B. Van-ommen, J. Van-der-greef, J. M. Ordovas, and H. Daniel, Phenotypic flexibility as key factor in the human nutrition and health relationship, Genes Nutr, vol.9, p.423, 2014.

A. Tremblay, A. Nadeau, J. P. Despres, and C. Bouchard, Hyperinsulinemia and regulation of energy balance, Am. J. Clin. Nutr, vol.61, pp.827-830, 1995.

S. Polakof, D. Remond, A. Bernalier-donadille, M. Rambeau, E. Pujos-guillot et al., Savary-Auzeloux, I. Metabolic adaptations to HFHS overfeeding: How whole body and tissues postprandial metabolic flexibility adapt in Yucatan mini-pigs, Eur. J. Nutr, vol.57, pp.119-135, 2018.

I. Savary-auzeloux, A. Mohamed, B. Cohade, D. Dardevet, J. David et al., Profound changes in net energy and nitrogen metabolites fluxes within the splanchnic area during overfeeding of Yucatan mini pigs that remain euglycemic, Nutrients, p.434, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02050118

S. Polakof, D. Remond, J. David, and D. Dardevet, Savary-Auzeloux, I. Time-course changes in circulating branched-chain amino acid levels and metabolism in obese Yucatan minipig, Nutrition, vol.50, pp.66-73, 2018.

Y. C. Zeng, J. David, D. Remond, D. Dardevet, I. Savary-auzeloux et al., Peripheral blood mononuclear cell metabolism acutely adapted to postprandial transition and mainly reflected metabolic adipose tissue adaptations to a high-fat diet in minipigs, Nutrients, vol.10, 1816.
URL : https://hal.archives-ouvertes.fr/hal-01938701

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.384-392, 2012.

J. Sébédio and S. Polakof, Using metabolomics to identify biomarkers for metabolic diseases: Analytical methods and applications, Metabolomics as a Tool in Nutrition Research, pp.145-166, 2015.

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.448-453, 2011.

F. Xu, S. Tavintharan, C. F. Sum, K. Woon, S. C. Lim et al., Metabolic signature shift in type 2 diabetes mellitus revealed by mass spectrometry-based metabolomics, J. Clin. Endocrinol. Metab, vol.98, pp.1060-1065, 2013.

S. Polakof, D. Dardevet, B. Lyan, L. Mosoni, E. Gatineau et al., Time course of molecular and metabolic events in the development of insulin resistance in fructose-fed rats, J. Proteome Res, vol.15, pp.1862-1874, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01540177

S. Polakof, D. Rémond, M. Rambeau, E. Pujos-guillot, J. Sébédio et al., Savary-Auzeloux, I. Postprandial metabolic events in mini-pigs: New insights from a combined approach using plasma metabolomics, tissue gene expression, and enzyme activity, Metabolomics, vol.11, pp.964-979, 2015.

G. Pimentel, K. J. Burton, F. P. Pralong, N. Vionnet, R. Portmann et al., The postprandial metabolome-A source of Nutritional Biomarkers of Health, Curr. Opin. Food Sci, vol.16, pp.67-73, 2017.

J. Fiamoncini, M. Rundle, H. Gibbons, E. L. Thomas, K. Geillinger-kästle et al., Plasma metabolome analysis identifies distinct human metabotypes in the postprandial state with different susceptibility to weight loss-mediated metabolic improvements, FASEB J, vol.32, pp.5447-5458, 2018.

L. Pellis, M. J. Van-erk, B. Van-ommen, G. C. Bakker, H. F. Hendriks et al., Plasma metabolomics and proteomics profiling after a postprandial challenge reveal subtle diet effects on human metabolic status, Metabolomics, vol.8, pp.347-359, 2012.

F. Baig, R. Pechlaner, and M. Mayr, Caveats of untargeted metabolomics for biomarker discovery, J. Am. Coll. Cardiol, vol.68, pp.1294-1296, 2016.

C. H. Johnson, J. Ivanisevic, and G. Siuzdak, Metabolomics: Beyond biomarkers and towards mechanisms, Nat. Rev. Mol. Cell Biol, vol.17, p.451, 2016.

C. Jang, S. Hui, X. Zeng, A. J. Cowan, L. Wang et al., Metabolite exchange between mammalian organs quantified in pigs, Cell Metab, vol.30, pp.594-606, 2019.

N. Poupin, M. Tremblay-franco, A. Amiel, C. Canlet, D. Rémond et al., Arterio-venous metabolomics exploration reveals major changes across liver and intestine in the obese Yucatan minipig, Sci. Rep, vol.9, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02282295

A. F. Kardinaal, M. J. Erk, A. E. Dutman, J. H. Stroeve, E. V. Steeg et al., Quantifying phenotypic flexibility as the response to a high-fat challenge test in different states of metabolic health, FASEB J, vol.29, pp.4600-4613, 2015.

Y. Benjamini and Y. Hochberg, Controlling the false discovery rate: A practical and powerful approach to multiple testing, J. Roy. Stat. Soc. Ser. B. (Stat. Method.), pp.289-300, 1995.

B. Liquet, K. L. Cao, H. Hocini, and R. Thiébaut, A novel approach for biomarker selection and the integration of repeated measures experiments from two assays, BMC Bioinform, vol.13, 2012.
URL : https://hal.archives-ouvertes.fr/inserm-00814235

,. Lê-cao, S. Boitard, and P. Besse, Sparse PLS discriminant analysis: Biologically relevant feature selection and graphical displays for multiclass problems, BMC Bioinform, vol.12, pp.253-269, 2011.

F. Rohart, B. Gautier, A. Singh, and K. Lê-cao, mixOmics: An R package for 'omics feature selection and multiple data integration, PLoS Comp. Biol, vol.13, 2017.

M. L. Katz and E. N. Bergman, Simultaneous measurements of hepatic and portal venous blood flow in the sheep and dog, Am. J. Physiol, vol.216, pp.946-952, 1969.

Z. Pang, J. Chong, S. Li, and J. Xia, MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics, vol.10, 2020.

S. M. Secor, Specific dynamic action: A review of the postprandial metabolic response, J. Comp. Physiol. B, vol.179, pp.1-56, 2009.

E. Fechner, L. Bilet, H. P. Peters, H. Hiemstra, D. M. Jacobs et al., Effects of a whole diet approach on metabolic flexibility, insulin sensitivity and postprandial glucose responses in overweight and obese adults-A randomized controlled trial, Clin. Nutr, 2019.

M. Serino, E. Luche, S. Gres, A. Baylac, M. Bergé et al., Metabolic adaptation to a high-fat diet is associated with a change in the gut microbiota, Gut, vol.61, pp.543-553, 2012.
URL : https://hal.archives-ouvertes.fr/inserm-00726182

F. Wang, F. Liu, H. Cai, L. Yang, and G. Sun, The efficacy of high fat load liquid meal on postprandial insulin level in postprandial insulin resistance population, FASEB J, vol.30, 2016.

D. Vegt, F. Dekker, J. M. Ruhé, H. G. Stehouwer, C. D. Nijpels et al., Hyperglycaemia is associated with all-cause and cardiovascular mortality in the Hoorn population: The Hoorn Study, Diabetologia, vol.42, pp.926-931, 1999.

L. Hu, N. B. Kristensen, L. Che, and . Wu,

P. K. Theil, Net absorption and liver metabolism of amino acids and heat production of portal-drained viscera and liver in multiparous sows during transition and lactation, J. Anim. Sci. Biotechnol, vol.11, issue.5, 2020.

S. P. Kim, M. Ellmerer, G. W. Van-citters, and R. N. Bergman, Primacy of hepatic insulin resistance in the development of the metabolic syndrome induced by an isocaloric moderate-fat diet in the dog, Diabetes, vol.52, pp.2453-2460, 2003.

A. Gastaldelli, K. Cusi, M. Pettiti, J. Hardies, Y. Miyazaki et al., Relationship between hepatic/visceral fat and hepatic insulin resistance in nondiabetic and type 2 diabetic subjects, Gastroenterology, vol.133, pp.496-506, 2007.

T. Hyotylainen, L. Jerby, E. M. Petaja, I. Mattila, S. Jantti et al., Genome-scale study reveals reduced metabolic adaptability in patients with non-alcoholic fatty liver disease, Nat. Commun, vol.7, pp.1-9, 2016.

A. Giusi-perier, M. Fiszlewicz, and A. Rerat, Influence of diet composition on intestinal volatile fatty acid and nutrient absorption in unanesthetized pigs, J. Anim. Sci, vol.67, pp.386-402, 1989.
URL : https://hal.archives-ouvertes.fr/hal-02725332

K. E. Bach-knudsen, H. Jorgensen, and N. Canibe, Quantification of the absorption of nutrients derived from carbohydrate assimilation: Model experiment with catheterised pigs fed on wheat-or oat-based rolls, Br. J. Nutr, vol.84, pp.449-458, 2000.

T. Hiyoshi, M. Fujiwara, and Z. Yao, Postprandial hyperglycemia and postprandial hypertriglyceridemia in type 2 diabetes, J. Biomed. Res, 2017.

D. W. Foster, Banting lecture 1984. From glycogen to ketones: And back, Diabetes, vol.33, pp.1188-1199, 1984.

D. Azzout-marniche, C. Gaudichon, C. Blouet, C. Bos, V. Mathe et al., Liver glyconeogenesis: A pathway to cope with postprandial amino acid excess in high-protein fed rats?, Am. J. Physiol. Regul. Integr. Comp. Physiol, vol.292, pp.1400-1407, 2007.
URL : https://hal.archives-ouvertes.fr/hal-01611429

A. A. Toye, M. E. Dumas, C. Blancher, A. R. Rothwell, J. F. Fearnside et al., Subtle metabolic and liver gene transcriptional changes underlie diet-induced fatty liver susceptibility in insulin-resistant mice, Diabetologia, vol.50, pp.1867-1879, 2007.

R. B. Bazotte, L. G. Silva, and F. P. Schiavon, Insulin resistance in the liver: Deficiency or excess of insulin?, Cell Cycle, vol.13, pp.2494-2500, 2014.

A. B. Mohamed, D. Remond, C. Chambon, T. Sayd, M. Hebraud et al., A mix of dietary fermentable fibers improves lipids handling by the liver of overfed minipigs, J. Nutr. Biochem, vol.65, pp.72-82, 2018.
URL : https://hal.archives-ouvertes.fr/hal-02101573

M. Pietzke, J. Meiser, and A. Vazquez, Formate metabolism in health and disease, vol.33, pp.23-37

M. Pietzke, S. F. Arroyo, D. Sumpton, G. M. Mackay, B. Martin-castillo et al., METTEN Study Group. Stratification of cancer and diabetes based on circulating levels of formate and glucose, Cancer Metab, vol.7, issue.3, 2019.

J. E. Ho, M. G. Larson, A. Ghorbani, S. Cheng, M. H. Chen et al., Metabolomic profiles of body mass index in the Framingham Heart Study reveal distinct cardiometabolic phenotypes, PLoS ONE, vol.11, 2016.

B. L. Costallat, L. Miglioli, P. A. Silva, N. F. Novo, and J. L. Duarte, Resistência à insulina com a suplementação de creatina em animais de experimentação. Revista Brasileira Medicina Esporte, vol.13, pp.22-26, 2007.

A. Alves, A. Bassot, A. L. Bulteau, L. Pirola, and B. Morio, Glycine Metabolism and Its Alterations in Obesity and Metabolic Diseases, Nutrients, vol.11, 1356.
URL : https://hal.archives-ouvertes.fr/hal-02195312

J. Hsieh, A. A. Hayashi, J. Webb, and K. Adeli, Postprandial dyslipidemia in insulin resistance: Mechanisms and role of intestinal insulin sensitivity, Atheroscler. Suppl, vol.9, pp.7-13, 2008.

A. Veilleux, S. Mayeur, J. C. Berube, J. F. Beaulieu, E. Tremblay et al., Altered intestinal functions and increased local inflammation in insulin-resistant obese subjects: A gene-expression profile analysis, BMC Gastroenterol, vol.15, pp.1-12, 2015.

T. Barber, J. R. Vina, J. Vina, and J. Cabo, Decreased urea synthesis in cafeteria-diet-induced obesity in the rat, Biochem. J, vol.230, pp.675-681, 1985.

C. J. Lynch and S. H. Adams, Branched-chain amino acids in metabolic signalling and insulin resistance, Nat. Rev. Endocrinol, vol.10, pp.723-736, 2014.

A. C. Shin, M. Fasshauer, N. Filatova, L. A. Grundell, E. Zielinski et al., Brain insulin lowers circulating BCAA levels by inducing hepatic BCAA catabolism, Cell Metab, vol.20, pp.898-909, 2014.

H. Zhao, F. Zhang, D. Sun, X. Wang, X. Zhang et al., Branched-chain amino acids exacerbate obesity-related hepatic glucose and lipid metabolic disorders via attenuating Akt2 signaling, Diabetes, vol.69, pp.1164-1177, 2020.