Abstract
The review considers the development of a new science—metabolomics. The metabolome is mainly regarded as a set of primarily biochemical parameters, each of which or their ratio can serve as a potential biomarker that increases the sensitivity and/or specificity of diagnostics of diseases.
Similar content being viewed by others
References
Ariza, A.C., Deen, P.M., and Robben, J.H., The succinate receptor as a novel therapeutic target for oxidative and metabolic stress-related conditions, Front. Endocrinol., 2012, vol. 3, p. 22.
Atkinson, A.J., Colburn, W.A., De Gruttola, V.G., et al., Biomarker and surrogate endpoints: preferred definition and conceptual framework, Clin. Pharmacol. Ther., 2001, vol. 69, pp. 89–95.
Balion, C., Santaguida, P.L., Hill, S., et al., Testing for BNP and NT-proBNP in the diagnosis and prognosis of heart failure, Evidence Rep. Technol. Assess. (Full Rep.), 2006, vol. 142, pp. 1–147.
Bauman, D.E., Mather, I.H., Wall, R.J., and Lock, A.L., Major advances associated with the biosynthesis of milk, J. Dairy Sci., 2006, vol. 89, no. 4, pp. 1235–1243.
Beckonert, O., Keun, H.C., Ebbels, T.M., et al., Metabolic profiling, metabolomic, and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts, Nat. Protoc., 2007, vol. 2, no. 11, pp. 2692–2703.
Bertram, H.C., Eggers, N., and Eller, N., Potential of human saliva for nuclear magnetic resonance-based metabolomics and for health-related biomarker identification, Anal. Chem., 2009, vol. 81, no. 21, pp. 9188–9193.
Bouhifd, M., Hartung, T., Hogberg, H.T., et al., Review: toxicometabolomics, J. Appl. Toxicol., 2013, vol. 33, no. 12, pp. 1365–1383.
Bouhifd, M., Hogberg, H.T., Kleensang, A., et al., Mapping the human toxome by systems toxicology, Basic Clin. Pharmacol.Toxicol., 2014. doi: 10.1111/bcpt.12198
Bruckbauer, A. and Zemel, M.B., Synergistic effects of metformin, resveratrol, and hydroxymethylbutyrate on insulin sensitivity, Diabetes, Metab. Syndr. Obes.: Targets Ther., 2013, vol. 6, pp. 93–102.
Bruckbauer, A., Zemel, M.B., Thorpe, T., et al., Synergistic effects of leucine and resveratrol on insulin sensitivity and fat metabolism in adipocytes and mice, Nutr. Metab., 2012, vol. 9, no. 1, p. 77.
Bruins Slot, M.H., van der Heijden, G.J., Rutten, F.H., et al., Heart-type fatty acid-binding protein in acute myocardial infarction evaluation (FAME): background and design of a diagnostic study in primary care, BMC Cardiovasc. Disord., 2008, vol. 8, p. 8.
Carpentier, A.C., Postprandial fatty acid metabolism in the development of lipotoxicity and type 2 diabetes, Diabetes Metab., 2008, vol. 34, no. 2, pp. 97–107.
Chang, T.W and Goldberg, A.L., The origin of alanine produced in skeletal muscle, J. Biol. Chem., 1978a, vol. 253, pp. 3677–3684.
Chang, T.W. and Goldberg, A.L., The metabolic fates of amino acids and the formation of glutamine in skeletal muscle, J. Biol. Chem., 1978b, vol. 253, pp. 3685–3695.
Charles, M.A., Eschwège, E., Thibult, N., et al., The role of non-esterified fatty acids in the deterioration of glucose tolerance in Caucasian subjects: results of the Paris prospective study, Diabetologia, 1997, vol. 40, no. 9, pp. 1101–1106.
Chorell, E., Moritz, T., Branth, S., et al., Predictive metab-olomics evaluation of nutrition-modulated metabolic stress responses in human blood serum during the early recovery phase of strenuous physical exercise, J. Pro-teome Res., 2009, vol. 8, no. 6, pp. 2966–2977.
Coen, M., Goldfain-Blanc, F., Rolland-Valognes, G., et al., Pharmacometabonomic investigation of dynamic metabolic phenotypes associated with variability in response to galactosamine hepatotoxicity, J. Proteome Res., 2012, vol. 11, no. 4, pp. 2427–2440.
Crews, B., Wikoff, W.R., Patti, G.J., et al., Variability analysis of human plasma and cerebral spinal fluid reveals statistical significance of changes in mass spectrometry-based metabolomics data, Anal. Chem., 2009, vol. 81, no. 20, pp. 8538–8544.
Crockford, D.J., Maher, A.D., Ahmadi, K.R., et al., 1HNMR and UPlC-MS(E) statistical heterospectroscopy: characterization of drug metabolites (xeno-metabolome) in epidemiological studies, Anal. Chem., 2008, vol. 80, no. 18, pp. 6835–6844.
Dabla, P.K., Renal function in diabetic nephropathy, World J. Diabetes, 2010, vol. 1, no. 2, pp. 48–56.
De Jager, S.C., Kraaijeveld, A.O., Grauss, R.W, et al., CCL3 (MIP-1 alpha) levels are elevated during acute coronary syndromes and show strong prognostic power for future ischemic events, J. Mol. Cell Cardiol., 2008, vol. 45, no. 3, pp. 446–452.
Eckel, R.H., Borra, S., Lichtenstein, A.H., and Yin-Piazza, S.Y., Understanding the complexity of trans fatty acid reduction in the American diet, Circulation, 2007, vol. 115, no. 16, pp. 2231–2246.
Ellis, J.K., Athersuch, T.J., Cavill, R., et al., Metabolic response to low-level toxicant exposure in a novel renal tubule epithelial cell system, Mol. Biosyst., 2011, vol. 7, no. 1, pp. 247–257.
Esbensen, K., Multivariate Data Analysis in Practice, Oslo CAMO, 2001, 5th ed.
Estadella, D., da Penha Oller do Nascimento, C.M., Oyama, L.M., et al., Lipotoxicity: effects of dietary saturated and transfatty acids, Mediators Inflammation, 2013. ID 137579.
Everett, J.R., Loo R.L., and Pullen, F.S., Pharmacometa-bonomics and personalized medicine, Ann. Clin. Bio-chem., 2013, vol. 50, no. 6, pp. 523–545.
Fischer, K., Kettunen, J., Wurtz, P., et al., Biomarker profiling by nuclear magnetic resonance spectroscopy for the prediction of all-cause mortality: an observational study of 17345 persons, PLoS Med., 2014, vol. 11, e1001606.
Gerszten, R.E. and Wang, T.J., The search for new cardiovascular biomarkers, Nature., 2008, vol. 451, no. 7181, pp. 949–952.
Golukhova, E.Z., Mashina, T.V., Mrikaev, D.V., and Gegechkori, N.R., Assessment of of intraventricular asynchrony in patients with heart ischemia, Kreativnaya Kardiol., 2009, no. 1, pp. 54–68.
Goncharov, N.V., Jenkins, R.O., and Radilov, A.S., Toxicology of fluoroacetate: a review, with possible directions for therapy research, J. Appl. Toxicol., 2006, vol. 26, no. 2, pp. 148–161.
Goncharov, N.V., Kuznetsov, A.V., and Radilov, A.S., Modern concepts about fluoroacetate toxicology, Toksikol. Vestn., 2005, no. 5, pp. 31–44.
Häberle, J., Boddaert, N., Burlina, A., et al., Suggested guidelines for the diagnosis and management of urea cycle disorders, Orphanet J. Rare Dis., 2012, vol. 7, p. 32.
Han, L.D., Xia, J.F., Liang, Q.L., et al., Plasma esterified and non-esterified fatty acids metabolic profiling using gas chromatography-mass spectrometry and its application in the study of diabetic mellitus and diabetic nephropathy, Anal. Chim. Acta, 2011, vol. 689, no. 1, pp. 85–91.
Hartung, T., Food for thought... on alternative methods for chemical safety testing, Altex, 2010, vol. 27, no. 1, pp. 3–14.
Hartung, T. and McBride, M., Food for thought...on mapping the human toxome, Altex, 2011, vol. 28, no. 2, pp. 83–93.
Huang, C.C., Lin, W.T., Hsu, F.L., et al., Metabolomics investigation of exercise-modulated changes in metabolism in rat liver after exhaustive and endurance exercises, Eur. J. Appl. Physiol., 2010, vol. 108, no. 3, pp. 557–566.
Ibrahim, S.H., Kohli, R., and Gores, G.J., Mechanisms of lipotoxicity in NAFLD and clinical implications, J. Pediatr. Gastroenterol. Nutr., 2011, vol. 53, no. 2, pp. 131–140.
Itoh, Y, Kawamata, Y, Harada, M., et al., Free fatty acids regulate insulin secretion from pancreatic beta cells through GPR40, Nature, 2003, vol. 422, no. 6928, pp. 173–176.
Kalantzi, O.I., Martin, F.L., Thomas, G.O., et al., Different levels of polybrominated diphenyl ethers (PBDEs) and chlorinated compounds in breast milk from two U.K. regions, Environ. Health Perspect., 2004, vol. 112, no. 10, pp. 1085–1091.
Kanoh, S., Kobayashi, H., and Motoyoshi, K., Exhaled ethane: an in vivo biomarker of lipid peroxidation in interstitial lung diseases, Chest, 2005, vol. 128, no. 4, pp. 2387–2392.
Kim, K.B., Um, S.Y., Chung, M.W., et al., Toxicometabo-lomics approach to urinary biomarkers for mercuric chloride (HgCl2)-induced nephrotoxicity using proton nuclear magnetic resonance (1H NMR) in rats, Toxicol. Appl. Pharmacol., 2010b, vol. 249, no. 2, pp. 114–126.
Kim, K.B., Yang, J.Y., Kwack, S.J., et al., Toxicometabolo-mics of urinary biomarkers for human gastric cancer in a mouse model, J. Toxicol. Environ. Health, Part A, 2010a, vol. 73, nos. 21–22, pp. 1420–1430.
Koek, M.M., Muilwijk, B., van der Werf, M.J., and Hanke-meier, T., Microbial metabolomics with gas chromatography/mass spectrometry, Anal. Chem., 2006, vol. 78, no. 4, pp. 1272–1281.
Kutyshenko, V.P., Molchanov, M., Beskaravayny, P., et al., Analyzing and mapping sweat metabolomics by high-resolution NMR spectroscopy, PLoSOne, 2011, vol. 6, no. 12, p. e28824.
Labugger, R., Organ, L., Collier, C., et al., Extensive troponin I and T modification detected in serum from patients with acute myocardial infarction, Circulation, 2000, vol. 102, no. 11, pp. 1221–1226.
Laskowitz, D.T., Kasner, S.E., Saver, J., et al., Clinical usefulness of a biomarker-based diagnostic test for acute stroke the biomarker rapid assessment in ischemic injury (BRAIN) study, Stroke, 2009, vol. 40, pp. 77–85.
Laufer, E.M., Reutelingsperger, C.P., Narula, J., and Hof-stra, L. Annexin A5: an imaging biomarker of cardiovascular risk, Basic Res. Cardiol., 2008, vol. 103, no. 2, pp. 95–104.
Lê Cao, K. A., Boitard, S., and Besse, P., Sparse PLS discriminant analysis: biologically relevant feature selection and graphical displays for multiclass problems, BMC Bioinformatics, 2011, vol. 12, p. 253.
Lewis, C.A., Parker, S.J., Fiske, B.P., et al., Tracing compartmentalized NADPH metabolism in the cytosol and mitochondria of mammalian cells, Mol. Cell., 2014, vol. 55, no. 2, pp. 253–263.
Lewis, G.D., Wei, R., Liu, E., et al., Metabolite profiling of blood from individuals undergoing planned myocardial infarction reveals early markers of myocardial injury, J. Clin. Invest., 2008, vol. 118, no. 10, pp. 3503–3512.
Lindon, J.C., Holmes, E., and Nicholson, J.K., Metabo-nomics techniques and applications to pharmaceutical research and development, Pharm. Res., 2006, vol. 23, no. 6, pp. 1075–1088.
Listenberger, L.L. and Schaffer, J.E., Mechanisms of lipoapoptosis: implications for human heart disease, Trends Cardiovasc. Med., 2002, vol. 12, no. 3, pp. 134–138.
Lynch, J.R., Blessing, R., White, W.D., et al., Novel diagnostic test for acute stroke, Stroke, 2004, vol. 35, pp. 57–63.
Mallenom Systems Company, Modeling and forecasting of multiparameter economic and technological processes: mathematical modeling techniques. http://www.maUe-nom.ru/article022.php
Manders, R.J., Little, J.P., Forbes, S.C., and Candow, D.G., Insulinotropic and muscle protein synthetic effects of branched-chain amino acids: potential therapy for type 2 diabetes and sarcopenia, Nutrients, 2012, vol. 4, no. 11, pp. 1664–1678.
Massart, D.L., Vandeginste, B.G.M., Deming, S.N., et al., Chemometrics: A Textbook, Amsterdam Elsevier, 1988.
Matthews, D.R., Hosker, J.P., Rudenski, A.S., et al., Homeostasis model assessment: insulin resistance and betacell function from fasting plasma glucose and insulin concentrations in man, Diabetologia, 1985, vol. 28, no. 7, pp. 412–419.
Millington, D.S., Kodo, N., Norwood, D.L., and Roe, C.R., Tandem mass spectrometry: a new method for acylcar-nitine profiling with potential for neonatal screening for inborn errors of metabolism, J. Inherited Metab. Dis., 1990, vol. 13, no. 3, pp. 321–324.
Nadeev, A.D., Zinchenko, V.P., Avdonin, P.V., and Goncharov, N.V., Toxic and signaling effects of active kinds of oxygen, Toksikol. Vestn., 2014, no. 2, pp. 22–27.
Nicholson, J.K., Connelly, J., Lindon, J.C., and Holmes, E., Metabonomics: a platform for studying drug toxicity and gene function, Nat. Rev. Drug Discovery, 2002, vol. 1, no. 2, pp. 153–161.
Nicholson, J.K., Lindon, J.C., and Holmes, E., “Metabo-nomics”: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data, Xenobiotica, 1999, vol. 29, no. 11, pp. 1181–1189.
Nieman, D.C., Gillitt, N.D., Henson, D.A., et al., Bananas as an energy source during exercise: a metab-olomics approach, PLoS One, 2012, vol. 7, no. 5, p. e37479.
Nordström, A., O’Maille, G., Qin, C., and Siuzdak, G., Nonlinear data alignment for UPLC-MS and HPLC-MS based metabolomics: quantitative analysis of endogenous and exogenous metabolites in human serum, Anal. Chem., 2006, vol. 78, no. 10, pp. 3289–3295.
Obara, N., Fukushima, K., Ueno, Y., et al., Possible involvement and the mechanisms of excess trans-fatty acid consumption in severe NAFLD in mice, J. Hepatol., 2010, vol. 53, no. 2, pp. 326–334.
Patra, K.C. and Hay, N., The pentose phosphate pathway and cancer, Trends Biochem. Sci., 2014, vol. 39, no. 8, pp. 347–354.
Pérez-Enciso, M. and Tenenhaus, M., Prediction of clinical outcome with microarray data: a partial least squares discriminant analysis (PLS-DA) approach, Hum. Genet., 2003, vol. 112, nos. 5–6, pp. 581–592.
Piraud, M., Ruet, S., Boyer, S., et al., Amino acid profiling for the diagnosis of inborn errors of metabolism, in Metabolic Profiling: Methods and Protocols, Methods in Molecular Biology, Metz, TO., Ed., New York Springer-Verlag, 2011, vol. 708, pp. 25–53.
Poitout, V, Hagman, D., Stein, R., et al., Regulation of the insulin gene by glucose and fatty acids, J. Nutr., 2006, vol. 136, no. 4, pp. 873–876.
Ramirez, T., Daneshian, M., Kamp, H., et al., Metabolomics in toxicology and preclinical research, Altex, 2013, vol. 30, no. 2, pp. 209–225.
Rashed, M.S., Clinical applications of tandem mass spectrometry: ten years of diagnosis and screening for inherited metabolic diseases, J. Chromatogr. B: Anal. Technol. Biomed. Life Sci., 2001, vol. 758, no. 1, pp. 27–48.
Reynolds, M.A., Kirchick, H.J., Dahlen, JR., et al., Early biomarkers of stroke, Clin. Chem., 2003, vol. 49, no. 10, pp. 1733–1739.
Robinson, A.B. and Robinson, N.E., Origins of metabolic profiling, in Metabolic Profiling, Methods in Molecular Biology, Metz, TO., Ed., New York Springer-Verlag, 2011, pp. 1–24.
Rockey, D.C. and Bissell, D.M., Noninvasive measures of liver fibrosis, Hepatology, 2006, vol. 43, pp. 113–120.
Rodionova, O.E., Chemometric approach to the study of large arrays of chemical data, Ross. Khim. Zh., 2006, vol. 60, no. 2, pp. 128–144.
Salio, M., Chimenti, S., De Angelis, N., et al., Cardioprotective function of the long pentraxin PTX3 in acute myocardial infarction, Circulation, 2008, vol. 117, no. 8, pp. 1055–1064.
Spravochnoe rukovodstvo po psikhofarmakologicheskim i protvoepilepticheskim preparatam, razreshennym k primeneniyu v Rossii (Handbook on Psychopharmaco-logical and Antiepileptic Drugs Approved for Use in Russia), Mosolov, S.N., Ed., Moscow: BINOM, 2004, 2nd ed.
Sreekumar, A., Poisson, L.M., Rajendiran, T.M., et al., Metabolomic profiles delineate potential role for sar-cosine in prostate cancer progression, Nature, 2009, vol. 457, no. 7231, pp. 910–914.
Suzuki, K., Babazono, T., Murata, H., and Iwamoto, Y., Clinical significance of urinary liver-type fatty acid-binding protein in patients with diabetic nephropathy, Diabetes Care, 2005, vol. 28, no. 8, pp. 2038–2039.
Toxicity Testing in the 21st Century: A Vision and a Strategy, New York: Natl. Acad. Press NRC, 2007.
Vliet van, E., Morath, S., Eskes, C., et al., A novel in vitro metabolomics approach for neurotoxicity testing, proof of principle for methyl mercury chloride and caffeine, Neurotoxicology, 2008, vol. 29, no. 1, pp. 1–12.
Voitenko, N.G., Prokof’eva, D.S., and Goncharov, N.V, Diagnostics of intoxication by organophosphorus compounds, Toksikol. Vestn., 2013, no. 5, pp. 2–6.
Wang, R.E. and Gerszten, T.J., The search for new cardiovascular biomarkers, Nature, 2008, vol. 451, pp. 949–1952.
Weinberg, J.M., Lipotoxicity, Kidney Int., 2006, vol. 70, no. 9, pp. 1560–1566.
Wittmann, J., Karg, E., Turi, S., et al., Newborn screening for lysosomal storage disorders in Hungary, J. Inherited Metab. Dis. Rep., 2012, vol. 6, pp. 117–125.
Worster, A., Devereaux, P.J., Heels-Ansdell, D., et al., Capability of ischemia-modified albumin to predict serious cardiac outcomes in the short term among patients with potential acute coronary syndrome, Can. Med. Assoc. J, 2005, vol. 172, no. 13, pp. 1685–1690.
Würtz, P., Mäkinen, V.P., Soininen, P., et al., Metabolic signatures of insulin resistance in 7.098 young adults, Diabetes, 2012, vol. 61, no. 6, pp. 1372–1380.
Würtz, P., Soininen, P., Kangas, A.J., et al., Branched-chain and aromatic amino acids are predictors of insulin resistance in young adults, Diabetes Care, 2013, vol. 36, no. 3, pp. 648–655.
Yamamoto, H., Schoonjans, K., and Auwerx, J., Sirtuin functions in health and disease, Mol. Endocrinol., 2007, vol. 21, no. 8, pp. 1745–1755.
Yan, B., Jiye, A., Wang, G., Lu, H., et al., Metabolomic investigation into variation of endogenous metabolites in professional athletes subject to strength-endurance training, J. Appl. Physiol., 2009, vol. 106, no. 2, pp. 531–538.
Yao, H., Shi, P., Zhang, L., et al., Untargeted metabolic profiling reveals potential biomarkers in myocardial infarction and its application, Mol. Biosyst., 2010, vol. 6, no. 6, pp. 1061–1070.
Zacho, J., Tybjaerg-Hansen, A., Jensen, J.S., et al., Genetically elevated C-reactive protein and ischemic vascular disease, N. Engl. J. Med., 2008, vol. 359, no. 18, pp. 1897–1908.
Zinov’ev, A.Yu., Vizualizatsiya mnogomernykh dannykh (Visualization of Multidimensional Data), Krasnoyarsk Krasn. Gos. Tekhnol. Univ., 2000.
Zivkovic, A.M. and German, J.B., Metabolomics for assessment of nutritional status, Curr. Opin. Clin. Nutr. Metab. Care, 2009, vol. 12, no. 5, pp. 501–507.
Author information
Authors and Affiliations
Corresponding author
Additional information
Original Russian Text © N.V. Goncharov, A.I. Ukolov, T.I. Orlova, E.D. Migalovskaia, N.G. Voitenko, 2015, published in Uspekhi Sovremennoi Biologii, 2015, Vol. 135, No. 1, pp. 3–17.
Rights and permissions
About this article
Cite this article
Goncharov, N.V., Ukolov, A.I., Orlova, T.I. et al. Metabolomics: On the way to an integration of biochemistry, analytical chemistry, and informatics. Biol Bull Rev 5, 296–307 (2015). https://doi.org/10.1134/S2079086415040027
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1134/S2079086415040027