, Centre de RMN à très hauts champs, p.69100

F. Villeurbanne, International Agency for Research on Cancer (IARC-WHO), Lyon, France. 3 Department of Epidemiology, Rollins School of Public Health

, DK 2100 Copenhagen, Denmark. 8 INSERM, Centre for Research in Epidemiology and Population Health (CESP), U1018, Nutrition, Hormones and Women's Health Team, F-94805 Villejuif, UMRS 1018, F-94805 Villejuif, France. 10 Institut Gustave Roussy, F-94805 Villejuif, France. 11 Human Genetics Foundation (HuGeF), vol.23, p.27

G. Athens, 16 Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Via Venezian 1, p.17, 20133.

D. Di-medicina-clinica-e-chirurgia and F. P. Arezzo, 19 MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK. 20 Department for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), 23 Department of Social & Preventive Medicine, Faculty of Medicine, p.27

, 34 Public Health Direction and Biodonostia CIBERESP, Basque Regional Health Department, Granada, Spain. 31 CIBER Epidemiología y Salud Pública (CIBERESP), vol.33

, 37 Department of Clinical Sciences, Division of Internal Medicine

J. Ferlay, I. Soerjomataram, M. Ervik, R. Dikshit, S. Eser et al., Cancer Incidence and Mortality Worldwide, 2012.

H. B. El-serag, Hepatocellular carcinoma, N Engl J Med, vol.365, pp.1118-1145, 2011.

Y. Chen, X. Wang, J. Wang, Z. Yan, and J. Luo, Excess body weight and the risk of primary liver cancer: an updated meta-analysis of prospective studies, Eur J Cancer, vol.48, pp.2137-2182, 2012.

S. C. Chuang, L. Vecchia, C. Boffetta, and P. , Liver cancer: descriptive epidemiology and risk factors other than HBV and HCV infection, Cancer Lett, vol.286, pp.9-14, 2009.

P. Wang, D. Kang, W. Cao, Y. Wang, and Z. Liu, Diabetes mellitus and risk of hepatocellular carcinoma: a systematic review and meta-analysis, Diabetes Metab Res Rev, vol.28, pp.109-131, 2012.

J. M. Llovet, A. Burroughs, J. Bruix, and . Hepatocellular, Lancet, vol.362, pp.1907-1924, 2003.

J. K. Nicholson, J. C. Lindon, and E. Holmes, Metabonomics': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data, Xenobiotica, vol.29, pp.1181-1190, 1999.

J. K. Nicholson, E. Holmes, J. M. Kinross, A. W. Darzi, Z. Takats et al., Metabolic phenotyping in clinical and surgical environments, Nature, vol.491, pp.384-92, 2012.

A. Floegel, N. Stefan, Z. Yu, K. Muhlenbruch, D. Drogan et al., Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach, Diabetes, vol.62, pp.639-687, 2013.

J. L. Griffin, H. Atherton, J. Shockor, and L. Atzori, Metabolomics as a tool for cardiac research, Nat Rev Cardiol, vol.8, pp.630-673, 2011.

J. L. Griffin and J. P. Shockcor, Metabolic profiles of cancer cells, Nat Rev Cancer, vol.4, pp.551-61, 2004.

J. R. Mayers, C. Wu, C. B. Clish, P. Kraft, M. E. Torrence et al., Elevation of circulating branched-chain amino acids is an early event in human pancreatic adenocarcinoma development, Nat Med, vol.20, pp.1193-1201, 2014.

S. H. Shah, J. L. Sun, R. D. Stevens, J. R. Bain, M. J. Muehlbauer et al., Baseline metabolomic profiles predict cardiovascular events in patients at risk for coronary artery disease, Am Heart J, vol.163, pp.844-50, 2012.

J. L. Spratlin, N. J. Serkova, and S. G. Eckhardt, Clinical applications of metabolomics in oncology: a review, Clin Cancer Res, vol.15, pp.431-471, 2009.

T. J. Wang, M. G. Larson, R. S. Vasan, S. Cheng, E. P. Rhee et al., Metabolite profiles and the risk of developing diabetes, Nat Med, vol.17, pp.448-53, 2011.

D. Beyoglu, S. Imbeaud, O. Maurhofer, P. Bioulac-sage, J. Zucman-rossi et al., Tissue metabolomics of hepatocellular carcinoma: tumor energy metabolism and the role of transcriptomic classification, Hepatology, vol.58, pp.229-267, 2013.

J. Bowers, E. Hughes, N. Skill, M. Maluccio, and D. Raftery, Detection of hepatocellular carcinoma in hepatitis C patients: biomarker discovery by LC-MS, J Chromatogr B, vol.966, pp.154-62, 2014.

J. Chen, W. Z. Wang, S. Lv, P. Y. Yin, X. J. Zhao et al., Metabonomics study of liver cancer based on ultra performance liquid chromatography coupled to mass spectrometry with HILIC and RPLC separations, Anal Chim Acta, vol.650, pp.3-9, 2009.

A. N. Da-costa, C. Pontoizeau, A. Plymoth, D. Santos-silva, M. Mendy et al., A multi-marker approach for early detection of HBV-related hepatocellular carcinoma in areas of high incidence, Eur J Cancer, vol.48, pp.169-70, 2012.

H. C. Gao, Q. Lu, X. Liu, H. Cong, L. C. Zhao et al., Application of H-1 NMR-based metabonomics in the study of metabolic profiling of human hepatocellular carcinoma and liver cirrhosis, Cancer Sci, vol.100, pp.782-787, 2009.

Q. Huang, Y. X. Tan, P. Y. Yin, G. Z. Ye, P. Gao et al., Metabolic characterization of hepatocellular carcinoma using nontargeted tissue metabolomics, Cancer Res, vol.73, pp.4992-5002, 2013.

S. Y. Liu, R. L. Zhang, H. Kang, Z. J. Fan, and Z. Du, Human liver tissue metabolic profiling research on hepatitis B virus-related hepatocellular carcinoma, World J Gastroenterol, vol.19, pp.3423-3455, 2013.

Y. Liu, Z. Hong, G. Tan, X. Dong, G. Yang et al., NMR and LC/MS-based global metabolomics to identify serum biomarkers differentiating hepatocellular carcinoma from liver cirrhosis, Int J Cancer, vol.135, pp.658-68, 2014.

P. Nahon, R. Amathieu, M. N. Triba, N. Bouchemal, J. C. Nault et al., Identification of serum proton NMR metabolomic fingerprints associated with hepatocellular carcinoma in patients with alcoholic cirrhosis, Clin Cancer Res, vol.18, pp.6714-6736, 2012.

A. D. Patterson, O. Maurhofer, D. Beyoglu, C. Lanz, K. W. Krausz et al., Aberrant lipid metabolism in hepatocellular carcinoma revealed by plasma metabolomics and lipid profiling, Cancer Res, vol.71, pp.6590-600, 2011.

H. W. Ressom, J. F. Xiao, L. Tuli, R. S. Varghese, B. Zhou et al., Utilization of metabolomics to identify serum biomarkers for hepatocellular carcinoma in patients with liver cirrhosis, Anal Chim Acta, vol.743, pp.90-100, 2012.

T. Soga, M. Sugimoto, M. Honma, M. Mori, K. Igarashi et al., Serum metabolomics reveals gamma-glutamyl dipeptides as biomarkers for discrimination among different forms of liver disease, J Hepatology, vol.55, pp.896-905, 2011.

Y. X. Tan, P. Y. Yin, L. Tang, W. B. Xing, Q. Huang et al., Metabolomics study of stepwise hepatocarcinogenesis from the model rats to patients: potential biomarkers effective for small hepatocellular carcinoma diagnosis, Mol Cell Proteomics, vol.11, 2012.

H. Wu, R. Y. Xue, L. Dong, T. T. Liu, C. H. Deng et al., Metabolomic profiling of human urine in hepatocellular carcinoma patients using gas chromatography/mass spectrometry, Anal Chim Acta, vol.648, pp.98-104, 2009.

J. F. Xiao, R. S. Varghese, B. Zhou, M. Ranjbar, Y. Zhao et al., LC-MS based serum metabolomics for identification of hepatocellular carcinoma biomarkers in Egyptian cohort, J Proteome Res, vol.11, pp.5914-5937, 2012.

L. N. Zhou, Q. C. Wang, P. Y. Yin, W. B. Xing, Z. M. Wu et al., Serum metabolomics reveals the deregulation of fatty acids metabolism in hepatocellular carcinoma and chronic liver diseases, Anal Bioanal Chem, vol.403, pp.203-216, 2012.

V. Fedirko, T. Duarte-salles, C. Bamia, A. Trichopoulou, K. Aleksandrova et al., Prediagnostic circulating vitamin D levels and risk of hepatocellular carcinoma in European populations: a nested case-control study, Hepatology, vol.60, pp.1222-1252, 2014.

G. Y. Lai, S. J. Weinstein, D. Albanes, P. R. Taylor, J. Virtamo et al., Association of serum alpha-tocopherol, beta-carotene, and retinol with liver cancer incidence and chronic liver disease mortality, Br J Cancer, vol.111, pp.2163-71, 2014.

A. Lukanova, S. Becker, A. Husing, H. Schock, V. Fedirko et al., Prediagnostic plasma testosterone, sex hormone-binding globulin, IGF-I and hepatocellular carcinoma: etiological factors or risk markers?, Int J Cancer, vol.134, pp.164-73, 2013.

E. Riboli, K. J. Hunt, N. Slimani, P. Ferrari, T. Norat et al., European prospective investigation into cancer and nutrition (EPIC): study populations and data collection, Public Health Nutr, vol.5, pp.1113-1137, 2002.

D. Trichopoulos, C. Bamia, P. Lagiou, V. Fedirko, E. Trepo et al., Hepatocellular carcinoma risk factors and disease burden in a European cohort: a nested case-control study, J Natl Cancer Inst, vol.103, pp.1686-95, 2011.

V. Fedirko, A. Trichopolou, C. Bamia, T. Duarte-salles, E. Trepo et al., Consumption of fish and meats and risk of hepatocellular carcinoma: the European Prospective Investigation into Cancer and Nutrition (EPIC)

, Ann Oncol, vol.24, pp.2166-73, 2013.

O. Beckonert, H. C. Keun, T. Ebbels, J. G. Bundy, E. Holmes et al., Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts, Nat Protoc, vol.2, pp.2692-703, 2007.

D. S. Wishart, C. Knox, A. C. Guo, R. Eisner, N. Young et al., HMDB: a knowledgebase for the human metabolome, Nucleic Acids Res, vol.37, pp.603-613, 2009.

Q. Cui, I. A. Lewis, A. D. Hegeman, M. E. Anderson, J. Li et al., Metabolite identification via the Madison Metabolomics Consortium Database, Nat Biotechnol, vol.26, pp.162-166, 2008.

J. Trygg and S. Wold, Orthogonal projections to latent structures (O-PLS), J Chemometrics, vol.16, pp.119-147, 2002.

P. I. Good, Permutation tests: a practical guide to resampling methods for testing hypotheses, 2000.

B. J. Blaise, L. Shintu, B. Elena, L. Emsley, M. E. Dumas et al., Statistical recoupling prior to significance testing in nuclear magnetic resonance based metabonomics, Anal Chem, vol.81, pp.6242-51, 2009.

Y. Benjamini and Y. Hochberg, Controlling the false discovery rate -a practical and powerful approach to multiple testing, J R Stat Soc Ser B, vol.57, pp.289-300, 1995.

A. Fages, P. Ferrari, S. Monni, L. Dossus, A. Floegel et al., Investigating sources of variability in metabolomic data in the EPIC study: the principal component partial R-square (PC-PR2) method, Metabolomics, vol.10, pp.1074-83, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00977571

. R-core-team, R: A language and environment for statistical computing. R Foundation for Statistical Computing, 2013.

A. K. Ghoshal and E. Farber, Choline deficiency, lipotrope deficiency and the development of liver disease including liver cancer: a new perspective, Lab Invest, vol.68, pp.255-60, 1993.

D. Haussinger, Regulation of hepatic ammonia metabolism: the intercellular glutamine cycle, Adv Enzyme Regul, vol.25, pp.159-80, 1986.

I. P. Pogribny, S. J. James, and F. A. Beland, Molecular alterations in hepatocarcinogenesis induced by dietary methyl deficiency, Mol Nutr Food Res, vol.56, pp.116-141, 2012.

M. Watford, Glutamine and glutamate metabolism across the liver sinusoid, J Nutr, vol.130, pp.983-990, 2000.

N. Psychogios, D. D. Hau, J. Peng, A. C. Guo, R. Mandal et al., The human serum metabolome, PLoS One, vol.6, p.16957, 2011.

T. Zar, C. Graeber, and M. A. Perazella, Recognition, treatment, and prevention of propylene glycol toxicity, Semin Dial, vol.20, pp.217-226, 2007.

D. Beyofülu and J. R. Idle, The metabolomic window into hepatobiliary disease, J Hepatol, vol.59, pp.842-58, 2013.

J. Barr, J. Caballeria, I. Martinez-arranz, A. Dominguez-diez, C. Alonso et al., Obesity-dependent metabolic signatures associated with nonalcoholic fatty liver disease progression, J Proteome Res, vol.11, pp.2521-2553, 2012.

J. Barr, M. Vazquez-chantada, C. Alonso, M. Perez-cormenzana, R. Mayo et al., Liquid chromatography-mass spectrometry-based parallel metabolic profiling of human and mouse model serum reveals putative biomarkers associated with the progression of nonalcoholic fatty liver disease, J Proteome Res, vol.9, pp.4501-4513, 2010.

N. Tanaka, T. Matsubara, K. W. Krausz, A. D. Patterson, and F. J. Gonzalez, Disruption of phospholipid and bile acid homeostasis in mice with nonalcoholic steatohepatitis, Hepatology, vol.56, pp.118-147, 2012.

S. W. Qi, Z. G. Tu, W. J. Peng, L. X. Wang, X. Ou-yang et al., )H NMR-based serum metabolic profiling in compensated and decompensated cirrhosis, World J Gastroenterol, vol.18, issue.1, pp.285-90, 2012.

X. Lin, Y. Zhang, G. Ye, X. Li, P. Yin et al., Classification and differential metabolite discovery of liver diseases based on plasma metabolic profiling and support vector machines, J Sep Sci, vol.34, pp.3029-3065, 2011.