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Role of metabolomics in identifying cardiac hypertrophy: an overview of the past 20 years of development and future perspective

Published online by Cambridge University Press:  11 August 2021

Sachendra Pratap Singh
Affiliation:
Centre of Biomedical Research, SGPGIMS Campus, Lucknow, India Department of Cardiology, King George's Medical University, Lucknow, India
Rishi Sethi
Affiliation:
Department of Cardiology, King George's Medical University, Lucknow, India
Shailendra Kumar Saxena
Affiliation:
Centre for Advance Research, King George's Medical University, Lucknow, India
Ashish Gupta*
Affiliation:
Centre of Biomedical Research, SGPGIMS Campus, Lucknow, India
*
Author for correspondence: Ashish Gupta, E-mail: ashishg24@yahoo.co.in

Abstract

Cardiac hypertrophy (CH) is an augmentation of either the right ventricular or the left ventricular mass in order to compensate for the increase of work load on the heart. Metabolic abnormalities lead to histological changes of cardiac myocytes and turn into CH. The molecular mechanisms that lead to initiate CH have been of widespread concern, hence the development of the new field of research, metabolomics: one ‘omics’ approach that can reveal comprehensive information of the paradigm shift of metabolic pathways network in contrast to individual enzymatic reaction-based metabolites, have attempted and until now only 19 studies have been conducted using experimental animal and human specimens. Nuclear magnetic resonance spectroscopy and mass spectrometry-based metabolomics studies have found that CH is a metabolic disease and is mainly linked to the harmonic imbalance of glycolysis, citric acid cycle, amino acids and lipid metabolism. The current review will summarise the main outcomes of the above mentioned 19 studies that have expanded our understanding of the molecular mechanisms that may lead to CH and eventually to heart failure.

Type
Review
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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References

Benjamin, EJ et al. (2019) American heart association council on epidemiology and prevention statistics committee and stroke statistics subcommittee. Heart disease and stroke statistics-2019 update: a report from the American Heart Association. Circulation 139, e56e528.CrossRefGoogle ScholarPubMed
Rapsomaniki, E et al. (2014) Blood pressure and incidence of twelve cardiovascular diseases: lifetime risks, healthy life-years lost, and age-specific associations in 1.25 million people. Lancet 383, 18991911.CrossRefGoogle ScholarPubMed
SPRINT Research group et al. (2015) A randomized trial of intensive versus standard blood-pressure control. New England Journal of Medicine 373, 2103–216.CrossRefGoogle Scholar
Whelton, PK et al. (2018) 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: executive summary. Journal of the American Society of Hypertension: JASH 12:579.e1579.e73.CrossRefGoogle ScholarPubMed
Nadar, SK et al. (2006) Target organ damage in hypertension: pathophysiology and implications for drug therapy. Current Pharmaceutical Design 12, 15811592.CrossRefGoogle ScholarPubMed
McMullen, JR et al. (2007) Differences between pathological and physiological cardiac hypertrophy: novel therapeutic strategies to treat heart failure. Clinical and Experimental Pharmacology and Physiology 34, 255262.CrossRefGoogle ScholarPubMed
Popescu, LM et al. (2006) Insights into the interstitium of ventricular myocardium: interstitial Cajallike cells (ICLC). Journal of Cellular and Molecular Medicine 10, 429458.CrossRefGoogle Scholar
McMurray, JJ et al. (2005) Heart failure. Lancet 365, 18771889.CrossRefGoogle ScholarPubMed
Pluim, BM et al. (2000) The athlete's heart. A meta-analysis of cardiac structure and function. Circulation 101, 336344.CrossRefGoogle ScholarPubMed
Grossman, W et al. (1975) Wall stress and patterns of hypertrophy in the human left ventricle. Journal of Clinical Investigation 56, 5664.CrossRefGoogle ScholarPubMed
Berenji, K et al. (2005) Does load-induced ventricular hypertrophy progress to systolic heart failure? American Journal of Physiology. Heart and Circulatory Physiology 289, H8H16.CrossRefGoogle ScholarPubMed
Eghbali, M et al. (2005) Molecular and functional signature of heart hypertrophy during pregnancy. Circulation Research 96, 12081216.CrossRefGoogle ScholarPubMed
Gunasinghe, SK et al. (2004) Myocardial basis for heart failure. In Mann, DL (ed.), Role of the Cardiac Interstitium Heart Failure. Philadelphia: Saunders, pp. 5770.Google Scholar
Iemitsu, M et al. (2001) Physiological and pathological cardiac hypertrophy induce different molecular phenotypes in the rat. American Journal of Physiology. Regulatory, Integrative and Comparative Physiology 281, R20292036.CrossRefGoogle ScholarPubMed
Saxton, RA et al. (2017) mTOR signalling in growth, metabolism, and disease. Cell 168, 960976.CrossRefGoogle Scholar
Sciarretta, S et al. (2018) New insights into the role of mTOR signalling in the cardiovascular system. Circulation Research 122, 489505.CrossRefGoogle Scholar
Zhang, D et al. (2010) mTORC1 regulates cardiac function and myocyte survival through 4E-BP1 inhibition in mice. Journal of Clinical Investigation 120, 28052816.CrossRefGoogle ScholarPubMed
Sadoshima, J et al. (1995) Rapamycin selectively inhibits angiotensin II-induced increase in protein synthesis in cardiac myocytes in vitro. Potential role of 70-kD S6 kinase in angiotensin II-induced cardiac hypertrophy. Circulation Research 77, 10401052.CrossRefGoogle ScholarPubMed
Shioi, T et al. (2003) Rapamycin attenuates load-induced cardiac hypertrophy in mice. Circulation 107, 16641670.CrossRefGoogle ScholarPubMed
McMullen, JR et al. (2004) Deletion of ribosomal S6 kinases does not attenuate pathological, physiological, or insulin-like growth factor 1 receptor-phosphoinositide 3-kinase-induced cardiac hypertrophy. Molecular and Cellular Biology 24, 62316240.CrossRefGoogle ScholarPubMed
Sciarretta, S et al. (2015) mTORC2 regulates cardiac response to stress by inhibiting MST1. Cell Reports 11, 125136.CrossRefGoogle ScholarPubMed
Horman, S et al. (2012) AMP-activated protein kinase in the control of cardiac metabolism and remodelling. Current Heart Failure Reports 9, 164173.CrossRefGoogle Scholar
Shibata, R et al. (2004) Adiponectin-mediated modulation of hypertrophic signals in the heart. Nature Medicine 10, 13841389.CrossRefGoogle ScholarPubMed
Zarrinpashneh, E et al. (2008) AMPKα2 counteracts the development of cardiac hypertrophy induced by isoproterenol. Biochemical and Biophysical Research Communications 376, 677681.CrossRefGoogle ScholarPubMed
Zhang, P et al. (2008) AMP activated protein kinase-α2 deficiency exacerbates pressure-overload-induced left ventricular hypertrophy and dysfunction in mice. Hypertension 52, 918924.CrossRefGoogle ScholarPubMed
Sakamoto, K et al. (2006) Deficiency of LKB1 in heart prevents ischemia-mediated activation of AMPKα2 but not AMPKα1. American Journal of Physiology. Endocrinology and Metabolism 290, e780e788.CrossRefGoogle Scholar
Ikeda, Y et al. (2009) Cardiac-specific deletion of LKB1 leads to hypertrophy and dysfunction. Journal of Biological Chemistry 284, 3583935849.CrossRefGoogle ScholarPubMed
Gundewar, S et al. (2009) Activation of AMP-activated protein kinase by metformin improves left ventricular function and survival in heart failure. Circulation Research 104, 403411.CrossRefGoogle ScholarPubMed
Akki, A et al. (2013) Magnetic resonance imaging and spectroscopy of the murine cardiovascular system. American Journal of Physiology-Heart and Circulatory Physiology 304, H633H648.CrossRefGoogle ScholarPubMed
Gupta, A et al. (2017) A comprehensive review of the bioenergetics of fatty acid and glucose metabolism in the healthy and failing heart in non-diabetic condition. Heart Failure Reviews 22, 825842.CrossRefGoogle Scholar
Gupta, A et al. (2021) Cardiac 1H MR spectroscopy: development of the past five decades and future perspective. Heart Failure Reviews 26, 839859.CrossRefGoogle Scholar
vanBilsen, M et al. (2009) Metabolic remodelling of the failing heart: beneficial or detrimental? Cardiovascular Research 81, 420428.CrossRefGoogle Scholar
William, E et al. (2014) Chapter 4 – The pathophysiology of cardiac hypertrophy and heart failure. In Cellular and Molecular Pathobiology of Cardiovascular Disease. USA: Elsevier Inc., pp. 5178.Google Scholar
Greenland, P et al. (2010) 2010 ACCF/AHA guideline for assessment of cardiovascular risk in asymptomatic adults. Journal of the American College of Cardiology 56, e50e103.CrossRefGoogle ScholarPubMed
Maslov, MY et al. (2010) Reduced in vivo high energy phosphates precede adriamycine-induced cardiac dysfunction. American Journal of Physiology-Heart and Circulatory Physiology 299, H332H337.CrossRefGoogle Scholar
Gupta, A et al. (2012) Metabolomics of urinary tract infection: a new uroscope in town. Expert Review of Molecular Diagnostics 12, 361369.CrossRefGoogle ScholarPubMed
Kumar, D et al. (2016) NMR based metabolomics of prostate cancer: a protagonist in clinical diagnostics. Expert Review of Molecular Diagnostics 16, 651661.CrossRefGoogle ScholarPubMed
Gupta, A et al. (2020) Role of metabolomics-derived biomarkers to identify renal cell carcinoma: a comprehensive past ten years perspective and advancements. Expert Review of Molecular Diagnostics 20, 518.CrossRefGoogle ScholarPubMed
Griffin, JL et al. (2011) Metabolomics as a tool for cardiac research. Nature Reviews Cardiology 8, 630643.CrossRefGoogle ScholarPubMed
McGarrah, RW et al. (2018) Cardiovascular metabolomics. Circulation Research 122, 12381258.CrossRefGoogle ScholarPubMed
Beckonert, O et al. (2007) Metabolic profiling, metabolomics and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Nature Protocols 2, 26922703.CrossRefGoogle Scholar
Dunn, WB et al. (2011) Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry. Nature Protocols 6, 10601083.CrossRefGoogle ScholarPubMed
Oliver, SG et al. (1998) Systematic functional analysis of the yeast genome. Trends in Biotechnology 16:373378.CrossRefGoogle ScholarPubMed
Nicholson, JK et al. (1999) Metabonomics: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 29, 11811189.CrossRefGoogle ScholarPubMed
Gadian, DG et al. (1976) Phosphorus nuclear magnetic resonance studies on normoxic and ischemic cardiac tissue. Proceedings of the National Academy of Sciences of the USA 73, 44464448.CrossRefGoogle ScholarPubMed
Evaristi, MF et al. (2016) Increased mean aliphatic lipid chain length in left ventricular hypertrophy secondary to arterial hypertension: a cross-sectional study. Medicine (Baltimore) 95, e4965.CrossRefGoogle ScholarPubMed
Lin, T et al. (2016) 1H NMR-based analysis of serum metabolites in monocrotaline-induced pulmonary arterial hypertensive rats. Disease Markers 2016, 5803031.CrossRefGoogle Scholar
Holmes, E et al. (2008) Human metabolic phenotype diversity and its association with diet and blood pressure. Nature 453, 396400.CrossRefGoogle ScholarPubMed
Spratlin, JL et al. (2009) Clinical applications of metabolomics in oncology: a review. Clinical Cancer Research 15, 431440.CrossRefGoogle ScholarPubMed
Izquierdo-Garcia, JL et al. (2018) Metabolic reprogramming in the heart and lung in a murine model of pulmonary arterial hypertension. Frontiers in Cardiovascular Medicine 5, 110.CrossRefGoogle Scholar
Brittain, EL et al. (2016) Fatty acid metabolic defects and right ventricular lipotoxicity in human pulmonary arterial hypertension. Circulation 133, 19361944.CrossRefGoogle ScholarPubMed
Jones, GL et al. (2005) A functional analysis of mouse models of cardiac disease through metabolic profiling. Journal of Biological Chemistry 280, 75307539.CrossRefGoogle ScholarPubMed
Zervou, S et al. (2016) Proteomic and metabolomic changes driven by elevating myocardial creatine suggest novel metabolic feedback mechanisms. Amino Acids 48, 19691981.CrossRefGoogle ScholarPubMed
Uddin, GM et al. (2019) Impaired branched chain amino acid oxidation contributes to cardiac insulin resistance in heart failure. Cardiovascular Diabetology 18, 86.CrossRefGoogle ScholarPubMed
Kato, T et al. (2010) Analysis of metabolic remodeling in compensated left ventricular hypertrophy and heart failure. Circulation. Heart Failure 3, 420430.CrossRefGoogle ScholarPubMed
Kolwicz, SC et al. (2012) Cardiac-specific deletion of acetyl CoA carboxylase 2 prevents metabolic remodeling during pressure-overload hypertrophy. Circulation Research 111, 728738.CrossRefGoogle ScholarPubMed
Pereira, RO et al. (2013) Inducible overexpression of GLUT1 prevents mitochondrial dysfunction and attenuates structural remodeling in pressure overload but does not prevent left ventricular dysfunction. Journal of the American Heart Association 2, e000301.CrossRefGoogle Scholar
Lewis, GD et al. (2016) Metabolic profiling of right ventricular-pulmonary vascular function reveals circulating biomarkers of pulmonary hypertension. Journal of the American College of Cardiology 67, 174189.CrossRefGoogle ScholarPubMed
Rhodes, CJ et al. (2017) Plasma metabolomics implicates modified transfer RNAs and altered bioenergetics in the outcomes of pulmonary arterial hypertension. Circulation 135, 460475.CrossRefGoogle ScholarPubMed
Zheng, HK et al. (2018) Metabolic reprogramming of the urea cycle pathway in experimental pulmonary arterial hypertension rats induced by monocrotaline. Respiratory Research 19, 94.CrossRefGoogle ScholarPubMed
Attard, MI et al. (2019) Metabolic pathways associated with right ventricular adaptation to pulmonary hypertension: 3D analysis of cardiac magnetic resonance imaging. European Heart Journal Cardiovascular Imaging 20, 668676.CrossRefGoogle ScholarPubMed
Chen, C et al. (2020) Metabolomics reveals metabolite changes of patients with pulmonary arterial hypertension in China. Journal of Cellular and Molecular Medicine 24, 24842496.CrossRefGoogle ScholarPubMed
Bujak, R et al. (2014) Metabolomics reveals metabolite changes in acute pulmonary embolism. Journal of Proteome Research 13, 805816.CrossRefGoogle ScholarPubMed
Li, J et al. (2019) Metabolic changes in spontaneously hypertensive rat hearts precede cardiac dysfunction and left ventricular hypertrophy. Journal of the American Heart Association 8, e010926.CrossRefGoogle ScholarPubMed
Bravo, CA et al. (2020) Metabolomic profiling of left ventricular diastolic dysfunction in women with or at risk for HIV infection: the women's interagency HIV study. Journal of the American Heart Association 9, e013522.CrossRefGoogle ScholarPubMed
Jørgenrud, B et al. (2015) The metabolome in Finnish carriers of the MYBPC3-Q1061X mutation for hypertrophic cardiomyopathy. PLoS ONE 10, e0134184.CrossRefGoogle ScholarPubMed
Emwas, AH et al. (2015) Standardizing the experimental conditions for using urine in NMR-based metabolomics studies with a particular focus on diagnostic studies: a review. Metabolomics 11, 872894.CrossRefGoogle ScholarPubMed
National Phenome Centre [cited June 2021] Available at http://phenomecentre.org.Google Scholar
Siskos, AP et al. (2017) Interlaboratory reproducibility of a target metabolomics platform for analysis of human serum and plasma. Analytical Chemistry 89, 656665.CrossRefGoogle Scholar
Jourdan, C et al. (2012) Body fat free mass is associated with serum metabolite profile in a population-based study. PLoS ONE 7, e40009.CrossRefGoogle ScholarPubMed
Lotta, LA et al. (2016) Genetic predisposition to an impaired metabolism of the branched-chain amino acids and risk of type 2 diabetes: a Mendelian randomisation analysis. PLoS Medicine 13, e1002179.CrossRefGoogle Scholar
Draisma, HHM et al. (2015) Genome-wide association study identifies novel genetic variants contributing to variation in blood metabolite levels. Nature Communications 6, 7208.CrossRefGoogle ScholarPubMed
Katajamaa, M et al. (2007) Data processing for mass spectrometry-based metabolomics. Journal of Chromatography A 1158, 318328.CrossRefGoogle ScholarPubMed
Wu, Y et al. (2016) Sample normalization methods in quantitative metabolomics. Journal of Chromatography A 1430, 8095.CrossRefGoogle ScholarPubMed
Takis, PG et al. (2017) Deconvoluting interrelationship between concentrations and chemical shifts in urine provides a powerful analysis tool. Nature Communications 8, 1662.CrossRefGoogle Scholar
Ren, S et al. (2015) Computational and statistical analysis of metabolomics data. Metabolomics 11, 14921513.CrossRefGoogle Scholar
Alakwaa, FM et al. (2018) Deep learning accurately predicts estrogen receptor status in breast cancer metabolomics data. Journal of Proteome Research 17, 337347.CrossRefGoogle ScholarPubMed
About us – PhenoMeNal [Internet]. [Cited June 2021] Available at http://phenomenal-h2020.eu/home/about/.Google Scholar
Alden, N et al. (2017) Biologically consistent annotation of metabolomics data. Analytical Chemistry 89, 1309713104.CrossRefGoogle ScholarPubMed