Analytical and Bioanalytical Chemistry

, Volume 406, Issue 4, pp 1209–1219 | Cite as

Data-handling strategies for metabonomic studies: example of the UHPLC-ESI/ToF urinary signature of tetrahydrocannabinol in humans

  • Agneta Kiss
  • Claire Bordes
  • Corinne Buisson
  • Francoise Lasne
  • Pierre Lanteri
  • Cécile Cren-Olivé
Research Paper


Metabonomics has become a very valuable tool and many research fields rely on results coming out from this combination of analytical techniques, chemometric strategies, and biological interpretation. Moreover, the matrices are more and more complex and the implications of the results are often of major importance. In this context, the need for pertinent validation strategies comes naturally. The choice of the appropriate chemometric method remains nevertheless a difficult task due to particularities such as: the number of measured variables, the complexity of the matrix and the purposes of the study. Consequently, this paper presents a detailed metabonomic study on human urine with a special emphasis on the importance of assessing the data's quality. It also describes, step by step, the statistical tools currently used and offers a critical view on some of their limits. In this work, 29 urine samples among which 15 samples obtained from tetrahydrocannabinol (delta-9-tetrahydrocannabinol)-consuming athletes, 5 samples provided by volunteers, and 9 samples obtained from athletes were submitted to untargeted analysis by means of ultra high-pressure liquid chromatography–electrospray ionization–time-of-flight mass spectrometry. Next, the quality of the obtained data was assessed and the results were compared to those found in databases. Then, unsupervised (principal component analysis (PCA)) and supervised (ANOVA/PCA, partial least-square–discriminant analysis (PLS-DA), orthogonal PLS-DA) univariate and multivariate statistical methods were applied.


Metabonomics Doping LC-MS THC Chemometrics Validation 



Analysis of variance


Capillary electrophoresis-mass spectrometry


Coefficient of variation


Gaseous chromatography–mass spectrometry


Liquid chromatography–mass spectrometry


Liquid chromatography–time-of-flight mass spectrometry


Nuclear magnetic resonance


Orthogonal partial least-square analysis


Principal component analysis


Partial least-square–discriminant analysis


Quality control


Tetrahydrocannabinol delta-9-tetrahydrocannabinol; (6aR,10aR)-6,6,9-trimethyl-3-pentyl-6a,7,8,10a-tetrahydrobenzo[c]chromen-1-ol


Ultra high-pressure liquid chromatography–electrospray ionization–time-of-flight mass spectrometry



The authors would like to acknowledge the contribution of the Rhone-Alpes Regional Council and the French anti-Doping Agency for the samples necessary to this work. We would also like to thank Aurélie Fildier for her technical help for the high resolution mass spectrometry.

Supplementary material

216_2013_7199_MOESM1_ESM.pdf (168 kb)
ESM 1 (PDF 167 kb)


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Agneta Kiss
    • 1
  • Claire Bordes
    • 2
  • Corinne Buisson
    • 3
  • Francoise Lasne
    • 3
  • Pierre Lanteri
    • 2
  • Cécile Cren-Olivé
    • 1
  1. 1.Institut des Sciences AnalytiquesUMR 5280 CNRS, Equipe TRACESVilleurbanneFrance
  2. 2.Institut des Sciences AnalytiquesUMR 5280 CNRS, Equipe CHEMOVilleurbanneFrance
  3. 3.Département des AnalysesAgence Française de Lutte contre le DopageChâtenay-MalabryFrance

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