Application of Rotated PCA Models to Facilitate Interpretation of Metabolite Profiles: Commercial Preparations of St. John’s Wort

Abstract

This paper describes the application of orthogonal rotation of models based on principal component analysis (PCA) of ¹H nuclear magnetic resonance (NMR) spectra and high-performance liquid chromatography-photo diode array detection (HPLC-PDA) profiles of natural product mixtures using extracts of antidepressive pharmaceutical preparations of St. John’s wort as an example. ¹H-NMR spectroscopy of complex mixtures is often used in metabolomic, metabonomic and metabolite profiling studies for assessment of sample composition. Interpretation of the derived chemometric models may be complicated because several sample properties often contribute to each principal component and because the influence of individual metabolites may be shared by several principal components. Furthermore, extensive signal overlap in ¹H-NMR spectra poses additional challenges to the interpretation of PCA models derived from such data. Orthogonal rotation of PCA models derived from ¹H-NMR spectra and HPLC-PDA profiles of the extracts of St. John’s wort preparations facilitate interpretation of the model. Using the varimax criterion, rotation of loadings provides simpler conditions for understanding the influence of individual metabolites on the observed clustering. Alternatively, rotation of scores simplifies the understanding of the influence of whole metabolite profiles on the clustering of individual samples.

Key words

Hypericum perforatum L. - St. John’s wort - Clusiaceae - principal component analysis (PCA) - orthogonal rotation - metabolite profiling

References

• 1 Martens H, Næs T. Multivariate calibration. New York; Wiley 1989
• 2 Bailey N J, Sampson J, Hylands P J, Nicholson J K, Holmes E. Multi-component metabolic classification of commercial feverfew preparations via high-field ¹H-NMR spectroscopy and chemometrics.  Planta Med. 2002;  68 734-8
• 3 Choi Y H, Kim H K, Hazekamp A, Erkelens C, Lefeber A WM, Verpoorte R. Metabolomic differentiation of Cannabis sativa cultivars using ¹H NMR spectroscopy and principal component analysis.  J Nat Prod. 2004;  67 953-7
• 4 Frédérich M, Choi Y H, Angenot L, Harnischfeger G, Lefeber A WM, Verpoorte R. Metabolomic analysis of Strychnos nux-vomica, Strychnos icaja and Strychnos ignatii extracts by ¹H nuclear magnetic resonance spectrometry and multivariate analysis techniques.  Phytochemistry. 2004;  65 1993-2001
• 5 Wang Y, Tang H, Nicholson J K, Hylands P J, Sampson J, Whitcombe I. Metabolomic strategy for the classification and quality control of phytomedicine: A case study of chamomile flower (Matricaria recutita L.).  Planta Med. 2004;  70 250-5
• 6 Kim H K, Choi Y H, Erkelens C, Lefeber A WM, Verpoorte R. Metabolic fingerprinting of Ephedra species using ¹H NMR spectroscopy and principal component analysis.  Chem Pharm Bull. 2005;  53 105-9
• 7 Holmes E, Tang H R, Wang Y L, Seger C. The assessment of plant metabolite profiles by NMR-based methodologies.  Planta Med. 2006;  72 771-85
• 8 Rasmussen B, Cloarec O, Tang H R, Stærk D, Jaroszewski J W. Multivariate analysis of integrated and full-resolution ¹H-NMR spectral data from complex pharmaceutical preparations: St. John’s wort.  Planta Med. 2006;  72 556-63
• 9 Seger C, Sturm S. Analytical aspects of plant metabolite profiling platforms: Current standings and future aims.  J Proteome Res. 2007;  6 480-97
• 10 Schmidt B, Jaroszewski J W, Bro R, Witt M, Stærk D. Combining PARAFAC analysis of HPLC-PDA profiles and structural characterization using HPLC-PDA-SPE-NMR-MS experiments: Commercial preparations of St. John’s wort.  Anal Chem. 2008;  80 1978-87
• 11 Kaiser H F. The Varimax criterion for analytic rotation in factor-analysis.  Psychometrika. 1958;  23 187-200
• 12 Kiers H AL. A comparison of techniques for finding components with simple structure. In: Cuadras CMC, Rao CR, editors.  Multivariate analysis: future directions 2 Amsterdam:. Elsevier;  1993 67-86
• 13 Bundy J G, Sidhu J K, Rana F, Spurgeon D J, Svendsen C, Wren J F. ”Systems toxicology” approach identifies coordinated metabolic responses to copper in a terrestrial non-model invertebrate, the earthworm, Lumbricus rubellus. .  BMC Biol. 2008;  6 25
• 14 Rasmussen S, Parsons A J, Fraser K, Xue H, Newman J A. Metabolic profiles of Lolium perenne are differentially affected by nitrogen supply, carbohydrate content, and fungal endophyte infection.  Plant Physiol. 2008;  146 1440-53
• 15 Soares P K, Bruns R E, Scarminio I S. Statistical mixture design – Varimax factor optimization for selective compound extraction from plant material.  Anal Chim Acta. 2008;  613 48-55
• 16 Stojanovic K, Jovancicevic B, Vitorovic D, Golovko Y, Pevneva G, Golovko A. Evaluation of saturated and aromatic hydrocarbons oil-oil maturity correlation parameters (SE Pannonian Basin, Serbia).  J Serb Chem Soc. 2007;  72 1237-54
• 17 Kiers H AL. Simple structure in component analysis techniques for mixtures of qualitative and quantitative variable.  Psychometrika. 1991;  56 197-212
• 18 Cattell R B. ”Parrallel proportional profiles” and other principles for determining the choice of factors by rotation.  Psychometrika. 1944;  9 267-83
• 19 Malinowski E R. Factor analysis in chemistry, 3 rd edition. New York; Wiley-Interscience 2002
• 20 Dien J, Beal D J, Berg P. Optimizing principal components analysis of event-related potentials: Matrix type, factor loading weighting, extraction, and rotations.  Clin Neurophysiol. 2005;  116 1808-25
• 21 Kiers H AL. Simplimax – oblique rotation to an optimal target with simple structure.  Psychometrika. 1994;  59 567-79
• 22 Ferguson G A. The concept of parsimony in factor analysis.  Psychometrika. 1954;  19 281-90
• 23 ten Berge J MF. Suppressing permutations or rigid planar rotations: A remedy against nonoptimal varimax rotations.  Psychometrika. 1995;  60 437-46
• 24 Harman H H. Modern factor analysis. 3 rd edition. Chicago; University of Chicago Press 1976
• 25 Bilia A R, Bergonzi M C, Mazzi G, Vincieri F F. Analysis of plant complex matrices by use of nuclear magnetic resonance spectroscopy: St. John’s wort extract.  J Agric Food Chem. 2001;  49 2115-24
• 26 European Pharmacopoeia, 5th edition. Strassbourg; Council of Europe 2005: 2485-6
• 27 United States Pharmacopeia, USP 30: The National Formulary 25. Rockville; The United States Pharmacopeial Convention 2007: 978-9