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Circulating Noncoding RNAs as Biomarkers of Cardiovascular Disease and Injury

Originally publishedhttps://doi.org/10.1161/CIRCRESAHA.116.308434Circulation Research. 2017;120:381–399

    Abstract

    The discovery of thousands of noncoding RNAs (ncRNAs) has expanded our view on mammalian genomes and transcriptomes, as well as their organization and regulation. Accumulating evidence on aberrantly regulated ncRNAs, including short microRNAs, long ncRNAs and circular RNAs, across various heart diseases indicates that ncRNAs are critical contributors to cardiovascular pathophysiology. In addition, ncRNAs are released into the circulation where they are present in concentration levels that differ between healthy subjects and diseased patients. Although little is known about the origin and function of such circulating ncRNAs, these molecules are increasingly recognized as noninvasive and readily accessible biomarker for risk stratification, diagnosis and prognosis of cardiac injury, and multiple forms of cardiovascular disease. In this review, we summarize recent findings on biological characteristics of circulating ncRNAs and highlight their value as potential biomarker in selected pathologies of cardiovascular disease.

    The pervasiveness of the bloodstream and its perfusion through all organs and tissues enables various biomolecules, which are generated and released locally, to be distributed throughout the circulation. Altered concentrations of various molecules have been linked to various disease states, including that of cardiovascular diseases. Such biomarkers provide useful information to (1) identify and categorize patients toward an individual risk profile, (2) to diagnose and monitor disease conditions, and (3) to effectively draw prognoses of patients and to adapt treatments.1 Because cardiovascular diseases, including ischemic cardiac injury, are the leading cause of death worldwide,2 an early diagnosis potentially enables earlier treatment and reduces recurrent events, as well as morbidity and mortality. Several proteinous biomarkers have been identified for diagnostic and prognostic purposes that show more or less specific expression profiles indicating various degrees of cardiac injury and cardiovascular disease. Exemplarily cardiac injury caused by acute myocardial infarction (AMI) is associated with a progressive loss of cardiomyocytes and leads to a time-dependent release of cardiac troponins T/I (cTnT/I) and creatine kinase (CK), as well as its myocardial band isoenzyme (CK-MB).1 Currently, cardiac troponins are the most widely used biomarkers for AMI because of their sensitivity and specificity for cardiac necrosis.1 Cardiovascular-derived brain natriuretic peptide (BNP) and the biologically inactive N-terminal portion of its prohormone (NT-proBNP) are regarded as sensitive biomarkers for the diagnostic evaluation and risk stratification of heart failure (HF) patients.3 However, regardless of their clinical use, the diagnostic value of such established biomarkers may be limited by the heterogeneity of the heart-associated disease, patient’s age, genetic background, and lifestyle.4,5 As a result, the diagnostic assessment of cardiovascular disease and cardiac injury remains challenging. Therefore, novel, noninvasive and highly sensitive biomarkers that, when combined with classical indicators, can provide a detailed and more accurate fingerprint of the patient’s disease state are urgently needed. Recently, interest in noncoding RNAs (ncRNAs) has begun increasing not only because they represent the vast majority of the human transcriptome6,7 but also because they have been associated with cardiovascular diseases.8,9,10 Because ncRNAs are found to be stable and detectable in body fluids, they represent an enormous reservoir for biomarker discovery and are increasingly recognized for diagnostic and prognostic applications.

    Noncoding RNAs

    Aberrant gene expression as a major cause and important indicator is not limited to cardiovascular disease. Historically, such dysregulation has been mainly linked to protein-coding genes. However, the majority of the transcriptional landscape is composed of ncRNAs.6,7 Considering the ability of such RNA molecules to fold into complex structures and to interact with proteins, DNA and other RNAs, noncoding transcripts exhibit versatile functions as proteins enabling them to regulate various cellular processes. The RNA world is a largely unexplored territory and comprises several groups of RNAs classified by their genomic orientation, function, cellular localization, or other emerging criteria. A common ncRNA definition is based on an operational length threshold: (1) small transcripts that are shorter than 200 nucleotides, which includes microRNAs (miRNAs, miRs) among other endogenous RNA species; while (2) long noncoding RNAs (lncRNAs) range from 200 up to thousands of nucleotides.11,12,13 It becomes evident that on the one hand altered ncRNA expression or function impairs biological processes leading to the development of (cardiovascular) disease, but on the other hand harbors an enormous potential for diagnostic and prognostic applications.

    MicroRNAs

    MiRNAs are a group of endogenous short noncoding RNAs (18–25 nucleotides) that orchestrate mammalian gene expression by sequence-specific recognition of their target transcripts. The unique and conserved biogenesis of miRNAs mainly involves 3 steps (reviewed by several authors11,12): transcription, endonucleolytic processing in the nucleus, as well as in the cytoplasm, and incorporation into the RNA-induced silencing complex (Figure 1). MiRNAs arise from dedicated miRNA loci or are cotranscribed with their host genes. Therefore, their expression involves the transcriptional machinery of protein-coding genes involving epigenetic regulators, enhancers, and transcription factors.12 RNA polymerase II generates a long transcript that is capped, spliced, and polyadenylated as messenger RNAs.14 This primary miRNA contains either one single miRNA sequence or a cluster of several miRNAs that mature by 2 processing events: initially, the nuclear microprocessor complex, composed of the RNase III enzyme Drosha and its cofactor DGCR8 (DiGeorge syndrome critical region 8),12,15 cleaves the primary miRNA into a shorter hairpin-shaped precursor (pre-miRNA). Then, the cytoplasmatic RNase III Dicer in association with the transactivation-responsive RNA-binding protein12,16 generates the mature miRNA:miRNA* duplex from that the guide strand immediately assembles with Argonaute proteins to form the miRNA-induced silencing complex.12,16 The miRNA target is recognized by annealing of the miRNA seed region with a complementary sequence mainly within the 3′ untranslated region or the coding region of a messenger, thus provoking gene silencing either by blocking the translational machinery or by target degradation.11,12 With this regulatory mechanism, one miRNA can influence hundreds of distinct targets, enabling them to fine-tune various genetic programs and cellular processes.

    Figure 1.

    Figure 1. Biogenesis and function of microRNAs (miRNAs). MiRNAs are transcribed from longer precursors with protein or other noncoding gene sequences and further processed via 2 endonucleolytic processing steps. Mature miRNAs associate with Argonaute proteins (Ago2) forming the RNA-induced silencing complex (miRISC). Within this complex, miRNAs recognize their target sequence and block their expression by translational repression or degradation. MiRNAs can be released or actively secreted into the extracellular space and circulatory system stabilized in vesicles or proteinous binding partners. DGCR8, DiGeorge syndrome critical region 8; TRBP, transactivation-responsive RNA-binding protein.

    Long Noncoding RNAs

    LncRNAs constitute the vast majority of the nonprotein-coding transcriptome. A least 58 000 lncRNA genes have been classified to date,17 but only a handful of transcripts have been described with respect to structure, function, and impact on cellular processes or disease development. The term lncRNA defines transcripts longer than 200 nucleotides that lack coding signatures; an operational definition that poorly describes this RNA species because lncRNAs indeed can be occupied by the translational machinery18 and give rise to small peptides.19 In particular, their unique characteristic is their function as regulatory RNA molecules themselves.

    The lncRNA biogenesis resembles the generation of messenger RNAs, including active epigenetic chromatin marks, transcription and its regulation, capping, polyadenylation, and splicing.7,20 A more specific expression profile of lncRNAs with respect to cell type, tissue, developmental stage, or disease state discriminates from nonprotein-coding transcripts, as well as the conservation of lncRNAs that exhibit relatively poor sequence similarities.7,20,21 In contrast, transcripts with syntenic genomic localization relative to protein-coding genes are more common, indicating a well-conserved function. The proximity to protein-coding genes provides a more detailed definition of defines lncRNAs: (1) sense lncRNAs overlap to exons or introns of messenger; (2) antisense transcripts originate from the opposite strand of protein-coding genes; (3) circular lncRNAs are covalently closed loops derived from splicing events of protein-coding RNAs; (4) intergenic lncRNAs are encoded between coding genes and are transcribed independently; (5) enhancer RNAs are located to genomic loci that activate gene expression; and (6) bidirectional transcripts are transcribed from the same promoter as coding genes, but in the opposite direction.8,9

    The function of lncRNAs is still less understood. Considering a length of up to thousands of nucleotides, the lncRNA sequence enables diverse structures based on Watson-Crick base pairing and higher-order secondary structure motifs forming flexible and complex interaction domains for proteins, DNA, and other RNA molecules. This unique structure determines the lncRNA activity in the same manner as their localization to the nucleus or the cytoplasm (Figure 2; reviewed by Quinn and Chang,20Geisler and Coller,22 and Ounzain and Pedrazzini23). Nuclear lncRNAs are involved in epigenetic and transcriptional regulation of neighboring loci in cis or distal genes in trans. Such transcripts influence gene expression by recruiting the chromatin remodeling machinery, including polycomb repressive complex provoking chromatin condensation, and gene silencing. Other lncRNAs repress gene expression by sequestering RNA-binding proteins and transcription factors, whereas some transcripts enhance transcription by mediating chromosomal looping, promoter demethylation, and transcription factor activation. Furthermore, lncRNAs bind and regulate the transcriptional machinery, including RNA polymerase II activity, transcription initiation or termination, and RNA editing and splicing. Cytoplasmatic transcripts are involved in messenger RNA translation, stability, and decay. They can serve as competing endogenous RNAs acting as decoys or sponges for proteinous factors or for miRNAs hampering their targeting and repressive activity.20,22,23

    Figure 2.

    Figure 2. Molecular mechanism of long noncoding RNA (lncRNA) activities. LncRNAs regulate the expression of genes in the nucleus by interacting directly with DNA recruiting chromatin modifying complexes and various transcriptional regulators. Cytoplasmatic noncoding transcripts act as sponges for other transcripts like microRNAs (miRNAs) or for proteins, serve as templates for small peptide synthesis or regulate messenger RNA (mRNA) degradation and translation. These transcripts enter the bloodstream bound to proteinous carriers or incorporated into extracellular vesicles that leads to a stabilization of transcripts. Ago2, Argonaute protein 2.

    NcRNA in the Extracellular Space and Circulation

    NcRNAs fulfill miscellaneous functions and are involved in key regulatory processes within the cell. Moreover, their physicochemical properties to form ordered structures enable these molecules to compactly accumulate biological information that can be propagated through their function, in particular by their interaction with proteins and nucleic acids. Because ncRNA have been shown to cross the membrane barrier, it has become evident that the informative content can be transmitted and propagated between adjacent and distant cells. Indeed, such circulating ncRNAs have been described in different human body fluids, including blood, serum/plasma, urine, and breast milk.24,25 Although these environments contain high amounts of RNases, the existence of circulating ncRNAs indicates that this RNA species is relatively resistant to nucleolytic degradation.26,27 In addition, some plasma ncRNAs are stable against harsh conditions, such as boiling, extreme pH, storage at room temperature, or freezing and thawing cycles.28,29 This feature makes circulating ncRNAs suitable for clinical assessment and monitoring patient’s pathophysiological state.

    Transport mechanisms of circulating ncRNAs (Figures 1 and 2) mediate their stability and involve (1) encapsulation into membranous vesicles including exosomes, microvesicles, and apoptotic bodies, and (2) association to RNA-binding proteins, such as nucleophosmin, Ago2 (Argonaute protein 2), or lipoprotein complexes like high-density lipoprotein.24 Exosomes are small vesicles (30–100 nm) that originate from intracellular endosomes and are released on fusion of multivesicular bodies with the plasma membrane.24 Microvesicles are generally larger (100–1000 nm) and originate from outward budding and blebbing of the plasma membrane.24 The largest class of extracellular vesicles is apoptotic bodies (500–2000 nm) that are released from cells during apoptosis.24 All these extracellular vesicles serve as carriers for miRNAs24 and, for instance, seem to be the main source of plasma lncRNAs.30 The ncRNA content of extracellular vesicles can differ from that of the parental cell.31,32 This indicates specific sorting and packing mechanisms.24 Sorting is favored by specific sequence motifs, posttranscriptional modifications, or subcellular localization, whereas the export of ncRNAs, especially of miRNAs, seems to be regulated by the ceramide pathway.24 nSMase2 (neutral sphingomyelinase 2) not only regulates the biogenesis and secretion of exosomes but also the release of miRNAs.33 Extracellular vesicles and their ncRNA content can be taken up by recipient cells, enabling cell-to-cell communication. How specific recipient cells are targeted remains elusive, but this is potentially mediated via membrane receptors.24 To propagate their RNA-derived information, vesicle fuse with the membrane of target cells, enter the cell by endocytosis, or remain attached to the plasma membrane activating specific signaling pathways.24 Our31 and other studies34,35 suggest that such vesicle-mediated intercellular communication via ncRNAs could play an important role in cardiovascular disease.

    Besides vesicle-mediated transport, a substantial proportion of circulating ncRNAs is associated with ribonucleoproteins or larger complexes. Indeed, several RNA-binding proteins have been identified to be released in association with miRNAs. Among them are Ago2,36 a factor of the RNA-induced silencing complex and likewise of the miRNA-mediated gene silencing, as well as NPM1 (nucleophosmin 1)37 and nucleolin that have been implicated in the nuclear export from ribosomes. Both protein families have been shown to protect miRNAs from RNase-mediated degradation37 and presumably stabilize circulating lncRNAs in a similar manner. In addition, extracellular miRNAs associate to lipoproteins, such as low- and high-density lipoproteins that stabilize miRNAs.38 Although lncRNAs are part of the cargo of circulating proteins, it remains elusive where such ncRNA-protein complexes originate from and by which mechanisms they are released. A possible source might be passive leakage of dead or apoptotic cells. NcRNAs would remain stabilized in the extracellular space by their proteinous carriers.24 Likewise it is possible that cells involve channels or receptors on their membrane for specific and selective release of protein-bound ncRNAs.24

    The presence of miRNAs and lncRNAs in the extracellular space and circulation indicates that these molecules exhibit signaling function acting in an autocrine, paracrine, and possibly endocrine manner.39 Although several studies assessed their function in cell-to-cell communication in the surrounding environment, the consequence and biological effect of systemically released ncRNAs on distant sites remains a challenging question. Nevertheless, expression patterns of ncRNAs in body fluids are highly correlated with disease states and conditions and thus extracellular transcripts seem to have the potential for next-generation prognostic and diagnostic applications.40

    NcRNAs in Diagnosis and Prognosis of Cardiovascular Disease

    NcRNAs as Biomarker of Cardiac Injury

    Acute Myocardial Infarction

    AMI is a sudden cardiovascular event that provokes cardiac remodeling and can progress to chronic HF. To reduce the mortality, an appropriate therapeutic strategy is required that in turn depends on a rapid diagnosis with high sensitivity and specificity. AMI is characterized by cardiac injury and ischemic and hypoxic stress that result in the release of various proteins from damaged cardiac cells into the circulation, including cardiac troponins and CK.1 It is likely that the heart tissue damage causes an additional release of ncRNAs analogous to the release of proteins. Limitations of such single marker approaches include lack of information about involvement of other organs (eg, lung congestion), prognostic information, or patient stratifications. To improve and supplement such established biomarker, circulating miRNAs and more recently lncRNAs and likely circular lncRNAs are expected to similarly reflect cardiac injury, involvement of other organ systems, and overall the pathophysiological state of the patient. This question has been addressed by several detailed reviews.4,41 Therefore, miRNAs with strong diagnostic and prognostic relevance, as well as recent studies on lncRNA-based biomarkers, are summarized below (see Tables 1 and 2).

    Table 1. Cardiac miRNA Biomarker in Cardiovascular Disease and Injury

    MiRNADiseaseRegulationPurposeNormalizationControlCaseEvent Rate (Follow-Up Time)Ref.
    miR-1AMIDiagnosticN/A20*31 AMI42
    DiagnosticmiR-17-5p1733 STEMI43
    DiagnosticN/A4229 ACS44
    DiagnosticU6 snRNA6693 MI45
    DiagnosticmiRNA spike-in1125 MI46
    Diagnostic/prognostic: deathCel-miR-54117 UA, 131 NSTEMI, 196 STEMI7.7% (6 mo)47
    DiagnosticCel-miR-397270 AMI48
    DiagnosticmiR-1799*92 NSTEMI49
    DiagnosticCel-miR-3932*67 AMI50
    TachycardiaDiagnosticU6 snRNA1624 tachycardia51
    AFDiagnosticN/A112*§112 AF52
    CADDiagnosticmiR-1620*§19 UA, 34 SA53
    TTCDiagnosticCel-miR-3928*36 TTC, 27 STEMI54
    HFDiagnosticSequencing1338 HF55
    Diagnostic/prognostic: HF or deathmiR-1788173 STEMI, 146 NSTEMI18.0% (30 d)56
    DiagnosticmiR-103-3p17*61 HF57
    Diagnostic/prognostic: deathCel-miRs58236 AHF, 44 CHF17.0% (1 y)58
    miR-133a/bAMIDiagnosticmiR-16110*76 AMI59
    DiagnosticmiR-17-5p1733 STEMI43
    DiagnosticN/A4229 ACS44
    DiagnosticmiRNA spike-in1125 MI46
    Diagnostic/prognostic: deathCel-miR-54117 UA, 131 NSTEMI, 196 STEMI7.7% (6 mo)47
    DiagnosticU6 snRNA12713 AMI, 176 AP60
    Diagnostic/prognostic: LV remodelingCel-miR-39246 AMI38.5% (1 y)61
    DiagnosticmiR-1799*92 NSTEMI, 81 CHF49
    DiagnosticCel-miR-3932*67 AMI50
    DiagnosticmiR-17-5p1733 STEMI43
    TachycardiaDiagnosticU6 snRNA1624 tachycardia51
    CADDiagnosticCel-miR-391431 CAD62
    DiagnosticmiR-1620*§19 UA, 34 SA53
    TTCDiagnosticCel-miR-3928*36 TTC, 27 STEMI54
    HFDiagnosticSequencing1338 HF55
    miR-208a/bAMIDiagnosticCel-miR-397270 AMI48
    DiagnosticCel-miR-393033 AMI63
    DiagnosticHY3 molecule819 STEMI, 12 CAD64
    DiagnosticmiRNA spike-in1125 MI46
    Diagnostic/prognostic: deathCel-miR-54117 UA, 131 NSTEMI, 196 STEMI7.7% (6 mo)47
    Diagnostic/prognostic: LV remodelingSV40 spike-in243116 AMI32.3% (121–226 d)65
    DiagnosticCel-miRs (3×)36*32 AMI66
    DiagnosticCel-miR-3932*67 AMI50
    VMDiagnosticCel-miRs (3×)20*34 VM, 20 post VM66
    CADDiagnosticCel-miR-391431 CAD62
    HFDiagnosticSequencing1338 HF55
    Diagnostic/prognostic: HF or deathmiR-1788173 STEMI, 146 NSTEMI18.0% (30 d)56
    miR-423-5pAMIDiagnostic/prognostic: LV remodelingCel-miR-39246 AMI38.5% (1 y)61
    DiagnosticmiR-1799*92 NSTEMI, 81 CHF49
    DCMDiagnosticCel-miR-3939*45 DCM67
    HFDiagnostic/prognostic: deathCel-miRs58236 AHF, 44 CHF17.0% (1 y)58
    DiagnosticmiR-12493930 HF, 20 non-HF68
    DiagnosticMean Ct30*30 CHF69
    DiagnosticCel-miR-5410*41 HF (transition of great arteries)70
    miR-499AMIDiagnosticCel-miR-397270 AMI48
    DiagnosticCel-miRs (3×)36*32 AMI66
    DiagnosticSpike-in RNA1014 ACF, 15 CHF71
    DiagnosticU6 snRNA100142 AMI72
    DiagnosticMean Ct3073 ACS73
    DiagnosticCel-miR-3932*67 AMI50
    Diagnostic/prognostic: PMIMedian Ct8928 PMI23.3% (PMI)74
    DiagnosticmiR-17-5p1733 STEMI43
    DiagnosticmiR-1799*92 NSTEMI, 81 CHF49
    DiagnosticU6 snRNA2537 UA, 48 NSTEMI75
    VMDiagnosticCel-miRs (3×)20*14 VM, 20 post VM66
    HFDiagnosticCel-miRs (3×)34*33 HF66
    DiagnosticSequencing1338 HF55
    Diagnostic/prognostic: HF or deathmiR-1788173 STEMI, 146 NSTEMI18.0% (30 d)56

    *†‡§indicates if controls have been matched to age, sex, ethnicity, and other parameters.

    ACS indicates acute coronary syndrome; AF, atrial fibrillation; AMI, acute myocardial infarction; AP, angina pectoris; CAD, coronary artery disease; Ct, cycle threshold; DCM, dilated cardiomyopathy; HF, heart failure (A=acute, C=chronic); LV, left ventricle; MI, myocardial infarction; miRNA, microRNA; N/A, not available; NSTEMI, non–ST-segment–elevation myocardial infarction; PMI, perioperative myocardial infarction; snRNA, small nuclear RNA; STEMI, ST-segment–elevation myocardial infarction; TTC, Takotsubo cardiomyopathy; U/SA, unstable/stable angina pectoris; and VM, viral myocarditis.

    Cardiac and Muscular miRNAs

    Several studies assessed miRNAs as early indicators of cardiac injury because of AMI. The muscle- and heart-enriched miRNAs miR-1, miR-133, miR-208, and miR-499 were consistently found to be elevated in the bloodstream of AMI patients (Table 1). This suggests their potential as novel biomarker for the diagnosis and prognosis of AMI.4

    MiR-1 is abundantly expressed in the skeletal and cardiac muscle and involved in muscle differentiation, cardiac development,97 and cardiovascular disease.4 Several studies found this miRNA to be elevated in the circulation of both AMI patients and animal models. In rodents, coronary artery ligation provoked a rapid induction of serum miR-1,42,43,63 whereas this miRNA was downregulated in heart tissue44 suggesting a release into the bloodstream on cardiac injury. Highest plasma miR-1 levels were detected after 6 hours that were cleared from the bloodstream 3 days later. Interestingly, miR-1 correlated with myocardial infarct size.42 In accordance with these findings, miR-1 had also markedly increased in the bloodstream of patients with AMI.42,43,63,45,46 Exemplarily, circulating miR-1 was ≈100-fold induced 6 hours after AMI and positively correlated with serum CK-MB.63 An inverse correlation was shown to circulate FABP3 (fatty acid–binding protein-3), an early AMI marker. This protein is a direct target of miR-1, and its plasma levels may indirectly mirror the myocardial activity of miR-1.98 In addition, Ai et al45 found that the elevation of miR-1 was associated with arrhythmia as indicated by abnormal QRS complex, but independent from age, sex, diabetes mellitus, or established biomarker of AMI. Studies in larger patient populations confirmed these proof-of-concept approaches.47 Therefore, miR-1 seems to be a valuable diagnostic biomarker for AMI.

    As miR-1, miR-133 is a crucial regulator of cardiac and skeletal muscle development, as well as during pathophysiologic alterations,97 and plays an additional role in vascular smooth muscle cell biology.4 First evidence that miR-133 is a potential biomarker of AMI came from animal studies. Plasma levels of miR-133a were elevated 1 hour after coronary artery ligation in rats and was 1000-fold induced after 3 hours,63 whereas mice post-AMI showed highest miR-133 levels 6 hours after the intervention.43 This release seems to be specific for cardiac injury because hindlimb ischemia had no effect on circulating miR-133 levels.43 In clinical studies, miR-133 was reported to be increased 4.4-fold in the plasma of MI patients and positively correlated with cTnT levels. D’Alessandra et al43 found highest miR-133a and miR-133b plasma levels shortly after the onset of symptoms and importantly earlier than cTnT. This finding was confirmed by Wang et al,60 where circulating miR-133a was shown to be induced in an early stage after AMI and positively correlated with cTnT levels. Although miR-133 elevation was significantly associated with the risk of death assessed in a larger cohort of patients with acute coronary syndrome, considering high-sensitive cTnT levels this association got lost, indicating that this miRNA is not an alternative or improvement for the established AMI troponin biomarkers.47 Furthermore, miR-133 did not provide prognostic information about future left ventricular remodeling after AMI.61

    MiR-208 is abundantly and specifically expressed in the heart and arises from an intron of the Myh6 (α-myosin heavy chain gene). This miRNA is involved in pathological cardiac remodeling, as well as fibrosis, and in the regulation of the cardiac muscle gene expression.4 As miR-1 and miR-133, miR-208a is a plasma marker with strong and early induction after coronary artery occlusion in rats and after AMI in humans.63 This miRNA correlated with cTnTs63,99 and was detected earlier because elevation of conventional marker of AMI was delayed.63,64 When compared with other cardiac- and muscle-associated miRNAs, miR-208 displayed highest specificity and sensitivity for AMI.63 Along with miR-499, miR-208 was reported to exhibit a more reliable predictive value in AMI diagnosis compared with miR-1.48 In addition, elevated levels of miR-208b and miR-34a were identified as predictors for left ventricular remodeling after AMI and correlated with elevated risk of mortality or HF.65 Although these findings were supported by studies of Corsten et al,66 Gidlöf et al46 and within a larger cohort presented by Widera et al,47 other studies failed to detect miR-208 in the circulation,43,71 presumably because of low plasma levels and rapid clearance of this miRNA from the bloodstream that limits its use as a clinical useful biomarker.

    MiR-499 is a cardiac-specific miRNA and encoded by an intron of the Myh7 (β-myosin heavy chain gene). Hypoxia and ischemic stress decrease the expression of this miRNA.4 In the circulation, miR-499 along with miR-208 seems to be a general indicator of cardiac injury induced by cardiovascular disease.66 Similar to other cardiac miRNAs, an increase of circulating miR-499 was described for both human AMI patients and rodent models.63,71 Interestingly, miR-499 was not detectable in the plasma of healthy subjects, which may be because of assay sensitivity issues.71 More recent reports support these findings. Zhang et al72 showed that miR-499 was already elevated 1 hour after first chest pain symptoms and increased gradually within 9 hours. Furthermore, this miRNA was positively correlated with serum CK-MB and cTnI. Another study by Chen et al73 suggests that miR-499 elevation was associated with the severity of AMI considering occurrence of coronary artery disease. Assessment of serum miR-499 within 3 hours of symptom onset was linked to unstable angina and non–ST-segment–elevation myocardial infarction (STEMI).75 Compared with cTnT, assessment of circulating miR-499 enabled discrimination between patients with non-STEMI and congestive HF.49 In elderly patients, miR-499 exhibited a better accuracy in the diagnosis of non-STEMI compared with cTnT.50 In addition, miR-499 has been suggested as a biomarker for mortality risk stratification and as an indicator to identify perioperative AMI in cardiac surgery.74

    To conclude, cardiac- and muscle-enriched miRNAs seem to be of relevance for AMI diagnosis. These miRNAs were found to be elevated in the circulation of AMI patients and indicate a favorable diagnostic performance, reflecting the accuracy of predictions (area under the curve) ranging from 0.77 to 0.98 for miR-1,44,46 0.86 to 0.93 for miR-133,44,46, 0.94 to 1.00 for miR-208,46,66 and 0.82 to 0.99 for miR-499.46,66 However, their clinical application for the diagnosis of AMI remains controversial. Presumably, these novel biomarkers should not be regarded independently. In fact, an integrative approach considering a combination of circulating miRNAs could provide an important key for the improvement of AMI diagnosis. Other miRNAs besides cardiac- and muscle-associated miRNAs might also play an important role.

    Noncardiac miRNAs

    Many studies identified noncardiac miRNAs to be deregulated in the circulation of AMI patients (Table 2). Resulting miRNA profiles overlap to a small extent, even though larger cohorts have been investigated. Exemplarily for diagnostic purposes, miR-633b and miR-1291 have been found to specifically and sensitively distinguish between AMI patients and controls59 as well as miR-150 and miR-486 that were used to discriminate STEMI and non-STEMI patients.88 In addition, noncardiac miRNAs have been assessed for AMI risk stratification. Zampetaki et al80 performed a 10-year follow-up study and investigated 19 plasma miRNAs. They found that elevated levels of miR-126 and low levels of miR-223 and miR-197 held a stronger association with incident of AMI than other risk factors. Later, miR-197 and miR-223 were confirmed as predictors for cardiovascular death in a larger cohort including 873 patients with coronary artery disease (CAD).93 Bye et al76 proposed a panel of 5 miRNAs (let-7g-5p, miR-106a-5p, miR-144-3p, miR-424-5p, and miR-660-5p) to improve AMI risk stratification in healthy individuals.

    Table 2. Selected Noncardiac miRNA Biomarker in Cardiovascular Disease and Injury

    MiRNADiseaseRegulationPurposeNormalizationControlCaseEvent Rate (Follow-Up Time)Ref.
    miR-106a-5pAMIPrognostic: AMI5 spike-in RNAs100*11250.0% (10 y)76
    HFDiagnostic/prognostic: mortalityN/A41137 AHFN/A (180 d)77
    miR-122CADDiagnosticmiR-1620*19 UA, 34 SA53
    DiagnosticCel-miR-391695 CAD78
    DiagnosticCel-miR-39100255 Hyperlipidemia79
    miR-126AMIPrognostic: AMIAverage Ct820Population-based study5.7% (10 y)80
    CADDiagnosticCel-miR-391431 CAD62
    DiagnosticU6 snRNA3745 UA, 31 SA81
    DiagnosticmiR-1620*19 UA, 34 SA53
    Diagnostic/prognostic: MACECel-miR-39176 CAD31.3% (6.0–6.4 y)82
    HFDiagnostic/prognostic: deathCel-miRs58236 AHF, 44 CHF17.0% (1 y)58
    miR-134AMIDiagnostic/prognostic: death and HFSV40 spike-in30359 AMI23.1% (6 mo)83
    CADDiagnosticCel-miR-3970*90 CAD84
    miR-145AFDiagnosticN/A112*§112 AF52
    CADDiagnosticCel-miR-391431 CAD62
    HFDiagnostic/prognostic: CRTCel-miR-3915/60*81 HF68.0% (1 y)85
    miR-146aAFDiagnosticN/A112*§112 AF52
    CADDiagnosticCel-miR-391695 CAD78
    DiagnosticU6 snRNA1010 CAD, 10 ACS86
    HFDiagnosticN/A7575 HFpEF; 75 HFrEF87
    miR-150AMIDiagnosticU6 snRNA11065 STEMI, 45 NSTEMI88
    Diagnostic/prognostic: low EFCel-miRs (3×)150 AMI47.0% (138–262 d)89
    AFDiagnosticCel-miR-393030 PAF or PersAF90
    DiagnosticMean Ct3541 HF91
    DiagnosticMean Ct99112 AF92
    miR-197AMIPrognostic: AMIAverage Ct773*Population-based study5.7% (10 y)80
    AMI/CADDiagnostic/prognostic: deathCel-miR-39340 ACS, 533 SA2.1% (2.78–5.04 y)93
    miR-199aCADDiagnosticmiR-1620*19 UA, 34 SA53
    Diagnostic/prognostic: MACECel-miR-39176 CAD31.3% (6.0–6.4 y)82
    HCMDiagnosticSpike-in N/A4141 HCM94
    HFDiagnostic/prognostic: mortalityN/A41137 AHFN/A (180 d)77
    miR-21AMIDiagnosticmiR-179992 NSTEMI, 81 AHF49
    AFDiagnosticMean Ct99112 AF92
    HCMDiagnosticU6 snRNA2827 HCM95
    CADDiagnosticU6 snRNA3745 UA, 31 SA81
    HFDiagnosticmiR-103-3p1761 HF57
    Diagnostic/prognostic: deathCel-miRs58236 AHF, 44 CHF17.0% (1 y)58
    miR-223AMIPrognostic: AMIAverage Ct773*47 AMI5.7% (10 y)80
    AMI/CADDiagnostic/prognostic: deathCel-miR-39340 ACS, 533 SA2.1% (2.78–5.04 y)93
    miR-26aTTCDiagnosticCel-miR-392836 TTC, 27 STEMI54
    HFDiagnostic/prognostic: mortalityN/A41137 AHFN/A (180 d)77
    Diagnostic: response to CRTCel-miR-3915/60*81 HF85
    miR-27aAMIDiagnostic/prognostic: low EFCel-miRs (3×)150 AMI47,0% (138–262 d)89
    HCMDiagnosticSpike-in N/A4141 HCM94
    HFDiagnostic/prognostic: mortalityN/A41137 AHF77
    miR-30c/dHCMDiagnosticU6 snRNA2827 HCM95
    HFDiagnosticN/A7575 HFpEF; 75 HFrEF87
    Diagnostic/prognostic: mortalityN/A41137 AHFN/A (180 d)77
    Diagnostic/prognostic: CRTCel-miR-3915/60*81 HF68.0% (1 y)85
    CADDiagnosticU6 snRNA1010 CAD, 10 ACS86
    miR-328AMIDiagnostic/prognostic: death and HFSV40 spike-in30359 AMI23.1% (6 mo)83
    AFDiagnosticN/A112*§112 AF52
    Diagnostic/prognostic: AFnoPopulation-based study24450.04% (5.4 y median)96
    HFDiagnosticN/A7575 HFpEF; 75 HFrEF87
    miR-486AMIDiagnosticU6 snRNA11065 STEMI, 45 NSTEMI88
    CADDiagnosticCel-miR-391695 CAD78

    *†‡§indicates if controls have been matched to other parameters, age, sex, and ethnicity.

    ACS indicates acute coronary syndrome; AF, atrial fibrillation (P=paroxysmal, Pers=persistent); AMI, acute myocardial infarction; CAD, coronary artery disease; CCS, case-control study; CRT, cardiac resynchronization therapy; Ct, cycle threshold; DCM, dilated cardiomyopathy; EF, ejection fraction; HCM, hypertrophic cardiomyopathy; HF, heart failure (A=acute, C=chronic, pEF=preserved ejection fraction, rEF=reduced ejection fraction); MACE, major adverse cardiovascular event; miRNA, microRNA; N/A, not available; NSTEMI, non–ST-segment–elevation myocardial infarction; PS, population-based study; snRNA, small nuclear RNA; TTC, Takotsubo cardiomyopathy; and U/SA, unstable/stable angina pectoris.

    To predict the outcome after AMI, Matsumoto et al100 screened miRNAs that were differentially expressed in the circulation of patients at high risk for cardiac death within 1 year after AMI and found an elevation of miR-155 and miR-380* in this patient group. In a subsequent study, the same authors investigated plasma levels of miRNAs responsive to p53 signaling 18 days after the cardiac event. MiR-192, miR-194, and miR-34a were found to be increased in AMI patients, who developed HF within 1 year, whereas miR-194 and miR-34a were associated to left ventricular end-diastolic dimensions.101 In addition, increased levels of miR-328 and miR-134 were strongly correlated with elevated risk of HF and mortality within 6 months after AMI.83 Four miRNAs were used to predict left ventricular contractility impairment after AMI. Patients with low levels of miR-150 and miR-101 and increased levels of miR-16 and miR-27a were found to be at higher risk.89

    It seems that compared with cardiac-enriched miRNAs, noncardiac miRNAs have a comparable potential as AMI biomarker. However, it is debatable whether these miRNAs reflect secondary rather than direct effects of cardiac injury and where they might originate from. A likely source might be platelets that on activation release their miRNA content into the circulation.102,103 Therefore, multicenter and large cohort studies are needed to confirm their suitability as a biomarker of AMI.

    Long Noncoding RNAs

    Although numerous studies highlighted miRNAs as potential AMI biomarkers, only a few focused on the diagnostic value of circulating lncRNAs (Table 3). A genome-wide association study identified the myocardial infarction-associated transcript as a susceptible locus for AMI.112 A global lncRNA profiling in plasma of patients with left ventricular cardiac remodeling after AMI unraveled a mitochondrial transcript, named LIPCAR (long intergenic ncRNA predicting cardiac remodeling) that was downregulated in an early phase after the cardiac event and remained elevated during later stages.105 Importantly, this study showed a strong prognostic power of LIPCAR with respect to future development of detrimental cardiac remodeling and death. In addition, MYHEART (myosin heavy-chain–associated RNA transcript), a recently described lncRNA protecting the heart from hypertrophic remodeling,113 was found to be elevated in AMI patients compared with control subjects and positively correlates with the cardiac injury marker cTnT.106 UCA1 (urothelial carcinoma-associated 1), a regulator and indicator of bladder and lung cancer, was downregulated shortly after AMI, but was found to be increased when assessed 3 days after cardiac injury. In comparison, miR-1, that was suggested to be regulated by UCA1, followed an opposite time course.104

    Drug-Induced Cardiotoxicity

    Several therapies for cancer and other diseases can cause severe side effects impairing cardiovascular health. Cardiac toxicity and injury hampers the cardiac performance and provokes hypertension, cellular apoptosis, arrhythmia, fibrosis, and finally HF. Therefore, minimization or prevention of such side effects by early monitoring of drug-induced cardiac toxicity and injury would be of great interest for therapeutic strategies.114 However, only few studies have evaluated ncRNA plasma levels in this setting. First evidence came from an in vivo study assessing isoproterenol-induced heart tissue injury in rats.99 This intervention led to increased serum miR-208 concentration and correlated in a time-dependent manner with the conventional plasma maker of myocardial injury cTnI, but was not affected by renal injury.99 Additional animal studies support miR-208 responsiveness to isoproterenol or to metaproterenol, allylamine, and mitoxantrone.115,116,117 Interestingly, miR-208 did not respond to a single administration of doxorubicin, whereas this treatment induced other muscle- and heart-specific miRNAs, suggesting an indication of skeletal muscle toxicity.117 In contrast, circulating miR-208a was not detected in the bloodstream of patients with breast cancer along the chemotherapy treatment with doxorubicin.118 These differences might be because of species specificities, temporal or dose-depended effects, or indicate that different drugs might provoke different circulating miRNA patterns. Therefore, other miRNAs have been considered as biomarkers for drug-induced cardiotoxicity. Zhao et al119 addressed this question and profiled miRNAs in the plasma of patients receiving bevacizumab, a monoclonal antibody used for the treatment of colorectal cancer. They identified 2 cancer-associated miRNAs (miR-579 and miR-1254) that were specifically induced in the circulation of patients with bevacizumab-induced cardiotoxicity and discriminated this patient group from those with AMI.

    With respect to the limited number of reports, it becomes evident that additional studies are needed to provide a more detailed description of miRNAs and other ncRNAs involved during cardiotoxicity. These biomarker studies should consider and link various drugs and interventions that exhibit detrimental side effects on the heart.

    Viral Myocarditis

    Myocarditis, an inflammatory disease of the heart, can be caused by microbial infections, immune or autoimmune reactions. As a consequence of the immune response, cardiac tissue can be injured. Cellular damage caused by viral infections seems to alter the pattern of circulating miRNAs that is comparable with AMI patients (Table 1). Corsten et al66 found 2 aforementioned cardiac-specific miRNAs miR-208 and miR-499 to be induced in the circulation of patients with acute viral myocarditis. Expression levels of these miRNAs were significantly associated with disease severity. Further research on plasma miRNAs and lncRNAs might lead to more specific ncRNA biomarkers for the diagnosis of myocarditis.

    NcRNAs as Biomarker of Cardiac Pathophysiology

    Arrhythmia

    Arrhythmias including atrial fibrillation and tachycardia are associated with pronounced morbidity and mortality. Genetic preposition determines individual susceptibility, occurrence, and progression of this disease involving dysregulation of neurohormones and Ca2+ handling, as well as structural and electric remodeling.120 Thus, novel and specific biomarkers for the diagnosis and prognosis of arrhythmias have great implications for the treatment of this condition and prevention of cardiac sudden death. Accordingly, Sun et al51 aimed to investigate heart-specific miRNAs in the plasma of pediatric patients with recurrent sustained tachycardia symptoms. MiR-133a was increased on ventricular tachycardia, whereas miR-1 was decreased in the circulation of patients with supraventricular tachycardia, suggesting these miRNAs as potential markers to sensitively distinguish among both patient groups. A recent study analyzed changes in plasma miRNA levels and suggested a functional relevance of miR-1, which was decreased in the circulation of atrial fibrillation patients, on intracellular Ca2+ handling.52 Aside from cardiac-specific miRNAs, miR-150 seems to be another marker of atrial fibrillation. This miRNA was found to be reduced in the bloodstream of patients with paroxysmal and persistent atrial fibrillation.90 Two further studies confirmed these findings: lower concentrations of miR-150 were detected in serum and platelets of patients with systolic HF and atrial fibrillation. Interestingly, circulating plasma and platelet concentrations of miR-150 correlated with each other,91 presumably being indicative for platelet activity.103 In addition, miR-150 along with miR-21 was reduced in the plasma of patients with paroxysmal atrial fibrillation, but increased after ablation of this arrhythmia. MiR-21, but not miR-150, was repressed in atrial tissues of these patients.92 In contrast, chronic atrial fibrillation increased atrial miR-21.121 Expression analysis of 385 circulating miRNAs in whole blood of atrial fibrillation patients identified miR-328, a known promoter of electric remodeling, that was associated with prevalent atrial fibrillation, but none of the candidates correlated with an incident of atrial fibrillation.96 MiR-328 was downregulated in the circulation, but upregulated in atrial tissues.122 MiR-29b showed a different relation. It was reduced both in the circulation of patients with either congestive HF or arterial fibrillation and in atria tissue of chronic atrial fibrillation patients.123

    Taken together, miRNA-based biomarkers of arrhythmias found increasing attention (summarized in Tables 1 and 2). Further studies are needed to link these finding to the underlying mechanisms of arrhythmogenesis. In contrast, plasma profiles of lncRNAs have not been assessed to date. Although first studies unravel differential expression of such ncRNAs in heart tissue of patients with atrial fibrillation,124 their potential as diagnostic and prognostic biomarker in this field remains elusive.

    Coronary Artery Disease

    CAD is caused by the formation of atherosclerotic plaques and is accompanied by structural remodeling of the arterial wall, activation of endothelial, and inflammatory cells and can finally develop into myocardial ischemia.125 Activation of the endothelium is critical for atherosclerosis and a potential source for circulation, thus providing the creation of novel biomarkers for an early diagnosis or identifying unstable plaques finally enabling risk stratification of patients (Tables 1 and 2). Accordingly, miRNAs that have been related to cellular components of atherogenesis have been found to be deregulated. However, data of circulating signatures of CAD miRNAs are conflicting. Endothelial (miR-17, miR-92a, and miR-126), inflammatory (miR-155), and smooth muscle cell–associated (miR-145) miRNAs were found to be reduced in the circulation of patients with CAD, whereas plasma levels of cardiac and muscular miRNAs (miR-133a, miR-208a, and miR-499) were increased. The authors suggest that miRNAs might be cleared from the bloodstream by an uptake into atherosclerotic lesions or the vasculature and that the enhanced release and elevation of miRNAs potentially reflects myocardial injury.62 In contrast, circulating miRNA patterns of miR-126 and the miR-17/92a cluster along with miR-451, the miR-106b/25 cluster, and the miR-21/590-5p family were upregulated in vulnerable CAD.81 In line with these findings, miR-1, miR-133a/b, miR-122, miR-126, and miR-199a were induced in the circulation of patients with stable and unstable angina53 and miR-92a, as well as miR-486, in association with high-density lipoprotein components were identified as potential circulating biomarker of coronary plaque vulnerability.78 Because of inconsistencies, most of the miRNAs were not validated in larger cohorts. Accordingly, severity of CAD in hyperlipidemia patients was suggested to correlate with increased plasma levels of lipometabolism-related miR-122 and miR-370.79 Liu et al84 characterized miRNA signatures for the risk assessment in symptomatic patients with obstructive CAD and chest pain. MiR-134, miR-2861, and miR-3135b were associated with the degree of coronary artery calcification and changed in patients with obstructive CAD. A prognostic analysis by Jansen et al82 associated elevated load of plasma-derived microvesicles with miR-126 and miR-199a with a reduced risk of adverse cardiovascular events within ≈6 years. Other studies focused on miRNA-197 and miRNA-22393 or miR-132, miR-140-3p, and miR-210126 as predictors for cardiovascular death.

    Taken together, plasma miRNAs have the potential to improve the diagnosis and prognosis of CAD. However, replication of findings and validation of candidate miRNAs in independent cohorts are still pending and would support the utility of these ncRNAs for the diagnosis and prognosis of CAD. Recently, lncRNAs gained attention as additional biomarkers (Table 3). A microarray-based screen in the plasma of patients with CAD unraveled one transcript, named CoroMarker, as a stable, sensitive, and specific indicator of this disease.107,108 Interestingly, this lncRNA was found in extracellular vesicles108 and circulating peripheral blood monocytes.107 The same group suggested LncPPARδ, which was elevated in circulating peripheral blood monocytes, as an additional CAD biomarker when combined with other risk factors.109

    Table 3. LncRNA Biomarker in Cardiovascular Disease and Injury

    DiseaseLncRNARegulationPurposeNormalizationControlsCasesEvent Rate (Follow-Up Time)Ref.
    AMIUCA1BiphasicDiagnosticU6 snRNA1549 AMI104
    LIPCARBiphasicDiagnostic/prognostic: death or LV remodelingCel-miR-39246 AMI, 344 HFLV remodeling: 38.5% (1 y)105
    MYHEARTDiagnostic5S rRNA2847 AMI106
    CADCoroMarkerDiagnosticβ-actin2020 CAD107
    CoroMarkerDiagnosticInternal control187221 CAD108
    LncPPARδ +DiagnosticGapdh171*†211 CAD109
    HCMuc004cov.4DiagnosticCel-miR-392628 HNCM, 57 HOCM110
    uc022bqu.1DiagnosticCel-miR-392628 HNCM, 57 HOCM110
    HFSENCRDiagnosticCel-miR-391278 Type 2 diabetes mellitus111

    *†indicates if controls have been matched to age and sex.

    AMI indicates acute myocardial infarction; CAD, coronary artery disease; CCS, case-control study; HCM, hypertrophic cardiomyopathy; HF, heart failure; HNCM, hypertrophic nonobstructive cardiomyopathy; HOCM, hypertrophic obstructive cardiomyopathy; LIPCAR, long intergenic ncRNA predicting cardiac remodeling; lncRNA, long noncoding RNA; LV, left ventricle; MYHEART, myosin heavy-chain–associated RNA transcript; N/A, not available; rRNA, ribosomal RNA; SENCR, smooth muscle and endothelial cell–enriched migration/differentiation–associated long noncoding RNA; snRNA, small nuclear RNA; and UCA1, urothelial carcinoma-associated 1.

    Cardiomyopathy

    Hypertrophic cardiomyopathy (HCM) is the most common genetically inherited heart disease, mainly caused by mutations impairing gene expression of the contractile apparatus. The pathophysiology is characterized by heterogeneous cardiac remodeling and progresses over time with variable clinical manifestations ranging from asymptomatic outcomes to cardiac arrhythmias, HF, and sudden cardiac death.127 This heterogeneity makes the prognosis uncertain. Therefore, several studies assessed plasma profiles of miRNAs as biomarkers of cardiac remodeling (Tables 1 and 2) and to discriminate between and characterize subtypes of cardiomyopathies. MiR-29a was increased in the bloodstream of patients with hypertrophic obstructive cardiomyopathy, but not in patients with nonobstructive indications, and correlated with the intraventricular septum size, whereas miR-29c was specifically indicative for aortic stenosis.128 This is in line with a pervious study that identified miR-29a as a potential indicator of myocardial remodeling in HCM. This miRNA correlated with clinical parameter of left ventricular hypertrophy and fibrosis.94 A third study focused on miRNAs as biomarkers of diffuse myocardial fibrosis in HCM patients. A combination of 8 miRNAs (miR-10b, miR-15a, miR-18a, miR-21, miR-29a, miR-30d, miR-193, and miR-296) showed improved predictive values over individual miRNAs or other circulating makers of collagen turnover.95 Aside from HCM, circulating miRNAs can be used to indicate dilated cardiomyopathy (DCM). This includes elevated concentrations of miR-423-5p in the circulation of DCM patients.67 Another study identified 4 miRNAs (miR-155, miR-636, miR-639, and miR-646) that were differentially regulated between children with DCM who died or needed heart transplantation and patients who recover ventricular function,129 which is of importance for risk stratification of this DCM population. A third increasingly recognized cardiomyopathy form is Takotsubo cardiomyopathy, a stress-induced acute syndrome that mimics AMI symptoms.130 As described before, myocardial injury was associated with a significant release of cardiac-specific miR-1 and miR-133a into the bloodstream. Elevated levels of these miRNAs were observed for Takotsubo cardiomyopathy as well,44,54 but interestingly differentiated Takotsubo cardiomyopathy patients from patients with AMI when combined with 2 stress- and depression-related miRNAs, miR-16 and miR-26a.54

    These data indicate that miRNAs are valuable indicators for cardiomyopathies and exhibit the potential to distinguish among different subtypes and from other cardiovascular diseases. Recently, lncRNAs are recognized as additional players in cardiomyopathies (Table 3).131,132 A recent work tested whether circulating mitochondrial lncRNAs might serve as biomarkers of cardiac remodeling in HCM patients. Two transcripts, uc004cov.4 and uc022bqu.1, were elevated in the circulation of hypertrophic obstructive cardiomyopathy patients when compared with hypertrophic nonobstructive cardiomyopathy and healthy subjects. These markers also provided strong sensitivity to identify this specific patient cohort, although the amount of patient studies was relatively low.110

    Heart Failure

    HF, or congestive HF , is preceded by pathological remodeling of the heart that finally impairs its capacity to maintain hemodynamic demands. HF is the final manifestation of cardiovascular disease and cardiac injury, as well as less common, but important, etiologies including cardiomyopathies, valvular heart disease, prolonged arrhythmias, myocarditis, infections, and cardiotoxic drugs.133 Several reports provide strong evidence that ncRNAs are involved in the development and progression of HF. Therefore, circulating ncRNAs have been increasingly studied as potential HF biomarker (summarized by several reviews10,40,125,133 and in Tables 1 and 2).

    Cardiac and Muscular miRNAs

    As for AMI, it seems reasonable that miRNAs reflecting myocardial injury might also serve as indicators for a failing heart (Table 1). Accordingly, the combined abundance of cardiac- and muscle-enriched miRNAs increased from 0.1% in healthy controls to over 1% in patients with advanced HF and correlated with increased cTnI, but not BNP levels.55 MiR-1, miR-133, miR-208, and miR-499 were found to be elevated in the circulation of patients with acute decompensated HF, but only miR-499 was significantly deregulated. None of the miRNAs correlated with BNP or cTnT levels.66 Subsequent studies associate miR-499 with AMI rather than HF,49 but assumed this miRNA along with miR-208b as useful predictors for HF risk after AMI.56 MiR-1 was found to be downregulated in patients with symptomatic HF. Its levels decreased with severity of HF and were further inversely correlated with NT-proBNP in patients with mild and moderate congestive HF.57 Accordingly, downregulation of circulating miR-1 was found in a larger cohort, including 711 patients with acute and 44 patients with stable HF.58

    MiR-423-5p is less specific for the heart and is present in various tissues,10 but frequently investigated as a potential HF biomarker. In a cohort of 30 patients with HF, 20 patients with non-HF dyspnea, and 39 healthy subjects, this miRNA was found to be elevated. Higher circulating levels of miR-423-5p correlated with NT-proBNP plasma concentrations, but were found to be independent from age and sex. Furthermore, miR-423-5p enabled discrimination among patients with or without HF with an area under the curve of 0.91, suggesting this miRNA as a highly sensitive and specific biomarker.68 The elevation of miR-423-5p was confirmed by several other reports assessing systolic69 and chronic HF58 and DCM.67 In contrast, circulating miR-423-5p was neither deregulated in patients with impaired ejection fraction and systemic right ventricular function70 nor because of left ventricular remodeling monitored 1 year after AMI.61 These findings suggest that this miRNA can be used to distinguish among different HF etiologies. Interestingly, miR-423-5p expression was upregulated in failing heart tissue,134 enriched in pericardial fluid,135 and positively correlated with BNP transcoronary gradients,136 indicating a potential cardiac origin. However, it is still unclear whether this miRNA is released by cell death or active secretion during HF. Taken together, miR-423-5p is a promising, but to date challenging biomarker for HF; clinical value needs to be determined in larger study cohorts.

    Noncardiac miRNAs

    A plethora of noncardiac miRNAs have been linked to the diagnosis of HF (Table 2).10,133 Among them were angiogenesis-associated miR-126, which was lowered in the circulation of acute HF and non-HF patients compared with patients with chronic HF58; liver-enriched miR-12266 and inflammation-associated miR-21,57 which were elevated or reduced because of HF, respectively. However, none of these candidates have been validated in larger cohorts.10

    Further diagnostic studies used circulating miRNAs to discriminate between HF patients with reduced (HFrEF) and those with preserved ejection fraction (HFpEF), a patient population where diagnostic and prognostic biomarkers remain to be established. To date, 2 relevant studies have focused on circulating miRNAs in HFpEF,87,137 but only provide less consistent results. MiRNA profiling in whole blood and plasma samples of 30 HFrEF and 30 HFpEF patients compared with 30 healthy subjects unraveled 4 differentially regulated miRNAs (miR-125a-5p, miR-190a, miR-550a-5p, and miR-638) that discriminated HFrEF from HFpEF. MiR-125a-5p or the combination of several miRNAs increased the discriminative abilities of the proteinous marker NT-proBNP.137 In a larger cohort including 75 HFrEF, HFpEF and non-HF patients each, miR-30c, miR-146a, miR-221, miR-328, and miR-375 were validated to be differentially expressed among all patient groups. Candidate miRNAs alone or a combination of at least 2 with BNP improved the predictive power to distinguish HFpEF and HFrEF patients.87

    The prognostic capacity of noncardiac miRNAs has been addressed by 2 recent reports: A reduction of miR-18a-5p and miR-652-3p during hospitalization for HF was predictive for mortality within 180 days,77 and the prognostic value of miR-182 was identified to be superior to NT-proBNP.138 Other studies used circulating miRNAs to evaluate the outcome of surgical interventions, including cardiac resynchronization therapy (CRT), MitraClip, or left ventricular assist device. Plasma profiles of 55 responders to cardiac resynchronization therapy showed an induced concentration of circulating miR-26b-5p, miR-29a-3p, miR-30c-5p, miR-92a-3p, and miR-145-5p compared to 26 nonresponder HF patients. This elevation was positively associated to ejection fraction and negatively correlated to NT-proBNP.85 Patients that underwent surgical valve repair and MitraClip procedure showed specific exosomal miRNA patterns predicting functional recovery after surgery.139 Left ventricular assist device support provoked an increase in plasma miR-483-3p, whereas miR-1202 discriminated responders from nonresponders.140 Finally, allograft rejection after heart transplantation led to a differential expression of miR-10a, miR-31, miR-92a, and miR-155 and discriminated patients with rejection from those without.141

    Taken together, blood-based circulating noncardiac miRNAs are valuable tools for the diagnosis and prognosis of HF. However, only a few candidates have been validated, and therefore, large-scale clinical studies are necessary to proof their clinical utility compared with traditional HF biomarker. In addition, circulating lncRNAs and circular lncRNAs might open a novel avenue.

    Long Noncoding RNAs

    To date, only few studies have assessed altered circulating lncRNA patterns in HF (Table 3). In an acute HF model induced by serial injections of isoproterenol, 1619 circulating lncRNAs were elevated and 1582 reduced. Interestingly, lncRNA levels were inversely deregulated compared with their expression in the myocardium.142 In addition and as mentioned before, the lncRNA LIPCAR was dynamically regulated post AMI and suggested to predict cardiac remodeling and future death. Plasma levels of this transcript were elevated in patients with chronic HF and strongly correlated with cardiovascular mortality caused by this pathology.105 Both studies indicate the relevance of lncRNAs as biomarkers for HF. Whether plasma-derived lncRNAs represent diagnostic and prognostic tools applied in clinics requires further well-designed validation studies. A first use of circulating lncRNAs in a personalized medicine approach was recently published; here, the authors showed circulating SENCR (smooth muscle and endothelial cell–enriched migration/differentiation–associated long noncoding RNA) levels to be a potential candidate biomarker for the identification of patients with diabetes mellitus that will benefit pioglitazone therapy.111

    Current Limitations and Challenges of ncRNA Biomarker

    An enormous number of studies suggest that circulating ncRNAs promise to serve as a minimally invasive diagnostic and prognostic biomarker for various types of cardiovascular disease. Nevertheless, the lack of consistency in these studies is intriguing. Therefore, reliable, accurate, and sensitive detection of circulating ncRNA candidates is a prerequisite for their use as a biomarker in clinical applications. Several methodological factors including sample collection and processing, as well as assay performance and ncRNA quantification, can influence the quality of the resulting data and need critical considerations.4,10,41,143 Here, we outline the main procedural aspects.

    First of all, study design and blood sampling are the most critical steps. Sex, age, and cardiovascular risk factors seem to contribute to the variability of ncRNA levels.41 Time-dependent variations in circulating ncRNA should be considered as well. Studies with relatively small sample size lack statistical power. Therefore, large cohorts and multicenter studies are necessary for a reliable and reproducible validation of ncRNA biomarkers.10 Likewise, several studies have proven that heparin administration144 or medications, such as aspirin or statins,103,62 alter circulating ncRNA concentrations or their quantification. Furthermore, the presence of blood cells in plasma or serum samples leads to confounding background noise.102,103 The degree of hemolysis can be estimated by assessing hemoglobin or other endogenous RNAs.145 Therefore, caution is needed when selecting patients or estimating the suitability of samples.

    Another challenge is the low abundance of transcripts in body fluids impeding the determination of quality and quantity of isolated RNA. To reduce heterogeneity of circulating ncRNA profiles, a selective and consistent RNA isolation method throughout the entire study is strongly recommended. Standard protocols, including commercial column-based kits or TRIzol-based reagents, are widely accepted.143 To identify circulating ncRNA profiles in a specific disease state and subsequently biomarker candidates, sequencing approaches, microarrays, and quantitative real-time polymerase chain reaction are well-established platforms to quantify ncRNA expression. However, each approach has its own advantage and disadvantage (discussed by Moldovan et al143). Among these techniques, quantitative real-time polymerase chain reaction is the most common and reliable method to specifically and sensitively quantify miRNAs and lncRNAs. Limitations of quantitative real-time polymerase chain reaction, such as primer design and normalization, can highly influence the outcome of biomarker studies.4,10,41 Several companies provide specific and sensitive assays for miRNA detection, whereas lncRNA measurement usually requires a careful and customized primer design, as well as validation. NcRNA quantification is further limited by the lack of standardized control transcripts for normalization. Some studies suggest other miRNAs (eg, miR-16) or U6 RNA as housekeeping genes, but levels of such transcripts might be sensitive to specific cardiopathological conditions. Currently, the use of more than one or a combination of circulating ncRNAs as reference genes might be more applicable. Another common normalization approach is the use of exogenous, synthetic transcripts (eg, miRNAs derived from Caenorhabditis elegans) that are spiked-in prior ncRNA isolation and that serve as a control for extraction efficiency and quality.4,10,41

    Considering these limitations, a consensus on standardized methods for study design, sample handling, and ncRNA profiling is needed to eliminate technical and analytic variability and to generate reliable and reproducible ncRNA biomarker for the diagnosis and prognosis of cardiovascular disease and injury. A first approach within a European Union-funded project (HOMAGE [Heart OMics in AGEing]) was recently started where miRNAs in HF patients are measured and compared in same sample sets of various laboratories to search for differences in technological approaches and data normalization (http://www.homage-hf.eu/).

    Future Perspectives

    Cardiovascular diseases and cardiac injury have many faces and therefore show distinct tissue and circulating ncRNA patterns. This seems to be mainly mediated by nonprotein-coding transcripts, formerly regarded as junk RNA or genomic noise. In addition, there is sufficient evidence that supports circulating miRNAs, as well as lncRNAs, as promising biomarkers to complement or possibly outperform established protein-based biomarkers in cardiology. However, the use of ncRNAs is currently limited by (1) the insufficient knowledge about their origin and function, (2) the diversity of methodologies used for RNA extraction and ncRNA detection, (3) the lack of consistency and standardization of various studies, and (4) the relatively small patient cohorts used to date.143 Nevertheless, some circulating ncRNAs seem to display stronger diagnostic and prognostic values than conventional biomarkers not only because of their tissue- and disease-specific expression patterns20 but also because of physicochemical properties20 and their high stability in the circulatory system.28,29

    Promising impulses for further development of ncRNA-based biomarker are frequently coming from cancer research. Various clinical trials for the use of miRNAs as indicators of cancers are ongoing (clinicaltrials.gov). Interestingly, in 2012, the FDA approved the lncRNA prostate cancer antigen 3 as one of the first noncoding biomarker that is used routinely in clinical practice for the diagnosis of prostate cancer. This transcript is a highly specific biomarker upregulated in prostate cancer cells. The according assay is an in vitro nucleic acid amplification test that determines the ratio of prostate cancer antigen 3 lncRNA to PSA (prostate cancer antigen) messenger RNA in urine. The resulting score can be used to guide the decision for an initial biopsy in patients with suspicion for prostate cancer or whether a repetition of prostate biopsies is required.146

    Such developments set the ground for future application of ncRNAs for the diagnosis of cardiovascular disease and injury. Incorporating ncRNAs in the current portfolio of clinically used biomarkers would complete the picture and expand the understanding of cardiac pathologies and finally would enable more accurate risk stratification, diagnosis, and prognosis for cardiovascular disease and injury. Therefore, it remains to be seen how this field will develop and if prospective studies are able to validate the feasibility of ncRNAs as next-generation biomarkers of cardiovascular disease.

    Nonstandard Abbreviations and Acronyms

    AMI

    acute myocardial infarction

    BNP

    brain natriuretic peptide

    CAD

    coronary artery disease

    CK

    creatine kinase

    cTnT/I

    cardiac troponins T/I

    DCM

    dilated cardiomyopathy

    HCM

    hypertrophic cardiomyopathy

    HF

    heart failure

    HFpEF

    heart failure with preserved ejection fraction

    HFrEF

    heart failure with reduced ejection fraction

    lncRNA

    long noncoding RNA

    miRNA

    microRNA

    ncRNA

    noncoding ribonucleic acids

    STEMI

    ST-segment elevation myocardial infarction

    Footnotes

    Correspondence to Prof Dr Dr Thomas Thum, Hannover Medical School, Institute for Molecular and Translational Therapeutic Strategies, Carl-Neuberg-Str. 1, OE8886, D-30625 Hannover, Germany. E-mail

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