Abstract
Background: The field of metabolomics has been steadily increasing in size for the last 15 years. Advances in analytical and statistical methods have allowed metabolomics to flourish in various areas of medicine. Cardiovascular diseases are some of the main research targets in metabolomics, due to their social and medical relevance, and also to the important role metabolic alterations play in their pathogenesis and evolution.
Metabolomics has been applied to the full spectrum of cardiovascular diseases: from patient risk stratification to myocardial infarction and heart failure. However - despite the many proof-ofconcept studies describing the applicability of metabolomics in the diagnosis, prognosis and treatment evaluation in cardiovascular diseases - it is not yet used in routine clinical practice.
Recently, large phenome centers have been established in clinical environments, and it is expected that they will provide definitive proof of the applicability of metabolomics in clinical practice. But there is also room for small and medium size centers to work on uncommon pathologies or to resolve specific but relevant clinical questions.
Objectives: In this review, we will introduce metabolomics, cover the metabolomic work done so far in the area of cardiovascular diseases.
Conclusion: The cardiovascular field has been at the forefront of metabolomics application and it should lead the transfer to the clinic in the not so distant future.
Keywords: Metabolic profiling, metabolomics, cardiovascular diseases, 1H NMR, metabolic phenotyping, precision medicine.
[1]
Mirnezami, R.; Nicholson, J.; Darzi, A. Preparing for precision medicine. N. Engl. J. Med., 2012, 366(6), 489-491.
[2]
Nicholson, J.K.; Lindon, J.C.; Holmes, E. ‘Metabonomics’: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica, 1999, 29(11), 1181-1189.
[3]
Raamsdonk, L.M.; Teusink, B.; Broadhurst, D.; Zhang, N.; Hayes, A.; Walsh, M.C.; Berden, J.A.; Brindle, K.M.; Kell, D.B.; Rowland, J.J.; Westerhoff, H.V.; van Dam, K.; Oliver, S.G. A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations. Nat. Biotechnol., 2001, 19(1), 45-50.
[4]
Fiehn, O. “Cellular Metabolomics : The Quest for Pathway
Structure,” in The Handbook of Metabonomics and Metabolomics. , 2007; p. 35-54.
[5]
Nicholson, J.K.; Holmes, E.; Kinross, J.M.; Darzi, A.W.; Takats, Z.; Lindon, J.C. Metabolic phenotyping in clinical and surgical environments. Nature, 2012, 491(7424), 384-392.
[6]
Bales, J.R.; Higham, D.P.; Howe, I.; Nicholson, J.K.; Sadler, P.J. Use of high-resolution proton nuclear magnetic resonance spectroscopy for rapid multi-component analysis of urine. Clin. Chem., 1984, 30(3), 426-432.
[7]
Tate, A.R.R.; Griffiths, J.R.R.; Martínez-Pérez, I.; Moreno, A.; Barba, I.; Cabañas, M.E.M.E.M.E.; Watson, D.; Alonso, J.; Bartumeus, F.; Isamat, F.; Ferrer, I.; Vila, F.; Ferrer, E.; Capdevila, A.; Arús, C.; Moreno-Torres, À.; Barba, I.; Cabañas, M.E.M.E.M.E.; Watson, D.; Alonso, J.; Bartumeus, F.; Isamat, F.; Ferrer, I.; Vila, F.; Ferrer, E.; Capdevila, A.; Arús, C. Towards a method for automated classification of 1H MRS spectra from brain tumours. NMR Biomed., 1998, 11(4-5), 177-191.
[8]
Griffin, J.L.; Atherton, H.; Shockcor, J.; Atzori, L. Metabolomics as a tool for cardiac research. Nat. Rev. Cardiol., 2011, 8(11), 630-643.
[9]
Heather, L.C.; Wang, X.; West, J.A.; Griffin, J.L. A practical guide to metabolomic profiling as a discovery tool for human heart disease. J. Mol. Cell. Cardiol., 2013, 55(1), 2-11.
[10]
Kolwicz, S.C., Jr; Purohit, S.; Tian, R. Cardiac metabolism and its interactions with contraction, growth, and survival of cardiomyocytes. Circ. Res., 2013, 113(5), 603-616.
[11]
Kannel, W.B.; Dawber, T.R.; Friedman, G.D.; Glennon, W.E.; McNamara, P.M. Risk Factors in Coronary Heart Disease: An Evaluation of Several Serum Lipids as Predictors of Coronary Heart Disease: The Framingham Study. Ann. Intern. Med., 1964, 61(5), 888-899.
[12]
Barabási, A-L.; Oltvai, Z.N. Network biology: understanding the cell’s functional organization. Nat. Rev. Genet., 2004, 5(2), 101-113.
[13]
Jeong, H.; Tombor, B.; Albert, R.; Oltvai, Z.N.; Barabási, A-L. The large-scale organization of metabolic networks. Nature, 2000, 407(6804), 651-654.
[15]
Ellis, D.I.; Dunn, W.B.; Griffin, J.L.; Allwood, J.W.; Goodacre, R. Metabolic fingerprinting as a diagnostic tool. Pharmacogenomics, 2007, 8(9), 1243-1266.
[16]
Bollard, M.E.; Stanley, E.G.; Lindon, J.C.; Nicholson, J.K.; Holmes, E. NMR-based metabonomic approaches for evaluating physiological influences on biofluid composition. NMR Biomed., 2005, 18(3), 143-162.
[17]
Houtkooper, R.H.; Argmann, C.; Houten, S.M.; Cantó, C.; Jeninga, E.H.; Andreux, P.A.; Thomas, C.; Doenlen, R.; Schoonjans, K.; Auwerx, J. The metabolic footprint of aging in mice. Sci. Rep., 2011, 1, 134.
[18]
Atherton, H.J.; Gulston, M.K.; Bailey, N.J.; Cheng, K-K.; Zhang, W.; Clarke, K.; Griffin, J.L. Metabolomics of the interaction between PPAR-alpha and age in the PPAR-alpha-null mouse. Mol. Syst. Biol., 2009, 5(259), 259.
[19]
Zhang, S.; Liu, L.; Steffen, D.; Ye, T.; Raftery, D. Metabolic profiling of gender: Headspace-SPME/GC–MS and 1H NMR analysis of urine. Metabolomics, 2011, 8(2), 1-12.
[20]
Krumsiek, J.; Mittelstrass, K.; Do, K.T.; Stückler, F.; Ried, J.; Adamski, J.; Peters, A.; Illig, T.; Kronenberg, F.; Friedrich, N.; Nauck, M.; Pietzner, M.; Mook-Kanamori, D.O.; Suhre, K.; Gieger, C.; Grallert, H.; Theis, F.J.; Kastenmüller, G. Gender-specific pathway differences in the human serum metabolome. Metabolomics, 2015, 11(6), 1815-1833.
[21]
Holmes, E.; Loo, R.L.; Stamler, J.; Bictash, M.; Yap, I.K.S.; Chan, Q.; Ebbels, T.; De Iorio, M.; Brown, I.J.; Veselkov, K.A.; Daviglus, M.L.; Kesteloot, H.; Ueshima, H.; Zhao, L.; Nicholson, J.K.; Elliott, P. Human metabolic phenotype diversity and its association with diet and blood pressure. Nature, 2008, 453(7193), 396-400.
[22]
Griffin, J.L.; Wang, X.; Stanley, E. Does our gut microbiome predict cardiovascular risk? A review of the evidence from metabolomics. Circ Cardiovasc Genet, 2015, 8(1), 187-191.
[23]
Eckel, R.H.; Jakicic, J.M.; Ard, J.D.; de Jesus, J.M.; Houston Miller, N.; Hubbard, V.S.; Lee, I-M.; Lichtenstein, A.H.; Loria, C.M.; Millen, B.E.; Nonas, C.A.; Sacks, F.M.; Smith, S.C.; Svetkey, L.P.; Wadden, T.A.; Yanovski, S.Z. 2013 AHA/ACC guideline on lifestyle management to reduce cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J. Am. Coll. Cardiol, 63(25 Pt B), 2960-84.Jul;2014.
[24]
Stone, N.J.; Robinson, J.G.; Lichtenstein, A.H.; Bairey Merz, C.; Blum, C.; Goldberg, A.; Gordon, D.; Levy, D.; Lloyd-Jones, D.P. BcBride, J. Schwartz, S. Shero, S. Smith, K. Watson, and P. Wilson, “2013 ACC/AHA Guideline on the Treatment of Blood Cholesterol to Reduce Atherosclerotic Cardiovascular Disease Risk in Adults. J. Am. Coll. Cardiol., 2014, 63(25), 2889-2934.
[25]
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(5), 559-565.
[26]
Mäkinen, V-P.; Soininen, P.; Forsblom, C.; Parkkonen, M.; Ingman, P.; Kaski, K.; Groop, P-H.; Ala-Korpela, M. 1H NMR metabonomics approach to the disease continuum of diabetic complications and premature death. Mol. Syst. Biol., 2008, 4(167), 167.
[27]
McGill, H.C., Jr; McMahan, C.A.; Zieske, A.W.; Tracy, R.E.; Malcom, G.T.; Herderick, E.E.; Strong, J.P. Association of coronary heart disease risk factors with microscopic qualities of coronary atherosclerosis in youth. Circulation, 2000, 102(4), 374-379.
[29]
Krauss, R.M.; Zhu, H.; Kaddurah-Daouk, R. Pharmacometabolomics of statin response. Clin. Pharmacol. Ther., 2013, 94(5), 562-565.
[30]
Clayton, T.A.; Lindon, J.C.; Cloarec, O.; Antti, H.; Charuel, C.; Hanton, G.; Provost, J-P.P.; Le Net, J-L.L.; Baker, D.; Walley, R.J.; Everett, J.R.; Nicholson, J.K.; Andrew Clayton, T.; Lindon, J.C.; Cloarec, O.; Antti, H.; Charuel, C.; Hanton, G.; Provost, J-P.P.; Le Net, J-L.L.; Baker, D.; Walley, R.J.; Everett, J.R.; Nicholson, J.K. Pharmaco-metabonomic phenotyping and personalized drug treatment. Nature, 2006, 440(7087), 1073-1077.
[31]
Everett, J.R.; Loo, R.L.; Pullen, F.S. Pharmacometabonomics and personalized medicine. Ann. Clin. Biochem., 2013, 50(Pt 6), 523-545.
[32]
Trupp, M.; Zhu, H.; Wikoff, W.R.; Baillie, R.A.; Zeng, Z.B.; Karp, P.D.; Fiehn, O.; Krauss, R.M.; Kaddurah-Daouk, R. Metabolomics reveals amino acids contribute to variation in response to simvastatin treatment. PLoS One, 2012, 7(7), e38386.
[33]
Bollard, M.E.; Murray, A.J.; Clarke, K.; Nicholson, J.K.; Griffin, J.L. A study of metabolic compartmentation in the rat heart and cardiac mitochondria using high-resolution magic angle spinning 1H NMR spectroscopy. FEBS Lett., 2003, 553(1-2), 73-78.
[34]
Barba, I.; Jaimez-Auguets, E.; Rodriguez-Sinovas, A.; Garcia-Dorado, D. 1H NMR-based metabolomic identification of at-risk areas after myocardial infarction in swine. MAGMA, 2007, 20(5-6), 265-271.
[35]
Takeda, I.; Stretch, C.; Barnaby, P.; Bhatnager, K.; Rankin, K.; Fu, H.; Weljie, A.; Jha, N.; Slupsky, C. Understanding the human salivary metabolome. NMR Biomed., 2009, 22(6), 577-584.
[36]
Barba, I.; Garcia-Ramírez, M.; Hernández, C.; Alonso, M.A.; Masmiquel, L.; García-Dorado, D.; Simó, R. Metabolic fingerprints of proliferative diabetic retinopathy: an 1H-NMR-based metabonomic approach using vitreous humor. Invest. Ophthalmol. Vis. Sci., 2010, 51(9), 4416-4421.
[37]
Lutz, N.W.; Viola, A.; Malikova, I.; Confort-Gouny, S.; Audoin, B.; Ranjeva, J.P.; Pelletier, J.; Cozzone, P.J. Inflammatory multiple-sclerosis plaques generate characteristic metabolic profiles in cerebrospinal fluid. PLoS One, 2007, 2(7), e595.
[38]
Li, S.; Todor, A.; Luo, R. Blood transcriptomics and metabolomics for personalized medicine. Comput. Struct. Biotechnol. J., 2015, 14, 1-7.
[39]
Psychogios, N.; Hau, D.D.; Peng, J.; Guo, A.C.; Mandal, R.; Bouatra, S.; Sinelnikov, I.; Krishnamurthy, R.; Eisner, R.; Gautam, B.; Young, N.; Xia, J.; Knox, C.; Dong, E.; Huang, P.; Hollander, Z.; Pedersen, T.L.; Smith, S.R.; Bamforth, F.; Greiner, R.; McManus, B.; Newman, J.W.; Goodfriend, T.; Wishart, D.S. The human serum metabolome. PLoS One, 2011, 6(2), e16957.
[40]
Bouatra, S.; Aziat, F.; Mandal, R.; Guo, A.C.; Wilson, M.R.; Knox, C.; Bjorndahl, T.C.; Krishnamurthy, R.; Saleem, F.; Liu, P.; Dame, Z.T.; Poelzer, J.; Huynh, J.; Yallou, F.S.; Psychogios, N.; Dong, E.; Bogumil, R.; Roehring, C.; Wishart, D.S. The human urine metabolome. PLoS One, 2013, 8(9), e73076.
[41]
Awonusonu, F.; Srinivasan, S.; Strange, J.; Al-Jumaily, W.; Bruce, M.C. Developmental shift in the relative percentages of lung fibroblast subsets: role of apoptosis postseptation. Am. J. Physiol., 1999, 277(4 Pt 1), L848-L859.
[42]
Shah, S.H.; Hauser, E.R.; Bain, J.R.; Muehlbauer, M.J.; Haynes, C.; Stevens, R.D.; Wenner, B.R.; Dowdy, Z.E.; Granger, C.B.; Ginsburg, G.S.; Newgard, C.B.; Kraus, W.E. High heritability of metabolomic profiles in families burdened with premature cardiovascular disease. Mol. Syst. Biol., 2009, 5(258), 258.
[43]
Gieger, C.; Geistlinger, L.; Altmaier, E.; Hrabé de Angelis, M.; Kronenberg, F.; Meitinger, T.; Mewes, H.W.; Wichmann, H.E.; Weinberger, K.M.; Adamski, J.; Illig, T.; Suhre, K. Genetics meets metabolomics: a genome-wide association study of metabolite profiles in human serum. PLoS Genet., 2008, 4(11), e1000282.
[44]
Hartiala, J.A.; Tang, W.H.W.; Wang, Z.; Crow, A.L.; Stewart, A.F.R.; Roberts, R.; McPherson, R.; Erdmann, J.; Willenborg, C.; Hazen, S.L.; Allayee, H. Genome-wide association study and targeted metabolomics identifies sex-specific association of CPS1 with coronary artery disease. Nat. Commun., 2016, 7, 10558.
[45]
Mayr, M.; Chung, Y-L.; Mayr, U.; Yin, X.; Ly, L.; Troy, H.; Fredericks, S.; Hu, Y.; Griffiths, J.R.; Xu, Q. Proteomic and metabolomic analyses of atherosclerotic vessels from apolipoprotein E-deficient mice reveal alterations in inflammation, oxidative stress, and energy metabolism. Arterioscler. Thromb. Vasc. Biol., 2005, 25(10), 2135-2142.
[46]
Mayr, M.; Madhu, B.; Xu, Q. Proteomics and metabolomics combined in cardiovascular research. Trends Cardiovasc. Med., 2007, 17(2), 43-48.
[47]
Mayr, M.; Siow, R.; Chung, Y.L.; Mayr, U.; Griffiths, J.R.; Xu, Q. Proteomic and metabolomic analysis of vascular smooth muscle cells: role of PKCdelta. Circ. Res., 2004, 94(10), e87-e96.
[48]
Griffin, J.L.; Des Rosiers, C. Applications of metabolomics and proteomics to the mdx mouse model of Duchenne muscular dystrophy: lessons from downstream of the transcriptome. Genome Med., 2009, 1(3), 32.
[49]
Inserte, J.; Barba, I.; Hernando, V.; Garcia-Dorado, D. Delayed recovery of intracellular acidosis during reperfusion prevents calpain activation and determines protection in postconditioned myocardium. Cardiovasc. Res., 2009, 81(1), 116-122.
[50]
Fan, T.W-M.; Lane, A.N. NMR-based stable isotope resolved metabolomics in systems biochemistry. J. Biomol. NMR, 2011, 49(3-4), 267-280.
[51]
Bothwell, J.H.F.; Griffin, J.L. An introduction to biological nuclear magnetic resonance spectroscopy. Biol. Rev. Camb. Philos. Soc., 2011, 86(2), 493-510.
[52]
Barba, I.; de León, G.; Martín, E.; Cuevas, A.; Aguade, S.; Candell-Riera, J.; Barrabés, J.A.; Garcia-Dorado, D.; De León, G.; Martín, E.; Cuevas, A.; Aguade, S.; Candell-Riera, J.; Barrabés, J.A.; Garcia-Dorado, D.; de Leon, G.; Martin, E.; Cuevas, A.; Aguade, S.; Candell-Riera, J.; Barrabes, J.A.; Garcia-Dorado, D. Nuclear magnetic resonance-based metabolomics predicts exercise-induced ischemia in patients with suspected coronary artery disease. Magn. Reson. Med., 2008, 60(1), 27-32.
[53]
Mallol, R.; Rodriguez, M.A.; Brezmes, J.; Masana, L.; Correig, X. Human serum/plasma lipoprotein analysis by NMR: application to the study of diabetic dyslipidemia. Prog. Nucl. Magn. Reson. Spectrosc., 2013, 70, 1-24.
[54]
Goonewardena, S.N.; Prevette, L.E.; Desai, A.A. Metabolomics and atherosclerosis. Curr. Atheroscler. Rep., 2010, 12(4), 267-272.
[55]
Gowda, G.A.; Zhang, S.; Gu, H.; Asiago, V.; Shanaiah, N.; Raftery, D. Metabolomics-based methods for early disease diagnostics. Expert Rev. Mol. Diagn., 2008, 8(5), 617-633.
[56]
Crutchfield, C.A.; Thomas, S.N.; Sokoll, L.J.; Chan, D.W. Advances in mass spectrometry-based clinical biomarker discovery. Clin. Proteomics, 2016, 13, 1-12.
[57]
Näsström, E.; Vu Thieu, N.T.; Dongol, S.; Karkey, A.; Voong Vinh, P.; Ha Thanh, T.; Johansson, A.; Arjyal, A.; Thwaites, G.; Dolecek, C.; Basnyat, B.; Baker, S.; Antti, H. Salmonella Typhi and Salmonella Paratyphi A elaborate distinct systemic metabolite signatures during enteric fever. eLife, 2014, 3, 1-19.
[58]
Beckonert, O.; Keun, H.C.; Ebbels, T.M.D.; Bundy, J.; Holmes, E.; Lindon, J.C.; Nicholson, J.K. Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Nat. Protoc., 2007, 2(11), 2692-2703.
[59]
Dunn, W.B.; Broadhurst, D.; Begley, P.; Zelena, E.; Francis-McIntyre, S.; Anderson, N.; Brown, M.; Knowles, J.D.; Halsall, A.; Haselden, J.N.; Nicholls, A.W.; Wilson, I.D.; Kell, D.B.; Goodacre, R. Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry. Nat. Protoc., 2011, 6(7), 1060-1083.
[60]
Haug, K.; Salek, R.M.; Conesa, P.; Hastings, J.; de Matos, P.; Rijnbeek, M.; Mahendraker, T.; Williams, M.; Neumann, S.; Rocca-Serra, P.; Maguire, E.; González-Beltrán, A.; Sansone, S.A.; Griffin, J.L.; Steinbeck, C. MetaboLights--an open-access general-purpose repository for metabolomics studies and associated meta-data. Nucleic Acids Res., 2013, 41(Database issue), D781-D786.
[61]
Rocca-Serra, P.; Salek, R.M.; Arita, M.; Correa, E.; Dayalan, S.; Gonzalez-Beltran, A.; Ebbels, T.; Goodacre, R.; Hastings, J.; Haug, K.; Koulman, A.; Nikolski, M.; Oresic, M.; Sansone, S.A.; Schober, D.; Smith, J.; Steinbeck, C.; Viant, M.R.; Neumann, S. Data standards can boost metabolomics research, and if there is a will, there is a way. Metabolomics, 2016, 12(1), 14.
[62]
Lewis, G.D.; Wei, R.; Liu, E.; Yang, E.; Shi, X.; Martinovic, M.; Farrell, L.; Asnani, A.; Cyrille, M.; Ramanathan, A.; Shaham, O.; Berriz, G.; Lowry, P.A.; Palacios, I.F.; Taşan, M.; Roth, F.P.; Min, J.; Baumgartner, C.; Keshishian, H.; Addona, T.; Mootha, V.K.; Rosenzweig, A.; Carr, S.A.; Fifer, M.A.; Sabatine, M.S.; Gerszten, R.E. Metabolite profiling of blood from individuals undergoing planned myocardial infarction reveals early markers of myocardial injury. J. Clin. Invest., 2008, 118(10), 3503-3512.
[63]
Szymańska, E.; Saccenti, E.; Smilde, A.K.; Westerhuis, J.A. Double-check: validation of diagnostic statistics for PLS-DA models in metabolomics studies. Metabolomics, 2012, 8(1)(Suppl. 1), 3-16.
[64]
Nyamundanda, G.; Gormley, I.C.; Fan, Y.; Gallagher, W.M.; Brennan, L. MetSizeR: selecting the optimal sample size for metabolomic studies using an analysis based approach. BMC Bioinformatics, 2013, 14, 338.
[65]
Xia, J.; Sinelnikov, I.V.; Han, B.; Wishart, D.S. MetaboAnalyst 3.0--making metabolomics more meaningful. Nucleic Acids Res., 2015, 43(W1), W251-7.
[66]
Dunn, W.B.; Lin, W.; Broadhurst, D.; Begley, P.; Brown, M.; Zelena, E.; Vaughan, A.A.; Halsall, A.; Harding, N.; Knowles, J.D.; Francis-McIntyre, S.; Tseng, A.; Ellis, D.I.; O’Hagan, S.; Aarons, G.; Benjamin, B.; Chew-Graham, S.; Moseley, C.; Potter, P.; Winder, C.L.; Potts, C.; Thornton, P.; McWhirter, C.; Zubair, M.; Pan, M.; Burns, A.; Cruickshank, J.K.; Jayson, G.C.; Purandare, N.; Wu, F.C.W.; Finn, J.D.; Haselden, J.N.; Nicholls, A.W.; Wilson, I.D.; Goodacre, R.; Kell, D.B. Molecular phenotyping of a UK population: defining the human serum metabolome. Metabolomics, 2015, 11(1), 9-26.
[67]
Brindle, J.T.; Antti, H.; Holmes, E.; Tranter, G.; Nicholson, J.K.; Bethell, H.W.L.; Clarke, S.; Schofield, P.M.; McKilligin, E.; Mosedale, D.E.; Grainger, D.J. Rapid and noninvasive diagnosis of the presence and severity of coronary heart disease using 1H-NMR-based metabonomics. Nat. Med., 2002, 8(12), 1439-1444.
[68]
Sansbury, B.E.; DeMartino, A.M.; Xie, Z.; Brooks, A.C.; Brainard, R.E.; Watson, L.J.; DeFilippis, A.P.; Cummins, T.D.; Harbeson, M.A.; Brittian, K.R.; Prabhu, S.D.; Bhatnagar, A.; Jones, S.P.; Hill, B.G. Metabolomic analysis of pressure-overloaded and infarcted mouse hearts. Circ Heart Fail, 2014, 7(4), 634-642.
[69]
Tenori, L.; Hu, X.; Pantaleo, P.; Alterini, B.; Castelli, G.; Olivotto, I.; Bertini, I.; Luchinat, C.; Gensini, G.F. Metabolomic fingerprint of heart failure in humans: a nuclear magnetic resonance spectroscopy analysis. Int. J. Cardiol., 2013, 168(4), e113-e115.
[70]
Heather, L.C.; Pates, K.M.; Atherton, H.J.; Cole, M.A.; Ball, D.R.; Evans, R.D.; Glatz, J.F.; Luiken, J.J.; Griffin, J.L.; Clarke, K. Differential translocation of the fatty acid transporter, FAT/CD36, and the glucose transporter, GLUT4, coordinates changes in cardiac substrate metabolism during ischemia and reperfusion. Circ Heart Fail, 2013, 6(5), 1058-1066.
[71]
Valls-Lacalle, L.; Barba, I.; Miró-Casas, E.; Alburquerque-Béjar, J.J.; Ruiz-Meana, M.; Fuertes-Agudo, M.; Rodríguez-Sinovas, A.; García-Dorado, D.; Juan José Alburquerque-Béjar, M. Succinate dehydrogenase inhibition with malonate during reperfusion reduces infarct size by preventing mitochondrial permeability transition. Cardiovasc. Res., 2016, 109(3), 374-384. [Succinate.].
[72]
Atherton, H.J.; Bailey, N.J.; Zhang, W.; Taylor, J.; Major, H.; Shockcor, J.; Clarke, K.; Griffin, J.L. A combined 1H-NMR spectroscopy- and mass spectrometry-based metabolomic study of the PPAR-alpha null mutant mouse defines profound systemic changes in metabolism linked to the metabolic syndrome. Physiol. Genomics, 2006, 27(2), 178-186.
[73]
Rodríguez-Sinovas, A.; Sánchez, J.A.; González-Loyola, A.; Barba, I.; Morente, M.; Aguilar, R.; Agulló, E.; Miró-Casas, E.; Esquerda, N.; Ruiz-Meana, M.; García-Dorado, D. Effects of substitution of Cx43 by Cx32 on myocardial energy metabolism, tolerance to ischaemia and preconditioning protection. J. Physiol., 2010, 588(Pt 7), 1139-1151.
[74]
Jones, G.L.A.H.; Sang, E.; Goddard, C.; Mortishire-Smith, R.J.; Sweatman, B.C.; Haselden, J.N.; Davies, K.; Grace, A.A.; Clarke, K.; Griffin, J.L. A functional analysis of mouse models of cardiac disease through metabolic profiling. J. Biol. Chem., 2005, 280(9), 7530-7539.
[75]
Sankaralingam, S.; Lopaschuk, G.D. Cardiac energy metabolic alterations in pressure overload-induced left and right heart failure (2013 Grover Conference Series). Pulm. Circ., 2015, 5(1), 15-28.
[76]
Beer, M.; Seyfarth, T.; Sandstede, J.; Landschütz, W.; Lipke, C.; Köstler, H.; von Kienlin, M.; Harre, K.; Hahn, D.; Neubauer, S. Absolute concentrations of high-energy phosphate metabolites in normal, hypertrophied, and failing human myocardium measured noninvasively with (31)P-SLOOP magnetic resonance spectroscopy. J. Am. Coll. Cardiol., 2002, 40(7), 1267-1274.
[77]
Lopaschuk, G.D.; Ussher, J.R.; Folmes, C.D.L.; Jaswal, J.S.; Stanley, W.C. Myocardial fatty acid metabolism in health and disease. Physiol. Rev., 2010, 90(1), 207-258.
[78]
Kang, S.M.; Park, J.C.; Shin, M.J.; Lee, H.; Oh, J.; Ryu, D.H.; Hwang, G.S.; Chung, J.H. 1H nuclear magnetic resonance based metabolic urinary profiling of patients with ischemic heart failure. Clin. Biochem., 2011, 44(4), 293-299.
[79]
Du, Z.; Shen, A.; Huang, Y.; Su, L.; Lai, W.; Wang, P.; Xie, Z.; Xie, Z.; Zeng, Q.; Ren, H.; Xu, D. 1H-NMR-based metabolic analysis of human serum reveals novel markers of myocardial energy expenditure in heart failure patients. PLoS One, 2014, 9(2), e88102.
[80]
Chouchani, E.T.; Pell, V.R.; Gaude, E.; Aksentijević, D.; Sundier, S.Y.; Robb, E.L.; Logan, A.; Nadtochiy, S.M.; Ord, E.N.J.; Smith, A.C.; Eyassu, F.; Shirley, R.; Hu, C-H.; Dare, A.J.; James, A.M.; Rogatti, S.; Hartley, R.C.; Eaton, S.; Costa, A.S.H.; Brookes, P.S.; Davidson, S.M.; Duchen, M.R.; Saeb-Parsy, K.; Shattock, M.J.; Robinson, A.J.; Work, L.M.; Frezza, C.; Krieg, T.; Murphy, M.P. Ischaemic accumulation of succinate controls reperfusion injury through mitochondrial ROS. Nature, 2014, 515(7527), 431-435.
[81]
Turer, A.T. Using metabolomics to assess myocardial metabolism and energetics in heart failure. J. Mol. Cell. Cardiol., 2013, 55(1), 12-18.
[82]
Zordoky, B.N.; Sung, M.M.; Ezekowitz, J.; Mandal, R.; Han, B.; Bjorndahl, T.C.; Bouatra, S.; Anderson, T.; Oudit, G.Y.; Wishart, D.S.; Dyck, J.R.B. Metabolomic fingerprint of heart failure with preserved ejection fraction. PLoS One, 2015, 10(5), e0124844.
[83]
Cheng, M-L.L.; Wang, C-H.H.; Shiao, M-S.S.; Liu, M-H.H.; Huang, Y-Y.Y.; Huang, C-Y.Y.; Mao, C-T.T.; Lin, J-F.F.; Ho, H-Y.Y.; Yang, N-I.I. Metabolic disturbances identified in plasma are associated with outcomes in patients with heart failure: diagnostic and prognostic value of metabolomics. J. Am. Coll. Cardiol., 2015, 65(15), 1509-1520.
[84]
Padeletti, L.; Modesti, P.A.; Cartei, S.; Checchi, L.; Ricciardi, G.; Pieragnolia, P.; Sacchi, S.; Padeletti, M.; Alterini, B.; Pantaleo, P.; Hu, X.; Tenori, L.; Luchinat, C. Metabolomic does not predict response to cardiac resynchronization therapy in patients with heart failure. J. Cardiovasc. Med. (Hagerstown), 2014, 15(4), 295-300.
[85]
Sabatine, M.S.; Liu, E.; Morrow, D.A.; Heller, E.; McCarroll, R.; Wiegand, R.; Berriz, G.F.; Roth, F.P.; Gerszten, R.E. Metabolomic identification of novel biomarkers of myocardial ischemia. Circulation, 2005, 112(25), 3868-3875.
[86]
Rasmiena, A.A.; Ng, T.W.; Meikle, P.J. Metabolomics and ischaemic heart disease. Clin. Sci. (Lond.), 2013, 124(5), 289-306.
[87]
Bodí, V.; Sanchis, J.; Morales, J.M.; Marrachelli, V.G.; Nunez, J.; Forteza, M.J.; Chaustre, F.; Gomez, C.; Mainar, L.; Minana, G.; Rumiz, E.; Husser, O.; Noguera, I.; Diaz, A.; Moratal, D.; Carratala, A.; Bosch, X.; Llacer, A.; Chorro, F.J.; Viña, J.R.; Monleon, D. Metabolomic profile of human myocardial ischemia by nuclear magnetic resonance spectroscopy of peripheral blood serum: a translational study based on transient coronary occlusion models. J. Am. Coll. Cardiol., 2012, 59(18), 1629-1641.
[88]
Turer, A.T.; Stevens, R.D.; Bain, J.R.; Muehlbauer, M.J.; van der Westhuizen, J.; Mathew, J.P.; Schwinn, D.A.; Glower, D.D.; Newgard, C.B.; Podgoreanu, M.V. Metabolomic profiling reveals distinct patterns of myocardial substrate use in humans with coronary artery disease or left ventricular dysfunction during surgical ischemia/reperfusion. Circulation, 2009, 119(13), 1736-1746.
[89]
Kirschenlohr, H.L.; Griffin, J.L.; Clarke, S.C.; Rhydwen, R.; Grace, A.A.; Schofield, P.M.; Brindle, K.M.; Metcalfe, J.C. Proton NMR analysis of plasma is a weak predictor of coronary artery disease. Nat. Med., 2006, 12(6), 705-710.
[90]
Shah, A.A.; Craig, D.M.; Sebek, J.K.; Haynes, C.; Stevens, R.C.; Muehlbauer, M.J.; Granger, C.B.; Hauser, E.R.; Newby, L.K.; Newgard, C.B.; Kraus, W.E.; Hughes, G.C.; Shah, S.H. Metabolic profiles predict adverse events after coronary artery bypass grafting. J. Thorac. Cardiovasc. Surg., 2012, 143(4), 873-878.
[91]
Würtz, P.; Havulinna, A.S.; Soininen, P.; Tynkkynen, T.; Prieto-Merino, D.; Tillin, T.; Ghorbani, A.; Artati, A.; Wang, Q.; Tiainen, M.; Kangas, A.J.; Kettunen, J.; Kaikkonen, J.; Mikkilä, V.; Jula, A.; Kähönen, M.; Lehtimäki, T.; Lawlor, D.A.; Gaunt, T.R.; Hughes, A.D.; Sattar, N.; Illig, T.; Adamski, J.; Wang, T.J.; Perola, M.; Ripatti, S.; Vasan, R.S.; Raitakari, O.T.; Gerszten, R.E.; Casas, J-P.; Chaturvedi, N.; Ala-Korpela, M.; Salomaa, V. Metabolite profiling and cardiovascular event risk: a prospective study of 3 population-based cohorts. Circulation, 2015, 131(9), 774-785.
[92]
Borodulin, K.; Vartiainen, E.; Peltonen, M.; Jousilahti, P.; Juolevi, A.; Laatikainen, T.; Mannisto, S.; Salomaa, V.; Sundvall, J.; Puska, P. Forty-year trends in cardiovascular risk factors in Finland. Eur. J. Public Health, 2014, 39(2), 504-518.
[93]
Tillin, T.; Forouhi, N.G.; McKeigue, P.M.; Chaturvedi, N. Southall And Brent REvisited: Cohort profile of SABRE, a UK population-based comparison of cardiovascular disease and diabetes in people of European, Indian Asian and African Caribbean origins. Int. J. Epidemiol., 2012, 41(1), 33-42.
[94]
Lawlor, D.A.; Bedford, C.; Taylor, M.; Ebrahim, S. Geographical variation in cardiovascular disease, risk factors, and their control in older women: British Women’s Heart and Health Study. J. Epidemiol. Community Health, 2003, 57(2), 134-140.
[95]
Cheng, S.; Rhee, E.P.; Larson, M.G.; Lewis, G.D.; McCabe, E.L.; Shen, D.; Palma, M.J.; Roberts, L.D.; Dejam, A.; Souza, A.L.; Deik, A.A.; Magnusson, M.; Fox, C.S.; O’Donnell, C.J.; Vasan, R.S.; Melander, O.; Clish, C.B.; Gerszten, R.E.; Wang, T.J. Metabolite profiling identifies pathways associated with metabolic risk in humans. Circulation, 2012, 125(18), 2222-2231.
[96]
Ganna, A.; Salihovic, S.; Sundström, J.; Broeckling, C.D.; Hedman, A.K.; Magnusson, P.K.E.; Pedersen, N.L.; Larsson, A.; Siegbahn, A.; Zilmer, M.; Prenni, J.; Arnlöv, J.; Lind, L.; Fall, T.; Ingelsson, E. Large-scale metabolomic profiling identifies novel biomarkers for incident coronary heart disease. PLoS Genet., 2014, 10(12), e1004801.
[97]
Basak, T.; Varshney, S.; Hamid, Z.; Ghosh, S.; Seth, S.; Sengupta, S. “Identification of metabolic markers in coronary
artery disease using an untargeted LC-MS based metabolomic
approach,” J. Proteomics, , 127, , (Pt A), 169-177.
[98]
Stegemann, C.; Pechlaner, R.; Willeit, P.; Langley, S.R.; Mangino, M.; Mayr, U.; Menni, C.; Moayyeri, A.; Santer, P.; Rungger, G.; Spector, T.D.; Willeit, J.; Kiechl, S.; Mayr, M. Lipidomics profiling and risk of cardiovascular disease in the prospective population-based Bruneck study. Circulation, 2014, 129(18), 1821-1831.
[99]
Ala-Korpela, M. Critical evaluation of 1H NMR metabonomics of serum as a methodology for disease risk assessment and diagnostics. Clin. Chem. Lab. Med., 2008, 46(1), 27-42.
[100]
Shah, S.H.; Bain, J.R.; Muehlbauer, M.J.; Stevens, R.D.; Crosslin, D.R.; Haynes, C.; Dungan, J.; Newby, L.K.; Hauser, E.R.; Ginsburg, G.S.; Newgard, C.B.; Kraus, W.E. Association of a peripheral blood metabolic profile with coronary artery disease and risk of subsequent cardiovascular events. Circ Cardiovasc Genet, 2010, 3(2), 207-214.
[101]
Shah, S.H.; Sun, J-L.; Stevens, R.D.; Bain, J.R.; Muehlbauer, M.J.; Pieper, K.S.; Haynes, C.; Hauser, E.R.; Kraus, W.E.; Granger, C.B.; Newgard, C.B.; Califf, R.M.; Newby, L.K. Baseline metabolomic profiles predict cardiovascular events in patients at risk for coronary artery disease. Am. Heart J., 2012, 163(5), 844-850.e1.
[102]
Dunn, W.B.; Goodacre, R.; Neyses, L.; Mamas, M. Integration of metabolomics in heart disease and diabetes research: current achievements and future outlook. Bioanalysis, 2011, 3(19), 2205-2222.
[104]
Klein, M.S.; Shearer, J. Metabolomics and Type 2 Diabetes: Translating Basic Research into Clinical Application. J. Diabetes Res., 2016, 2016, 3898502.
[105]
Lindon, J.C.; Nicholson, J.K. The emergent role of metabolic phenotyping in dynamic patient stratification. Expert Opin. Drug Metab. Toxicol., 2014, 10(7), 915-919.
[106]
Soininen, P.; Kangas, A.J.; Würtz, P.; Suna, T.; Ala-Korpela, M. Quantitative serum nuclear magnetic resonance metabolomics in cardiovascular epidemiology and genetics. Circ Cardiovasc Genet, 2015, 8(1), 192-206.
[107]
Markley, J.L.; Brüschweiler, R.; Edison, A.S.; Eghbalnia, H.R.; Powers, R.; Raftery, D.; Wishart, D.S. The future of NMR-based metabolomics. Curr. Opin. Biotechnol., 2017, 43, 34-40.
[108]
Tzoulaki, I.; Ebbels, T.M.D.; Valdes, A.; Elliott, P.; Ioannidis, J.P.A. Design and analysis of metabolomics studies in epidemiologic research: a primer on -Omic technologies. Am. J. Epidemiol., 2014, 180(2), 129-139.
[109]
Sharkey, S.W.; Maron, B.J. Epidemiology and clinical profile of Takotsubo cardiomyopathy. Circ. J., 2014, 78(9), 2119-2128.
[110]
Komamura, K.; Fukui, M.; Iwasaku, T.; Hirotani, S.; Masuyama, T. Takotsubo cardiomyopathy: Pathophysiology, diagnosis and treatment. World J. Cardiol., 2014, 6(7), 602-609.
[111]
Eitel, I.; von Knobelsdorff-Brenkenhoff, F.; Bernhardt, P.; Carbone, I.; Muellerleile, K.; Aldrovandi, A.; Francone, M.; Desch, S.; Gutberlet, M.; Strohm, O.; Schuler, G.; Schulz-Menger, J.; Thiele, H.; Friedrich, M.G. Clinical characteristics and cardiovascular magnetic resonance findings in stress (takotsubo) cardiomyopathy. JAMA, 2011, 306(3), 277-286.
[112]
Wittstein, I.S.; Thiemann, D.R.; Lima, J.A.; Baughman, K.L.; Schulman, S.P.; Gerstenblith, G.; Wu, K.C.; Rade, J.J.; Bivalacqua, T.J.; Champion, H.C. Neurohumoral features of myocardial stunning due to sudden emotional stress. N. Engl. J. Med., 2005, 352(6), 539-548.
[114]
Novo, S.; Peritore, A.; Trovato, R.L.; Guarneri, F.P.; Di Lisi, D.; Muratori, I.; Novo, G. Preclinical atherosclerosis and metabolic syndrome increase cardio- and cerebrovascular events rate: a 20-year follow up. Cardiovasc. Diabetol., 2013, 12(1), 155.
[115]
Koskinen, J.; Kähönen, M.; Viikari, J. S. A. Conventional Cardiovascular Risk Factors and Metabolic Syndrome in Predicting Carotid Intima-Media Thickness Progression in Young Adults The Cardiovascular Risk in Young Finns Study, 2009.
[116]
Balog, J.; Sasi-Szabó, L.; Kinross, J.; Lewis, M.R.; Muirhead, L.J.; Veselkov, K.; Mirnezami, R.; Dezső, B.; Damjanovich, L.; Darzi, A.; Nicholson, J.K.; Takáts, Z. Intraoperative tissue identification using rapid evaporative ionization mass spectrometry. Sci. Transl. Med., 2013, 5(194), 194ra93.
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