

    Article  CAS  PubMed  Google Scholar 

  • Salek, R. M., Maguire, M. L., Bentley, E., Rubtsov, D. V., Hough, T., Cheeseman, M., et al. (2007). A metabolomic comparison of urinary changes in type 2 diabetes in mouse, rat, and human. Physiological Genomics, 29(2), 99–108.

    Article  CAS  PubMed  Google Scholar 

  • Staab, J. M., O’Connell, T. M., & Gomez, S. M. (2010). Enhancing metabolomic data analysis with Progressive Consensus Alignment of NMR Spectra (PCANS). BMC Bioinformatics, 11, 123.

    Article  PubMed Central  PubMed  Google Scholar 

  • van den Berg, R. A., Hoefsloot, H. C., Westerhuis, J. A., Smilde, A. K., & van der Werf, M. J. (2006). Centering, scaling, and transformations: improving the biological information content of metabolomics data. BMC Genomics, 7, 142.

    Article  PubMed Central  PubMed  Google Scholar 

  • Wang, L., Chen, J., Chen, L., Deng, P., Bu, Q., Xiang, P., et al. (2013). 1H-NMR based metabonomic profiling of human esophageal cancer tissue. Molecular Cancer, 12, 25.

    Article  PubMed Central  PubMed  Google Scholar 

  • Wishart, D. S. (2008). Quantitative metabolomics using NMR. Trac-Trends in Analytical Chemistry, 27(3), 228–237.

    Article  CAS  Google Scholar 

  • Wishart, D. S., Jewison, T., Guo, A. C., Wilson, M., Knox, C., Liu, Y., et al. (2013). HMDB 3.0–The Human Metabolome Database in 2013. Nucleic Acids Research, 41, D801–D807.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Wishart, D. S., Tzur, D., Knox, C., Eisner, R., Guo, A. C., Young, N., et al. (2007). HMDB: the Human Metabolome Database. Nucleic Acids Research, 35, D521–D526.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Yang, W. J., Wang, Y. W., Zhou, Q. F., & Tang, H. R. (2008). Analysis of human urine metabolites using SPE and NMR spectroscopy. Science in China Series B-Chemistry, 51(3), 218–225.

    Article  CAS  Google Scholar 

  • Zheng, C., Zhang, S., Ragg, S., Raftery, D., & Vitek, O. (2011). Identification and quantification of metabolites in 1H-NMR spectra by Bayesian model selection. Bioinformatics, 27(12), 1637–1644.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

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Acknowledgments

This study is part of the Limburg Clinical Research Program UHasselt-ZOL-Jessa, supported by the foundation Limburg Sterk Merk, Hasselt University, Ziekenhuis Oost-Limburg and Jessa Hospital. We thank the Research Foundation Flanders (FWO-Vlaanderen) for their support via the MULTIMAR scientific research community project. We thank P. Degryse for his valuable contribution to the statistical discussions.

Ethical standards

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000 (5). Informed consent was obtained from all patients for being included in the study.

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Correspondence to Peter Adriaensens.

Additional information

The authors Evelyne Louis and Liene Bervoets contributed equally to this work.

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Louis, E., Bervoets, L., Reekmans, G. et al. Phenotyping human blood plasma by 1H-NMR: a robust protocol based on metabolite spiking and its evaluation in breast cancer. Metabolomics 11, 225–236 (2015). https://doi.org/10.1007/s11306-014-0690-6

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  • DOI: https://doi.org/10.1007/s11306-014-0690-6

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