Biomarkers for Heart Failure Prognosis: Proteins, Genetic Scores and Non-coding RNAs PDF
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2020
Apurva Shrivastava, Tina Haase, Tanja Zeller, and Christian Schulte
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This review article discusses biomarkers for heart failure prognosis, focusing on proteins, genetic scores, and non-coding RNAs. The authors examine the role of protein biomarkers, such as NT-proBNP, and explore the potential of genetic risk scores and non-coding RNAs in predicting heart failure risk. They also highlight the challenges in identifying true cardiac-specific biomarkers.
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REVIEW published: 23 November 2020 doi: 10.3389/fcvm.2020.601364 Biomarkers for Heart Failure Prognosis: Proteins, Genetic Scores and Non-coding RNAs Apurva Shrivastava 1,2 , Tina Haase 1,2 , Tanja Zeller 1,2 and Christian Schulte 1,2,3* 1 Clinic for Cardiology, University Heart and Vascular Center, University Medical Center Eppendorf, Hamburg, Germany, 2 German Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Kiel/Luebeck, University Medical Center Eppendorf, Hamburg, Germany, 3 King’s British Heart Foundation Centre, King’s College London, London, United Kingdom Heart failure (HF) is a complex disease in which cardiomyocyte injury leads to a cascade of inflammatory and fibrosis pathway activation, thereby causing decrease in cardiac function. As a result, several biomolecules are released which can be identified easily in circulating body fluids. The complex biological processes involved in the development and worsening of HF require an early treatment strategy to stop deterioration of cardiac function. Circulating biomarkers provide not only an ideal platform to detect subclinical changes, their clinical application also offers the opportunity to monitor disease treatment. Many of these biomarkers can be quantified with high sensitivity; Edited by: allowing their clinical application to be evaluated beyond diagnostic purposes as potential Alexander E. Berezin, Zaporizhia State Medical tools for HF prognosis. Though the field of biomarkers is dominated by protein molecules, University, Ukraine non-coding RNAs (microRNAs, long non-coding RNAs, and circular RNAs) are novel and Reviewed by: promising biomarker candidates that encompass several ideal characteristics required Kenichi Hongo, Jikei University School of in the biomarker field. The application of genetic biomarkers as genetic risk scores in Medicine, Japan disease prognosis, albeit in its infancy, holds promise to improve disease risk estimation. Alberto Aimo, Despite the multitude of biomarkers that have been available and identified, the majority Sant’Anna School of Advanced Studies, Italy of novel biomarker candidates are not cardiac-specific, and instead may simply be a *Correspondence: readout of systemic inflammation or other pathological processes. Thus, the true value Christian Schulte of novel biomarker candidates in HF prognostication remains unclear. In this article, we [email protected] discuss the current state of application of protein, genetic as well as non-coding RNA Specialty section: biomarkers in HF risk prognosis. This article was submitted to Keywords: biomarker, heart failure, prognosis, protein biomarker, NT-proBNP, non-coding RNA, genetic risk score Heart Failure and Transplantation, a section of the journal Frontiers in Cardiovascular Medicine INTRODUCTION Received: 31 August 2020 Accepted: 14 October 2020 Heart failure (HF) is a complex cardiovascular disease (CVD) in which the heart’s functional Published: 23 November 2020 capacity is reduced, leading to failure in meeting the body’s blood and oxygen demand (1). The Citation: most common risk factors are age, sex, environmental risk factors, genetic disposition, and diseases Shrivastava A, Haase T, Zeller T and such as diabetes, hypertension, coronary artery disease, and atrial fibrillation. HF is described Schulte C (2020) Biomarkers for Heart Failure Prognosis: Proteins, Genetic as a global pandemic as it affects ∼26 million people worldwide (2). In North America and Scores and Non-coding RNAs. Europe, >80% of HF cases comprise of people who are ≥65 years old (2–5). Survival rate of Front. Cardiovasc. Med. 7:601364. HF patients is poor with 2–17% of HF patients dying while in hospital, 17–45% patients die doi: 10.3389/fcvm.2020.601364 within 1-year of admission and the majority dies within 5-years of admission (6). Due to the high Frontiers in Cardiovascular Medicine | www.frontiersin.org 1 November 2020 | Volume 7 | Article 601364 Shrivastava et al. Biomarkers for Heart Failure Prognosis mortality rates associated with HF, early diagnosis of the first In this review article, we elucidate the role of the most subclinical signs is essential to prevent severe outcomes. prominent circulating protein biomarkers which show promising HF is a multi-system disorder which is characterized by results in HF prognosis. In addition, we provide details on a decrease in functional capacity of the heart. Reduced genetic biomarkers and polygenic risk scores that are currently cardiac output due to impairment in left ventricular function being developed along with details about emerging evidence on leads to an activation of the neuro-hormonal system. This, circulating non-coding RNA biomarkers. in turn, stimulates the renin-angiotensin-aldosterone system leading to increased concentrations of renin, angiotensin II and PROTEIN-BASED BIOMARKERS aldosterone, each of which causes salt and water retention, vasoconstriction, and enhanced sympathetic activity. Prolonged Protein biomarkers are released into the circulation and can exposure to neuro-hormonal activation leads to dilation and be detected using various assays. Protein biomarkers that have structural changes in the myocardium and fibrosis, thereby entered the prognostic field for HF are either released from further worsening cardiac output (7). The severity of HF is graded the heart exhibiting its value of tissue-specific damage, or in accordance to the New York Heart Association (NYHA) are released from other cells as a systemic response to HF classification I, II, III, and IV. This gradation is based on patient (Figure 2). In addition to tissue specificity, the half-life of protein clinical symptoms and effect of HF on their physical mobility. biomarkers is often the crucial factor for its potential use as This definition also takes into account the decrease in the left a biomarker (Table 1). The ease of measurement of circulating ventricular ejection fraction (LVEF), classifying HF as either protein biomarkers and the speed of assay results make them HF with preserved ejection fraction (HFpEF; LVEF ≥50%) or invaluable to HF diagnosis and prognosis. HF with reduced ejection fraction (HFrEF, LVEF 200 nucleotides in length patients suffering from severe MI (74), introducing a potential (198). There is thus far no agreement on sub-classification for detectability bias in quantification efforts; (2) up to date there are these RNAs. A recent review summarized different characteristic no harmonized methods with respect to miRNA quantification, features that could be used for this purpose, comprising of their which is particularly problematic for miRNA quantification in length, their relation to protein-coding genes or their relation low-RNA-yield samples such as plasma and serum in terms of to DNA/promoter elements (199). Unlike miRNAs, lncRNAs comparability of the results (78); (3) Only few large-scale studies are mainly located within the nucleus or in mitochondria have been conducted assessing the prognostic properties of (200, 201) (Figure 4) and their biosynthesis seems to largely miRNAs in CVD and their common interpretation of the results overlap with that of mRNAs with regards to their transcription, is, that not single miRNAs, but instead miRNA combinations polyadenylation, capping, and splicing (202). For the majority comprise prognostic potential as biomarker (194, 195). of identified lncRNAs, the function remains unclear. Nuclear Detailed reviews of specific cardiac-enriched (187) and other lncRNAs are involved in regulation of neighboring loci through miRNAs (196) involved in HFrEF and HFpEF (172) are beyond transcriptional regulation or by inhibiting expression of a gene the scope of this article and can be found elsewhere. Using miR- through sequestration of transcription factors (203). Conversely, 1 as an example, it can be seen that miRNAs are important other lncRNAs were shown to enhance transcription of genes. biological players in the development of HF and are suggested lncRNAs are more tissue-specific than protein coding genes (200) as promising circulating biomarker in HF prognostication, while and compared with miRNAs, many more transcripts have been Frontiers in Cardiovascular Medicine | www.frontiersin.org 11 November 2020 | Volume 7 | Article 601364 Shrivastava et al. Biomarkers for Heart Failure Prognosis identified (204). They have emerged as mediators of protein proven to be expressed in a tissue- and developmental-specific translation (205). Data is available suggesting key regulatory context (214, 215). They can either emerge from exons or roles of lncRNAs in cardiac and vascular tissue with respect to introns of primary gene transcripts (pre-mRNA) (215, 216) CVD (205). Both, miRNAs and lncRNAs are potent regulators of and are products of alternative splicing in a head-to-tail translation and their expression influences protein levels, while fashion known as “back-splicing” (214) (Figure 4). circRNAs at the same time these two ncRNA species influence each other’s are resistant to degradation by the exonuclease RNase R—a expression (206). type of RNase that cleaves linear RNA. RNase R treatment Several lncRNAs are also readily detected in the circulation. can therefore be used to enrich circRNAs over their linear This indicates the presence of protective mechanisms against counterparts (217, 218). In combination with the use of divergent RNase-mediated degradation, for which the mechanisms show primers in polymerase chain reaction (PCR) amplification, overlap with those of miRNAs (198). The plasma level of Long this approach yields high specificity for the detection of Intergenic ncRNA Predicting CArdiac Remodeling (LIPCAR) circular transcripts. was found to predict adverse cardiac remodeling and death in Functionally, circRNAs appear to influence gene expression in the aftermath of MI, imposing an increased risk for ischemic different ways. They act as potent miRNA sponges—decreasing cardiomyopathy and HF (201). Thus, LIPCAR has potential as the inhibitory effect of miRNAs on protein synthesis (219). a circulating biomarker for HF prognostication, but has not yet More recently, circRNAs were reported to be translated into been evaluated in a clinical trial. Myosin Heavy Chain Associated proteins (220). At the same time, their expression is regulated RNA Transcripts (MHRT) levels were found dysregulated in by proteins such as RNA-binding proteins. circRNAs appear to plasma depending on the SNP alleles (rs7140721, rs3729829, and influence gene expression by competing with splicing of their rs3729825) in chronic HF patients. Significant difference in risk linear counterparts (173, 218, 221). circRNA expression has been of mortality was observed based on these SNP genotypes (p < mapped in different tissue types and it is now clear that they can 0.001) indicating an association of these SNPs with chronic HF be reliably detected in a tissue- and cell-specific manner, whilst risk and prognosis (207). The latter might provide a way to also showing a certain degree of conservation across species link a single circulating molecule/biomarker with genetic risk (173, 222). prediction, while additional evaluation of this interesting link Bearing in mind the vast opportunities for disease detection remains to be further explored. lncRNA H19 was discovered and possibly treatment offered by miRNAs, efforts have been to be down-regulated in failing hearts from mice and was undertaken to evaluate circRNAs for their applicability as validated in pig and human hearts (208). The authors were biomarkers and disease modifiers. A growing number of studies further able to prove H19’s essential HF-reversing effect. While have reported the involvement of circRNAs across features these findings are backed-up by similar results on cardiac tissue of CVD, indicating diagnostic potential as well as potential level (209), validation of H19 as a circulating biomarker for relevance as regulators of biology (223). Sequencing data revealed HF prognostication is still pending. These findings indicate the more than 15,000 circRNAs present in the human heart, some potential use of lncRNAs as prognostic circulating biomarkers for in high abundance (224). A number of studies have described CVD—similar to some miRNAs. cardiac circRNAs to be involved in MI-related apoptosis in the lncRNAs are promising RNA molecules with good myocardium (225, 226) and circRNA MICRA was identified characteristics as circulating biomarkers for CVD such as to predict left ventricular dysfunction in MI patients (227). detectability in the circulation and distinct biological function in The results were validated in a different study where circRNA the heart. Their general exploration as circulating biomarkers is MICRA was reported to improve risk stratification of post- still in its infancy and more interesting results can be expected in MI patients (228). Recently, cardiac circRNAs were assessed for the near future. their detectability in the circulation after MI in a controlled stepwise approach (74). Interestingly, none of the screened and circRNAs validated circRNAs were identified as well-enough detectable The first single-stranded DNA product (replicating form of in neither plasma nor serum to be used as circulating cell-free DNA) that was shown to have a circular shape was described biomarkers. The findings question the validity of quantifying by Chandler et al. in 1964 (210), whereas the first circular circulating circRNAs in cell-free body liquids using currently RNA was described a decade later in plant viroids (211). Before available technology. In fact, when studying literature regarding circular RNAs were first described in humans in 1993, RNA circulating circRNAs including the abovementioned studies species were identified, where “exons were joined accurately regarding circRNA MICRA, an interesting fact can be observed: at consensus splice sites, but in an order different from that all circulating circRNA biomarker studies report their findings in present in genomic DNA”(212). These “scrambled exons” were whole blood samples—containing a large number of circulating described as stable and situated in the cellular cytoplasm (213). cells instead of cell-free serum or plasma. The use of whole Only during the past decade however, novel RNA analysis blood samples in the assessment of disease biomarkers yields tools such as biochemical enrichment strategies and high- a risk of confounding by cells such as platelets and leukocytes. throughput deep sequencing methods have allowed for large Thus, the assessment of circRNAs as circulating biomarkers in numbers of circRNAs to be detected (214). circRNAs are CVD currently suffers from detectability problems and efforts to a stable RNA species, endogenous to mammalian cells and improve detectability are needed to further evaluate this issue. Frontiers in Cardiovascular Medicine | www.frontiersin.org 12 November 2020 | Volume 7 | Article 601364 Shrivastava et al. Biomarkers for Heart Failure Prognosis TABLE 2 | Characteristics of a biomarker. Characteristics of a biomarker Protein biomarkers Genetic biomarkers Non-coding RNA biomarkers Pathophysiological reliability Stability - of biomolecule in body fluids Accessability - through routine clinical procedures Added value - does the biomarker improve standard clinical evaluation/risk stratification? Detectability - is the biomarker stably detectable in target phenotype? Diagnostic and/or prognostic validation - can the biomarker differentiate affected vs. non-affected individuals? Consensual agreement - are the quantification techniques standardized? Reference values - are they available and reliable? Comparability - of results across centers Gender specificity Tested in various ethnicities Protein biomarkers are the most widely used, largely due to methodological advances in their quantification methods and consensual agreement on their detection techniques. Genetic risk scores have the advantage of gender specificity tested across various ethnicities. ncRNAs specifically lack consensual agreement on the quantification methods, reference values and thus comparability of results. DISCUSSION implementation into clinical routine at the current stage. ncRNAs can be stably detected in the circulation and their potential The identification and further exploration of biomolecules as circulating biomarkers has been recognized. Several ncRNAs suitable as biomarkers for specific disease is a complex process, have been studied in the context of CVD. miRNAs, lncRNAs, which requires numerous prerequisites to be met such as and circRNAs are the most promising ncRNA species being detectability in the circulation, reliable quantification methods, evaluated for their biomarker potential. Several of them are pathophysiologic relation to the suspected disease, and many expressed in a cell type- and tissue-specific manner and are more (Table 2). Proteins have been evaluated as circulating involved in distinct physiological and pathological processes, biomarkers for quite a long time and their quantification raising hopes for them to evolve as helpful in diagnosis and methods are established. They have also been analyzed for their prognosis of CVD and HF. Currently, application of ncRNAs applicability in heart failure prognosis with promising results in clinical settings is hampered by methodological issues such already available. Nevertheless, validation of existing results is as lack of harmonized quantification methods and suboptimal crucial and has only just begun in this respect. Interestingly, the detectability in the circulation of some transcripts. added value of promising protein biomarkers on top of classic With respect to HF prognostication, currently the best data is risk factors still remains limited. Therefore, the exploration of available for NT-proBNP, which has been used in the diagnosis alternative biomarkers is a focus of current biomarker research. of HF for decades. Its value in HF prognostication has recently Alternatives such as genetic risk scores and also ncRNAs have been recognized and validation of currently available results caught scientists’ attention for a few years. Genetic biomarkers seems to be only a matter of time. NT-proBNP has been provide a promising platform to improve mid- and long-term included into the ESC and AHA guidelines not only because prognostication of HF, in particular with regards to improving it provides insights into the severity of cardiac damage, but individualized approaches of risk evaluation. On the other hand, also because current assays allow its detection even at small the current laboratory methodology for their determination amounts. But importantly, there is still need for validation of is complex, expensive, and time-consuming, limiting their sensitivity and specificity. Large-scale population-based cohort Frontiers in Cardiovascular Medicine | www.frontiersin.org 13 November 2020 | Volume 7 | Article 601364 Shrivastava et al. Biomarkers for Heart Failure Prognosis studies applying state-of-the-art laboratory methodology will AUTHOR CONTRIBUTIONS give the opportunity to identify additional prognostic biomarkers such as genetic biomarkers and validate existing biomarkers for AS, TH, and CS wrote the manuscript. TZ and CS edited the the prognosis of HF. Tissue-specificity seems to play a major role manuscript, figures and tables. All authors were responsible for in the application of biomolecules as biomarkers when assessing overall editing of the manuscript. All authors contributed to the single markers and it is not surprising that NT-proBNP, as one article and approved the submitted version. of only few heart-specific markers, ranks high in the list of biomarker candidates for HF prognostication. On the other hand, FUNDING given the complex etiology of HF, up until now trials failed to identify single biomarkers in the prognostic assessment of TZ is funded by the German Center for Cardiovascular patients with HF. This stretches the importance of the idea to Research (DZHK). CS was funded by a research fellowship identify complementary biomarkers in order to define biomarker by the Deutsche Forschungsgemeinschaft (DFG) (SCHU panels as a promising way of improving prognostication of 2983/1-1 and SCHU 2983/2-1). TH is funded by Grant multifactorial disease entities such as HF and argues to include No. 8/18 from the Ernst und Berta Grimmke-Stiftung and non-organ-specific molecules, which may provide a readout of the Research Promotion Fund of the Faculty of Medicine systemic disease, such as i.e., inflammation, in the seek for (FFM) of the University Medical Center Eppendorf, biomarkers in HF. Hamburg (UKE). REFERENCES 12. Lang RM, Badano LP, Mor-Avi V, Afilalo J, Armstrong A, Ernande L, et al. Recommendations for cardiac chamber quantification by 1. National Heart Lung and Blood Institute. What Is Heart Failure? Maryland, echocardiography in adults: an update from the American society of MD: Nhlbi (2015). Available online at: https://www.nhlbi.nih.gov/health- echocardiography and the European Association of cardiovascular imaging. topics/heart-failure. J Am Soc Echocardiogr. (2015) 28:1–39.e14. doi: 10.1016/j.echo.2014. 2. Ambrosy AP, Fonarow GC, Butler J, Chioncel O, Greene SJ, Vaduganathan 10.003 M, et al. The global health and economic burden of hospitalizations 13. Gonzalez JA, Kramer CM. Role of imaging techniques for diagnosis, for heart failure: lessons learned from hospitalized heart failure prognosis and management of heart failure patients: cardiac registries. J Am Coll Cardiol. (2014) 63:1123–33. doi: 10.1016/j.jacc.2013. magnetic resonance. Curr Heart Fail Rep. (2015) 12:276–83. 11.053 doi: 10.1007/s11897-015-0261-9 3. Go AS, Mozaffarian D, Roger VL, Benjamin EJ, Berry JD, Blaha 14. Hundley WG, Bluemke DA, Finn JP, Flamm SD, Fogel MA, Friedrich MG, MJ, et al. Heart disease and stroke statistics−2014 update: a report et al. ACCF/ACR/AHA/NASCI/SCMR 2010 expert consensus document on from the American heart association. Circulation. (2014) 129:e28–292. cardiovascular magnetic resonance: a report of the American College of doi: 10.1161/01.cir.0000441139.02102.80 cardiology foundation task force on expert consensus documents. J Am Coll 4. Ceia F, Fonseca C, Mota T, Morais H, Matias F, de Sousa A, Cardiol. (2010) 55:2614–62. doi: 10.1016/j.jacc.2009.11.011 et al. Prevalence of chronic heart failure in Southwestern Europe: the 15. Kilner PJ, Geva T, Kaemmerer H, Trindade PT, Schwitter J, Webb EPICA study. Eur Heart J. (2002) 4:531–9. doi: 10.1016/S1388-9842(02) GD. Recommendations for cardiovascular magnetic resonance in adults 00034-X with congenital heart disease from the respective working groups of 5. Townsend N, Wickramasinghe K, Bhatnagar P, Nichols MS, Leal J, the European society of cardiology. Eur Heart J. (2010) 31:794–805. et al. Coronary Heart Disease Statistics (2012 Edition). London: British doi: 10.1093/eurheartj/ehp586 Heart Foundation (2012). Available online at: https://www.bhf.org. 16. Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JGF, Coats AJS, et al. uk/informationsupport/publications/statistics/coronary-heart-disease- 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic statistics-2012 (accessed July 26, 2020). heart failure. Eur J Heart Fail. (2016) 18:891–975. doi: 10.1002/ejhf.592 6. Ponikowski P, Anker SD, Alhabib KF, Cowie MR, Force TL, Hu S, et al. Heart 17. Yancy CW, Jessup M, Bozkurt B, Butler J, Casey DE, Colvin MM, et al. failure: preventing disease and death worldwide. ESC Heart Fail. (2014) 2017 ACC/AHA/HFSA focused update of the 2013 ACCF/AHA Guideline 1:4–25. doi: 10.1002/ehf2.12005 for the management of heart failure: a report of the American college 7. Jackson G, Gibbs CR, Davies MK, Lip GY. ABC of heart failure of cardiology/American heart association task force on clinical practice Pathophysiology. BMJ. (2000) 320:167–70. doi: 10.1136/bmj.320.7228.167 guidelines and the heart failure society of America. Circulation. (2017) 8. Hawkins NM, Petrie MC, Jhund PS, Chalmers GW, Dunn FG, 136:e137–e161. doi: 10.1161/CIR.0000000000000509 Mcmurray JJ. Heart failure and chronic obstructive pulmonary disease: 18. Maisel AS, Duran JM, Wettersten N. Natriuretic peptides in heart failure: diagnostic pitfalls and epidemiology. Eur J Heart Fail. (2009) 11:130–9. atrial and B-type natriuretic peptides. Heart Fail Clin. (2018) 14:13–25. doi: 10.1093/eurjhf/hfn013 doi: 10.1016/j.hfc.2017.08.002 9. Thomas JT, Kelly RF, Thomas SJ, Stamos TD, Albasha K, Parrillo 19. Nakagawa Y, Nishikimi T, Kuwahara K. Atrial and brain natriuretic JE, et al. Utility of history, physical examination, electrocardiogram, peptides: hormones secreted from the heart. Peptides. (2019) 111:18–25. and chest radiograph for differentiating normal from decreased systolic doi: 10.1016/j.peptides.2018.05.012 function in patients with heart failure. Am J Med. (2002) 112:437–45. 20. Nishikimi T, Maeda N, Matsuoka H. The role of natriuretic doi: 10.1016/S0002-9343(02)01048-3 peptides in cardioprotection. Cardiovasc Res. (2006) 69:318–28. 10. Kirkpatrick JN, Vannan MA, Narula J, Lang RM. Echocardiography in heart doi: 10.1016/j.cardiores.2005.10.001 failure: applications, utility, and new horizons. J Am Coll Cardiol. (2007) 21. Nishikimi T, Kuwahara K, Nakao K. Current biochemistry, 50:381–96. doi: 10.1016/j.jacc.2007.03.048 molecular biology, and clinical relevance of natriuretic 11. Nagueh SF, Bhatt R, Vivo RP, Krim SR, Sarvari SI, Russell K, peptides. J Cardiol. (2011) 57:131–40. doi: 10.1016/j.jjcc.2011. et al. Echocardiographic evaluation of hemodynamics in patients with 01.002 decompensated systolic heart failure. Circ Cardiovasc Imaging. (2011) 4:220– 22. Tokola H, Hautala N, Marttila M, Magga J, Pikkarainen S, Kerkelä 7. doi: 10.1161/CIRCIMAGING.111.963496 R, et al. Mechanical load-induced alterations in B-type natriuretic Frontiers in Cardiovascular Medicine | www.frontiersin.org 14 November 2020 | Volume 7 | Article 601364 Shrivastava et al. Biomarkers for Heart Failure Prognosis peptide gene expression. Canad J Physiol Pharmacol. (2001) 79:646–53. and renal, hormonal, and hemodynamic responses to peptide infusion. J Clin doi: 10.1139/y01-031 Invest. (1986) 78:1362–74. 23. Daniels LB, Maisel AS. Natriuretic peptides. J Am College Cardiol. (2007) 40. Goetze JP, Hansen LH, Terzic D, Zois NE, Albrethsen J, Timm A, et al. 50:2357–68. doi: 10.1016/j.jacc.2007.09.021 Atrial natriuretic peptides in plasma. Clin Chim Acta. (2015) 443:25–8. 24. Potter LR. Natriuretic peptide metabolism, clearance and degradation. FEBS doi: 10.1016/j.cca.2014.08.017 J. (2011) 278:1808–17. doi: 10.1111/j.1742-4658.2011.08082.x 41. Lee CY, Burnett JC, Jr. Natriuretic peptides and therapeutic applications. 25. Abassi Z, Karram T, Ellaham S, Winaver J, Hoffman A. Implications Heart Fail Rev. (2007) 12:131–42. doi: 10.1007/s10741-007-9016-3 of the natriuretic peptide system in the pathogenesis of heart failure: 42. Yandle TG, Richards AM, Nicholls MG, Cuneo R, Espiner EA, Livesey diagnostic and therapeutic importance. Pharmacol Ther. (2004) 102:223–41. JH. Metabolic clearance rate and plasma half life of alpha-human atrial doi: 10.1016/j.pharmthera.2004.04.004 natriuretic peptide in man. Life Sci. (1986) 38:1827–33. 26. Baba M, Yoshida K, Ieda M. Clinical applications of natriuretic peptides 43. Nakao K, Sugawara A, Morii N, Sakamoto M, Yamada T, Itoh H, et al. in heart failure and atrial fibrillation. Int J Mol Sci. (2019) 20:2824. The pharmacokinetics of α-human atrial natriuretic polypeptide in healthy doi: 10.3390/ijms20112824 subjects. Euro J of Clin. (1986) Pharmacol. 31:101–3. 27. Masson S, Latini R, Anand IS, Barlera S, Angelici L, Vago T, et al. Prognostic 44. Morgenthaler NG, Struck J, Thomas B, Bergmann A. Immunoluminometric value of changes in N-terminal pro-brain natriuretic peptide in Val-HeFT assay for the midregion of pro-atrial natriuretic peptide in human plasma. (valsartan heart failure trial). J Am College Cardiol. (2008) 52:997–1003. Clin Chem. (2004) 50:234–6. doi: 10.1373/clinchem.2003.021204 doi: 10.1016/j.jacc.2008.04.069 45. Seronde M-F, Gayat E, Logeart D, Lassus J, Laribi S, Boukef R, et al. 28. Bettencourt P, Azevedo A, Pimenta J, Friões F, Ferreira S, Ferreira A. Comparison of the diagnostic and prognostic values of B-type and atrial-type N-terminal-pro-brain natriuretic peptide predicts outcome after hospital natriuretic peptides in acute heart failure. Int J Cardiol. (2013) 168:3404–11. discharge in heart failure patients. Circulation. (2004) 110:2168–74. doi: 10.1016/j.ijcard.2013.04.164 doi: 10.1161/01.CIR.0000144310.04433.BE 46. Zelenak C, Chavanon M-L, Tahirovic E, Trippel TD, Tscholl V, Stroux A, et al. 29. Hartmann F, Packer M, Coats AJS, Fowler MB, Krum H, Mohacsi P, et al. Early NT-proBNP and MR-proANP associated with QoL 1 year after acutely Prognostic impact of plasma N-terminal pro-brain natriuretic peptide in decompensated heart failure: secondary analysis from the MOLITOR trial. severe chronic congestive heart failure. Circulation. (2004) 110:1780–6. Biomark Med. (2019) 13:1493–507. doi: 10.2217/bmm-2019-0083 doi: 10.1161/01.CIR.0000143059.68996.A7 47. Masson S, Latini R, Carbonieri E, Moretti L, Rossi MG, Ciricugno S, et al. 30. Logeart D, Thabut G, Jourdain P, Chavelas C, Beyne P, Beauvais F, et al. The predictive value of stable precursor fragments of vasoactive peptides in Predischarge B-type natriuretic peptide assay for identifying patients at high patients with chronic heart failure: data from the GISSI-heart failure (GISSI- risk of re-admission after decompensated heart failure. J Am Coll Cardiol. HF) trial. Euro J Heart Failure. (2010) 12, 338–47. doi: 10.1093/eurjhf/hfp206 (2004) 43:635–41. doi: 10.1016/j.jacc.2003.09.044 48. Tzikas S, Keller T, Ojeda FM, Zeller T, Wild PS, Lubos E, et al. MR-proANP 31. Stolfo D, Stenner E, Merlo M, Porto AG, Moras C, Barbati G, et al. Prognostic and MR-proADM for risk stratification of patients with acute chest pain. impact of BNP variations in patients admitted for acute decompensated heart Heart. (2013) 99:388–95. doi: 10.1136/heartjnl-2012-302956 failure with in-hospital worsening renal function. Heart Lung Circ. (2017) 49. Arrigo M, Truong QA, Szymonifka J, Rivas-Lasarte M, Tolppanen H, 26:226–34. doi: 10.1016/j.hlc.2016.06.1205 Sadoune M, et al. Mid-regional pro-atrial natriuretic peptide to predict 32. Zile MR, Claggett BL, Prescott MF, Mcmurray JJV, Packer M, Rouleau clinical course in heart failure patients undergoing cardiac resynchronization JL, et al. Prognostic implications of changes in N-terminal pro-B-type therapy. Europace. (2017) 19:1848–54. doi: 10.1093/europace/euw305 natriuretic peptide in patients with heart failure. J Am Coll Cardiol. (2016) 50. Parmacek MS, Solaro RJ. Biology of the troponin complex 68:2425–36. doi: 10.1016/j.jacc.2016.09.931 in cardiac myocytes. Prog Cardiovasc Dis. (2004) 47:159–76. 33. Myhre PL, Vaduganathan M, Claggett B, Packer M, Desai AS, Rouleau JL, doi: 10.1016/j.pcad.2004.07.003 et al. B-type natriuretic peptide during treatment with sacubitril/valsartan. 51. Felker GM, Hasselblad V, Tang WHW, Hernandez AF, Armstrong PW, the PARADIGM-HF trial. J Am Coll Cardiol. (2019) 73:1264–72. Fonarow GC, et al. Troponin I in acute decompensated heart failure: doi: 10.1016/j.jacc.2019.01.018 insights from the ASCEND-HF study. Eur J Heart Fail. (2012) 14:1257–64. 34. Noveanu M, Breidthardt T, Potocki M, Reichlin T, Twerenbold R, doi: 10.1093/eurjhf/hfs110 Uthoff H, et al. Direct comparison of serial B-type natriuretic peptide 52. Gravning J, Askevold ET, Nymo SH, Ueland T, Wikstrand J, Mcmurray and NT-proBNP levels for prediction of short- and long-term outcome JJV, et al. Prognostic effect of high-sensitive troponin t assessment in in acute decompensated heart failure. Critical Care. (2011) 15:R1. elderly patients with chronic heart failure. Circulation. (2014) 7:96–103. doi: 10.1186/cc9398 doi: 10.1161/CIRCHEARTFAILURE.113.000450 35. Weiner RB, Baggish AL, Chen-Tournoux A, Marshall JE, Gaggin 53. Felker GM, Mentz RJ, Teerlink JR, Voors AA, Pang PS, Ponikowski P, et al. HK, Bhardwaj A, et al. Improvement in structural and functional Serial high sensitivity cardiac troponin T measurement in acute heart failure: echocardiographic parameters during chronic heart failure therapy guided insights from the RELAX-AHF study. Eur J Heart Fail. (2015) 17:1262–70. by natriuretic peptides: mechanistic insights from the ProBNP Outpatient doi: 10.1002/ejhf.341 Tailored Chronic Heart Failure (PROTECT) study. Eur J Heart Fail. (2013) 54. Welsh P, Kou L, Yu C, Anand I, Van Veldhuisen DJ, Maggioni AP, 15:342–51. doi: 10.1093/eurjhf/hfs180 et al. Prognostic importance of emerging cardiac, inflammatory, and 36. Stienen S, Salah K, Moons AH, Bakx AL, Van Pol P, Kortz R, renal biomarkers in chronic heart failure patients with reduced ejection et al. NT-proBNP (N-terminal pro-B-type natriuretic peptide)- fraction and anaemia: RED-HF study. Eur J Heart Fail. (2018) 20:268–77. guided therapy in acute decompensated heart failure: PRIMA II doi: 10.1002/ejhf.988 randomized controlled trial (Can NT-ProBNP-guided therapy during 55. Rørth R, Jhund PS, Kristensen SL, Desai AS, Køber L, Rouleau JL, et al. hospital admission for acute decompensated heart failure reduce The prognostic value of troponin T and N-terminal pro B-type natriuretic mortality and readmissions?). Circulation. (2018) 137:1671–83. peptide, alone and in combination, in heart failure patients with and without doi: 10.1161/CIRCULATIONAHA.117.029882 diabetes. Eur J Heart Fail. (2019) 21:40–9. doi: 10.1002/ejhf.1359 37. Edwards BS, Zimmerman RS, Schwab TR, Heublein DM, and Burnett JC, Jr. 56. Ford I, Shah AS, Zhang R, Mcallister DA, Strachan FE, Caslake M, et al. Atrial stretch, not pressure, is the principal determinant controlling the acute High-sensitivity cardiac troponin, statin therapy, and risk of coronary heart release of atrial natriuretic factor. Circ Res. (1988) 62:191–5. disease. J Am Coll Cardiol. (2016) 68:2719–28. doi: 10.1016/j.jacc.2016.10.020 38. Marin-Grez M, Fleming JT, and Steinhausen M. Atrial natriuretic peptide 57. Omland T, Røsj,ø H, Giannitsis E, Agewall S. Troponins in heart failure. Clin causes pre-glomerular vasodilatation and post-glomerular vasoconstriction Chim Acta. (2015) 443:78–84. doi: 10.1016/j.cca.2014.08.016 in rat kidney. Nature. (1986) 324:473–6. 58. Ackermann MA, Kontrogianni-Konstantopoulos A. Myosin binding 39. Cody RJ, Atlas SA, Laragh JH, Kubo SH, Covit AB, Ryman KS, et al. Atrial protein-C: a regulator of actomyosin interaction in striated muscle. J Biomed natriuretic factor in normal subjects and heart failure patients. Plasma levels Biotechnol. (2011) 2011:636403. doi: 10.1155/2011/636403 Frontiers in Cardiovascular Medicine | www.frontiersin.org 15 November 2020 | Volume 7 | Article 601364 Shrivastava et al. Biomarkers for Heart Failure Prognosis 59. Finley NL, Cuperman TI. Cardiac myosin binding protein-C: a structurally of acute myocardial infarction. Circulation. (2017) 136:1495–508. dynamic regulator of myocardial contractility. Pflügers Archiv. (2014) doi: 10.1161/CIRCULATIONAHA.117.028084 466:433–8. doi: 10.1007/s00424-014-1451-0 77. Baker JO, Tyther R, Liebetrau C, Clark J, Howarth R, Patterson T, et al. 60. Sadayappan S, Osinska H, Klevitsky R, Lorenz JN, Sargent M, Molkentin JD, Cardiac myosin-binding protein C: a potential early biomarker of myocardial et al. Cardiac myosin binding protein C phosphorylation is cardioprotective. injury. Basic Res Cardiol. (2015) 110:23. doi: 10.1007/s00395-015-0478-5 Proc Natl Acad Sci USA. (2006) 103:16918–23. doi: 10.1073/pnas.0607069103 78. Schulte C, Barwari T, Joshi A, Zeller T, Mayr M. Noncoding RNAs versus 61. Lin B, Govindan S, Lee K, Zhao P, Han R, Runte KE, et al. Cardiac myosin protein biomarkers in cardiovascular disease. Trends Mol Med. (2020) binding protein-c plays no regulatory role in skeletal muscle structure and 26:583–96. doi: 10.1016/j.molmed.2020.02.001 function. PLoS ONE. (2013) 8:e69671. doi: 10.1371/journal.pone.0069671 79. El Amrousy D, Hodeib H, Suliman G, Hablas N, Salama ER, Esam A. 62. Ababou A, Gautel M, Pfuhl M. Dissecting the N-terminal myosin Diagnostic and prognostic value of plasma levels of cardiac myosin binding binding site of human cardiac myosin-binding protein C. Structure protein-C as a novel biomarker in heart failure. Pediatric Cardiol. 38:418–24. and myosin binding of domain C2. J Biol Chem. (2007) 282:9204–15. doi: 10.1007/s00246-016-1532-2 doi: 10.1074/jbc.M610899200 80. Anand A, Chin C, Shah ASV, Kwiecinski J, Vesey A, Cowell J, et al. 63. Sadayappan S, Gulick J, Osinska H, Barefield D, Cuello F, Avkiran M, Cardiac myosin-binding protein C is a novel marker of myocardial et al. A critical function for Ser-282 in cardiac Myosin binding protein- injury and fibrosis in aortic stenosis. Heart. (2018) 104:1101–8. C phosphorylation and cardiac function. Circ Res. (2011) 109:141–50. doi: 10.1136/heartjnl-2017-312257 doi: 10.1161/CIRCRESAHA.111.242560 81. Piek A, Du W, De Boer RA, Silljé HHW. Novel heart failure biomarkers: why 64. Shaffer JF, Kensler RW, Harris SP. (2009). The myosin-binding protein C do we fail to exploit their potential? Crit Rev Clin Lab Sci. (2018) 55:246–63. motif binds to F-actin in a phosphorylation-sensitive manner. J Biol Chem. doi: 10.1080/10408363.2018.1460576 (2011) 284:12318–27. doi: 10.1074/jbc.M808850200 82. Otaki Y, Watanabe T, Kubota I. Heart-type fatty acid-binding protein in 65. Govindan S, Sarkey J, Ji X, Sundaresan NR, Gupta MP, De Tombe PP, cardiovascular disease: a systemic review. Clin Chim Acta. (2017) 474:44–53. et al. Pathogenic properties of the N-terminal region of cardiac myosin doi: 10.1016/j.cca.2017.09.007 binding protein-C in vitro. J Muscle Res Cell Motil. (2012) 33:17–30. 83. Okamoto F, Sohmiya K, Ohkaru Y, Kawamura K, Asayama K, Kimura H, doi: 10.1007/s10974-012-9292-y et al. Human heart-type cytoplasmic fatty acid-binding protein (H-FABP) for 66. Govindan S, Mcelligott A, Muthusamy S, Nair N, Barefield D, Martin the diagnosis of acute myocardial infarction. clinical evaluation of H-FABP in JL, et al. Cardiac myosin binding protein-C is a potential diagnostic comparison with myoglobin and creatine kinase isoenzyme MB. Clin Chem biomarker for myocardial infarction. J Mol Cell Cardiol. (2012) 52:154–64. Lab Med. (2000) 38:231–8. doi: 10.1515/CCLM.2000.034 doi: 10.1016/j.yjmcc.2011.09.011 84. Aartsen WM, Pelsers MM, Hermens WT, Glatz JF, Daemen MJ, 67. Razzaque MA, Gupta M, Osinska H, Gulick J, Blaxall BC, Robbins J. An Smits JF. Heart fatty acid binding protein and cardiac troponin endogenously produced fragment of cardiac myosin-binding protein C is T plasma concentrations as markers for myocardial infarction after pathogenic and can lead to heart failure. Circ Res. (2013) 113:553–61. coronary artery ligation in mice. Pflugers Arch. (2000) 439:416–22. doi: 10.1161/CIRCRESAHA.113.301225 doi: 10.1007/s004249900180 68. Govindan S, Kuster DW, Lin B, Kahn DJ, Jeske WP, Walenga JM, et al. 85. Kleine AH, Glatz JF, Van Nieuwenhoven FA, Van Der Vusse GJ. Release of Increase in cardiac myosin binding protein-C plasma levels is a sensitive and heart fatty acid-binding protein into plasma after acute myocardial infarction cardiac-specific biomarker of myocardial infarction. Am J Cardiovasc Dis. in man. Mol Cell Biochem. (1992) 116:155–62. doi: 10.1007/BF01270583 (2013) 3:60–70. 86. Ishii J, Ozaki Y, Lu J, Kitagawa F, Kuno T, Nakano T, et al. 69. El-Armouche A, Pohlmann L, Schlossarek S, Starbatty J, Yeh YH, Nattel S, Prognostic value of serum concentration of heart-type fatty acid-binding et al. Decreased phosphorylation levels of cardiac myosin-binding protein-C protein relative to cardiac troponin T on admission in the early in human and experimental heart failure. J Mol Cell Cardiol. (2007) 43:223–9. hours of acute coronary syndrome. Clin Chem. (2005) 51:1397–404. doi: 10.1016/j.yjmcc.2007.05.003 doi: 10.1373/clinchem.2004.047662 70. Jacques AM, Copeland O, Messer AE, Gallon CE, King K, Mckenna WJ, 87. Kazimierczyk E, Kazimierczyk R, Harasim-Symbor E, Kaminski K, et al. Myosin binding protein C phosphorylation in normal, hypertrophic Sobkowicz B, Chabowski A, et al. Persistently elevated plasma heart-type and failing human heart muscle. J Mol Cell Cardiol. (2008) 45:209–16. fatty acid binding protein concentration is related with poor outcome in doi: 10.1016/j.yjmcc.2008.05.020 acute decompensated heart failure patients. Clin Chim Acta. (2018) 487:48– 71. Zaremba R, Merkus D, Hamdani N, Lamers JM, Paulus WJ, Dos Remedios 53. doi: 10.1016/j.cca.2018.09.004 C, et al. Quantitative analysis of myofilament protein phosphorylation 88. Niizeki T, Takeishi Y, Arimoto T, Nozaki N, Hirono O, Watanabe T, et al. in small cardiac biopsies. Proteomics Clin Appl. (2007) 1:1285–90. Persistently increased serum concentration of heart-type fatty acid-binding doi: 10.1002/prca.200600891 protein predicts adverse clinical outcomes in patients with chronic heart 72. Copeland O, Sadayappan S, Messer AE, Steinen GJ, Van Der Velden J, failure. Circ J. (2008) 72:109–14. doi: 10.1253/circj.72.109 Marston SB. Analysis of cardiac myosin binding protein-C phosphorylation 89. Niizeki T, Takeishi Y, Arimoto T, Takahashi T, Okuyama H, Takabatake in human heart muscle. J Mol Cell Cardiol. (2010) 9:1003–11. N, et al. Combination of heart-type fatty acid binding protein and brain doi: 10.1016/j.yjmcc.2010.09.007 natriuretic peptide can reliably risk stratify patients hospitalized for chronic 73. Hamdani N, Borbély A, Veenstra SP, Kooij V, Vrydag W, Zaremba R, et al. heart failure. Circ J. (2005) 69:922–7. doi: 10.1253/circj.69.922 More severe cellular phenotype in human idiopathic dilated cardiomyopathy 90. Hoffmann U, Espeter F, Weiß C, Ahmad-Nejad P, Lang S, Brueckmann M, compared to ischemic heart disease. J Muscle Res Cell Motil. (2010) 31:289– et al. Ischemic biomarker heart-type fatty acid binding protein (hFABP) 301. doi: 10.1007/s10974-010-9231-8 in acute heart failure - diagnostic and prognostic insights compared 74. Schulte C, Barwari T, Joshi A, Theofilatos K, Zampetaki A, Barallobre- to NT-proBNP and troponin I. BMC Cardiovasc Disord. (2015) 15:50. Barreiro J, et al. Comparative analysis of circulating noncoding RNAs versus doi: 10.1186/s12872-015-0026-0 protein biomarkers in the detection of myocardial injury. Circ Res. (2019) 91. Kutsuzawa D, Arimoto T, Watanabe T, Shishido T, Miyamoto T, 125:328–40. doi: 10.1161/CIRCRESAHA.119.314937 Miyashita T, et al. Ongoing myocardial damage in patients with heart 75. Jacquet S, Yin X, Sicard P, Clark J, Kanaganayagam GS, Mayr M, et al. failure and preserved ejection fraction. J Cardiol. (2012) 60:454–61. Identification of cardiac myosin-binding protein C as a candidate biomarker doi: 10.1016/j.jjcc.2012.06.006 of myocardial infarction by proteomics analysis. Mol Cell Proteomics. (2009) 92. Dumic J, Dabelic S, Flögel M. Galectin-3: an open-ended story. Biochim 8:2687–99. doi: 10.1074/mcp.M900176-MCP200 Biophys Acta. (2006) 1760:616–35. doi: 10.1016/j.bbagen.2005.12.020 76. Kaier TE, Twerenbold R, Puelacher C, Marjot J, Imambaccus 93. Kim H, Lee J, Hyun JW, Park JW, Joo HG, Shin T. Expression and N, Boeddinghaus J, et al. Direct comparison of cardiac myosin- immunohistochemical localization of galectin-3 in various mouse tissues. binding protein C with cardiac troponins for the early diagnosis Cell Biol Int. (2007) 31:655–62. doi: 10.1016/j.cellbi.2006.11.036 Frontiers in Cardiovascular Medicine | www.frontiersin.org 16 November 2020 | Volume 7 | Article 601364 Shrivastava et al. Biomarkers for Heart Failure Prognosis 94. Yang RY, Hsu DK, Liu FT. Expression of galectin-3 modulates T-cell 111. Ferrari N, Pfeffer U, Dell’eva R, Ambrosini C, Noonan DM, Albini A. growth and apoptosis. Proc Natl Acad Sci USA. (1996) 93:6737–42. The transforming growth factor-beta family members bone morphogenetic doi: 10.1073/pnas.93.13.6737 protein-2 and macrophage inhibitory cytokine-1 as mediators of the 95. Hsu DK, Hammes SR, Kuwabara I, Greene WC, Liu FT. Human antiangiogenic activity of N-(4-hydroxyphenyl)retinamide. Clin Cancer Res. T lymphotropic virus-I infection of human T lymphocytes induces (2005) 11:4610–9. doi: 10.1158/1078-0432.CCR-04-2210 expression of the beta-galactoside-binding lectin, galectin-3. Am J Pathol. 112. Secchiero P, Corallini F, Gonelli A, Dell’eva R, Vitale M, Capitani S, et al. (1996) 148:1661–70. Antiangiogenic activity of the MDM2 antagonist nutlin-3. Circ Res. (2007) 96. Sundblad V, Croci DO, Rabinovich GA. Regulated expression of 100:61–9. doi: 10.1161/01.RES.0000253975.76198.ff galectin-3, a multifunctional glycan-binding protein, in haematopoietic 113. Nickel N, Jonigk D, Kempf T, Bockmeyer CL, Maegel L, Rische J, et al. GDF- and non-haematopoietic tissues. Histol Histopathol. (2011) 26:247–65. 15 is abundantly expressed in plexiform lesions in patients with pulmonary doi: 10.14670/HH-26.247 arterial hypertension and affects proliferation and apoptosis of pulmonary 97. Kim K, Mayer EP, Nachtigal M. Galectin-3 expression in macrophages endothelial cells. Respir Res. (2011) 12:62. doi: 10.1186/1465-9921-12-62 is signaled by Ras/MAP kinase pathway and up-regulated by 114. Ding Q, Mracek T, Gonzalez-Muniesa P, Kos K, Wilding J, Trayhurn P, et al. modified lipoproteins. Biochim Biophys Acta. (2003) 1641:13–23. Identification of macrophage inhibitory cytokine-1 in adipose tissue and doi: 10.1016/S0167-4889(03)00045-4 its secretion as an adipokine by human adipocytes. Endocrinology. (2009) 98. Sharma UC, Pokharel S, Van Brakel TJ, Van Berlo JH, Cleutjens JP, 150:1688–96. doi: 10.1210/en.2008-0952 Schroen B, et al. Galectin-3 marks activated macrophages in failure-prone 115. Kempf T, Eden M, Strelau J, Naguib M, Willenbockel C, Tongers J, hypertrophied hearts and contributes to cardiac dysfunction. Circulation. et al. The transforming growth factor-beta superfamily member growth- (2004) 110:3121–8. doi: 10.1161/01.CIR.0000147181.65298.4D differentiation factor-15 protects the heart from ischemia/reperfusion injury. 99. Liu YH, D’ambrosio M, Liao TD, Peng H, Rhaleb NE, Sharma U, Circ Res. (2006) 98:351–60. doi: 10.1161/01.RES.0000202805.73038.48 et al. N-acetyl-seryl-aspartyl-lysyl-proline prevents cardiac remodeling 116. Clerk A, Kemp TJ, Zoumpoulidou G, Sugden PH. Cardiac myocyte gene and dysfunction induced by galectin-3, a mammalian adhesion/growth- expression profiling during H2O2-induced apoptosis. Physiol Genom. (2007) regulatory lectin. Am J Physiol Heart Circ Physiol. (2009) 296:H404–12. 29:118–27. doi: 10.1152/physiolgenomics.00168.2006 doi: 10.1152/ajpheart.00747.2008 117. Frank D, Kuhn C, Brors B, Hanselmann C, Lüdde M, Katus HA, et al. 100. Lin YH, Lin LY, Wu YW, Chien KL, Lee CM, Hsu RB, et al. The relationship Gene expression pattern in biomechanically stretched cardiomyocytes: between serum galectin-3 and serum markers of cardiac extracellular evidence for a stretch-specific gene program. Hypertension. (2008) 51:309– matrix turnover in heart failure patients. Clin Chim Acta. (2009) 409:96–9. 18. doi: 10.1161/HYPERTENSIONAHA.107.098046 doi: 10.1016/j.cca.2009.09.001 118. De Jager SC, Bermúdez B, Bot I, Koenen RR, Bot M, Kavelaars A, et al. 101. Gullestad L, Ueland T, Kjekshus J, Nymo SH, Hulthe J, Muntendam P, Growth differentiation factor 15 deficiency protects against atherosclerosis et al. The predictive value of galectin-3 for mortality and cardiovascular by attenuating CCR2-mediated macrophage chemotaxis. J Exp Med. (2011) events in the Controlled Rosuvastatin Multinational Trial in Heart Failure 208:217–25. doi: 10.1084/jem.20100370 (CORONA). Am Heart J. (2012) 164:878–83. doi: 10.1016/j.ahj.2012.08.021 119. Anand IS, Kempf T, Rector TS, Tapken H, Allhoff T, Jantzen F, et al. Serial 102. Felker GM, Fiuzat M, Shaw LK, Clare R, Whellan DJ, Bettari L, et al. measurement of growth-differentiation factor-15 in heart failure: relation to Galectin-3 in ambulatory patients with heart failure. Circulation. (2012) disease severity and prognosis in the valsartan heart failure trial. Circulation. 5:72–8. doi: 10.1161/CIRCHEARTFAILURE.111.963637 (2010) 122:1387–95. doi: 10.1161/CIRCULATIONAHA.109.928846 103. Lok DJA, Van Der Meer P, De La Porte PWB-A, Lipsic E, Van Wijngaarden J, 120. Kempf T, Von Haehling S, Peter T, Allhoff T, Cicoira M, Doehner W, Hillege HL, et al. Prognostic value of galectin-3, a novel marker of fibrosis, in et al. Prognostic utility of growth differentiation factor-15 in patients patients with chronic heart failure: data from the DEAL-HF study. Clin Res with chronic heart failure. J Am Coll Cardiol. (2007) 50:1054–60. Cardiol. (2010) 99:323–8. doi: 10.1007/s00392-010-0125-y doi: 10.1016/j.jacc.2007.04.091 104. Velde ARVD, Gullestad L, Ueland T, Aukrust P, Guo Y, Adourian 121. Schmitz J, Owyang A, Oldham E, Song Y, Murphy E, Mcclanahan TK, et al. A, et al. Prognostic value of changes in galectin-3 levels over IL-33, an interleukin-1-like cytokine that signals via the IL-1 receptor-related time in patients with heart failure. Circulation. (2013) 6:219–26. protein ST2 and induces T helper type 2-associated cytokines. Immunity. doi: 10.1161/CIRCHEARTFAILURE.112.000129 (2005) 23:479–90. doi: 10.1016/j.immuni.2005.09.015 105. Bootcov MR, Bauskin AR, Valenzuela SM, Moore AG, Bansal M, He XY, 122. Kakkar R, Hei H, Dobner S, Lee RT. Interleukin 33 as a mechanically et al. MIC-1, a novel macrophage inhibitory cytokine, is a divergent member responsive cytokine secreted by living cells. J Biol Chem. (2012) 287:6941–8. of the TGF-β superfamily. Proc Natl Acad Sci USA. (1997) 94:11514–9. doi: 10.1074/jbc.M111.298703 doi: 10.1073/pnas.94.21.11514 123. Pascual-Figal DA, Januzzi JL. The biology of ST2: the 106. Hromas R, Hufford M, Sutton J, Xu D, Li Y, Lu L. PLAB, a novel placental international ST2 consensus panel. Am J Cardiol. (2015) 115:3B−7. bone morphogenetic protein. Biochim Biophys Acta. (1997) 1354:40–4. doi: 10.1016/j.amjcard.2015.01.034 doi: 10.1016/S0167-4781(97)00122-X 124. Tang WHW, Wu Y, Grodin JL, Hsu AP, Hernandez AF, Butler J, et al. 107. Lawton LN, Bonaldo MDF, Jelenc PC, Qiu L, Baumes SA, Marcelino RA, Prognostic value of baseline and changes in circulating soluble ST2 levels et al. Identification of a novel member of the TGF-beta superfamily and the effects of nesiritide in acute decompensated heart failure. JACC Heart highly expressed in human placenta. Gene. (1997) 203:17–26. Fail. (2016) 4:68–77. doi: 10.1016/j.jchf.2015.07.015 doi: 10.1016/S0378-1119(97)00485-X 125. Skali H, Gerwien R, Meyer TE, Snider JV, Solomon SD, Stolen CM. Soluble 108. Bauskin AR, Zhang HP, Fairlie WD, He XY, Russell PK, Moore AG, et al. ST2 and risk of arrhythmias, heart failure, or death in patients with mildly The propeptide of macrophage inhibitory cytokine (MIC-1), a TGF-beta symptomatic heart failure: results from MADIT-CRT. J Cardiovasc Transl superfamily member, acts as a quality control determinant for correctly Res. (2016) 9:421–8. doi: 10.1007/s12265-016-9713-1 folded MIC-1. EMBO J. (2000) 19:2212–20. doi: 10.1093/emboj/19.10.2212 126. Anand IS, Rector TS, Kuskowski M, Snider J, Cohn JN. Prognostic value 109. Schlittenhardt D, Schober A, Strelau J, Bonaterra GA, Schmiedt W, Unsicker of soluble ST2 in the valsartan heart failure trial. Circ Heart Fail. (2014) K, et al. Involvement of growth differentiation factor-15/macrophage 7:418–26. doi: 10.1161/CIRCHEARTFAILURE.113.001036 inhibitory cytokine-1 (GDF-15/MIC-1) in oxLDL-induced apoptosis of 127. Liu Z, Ma C, Gu J, Yu M. Potential biomarkers of acute myocardial infarction human macrophages in vitro and in arteriosclerotic lesions. Cell Tissue Res. based on weighted gene co-expression network analysis. Biomed Eng Online. (2004) 318:325–33. doi: 10.1007/s00441-004-0986-3 (2019) 18:9. doi: 10.1186/s12938-019-0625-6 110. Bermúdez B, López S, Pacheco YM, Villar J, Muriana FJ, Hoheisel JD, et al. 128. Shah S, Henry A, Roselli C, Lin H, Sveinbjörnsson G, Fatemifar G, et al. Influence of postprandial triglyceride-rich lipoproteins on lipid-mediated Genome-wide association and Mendelian randomisation analysis provide gene expression in smooth muscle cells of the human coronary artery. insights into the pathogenesis of heart failure. Nat Commun. (2020) 11:163. Cardiovasc Res. (2008) 79:294–303. doi: 10.1093/cvr/cvn082 doi: 10.1038/s41467-019-13690-5 Frontiers in Cardiovascular Medicine | www.frontiersin.org 17 November 2020 | Volume 7 | Article 601364 Shrivastava et al. Biomarkers for Heart Failure Prognosis 129. Myers RH, Kiely DK, Cupples LA, Kannel WB. Parental history is an polymorphisms in chronic heart failure. Acta Biomed. (2019) 90:221–7. independent risk factor for coronary artery disease: the Framingham study. doi: 10.23750/abm.v90i2.6681 Am Heart J. (1990) 120:963–9. doi: 10.1016/0002-8703(90)90216-K 149. Bartekova M, Radosinska J, Jelemensky M, Dhalla NS. Role of cytokines and 130. Samani NJ, Erdmann J, Hall AS, Hengstenberg C, Mangino M, Mayer B, et al. inflammation in heart function during health and disease. Heart Fail Rev. Genomewide association analysis of coronary artery disease. N Engl J Med. (2018) 23:733–58. doi: 10.1007/s10741-018-9716-x (2007) 357:443–53. doi: 10.1056/NEJMoa072366 150. Schlossarek S, Mearini G, Carrier L. Cardiac myosin-binding protein C in 131. Mcpherson R, Pertsemlidis A, Kavaslar N, Stewart A, Roberts R, hypertrophic cardiomyopathy: mechanisms and therapeutic opportunities. Cox DR, et al. A common allele on chromosome 9 associated with J Mol Cell Cardiol. (2011) 50:613–20. doi: 10.1016/j.yjmcc.2011. coronary heart disease. Science. (2007) 316:1488–91. doi: 10.1126/science.11 01.014 42447 151. Behrens-Gawlik V, Mearini G, Gedicke-Hornung C, Richard P, 132. Helgadottir A, Thorleifsson G, Manolescu A, Gretarsdottir S, Blondal Carrier L. MYBPC3 in hypertrophic cardiomyopathy: from mutation T, Jonasdottir A, et al. A common variant on chromosome 9p21 identification to RNA-based correction. Pflugers Arch. (2014) 466:215–23. affects the risk of myocardial infarction. Science. (2007) 316:1491–3. doi: 10.1007/s00424-013-1409-7 doi: 10.1126/science.1142842 152. Niu X, Zhang J, Zhang L, Hou Y, Pu S, Chu A, et al. Weighted gene co- 133. Consortium WTCC. Genome-wide association study of 14,000 cases of seven expression network analysis identifies critical genes in the development of common diseases and 3,000 shared controls. Nature. (2007) 447:661–78. heart failure after acute myocardial infarction. Front Genet. (2019) 10:1214. doi: 10.1038/nature05911 doi: 10.3389/fgene.2019.01214 134. Holdt LM, Stahringer A, Sass K, Pichler G, Kulak NA, Wilfert W, 153. Kreisel D, Sugimoto S, Tietjens J, Zhu J, Yamamoto S, Krupnick AS, et al. Bcl3 et al. Circular non-coding RNA ANRIL modulates ribosomal RNA prevents acute inflammatory lung injury in mice by restraining emergency maturation and atherosclerosis in humans. Nat Commun. (2016) 7:12429. granulopoiesis. J Clin Invest. (2011) 121:265–76. doi: 10.1172/JCI42596 doi: 10.1038/ncomms12429 154. Schilling J, Kelly DP. The PGC-1 cascade as a therapeutic 135. Erdmann J, Kessler T, Munoz Venegas L, Schunkert H. A decade of genome- target for heart failure. J Mol Cell Cardiol. (2011) 51:578–83. wide association studies for coronary artery disease: the challenges ahead. doi: 10.1016/j.yjmcc.2010.09.021 Cardiovasc Res. (2018) 114:1241–57. doi: 10.1093/cvr/cvy084 155. Weinberg EO, Shimpo M, De Keulenaer GW, Macgillivray C, Tominaga 136. Poetsch MS, Strano A, Guan K. Role of leptin in cardiovascular diseases. S, Solomon SD, et al. Expression and regulation of ST2, an interleukin-1 Front Endocrinol. (2020) 11:354. doi: 10.3389/fendo.2020.00354 receptor family member, in cardiomyocytes and myocardial infarction. 137. Kaur J, Mattu HS, Chatha K, Randeva HS. Chemerin in Circulation. (2002) 106:2961–6. doi: 10.1161/01.CIR.0000038705. human cardiovascular disease. Vascul Pharmacol. (2018) 110:1–6. 69871.D9 doi: 10.1016/j.vph.2018.06.018 156. Khera AV, Chaffin M, Aragam KG, Haas ME, Roselli C, Choi SH, et al. 138. Silva CP, Kamens HM. Cigarette smoke-induced alterations in blood: a Genome-wide polygenic scores for common diseases identify individuals review of research on DNA methylation and gene expression. Exp Clin with risk equivalent to monogenic mutations. Nat Genet. (2018) 50:1219–24. Psychopharmacol. (2020). doi: 10.1037/pha0000382 doi: 10.1038/s41588-018-0183-z 139. Haase T, Müller C, Krause J, Röthemeier C, Stenzig J, Kunze S, et al. Novel 157. Erdmann J, Stark K, Esslinger UB, Rumpf PM, Koesling D, De Wit C, et al. DNA methylation sites influence GPR15 expression in relation to smoking. Dysfunctional nitric oxide signalling increases risk of myocardial infarction. Biomolecules. (2018) 8:74. doi: 10.3390/biom8030074 Nature. (2013) 504:432–6. doi: 10.1038/nature12722 140. Schunkert H, Von Scheidt M, Kessler T, Stiller B, Zeng L, Vilne B. Genetics of 158. Khera AV, Emdin CA, Kathiresan S. Genetic risk, lifestyle, and coronary coronary artery disease in the light of genome-wide association studies. Clin artery disease. N Engl J Med. (2017) 376:1194–5. doi: 10.1056/NEJMc1700362 Res Cardiol. (2018) 107:2–9. doi: 10.1007/s00392-018-1324-1 159. Jia X, Al Rifai M, Liu J, Agarwala A, Gulati M, Virani SS. Highlights of studies 141. Van Der Ende MY, Said MA, Van Veldhuisen DJ, Verweij N, Van in cardiovascular disease prevention presented at the 2020 american college Der Harst P. Genome-wide studies of heart failure and endophenotypes: of cardiology annual scientific session. Curr Atheroscler Rep. (2020) 22:32. lessons learned and future directions. Cardiovasc Res. (2018) 114:1209–25. doi: 10.1007/s11883-020-00856-6 doi: 10.1093/cvr/cvy083 160. Siemelink MA, Zeller T. Biomarkers of coronary artery disease: 142. Hellström M, Ericsson M, Johansson B, Faraz M, Anderson F, Henriksson the promise of the transcriptome. Curr Cardiol Rep. (2014) 16:513. R, et al. Cardiac hypertrophy and decreased high-density lipoprotein doi: 10.1007/s11886-014-0513-4 cholesterol in Lrig3-deficient mice. Am J Physiol Regul Integr Comp Physiol. 161. Pua CJ, Bhalshankar J, Miao K, Walsh R, John S, Lim SQ, et al. Development (2016) 310:R1045–52. doi: 10.1152/ajpregu.00309.2015 of a comprehensive sequencing assay for inherited cardiac condition genes. J 143. Cappola TP, Li M, He J, Ky B, Gilmore J, Qu L, et al. Common variants in Cardiovasc Transl Res. (2016) 9:3–11. doi: 10.1007/s12265-016-9673-5 HSPB7 and FRMD4B associated with advanced heart failure. Circ Cardiovasc 162. Rao AS, Knowles JW. Polygenic risk scores in coronary artery disease. Curr Genet. (2010) 3:147–54. doi: 10.1161/CIRCGENETICS.109.898395 Opin Cardiol. (2019) 34:435–40. doi: 10.1097/HCO.0000000000000629 144. Liu L, Sun K, Zhang X, Tang Y, Xu D. Advances in the role and 163. Curtis D. Clinical relevance of genome-wide polygenic score may be less than mechanism of BAG3 in dilated cardiomyopathy. Heart Fail Rev. (2019). claimed. Ann Hum Genet. (2019) 83:274–7. doi: 10.1111/ahg.12302 doi: 10.1007/s10741-019-09899-7. [Epub ahead of print]. 164. Soler-Botija C, Gálvez-Montón C, Bayés-Genís A. Epigenetic 145. Mazzarotto F, Tayal U, Buchan RJ, Midwinter W, Wilk A, biomarkers in cardiovascular diseases. Front Genet. (2019) 10:950. Whiffin N, et al. Reevaluating the genetic contribution of doi: 10.3389/fgene.2019.00950 monogenic dilated cardiomyopathy. Circulation. (2020) 141:387–98. 165. Sweet ME, Cocciolo A, Slavov D, Jones KL, Sweet JR, Graw SL, et al. doi: 10.1161/CIRCULATIONAHA.119.037661 Transcriptome analysis of human heart failure reveals dysregulated 146. Choquet H, Thai KK, Jiang C, Ranatunga DK, Hoffmann TJ, Go AS, et al. cell adhesion in dilated cardiomyopathy and activated immune Meta-analysis of 26,638 individuals identifies two genetic loci associated with pathways in ischemic heart failure. BMC Genomics. (2018) 19:812. left ventricular ejection fraction. Circ Genom Precis Med. (2020) 13:e002804. doi: 10.1186/s12864-018-5213-9 doi: 10.1161/CIRCGEN.119.002804 166. Schulte C, Zeller T. Biomarkers in primary prevention: meaningful 147. Yu B, Barbalic M, Brautbar A, Nambi V, Hoogeveen RC, Tang W, diagnosis based on biomarker scores? Herz. (2020) 45:10–6. et al. Association of genome-wide variation with highly sensitive cardiac doi: 10.1007/s00059-019-04874-2 troponin-T levels in European Americans and blacks: a meta-analysis 167. Osman J, Tan SC, Lee PY, Low TY, Jamal R. Sudden Cardiac Death (SCD) from atherosclerosis risk in communities and cardiovascular health studies. – risk stratification and prediction with molecular biomarkers. J Biomed Sci. Circ Cardiovasc Genet. (2013) 6:82–8. doi: 10.1161/CIRCGENETICS.112.9 (2019) 26:39. doi: 10.1186/s12929-019-0535-8 63058 168. Lee RC, Feinbaum RL, Ambros V. The C. elegans heterochronic gene lin-4 148. Mahmoudi MJ, Hedayat M, Taghvaei M, Harsini S, Nematipour E, Rezaei encodes small RNAs with antisense complementarity to lin-14. Cell. (1993) N, et al. Interleukin-10 and transforming growth factor beta1 gene 75:843–54. doi: 10.1016/0092-8674(93)90529-Y Frontiers in Cardiovascular Medicine | www.frontiersin.org 18 November 2020 | Volume 7 | Article 601364 Shrivastava et al. Biomarkers for Heart Failure Prognosis 169. Barwari T, Joshi A, Mayr M. MicroRNAs in cardiovascular disease. J Am Coll 190. Lai KB, Sanderson JE, Izzat MB, Yu CM. Micro-RNA and mRNA myocardial Cardiol. (2016) 68:2577–84. doi: 10.1016/j.jacc.2016.09.945 tissue expression in biopsy specimen from patients with heart failure. Int J 170. Bauersachs J, Thum T. Biogenesis and regulation of Cardiol. (2015) 199:79–83. doi: 10.1016/j.ijcard.2015.07.043 cardiovascular microRNAs. Circ Res. (2011) 109:334–47. 191. Rigaud VO, Ferreira LR, Ayub-Ferreira SM, Ávila MS, Brandão SM, Cruz doi: 10.1161/CIRCRESAHA.110.228676 FD, et al. Circulating miR-1 as a potential biomarker of doxorubicin-induced 171. Schulte C, Zeller T. microRNA-based diagnostics and therapy in cardiotoxicity in breast cancer patients. Oncotarget. (2017) 8:6994–7002. cardiovascular disease-Summing up the facts. Cardiovasc Diagn Ther. doi: 10.18632/oncotarget.14355 (2015) 5:17–36. doi: 10.3978/j.issn.2223-3652.2014.12.03 192. Zhang R, Niu H, Ban T, Xu L, Li Y, Wang N, et al. Elevated plasma 172. Schulte C, Westermann D, Blankenberg S, Zeller T. Diagnostic and microRNA-1 predicts heart failure after acute myocardial infarction. Int J prognostic value of circulating microRNAs in heart failure with preserved Cardiol. (2013) 166:259–60. doi: 10.1016/j.ijcard.2012.09.108 and reduced ejection fraction. World J Cardiol. (2015) 7:843–60. 193. Seronde MF, Vausort M, Gayat E, Goretti E, Ng LL, Squire IB, doi: 10.4330/wjc.v7.i12.843 et al. Circulating microRNAs and outcome in patients with acute heart 173. Rybak-Wolf A, Stottmeister C, GlaŽar P, Jens M, Pino N, Giusti S, failure. PLoS ONE. (2015) 10:e0142237. doi: 10.1371/journal.pone.01 et al. Circular RNAs in the mammalian brain are highly abundant, 42237 conserved, and dynamically expressed. Molecular Cell. (2015) 58:870–85. 194. Schulte C, Molz S, Appelbaum S, Karakas M, Ojeda F, Lau DM, et al. miRNA- doi: 10.1016/j.molcel.2015.03.027 197 and miRNA-223 predict cardiovascular death in a cohort of patients 174. Kaudewitz D, Zampetaki A, Mayr M. MicroRNA biomarkers with symptomatic coronary artery disease. PLoS ONE. (2015) 10:e0145930. for coronary artery disease? Curr Atheroscler Rep. (2015) 17:70. doi: 10.1371/journal.pone.0145930 doi: 10.1007/s11883-015-0548-z 195. Zampetaki A, Willeit P, Tilling L, Drozdov I, Prokopi M, Renard 175. Mendell JT, Olson EN. MicroRNAs in stress signaling and human disease. JM, et al. Prospective study on circulating MicroRNAs and risk Cell. (2012) 148:1172–87. doi: 10.1016/j.cell.2012.02.005 of myocardial infarction. J Am Coll Cardiol. (2012) 60:290–9. 176. Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova- doi: 10.1016/j.jacc.2012.03.056 Agadjanyan EL, et al. Circulating microRNAs as stable blood-based 196. Cruz MS, Da Silva AMG, De Souza KSC, Luchessi AD, Silbiger VN. miRNAs markers for cancer detection. Proc Natl Acad Sci USA. (2008) 105:10513–8. emerge as circulating biomarkers of post-myocardial infarction heart failure. doi: 10.1073/pnas.0804549105 Heart Fail Rev. (2020) 25:321–9. doi: 10.1007/s10741-019-09821-1 177. Arroyo JD, Chevillet JR, Kroh EM, Ruf IK, Pritchard CC, Gibson DF, 197. Li DY, Busch A, Jin H, Chernogubova E, Pelisek J, et al. Argonaute2 complexes carry a population of circulating microRNAs Karlsson J, et al. H19 induces abdominal aortic aneurysm independent of vesicles in human plasma. Proc Natl Acad Sci USA. (2011) development and progression. Circulation. (2018) 138:1551–68. 108:5003–8. doi: 10.1073/pnas.1019055108 doi: 10.1161/CIRCULATIONAHA.117.032184 178. Vickers KC, Palmisano BT, Shoucri BM, Shamburek RD, Remaley 198. Viereck J, Thum T. Circulating noncoding RNAs as biomarkers AT. MicroRNAs are transported in plasma and delivered to recipient of cardiovascular disease and injury. Circ Res. (2017) 120:381–99. cells by high-density lipoproteins. Nat Cell Biol. (2011) 13:423–33. doi: 10.1161/CIRCRESAHA.116.308434 doi: 10.1038/ncb2210 199. Sallam T, Sandhu J, Tontonoz P. Long noncoding RNA discovery in 179. Turchinovich A, Weiz L, Langheinz A, Burwinkel B. Characterization of cardiovascular disease: decoding form to function. Circ Res. (2018) 122:155– extracellular circulating microRNA. Nucleic Acids Res. (2011) 39:7223–33. 66. doi: 10.1161/CIRCRESAHA.117.311802 doi: 10.1093/nar/gkr254 200. Derrien T, Johnson R, Bussotti G, Tanzer A, Djebali S, Tilgner H, et al. The 180. Boon RA, Vickers KC. Intercellular transport of microRNAs. Arterioscler GENCODE v7 catalog of human long noncoding RNAs: analysis of their Thromb Vasc Biol. (2013) 33:186–92. doi: 10.1161/ATVBAHA.112.300139 gene structure, evolution, and expression. Genome Res. (2012) 22:1775–89. 181. Sunderland N, Skroblin P, Barwari T, Huntley RP, Lu R, Joshi A, et al. doi: 10.1101/gr.132159.111 MicroRNA biomarkers and platelet reactivity: the clot thickens. Circ Res. 201. Kumarswamy R, Bauters C, Volkmann I, Maury F, Fetisch J, Holzmann (2017) 120:418–35. doi: 10.1161/CIRCRESAHA.116.309303 A, et al. Circulating long noncoding RNA, LIPCAR, predicts 182. Reid G, Kirschner MB, Van Zandwijk N. Circulating microRNAs: association survival in patients with heart failure. Circ Res. (2014) 114:1569–75. with disease and potential use as biomarkers. Crit Rev Oncol Hematol. (2011) doi: 10.1161/CIRCRESAHA.114.303915 80:193–208. doi: 10.1016/j.critrevonc.2010.11.004 202. Wilusz JE, Sunwoo H, Spector DL. Long noncoding RNAs: functional 183. Simons M, Raposo G. Exosomes–vesicular carriers for intercellular surprises from the RNA world. Genes Dev. (2009) 23:1494–504. communication. Curr Opin Cell Biol. (2009) 21:575–81. doi: 10.1101/gad.1800909 doi: 10.1016/j.ceb.2009.03.007 203. Gangwar RS, Rajagopalan S, Natarajan R, Deiuliis JA. Noncoding RNAs 184. Creemers EE, Tijsen AJ, Pinto YM. Circulating microRNAs: novel in cardiovascular disease: pathological relevance and emerging role biomarkers and extracellular communicators in cardiovascular disease? Circ as biomarkers and therapeutics. Am J Hypertens. (2018) 31:150–65. Res. (2012) 110:483–95. doi: 10.1161/CIRCRESAHA.111.247452 doi: 10.1093/ajh/hpx197 185. Kwon C, Han Z, Olson EN, Srivastava D. MicroRNA1 influences cardiac 204. Uchida S, Dimmeler S. Long noncoding RNAs in cardiovascular differentiation in drosophila and regulates Notch signaling. Proc Natl Acad diseases. Circ Res. (2015) 116:737–50. doi: 10.1161/CIRCRESAHA.116.3 Sci USA. (2005) 102:18986–91. doi: 10.1073/pnas.0509535102 02521 186. Zhao Y, Samal E, Srivastava D. Serum response factor regulates a muscle- 205. Tan P, Guo YH, Zhan JK, Long LM, Xu ML, Ye L, et al. LncRNA-ANRIL specific microRNA that targets Hand2 during cardiogenesis. Nature. (2005) inhibits cell senescence of vascular smooth muscle cells by regulating miR- 436:214–20. doi: 10.1038/nature03817 181a/Sirt1. Biochem Cell Biol. (2019) 97:571–80. doi: 10.1139/bcb-2018-0126 187. Chistiakov DA, Orekhov AN, Bobryshev YV. Cardiac-specific miRNA 206. Natarelli L, Geißler C, Csaba G, Wei Y, Zhu M, Di Francesco in cardiogenesis, heart function, and cardiac pathology (with focus A, et al. miR-103 promotes endothelial maladaptation by targeting on myocardial infarction). J Mol Cell Cardiol. (2016) 94:107–21. lncWDR59. Nat Commun. (2018) 9:2645. doi: 10.1038/s41467-018-0 doi: 10.1016/j.yjmcc.2016.03.015 5065-z 188. Kumarswamy R, Lyon AR, Volkmann I, Mills AM, Bretthauer J, Pahuja A, 207. Zhang G, Dou L, Chen Y. Association of long-chain non-coding et al. SERCA2a gene therapy restores microRNA-1 expression in heart failure RNA MHRT gene single nucleotide polymorphism with risk and via an Akt/FoxO3A-dependent pathway. Eur Heart J. (2012) 33:1067–75. prognosis of chronic heart failure. Medicine. (2020) 99:e19703. doi: 10.1093/eurheartj/ehs043 doi: 10.1097/MD.0000000000019703 189. Ikeda S, He A, Kong SW, Lu J, Bejar R, Bodyak N, et al. MicroRNA- 208. Viereck J, Bührke A, Foinquinos A, Chatterjee S, Kleeberger JA, Xiao 1 negatively regulates expression of the hypertrophy-associated K, et al. (2020). Targeting muscle-enriched long non-coding RNA H19 calmodulin and Mef2a genes. Mol Cell Biol. (2009) 29:2193–204. reverses pathological cardiac hypertrophy. Eur Heart J. 41:3462–74. doi: 10.1128/MCB.01222-08 doi: 10.1093/eurheartj/ehaa519 Frontiers in Cardiovascular Medicine | www.frontiersin.org 19 November 2020 | Volume 7 | Article 601364 Shrivastava et al. Biomarkers for Heart Failure Prognosis 209. Greco S, Zaccagnini G, Perfetti A, Fuschi P, Valaperta R, Voellenkle C, et al. 221. Ashwal-Fluss R, Meyer M, Pamudurti NR, Ivanov A, Bartok O, Hanan M, Long noncoding RNA dysregulation in ischemic heart failure. J Transl Med. et al. circRNA biogenesis competes with pre-mRNA splicing. Mol Cell. (2014) (2016) 14:183. doi: 10.1186/s12967-016-0926-5 56:55–66. doi: 10.1016/j.molcel.2014.08.019 210. Chandler B, Hayashi M, Hayashi MN, Spiegelman S. Circularity of the 222. Barrett SP, Salzman J. Circular RNAs: analysis, expression and potential replicating form of a single-stranded DNA virus. Science. (1964) 143:47–9. functions. Development. (2016) 143:1838–47. doi: 10.1242/dev.128074 doi: 10.1126/science.143.3601.47 223. Han B, Chao J, Yao H. Circular RNA and its mechanisms in disease: 211. Sanger HL, Klotz G, Riesner D, Gross HJ, Kleinschmidt AK. Viroids are from the bench to the clinic. Pharmacol Ther. (2018) 187:31–44. single-stranded covalently closed circular RNA molecules existing as highly doi: 10.1016/j.pharmthera.2018.01.010 base-paired rod-like structures. Proc Natl Acad Sci USA. (1976) 73:3852–6. 224. Tan WL, Lim BT, Anene-Nzelu CG, Ackers-Johnson M, Dashi A, See K, et al. doi: 10.1073/pnas.73.11.3852 A landscape of circular RNA expression in the human heart. Cardiovasc Res. 212. Nigro JM, Cho KR, Fearon ER, Kern SE, Ruppert JM, (2017) 113:298–309. doi: 10.1093/cvr/cvw250 Oliner JD, et al. Scrambled exons. Cell. (1991) 64:607–13. 225. Wang K, Gan TY, Li N, Liu CY, Zhou LY, Gao JN, et al. Circular RNA doi: 10.1016/0092-8674(91)90244-S mediates cardiomyocyte death via miRNA-dependent upregulation 213. Cocquerelle C, Mascrez B, Hétuin D, Bailleul B. Mis-splicing yields circular of MTP18 expression. Cell Death Differ. (2017) 24:1111–20. RNA molecules. FASEB J. (1993) 7:155–60. doi: 10.1096/fasebj.7.1.7678559 doi: 10.1038/cdd.2017.61 214. Jeck WR, Sharpless NE. Detecting and characterizing circular RNAs. Nat 226. Geng HH, Li R, Su YM, Xiao J, Pan M, Cai XX, et al. The Circular Biotechnol. (2014) 32:453–61. doi: 10.1038/nbt.2890 RNA Cdr1as promotes myocardial infarction by mediating the regulation 215. Memczak S, Jens M, Elefsinioti A, Torti F, Krueger J, Rybak A, et al. Circular of mir-7a on its target genes expression. PLoS ONE. (2016) 11:e0151753. RNAs are a large class of animal RNAs with regulatory potency. Nature. doi: 10.1371/journal.pone.0151753 (2013) 495:333–8. doi: 10.1038/nature11928 227. Vausort M, Salgado-Somoza A, Zhang L, Leszek P, Scholz M, Teren 216. Zhang Y, Zhang X-O, Chen T, Xiang J-F, Yin Q-F, Xing Y-H, et al. A, et al. Myocardial infarction-associated circular RNA predicting Circular intronic long noncoding RNAs. Mol Cell. (2013) 51:792–806. left ventricular dysfunction. J Am Coll Cardiol. (2016) 68:1247–8. doi: 10.1016/j.molcel.2013.08.017 doi: 10.1016/j.jacc.2016.06.040 217. Suzuki H, Zuo Y, Wang J, Zhang MQ, Malhotra A, Mayeda A. 228. Salgado-Somoza A, Zhang L, Vausort M, Devaux Y. The circular RNA Characterization of RNase R-digested cellular RNA source that consists of MICRA for risk stratification after myocardial infarction. Int J Cardiol Heart lariat and circular RNAs from pre-mRNA splicing. Nucleic Acids Res. (2006) Vasc. (2017) 17:33–6. doi: 10.1016/j.ijcha.2017.11.001 34:e63–e63. doi: 10.1093/nar/gkl151 218. Khan MA, Reckman YJ, Aufiero S, van den Hoogenhof MM, van der Made Conflict of Interest: The authors declare that the research was conducted in the I, Beqqali A, et al. (2016). RBM20 regulates circular RNA production from absence of any commercial or financial relationships that could be construed as a the titin gene. Circ Res. 119, 996–1003. doi: 10.1161/CIRCRESAHA.116. potential conflict of interest. 309568 219. Hansen TB, Jensen TI, Clausen BH, Bramsen JB, Finsen B, Damgaard CK, Copyright © 2020 Shrivastava, Haase, Zeller and Schulte. This is an open-access et al. Natural RNA circles function as efficient microRNA sponges. Nature. article distributed under the terms of the Creative Commons Attribution License (CC (2013) 495:384–8. doi: 10.1038/nature11993 BY). The use, distribution or reproduction in other forums is permitted, provided 220. Legnini I, Di Timoteo G, Rossi F, Morlando M, Briganti F, Sthandier O, the original author(s) and the copyright owner(s) are credited and that the original et al. Circ-ZNF609 Is a circular RNA that can be translated and functions publication in this journal is cited, in accordance with accepted academic practice. in myogenesis. Mol Cell. (2017) 66:22–37.e9. doi: 10.1016/j.molcel.2017. No use, distribution or reproduction is permitted which does not comply with these 02.017 terms. Frontiers in Cardiovascular Medicine | www.frontiersin.org 20 November 2020 | Volume 7 | Article 601364