Metabolomics-based methods for early disease diagnostics

References

• Nicholson JK, Wilson ID. High-resolution proton magnetic resonance spectroscopy of biological-fluids. Prog. NMR Spectrosc.21, 449–501 (1989).
   Web of Science ®Google Scholar
• Nicholson JK, Lindon JC, Holmes E. ‘Metabonomics’: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica29, 1181–1189 (1999).
   PubMed Web of Science ®Google Scholar
• Shockcor JP, Holmes E. Metabonomic applications in toxicity screening and disease diagnosis. Curr. Top. Med. Chem.2, 35–51 (2002).
   PubMedGoogle Scholar
• Nicholson JK, Wilson ID. Understanding ‘global’ systems biology: metabonomics and the continuum of metabolism. Nat. Rev. Drug Discov.2, 668–676 (2003).
   PubMed Web of Science ®Google Scholar
• Lindon JC, Holmes E, Nicholson JK. Metabonomics and its role in drug development and disease diagnosis. Expert. Rev. Mol. Diagn.4, 189–199 (2004).
   PubMed Web of Science ®Google Scholar
• Robertson DG. Metabonomics in toxicology: a review. Toxicol. Sci.85, 809–822 (2005).
   PubMed Web of Science ®Google Scholar
• Nicholson JK. Global systems biology, personalized medicine and molecular epidemiology. Mol. Syst. Biol.1–6 (2006).
   Google Scholar
• Wishart DS, Tzur D, Knox C et al. HMDB: the Human Metabolome Database. Nucleic Acids Res.35, D521–D526 (2007).
   PubMed Web of Science ®Google Scholar
• Griffin JL. The Cinderella story of metabolic profiling: does metabolomics get to go to the functional genomics ball? Philos. Trans. R. Soc. Lond. B Biol. Sci.361, 147–161 (2006).
   PubMed Web of Science ®Google Scholar
• Villar-Garea A, Griese M, Imhof A. Biomarker discovery from body fluids using mass spectrometry. J. Chromatogr. B849(1–2), 105–114 (2007).
   PubMedGoogle Scholar
• Wishart DS. Metabolomics: the principles and potential applications to transplantation. Am. J. Transplant.5, 2814–2820 (2005).
   PubMed Web of Science ®Google Scholar
• Pelczer I. High-resolution NMR for metabomics. Curr. Opin. Drug Discov. Devel.8, 127–133 (2005).
   PubMedGoogle Scholar
• Keun HC. Metabonomic modeling of drug toxicity. Pharmacol. Ther.109, 92–106 (2006).
   PubMed Web of Science ®Google Scholar
• Serkova NJ, Niemann CU. Pattern recognition and biomarker validation using quantitative 1H-NMR-based metabolomics. Expert Rev. Mol. Diagn.6, 717–731 (2006).
   PubMed Web of Science ®Google Scholar
• Lindon JC, Holmes E, Nicholson JK. Metabonomics techniques and applications to pharmaceutical research & development. Pharm. Res.23, 1075–1088 (2006).
   PubMed Web of Science ®Google Scholar
• Harrigan GG, Goodacre R. Metabolic Profiling: Its Role in Biomarker Discovery and Gene Functional Analysis. Kluwer Academic Publishers, MA, USA 1–8 (2003).
   Google Scholar
• Fiehn O. Metabolomics – the link between genotype and phenotype. Plant Mol. Biol.48, 155–171 (2002).
   PubMed Web of Science ®Google Scholar
• Kell DB. Metabolomics and systems biology: making sense of the soup. Curr. Opin. Microbiol.7, 296–307 (2004).
   PubMed Web of Science ®Google Scholar
• van der Greef J, Smilde AK. Symbiosis of chemometrics and metabolomics: past, present, and future. J. Chemomet.19, 376–386 (2005).
   Web of Science ®Google Scholar
• Lacey ME, Subramanian R, Olson DL, Webb AG, Sweedler JV. High-resolution NMR spectroscopy of sample volumes from 1 nL to 10 µL. Chem. Rev.99, 3133–3152 (1999).
   PubMed Web of Science ®Google Scholar
• Raftery D. High-throughput NMR spectroscopy. Anal. Bioanal. Chem.378, 1403–1404 (2004).
   PubMed Web of Science ®Google Scholar
• Lindon JC. HPLC-NMR-MS: past, present and future. Drug Disc. Today8, 1021–1022 (2003).
   PubMed Web of Science ®Google Scholar
• Brown SC, Kruppa G, Dasseux JL. Metabolomics applications of FT-ICR mass spectrometry. Mass Spectrom. Rev.24, 223–231 (2005).
   PubMed Web of Science ®Google Scholar
• Granger JH, Bake A, Plumb RS, Perez JC, Wilson ID. Ultra performance liquid chromatography-MS(TOF): new separations technology for high throughput metabonomics. Drug Met. Rev.36, 252–252 (2004).
   Google Scholar
• Villas-Boas SG, Mas S, Akesson M, Smedsgaard J, Nielsen J. Mass spectrometry in metabolome analysis. Mass Spectrom. Rev.24, 613–646 (2005).
   PubMed Web of Science ®Google Scholar
• Wilson ID, Plumb R, Granger J, Major H, Williams R, Lenz EA. HPLC-MS-based methods for the study of metabonomics. J. Chromatog. B817, 67–76 (2005).
   PubMed Web of Science ®Google Scholar
• Mohler RE, Dombek KM, Hoggard JC, Young ET, Synovec RE. Comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry analysis of metabolites in fermenting and respiring yeast cells. Anal. Chem.78, 2700–2709 (2006).
   PubMed Web of Science ®Google Scholar
• Chen H, Venter A, Cooks RG. Extractive electrospray ionization for direct analysis of undiluted urine, milk and other complex mixtures without sample preparation. Chem. Commun.19, 2042–2044 (2006).
   Google Scholar
• Takats Z, Wiseman JM, Gologan B, Cooks RG. Mass spectrometry sampling under ambient conditions with desorption electrospray ionization. Science306, 471–473 (2004).
   PubMed Web of Science ®Google Scholar
• Cody RB, Laramee JA, Durst HD. Versatile new ion source for the analysis of materials in open air under ambient conditions. Anal. Chem.77, 2297–2302 (2005).
   Google Scholar
• Johnson RA, Wichern DW. Applied Multivariate Statistical Analysis. Prentice Hall, NJ, USA (1999).
   Google Scholar
• Krzanowski WJ. Principles of Multivariate Analysis: a User’s Perspective (Revised Edition). Oxford University Press, Oxford, UK (2000).
   Google Scholar
• Brereton RG. Chemometrics: Data Analysis for the Laboratory and Chemical Plant. Wiley, West Sussex, UK (2003).
   Google Scholar
• Keun HC, Ebbels TMD, Antti H et al. Improved analysis of multivariate data by variable stability scaling: application to NMR-based metabolic profiling. Anal. Chim. Acta490, 265–276 (2003).
   Web of Science ®Google Scholar
• Beckwith-Hall BM, Brindle JT, Barton RH et al. Application of orthogonal signal correction to minimise the effects of physical and biological variation in high resolution 1H NMR spectra of biofluids. Analyst127, 1283–1288 (2002).
   PubMed Web of Science ®Google Scholar
• Bollard ME, Stanley EG, Lindon JC, Nicholson JK, Holmes E. NMR-based metabonomic approaches for evaluating physiological influences on biofluid composition. NMR Biomed.18, 143–162 (2005).
   PubMed Web of Science ®Google Scholar
• Nagana Gowda GA, Ijare OB, Somashekar BS, Sharma A, Kapoor VK, Khetrapal CL. Single-step analysis of individual conjugated bile acids in human bile using 1H NMR spectroscopy. Lipids41, 591–603 (2006).
   Google Scholar
• Bala L, Ghoshal UC, Ghoshal U et al. Malabsorption syndrome with and without small intestinal bacterial overgrowth: a study on upper-gut aspirate using 1H NMR spectroscopy. Magn. Reson. Med.56, 738–744 (2006).
   PubMed Web of Science ®Google Scholar
• Griffin JL, Kauppinen RA. Tumour metabolomics in animal models of human cancer. J. Proteome Res.6, 498–505 (2007).
   PubMed Web of Science ®Google Scholar
• Beckonert O, Keun HC, Ebbels TMD et al. Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Nat. Protoc.2, 2692–2703 (2007).
   PubMed Web of Science ®Google Scholar
• Saude EJ, Slupsky CM, Sykes BD. Optimization of NMR analysis of biological fluids for quantitative accuracy. Metabolomics2, 113–123 (2006).
   Google Scholar
• Mo H, Raftery D. Pre-SAT180, a simple and effective faraway water suppression method. J. Magn. Reson.190, 1–6 (2008).
   Google Scholar
• Wu D, Chen A, Johnson CS. An improved diffusion-ordered spectroscopy experiment incorporating bipolar-gradient pulses. J. Magn. Reson.115, 260–264 (1995).
   Web of Science ®Google Scholar
• Sandusky P, Raftery D. Use of selective TOCSY NMR experiments for quantifying minor components in complex mixtures: application to the metabonomics of amino acids in honey. Anal. Chem.77, 2455–2463 (2005).
   Google Scholar
• Sandusky P, Raftery D. Use of semiselective TOCSY and the Pearson Correlation for the metabonomic analysis of biofluid mixtures: application to urine. Anal. Chem.77, 7717–7723 (2005).
   Google Scholar
• Dumas M-E, Canlet C, Andre F, Vercauteren J, Paris A. Metabonomic assessment of physiological disruptions using 1H–13C HMBC NMR spectroscopy combined with pattern recognition procedures performed on filtered variables. Anal. Chem.74, 2261–2273 (2002).
   PubMed Web of Science ®Google Scholar
• Tang H, Wang Y, Nicholson JK, Lindon JC. Use of relaxation-edited one-dimensional and two-dimensional nuclear magnetic resonance spectroscopy to improve detection of small metabolites in blood plasma. Anal. Biochem.325, 260–272 (2004).
   PubMed Web of Science ®Google Scholar
• Dumas M-E, Canlet C, Vercauteren J, Andre F, Paris A. Homeostatic signature of anabolic steroids in cattle using 1H–13C HMBC NMR metabonomics. J. Proteome Res.4, 1493–1502 (2005).
   Web of Science ®Google Scholar
• Xi Y, de Ropp JS, Viant MR, Woodruff DL, Yu P. Automated screening for metabolites in complex mixtures using 2D COSY NMR spectroscopy. Metabolomics2, 221–233 (2006).
   Google Scholar
• Viant MR. Improved methods for the acquisition and interpretation of NMR metabolomic data. Biochem. Biophys. Res. Commun.310, 943–948 (2003).
   PubMed Web of Science ®Google Scholar
• Shanaiah N, Desilva MA, Nagana Gowda GA, Raftery MA, Hainline BE, Raftery D. Class selection of amino acid metabolites in body fluids using chemical derivatization and their enhanced 13C NMR. Proc. Natl Acad. Sci.104, 11540–11544 (2007).
   PubMed Web of Science ®Google Scholar
• Yang Y, Li C, Nie X et al. Metabonomic studies of human hepatocellular carcinoma using high-resolution magic-angle spinning 1H NMR spectroscopy in conjunction with multivariate data analysis. J. Proteome Res.6, 2605–2614 (2007).
   PubMed Web of Science ®Google Scholar
• Zhang X, Wei D, Yap Y, Li L, Guo S, Chen F. Mass spectrometry-based “omics” technologies in cancer diagnostics. Mass Spectrom. Rev.26, 403–431 (2007).
   PubMed Web of Science ®Google Scholar
• Wilson ID, Nicholson JK, Castro-Perez J et al. High resolution “ultra performance” liquid chromatography coupled to oa-TOF mass spectrometry as a tool for differential metabolic pathway profiling in functional genomic studies. J. Proteome Res.4, 591–598 (2005).
   PubMed Web of Science ®Google Scholar
• Villas-Boas SG, Delicado DG, Akesson M, Nielsen J. Simultaneous analysis of amino and non-amino organic acids as methyl chloroformate derivatives using gas chromatography-mass spectrometry. Anal. Biochem.322(1), 134–138 (2003).
   PubMed Web of Science ®Google Scholar
• O’Hagan S, Dunn WB, Knowles JD et al. Closed-loop, multiobjective optimization of two-dimensional gas chromatography/mass spectrometry for serum metabolomics. Anal. Chem.79(2), 464–476 (2007).
   PubMed Web of Science ®Google Scholar
• Kelly RT, Page JS, Zhao R et al. Capillary?based multi nanoelectrospray emitters: improvements in ion transmission efficiency and implementation with capillary reversed-phase LC-ESI-MS. Anal. Chem.80, 143–149 (2008).
   PubMed Web of Science ®Google Scholar
• Chen H, Wortmann A, Zhang W, Zenobi R. Rapidin vivo fingerprinting of nonvolatile compounds in breath by extractive electrospray ionization quadrupole time-of-flight mass spectrometry. Angew. Chem. Int. Ed. Engl.46(4), 580–583 (2007).
   PubMed Web of Science ®Google Scholar
• Gu H, Chen H, Pan Z et al. Monitoring diet effects via biofluids and their implications for metabolomics studies. Anal. Chem.79(1), 89–97 (2007).
   PubMed Web of Science ®Google Scholar
• Vaidyanathan S, Gaskell S, Goodacre R. Matrix-suppressed laser desorption/ionisation mass spectrometry and its suitability for metabolome analyses. Rapid Commun. Mass Spectrom.20(8), 1192–1198 (2006).
   Google Scholar
• Nordstro1m A, Want E, Northen T, Lehtio1 J, Siuzdak G. Multiple ionization mass spectrometry strategy used to reveal the complexity of metabolomics. Anal. Chem.80, 421–429 (2008).
   Google Scholar
• Stoyanova R, Nicholson JK, Lindon JC, Brown TR. Sample classification based on Bayesian spectral decomposition of metabonomic NMR data sets. Anal. Chem.76, 3666–3674 (2004).
   Google Scholar
• Stoyanova R, Nicholls AW, Nicholson JK, Lindon JC, Brown TR. Automatic alignment of individual peaks in large high-resolution spectral data sets. J. Magn. Reson.170, 329–335 (2004).
   PubMed Web of Science ®Google Scholar
• Forshed J, Torgrip RJ, Aberg KM, Karlberg B, Lindberg J, Jacobsson SP. A comparison of methods for alignment of NMR peaks in the context of cluster analysis J. Pharm. Biomed. Anal.38, 824–832 (2005).
   PubMed Web of Science ®Google Scholar
• Robinson MD, De Souza DP, Keen WW et al. A dynamic programming approach for the alignment of signal peaks in multiple gas chromatography-mass spectrometry experiments. BMC Bioinformatics8, 419–432 (2007).
   PubMedGoogle Scholar
• Katajamaa M, Oresic M. Processing methods for differential analysis of LC/MS profile data. BMC Bioinformatics6, 179–190 (2005).
   PubMed Web of Science ®Google Scholar
• Le Moyec L, Valensi P, Charniot JC, Hantz E, Albertini JP. Serum 1H nuclear magnetic spectroscopy followed by principal component analysis and hierarchical cluster analysis to demonstrate effects of statins on hyperlipidemic patients. NMR Biomed.18, 421–429 (2005).
   PubMed Web of Science ®Google Scholar
• Barker M, Rayens W. Partial least squares for discrimination. J. Chemom.17, 166–173 (2003).
   Web of Science ®Google Scholar
• Cloarec O, Dumas ME, Craig A et al. Statistical total correlation spectroscopy: an exploratory approach for latent biomarker identification from metabolic 1H NMR data sets. Anal. Chem.77, 1282–1289 (2005).
   PubMed Web of Science ®Google Scholar
• Crockford DJ, Holmes E, Lindon JC et al. Statistical heterospectroscopy, an approach to the integrated analysis of NMR and UPLC-MS data sets: application in metabonomic toxicology studies. Anal. Chem.78(2), 363–371 (2006).
   PubMed Web of Science ®Google Scholar
• Pan Z, Raftery D. Combining NMR spectroscopy and mass spectrometry in metabolomics. Anal. Bioanal. Chem.387, 525–527 (2007).
   PubMed Web of Science ®Google Scholar
• Chen HW, Pan Z, Talaty N, Cooks RG, Raftery D. Combining desorption electrospray ionization mass spectrometry and nuclear magnetic resonance for differential metabolomics without sample preparation. Rapid. Commun. Mass Spectrom.20, 1577–1584 (2006).
   PubMed Web of Science ®Google Scholar
• Sitter B, Lundgren S, Bathen TF, Halgunset J, Fjosne HE, Gribbestad IS. Comparison of HR MAS MR spectroscopic profiles of breast cancer tissue with clinical parameters. NMR Biomed.19, 30–40 (2006).
   PubMed Web of Science ®Google Scholar
• Sitter B, Sonnewald U, Spraul M, Fjösne HE, Gribbestad IS. High-resolution magic angle spinning MRS of breast cancer tissue. NMR Biomed.15, 327–337 (2002).
   PubMed Web of Science ®Google Scholar
• Whitehead TL, Kieber-Emmons T. Applying in vitro NMR spectroscopy and 1H NMR metabonomics to breast cancer characterization and detection. Prog. NMR Spectr.47, 165–174 (2005).
   Google Scholar
• Cheng LL, Chang IW, Smith BL, Gonzalez RG. Evaluating human breast ductal carcinomas with high-resolution magic-angle spinning proton magnetic resonance spectroscopy. J. Magn. Reson.135, 194–202 (1998).
   PubMed Web of Science ®Google Scholar
• Bathen TF, Jensen LR, Sitter B et al. MR-determined metabolic phenotype of breast cancer in prediction of lymphatic spread, grade, and hormone status. Breast Cancer Res. Treat.104, 181–189 (2006).
   Google Scholar
• Yang C, Richardson AD, Smith JW, Osterman A. Comparative metabolomics of breast cancer. Pac. Symp. Biocomput.181–192 (2007).
   Google Scholar
• Phillips M, Cataneo RN, Ditkoff BA et al. Volatile markers of breast cancer in the breath. Breast J.9, 184–191 (2003).
   PubMedGoogle Scholar
• Odunsi K, Wollman RM, Ambrosone CB et al. Detection of epithelial ovarian cancer using H-1-NMR-based metabonomics. Int. J. Cancer113, 782–788 (2005).
   PubMed Web of Science ®Google Scholar
• Denkert C, Budczies J, Kind T et al. Mass spectrometry-based metabolic profiling reveals different metabolite patterns in invasive ovarian carcinomas and ovarian borderline tumors. Cancer Res.66, 10795–10804 (2006).
   PubMed Web of Science ®Google Scholar
• Beger RD, Schnackenberg LK, Holland RD, Li D, Dragan Y. Metabonomic models of human pancreatic cancer using 1D proton NMR spectra of lipids in plasma. Metabolomics2, 125–134 (2006).
   Web of Science ®Google Scholar
• Fang F, He X, Deng H et al. Discrimination of metabolic profiles of pancreatic cancer from chronic pancreatitis by high-resolution magic angle spinning 1H nuclear magnetic resonance and principal components analysis. Cancer Sci.98, 1678–1682 (2007).
   Google Scholar
• Sitter B, Bathen T, Hagen B, Arentz C, Skjeldestad FE, Gribbestad IS. Cervical cancer tissue characterized by high-resolution magic angle spinning MR spectroscopy. MAGMA16, 174–181 (2004).
   Google Scholar
• Lyng H, Sitter B, Bathen TF et al. Metabolic mapping by use of high-resolution magic angle spinning 1H MR spectroscopy for assessment of apoptosis in cervical carcinomas. BMC Cancer7, 11(1–12) (2007).
   Google Scholar
• Phillips M, Gleeson K, Hughes JM et al. Volatile organic compounds in breath as markers of lung cancer: a cross-sectional study. Lancet353, 1930–1933 (1999).
   PubMed Web of Science ®Google Scholar
• Deng C, Li N, Zhang X. Development of headspace solid-phase microextraction with on-fiber derivatization for determination of hexanal and heptanal in human blood. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci.813, 47–52 (2004).
   PubMed Web of Science ®Google Scholar
• Chen X, Xu F, Wang Y et al. A study of the volatile organic compounds exhaled by lung cancer cells in vitro for breath diagnosis. Cancer110, 835–844 (2007).
   PubMed Web of Science ®Google Scholar
• Machado RF, Laskowski D, Deffenderfer O et al. Detection of lung cancer by sensor array analyses of exhaled breath. Am. J. Respir. Crit. Care Med.171, 1286–1291 (2005).
   PubMed Web of Science ®Google Scholar
• Phillips M, Altorki N, Austin JH et al. Prediction of lung cancer using volatile biomarkers in breath. Cancer Biomark.3, 95–109 (2007).
   PubMedGoogle Scholar
• Poli D, Carbognani P, Corradi M et al. Exhaled volatile organic compounds in patients with non-small cell lung cancer: cross sectional and nested short-term follow-up study. Respir. Res.6, 71–80 (2005).
   PubMed Web of Science ®Google Scholar
• Rantalainen M, Cloarec O, Beckonert O et al. Statistically integrated metabonomic-proteomic studies on a human prostate cancer xenograft model in mice. J. Proteome Res.5(10), 2642–2655 (2006).
   PubMed Web of Science ®Google Scholar
• Cheng LL, Wu C, Smith MR, Gonzalez RG. Non-destructive quantitation of spermine in human prostate tissue samples using HRMAS 1H NMR spectroscopy at 9.4 T. FEBS Lett.494(1–2), 112–116 (2001).
   PubMed Web of Science ®Google Scholar
• Swanson MG, Vigneron DB, Tabatabai ZL et al. Proton HR-MAS spectroscopy and quantitative pathologic analysis of MRI/3D-MRSI-targeted postsurgical prostate tissues. Magn. Reson. Med.50(5), 944–954 (2003).
   PubMedGoogle Scholar
• Burns MA, He W, Wu CL, Cheng LL. Quantitative pathology in tissue MR spectroscopy based human prostate metabolomics. Technol. Cancer Res. Treat.3(6), 591–598 (2004).
   Google Scholar
• Cheng LL, Burns MA, Taylor JL et al. Metabolic characterization of human prostate cancer with tissue magnetic resonance spectroscopy. Cancer Res.65(8), 3030–3034 (2005).
   PubMed Web of Science ®Google Scholar
• Swanson MG, Zektzer AS, Tabatabai ZL et al.Quantitative analysis of prostate metabolites using 1H HR-MAS spectroscopy. Magn. Reson. Med.55(6), 1257–1264 (2006).
   PubMed Web of Science ®Google Scholar
• Kline EE, Treat EG, Averna TA et al. Citrate concentrations in human seminal fluid and expressed prostatic fluid determined via 1H nuclear magnetic resonance spectroscopy outperform prostate specific antigen in prostate cancer detection. J. Urol.176(5), 2274–2279 (2006).
   PubMed Web of Science ®Google Scholar
• Serkova NJ, Gamito EJ, Jones RH et al. The metabolites citrate, myo-inositol, and spermine are potential age-independent markers of prostate cancer in human expressed prostatic secretions. Prostate68(6), 620–628 (2008).
   PubMed Web of Science ®Google Scholar
• Moka D, Vorreuther R, Schicha H et al. Biochemical classification of kidney carcinoma biopsy samples using magic-angle-spinning 1H nuclear magnetic resonance spectroscopy. J. Pharm. Biomed. Anal.17, 125–132 (1998).
   Google Scholar
• Tate AR, Foxall PJD, Holmes E et al. Distinction between normal and renal cell carcinoma kidney cortical biopsy samples using pattern recognition of 1H magic angle spinning (MAS) NMR spectra. NMR Biomed.13, 64–71 (2003).
   Google Scholar
• Righi V, Mucci A, Schenetti L et al.Ex vivo HR-MAS magnetic resonance spectroscopy of normal and malignant human renal tissues. Anticancer Res.27, 3195–3204 (2007).
   PubMed Web of Science ®Google Scholar
• Kind T, Tolstikov V, Fiehn O, Weiss RH. A comprehensive urinary metabolomic approach for identifying kidney cancer. Anal. Biochem.363(2), 185–195 (2007).
   PubMed Web of Science ®Google Scholar
• Martínez-Bisbal MC, Martí-Bonmatí L, Piquer J et al.1H and 13C HR-MAS spectroscopy of intact biopsy samples ex vivo and in vivo1H MRS study of human high grade gliomas. NMR Biomed.17, 191–205 (2004).
   PubMed Web of Science ®Google Scholar
• Cheng U, Chang I, Louis DN, Gonzalez RG. Correlation of high-resolution magic angle spinning proton magnetic resonance spectroscopy with histopathology of intact human brain tumor specimens. Cancer Res.58, 1825–1832 (1998).
   PubMed Web of Science ®Google Scholar
• Tzika AA, Cheng LL, Goumnerova L et al. Biochemical characterization of pediatric brain tumors by using in vivo and ex vivo magnetic resonance spectroscopy. J. Neurosurg.96, 1023–1031 (2002).
   PubMedGoogle Scholar
• Tzika AA, Astrakas L, Cao H et al. Combination of high-resolution magic angle spinning proton magnetic resonance spectroscopy and microscale genomics to type brain tumor biopsies. Int. J. Mol. Med.20, 199–208 (2007).
   PubMed Web of Science ®Google Scholar
• Sjøbakk TE, Johansen R, Bathen TF et al. Characterization of brain metastases using high-resolution magic angle spinning MRS. NMR Biomed.21(2), 175–185 (2008).
   Google Scholar
• Valonen PK, Griffin JL, Lehtimäki KK et al. High-resolution magic-angle-spinning 1H NMR spectroscopy reveals different responses in choline-containing metabolites upon gene therapy-induced programmed cell death in rat brain glioma. NMR Biomed.18, 252–259 (2005).
   Google Scholar
• Horszty?ski D, Wawer I, Grieb P. A study of lyophylized human brain tumor tissue using MAS 1H-MRS spectroscopy. Neurol. Neurochir. Pol.37, 123–132 (2003).
   Google Scholar
• Barton SJ, Howe FA, Tomlins AM et al. Comparison of in vivo1H MRS of human brain tumours with 1H HR-MAS spectroscopy of intact biopsy samples in vitro.MAGMA8, 121–128 (1999).
   Google Scholar
• Griffin JL, Kauppinen RA. A metabolomics perspective of human brain tumours. FEBS J.2741132–1139 (2007).
   PubMed Web of Science ®Google Scholar
• Zuppi C, Messana I, Tapanainen P et al. Proton nuclear magnetic resonance spectral profiles of urine from children and adolescents with type 1 diabetes. Clin. Chem.48, 660–662 (2002).
   PubMed Web of Science ®Google Scholar
• Messana I, Forni F, Ferrari F, Rossi C, Giardina B, Zuppi C. Proton nuclear magnetic resonance spectral profiles of urine in Type II diabetic patients. Clin. Chem.44, 1529–1534 (1998).
   PubMed Web of Science ®Google Scholar
• Salek RM, Maguire ML, Bentley E et al.A metabolomic comparison of urinary changes in type 2 diabetes in mouse, rat, and human. Physiol. Genomics29, 99–108 (2007).
   PubMed Web of Science ®Google Scholar
• Zhang S, Nagana Gowda GA, Asiago V et al. Correlative and quantitative 1H NMR-based metabolomics reveals specific metabolic pathway disturbances in diabetic rats. Anal. Biochem. (2008) (In press).
   Google Scholar
• Toye A, Gauguier D. Genetics and functional genomics of Type 2 diabetes mellitus. Genome Biol.4, 241 (2003).
   PubMedGoogle Scholar
• Dumas ME, Barton RH, Toye A et al. Metabolic profiling reveals a contribution of gut microbiota to fatty liver phenotype in insulin-resistant mice. Proc. Natl Acad. Sci. USA103, 12511–12516 (2006).
   PubMed Web of Science ®Google Scholar
• Makinen VP, Soininen P, Forsblom C et al. Diagnosing diabetic nephropathy by 1H NMR metabonomics of serum. MAGMA19, 281–296 (2006).
   Google Scholar
• Hodavance MS, Ralston SL, Pelczer I. Beyond blood sugar: the potential of NMR-based metabonomics for Type 2 human diabetes, and the horse as a possible model. Anal. Bioanal. Chem.387, 533–537 (2007).
   Google Scholar
• Shulman GI, Rothman DL, Shulman RG, Brindle K. 13C NMR-studies of glucose disposal in normal and non-insulin-dependent diabetic humans. Philos. Trans. Phys. Sci. Eng.333, 525–529 (1990).
   Google Scholar
• Cline GW, Magnusson I, Rothman DL, Petersen KF, Laurent D, Shulman GI. Mechanism of impaired insulin-stimulated muscle glucose metabolism in subjects with insulin-dependent diabetes mellitus. J. Clin. Invest.99, 2219–2224 (1997).
   Google Scholar
• Roden M, Shulman GI. Applications of NMR spectroscopy to study muscle glycogen metabolism in man. Annu. Rev. Med.50, 277–290 (1999).
   PubMed Web of Science ®Google Scholar
• Boden G, Shulman GI. Free fatty acids in obesity and Type 2 diabetes: defining their role in the development of insulin resistance and β-cell dysfunction. Eur. J. Clin. Invest.32, 14–23 (2002).
   PubMed Web of Science ®Google Scholar
• Roden M, Price TB, Perseghin G et al. Mechanism of free fatty acid-induced insulin resistance in humans. J. Clin. Invest.97, 2859–2865 (1996).
   PubMed Web of Science ®Google Scholar
• Wang C, Kong HW, Guan YF et al. Plasma phospholipid metabolic profiling and biomarkers of Type 2 diabetes mellitus based on high-performance liquid chromatography/electrospray mass spectrometry and multivariate statistical analysis. Anal. Chem.77, 4108–4116 (2005).
   PubMed Web of Science ®Google Scholar
• Plumb RS, Johnson KA, Rainville P et al. The detection of phenotypic differences in the metabolic plasma profile of three strains of Zucker rats at 20 weeks of age using ultra-performance liquid chromatography/orthogonal acceleration time-of-flight mass spectrometry. Rapid Commun. Mass Spec.20, 2800–2806 (2006).
   Google Scholar
• Major HJ, Williams R, Wilson AJ, Wilson ID. A metabonomic analysis of plasma from Zucker rat strains using gas chromatography/mass spectrometry and pattern recognition. Rapid Commun. Mass Spec.20, 3295–3302 (2006).
   PubMedGoogle Scholar
• Yi LZ, He J, Liang YZ, Yuan DL, Chau FT. Plasma fatty acid metabolic profiling and biomarkers of type 2 diabetes mellitus based on GCMS and PLS-LDA. Febs Lett.580, 6837–6845 (2006).
   PubMed Web of Science ®Google Scholar
• Newgard CB, Stedman SW. Metabolic profiling for understanding of diabetes and obesity mechanisms. FASEB J.20, A1307–A1307 (2006).
   Google Scholar
• Williams R, Lenz EM, Wilson AJ et al. A multi-analytical platform approach to the metabonomic analysis of plasma from normal and zucker (fa/fa) obese rats. Mol. Biosyst.2, 174–183 (2006).
   Google Scholar
• Atherton HJ, Bailey NJ, Zhang W et al. A combined H-1-NMR spectroscopy- and mass spectrometry-based metabolomic study of the PPAR-α null mutant mouse defines profound systemic changes in metabolism linked to the metabolic syndrome. Physiol. Genomics27, 178–186 (2006).
   PubMed Web of Science ®Google Scholar
• Jones PM, Bennett MJ. The changing face of newborn screening: diagnosis of inborn errors of metabolism by tandem mass spectrometry. Clin. Chim. Acta324, 121–128 (2002).
   PubMed Web of Science ®Google Scholar
• Engelke UFH, Liebrand-van Sambeek MLF, DeJong JGN et al. N-acetylated metabolites in urine: proton nuclear magnetic resonance spectroscopic study on patients with inborn errors of metabolism. Clin. Chem.50, 58–66 (2004).
   Google Scholar
• Moolenaar SH, Engelke UFH, Wevers RA. Proton nuclear magnetic resonance spectroscopy of body fluids in the field of inborn errors of metabolism. Ann. Clin. Biochem.40, 16–24 (2003).
   PubMedGoogle Scholar
• Iles RA, Hind AJ, Chalmers RA. Use of proton nuclear magnetic resonance spectroscopy in detection and study of organic acidurias. Clin. Chem.31, 1795–1801 (1985).
   PubMed Web of Science ®Google Scholar
• Constantinou MA, Papakonstantinou E, Benaki D et al. Application of nuclear magnetic resonance spectroscopy combined with principal component analysis in detecting inborn errors of metabolism using blood spots: a metabonomic approach. Anal. Chim. Acta511, 303–312 (2004).
   Web of Science ®Google Scholar
• Constantinou MA, Papakonstantinou E, Spraul M et al.1H NMR-based metabonomics for the diagnosis of inborn errors of metabolism in urine. Anal. Chim. Acta542, 169–177 (2005).
   Google Scholar
• Pan Z, Gu H, Talaty N et al. Principal component analysis of urine metabolites detected by NMR and DESI–MS in patients with inborn errors of metabolism. Anal. Bioanal. Chem.387, 539–549 (2007).
   PubMed Web of Science ®Google Scholar
• Engelke UFH, Oostendorp M, Wevers RA. NMR spectroscopy of body fluids as a metabolomics approach to inborn errors of metabolism. In: The Handbook of Metabonomics and Metabolomics. Lindon JC, Nicholson JK, Holmes E (Eds). Elsevier Science 375–412 (2007).
   Google Scholar
• Otvos JD, Jeyarajah EJ, Bennett DW. Quantification of plasma lipoproteins by proton nuclear magnetic resonance spectroscopy. Clin. Chem.37, 377–386 (1991).
   PubMed Web of Science ®Google Scholar
• Kuller L, Arnold A, Tracy R et al. Nuclear magnetic resonance spectroscopy of lipoproteins and risk of coronary heart disease in the cardiovascular health study. Arterioscler. Thromb. Vasc. Biol.22, 1175–1180 (2002).
   PubMed Web of Science ®Google Scholar
• Brindle JT, Antti H, Holmes E et al. Rapid and noninvasive diagnosis of the presence and severity of coronary heart disease using 1H-NMR based metabonomics. Nat. Med.8, 1439–1444 (2002).
   PubMed Web of Science ®Google Scholar
• Brindle JT, Nicholson JK, Schofield PM, Grainger DJ, Holmes E. Application of chemometrics to 1H NMR spectroscopic data to investigate a relationship between human serum metabolic profiles and hypertension. Analyst128, 32–36 (2003).
   PubMed Web of Science ®Google Scholar
• Kirschenlohr HL, Griffin JL, Clarke SC et al. Proton NMR analysis of plasma is a weak predictor of coronary artery disease. Nat. Med.12, 705–710 (2006).
   PubMed Web of Science ®Google Scholar
• Ala-Korpela M. Critical evaluation of 1H NMR metabonomics of serum as a methodology for disease risk assessment and diagnostics. Clin. Chem. Lab. Med.46(1), 27–42 (2008).
   PubMed Web of Science ®Google Scholar