Advertisement

Circulating Biomarkers in Heart Failure

  • Alexander E. BerezinEmail author
Chapter
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 1067)

Abstract

Biological markers have served for diagnosis, risk stratification and guided therapy of heart failure (HF). Our knowledge regarding abilities of biomarkers to relate to several pathways of HF pathogenesis and reflect clinical worsening or improvement in the disease is steadily expanding. Although there are numerous clinical guidelines, which clearly diagnosis, prevention and evidence-based treatment of HF, a strategy regarding exclusion of HF, as well as risk stratification of HF, nature evolution of disease is not well established and requires more development. The aim of the chapter is to discuss a role of biomarker-based approaches for more accurate diagnosis, in-depth risk stratification and individual targeting in treatment of patients with HF.

Keywords

Heart failure Biomarkers Prediction Stratification Biomarker guided-therapy 

Abbreviations

ADM

adrenomedullin

ANP

atrial natriuretic peptide

ARNI

angiotensin receptor neprilysin inhibitors

BNP

brain natriuretic peptide

BRPs

bone related proteins

cGMP

cyclic guanylyl monophosphate

CITP

carboxy-terminal telopeptide

CNP

C-type natriuretic peptide

CRP

C-reactive protein

CT-proET-1

C-terminal-pro-endothelin-1

CV

cardiovascular

EMPs

endothelial microparticles

EPCs

endothelial progenitor cells

Gal-3

galectin-3

GDF-15

Growth differentiation factor-15

HF

heart failure

hFABP

heart type of fatty acid binding protein

HFpEF

heart failure with preserved ejection fraction

HFrEF

heart failure with reduced ejection fraction

LV

left ventricular

MMP

matrix metalloproteinase

MPs

micro particles

MR-proANP

mid-regional pro-atrial natriuretic peptide

MR-proADM

mid-regional pro-adrenomedullin

NPs

natriuretic peptides

NT-proBNP

NT-pro-brain natriuretic peptide

PICP

carboxy-terminal propeptide

sST2

soluble suppressor of tumorigenicity-2 receptor

Notes

Acknowledgements

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Conflicts of Interest

Not declared.

References

  1. AbouEzzeddine OF, McKie PM, Dunlay SM, Stevens SR, Felker GM, Borlaug BA et al (2017) Suppression of tumorigenicity 2 in heart failure with preserved ejection fraction. J Am Heart Assoc 6(2).  https://doi.org/10.1161/JAHA.116.004382CrossRefPubMedPubMedCentralGoogle Scholar
  2. Agnello L, Bivona G, Sasso BL, Scazzone C, Bazan V, Bellia C et al (2017) Galectin-3 in acute coronary syndrome. Clin Biochem.  https://doi.org/10.1016/j.clinbiochem.2017.04.018. [Epub ahead of print]
  3. Aimo A, Vergaro G, Ripoli A, Bayes-Genis A, Pascual Figal DA, de Boer RA et al (2017) Meta-analysis of soluble suppression of tumorigenicity-2 and prognosis in acute heart failure. JACC Heart Fail 5(4):287–296CrossRefPubMedGoogle Scholar
  4. Amin A, Chitsazan M, Shiukhi Ahmad Abad F, Taghavi S, Naderi N (2017) On admission serum sodium and uric acid levels predict 30 day rehospitalization or death in patients with acute decompensated heart failure. ESC Heart Fail 4(2):162–168CrossRefPubMedPubMedCentralGoogle Scholar
  5. Anguita M (2017) High-sensitivity troponins and prognosis of heart failure. Rev Clin Esp 217(2):95–96CrossRefPubMedGoogle Scholar
  6. Aspromonte N, Gulizia MM, Clerico A, Di Tano G, Emdin M, Feola M et al (2016) ANMCO/ELAS/SIBioC consensus document: recommendations for the use of cardiac biomarkers in heart failure patients. G Ital Cardiol (Rome) 17(9):615–656Google Scholar
  7. Bayes-Genis A, Ordonez-Llanos J (2015) Multiple biomarker strategies for risk stratification in heart failure. Clin Chim Acta 443:120–125CrossRefPubMedGoogle Scholar
  8. Bayes-Genis A, de Antonio M, Vila J, Peñafiel J, Galán A, Barallat J et al (2014) Head-to-head comparison of 2 myocardial fibrosis biomarkers for long-term heart failure risk stratification: ST2 versus galectin-3. J Am Coll Cardiol 63(2):158–166CrossRefPubMedGoogle Scholar
  9. Berezin AE (2014) Serum uric acid as a metabolic regulator of endothelial reparative processes in heart failure patients. Stem Cell Transl Invest 1(1):1–5Google Scholar
  10. Berezin AE (2015a) Biological markers of cardiovascular diseases. Part 4. Diagnostic and prognostic value of biological markers at risk stratification among patients with heart failure. LAMBERT Academic Publishing GmbH, Moscow. 329 pGoogle Scholar
  11. Berezin AE (2015b) The risk stratification in heart failure patients: the controversial role of high-sensitive ST2. J Integr Cardiol 1(6):216–217Google Scholar
  12. Berezin A (2015c) Endothelial derived micro particles: biomarkers for heart failure diagnosis and management. J Clin Trial Cardiol 2(3):1–3CrossRefGoogle Scholar
  13. Berezin AE (2015d) Impaired pattern of endothelial derived microparticles in heart failure patients. J Mol Genet Med 9:1.  https://doi.org/10.4172/1747-0862.1000152CrossRefGoogle Scholar
  14. Berezin AE (2016a) Prognostication in different heart failure phenotypes: the role of circulating biomarkers. J Circ Biomark 5:01.  https://doi.org/10.5772/62797CrossRefGoogle Scholar
  15. Berezin A (2016b) Biomarkers for cardiovascular risk in diabetic patients. Heart 102(24):1939–1941CrossRefPubMedGoogle Scholar
  16. Berezin AE (2016c) Impaired phenotype of endothelial cell-derived micro particles: the missed link in heart failure development? Biom J 2(2):14–19Google Scholar
  17. Berezin A (2016d) Epigenetics in heart failure phenotypes. BBA Clinical 6:31–37CrossRefPubMedPubMedCentralGoogle Scholar
  18. Berezin AE (2016e) Epigenetically modified endothelial progenitor cells in heart failure. J Clin Epigenet 2(2):21–23Google Scholar
  19. Berezin AE (2016f) Genetic predictive scores in heart failure: possibilities and expectations. J Data Mining Genomics Proteomics 7(5):e127–e128Google Scholar
  20. Berezin AE (2017a) Contemporary approaches of biological markers in heart failure. Scholars’ Press, Omni Scriptum Management GmbH, SaarbrückenGoogle Scholar
  21. Berezin A (2017b) Does serum uric acid play a protective role against tissue damage in cardiovascular and metabolic diseases? Ann Clin Hypertens 1:39–41CrossRefGoogle Scholar
  22. Berezin A (2017c) Biomarkers in heart failure. J Blood Lymph 7(3):172–179Google Scholar
  23. Berezin A (2017d) Up-to-date clinical approaches of biomarkers’ use in heart failure. Biomed Res Ther 4(6):1341–1370CrossRefGoogle Scholar
  24. Berezin AE, Kremzer AA (2013) Serum uric acid as a marker of coronary calcification in patients with asymptomatic coronary artery disease with preserved left ventricular pump function. Cardiol Res Pract, Article ID 129369.  https://doi.org/10.1155/2013/129369
  25. Berezin AE, Samura TA (2013) Prognostic value of biological markers in myocardial infarction patients. Asian Cardiovasc Thorac Ann 21(2):142–150CrossRefPubMedGoogle Scholar
  26. Berezin AE, Kremzer AA, Samura TA, Martovitskaya YV (2014a) Apoptotic microparticles to progenitor mononuclear cells ratio in heart failure: relevance of clinical status and outcomes. JCvD 2(2):50–57Google Scholar
  27. Berezin AE, Kremzer AA, Martovitskaya YV, Samura TA, Berezina TA (2014b) Serum uric acid predicts declining of circulating proangiogenic mononuclear progenitor cells in chronic heart failure patients. J Cardiovasc Thorac Res 6(3):153–162.  https://doi.org/10.5681/jcvtr.2014.0XXCrossRefPubMedPubMedCentralGoogle Scholar
  28. Berezin AE, Kremzer AA, Martovitskaya YV, Samura TA, Berezina TA, Zulli A et al (2015a) The utility of biomarker risk prediction score in patients with chronic heart failure. Int J Clin Exp Med 8(10):18255–18264PubMedPubMedCentralGoogle Scholar
  29. Berezin AE, Kremzer AA, Berezina TA, Martovitskaya YV (2015b) Pattern of circulating microparticles in chronic heart failure patients with metabolic syndrome: relevance to neurohumoral and inflammatory activation. BBA Clinical 4:69–75CrossRefPubMedPubMedCentralGoogle Scholar
  30. Berezin AE, Kremzer AA, Samura TA (2015c) Circulating thrombospondine-2 in patients with moderate-to-severe chronic heart failure due to coronary artery disease. J Biomed Res 30.  https://doi.org/10.7555/JBR.29.20140025. [Epub ahead of print]
  31. Berezin A, Kremzer A, Martovitskaya Y, Samura T, Berezina T (2016) The novel biomarker risk prediction score in patients with chronic heart failure. Clin Hypertens 22(3).  https://doi.org/10.1186/s40885-016-0041-1.
  32. Besler C, Lang D, Urban D, Rommel KP, von Roeder M, Fengler K et al (2017a) Plasma and cardiac Galectin-3 in patients with heart failure reflects both inflammation and fibrosis: implications for its use as a biomarker. Circ Heart Fail 10(3).  https://doi.org/10.1161/CIRCHEARTFAILURE.116.003804Google Scholar
  33. Besler C, Lang D, Urban D, Rommel KP, von Roeder M, Fengler K et al (2017b) Plasma and cardiac galectin-3 in patients with heart failure reflects both inflammation and fibrosis: implications for its use as a biomarker. Circ Heart Fail 10(3).  https://doi.org/10.1161/CIRCHEARTFAILURE.116.003804Google Scholar
  34. Billebeau G, Vodovar N, Sadoune M, Launay JM, Beauvais F, Cohen-Solal A (2017) Effects of a cardiac rehabilitation programme on plasma cardiac biomarkers in patients with chronic heart failure. Eur J Prev Cardiol.  https://doi.org/10.1177/2047487317705488. [Epub ahead of print]
  35. Biomarkers Definitions Working Group (National Institutes of Health) (2001) Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther 69:89–95CrossRefGoogle Scholar
  36. Bondar G, Cadeiras M, Wisniewski N, Maque J, Chittoor J, Chang E et al (2014) Comparison of whole blood and peripheral blood mononuclear cell gene expression for evaluation of the perioperative inflammatory response in patients with advanced heart failure. PLoS One 9(12):e115097CrossRefPubMedPubMedCentralGoogle Scholar
  37. Borghi C, Rosei EA, Bardin T, Dawson J, Dominiczak A, Kielstein JT et al (2015) Serum uric acid and the risk of cardiovascular and renal disease. J Hypertens 33:1729–1741CrossRefPubMedGoogle Scholar
  38. Boulogne M, Sadoune M, Launay JM, Baudet M, Cohen-Solal A, Logeart D (2017a) Inflammation versus mechanical stretch biomarkers over time in acutely decompensated heart failure with reduced ejection fraction. Int J Cardiol 226:53–59CrossRefPubMedGoogle Scholar
  39. Boulogne M, Sadoune M, Launay JM, Baudet M, Cohen-Solal A, Logeart D (2017b) Inflammation versus mechanical stretch biomarkers over time in acutely decompensated heart failure with reduced ejection fraction. Int J Cardiol 226:53–59CrossRefPubMedGoogle Scholar
  40. Bustamante A, García-Berrocoso T, Penalba A, Giralt D, Simats A, Muchada M et al (2017) Sepsis biomarkers reprofiling to predict stroke-associated infections. J Neuroimmunol 312:19–23CrossRefPubMedGoogle Scholar
  41. Chan MM, Santhanakrishnan R, Chong JP, Chen Z, Tai BC, Liew OW et al (2016) Growth differentiation factor 15 in heart failure with preserved vs. reduced ejection fraction. Eur J Heart Fail 18(1):81–88CrossRefPubMedGoogle Scholar
  42. Chmurzynska A (2006) The multigene family of fatty acidbinding proteins (FABPs): function, structure, and polymorphism. J Appl Genet 47:39–48CrossRefPubMedGoogle Scholar
  43. Chow SL, Maisel AS, Anand I, Bozkurt B, de Boer RA, Felker GM, Fonarow GC et al (2017) Role of biomarkers for the prevention, assessment, and management of heart failure: a scientific statement from the American Heart Association. Circulation.  https://doi.org/10.1161/CIR.0000000000000490. [Epub ahead of print]
  44. Cohen-Solal A, Laribi S, Ishihara S, Vergaro G, Baudet M, Logeart D et al (2015) Prognostic markers of acute decompensated heart failure: the emerging roles of cardiac biomarkers and prognostic scores. Arch Cardiovasc Dis 108(1):64–74CrossRefPubMedGoogle Scholar
  45. Collier P, Watson CJ, Voon V, Phelan D, Jan A, Mak G et al (2011) Can emerging biomarkers of myocardial remodeling identify asymptomatic hypertensive patients at risk for diastolic dysfunction and diastolic heart failure? Eur J Heart Fail 13(10):1087–1095CrossRefPubMedGoogle Scholar
  46. Demissei BG, Cotter G, Prescott MF, Felker GM, Filippatos G, Greenberg BH et al (2017) A multimarker multi-time point-based risk stratification strategy in acute heart failure: results from the RELAX-AHF trial. Eur J Heart Fail.  https://doi.org/10.1002/ejhf.749. [Epub ahead of print]
  47. Dres M, Hausfater P, Foissac F, Bernard M, Joly LM, Sebbane M et al (2017) Mid-regional pro-adrenomedullin and copeptin to predict short-term prognosis of COPD exacerbations: a multicenter prospective blinded study. Int J Chron Obstruct Pulmon Dis 12:1047–1056CrossRefPubMedPubMedCentralGoogle Scholar
  48. Favresse J, Gruson D (2017) Natriuretic peptides: degradation, circulating forms, dosages and new therapeutic approaches. Ann Biol Clin (Paris).  https://doi.org/10.1684/abc.2017.1235. [Epub ahead of print]
  49. Fazakas Á, Szelényi Z, Szénási G, Nyírő G, Szabó PM, Patócs A et al (2016) Genetic predisposition in patients with hypertension and normal ejection fraction to oxidative stress. J Am Soc Hypertens 10(2):124–132CrossRefPubMedGoogle Scholar
  50. Felker GM, Anstrom KJ, Adams KF, Ezekowitz JA, Fiuzat M, Houston-Miller N et al (2017) Effect of natriuretic peptide-guided therapy on hospitalization or cardiovascular mortality in high-risk patients with heart failure and reduced ejection fraction: a randomized clinical trial. JAMA 318(8):713–720CrossRefPubMedPubMedCentralGoogle Scholar
  51. Feng SD, Jiang Y, Lin ZH, Lin PH, Lin SM, Liu QC (2017) Diagnostic value of brain natriuretic peptide and β-endorphin plasma concentration changes in patients with acute left heart failure and atrial fibrillation. Medicine (Baltimore) 96(34):e7526.  https://doi.org/10.1097/MD.0000000000007526CrossRefGoogle Scholar
  52. Fonarow GC (2017) Biomarker-guided vs guideline-directed titration of medical therapy for heart failure. JAMA 318(8):707–708CrossRefPubMedGoogle Scholar
  53. Friedrich FW, Dilanian G, Khattar P, Juhr D, Gueneau L, Charron P et al (2013) A novel genetic variant in the transcription factor Islet-1 exerts gain of function on myocyte enhancer factor 2C promoter activity. Eur J Heart Fail 15(3):267–276CrossRefPubMedGoogle Scholar
  54. Ganna A, Rivadeneira F, Hofman A, Uitterlinden AG, Magnusson PK, Pedersen NL et al (2013) Genetic determinants of mortality. Can findings from genome-wide association studies explain variation in human mortality? Hum Genet 132(5):553–561CrossRefPubMedGoogle Scholar
  55. Grassi D, Ferri L, Desideri G, Di Giosia P, Cheli P, Del Pinto R et al (2013) Chronic hyperuricemia, uric acid deposit and cardiovascular risk. Curr Pharm Des 19:2432–2438CrossRefPubMedPubMedCentralGoogle Scholar
  56. Hage C, Michaëlsson E, Linde C, Donal E, Daubert JC, Gan LM et al (2017) Inflammatory biomarkers predict heart failure severity and prognosis in patients with heart failure with preserved ejection fraction: a holistic proteomic approach. Circ Cardiovasc Genet 10(1).  https://doi.org/10.1161/CIRCGENETICS.116.001633Google Scholar
  57. Hayashida K, Kondo Y, Hara Y, Aihara M, Yamakawa K (2017) Head-to-head comparison of procalcitonin and presepsin for the diagnosis of sepsis in critically ill adult patients: a protocol for a systematic review and meta-analysis. BMJ Open 7(3):e014305CrossRefPubMedPubMedCentralGoogle Scholar
  58. Herrero-Puente P, Prieto-García B, García-García M, Jacob J, Martín-Sánchez FJ, Pascual-Figal D et al (2017) Predictive capacity of a multimarker strategy to determine short-term mortality in patients attending a hospital emergency department for acute heart failure. BIO-EAHFE study. Clin Chim Acta 466:22–30CrossRefPubMedGoogle Scholar
  59. Hershberger RE, Siegfried JD (2011) Update 2011: clinical and genetic issues in familial dilated cardiomyopathy. J Am Coll Cardiol 57(16):1641–1649CrossRefPubMedPubMedCentralGoogle Scholar
  60. Hofman N, van Langen I, Wilde AAM (2010) Genetic testing in cardiovascular diseases. Curr Opin Cardiol 25(3):243–248CrossRefPubMedGoogle Scholar
  61. Huerta A, López B, Ravassa S, San José G, Querejeta R, Beloqui Ó et al (2016) Association of cystatin C with heart failure with preserved ejection fraction in elderly hypertensive patients: potential role of altered collagen metabolism. J Hypertens 34(1):130–138CrossRefPubMedGoogle Scholar
  62. Hutchinson KR, Stewart JA Jr, Lucchesi PA (2010) Extracellular matrix remodeling during the progression of volume overload-induced heart failure. J Mol Cell Cardiol 48(3):564–569CrossRefPubMedGoogle Scholar
  63. Imran TF, Shin HJ, Mathenge N, Wang F, Kim B, Joseph J et al (2017) Meta-analysis of the usefulness of plasma Galectin-3 to predict the risk of mortality in patients with heart failure and in the general population. Am J Cardiol 119(1):57–64CrossRefPubMedGoogle Scholar
  64. Jin P, Gu W, Lai Y, Zheng W, Zhou Q, Wu X (2017) The circulating MicroRNA-206 level predicts the severity of pulmonary hypertension in patients with left heart diseases. Cell Physiol Biochem 41(6):2150–2160CrossRefPubMedGoogle Scholar
  65. Kempf T, Wollert KC (2009) Growth differentiation Factor-15: a new biomarker in cardiovascular disease. Herz 34:594–599CrossRefPubMedGoogle Scholar
  66. Kim H, Yoon HJ, Park HS, Cho YK, Nam CW, Hur SH et al (2013) Potentials of cystatin C and uric acid for predicting prognosis of heart failure. Congest Heart Fail 19(3):123–129CrossRefPubMedGoogle Scholar
  67. Kim TH, Kim H, Kim IC (2015) The potential of cystatin-C to evaluate the prognosis of acute heart failure: a comparative study. Acute Card Care 17(4):72–76CrossRefPubMedGoogle Scholar
  68. Kitai T, Kim YH, Kiefer K, Morales R, Borowski AG, Grodin JL et al (2017) Circulating intestinal fatty acid-binding protein (I-FABP) levels in acute decompensated heart failure. Clin Biochem.  https://doi.org/10.1016/j.clinbiochem.2017.02.014. [Epub ahead of print]
  69. Kolder IC, Michels M, Christiaans I, Ten Cate FJ, Majoor-Krakauer D, Danser AH et al (2012) The role of renin-angiotensin-aldosterone system polymorphisms in phenotypic expression of MYBPC3-related hypertrophic cardiomyopathy. Eur J Hum Genet 20(10):1071–1077CrossRefPubMedPubMedCentralGoogle Scholar
  70. Krane V, Genser B, Kleber ME, Drechsler C, März W, Delgado G et al (2017) Copeptin associates with cause-specific mortality in patients with impaired renal function: results from the LURIC and the 4D study. Clin Chem.  https://doi.org/10.1373/clinchem.2016.266254. [Epub ahead of print]
  71. Krintus M, Kozinski M, Fabiszak T, Kubica J, Panteghini M, Sypniewska G (2017) Establishing reference intervals for galectin-3 concentrations in serum requires careful consideration of its biological determinants. Clin Biochem.  https://doi.org/10.1016/j.clinbiochem.2017.03.015. [Epub ahead of print]
  72. Lala RI, Lungeanu D, Darabantiu D, Pilat L, Puschita M (2017) Galectin-3 as a marker for clinical prognosis and cardiac remodeling in acute heart failure. Herz.  https://doi.org/10.1007/s00059-017-4538-5. [Epub ahead of print]
  73. Ledwidge M, Gallagher J, Conlon C, Tallon E, O’Connell E, Dawkins I et al (2013) Natriuretic peptide-based screening and collaborative care for heart failure: the STOP-HF randomized trial. JAMA 310:66–74CrossRefPubMedGoogle Scholar
  74. Löfsjögård J, Persson H, Díez J, López B, González A, Edner M et al (2014) Atrial fibrillation and biomarkers of myocardial fibrosis in heart failure. Scand Cardiovasc J 48(5):299–303CrossRefPubMedGoogle Scholar
  75. Löfsjögård J, Kahan T, Díez J, López B, González A, Ravassa S et al (2017) Usefulness of collagen Carboxy-terminal propeptide and telopeptide to predict disturbances of long-term mortality in patients ≥60 years with heart failure and reduced ejection fraction. Am J Cardiol.  https://doi.org/10.1016/j.amjcard.2017.03.036. [Epub ahead of print]
  76. Lopes LR, Elliott PM (2013) Genetics of heart failure. BBA Mol Basis Dis 1832(12):2451–2461CrossRefGoogle Scholar
  77. Lopes D, Menezes Falcão L (2017) Mid-regional pro-adrenomedullin and ST2 in heart failure: contributions to diagnosis and prognosis. Rev Port Cardiol 36(6):465–472PubMedCrossRefGoogle Scholar
  78. Luchner A, von Haehling S, Holubarsch C, Keller T, Knebel F, Zugck C et al (2017) Indications and clinical implications of the use of the cardiac markers BNP and NT-proBNP. Dtsch Med Wochenschr 142(5):346–355CrossRefPubMedGoogle Scholar
  79. Maisel AS, Di Somma S (2016) Do we need another heart failure biomarker: focus on soluble suppression of tumorigenicity 2 (sST2). Eur Heart J.  https://doi.org/10.1093/eurheartj/ehw462. [Epub ahead of print]
  80. Malek V, Gaikwad AB (2017) Neprilysin inhibitors: a new hope to halt the diabetic cardiovascular and renal complications? Biomed Pharmacother 90:752–759CrossRefPubMedGoogle Scholar
  81. Masson S, Latini R, Anand IS (2010) An update on cardiac troponins as circulating biomarkers in heart failure. Curr Heart Fail Rep 7(1):15–21CrossRefPubMedGoogle Scholar
  82. McNamara DM, Taylor AL, Tam SW, Worcel M, Yancy CW, Hanley-Yanez K et al (2014) G-protein beta-3 subunit genotype predicts enhanced benefit of fixed-dose isosorbide dinitrate and hydralazine: results of A-HeFT. JACC Heart Fail 2(6):551–557CrossRefPubMedGoogle Scholar
  83. Meijers WC, van der Velde AR, Muller Kobold AC, Dijck-Brouwer J, AH W, Jaffe A et al (2017) Variability of biomarkers in patients with chronic heart failure and healthy controls. Eur J Heart Fail 19(3):357–365CrossRefPubMedGoogle Scholar
  84. Miró Ò, González de la Presa B, Herrero-Puente P, Fernández Bonifacio R, Möckel M, Mueller C et al (2017) The GALA study: relationship between galectin-3 serum levels and short- and long-term outcomes of patients with acute heart failure. Biomarkers 2:1–9.  https://doi.org/10.1080/1354750X.2017.1319421.CrossRefGoogle Scholar
  85. Moayedi Y, Ross HJ (2017) Advances in heart failure: a review of biomarkers, emerging pharmacological therapies, durable mechanical support and telemonitoring. Clin Sci (Lond) 131(7):553–566CrossRefGoogle Scholar
  86. Morgenthaler NG (2006) Assay for the measurement of copeptin, a stable peptide derived from the precursor of vasopressin. Clin Chem 52:112–119CrossRefPubMedGoogle Scholar
  87. Mozos I, Marginean O (2015) Links between vitamin D deficiency and cardiovascular diseases. Biomed Res Int 2015:109275.  https://doi.org/10.1155/2015/109275CrossRefPubMedPubMedCentralGoogle Scholar
  88. Mozos I, Stoian D, Luca CT (2017) Crosstalk between vitamin A, B12, D, K, C and E status and arterial stiffness. Dis Markers 2017:8784971.  https://doi.org/10.1155/2017/8784971CrossRefPubMedPubMedCentralGoogle Scholar
  89. Nagarajan V, Hernandez AV, Tang WH (2012) Prognostic value of cardiac troponin in chronic stable heart failure: a systematic review. Heart 98(24):1778–1786CrossRefPubMedGoogle Scholar
  90. Nakanishi M, Nakao K, Kumasaka L, Arakawa T, Fukui S, Ohara T et al (2017) Improvement in exercise capacity by exercise training associated with favorable clinical outcomes in advanced heart failure with high B-type natriuretic peptide level. Circ J.  https://doi.org/10.1253/circj.CJ-16-1268. [Epub ahead of print]
  91. Nelveg-Kristensen KE, Busk Madsen M, Torp-Pedersen C, Køber L, Egfjord M, Berg Rasmussen H et al (2015) Pharmacogenetic risk stratification in angiotensin-converting enzyme inhibitor-treated patients with congestive heart failure: a retrospective cohort study. PLoS One 10(12):e0144195CrossRefPubMedPubMedCentralGoogle Scholar
  92. Nymo SH, Aukrust P, Kjekshus J, McMurray JJ, Cleland JG, Wikstrand J et al (2017) CORONA study group. Limited added value of circulating inflammatory biomarkers in chronic heart failure. JACC Heart Fail 5(4):256–264.  https://doi.org/10.1016/j.jchf.2017.01.008.CrossRefPubMedGoogle Scholar
  93. Odermatt J, Meili M, Hersberger L, Bolliger R, Christ-Crain M, Briel M et al (2017) Pro-Adrenomedullin predicts 10-year all-cause mortality in community-dwelling patients: a prospective cohort study. BMC Cardiovasc Disord 17(1):178CrossRefPubMedPubMedCentralGoogle Scholar
  94. Okazaki H, Shirakabe A, Kobayashi N, Hata N, Shinada T, Matsushita M et al (2016) The prognostic impact of uric acid in patients with severely decompensated acute heart failure. J Cardiol 68(5):384–391CrossRefPubMedGoogle Scholar
  95. Okazaki H, Shirakabe A, Kobayashi N, Hata N, Shinada T, Matsushita M et al (2017) Are atherosclerotic risk factors associated with a poor prognosis in patients with hyperuricemic acute heart failure? The evaluation of the causal dependence of acute heart failure and hyperuricemia. Heart Vessel 32(4):436–445CrossRefGoogle Scholar
  96. Otaki Y, Watanabe T, Kinoshita D, Yokoyama M, Takahashi T, Toshima T et al (2017) Association of plasma xanthine oxidoreductase activity with severity and clinical outcome in patients with chronic heart failure. Int J Cardiol 228:151–157CrossRefPubMedGoogle Scholar
  97. Poller W, Dimmeler S, Heymans S, Zeller T, Haas J, Karakas M et al (2017) Non-coding RNAs in cardiovascular diseases: diagnostic and therapeutic perspectives. Eur Heart J.  https://doi.org/10.1093/eurheartj/ehx165. [Epub ahead of print]
  98. Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JG, Coats AJ, Authors/Task Force Members et al (2016) 2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur Heart J 37:2129–2200CrossRefGoogle Scholar
  99. Pouleur AC (2015) Which biomarkers do clinicians need for diagnosis and management of heart failure with reduced ejection fraction? Clin Chim Acta 443:9–16CrossRefPubMedGoogle Scholar
  100. Qian HY, Huang J, Yang YJ, Yang YM, Li ZZ, Zhang JM (2016) Heart-type fatty acid binding protein in the assessment of acute pulmonary embolism. Am J Med Sci 352(6):557–562CrossRefPubMedGoogle Scholar
  101. Reiner MM, Khoury WE, Canales MB, Chmielewski RA, Patel K, Razzante MC et al (2017) Procalcitonin as a biomarker for predicting amputation level in lower extremity infections. J Foot Ankle Surg.  https://doi.org/10.1053/j.jfas.2017.01.014. [Epub ahead of print]
  102. Remde H, Dietz A, Emeny R, Riester A, Peters A, de Las Heras Gala T et al (2016) The cardiovascular markers copeptin and high-sensitive C-reactive protein decrease following specific therapy for primary aldosteronism. J Hypertens 34:2066–2073CrossRefPubMedGoogle Scholar
  103. Ryu JA, Yang JH, Lee D, Park CM, Suh GY, Jeon K et al (2015) Clinical usefulness of procalcitonin and C-reactive protein as outcome predictors in critically ill patients with severe sepsis and septic shock. PLoS One 10(9):e0138150CrossRefPubMedPubMedCentralGoogle Scholar
  104. Sahin I, Gungor B, Ozkaynak B, Uzun F, Küçük SH, Avci II et al (2017) Higher copeptin levels are associated with worse outcome in patients with hypertrophic cardiomyopathy. Clin Cardiol 40(1):32–37CrossRefPubMedGoogle Scholar
  105. Savic-Radojevic A, Pljesa-Ercegovac M, Matic M, Simic D, Radovanovic S, Simic T (2017) Novel biomarkers of heart failure. Adv Clin Chem 79:93–152CrossRefPubMedGoogle Scholar
  106. Simon L, Gauvin F, Amre DK, Saint-Louis P, Lacroix J (2004) Serum procalcitonin and C-reactive protein levels as markers of bacterial infection: a systematic review and meta-analysis. Clin Infect Dis 39:206–217CrossRefPubMedGoogle Scholar
  107. Skaf S, Thibault B, Khairy P, O’Meara E, Fortier A, Vakulenko HV, EARTH Investigators et al (2017) Impact of left ventricular vs biventricular pacing on reverse remodelling: insights from the evaluation of resynchronization therapy for heart failure (EARTH) trial. Can J Cardiol 33(10):1274–1282CrossRefPubMedGoogle Scholar
  108. Smaradottir MI, Ritsinger V, Gyberg V, Norhammar A, Näsman P, Mellbin LG (2017) Copeptin in patients with acute myocardial infarction and newly detected glucose abnormalities – a marker of increased stress susceptibility? A report from the glucose in acute myocardial infarction cohort. Diab Vasc Dis Res 14(2):69–76CrossRefPubMedGoogle Scholar
  109. Souza BSF, Silva DN, Carvalho RH, Sampaio GLA, Paredes BD, Aragão França L et al (2017) Association of cardiac galectin-3 expression, myocarditis, and fibrosis in chronic chagas disease cardiomyopathy. Am J Pathol 187(5):1134–1146CrossRefPubMedGoogle Scholar
  110. Srivatsan V, George M, Shanmugam E (2015) Utility of galectin-3 as a prognostic biomarker in heart failure: where do we stand? Eur J Prev Cardiol 22(9):1096–1110CrossRefPubMedGoogle Scholar
  111. Sutter ME, Gaedigk A, Albertson TE, Southard J, Owen KP, Mills LD et al (2013) Polymorphisms in CYP2D6 may predict methamphetamine related heart failure. Clin Toxicol (Phila) 51(7):540–544CrossRefGoogle Scholar
  112. Taub PR, Borden KC, Fard A, Maisel A (2012) Role of biomarkers in the diagnosis and prognosis of acute kidney injury in patients with cardiorenal syndrome. Expert Rev Cardiovasc Ther 10(5):657–667CrossRefPubMedPubMedCentralGoogle Scholar
  113. Teekakirikul P, Kelly MA, Rehm HL, Lakdawala NK, Funke BH (2013) Inherited cardiomyopathies: molecular genetics and clinical genetic testing in the postgenomic era. J Mol Diagn 15(2):158–170CrossRefPubMedGoogle Scholar
  114. Teo LY, Moran RT, Tang WH (2015) Evolving approaches to genetic evaluation of specific cardiomyopathies. Curr Heart Fail Rep 12(6):339–349CrossRefPubMedGoogle Scholar
  115. Tziakas DN, Chalikias GK, Stakos D, Chatzikyriakou SV, Papazoglou D, Mitrousi K et al (2012) Independent and additive prognostic ability of serum carboxy-terminal telopeptide of collagen type-I in heart failure patients: a multi-marker approach with high-negative predictive value to rule out long-term adverse events. Eur J Prev Cardiol 19(1):62–71CrossRefPubMedGoogle Scholar
  116. Vegter EL, van der Meer P, Voors AA (2017) Associations between volume status and circulating microRNAs in acute heart failure. Eur J Heart Fail.  https://doi.org/10.1002/ejhf.867. [Epub ahead of print]
  117. Welsh P, Kou L, Yu C, Anand I, van Veldhuisen DJ, Maggioni AP et al (2017) Prognostic importance of emerging cardiac, inflammatory, and renal biomarkers in chronic heart failure patients with reduced ejection fraction and anaemia: RED-HF study. Eur J Heart Fail.  https://doi.org/10.1002/ejhf.988. [Epub ahead of print]
  118. Wettersten N, Maisel AS (2016) Biomarkers for heart failure: an update for practitioners of internal medicine. Am J Med 129(6):560–567CrossRefPubMedGoogle Scholar
  119. Wojciechowska C, Romuk E, Nowalany-Kozielska E, Jacheć W (2017) Serum Galectin-3 and ST2 as predictors of unfavorable outcome in stable dilated cardiomyopathy patients. Hell J Cardiol.  https://doi.org/10.1016/j.hjc.2017.03.006. [Epub ahead of print]
  120. Wong CM, Hawkins NM, Petrie MC, Jhund PS, Gardner RS, Ariti CA, MAGGIC Investigators et al (2014) Heart failure in younger patients: the meta-analysis global Group in Chronic Heart Failure (MAGGIC). Eur Heart J 35(39):2714–2721CrossRefPubMedGoogle Scholar
  121. Wong PC, Guo J, Zhang A (2017) The renal and cardiovascular effects of natriuretic peptides. Absence of clear clinical recommendations of biomarker-based HF therapy is the main cause of uncertainty regarding practical use of this approach. Adv Physiol Educ 41(2):179–185.  https://doi.org/10.1152/advan.00177.2016CrossRefPubMedGoogle Scholar
  122. Wu CK, Luo JL, XM W, Tsai CT, Lin JW, Hwang JJ et al (2009) A propensity score-based case-control study of renin-angiotensin system gene polymorphisms and diastolic heart failure. Atherosclerosis 205(2):497–502CrossRefPubMedGoogle Scholar
  123. Wu CK, Luo JL, Tsai CT, Huang YT, Cheng CL, Lee JK et al (2010) Demonstrating the pharmacogenetic effects of angiotensin-converting enzyme inhibitors on long-term prognosis of diastolic heart failure. Pharmacogenomics J 10(1):46–53CrossRefPubMedGoogle Scholar
  124. Yan JJ, Lu Y, Kuai ZP, Yong YH (2017a) Predictive value of plasma copeptin level for the risk and mortality of heart failure: a meta-analysis. J Cell Mol Med.  https://doi.org/10.1111/jcmm.13102. [Epub ahead of print]
  125. Yan H, Ma F, Zhang Y, Wang C, Qiu D, Zhou K et al (2017b) miRNAs as biomarkers for diagnosis of heart failure: a systematic review and meta-analysis. Medicine (Baltimore) 96(22):e6825.  https://doi.org/10.1097/MD.0000000000006825CrossRefGoogle Scholar
  126. Yancy CW, Jessup M, Bozkurt B, Butler J, Casey DE Jr, Colvin MM et al (2017) ACC/AHA/HFSA focused update of the 2013 ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology/American Heart Association task force on clinical practice guidelines and the Heart Failure Society of America. J Card Fail.  https://doi.org/10.1016/j.cardfail.2017.04.014. [Epub ahead of print]
  127. Yang J, Xu WW, Hu SJ (2015) Heart failure: advanced development in genetics and epigenetics. Biomed Res Int 2015:352734PubMedPubMedCentralGoogle Scholar
  128. Yip VL, Pirmohamed M (2013) Expanding role of pharmacogenomics in the management of cardiovascular disorders. Am J Cardiovasc Drugs 13(3):151–162CrossRefPubMedGoogle Scholar
  129. Yu B, Zheng Y, Alexander D, Manolio TA, Alonso A, Nettleton JA et al (2013) Genome-wide association study of a heart failure related metabolomic profile among African Americans in the Atherosclerosis Risk in Communities (ARIC) study. Genet Epidemiol 37(8):840–845CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Internal Medicine DepartmentState Medical University of ZaporozhyeZaporozhyeUkraine

Personalised recommendations