Metabolomics: An Emerging Tool for Precision Medicine
Abstract
BACKGROUND: Metabolomics is a developed technology that comprehensively analyzes the metabolites in biological specimens. It appears to be a prospective method in the practice of precision medicine.
CONTENT: Metabolomic technologies currently surpass beyond the traditional clinical chemistry techniques. Metabolomic is capable to perform a precise analysis for hundreds to thousands of metabolites, therefore provide a detailed characterization of metabolic phenotypes and metabolic derangements that underlie disease, to represent an individual’s overall health status, furthermore to discover new precise therapeutic targets, and discovery of biomarkers, either for diagnosis or therapy monitoring purpose.
SUMMARY: Adequate data processing and quantification methods are still needed to be developed to boost integrated -omics as a powerful clinical practice platform.
KEYWORDS: metabolomic, precision medicine, phenotyping, biomarker, nutritional pattern
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Beger RD, Dunn W, Schmidt MA, Gross SS, Kirwan JA, Cascante M, et al. Metabolomics enables precision medicine: “A White Paper, Community Perspective.” Metabolomics Off J Metabolomic Soc. 2016; 12:149, CrossRef.
Clish CB. Metabolomics: an emerging but powerful tool for precision medicine. Cold Spring Harb Mol Case Stud. 2015; 1: a000588, CrossRef.
Beger RD, Bhattacharyya S, Yang X, Gill PS, Schnackenberg LK, Sun J, et al. Translational biomarkers of acetaminophen-induced acute liver injury. Arch Toxicol. 2015; 89: 1497-522, CrossRef.
Cacciatore S, Loda M. Innovation in metabolomics to improve personalized healthcare. Ann NY Acad Sci. 2015; 1346: 57-62, CrossRef.
Everett JR. Pharmacometabonomics in humans: a new tool for personalized medicine. Pharmacogenomics. 2015; 16: 737-54, CrossRef.
Kaddurah-Daouk R, Kristal BS, Weinshilboum RM. Metabolomics: a global biochemical approach to drug response and disease. Annu Rev Pharmacol Toxicol. 2008; 48: 653-83, CrossRef.
Kaddurah-Daouk R, Weinshilboum RM, Pharmacometabolomics Research Network. Pharmacometabolomics: implications for clinical pharmacology and systems pharmacology. Clin Pharmacol Ther. 2014; 95: 154-67, CrossRef.
Kaddurah-Daouk R, Weinshilboum R, Pharmacometabolomics Research Network. Metabolomic signatures for drug response phenotypes: pharmacometabolomics enables precision medicine. Clin Pharmacol Ther. 2015; 98: 71-5, CrossRef.
Kastenmüller G, Raffler J, Gieger C, Suhre K. Genetics of human metabolism: an update. Hum Mol Genet. 2015; 24: R93-101, CrossRef.
Nicholson JK, Everett JR, Lindon JC. Longitudinal pharmacometabonomics for predicting patient responses to therapy: drug metabolism, toxicity and efficacy. Expert Opin Drug Metab Toxicol. 2012; 8: 135-9, CrossRef.
Patti GJ, Yanes O, Siuzdak G. Metabolomics: the apogee of the omic triology. Nat Rev Mol Cell Biol. 2012; 13: 263-9, CrossRef.
Su LJ, Fiehn O, Maruvada P, Moore SC, O’Keefe SJ, Wishart DS, et al. The use of metabolomics in population-based research123. Adv Nutr. 2014; 5: 785-8, CrossRef.
Suhre K, Raffler J, Kastenmüller G. Biochemical insights from population studies with genetics and metabolomics. Arch Biochem Biophys. 2016; 589: 168-76, CrossRef.
Wilson ID. Drugs, bugs, and personalized medicine: pharmacometabonomics enters the ring. Proc Natl Acad Sci USA. 2009; 106: 14187-8, CrossRef.
Zamboni N, Saghatelian A, Patti GJ. Defining the metabolome: size, flux, and regulation. Mol Cell. 2015; 58: 699-706, CrossRef.
Pinu FR, Goldansaz SA, Jaine J. Translational metabolomics: current challenges and future opportunities. Metabolites. 2019; 9: 108, CrossRef.
Roessner U, Bowne J. What is metabolomics all about? BioTechniques. 2009; 46: 363-5, CrossRef.
Wishart DS, Knox C, Guo AC, Eisner R, Young N, Gautam B, et al. HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res. 2009; 37: D603-10, CrossRef.
Spratlin JL, Serkova NJ, Eckhardt SG. Clinical applications of metabolomics in oncology: a review. Clin Cancer Res Off J Am Assoc Cancer Res. 2009; 15: 431-40, CrossRef.
Lindon JC, Nicholson JK. Analytical technologies for metabonomics and metabolomics, and multi-omic information recovery. TrAC Trends Anal Chem. 2008; 27: 194-204, CrossRef.
Wishart DS, Tzur D, Knox C, Eisner R, Guo AC, Young N, et al. HMDB: the Human Metabolome Database. Nucleic Acids Res. 2007; 35: D521-6, CrossRef.
van der Greef J, van Wietmarschen H, van Ommen B, Verheij E. Looking back into the future: 30 years of metabolomics at TNO. Mass Spectrom Rev. 2013; 32: 399-415, CrossRef.
He JC, Chuang PY, Ma’ayan A, Iyengar R. Systems biology of kidney diseases. Kidney Int. 2012; 81: 22-39, CrossRef.
Weiss RH, Kim K. Metabolomics in the study of kidney diseases. Nat Rev Nephrol. 2011; 8: 22-33, CrossRef.
Gomase VS, Changbhale SS, Patil SA, Kale KV. Metabolomics. Curr Drug Metab. 2008; 9: 89-98, CrossRef.
Rochfort S. Metabolomics reviewed: a new “omics” platform technology for systems biology and implications for natural products research. J Nat Prod. 2005; 68: 1813-20, CrossRef.
Edelstein CL. Biomarkers of Kidney Disease. 2nd Ed. Cambridge: Academic Press; 2017, NLMID.
Ryan D, Robards K. Metabolomics: the greatest omics of them all? Anal Chem. 2006; 78: 7954-8, CrossRef.
Griffiths WJ, Koal T, Wang Y, Kohl M, Enot DP, Deigner HP. Targeted metabolomics for biomarker discovery. Angew Chem Int Ed Engl. 2010; 49: 5426-45, CrossRef.
Goodacre R, Vaidyanathan S, Dunn WB, Harrigan GG, Kell DB. Metabolomics by numbers: acquiring and understanding global metabolite data. Trends Biotechnol. 2004; 22: 245-52, CrossRef.
Rattray NJW, Daouk RK. Pharmacometabolomics and precision medicine special issue editorial. Metabolomics. 2017; 13: 59, CrossRef.
Trivedi DK, Hollywood KA, Goodacre R. Metabolomics for the masses: The future of metabolomics in a personalized world. New Horiz Transl Med. 2017; 3: 294-305, CrossRef.
Dunn WB, Lin W, Broadhurst D, Begley P, Brown M, Zelena E, et al. Molecular phenotyping of a UK population: defining the human serum metabolome. Metabolomics Off J Metabolomic Soc. 2015; 11: 9-26, CrossRef.
Newgard CB, An J, Bain JR, Muehlbauer MJ, Stevens RD, Lien LF, et al. A branched-chain amino acid-related metabolic signature that differentiates obese and lean humans and contributes to insulin resistance. Cell Metab. 2009; 9: 311-26, CrossRef.
Koeth RA, Wang Z, Levison BS, Buffa JA, Org E, Sheehy BT, et al. Intestinal microbiota metabolism of L-carnitine, a nutrient in red meat, promotes atherosclerosis. Nat Med. 2013; 19: 576-85, CrossRef.
Draisma HHM, Pool R, Kobl M, Jansen R, Petersen AK, Vaarhorst AAM, et al. Genome-wide association study identifies novel genetic variants contributing to variation in blood metabolite levels. Nat Commun. 2015; 6: 7208, CrossRef.
Dunn WB, Bailey NJC, Johnson HE. Measuring the metabolome: current analytical technologies. The Analyst. 2005; 130: 606-25, CrossRef.
Wishart DS, Jewison T, Guo AC, Wilson M, Knox C, Liu Y, et al. HMDB 3.0--The Human Metabolome Database in 2013. Nucleic Acids Res. 2013; 41: D801-7, CrossRef.
Manach C, Hubert J, Llorach R, Scalbert A. The complex links between dietary phytochemicals and human health deciphered by metabolomics. Mol Nutr Food Res. 2009; 53: 1303-15, CrossRef.
Johnson CH, Patterson AD, Idle JR, Gonzalez FJ. Xenobiotic metabolomics: major impact on the metabolome. Annu Rev Pharmacol Toxicol. 2012; 52: 37-56, CrossRef.
Mapstone M, Cheema AK, Fiandaca MS, Zhong X, Mhyre TR, MacArthur LH, et al. Plasma phospholipids identify antecedent memory impairment in older adults. Nat Med. 2014; 20: 415-8, CrossRef.
German JB, Hammock BD, Watkins SM. Metabolomics: building on a century of biochemistry to guide human health. Metabolomics Off J Metabolomic Soc. 2005; 1: 3-9, CrossRef.
Cascante M, Marin S. Metabolomics and fluxomics approaches. Essays Biochem. 2008; 45: 67-82, CrossRef.
Rhee EP, Cheng S, Larson MG, Walford GA, Lewis GD, McCabe E, et al. Lipid profiling identifies a triacylglycerol signature of insulin resistance and improves diabetes prediction in humans. J Clin Invest. 2011; 121: 1402-11, CrossRef.
Monteiro MS, Carvalho M, Bastos ML, Guedes de Pinho P. Metabolomics analysis for biomarker discovery: advances and challenges. Curr Med Chem. 2013; 20: 257-71, CrossRef.
Nordström A, Lewensohn R. Metabolomics: moving to the clinic. J Neuroimmune Pharmacol Off J Soc NeuroImmune Pharmacol. 2010; 5: 4-17, CrossRef.
Mamas M, Dunn WB, Neyses L, Goodacre R. The role of metabolites and metabolomics in clinically applicable biomarkers of disease. Arch Toxicol. 2011; 85: 5-17, CrossRef.
Wang TJ, Ngo D, Psychogios N, Dejam A, Larson MG, Vasan RS, et al. 2-Aminoadipic acid is a biomarker for diabetes risk. J Clin Invest. 2013; 123: 4309-17, CrossRef.
Wei R, Li G, Seymour AB. Multiplexed, quantitative, and targeted metabolite profiling by LC-MS/MRM. Methods Mol Biol Clifton NJ. 2014; 1198: 171-99, CrossRef.
Altadill T, Campoy I, Lanau L, Gill K, Rigau M, Gil-Moreno A, et al. Enabling metabolomics based biomarker discovery studies using molecular phenotyping of exosome-like vesicles. PloS One. 2016; 11: e0151339, CrossRef.
Brennan L. Metabolomics in nutrition research: current status and perspectives. Biochem Soc Trans. 2013; 41: 670-3, CrossRef.
Madsen R, Lundstedt T, Trygg J. Chemometrics in metabolomics--a review in human disease diagnosis. Anal Chim Acta. 2010 Feb; 659: 23-33, CrossRef.
Erazo M, Garcýa A, Ruperez F, Barbaz C. Metabolomics of diet-related diseases. In: Cifuentes A, editor. Foodomics: Advanced Mass Spectrometry in Modern Food Science and Nutrition. Hoboken: John Wiley & Sons; 2013. p. 429-51, CrossRef.
Bingham SA. Biomarkers in nutritional epidemiology. Public Health Nutr. 2002; 5: 821-7, CrossRef.
Kipnis V, Midthune D, Freedman L, Bingham S, Day NE, Riboli E, et al. Bias in dietary-report instruments and its implications for nutritional epidemiology. Public Health Nutr. 2002; 5: 915-23, CrossRef.
Tasevska N, Runswick SA, McTaggart A, Bingham SA. Urinary sucrose and fructose as biomarkers for sugar consumption. Cancer Epidemiol Biomark Prev Publ Am Assoc Cancer Res Cosponsored Am Soc Prev Oncol. 2005; 14: 1287-94, CrossRef.
Freedman LS, Kipnis V, Schatzkin A, Tasevska N, Potischman N. Can we use biomarkers in combination with self-reports to strengthen the analysis of nutritional epidemiologic studies? Epidemiol Perspect Innov EPI. 2010; 7: 2, CrossRef.
Armitage EG, Rupérez FJ, Barbas C. Metabolomics of diet-related diseases using mass spectrometry. TrAC Trends Anal Chem. 2013; 52: 61-73, CrossRef.
Dagogo-Jack S. Metabolomic prediction of diabetes and cardiovascular risk. Med Princ Pract. 2012; 21: 401-3, CrossRef.
Kim SA, Kim JY, Yun EJ, Kim KH. Food metabolomics: from farm to human. Curr Opin Biotechnol. 2016; 37: 16-23, CrossRef.
Monteiro CA, Levy RB, Claro RM, Castro IRR de, Cannon G. A new classification of foods based on the extent and purpose of their processing. Cad Saude Publica. 2010; 26: 2039-49, CrossRef.
Liu H, Tayyari F, Khoo C, Gu L. A 1H NMR-based approach to investigate metabolomic differences in the plasma and urine of young women after cranberry juice or apple juice consumption. J Funct Foods. 2015; 14: 76-86, CrossRef.
Pujos-Guillot E, Hubert J, Martin JF, Lyan B, Quintana M, Claude S, et al. Mass spectrometry-based metabolomics for the discovery of biomarkers of fruit and vegetable intake: citrus fruit as a case study. J Proteome Res. 2013; 12: 1645-59, CrossRef.
Hanhineva K, Lankinen MA, Pedret A, Schwab U, Kolehmainen M, Paananen J, et al. Nontargeted metabolite profiling discriminates diet-specific biomarkers for consumption of whole grains, fatty fish, and bilberries in a randomized controlled trial. J Nutr. 2015; 145: 7-17, CrossRef.
Urpi-Sarda M, Boto-Ordóñez M, Queipo-Ortuño MI, Tulipani S, Corella D, Estruch R, et al. Phenolic and microbial-targeted metabolomics to discovering and evaluating wine intake biomarkers in human urine and plasma. Electrophoresis. 2015; 36: 2259-68, CrossRef.
Rothwell JA, Fillâtre Y, Martin JF, Lyan B, Pujos-Guillot E, Fezeu L, et al. New biomarkers of coffee consumption identified by the non-targeted metabolomic profiling of cohort study subjects. PloS One. 2014; 9: e93474, CrossRef.
Bouchard-Mercier A, Rudkowska I, Lemieux S, Couture P, Vohl MC. The metabolic signature associated with the Western dietary pattern: a cross-sectional study. Nutr J. 2013; 12: 158, CrossRef.
O’Sullivan A, Gibney MJ, Brennan L. Dietary intake patterns are reflected in metabolomic profiles: potential role in dietary assessment studies. Am J Clin Nutr. 2011; 93: 314-21, CrossRef.
Brennan L. Session 2: Personalised nutrition metabolomic applications in nutritional research: Symposium on ‘The challenge of translating nutrition research into public health nutrition.’ Proc Nutr Soc. 2008; 67: 404-8, CrossRef.
Menni C, Zhai G, Macgregor A, Prehn C, Römisch-Margl W, Suhre K, et al. Targeted metabolomics profiles are strongly correlated with nutritional patterns in women. Metabolomics Off J Metabolomic Soc. 2013; 9: 506-14, CrossRef.
Newby PK, Tucker KL. Empirically derived eating patterns using factor or cluster analysis: a review. Nutr Rev. 2004; 62: 177–203, CrossRef.
Bhupathiraju SN, Tucker KL. Coronary heart disease prevention: nutrients, foods, and dietary patterns. Clin Chim Acta Int J Clin Chem. 2011; 412: 1493-514, CrossRef.
Yusof AS, Isa ZM, Shah SA. Dietary patterns and risk of colorectal cancer: a systematic review of cohort studies (2000-2011). Asian Pac J Cancer Prev APJCP. 2012; 13: 4713-7, CrossRef.
Esmaillzadeh A, Kimiagar M, Mehrabi Y, Azadbakht L, Hu FB, Willett WC. Dietary patterns, insulin resistance, and prevalence of the metabolic syndrome in women. Am J Clin Nutr. 2007; 85: 910-8, CrossRef.
Schulze MB, Hoffmann K, Manson JE, Willett WC, Meigs JB, Weikert C, et al. Dietary pattern, inflammation, and incidence of type 2 diabetes in women. Am J Clin Nutr. 2005; 82: 675–84, CrossRef.
Allen J, Davey HM, Broadhurst D, Heald JK, Rowland JJ, Oliver SG, et al. High-throughput classification of yeast mutants for functional genomics using metabolic footprinting. Nat Biotechnol. 2003; 21: 692-6, CrossRef.
An J, Muoio DM, Shiota M, Fujimoto Y, Cline GW, Shulman GI, et al. Hepatic expression of malonyl-CoA decarboxylase reverses muscle, liver and whole-animal insulin resistance. Nat Med. 2004; 10: 268-74, CrossRef.
Nicholson JK, Wilson ID. Opinion: understanding “global” systems biology: metabonomics and the continuum of metabolism. Nat Rev Drug Discov. 2003; 2: 668-76, CrossRef.
Raamsdonk LM, Teusink B, Broadhurst D, Zhang N, Hayes A, Walsh MC, et al. A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations. Nat Biotechnol. 2001; 19: 45-50, CrossRef.
Holmes E, Loo RL, Stamler J, Bictash M, Yap IKS, Chan Q, et al. Human metabolic phenotype diversity and its association with diet and blood pressure. Nature. 2008; 453: 396-400, CrossRef.
Shaham O, Wei R, Wang TJ, Ricciardi C, Lewis GD, Vasan RS, et al. Metabolic profiling of the human response to a glucose challenge reveals distinct axes of insulin sensitivity. Mol Syst Biol. 2008; 4: 214, CrossRef.
Wopereis S, Rubingh CM, Erk MJ van, Verheij ER, Vliet T van, Cnubben NHP, et al. Metabolic profiling of the response to an oral glucose tolerance test detects subtle metabolic changes. PloS One. 2009; 4: e4525, CrossRef.
Zhao X, Peter A, Fritsche J, Elcnerova M, Fritsche A, Häring HU, et al. Changes of the plasma metabolome during an oral glucose tolerance test: is there more than glucose to look at? Am J Physiol Endocrinol Metab. 2009; 296: E384-93, CrossRef.
Cheng S, Rhee EP, Larson MG, Lewis GD, McCabe EL, Shen D, et al. Metabolite profiling identifies pathways associated with metabolic risk in humans. Circulation. 2012; 125: 2222-31, CrossRef.
Dietary Guidelines Advisory Committee. Scientific Report of the 2015 Dietary Guidelines Advisory Committee. Maryland: U.S. Department of Agriculture, Agricultural Research Service; 2015, article.
Liu X, Wang X, Lin S, Yuan J, Yu ITS. Dietary patterns and oesophageal squamous cell carcinoma: a systematic review and meta-analysis. Br J Cancer. 2014; 110: 2785-95, CrossRef.
Reedy J, Wirfält E, Flood A, Mitrou PN, Krebs-Smith SM, Kipnis V, et al. Comparing 3 dietary pattern methods--cluster analysis, factor analysis, and index analysis--With colorectal cancer risk: The NIH-AARP Diet and Health Study. Am J Epidemiol. 2010; 171: 479-87, CrossRef.
George SM, Ballard-Barbash R, Manson JE, Reedy J, Shikany JM, Subar AF, et al. Comparing indices of diet quality with chronic disease mortality risk in postmenopausal women in the Women’s Health Initiative Observational Study: evidence to inform national dietary guidance. Am J Epidemiol. 2014; 180: 616-25, CrossRef.
Reedy J, Krebs-Smith SM, Miller PE, Liese AD, Kahle LL, Park Y, et al. Higher diet quality is associated with decreased risk of all-cause, cardiovascular disease, and cancer mortality among older adults. J Nutr. 2014; 144: 881-9, CrossRef.
Slattery ML. Defining dietary consumption: is the sum greater than its parts? Am J Clin Nutr. 2008; 88: 14-5, CrossRef.
Guenther PM, Kirkpatrick SI, Reedy J, Krebs-Smith SM, Buckman DW, Dodd KW, et al. The Healthy Eating Index-2010 is a valid and reliable measure of diet quality according to the 2010 Dietary Guidelines for Americans. J Nutr. 2014; 144: 399-407, CrossRef.
NEL. A series of systematic reviews on the relationship between dietary patterns and health outcomes. Alexandria: US Department of Agriculture, Center for Nutrition Policy and Promotion; 2014, article.
Jenab M, Slimani N, Bictash M, Ferrari P, Bingham SA. Biomarkers in nutritional epidemiology: applications, needs and new horizons. Hum Genet. 2009; 125: 507-25, CrossRef.
Wishart DS. Metabolomics: applications to food science and nutrition research. Trends Food Sci Technol. 2008; 19: 482-93, CrossRef.
Scalbert A, Brennan L, Fiehn O, Hankemeier T, Kristal BS, van Ommen B, et al. Mass-spectrometry-based metabolomics: limitations and recommendations for future progress with particular focus on nutrition research. Metabolomics Off J Metabolomic Soc. 2009; 5: 435-58, CrossRef.
Heinzmann SS, Brown IJ, Chan Q, Bictash M, Dumas ME, Kochhar S, et al. Metabolic profiling strategy for discovery of nutritional biomarkers: proline betaine as a marker of citrus consumption. Am J Clin Nutr. 2010; 92: 436-43, CrossRef.
Evans AM, Bridgewater BR, Liu Q, Mitchell MW, Robinson RJ, Dai H, et al. High resolution mass spectrometry improves data quantity and quality as compared to unit mass resolution mass spectrometry in high-throughput profiling metabolomics. J Postgenomics Drug Biomark Dev. 2014; 4: 1000132, CrossRef.
Playdon MC, Moore SC, Derkach A, Reedy J, Subar AF, Sampson JN, et al. Identifying biomarkers of dietary patterns by using metabolomics. Am J Clin Nutr. 2017; 105: 450-65, CrossRef.
Floegel A, Drogan D, Wang-Sattler R, Prehn C, Illig T, Adamski J, et al. Reliability of serum metabolite concentrations over a 4-month period using a targeted metabolomic approach. PloS One. 2011; 6: e21103, CrossRef.
Mokdad AH, Serdula MK, Dietz WH, Bowman BA, Marks JS, Koplan JP. The spread of the obesity epidemic in the United States, 1991-1998. JAMA. 1999; 282: 1519-22, CrossRef.
Aguilar-Salinas CA, García EG, Robles L, Riaño D, Ruiz-Gomez DG, García-Ulloa AC, et al. High adiponectin concentrations are associated with the metabolically healthy obese phenotype. J Clin Endocrinol Metab. 2008; 93: 4075-9, CrossRef.
Wildman RP, Muntner P, Reynolds K, McGinn AP, Rajpathak S, Wylie-Rosett J, et al. The obese without cardiometabolic risk factor clustering and the normal weight with cardiometabolic risk factor clustering: prevalence and correlates of 2 phenotypes among the US population (NHANES 1999-2004). Arch Intern Med. 2008; 168: 1617-24, CrossRef.
Hamer M, Stamatakis E. Metabolically healthy obesity and risk of all-cause and cardiovascular disease mortality. J Clin Endocrinol Metab. 2012; 97: 2482-8, CrossRef.
Appleton SL, Seaborn CJ, Visvanathan R, Hill CL, Gill TK, Taylor AW, et al. Diabetes and cardiovascular disease outcomes in the metabolically healthy obese phenotype: a cohort study. Diabetes Care. 2013; 36: 2388-94, CrossRef.
Chen HH, Tseng YJ, Wang SY, Tsai YS, Chang CS, Kuo TC, et al. The metabolome profiling and pathway analysis in metabolic healthy and abnormal obesity. Int J Obes 2005. 2015; 39: 1241-8, CrossRef.
Kuehnbaum NL, Britz-McKibbin P. New advances in separation science for metabolomics: resolving chemical diversity in a post-genomic era. Chem Rev. 2013; 113: 2437-68, CrossRef.
Kochhar S, Jacobs DM, Ramadan Z, Berruex F, Fuerholz A, Fay LB. Probing gender-specific metabolism differences in humans by nuclear magnetic resonance-based metabonomics. Anal Biochem. 2006; 352: 274-81, CrossRef.
Mihalik SJ, Goodpaster BH, Kelley DE, Chace DH, Vockley J, Toledo FGS, et al. Increased levels of plasma acylcarnitines in obesity and type 2 diabetes and identification of a marker of glucolipotoxicity. Obes Silver Spring Md. 2010; 18: 1695-700, CrossRef.
Oberbach A, Blüher M, Wirth H, Till H, Kovacs P, Kullnick Y, et al. Combined proteomic and metabolomic profiling of serum reveals association of the complement system with obesity and identifies novel markers of body fat mass changes. J Proteome Res. 2011; 10: 4769-88, CrossRef.
Tai ES, Tan MLS, Stevens RD, Low YL, Muehlbauer MJ, Goh DLM, et al. Insulin resistance is associated with a metabolic profile of altered protein metabolism in Chinese and Asian-Indian men. Diabetologia. 2010; 53: 757-67, CrossRef.
Huffman KM, Shah SH, Stevens RD, Bain JR, Muehlbauer M, Slentz CA, et al. Relationships between circulating metabolic intermediates and insulin action in overweight to obese, inactive men and women. Diabetes Care. 2009; 32: 1678-83, CrossRef.
van der Greef J, Stroobant P, van der Heijden R. The role of analytical sciences in medical systems biology. Curr Opin Chem Biol. 2004; 8: 559-65, CrossRef.
McCormack SE, Shaham O, McCarthy MA, Deik AA, Wang TJ, Gerszten RE, et al. Circulating branched-chain amino acid concentrations are associated with obesity and future insulin resistance in children and adolescents. Pediatr Obes. 2013; 8: 52-61, CrossRef.
Perng W, Gillman MW, Fleisch AF, Michalek RD, Watkins SM, Isganaitis E, et al. Metabolomic profiles and childhood obesity. Obes Silver Spring Md. 2014; 22: 2570-8, CrossRef.
Bain JR, Stevens RD, Wenner BR, Ilkayeva O, Muoio DM, Newgard CB. Metabolomics applied to diabetes research: moving from information to knowledge. Diabetes. 2009; 58: 2429-43, CrossRef.
Allam-Ndoul B, Guénard F, Garneau V, Cormier H, Barbier O, Pérusse L, et al. Association between metabolite profiles, metabolic syndrome and obesity status. Nutrients. 2016; 8: 324, CrossRef.
Zeisel SH, Blusztajn JK. Choline and human nutrition. Annu Rev Nutr. 1994; 14: 269-96, CrossRef.
Zeisel SH, Mar MH, Howe JC, Holden JM. Concentrations of choline-containing compounds and betaine in common foods. J Nutr. 2003; 133: 1302-7, CrossRef.
Zeisel SH. Choline: critical role during fetal development and dietary requirements in adults. Annu Rev Nutr. 2006; 26: 229-50, CrossRef.
Niculescu MD, Craciunescu CN, Zeisel SH. Dietary choline deficiency alters global and gene-specific DNA methylation in the developing hippocampus of mouse fetal brains. FASEB J Off Publ Fed Am Soc Exp Biol. 2006; 20: 43-9, CrossRef.
Konstantinova SV, Tell GS, Vollset SE, Nygård O, Bleie Ø, Ueland PM. Divergent associations of plasma choline and betaine with components of metabolic syndrome in middle age and elderly men and women. J Nutr. 2008; 138: 914-20, CrossRef.
Chern MK, Pietruszko R. Evidence for mitochondrial localization of betaine aldehyde dehydrogenase in rat liver: purification, characterization, and comparison with human cytoplasmic E3 isozyme. Biochem Cell Biol Biochim Biol Cell. 1999; 77: 179-87, CrossRef.
Craig SAS. Betaine in human nutrition. Am J Clin Nutr. 2004; 80: 539-49, CrossRef.
Delgado-Reyes CV, Garrow TA. High sodium chloride intake decreases betaine-homocysteine S-methyltransferase expression in guinea pig liver and kidney. Am J Physiol Regul Integr Comp Physiol. 2005; 288: R182-7, CrossRef.
Ueland PM, Holm PI, Hustad S. Betaine: a key modulator of one-carbon metabolism and homocysteine status. Clin Chem Lab Med. 2005; 43: 1069-75, CrossRef.
Mato JM, Martínez-Chantar ML, Lu SC. Methionine metabolism and liver disease. Annu Rev Nutr. 2008; 28: 273-93, CrossRef.
Olthof MR, Verhoef P. Effects of betaine intake on plasma homocysteine concentrations and consequences for health. Curr Drug Metab. 2005; 6: 15-22, CrossRef.
Holm PI, Bleie Ø, Ueland PM, Lien EA, Refsum H, Nordrehaug JE, et al. Betaine as a determinant of postmethionine load total plasma homocysteine before and after B-vitamin supplementation. Arterioscler Thromb Vasc Biol. 2004; 24: 301-7, CrossRef.
Holm PI, Hustad S, Ueland PM, Vollset SE, Grotmol T, Schneede J. Modulation of the homocysteine-betaine relationship by methylenetetrahydrofolate reductase 677 C->t genotypes and B-vitamin status in a large-scale epidemiological study. J Clin Endocrinol Metab. 2007; 92: 1535-41, CrossRef.
Graham IM, Daly LE, Refsum HM, Robinson K, Brattström LE, Ueland PM, et al. Plasma homocysteine as a risk factor for vascular disease: The European Concerted Action Project. JAMA. 1997; 277: 1775-81, CrossRef.
Eckel RH, Grundy SM, Zimmet PZ. The metabolic syndrome. Lancet Lond Engl. 2005; 365: 1415-28, CrossRef.
Detopoulou P, Panagiotakos DB, Antonopoulou S, Pitsavos C, Stefanadis C. Dietary choline and betaine intakes in relation to concentrations of inflammatory markers in healthy adults: the ATTICA study. Am J Clin Nutr. 2008; 87: 424-30, CrossRef.
Ratnam S, Wijekoon EP, Hall B, Garrow TA, Brosnan ME, Brosnan JT. Effects of diabetes and insulin on betaine-homocysteine S-methyltransferase expression in rat liver. Am J Physiol Endocrinol Metab. 2006; 290: E933-9, CrossRef.
Wang Z, Yao T, Pini M, Zhou Z, Fantuzzi G, Song Z. Betaine improved adipose tissue function in mice fed a high-fat diet: a mechanism for hepatoprotective effect of betaine in nonalcoholic fatty liver disease. Am J Physiol Gastrointest Liver Physiol. 2010; 298: G634-42, CrossRef.
Ejaz A, Martinez-Guino L, Goldfine AB, Ribas-Aulinas F, De Nigris V, Ribó S, et al. Dietary betaine supplementation increases Fgf21 levels to improve glucose homeostasis and reduce hepatic lipid accumulation in mice. Diabetes. 2016; 65: 902-12, CrossRef.
Tabák AG, Jokela M, Akbaraly TN, Brunner EJ, Kivimäki M, Witte DR. Trajectories of glycaemia, insulin sensitivity, and insulin secretion before diagnosis of type 2 diabetes: an analysis from the Whitehall II study. Lancet Lond Engl. 2009; 373: 2215-21, CrossRef.
Wilson PWF, Meigs JB, Sullivan L, Fox CS, Nathan DM, D’Agostino RB. Prediction of incident diabetes mellitus in middle-aged adults: the Framingham Offspring Study. Arch Intern Med. 2007; 167: 1068-74, CrossRef.
Nisoli E, Clementi E, Carruba MO, Moncada S. Defective mitochondrial biogenesis: a hallmark of the high cardiovascular risk in the metabolic syndrome? Circ Res. 2007; 100: 795-806, CrossRef.
Lin CS, Wu RD. Choline oxidation and choline dehydrogenase. J Protein Chem. 1986; 5: 193-200, CrossRef.
Walford GA, Ma Y, Clish C, Florez JC, Wang TJ, Gerszten RE, et al. Metabolite profiles of diabetes incidence and intervention response in the diabetes prevention program. Diabetes. 2016; 65: 1424-33, CrossRef.
Song Z, Deaciuc I, Zhou Z, Song M, Chen T, Hill D, et al. Involvement of AMP-activated protein kinase in beneficial effects of betaine on high-sucrose diet-induced hepatic steatosis. Am J Physiol Gastrointest Liver Physiol. 2007; 293: G894-902, CrossRef.
Mihalik SJ, Michaliszyn SF, de las Heras J, Bacha F, Lee S, Chace DH, et al. Metabolomic profiling of fatty acid and amino acid metabolism in youth with obesity and type 2 diabetes: evidence for enhanced mitochondrial oxidation. Diabetes Care. 2012; 35: 605-11, CrossRef.
Waldram A, Holmes E, Wang Y, Rantalainen M, Wilson ID, Tuohy KM, et al. Top-down systems biology modeling of host metabotype-microbiome associations in obese rodents. J Proteome Res. 2009; 8: 2361-75, CrossRef.
Kim JY, Park JY, Kim OY, Ham BM, Kim HJ, Kwon DY, et al. Metabolic profiling of plasma in overweight/obese and lean men using ultra performance liquid chromatography and Q-TOF mass spectrometry (UPLC−Q-TOF MS). J Proteome Res. 2010; 9: 4368-75, CrossRef.
Calvani R, Miccheli A, Capuani G, Tomassini Miccheli A, Puccetti C, Delfini M, et al. Gut microbiome-derived metabolites characterize a peculiar obese urinary metabotype. Int J Obes. 2010; 34: 1095-8, CrossRef.
Kharbanda KK, Mailliard ME, Baldwin CR, Beckenhauer HC, Sorrell MF, Tuma DJ. Betaine attenuates alcoholic steatosis by restoring phosphatidylcholine generation via the phosphatidylethanolamine methyltransferase pathway. J Hepatol. 2007; 46: 314-21, CrossRef.
Kathirvel E, Morgan K, Nandgiri G, Sandoval BC, Caudill MA, Bottiglieri T, et al. Betaine improves nonalcoholic fatty liver and associated hepatic insulin resistance: a potential mechanism for hepatoprotection by betaine. Am J Physiol Gastrointest Liver Physiol. 2010; 299: G1068-77, CrossRef.
Pan XR, Li GW, Hu YH, Wang JX, Yang WY, An ZX, et al. Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance: The Da Qing IGT and Diabetes Study. Diabetes Care. 1997; 20: 537-44, CrossRef.
Tuomilehto J, Lindström J, Eriksson JG, Valle TT, Hämäläinen H, Ilanne-Parikka P, et al. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med. 2001; 344: 1343-50, CrossRef.
Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002; 346: 393-403, CrossRef.
DREAM (Diabetes REduction Assessment with ramipril and rosiglitazone Medication) Trial Investigators. Effect of rosiglitazone on the frequency of diabetes in patients with impaired glucose tolerance or impaired fasting glucose: a randomised controlled trial. Lancet Lond Engl. 2006; 368: 1096-105, CrossRef.
Adamski J. Key elements of metabolomics in the study of biomarkers of diabetes. Diabetologia. 2016; 59: 2497-502, CrossRef.
Fuhrer T, Zamboni N. High-throughput discovery metabolomics. Curr Opin Biotechnol. 2015; 31: 73-8, CrossRef.
Yu D, Moore SC, Matthews CE, Xiang YB, Zhang X, Gao YT, et al. Plasma metabolomic profiles in association with type 2 diabetes risk and prevalence in Chinese adults. Metabolomics Off J Metabolomic Soc. 2016; 12: 3, CrossRef.
Menni C, Fauman E, Erte I, Perry JRB, Kastenmüller G, Shin SY, et al. Biomarkers for type 2 diabetes and impaired fasting glucose using a nontargeted metabolomics approach. Diabetes. 2013; 62: 4270-6, CrossRef.
Peddinti G, Cobb J, Yengo L, Froguel P, Kravić J, Balkau B, et al. Early metabolic markers identify potential targets for the prevention of type 2 diabetes. Diabetologia. 2017; 60: 1740-50, CrossRef.
Gall WE, Beebe K, Lawton KA, Adam KP, Mitchell MW, Nakhle PJ, et al. alpha-hydroxybutyrate is an early biomarker of insulin resistance and glucose intolerance in a nondiabetic population. PloS One. 2010; 5: e10883, CrossRef.
Ferrannini E, Natali A, Camastra S, Nannipieri M, Mari A, Adam KP, et al. Early metabolic markers of the development of dysglycemia and type 2 diabetes and their physiological significance. Diabetes. 2013; 62: 1730-7, CrossRef.
Wang-Sattler R, Yu Z, Herder C, Messias AC, Floegel A, He Y, et al. Novel biomarkers for pre-diabetes identified by metabolomics. Mol Syst Biol. 2012; 8: 615, CrossRef.
Klein MS, Shearer J. Metabolomics and type 2 diabetes: translating basic research into clinical application. J Diabetes Res. 2016; 2016: 3898502, CrossRef.
Stumvoll M, Mitrakou A, Pimenta W, Jenssen T, Yki-Järvinen H, Van Haeften T, et al. Use of the oral glucose tolerance test to assess insulin release and insulin sensitivity. Diabetes Care. 2000; 23: 295-301, CrossRef.
Basu R, Schwenk WF, Rizza RA. Both fasting glucose production and disappearance are abnormal in people with “mild” and “severe” type 2 diabetes. Am J Physiol-Endocrinol Metab. 2004; 287: E55-62, CrossRef.
Li L, Krznar P, Erban A, Agazzi A, Martin-Levilain J, Supale S, et al. Metabolomics identifies a biomarker revealing in vivo loss of functional β-cell mass before diabetes onset. Diabetes. 2019; 68: 2272-86, CrossRef.
Palmer ND, Stevens RD, Antinozzi PA, Anderson A, Bergman RN, Wagenknecht LE, et al. Metabolomic profile associated with insulin resistance and conversion to diabetes in the insulin resistance atherosclerosis study. J Clin Endocrinol Metab. 2015; 100: E463-8, CrossRef.
Newgard CB. Interplay between lipids and branched-chain amino acids in development of insulin resistance. Cell Metab. 2012; 15: 606-14, CrossRef.
Avogaro A, Bier DM. Contribution of 3-hydroxyisobutyrate to the measurement of 3-hydroxybutyrate in human plasma: comparison of enzymatic and gas-liquid chromatography-mass spectrometry assays in normal and in diabetic subjects. J Lipid Res. 1989; 30: 1811-7, CrossRef.
Giesbertz P, Padberg I, Rein D, Ecker J, Höfle AS, Spanier B, et al. Metabolite profiling in plasma and tissues of ob/ob and db/db mice identifies novel markers of obesity and type 2 diabetes. Diabetologia. 2015; 58: 2133-43, CrossRef.
Jang C, Oh SF, Wada S, Rowe GC, Liu L, Chan MC, et al. A branched-chain amino acid metabolite drives vascular fatty acid transport and causes insulin resistance. Nat Med. 2016; 22: 421-6, CrossRef.
Lu J, Zhou J, Bao Y, Chen T, Zhang Y, Zhao A, et al. Serum metabolic signatures of fulminant type 1 diabetes. J Proteome Res. 2012; 11: 4705-11, CrossRef.
Xu F, Tavintharan S, Sum CF, Woon K, Lim SC, Ong CN. Metabolic signature shift in type 2 diabetes mellitus revealed by mass spectrometry-based metabolomics. J Clin Endocrinol Metab. 2013; 98: E1060-5, CrossRef.
Adams SH, Hoppel CL, Lok KH, Zhao L, Wong SW, Minkler PE, et al. Plasma acylcarnitine profiles suggest incomplete long-chain fatty acid β-oxidation and altered tricarboxylic acid cycle activity in type 2 diabetic African-American women. J Nutr. 2009; 139: 1073-81, CrossRef.
Pflueger M, Seppänen-Laakso T, Suortti T, Hyötyläinen T, Achenbach P, Bonifacio E, et al. Age- and islet autoimmunity-associated differences in amino acid and lipid metabolites in children at risk for type 1 diabetes. Diabetes. 2011; 60: 2740-7, CrossRef.
Suhre K, Meisinger C, Döring A, Altmaier E, Belcredi P, Gieger C, et al. Metabolic footprint of diabetes: a multiplatform metabolomics study in an epidemiological setting. PLoS One. 2010; 5: e13953, CrossRef.
Floegel A, Stefan N, Yu Z, Mühlenbruch K, Drogan D, Joost HG, et al. Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach. Diabetes. 2013; 62: 639-48, CrossRef.
Meiliana A, Dewi NM, Wijaya A. Molecular regulation and rejuvenation of muscle stem (satellite) cell aging. Indones Biomed J. 2015; 7: 73-86, CrossRef.
Crockett D. Health Catalyst [Internet]. The Real Opportunity of Precision Medicine and How to Not Miss Out [updated 2019 Feb 19; cited 2020 May 29]. Available from: https://www.healthcatalyst.com/.
Harrer S. Measuring life: sensors and analytics for precision medicine. Bio-MEMS and Medical Microdevices II. 2015; 2015: 951802, CrossRef.
International Human Genome Sequencing Consortium. Finishing the euchromatic sequence of the human genome. Nature. 2004; 431: 931-45, CrossRef.
Bertini I, Calabrò A, De Carli V, Luchinat C, Nepi S, Porfirio B, et al. The metabonomic signature of celiac disease. J Proteome Res. 2009; 8: 170-7, CrossRef.
Bertini I, Cacciatore S, Jensen BV, Schou JV, Johansen JS, Kruhøffer M, et al. Metabolomic NMR fingerprinting to identify and predict survival of patients with metastatic colorectal cancer. Cancer Res. 2012; 72: 356-64, CrossRef.
Aimetti M, Cacciatore S, Graziano A, Tenori L. Metabonomic analysis of saliva reveals generalized chronic periodontitis signature. Metabolomics. 2012; 8: 465-74, CrossRef.
Nicholson JK, Lindon JC. Systems biology: Metabonomics. Nature. 2008; 455: 1054-6, CrossRef.
Marshall E. Metabolic research. Canadian group claims “unique” database. Science. 2007; 315: 583-4, CrossRef.
Lindon JC, Nicholson JK. The emergent role of metabolic phenotyping in dynamic patient stratification. Expert Opin Drug Metab Toxicol. 2014; 10: 915-9, CrossRef.
Backshall A, Sharma R, Clarke SJ, Keun HC. Pharmacometabonomic profiling as a predictor of toxicity in patients with inoperable colorectal cancer treated with capecitabine. Clin Cancer Res Off J Am Assoc Cancer Res. 2011; 17: 3019-28, CrossRef.
Evans WE, McLeod HL. Pharmacogenomics--drug disposition, drug targets, and side effects. N Engl J Med. 2003; 348: 538-49, CrossRef.
Ma Q, Lu AYH. Pharmacogenetics, pharmacogenomics, and individualized medicine. Pharmacol Rev. 2011; 63: 437-59, CrossRef.
Mancinelli L, Cronin M, Sadée W. Pharmacogenomics: The promise of personalized medicine. AAPS PharmSci. 2000; 2: 29-41,
March R. Pharmacogenomics: the genomics of drug response. Yeast Chichester Engl. 2000; 17: 16-21, CrossRef.
Carr DF, Alfirevic A, Pirmohamed M. Pharmacogenomics: current state-of-the-art. Genes. 2014; 5: 430-43, CrossRef.
Drucker E, Krapfenbauer K. Pitfalls and limitations in translation from biomarker discovery to clinical utility in predictive and personalised medicine. EPMA J. 2013; 4: 7, CrossRef.
Sun J, Ando Y, Ahilbory-Dieker D, Schnackenberg L, Greenhaw J, Pence L, et al. Systems biology investigation to discover metabolic biomarkers of acetaminophen-induced hepatic injury using integrated transcriptomics and metabolomics. J Mol Biomark Diagn. 2013; S1: 002, CrossRef.
Abdin AA, Hamouda HE. Mechanism of the neuroprotective role of coenzyme Q10 with or without L-dopa in rotenone-induced parkinsonism. Neuropharmacology. 2008; 55: 1340-6, CrossRef.
Ellero-Simatos S, Lewis JP, Georgiades A, Yerges-Armstrong LM, Beitelshees AL, Horenstein RB, et al. Pharmacometabolomics reveals that serotonin is implicated in aspirin response variability. CPT Pharmacomet Syst Pharmacol. 2014; 3: e125, CrossRef.
Li M, Wang B, Zhang M, Rantalainen M, Wang S, Zhou H, et al. Symbiotic gut microbes modulate human metabolic phenotypes. Proc Natl Acad Sci USA. 2008; 105: 2117-22, CrossRef.
Yapar K, Kart A, Karapehlivan M, Atakisi O, Tunca R, Erginsoy S, et al. Hepatoprotective effect of l-carnitine against acute acetaminophen toxicity in mice. Exp Toxicol Pathol. 2007; 59: 121-8, CrossRef.
Schnackenberg LK, Kaput J, Beger RD. Metabolomics: a tool for personalizing medicine? Pers Med. 2008; 5: 495-504, CrossRef.
Ji Y, Hebbring S, Zhu H, Jenkins GD, Biernacka J, Snyder K, et al. Glycine and a glycine dehydrogenase (GLDC) SNP as citalopram/escitalopram response biomarkers in depression: pharmacometabolomics-informed pharmacogenomics. Clin Pharmacol Ther. 2011; 89: 97-104, CrossRef.
Abo R, Hebbring S, Ji Y, Zhu H, Zeng ZB, Batzler A, et al. Merging pharmacometabolomics with pharmacogenomics using “1000 Genomes” single-nucleotide polymorphism imputation: selective serotonin reuptake inhibitor response pharmacogenomics. Pharmacogenet Genomics. 2012; 22: 247-53, CrossRef.
Evans WE, Relling MV. Moving towards individualized medicine with pharmacogenomics. Nature. 2004; 429: 464-8, CrossRef.
Pirmohamed M. Personalized pharmacogenomics: predicting efficacy and adverse drug reactions. Annu Rev Genomics Hum Genet. 2014; 15: 349-70, CrossRef.
Neavin D, Kaddurah-Daouk R, Weinshilboum R. Pharmacometabolomics informs Pharmacogenomics. Metabolomics Off J Metabolomic Soc. 2016; 12: 121, CrossRef.
Beger RD, Flynn TJ. Pharmacometabolomics in drug safety and drug-exposome interactions. Metabolomics. 2016; 12: 123, CrossRef.
Weinshilboum R. Inheritance and drug response. N Engl J Med. 2003; 348: 529-37, CrossRef.
Li H, Jia W. Cometabolism of microbes and host: implications for drug metabolism and drug-induced toxicity. Clin Pharmacol Ther. 2013; 94: 574-81, CrossRef.
Kantae V, Krekels EHJ, Esdonk MJV, Lindenburg P, Harms AC, Knibbe CAJ, et al. Integration of pharmacometabolomics with pharmacokinetics and pharmacodynamics: towards personalized drug therapy. Metabolomics Off J Metabolomic Soc. 2017; 13: 9, CrossRef.
Clayton TA, Baker D, Lindon JC, Everett JR, Nicholson JK. Pharmacometabonomic identification of a significant host-microbiome metabolic interaction affecting human drug metabolism. Proc Natl Acad Sci USA. 2009; 106: 14728-33, CrossRef.
Lindon JC, Holmes E, Nicholson JK. Metabonomics techniques and applications to pharmaceutical research & development. Pharm Res. 2006; 23: 1075-88, CrossRef.
Nicholson JK, Wilson ID, Lindon JC. Pharmacometabonomics as an effector for personalized medicine. Pharmacogenomics. 2011; 12: 103-11, CrossRef.
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. Xenobiotica Fate Foreign Compd Biol Syst. 1999; 29: 1181-9, CrossRef.
Nicholson JK, Connelly J, Lindon JC, Holmes E. Metabonomics: a platform for studying drug toxicity and gene function. Nat Rev Drug Discov. 2002; 1: 153-61, CrossRef.
Yatsunenko T, Rey FE, Manary MJ, Trehan I, Dominguez-Bello MG, Contreras M, et al. Human gut microbiome viewed across age and geography. Nature. 2012; 486: 222-7, CrossRef.
Everett JR, Loo RL, Pullen FS. Pharmacometabonomics and personalized medicine. Ann Clin Biochem. 2013; 50: 523-45, CrossRef.
Lindon JC, Nicholson JK, Holmes E. The Handbook of Metabonomics and Metabolomics. Philadelphia: Elsevier Science; 2011, article.
Robertson DG, Lindon JC. Metabonomics in Toxicity Assessment. Boca Raton: Taylor & Francis; 2005, CrossRef.
Griffiths WJ. Metabolomics, Metabonomics, and Metabolite Profiling. Cambridge: Royal Society of Chemistry; 2008, CrossRef.
Knapp JS, Cabrera WL. Metabolomics: Metabolites, Metabonomics, and Analytical Technologies. New York: Nova Science Publishers; 2009, NLMID.
Nicholson JK, Holmes E, Kinross JM, Darzi AW, Takats Z, Lindon JC. Metabolic phenotyping in clinical and surgical environments. Nature. 2012; 491: 384-92, CrossRef.
DOI: https://doi.org/10.18585/inabj.v13i1.1309
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