Skip to main content Accessibility help
×
Home

Multivariate techniques and their application in nutrition: a metabolomics case study

  • E. Katherine Kemsley (a1), Gwénaëlle Le Gall (a1), Jack R. Dainty (a1), Andrew D. Watson (a1), Linda J. Harvey (a1), Henri S. Tapp (a1) and Ian J. Colquhoun (a1)...

Abstract

The post-genomic technologies are generating vast quantities of data but many nutritional scientists are not trained or equipped to analyse it. In high-resolution NMR spectra of urine, for example, the number and complexity of spectral features mean that computational techniques are required to interrogate and display the data in a manner intelligible to the researcher. In addition, there are often multiple underlying biological factors influencing the data and it is difficult to pinpoint which are having the most significant effect. This is especially true in nutritional studies, where small variations in diet can trigger multiple changes in gene expression and metabolite concentration. One class of computational tools that are useful for analysing this highly multivariate data include the well-known ‘whole spectrum’ methods of principal component analysis and partial least squares. In this work, we present a nutritional case study in which NMR data generated from a human dietary Cu intervention study is analysed using multivariate methods and the advantages and disadvantages of each technique are discussed. It is concluded that an alternative approach, called feature subset selection, will be important in this type of work; here we have used a genetic algorithm to identify the small peaks (arising from metabolites of low concentration) that have been altered significantly following a dietary intervention.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

      Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Multivariate techniques and their application in nutrition: a metabolomics case study
      Available formats
      ×

      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

      Multivariate techniques and their application in nutrition: a metabolomics case study
      Available formats
      ×

      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

      Multivariate techniques and their application in nutrition: a metabolomics case study
      Available formats
      ×

Copyright

Corresponding author

*Corresponding author: Jack R. Dainty, fax 01603 507723, email jack.dainty@bbsrc.ac.uk

References

Hide All
Bales, JR, Sadler, PJ, Nicholson, JK & Timbrell, JA (1984) Urinary excretion of acetaminophen and its metabolites as studied by proton NMR spectroscopy. Clin Chem 30, 16311636.
Cloarec, O, Dumas, ME, Trygg, J, Craig, A, Barton, RH, Lindon, JC, Nicholson, JK & Holmes, E (2005) Evaluation of the orthogonal projection on latent structure model limitations caused by chemical shift variability and improved visualisation of biomarker changes in 1H NMR spectroscopic metabonomic studies. Anal Chem 77, 517526.
Craig, A, Cloarec, O, Holmes, E, Nicholson, JK & Lindon, JC (2006) Scaling and normalisation effects in NMR spectroscopic metabonomic data sets. Anal Chem 78, 22622267.
Daykin, CA, van Duynhoven, JPM, Groenewegen, A, Dachtler, M, van Amelsvoort, JMM & Mulder, TPJ (2005) Nuclear magnetic resonance spectroscopic based studies of the metabolism of black tea polyphenols in humans. J Agric Food Chem 53, 14281434.
Defernez, M & Kemsley, EK (1997) The use and misuse of chemometrics for treating classification problems. TRAC-Trend Anal Chem 16, 216221.
Dieterle, F, Ross, A, Schlotterbeck, G & Senn, H (2006) Probabilistic quotient normalisation as robust method to account for dilution of complex biological mixtures. Application to 1H NMR metabolomics. Anal Chem 78, 42814290.
Fan, TW-M (1996) Metabolite profiling by one- and two-dimensional NMR analysis of complex mixtures. Prog NMR Spectrosc 28, 161219.
Geladi, P & Kowalski, BR (1986) Partial Least-Squares Regression – a tutorial. Anal Chim Acta 185, 117.
Gibney, MJ, Walsh, M, Brennan, L, Roche, HM, German, JB & van Ommen, B (2005) Metabolomics in human nutrition: opportunities and challenges. Am J Clin Nutr 82, 497503.
Günther, H (1995) NMR Spectroscopy: Basic Principles, Concepts and Applications in Chemistry, 2nd ed. Chichester: J. Wiley & Sons.
Harvey, LJ, Dainty, JR, Hollands, WJ, Bull, VJ, Beattie, JH, Venelinov, TI, Hoogewerff, JA, Davies, IM & Fairweather-Tait, SJ (2005) Use of mathematical modeling to study copper metabolism in humans. Am J Clin Nutr 81, 807813.
Holmes, E, Foxall, PJD, Nicholson, JK, et al. (1994) Automatic data reduction and pattern recognition methods for analysis of 1H nuclear magnetic resonance spectra of human urine from normal and pathological states. Anal Biochem 220, 284296.
Kochhar, S, Jacobs, DM, Ramadan, Z, Berruex, F, Fuerholz, A & Fay, LB (2006) Probing gender-specific metabolism differences in humans by nuclear magnetic resonance-based metabonomics. Anal Biochem 352, 274281.
Leardi, R, Boggia, R & Terrile, M (1992) Genetic algorithms as a strategy for feature-selection. J Chemometrics 6, 267281.
Lenz, EM, Bright, J, Wilson, ID, Hughes, A, Morrisson, J, Lindberg, H & Lockton, A (2004) Metabonomics, dietary influences and cultural differences: a 1H NMR-based study of urine samples obtained from healthy British and Swedish subjects. J Pharmaceut Biomed 36, 841849.
Lenz, EM, Bright, J, Wilson, ID, Morgan, SR & Nash, AFP (2003) A H-1 NMR-based metabonomic study of urine and plasma samples obtained from healthy human subjects. J Pharmaceut Biomed 33, 11031115.
Lindon, JC, Nicholson, JK & Everett, JR (1999) NMR spectroscopy of biofluids. Ann Rep NMR Spectrosc 38, 287.
Pearson, K (1901) On lines and planes of closest fit to systems of points in space. Phil Mag 2, 559572.
Seber, GAF (1984) Multivariate Observations. Chichester: J. Wiley & Sons.
Solanky, KS, Bailey, NJC, Beckwith-Hall, BM, Bingham, S, Davis, A, Holmes, E, Nicholson, JK & Cassidy, A (2005) Biofluid 1H NMR-based metabonomic techniques in nutrition research – metabolic effects of dietary isoflavones in humans. J Nutr Biochem 16, 236244.
Solanky, KS, Bailey, NJC, Beckwith-Hall, BM, Davis, A, Bingham, S, Holmes, E, Nicholson, JK & Cassidy, A (2003) Application of biofluid 1H nuclear magnetic resonance-based metabonomic techniques for the analysis of the biochemical effects of dietary isoflavones on human plasma profile. Anal Biochem 323, 197204.
Tapp, HS, Defernez, M & Kemsley, EK (2003) FTIR spectroscopy and multivariate analysis can distinguish the geographic origin of extra virgin olive oils. J Agr Food Chem 51, 61106115.
van den Berg, RA, Hoefsloot, HCJ, Westerhuis, JA, Smilde, AK & van der Werf, MJ (2006) Centering, scaling and transformations: improving the biological information content of metabolomics data. BMC Genomics 7, 142(http://www.biomedcentral.com/1471-2164/7/142 ).
Wang, Y, Tang, H, Nicholson, JK, Hylands, PJ, Sampson, J & Holmes, E (2005) A metabonomic strategy for the detection of the metabolic effects of chamomile (Matricaria recutita L.) ingestion. J Agric Food Chem 53, 191196.
Westfall, PH & Young, SS (1993) Resampling-Based Multiple Testing. New York: J. Wiley & Sons.
Whitfield, PD, German, AJ & Noble, P-JM (2004) Metabolomics: an emerging post-genomic tool for nutrition. Br J Nutr 92, 549555.
Wold, S, Martens, H & Wold, H (1982) The multivariate calibration problem in chemistry solved by the PLS method. In Lecture Notes in Mathematics, pp. 286–293. Heidelberg: Springer Verlag.
Wold, S, Ruhe, A, Wold, H & Dunn, WJ (1984) The collinearity problem in linear regression: the partial least squares (PLS) approach to generalized inverses. SIAM J Sci Stats Comput 5, 735743.
Yoshida, H, Leardi, R, Funatsu, K & Varmuza, K (2001) Feature selection by genetic algorithms for mass spectral classifiers. Anal Chim Acta 446, 485–494.

Keywords

Related content

Powered by UNSILO

Multivariate techniques and their application in nutrition: a metabolomics case study

  • E. Katherine Kemsley (a1), Gwénaëlle Le Gall (a1), Jack R. Dainty (a1), Andrew D. Watson (a1), Linda J. Harvey (a1), Henri S. Tapp (a1) and Ian J. Colquhoun (a1)...

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed.