Next Article in Journal
Sphingolipid Metabolism in Glioblastoma and Metastatic Brain Tumors: A Review of Sphingomyelinases and Sphingosine-1-Phosphate
Next Article in Special Issue
The c.*52 A/G and c.*773 A/G Genetic Variants in the UTR′3 of the LDLR Gene Are Associated with the Risk of Acute Coronary Syndrome and Lower Plasma HDL-Cholesterol Concentration
Previous Article in Journal
MiRNA Profiles of Extracellular Vesicles Secreted by Mesenchymal Stromal Cells—Can They Predict Potential Off-Target Effects?
Previous Article in Special Issue
Galectin-3: A Potential Prognostic and Diagnostic Marker for Heart Disease and Detection of Early Stage Pathology
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Circulating microRNA as a Biomarker for Coronary Artery Disease

1
Faculty of Health and Medical Science, University of Surrey, Guildford GU2 7AL, UK
2
School of Clinical Medicine, University of Cambridge, Cambridge CB2 1TN, UK
3
School of Medicine, University Malaysia Sarawak, Kota Samarahan 94300, Sarawak, Malaysia
*
Author to whom correspondence should be addressed.
Biomolecules 2020, 10(10), 1354; https://doi.org/10.3390/biom10101354
Submission received: 7 August 2020 / Revised: 15 September 2020 / Accepted: 19 September 2020 / Published: 23 September 2020
(This article belongs to the Special Issue Molecular Biomarkers In Cardiology)

Abstract

:
Coronary artery disease (CAD) is the leading cause of sudden cardiac death in adults, and new methods of predicting disease and risk-stratifying patients will help guide intervention in order to reduce this burden. Current CAD detection involves multiple modalities, but the consideration of other biomarkers will help improve reliability. The aim of this narrative review is to help researchers and clinicians appreciate the growing relevance of miRNA in CAD and its potential as a biomarker, and also to suggest useful miRNA that may be targets for future study. We sourced information from several databases, namely PubMed, Scopus, and Google Scholar, when collating evidentiary information. MicroRNAs (miRNA) are short, noncoding RNAs that are relevant in cardiovascular physiology and pathophysiology, playing roles in cardiac hypertrophy, maintenance of vascular tone, and responses to vascular injury. CAD is associated with changes in miRNA expression profiles, and so are its risk factors, such as abnormal lipid metabolism and inflammation. Thus, they may potentially be biomarkers of CAD. Nevertheless, there are limitations in using miRNA. These include cost and the presence of several confounding factors that may affect miRNA profiles. Furthermore, there is difficulty in the normalisation of miRNA values between published studies, due to pre-analytical variations in samples.

Graphical Abstract

1. Introduction

Coronary artery disease (CAD) is a significant cause of morbidity and mortality in the elderly. It is a complex, chronic pathological process in the intima of coronary arteries, yielding atherosclerotic lesions that restrict blood flow to the myocardium and may be associated with a degree of inflammation. Whilst the disease can remain stable, acute plaque rupture followed by coronary artery thrombosis can be a fatal event. Early detection of this disease will allow for early management and intervention, reducing morbidity and mortality.
Biomarkers are defined as characteristics that may be measured as indicators of normal biological processes or pathogenic processes [1]. Biomarkers may involve several modalities, such as substances measured in the blood and other bodily fluids, as well as imaging results and technologies like electrocardiography; in particular, multi-biomarker approaches may be promising approaches for the better detection of pathophysiology [2]. Currently, CAD detection involves several modalities. Functional tests, such as stress electrocardiograms, and anatomical imaging, such as angiography, provide clinicians with indications of CAD severity [3]. Numerous studies have assessed the validity of these modalities. Their reliability, whilst being generally suitable, varies depending on context [4]. A potential reason for this is variations between heterogenous study populations; however, simultaneous consideration of different biomarkers may improve reliability [4].
Recently, microRNAs (miRNA) have been proposed as a potential biomarker for use in various clinical contexts. They are major effectors of gene silencing through post-transcriptional repression and mRNA degradation [5]. This review aims to discuss the potential utility of microRNA (miRNA), as a diagnostic and prognostic tool for clinicians to detect CAD.

2. Localisation of miRNA

MiRNA are short RNAs (18–25 nts) that engage in the sequence specific inactivation of mRNA (Figure 1). They are encoded by their own non-protein coding genes located across the genome, though they also occur in the introns and exons of other genes [6,7]. MiRNAs are predominantly located intracellularly, although a proportion of them can be detected in the extracellular environment (ECmiRNA), including in plasma and various other body fluids [8,9,10]. They occur freely circulating or associated with other molecules, including within extracellular vesicles, such as exosomes and microvesicles, and can also be complexed with lipoproteins [11,12,13,14,15].
Microvesicles and exosomes are both types of extracellular vesicles with multiple roles in normal cell physiology. One of their major functions is intercellular communication through the carriage of signalling molecules, including proteins, mRNAs, and miRNAs amongst others, to targets of variable distance from the cell of origin [16,17]. Exosomes have a size range of 30–100 nm, and themselves originate from organelles of the endocytic pathway, the multivesicular bodies [16,17]. A multivesicular body is produced by the invagination of an endosome to produce intraluminal vesicles, into which specific molecules are sorted. Multivesicular bodies are trafficked to and subsequently fuse with the plasma membrane, at which point the intraluminal vesicles, now labelled as exosomes, are released into the extracellular space [16,17]. Microvesicles have a size range of 0.1–1.0 μm and are produced from the plasma membrane directly through outward blebbing [17,18]. Specific molecular cargo is transported towards regions of the plasma membrane where local alterations in the lipid composition reduce the rigidity of the membrane and facilitate further curvature [17,18]. The assembly of contractile machinery in these regions produce cytoskeletal rearrangements that pinch off nascent microvesicles [17,18]. The membrane budding that produces microvesicles differs from the blebbing process that produces apoptotic bodies, which is a less specific process [17,18]. These extracellular vesicles can then be trafficked through autocrine, paracrine, and endocrine paths (Figure 2). The multiple forms of endocytosis are the typical forms of vesicle uptake, though membrane fusion between microvesicles and the target cell plasma membrane has also been observed [17]. The mechanism utilised is likely dependent on the recipient cell type and the suitable expression of receptors compatible with the vesicle [17].
Research suggests that miRNA occur within exosomes, not on their surface membranes or associated with surface structures [11,19]. Additionally, a significant number of transcripts in the exosomes are not present in the donor cells from which they are derived; this profiling suggests that the miRNA profile of exosomes does not directly reflect the transcriptional status of the donor cell [11,19]. Exosomes have therefore been proposed to be a means of cell type-specific intercellular paracrine communication through delivering RNAs, which would affect the recipient cell’s proteome, and this has been demonstrated in several in vitro models involving both animal and human cells [11,19,20,21,22,23].
While the principles of miRNA transfer by microvesicles are similar to that by exosomes, there are some notable differences [13]. For one, microvesicles (MVs) are synthesised from the plasma membranes of donor cells, and so the profile of the membrane proteins on them reflects the donor cell type. It seems probable that miRNA secretion via this mechanism is independent of the donor cell’s transcriptional status [24]. Known cell types that produce miRNA-loaded MVs include endothelial cells, mesenchymal stem cells, and cancer cells [12]. Finally, ECmiRNA are also found complexed with HDLs, and these have been of interest as biomarkers of CAD [25,26]. However, recent studies cast doubt on the exact role of exosomes and microvesicles as carriers of miRNA. One important criticism has been that extracellular vesicles may co-purify miRNA found in culture and supplement media, such as foetal bovine serum, potentially confounding results [27]. Newer techniques, such as high-resolution density gradient fractionation and direct immunoaffinity capture, suggest that the secretion of DNA and RNA products is independent of extracellular vesicles, perhaps through a proposed model of autophagy or multivesicular-endosome-dependent but exosome-independent mechanism [28]. Furthermore, only a small fraction of in vitro, human lymphocyte-derived extracellular vesicles have been found to carry miRNA, and the binding of extracellular vesicles to cell membranes has not been observed. This may be due to a short exposure time and variability in conditions from physiological conditions [29]. Thus, there is a requirement for further investigation in this domain, although microvesicle RNA biology has been successfully translated to use in clinical settings in the diagnosis of haematological and oncological disorders [30].
Freely-circulating miRNA have been demonstrated by PCR miRNA assays conducted on fractionated, filtered, and ultracentrifuged plasma obtained from peripheral blood samples [14,15]. The miRNA may be bound to Argonaute (Ago2), an extracellular miRNA binding protein, and together they form a stable nucleoprotein complex. These stable complexes exist intracellularly, so it may be plausible that a certain proportion of ECmiRNA are released following cell death processes, e.g., necrosis and apoptosis, though it remains a possibility that miRNA/Ago2 complexes are/can be directly released from cells in order to communicate with others [14,15].

3. Physiological Roles of miRNA and Their Clinical Relevance

The significance of miRNA is made evident by the defective organogenesis and embryonic lethality that is found in murine models of tissue-specific or germline Dicer knockouts, respectively [31,32]. Dysregulation of miRNA is linked to the aetiology or pathogenesis of viral infections, cancer, and metabolic diseases [33]. Notable cardiovascular examples are miR-208, miR-143/145, and miR-21. MiR-208 is derived from an intron of the α-MHC (myosin heavy chain) gene, which is uniquely expressed in the myocardium and encodes an isoform of myosin heavy chain [34]. It acts within a network to upregulate the expression of β-MHC in response to stress, but its absence does not result in the absence of myocardium, therefore yielding viable mice [35].
The miR-143/145 cluster regulates the expression of cytoskeletal genes in vascular smooth muscle cells (VSMCs), and although murine knockouts are still viable, they show reduced vascular tone and significantly reduced capacity for migration in the process of neointima formation following vascular injury [36,37]. Stress-induced hypertrophy of cardiomyocytes is, at least in part, facilitated by miR-21-mediated silencing of two target proteins [38]. Indeed, miRNA have a wide range of cardiovascular functions, and their absence induces many abnormal phenotypes [7]. A recently compiled database of extracellular vesicle miRNA describes their potential roles as biomarkers in various diseases, including myocardial infarctions [39,40,41,42].
Thus, miRNA may either have a causative role or are a consequence of pathology. In the case of the former, the relevant miRNA could be operating as an initiator or maintainer of the condition (i.e., is a necessary component of a particular disease process), or could simply yield susceptibility (i.e., could potentially be sufficient to produce the disease phenotype, for example by yielding a substrate that enables the disease to precipitate). In the case of the latter, the measured changes in miRNA levels may be due to unregulated secretion from injured/stressed cells, or as a homeostatic response to the insult, with the communication between the cells occurring at the paracrine or the endocrine level [43].
Hence, for both of these, by measuring the changes in the miRNA signatures in an individual before, during, and after recovery from a particular pathology, we may be able to identify how the miRNA are behaving with respect to aetiology and pathogenesis (i.e., whether changes in miRNA behaviour affect susceptibility, are an outright cause, or more simply are products of the disease process). These signatures themselves may be detected in biopsies or peripheral blood samples, and are defined by the identity of the specific miRNAs that are detected, as well as by their concentrations. There already exists diagnostic miRNA tests based on either an miRNA panel or single miRNA quantification for diseases like certain cancers, indicating a successful proof of concept for the use of miRNA as biomarkers in disease [44,45].

4. Coronary Artery Disease (CAD) Pathophysiology

To better appreciate and evaluate the potential of miRNA as biomarkers in CAD, it is necessary to first consider the pathology of CAD. The pathogenesis of coronary artery plaques in CAD involves endothelial cell activation and the subsequent infiltration of the tunica intima by oxidised lipoproteins and monocytes. These monocytes go on to differentiate into macrophages and transform into foam cells as they consume these lipoproteins [46,47]. Consequently, a chronic inflammatory response is produced, whereby the macrophages begin the secretion of cytokines and chemoattractant factors that promotes the activation of the endothelium, which beckons further adhesion and infiltration (diapedesis) of more monocytes/other leukocytes [48]. This leads to the development of a raised lesion with a fibrous cap (from the myofibroblasts) and a lipid-rich interior (from lysed foam cells). The “shoulder” of the cap is found to have both of these cell types in addition to T-lymphocytes (although their role is not entirely understood) [49].
Angiogenesis may occur within the plaque and contribute to the expansion of the plaque through haemorrhaging of the new vessels forming at the shoulder into the less dense, lipid-rich core. The plaque may subsequently rupture, which can lead to thrombosis as coagulation factors and thrombocytes adhere to the lesion, as well as embolisation of plaque fragments. Other complications include calcification, or the formation of an aneurysm as the tunica media weakens from the arterial remodelling [50]. Endothelial cells are also induced to produce a pro-inflammatory response, which propagates the further infiltration of monocytes and degeneration of the elastic laminae in the media [51]. This weakened area of vessel wall can dilate in response to pressure applied to it. CAD pathophysiology therefore has the potential to give rise to measurable circulating biomarkers, due to the close involvement of disease with the circulating vasculature. Established surrogates that are commonly used, such as circulating LDL, HDL, troponin, and creatinine kinase, are associated with different stages in their pathophysiology: LDL and HDL being more relevant upstream as risk factors, and troponin and creatinine kinase more relevant downstream as a consequence of sufficiently advanced disease. Thus, there may be other biomarkers that may be of use in either a prognostic or diagnostic capacity. miRNA may be one such class.

5. CAD Biomarkers and miRNA

Current standard molecular biomarkers include proteins, lipids, and other metabolites. Cardiac troponins are well-established and are commonly used indicators of adverse cardiac events [52]. Creatinine kinase is also used in the same context, although it is less specific due to its presence in skeletal muscle and cerebral tissue. However, troponins and creatinine kinase involve the terminal series of events in CAD: ischaemic damage to the myocardium arising as a result of acute coronary syndrome [9,53].
Novel serum biomarkers, and more recently urinary biomarkers for CAD, are of increasing interest. For example, high-sensitivity C-reactive protein and high-sensitivity troponin I assays have been proposed as biomarkers of coronary artery disease and its progression [54,55,56]. They pose the advantages of being non-invasive, compared to percutaneous coronary angiography, and without the radiation exposure of CT coronary angiography [57]. In a study that tested over 100 different serum biomarkers in over 1000 patients, four biomarkers in combination (adiponectin, apolipoprotein C-I, midkine, and kidney injury molecule-1 (KIM-1)) were found to predict incidence of severe CAD [58].
Alongside these novel biomarkers, numerous studies have tried to identify miRNA, which may distinguish between individuals with different cardiovascular health statuses (Table 1) [59,60,61]. These miRNAs may be considered at local sites, such as at plaques or sites of endothelial injury, or freely circulating in serum. There is a vast constellation of research, and several candidate miRNAs have been identified, although this is complicated by a lack of correlation between studies. This may be due to experimental design variation, as studies involve different experimental models, time courses (acute vs. chronic disease), and quantification methodologies.

5.1. Localised Changes in miRNA Profiles

At the tissue level, specific miRNAs are expressed at the sites of myocardial injury/ischaemia or at the site of the atherosclerotic lesion. This expression may be in vascular tissue, myocardium, or plaque cells. Vessel wall biology changes drastically as atherogenesis progresses, and the changes in miRNA expression reflect this (Figure 3). In vascular smooth muscle cells. miRNA-1, -10a, -21, -100, -133, -143, -145, and -204 have been characterised with their standard contractile phenotype [62,63]. This is contrasted with a myofibroblast phenotype that VSMCs differentiate into during plaque development, which is instead associated with miRNA-24, -26a, -31, -146a, -208, and -221 [62,63]. The latter set of miRNA directs VSMCs to a secretory phenotype, with increased proliferative and migratory activity [63,64,65,66,67,68].
In the case of miRNA-21, however, there is evidence of the inverse, whereby this miRNA, which is elevated in CAD, may promote VSMC proliferation and indicate the progression of atherosclerosis [69]. Through the inhibition of FOXP1 and ZDHHC14 expression, respectively, miRNA-206 and -574-5p also act to do the same, and are demonstrated to be elevated in CAD patients, although the former seems to actually be anti-atherogenic [70].
Endothelial cells produce a baseline level of miRNA-155 and miRNA-126-5p under healthy conditions, whereas miRNA-21, miRNA-34a, and miRNA-210 are featured more in the endothelium of atherosclerotic lesions (Figure 3) [63]. These are due to increased shear stress from altered tissue morphology, interrupted cell cycle control, and hypoxia, respectively, all of which occur in atherosclerotic plaques. However, the downregulation of miRNA-126-5p removes a significant promoter of endothelial cell repair and maintenance, which further enables atherogenesis [71].
Endothelial progenitor cells (EPCs) are mobilised to give rise to endothelial cells in angiogenic atherosclerotic lesions, in a process marked by changes in the miRNA. In particular, miRNA-361-5p and miRNA-206, which are upregulated in CAD patients, are potentially responsible for controlling the expression of vascular endothelial growth factor in EPCs, as well as EPC activity [72,73]. Connections have been made with further miRNA, though only in the broad scope of these lesions as a whole (Table 1).

5.2. Changes in Circulating miRNA

Certain miRNA will be released from cells as either a homeostatic response to CAD or following cell death (Figure 3). Therefore, miRNAs that are linked to such insults, such as miRNA-499, miRNA-208, and miRNA-1 [74,75,76,77], could plausibly be released from ischaemic cardiomyocytes as they necrose. Muscle-enriched miR-133a, together with miR-1, shows a steeper and earlier increase than cardiac-enriched miRNA (miR-499 and miR-208b) upon myocardial injury [42]. Alternatively, cell death within the atherosclerotic lesion itself can produce circulating miRNA. A fraction of endothelial cells in atherosclerotic plaques undergo apoptosis, and thus release apoptotic bodies that have been found to contain miRNA-126 (Figure 3) [14]. In actuality, this miRNA acts through CXCL12 to stabilise plaques and protect the vessel wall structure from further damage under atherogenesis (Table 1).
In terms of homeostatic responses, leukocytes, such as peripheral blood mononuclear cells (PBMCs), demonstrate altered miRNA profiles in CAD patients relative to healthy controls. One study reported differences in the levels of miRNA-147, which was downregulated, and miRNA-135a, which was upregulated, in these cells [78]. Another group observed that CAD patients’ PBMCs also had an increased expression of miRNA-146a/b under inflammatory stimuli associated with CAD, and lowered expression of let-7i [79,80].
In another study comparing the expression levels of multiple circulating miRNAs between eight CAD patients and eight healthy volunteers, all of the miRNA primarily expressed in the endothelium—miRNA-126, -17, -20a, -92a, -221, -199a-5p, -27a, -130a, and -21, as well as let-7d—had significantly lower levels in the circulation in CAD patients [61] (note, however, that miRNA-126 is also highly enriched in platelets [81]). This was in contrast to the miRNAs that were specifically expressed in striated muscle, of which only one (miRNA-208b) was found to have a significant difference, and was instead elevated in CAD patients [61].
Determining the cell type of origin, as well as the precise roles of both of these types of miRNA, would further define the underlying communications and transformations that lead to plaque formation. However, it may be suggested that circulating miRNA are the most feasible candidates as biomarkers, due to the comparative ease of extraction

6. miRNA in CAD Pathophysiology

The relevance of miRNAs as biochemical precursors to the more macroscopic cellular and histological events that comprise atherogenesis is becoming increasingly evident [82,83]. As discussed above, lipid metabolism and inflammatory changes are key aspects of this process. Therefore, here we discuss miRNA in these contexts and highlight the changes that occur in pathological processes.

6.1. Lipid Metabolism

LDLs, mainly in their oxidised form, are the primary carriers of the cholesterol and triglycerides that are found in atherosclerotic lesions. Implicated in the synthesis of these molecules are miRNA-24, -33, -103a, and -122, all of which are found to have been significantly increased in the PBMCs of CAD patients [84,85]. Further investigations of miRNA-33 have reported that it suppresses the cholesterol efflux mechanism in cells, at least in part by inhibiting the expression of ATP-binding cassette transporter A1 [86,87]. Likewise, the expression miRNA-370 is also significantly raised in CAD patients [88]. This miRNA downregulates the expression of a carnitine palmitoyl transferase protein that is required for the trafficking of fatty acids into the mitochondria for β-oxidation, and is also higher in CAD patients [87]. In addition, these individuals can be identified from increased miRNA-486, -92a, -208a, -122, -93, and -17-5p [86,87].

6.2. Inflammation

Endothelial vulnerability to pathological inflammatory activity may, in part, be regulated by miRNA-10a, which is also reduced in CAD patients compared to healthy controls [71,82,89,90]. miRNA-155 shows the same trend, though there is contrasting evidence when the miRNA’s levels in the plasma and plaques of individuals with atherosclerosis were investigated [89,90]. Li et al. [90] have also shown that miRNA-155 reduces the expression of calcium-regulated heat stable protein 1 and promotes TNF-α expression in macrophages, suppressing foam cell formation [71,89,90].
Furthermore, miRNA-22 is known to repress the chemokine CCL2 in PBMCs, which modulates intercellular communication in inflamed tissues [82,91]. In CAD patients, the levels of these miRNAs in PBMCs are reduced. In addition to this, miRNA-146a is also reduced in CAD patients [91]. This miRNA is induced by pro-inflammatory cytokines to inhibit the nuclear factor-κB pathway in a negative feedback loop to resolve inflammation in its later stages [82,91]. MiRNA, therefore, plays a role in inflammatory processes that may form one component of the complex pathophysiology of atherosclerosis, and may represent potential biomarker candidates early in the disease process [82].

7. Pitfalls in Assessing miRNA as Biomarker Targets

7.1. Confounding Factors

When considering the utility of miRNA as biomarkers, one needs to consider any variances in their expression not relating to pathological processes alone. One such source of variation may be population-level changes. Thus, studies has shown geographical/ethnic differences in the expression levels of miRNA [92,93].
Age and sex are other factors that correlate with the frequency of different miRNA in circulation [94]. This has been demonstrated in an analysis of platelet-derived mRNA and miRNA [95]. However, in terms of cardiac-specific miRNA, there is limited data on CAD-associated miRNAs and their variation with the sex and ethnicity of a patient. Discrepancies in miRNA levels with respect to age have been reported in a few studies, which is a further confounder, as ageing is a critical risk factor of cardiovascular health. For example, with miRNA-149, -424, and -765, the former two are downregulated and the latter upregulated in middle-aged (aged 49–57) CAD patients [96]. Another study showed that miRNA-126-3p expression is greater in senescent endothelial cells than in younger cells, and their quantity in circulation is also increased [97].
Furthermore, cardiac fibroblasts increase their expression of miRNA-21 and miRNA-22 with age, which can lead to increased fibrosis and progression towards senescence, respectively [98]. Cardiomyocytes show the same change in miRNA-22, whereby they have been demonstrated to have a suppressive effect on autophagy in aged cardiomyocytes, producing an improved functional recovery of myocardium post-infarct in elderly mice, though not in younger mice [99].
Moreover, the level of miRNA-155, in addition to actually being higher in human females, decreases with age. Other miRNA have been implicated in cardiac ageing and associated dysfunction in addition to CAD, including the miRNA-17-92 cluster, miRNA-18, miRNA-19, and miRNA-17-3p [98,100,101,102]. Therefore, since not all studies investigating these miRNA have adjusted their results to control for these factors, any reported variation in miRNA may partially be explained by factors other than CAD [103].

7.2. Measuring Serum and Plasma miRNA

Of the published studies that analyse circulating miRNA, the general trend seems to concentrate on using plasma-based samples. This specification is critical, as the difference in the molecular profile between serum and plasma results in a difference between the recorded miRNA levels as the sample is being prepared, as serum holds a higher concentration of RNA than plasma [104]. Further to this point is that coagulation increases variability in serum miRNA concentrations [104]. Hence, we must recognise the difficulty of normalising miRNA values due to pre-analytical variations, including blood cell counts and the miRNA load of the cells and platelets in circulation.
Furthermore, any haemolysis releasing the miRNA contained within blood cells will affect the total miRNA concentration and profile that we identify from serum, though cellular contamination would cause the same changes in plasma and serum samples. Thus, care should be taken when preparing samples to prevent distorted results [104,105,106], and it may be best to produce a standard operating procedure (SOP) for acquiring miRNA data, based on currently existing SOPs for collecting such samples.

8. Validity of miRNA as Biomarkers

When addressing the feasibility/validity of miRNA as a biomarker, a few critical points must first be considered. Firstly, ease of access is not a concern, as miRNAs occur in peripheral blood so whole blood samples can be taken. However, it should be noted that the majority of miRNA in peripheral blood will likely be derived primarily from well-vascularised tissues, e.g., lungs and kidneys, in addition to blood cells themselves (platelets are a major contributor to the circulating RNA pool [107]), so the relative quantities of particular miRNAs should be taken into account.
Secondly, cost is likely a significant concern, due to the processes required to prepare the miRNA: RNA purification, reverse transcription–polymerase and quantitative polymerase chain reaction/microarrays/sequencing, controlling RNase activity, etc. [108,109]
Thirdly is timing/storage. MiRNA/Ago2 complexes have remarkable biologic stability and occur both in microvesicles and freely in plasma, though miRNA integrity is also maintained in tissues that have been fixed in formalin and embedded in paraffin, as is done with biopsies [108,109]. This protects the original samples, though preparation of purified miRNA must still be done carefully, and regular monitoring and appropriate storage are necessary. Control of the temperature and RNase activity are crucial to prevent degradation.
Lastly is content/criterion validity [110]. Major efforts have been and are currently being invested into establishing the reliability of miRNA as a diagnostic for a diverse range of human diseases (i.e., carrying indicative or predictive value), as well as into developing diagnostic tests for them and trying to understand their contribution to the disease’s manifestation, as mentioned [43,111,112,113,114]. Prognostic information and severity assessments also stand to be improved through the use of miRNA [115].
While the quantification and normalisation methodologies are still being developed, stability, accessibility, and disease specificity still lend miRNAs significant value as biomarkers, and evidence of this continues to grow [116,117].
Given that there are several miRNAs, it is likely to be beneficial to assay these particular biomarkers in a panel of tests. When considering the levels of all of those that are tested for, we gain a better understanding of the pathology’s context. Some groups support this notion, with the suggestion that using a panel of select miRNA “may have a greater target-organ specificity and better diagnostic value than a single miRNA or well-established clinical biomarker” [116]. This is easily demonstrated by the range of miRNAs that are found to be involved in a singular disease, and a singular miRNA may be involved in multiple diseases, producing a web of interaction [116]. A gene can have sequences complementary to different miRNA seed sequences, and an miRNA may target multiple genes, so this is a feasible paradigm.

9. Conclusions

The field of miRNA biomarkers is still relatively young, although it shows significant promise for diagnostics, including for CAD. Many candidate biomarkers have been investigated which characterise different aspects of this vascular disease. There are still challenges, both in the scientific understanding of their roles in CAD and in normalising their measured values across samples and accounting for natural variation in the healthy population.

Author Contributions

Conceptualization, K.J.; writing—original draft preparation, I.T.F. and Z.A.; writing—review and editing, I.T.F., Z.A., C.E.E., and A.S.; supervision, A.S. and K.J.; funding acquisition, K.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Research England Global Challenge Research Fund, and the APC was funded by the University of Surrey.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. 2016 Diagnostic Biomarkers. In BEST (Biomarkers, EndpointS, and other Tools) Resource; Food and Drug Administration (US): Silver Spring, MD, USA; National Institutes of Health (US): Bethesda, MD, USA, 2018; pp. 3–5.
  2. Salzano, A.; Marra, A.M.; D’Assante, R.; Arcopinto, M.; Bossone, E.; Suzuki, T.; Cittadini, A. Biomarkers and Imaging: Complementary or Subtractive? Heart Fail. Clin. 2019, 15, 321–331. [Google Scholar] [CrossRef] [PubMed]
  3. Mordi, I.R.; Badar, A.A.; John Irving, R.; Weir-McCall, J.R.; Houston, J.G.; Lang, C.C. Efficacy of noninvasive cardiac imaging tests in diagnosis and management of stable coronary artery disease. Vasc. Health Risk Manag. 2017, 13, 427–437. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Vogel, R.A. Biomarkers of High-Grade Coronary Stenosis: Searching for Seventies. J. Am. Coll. Cardiol. 2017, 69, 1157–1159. [Google Scholar] [CrossRef] [PubMed]
  5. Carthew, R.W.; Sontheimer, E.J. Origins and Mechanisms of miRNAs and siRNAs. Cell 2009, 136, 642–655. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Rodriguez, A.; Griffiths-Jones, S.; Ashurst, J.L.; Bradley, A. Identification of mammalian microRNA host genes and transcription units. Genome Res. 2004, 14, 1902–1910. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  7. Bartel, D.P. MicroRNAs: Genomics, Biogenesis, Mechanism, and Function. Cell 2004, 116, 281–297. [Google Scholar] [CrossRef] [Green Version]
  8. Arroyo, J.D.; Chevillet, J.R.; Kroh, E.M.; Ruf, I.K.; Pritchard, C.C.; Gibson, D.F.; Mitchell, P.S.; Bennett, C.F.; Pogosova-Agadjanyan, E.L.; Stirewalt, D.L.; et al. Argonaute2 complexes carry a population of circulating microRNAs independent of vesicles in human plasma. Proc. Natl. Acad. Sci. USA 2011, 108, 5003–5008. [Google Scholar] [CrossRef] [Green Version]
  9. Cortez, M.A.; Bueso-Ramos, C.; Ferdin, J.; Lopez-Berestein, G.; Sood, A.K.; Calin, G.A. MicroRNAs in body fluids--the mix of hormones and biomarkers. Nat. Rev. Clin. Oncol. 2011, 8, 467–477. [Google Scholar] [CrossRef] [Green Version]
  10. Weber, J.A.; Baxter, D.H.; Zhang, S.; Huang, D.Y.; Huang, K.H.; Lee, M.J.; Galas, D.J.; Wang, K. The microRNA spectrum in 12 body fluids. Clin. Chem. 2010, 56, 1733–1741. [Google Scholar] [CrossRef]
  11. Valadi, H.; Ekström, K.; Bossios, A.; Sjöstrand, M.; Lee, J.J.; Lötvall, J.O. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat. Cell Biol. 2007, 2, 1000. [Google Scholar] [CrossRef] [Green Version]
  12. Sohel, M.H. Extracellular/Circulating MicroRNAs: Release Mechanisms, Functions and Challenges. ALS 2016, 10, 175–186. [Google Scholar] [CrossRef] [Green Version]
  13. Yuan, A.; Farber, E.L.; Rapoport, A.L.; Tejada, D.; Deniskin, R.; Akhmedov, N.B.; Farber, D.B. Transfer of microRNAs by embryonic stem cell microvesicles. PLoS ONE 2009, 4, e4722. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Zernecke, A.; Bidzhekov, K.; Noels, H.; Shagdarsuren, E.; Gan, L.; Denecke, B.; Hristov, M.; Köppel, T.; Jahantigh, M.N.; Lutgens, E.; et al. Delivery of MicroRNA-126 by Apoptotic Bodies Induces CXCL12-Dependent Vascular Protection. Sci. Signal 2009, 2, 81. [Google Scholar] [CrossRef] [PubMed]
  15. Turchinovich, A.; Weiz, L.; Langheinz, A.; Burwinkel, B. Characterization of extracellular circulating microRNA. Nucleic Acids Res. 2011, 39, 7223–7233. [Google Scholar] [CrossRef] [PubMed]
  16. Hessvik, N.P.; Llorente, A. Current knowledge on exosome biogenesis and release. Cell. Mol. Life Sci. 2018, 75, 193–208. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  17. Ståhl, A.L.; Johansson, K.; Mossberg, M.; Kahn, R.; Karpman, D. Exosomes and microvesicles in normal physiology, pathophysiology, and renal diseases. Pediatr. Nephrol. 2019, 34, 11–30. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  18. Tricarico, C.; Clancy, J.; D’Souza-Schorey, C. Biology and biogenesis of shed microvesicles. Small GTPases 2017, 8, 220–232. [Google Scholar] [CrossRef] [Green Version]
  19. Pegtel, D.M.; Cosmopoulos, K.; Thorley-Lawson, D.A.; Van Eijndhoven, M.A.J.; Hopmans, E.S.; Lindenberg, J.L.; De Gruijl, T.D.; Würdinger, T.; Middeldorp, J.M. Functional delivery of viral miRNAs via exosomes. Proc. Natl. Acad. Sci. USA 2010, 107, 6328–6333. [Google Scholar] [CrossRef] [Green Version]
  20. Stoorvogel, W. Functional transfer of microRNA by exosomes. Blood 2012, 119, 646–648. [Google Scholar] [CrossRef]
  21. Pfeffer, S.; Zavolan, M.; Grässer, F.A.; Chien, H.; Russo, J.J.; Ju, J.; John, B.; Enright, A.J.; Marks, D.; Sander, C.; et al. Identification of Virus-Encoded MicroRNAs. Science (80-) 2004, 304, 734–736. [Google Scholar] [CrossRef]
  22. Xia, T.; O’Hara, A.; Araujo, I.; Barreto, J.; Carvalho, E.; Sapucaia, J.B.; Ramos, J.C.; Luz, E.; Pedroso, C.; Manrique, M.; et al. EBV microRNAs in primary lymphomas and targeting of CXCL-11 by ebv-mir-BHRF1-3. Cancer Res. 2008, 68, 1436–1442. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Buck, A.H.; Coakley, G.; Simbari, F.; Mcsorley, H.J.; Quintana, J.F.; Le, T.; Kumar, S.; Abreu-goodger, C.; Lear, M.; Harcus, Y.; et al. Exosomes secreted by nematode parasites transfer small RNAs to mammalian cells and modulate innate immunity. Nat. Commun. 2014, 5, 5488. [Google Scholar] [CrossRef] [PubMed]
  24. Mause, S.F.; Weber, C. Microparticles: Protagonists of a novel communication network for intercellular information exchange. Circ. Res. 2010, 107, 1047–1057. [Google Scholar] [CrossRef]
  25. Vickers, K.C.; Palmisano, B.T.; Shoucri, B.M.; Shamburek, R.D.; Remaley, A.T. MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins. Nat. Cell Biol. 2011, 13, 423–435. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Niculescu, L.S.; Simionescu, N.; Sanda, G.M.; Carnuta, M.G.; Stancu, C.S.; Popescu, A.C.; Popescu, M.R.; Vlad, A.; Dimulescu, D.R.; Simionescu, M.; et al. MiR-486 and miR-92a Identified in Circulating HDL Discriminate between Stable and Vulnerable Coronary Artery Disease Patients. PLoS ONE 2015, 10, e0140958. [Google Scholar] [CrossRef] [PubMed]
  27. Auber, M.; Fröhlich, D.; Drechsel, O.; Karaulanov, E.; Krämer-Albers, E.M. Serum-free media supplements carry miRNAs that co-purify with extracellular vesicles. J. Extracell. Vesicles 2019, 8, 1656042. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Jeppesen, D.K.; Fenix, A.M.; Franklin, J.L.; Higginbotham, J.N.; Zhang, Q.; Zimmerman, L.J.; Liebler, D.C.; Ping, J.; Liu, Q.; Evans, R.; et al. Reassessment of Exosome Composition. Cell 2019, 177, 428–445. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  29. Albanese, M.; Chen, Y.-F.A.; Hüls, C.; Gärtner, K.; Tagawa, T.; Keppler, O.T.; Göbel, C.; Zeidler, R.; Hammerschmidt, W. Micro RNAs Are Minor Constituents of Extracellular Vesicles and Are Hardly Delivered to Target Cells. Available online: https://www.biorxiv.org/content/10.1101/2020.05.20.106393v1.abstract (accessed on 26 July 2020).
  30. O’Brien, K.; Breyne, K.; Ughetto, S.; Laurent, L.C.; Breakefield, X.O. RNA delivery by extracellular vesicles in mammalian cells and its applications. Nat. Rev. Mol. Cell Biol. 2020, 21, 585–606. [Google Scholar] [CrossRef]
  31. Park, C.Y.; Choi, Y.S.; McManus, M.T. Analysis of microRNA knockouts in mice. Hum. Mol. Genet. 2010, 19, 169–175. [Google Scholar] [CrossRef] [Green Version]
  32. Bernstein, E.; Kim, S.Y.; Carmell, M.A.; Murchison, E.P.; Alcorn, H.; Li, M.Z.; Mills, A.A.; Elledge, S.J.; Anderson, K.V.; Hannon, G.J. Dicer is essential for mouse development. Nat. Genet. 2003, 35, 215–217. [Google Scholar] [CrossRef]
  33. London, L. Motivator and Barriers to Latina’s Participation in Clinical Trials. Contemp. C 2015, 40, 3–14. [Google Scholar] [CrossRef] [Green Version]
  34. Van Rooij, E.; Quiat, D.; Johnson, B.A.; Sutherland, L.B.; Qi, X.; Richardson, J.A.; Kelm, R.J.; Olson, E.N. Expression and Muscle Performance. Dev. Cell 2009, 17, 662–673. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Van Rooij, E.; Sutherland, L.B.; Qi, X.; Richardson, J.A.; Hill, J.; Olson, E.N. Control of stress-dependent cardiac growth and gene expression by a microRNA. Science 2007, 316, 575–579. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Xin, M.; Small, E.M.; Sutherland, L.B.; Qi, X.; McAnally, J.; Plato, C.F.; Richardson, J.A.; Bassel-Duby, R.; Olson, E.N. MicroRNAs miR-143 and miR-145 modulate cytoskeletal dynamics and responsiveness of smooth muscle cells to injury. Genes Dev. 2009, 23, 2166–2178. [Google Scholar] [CrossRef] [Green Version]
  37. Zhao, W.; Zhao, S.-P.; Zhao, Y.-H. MicroRNA-143/-145 in Cardiovascular Diseases. Biomed. Res. Int. 2015, 2015, 531740. [Google Scholar] [CrossRef]
  38. Bang, C.; Batkai, S.; Dangwal, S.; Gupta, S.K.; Foinquinos, A.; Holzmann, A.; Just, A.; Remke, J.; Zimmer, K.; Zeug, A.; et al. Cardiac fibroblast-derived microRNA passenger strand-enriched exosomes mediate cardiomyocyte hypertrophy. J. Clin. Invest. 2014, 124, 2136–2146. [Google Scholar] [CrossRef]
  39. Fu, F.; Jiang, W.; Zhou, L. Circulating Exosomal miR-17-5p and miR-92a-3p Predict Pathologic Stage and Grade of Colorectal Cancer. Transl. Oncol. 2018, 11, 221–232. [Google Scholar] [CrossRef]
  40. Liu, T.; Zhang, Q.; Zhang, J.; Li, C.; Miao, Y.R.; Lei, Q.; Li, Q.; Guo, A.Y. EVmiRNA: A database of miRNA profiling in extracellular vesicles. Nucleic Acids Res. 2019, 47, 89–93. [Google Scholar] [CrossRef] [Green Version]
  41. Yang, S.Y.; Wang, Y.Q.; Gao, H.M.; Wang, B.; He, Q. The clinical value of circulating MIR-99a in plasma of patients with acute myocardial infarction. Eur. Rev. Med. Pharmacol. Sci. 2016, 20, 5193–5197. [Google Scholar]
  42. Schulte, C.; Barwari, T.; Joshi, A.; Theofilatos, K.; Zampetaki, A.; Barallobre-Barreiro, J.; Singh, B.; Sörensen, N.A.; Neumann, J.T.; Zeller, T.; et al. Comparative analysis of circulating noncoding rnas versus protein biomarkers in the detection of myocardial injury. Circ. Res. 2019, 125, 328–340. [Google Scholar] [CrossRef]
  43. Mendell, J.T.; Olson, E.N. MicroRNAs in stress signaling and human disease. Cell 2012, 148, 1172–1187. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Bonneau, E.; Neveu, B.; Kostantin, E.; Tsongalis, G.J.; De Guire, V. How close are miRNAs from clinical practice? A perspective on the diagnostic and therapeutic market. Electron. J. Int. Fed. Clin. Chem. Lab. Med. 2019, 30, 114–127. [Google Scholar]
  45. Bajan, S.; Hutvagner, G. RNA-Based Therapeutics: From Antisense Oligonucleotides to miRNAs. Cells 2020, 9, 137. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. Mitra, S.; Deshmukh, A.; Sachdeva, R.; Lu, J.; Mehta, J.L. Oxidized Low-Density Lipoprotein and Atherosclerosis Implications in Antioxidant Therapy. Am. J. Med. Sci. 2011, 342, 135–142. [Google Scholar] [CrossRef] [PubMed]
  47. Linton, M.F.; Yancey, P.G.; Davies, S.S.; Jerome, W.G.; Linton, E.F.; Vickers, K.C. The Role of Lipids and Lipoproteins in Atherosclerosis; MDText: South Dartmouth, MA, USA, 2000. [Google Scholar]
  48. Bairey Merz, C.N.; Pepine, C.J.; Walsh, M.N.; Fleg, J.L.; Camici, P.G.; Chilian, W.M.; Clayton, J.A.; Cooper, L.S.; Crea, F.; Di Carli, M.; et al. Ischemia and No Obstructive Coronary Artery Disease (INOCA). Circulation 2017, 135, 1075–1092. [Google Scholar] [CrossRef] [PubMed]
  49. Tse, K.; Tse, H.; Sidney, J.; Sette, A.; Ley, K. T cells in atherosclerosis. Int. Immunol. 2013, 25, 615–622. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  50. Golledge, J.; Norman, P.E. Atherosclerosis and abdominal aortic aneurysm: Cause, response, or common risk factors? Arterioscler. Thromb. Vasc. Biol. 2010, 30, 1075–1077. [Google Scholar] [CrossRef] [Green Version]
  51. Koroleva, I.A.; Nazarenko, M.S.; Kucher, A.N. Role of microRNA in development of instability of atherosclerotic plaques. Biochemistry 2017, 82, 1380–1390. [Google Scholar] [CrossRef]
  52. Sharma, S.; Jackson, P.G.; Makan, J. Cardiac troponins. J. Clin. Pathol. 2004, 57, 1025–1026. [Google Scholar] [CrossRef] [Green Version]
  53. Omland, T.; de Lemos, J.A.; Sabatine, M.S.; Christophi, C.A.; Rice, M.M.; Jablonski, K.A.; Tjora, S.; Domanski, M.J.; Gersh, B.J.; Rouleau, J.L.; et al. A sensitive cardiac troponin T assay in stable coronary artery disease. N. Engl. J. Med. 2009, 361, 2538–2547. [Google Scholar] [CrossRef] [Green Version]
  54. Speidl, W.S.; Graf, S.; Hornykewycz, S.; Nikfardjam, M.; Niessner, A.; Zorn, G.; Wojta, J.; Huber, K. High-sensitivity C-reactive protein in the prediction of coronary events in patients with premature coronary artery disease. Am. Heart J. 2002, 144, 449–455. [Google Scholar] [CrossRef]
  55. Sara, J.D.S.; Prasad, M.; Zhang, M.; Lennon, R.J.; Herrmann, J.; Lerman, L.O.; Lerman, A. High-sensitivity C-reactive protein is an independent marker of abnormal coronary vasoreactivity in patients with non-obstructive coronary artery disease. Am. Heart J. 2017, 190, 1–11. [Google Scholar] [CrossRef] [PubMed]
  56. Tahhan, A.S.; Sandesara, P.; Hayek, S.S.; Hammadah, M.; Alkhoder, A.; Kelli, H.M.; Topel, M.; O’Neal, W.T.; Ghasemzadeh, N.; Ko, Y.A.; et al. High-sensitivity troponin I levels and coronary artery disease severity, progression, and long-term outcomes. J. Am. Heart Assoc. 2018, 7, e007914. [Google Scholar] [CrossRef] [Green Version]
  57. Zimmerli, L.U.; Schiffer, E.; Zürbig, P.; Good, D.M.; Kellmann, M.; Mouls, L.; Pitt, A.R.; Coon, J.J.; Schmieder, R.E.; Peter, K.H.; et al. Urinary proteomic biomarkers in coronary artery disease. Mol. Cell. Proteomics 2008, 7, 290–298. [Google Scholar] [CrossRef] [Green Version]
  58. Ibrahim, N.E.; Januzzi, J.L.; Magaret, C.A.; Gaggin, H.K.; Rhyne, R.F.; Gandhi, P.U.; Kelly, N.; Simon, M.L.; Motiwala, S.R.; Belcher, A.M.; et al. A Clinical and Biomarker Scoring System to Predict the Presence of Obstructive Coronary Artery Disease. J. Am. Coll. Cardiol. 2017, 69, 1147–1156. [Google Scholar] [CrossRef] [PubMed]
  59. D’Alessandra, Y.; Devanna, P.; Limana, F.; Straino, S.; Di Carlo, A.; Brambilla, P.G.; Rubino, M.; Carena, M.C.; Spazzafumo, L.; De Simone, M.; et al. Circulating microRNAs are new and sensitive biomarkers of myocardial infarction. Eur. Heart J. 2010, 31, 2765–2773. [Google Scholar] [CrossRef] [Green Version]
  60. Condorelli, G.; Latronico, M.V.G.; Dorn, G.W. MicroRNAs in heart disease: Putative novel therapeutic targets? Eur. Heart J. 2010, 31, 649–658. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  61. Fichtlscherer, S.; De Rosa, S.; Fox, H.; Schwietz, T.; Fischer, A.; Liebetrau, C.; Weber, M.; Hamm, C.W.; Röxe, T.; Müller-Ardogan, M.; et al. Circulating microRNAs in patients with coronary artery disease. Circ. Res. 2010, 107, 677–684. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  62. Raitoharju, E.; Lyytikäinen, L.-P.; Levula, M.; Oksala, N.; Mennander, A.; Tarkka, M.; Klopp, N.; Illig, T.; Kähönen, M.; Karhunen, P.J.; et al. miR-21, miR-210, miR-34a, and miR-146a/b are up-regulated in human atherosclerotic plaques in the Tampere Vascular Study. Atherosclerosis 2011, 219, 211–217. [Google Scholar] [CrossRef]
  63. Raitoharju, E.; Oksala, N.; Lehtimäki, T. MicroRNAs in the atherosclerotic plaque. Clin. Chem. 2013, 59, 1708–1721. [Google Scholar] [CrossRef] [Green Version]
  64. Chan, M.C.; Hilyard, A.C.; Wu, C.; Davis, B.N.; Hill, N.S.; Lal, A.; Lieberman, J.; Lagna, G.; Hata, A. Molecular basis for antagonism between PDGF and the TGF b family of signalling pathways by control of miR-24 expression. EMBO J. 2009, 29, 559–573. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  65. Davis, B.N.; Hilyard, A.C.; Nguyen, P.H.; Lagna, G.; Hata, A. Induction of MicroRNA-221 by platelet-derived growth factor signaling is critical for modulation of vascular smooth muscle phenotype. J. Biol. Chem. 2009, 284, 3728–3738. [Google Scholar] [CrossRef] [Green Version]
  66. Liu, X.; Cheng, Y.; Chen, X.; Yang, J.; Xu, L.; Zhang, C. MicroRNA-31 regulated by the extracellular regulated kinase is involved in vascular smooth muscle cell growth via large tumor suppressor homolog 2. J. Biol. Chem. 2011, 286, 42371–42380. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  67. Zhang, Y.; Wang, Y.; Wang, X.; Zhang, Y.; Eisner, G.M.; Asico, L.D.; Jose, P.A.; Zeng, C. Insulin promotes vascular smooth muscle cell proliferation via microRNA-208-mediated downregulation of p21. J. Hypertens. 2011, 152, 66. [Google Scholar] [CrossRef]
  68. Leeper, N.J.; Raiesdana, A.; Kojima, Y.; Chun, H.J.; Azuma, J.; Maegdefessel, L.; Kundu, R.K.; Quertermous, T.; Tsao, P.S.; Spin, J.M. MicroRNA-26a is a novel regulator of vascular smooth muscle cell function. J. Cell. Physiol. 2011, 226, 1035–1043. [Google Scholar] [CrossRef] [Green Version]
  69. Hutcheson, R.; Chaplin, J.; Hutcheson, B.; Borthwick, F.; Proctor, S.; Gebb, S.; Jadhav, R.; Smith, E.; Russell, J.C.; Rocic, P. miR-21 normalizes vascular smooth muscle proliferation and improves coronary collateral growth in metabolic syndrome. FASEB J. 2014, 28, 4088–4099. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  70. Zhou, J.; Shao, G.; Chen, X.; Yang, X.; Huang, X.; Peng, P.; Ba, Y. miRNA 206 and miRNA 574-5p are highly expression in coronary artery disease. Biosci. Rep. 2016, 36, e00295. [Google Scholar] [CrossRef] [PubMed]
  71. Li, H.Y.; Zhao, X.; Liu, Y.Z.; Meng, Z.; Wang, D.; Yang, F.; Shi, Q.W. Plasma MicroRNA-126-5p is Associated with the Complexity and Severity of Coronary Artery Disease in Patients with Stable Angina Pectoris. Cell. Physiol. Biochem. 2016, 39, 837–846. [Google Scholar] [CrossRef]
  72. Wang, H.W.; Lo, H.H.; Chiu, Y.L.; Chang, S.J.; Huang, P.H.; Liao, K.H.; Tasi, C.F.; Wu, C.H.; Tsai, T.N.; Cheng, C.C.; et al. Dysregulated miR-361-5p/VEGF axis in the plasma and endothelial progenitor cells of patients with coronary artery disease. PLoS ONE 2014, 9, e98070. [Google Scholar] [CrossRef] [Green Version]
  73. Wang, M.; Ji, Y.; Cai, S.; Ding, W. MiR-206 suppresses the progression of coronary artery disease by modulating vascular endothelial growth factor (VEGF) expression. Med. Sci. Monit. 2016, 22, 5011–5020. [Google Scholar] [CrossRef] [Green Version]
  74. Adachi, T.; Nakanishi, M.; Otsuka, Y.; Nishimura, K.; Hirokawa, G.; Goto, Y.; Nonogi, H.; Iwai, N. Plasma microRNA 499 as a biomarker of acute myocardial infarction. Clin. Chem. 2010, 56, 1183–1185. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  75. Corsten, M.F.; Dennert, R.; Jochems, S.; Kuznetsova, T.; Devaux, Y.; Hofstra, L.; Wagner, D.R.; Staessen, J.A.; Heymans, S.; Schroen, B. Circulating MicroRNA-208b and MicroRNA-499 reflect myocardial damage in cardiovascular disease. Circ. Cardiovasc. Genet. 2010, 3, 499–506. [Google Scholar] [CrossRef] [PubMed]
  76. Ji, X.; Takahashi, R.; Hiura, Y.; Hirokawa, G.; Fukushima, Y.; Iwai, N. Plasma miR-208 as a biomarker of myocardial injury. Clin. Chem. 2009, 55, 1944–1949. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  77. Ai, J.; Zhang, R.; Li, Y.; Pu, J.; Lu, Y.; Jiao, J.; Li, K.; Yu, B.; Li, Z.; Wang, R.; et al. Circulating microRNA-1 as a potential novel biomarker for acute myocardial infarction. Biochem. Biophys. Res. Commun. 2010, 391, 73–77. [Google Scholar] [CrossRef] [PubMed]
  78. Hoekstra, M.; van der Lans, C.A.C.; Halvorsen, B.; Gullestad, L.; Kuiper, J.; Aukrust, P.; van Berkel, T.J.C.; Biessen, E.A.L. The peripheral blood mononuclear cell microRNA signature of coronary artery disease. Biochem. Biophys. Res. Commun. 2010, 394, 792–797. [Google Scholar] [CrossRef]
  79. Takahashi, Y.; Satoh, M.; Minami, Y.; Tabuchi, T.; Itoh, T.; Nakamura, M. Expression of miR-146a/b is associated with the Toll-like receptor 4 signal in coronary artery disease: Effect of renin-angiotensin system blockade and statins on miRNA-146a/b and Toll-like receptor 4 levels. Clin. Sci. 2010, 119, 395–405. [Google Scholar] [CrossRef] [Green Version]
  80. Satoh, M.; Tabuchi, T.; Minami, Y.; Takahashi, Y.; Itoh, T.; Nakamura, M. Expression of let-7i is associated with Toll-like receptor 4 signal in coronary artery disease: Effect of statins on let-7i and Toll-like receptor 4 signal. Immunobiology 2012, 217, 533–539. [Google Scholar] [CrossRef]
  81. Willeit, P.; Zampetaki, A.; Dudek, K.; Kaudewitz, D.; King, A.; Kirkby, N.S.; Crosby-Nwaobi, R.; Prokopi, M.; Drozdov, I.; Langley, S.R.; et al. Circulating MicroRNAs as novel biomarkers for platelet activation. Circ. Res. 2013, 112, 595–600. [Google Scholar] [CrossRef] [Green Version]
  82. Das, A.; Samidurai, A.; Salloum, F.N. Deciphering Non-coding RNAs in Cardiovascular Health and Disease. Front. Cardiovasc. Med. 2018, 5, 73. [Google Scholar] [CrossRef] [Green Version]
  83. Zhang, Y.; Zhang, L.; Wang, Y.; Ding, H.; Xue, S.; Qi, H.; Li, P. MicroRNAs or long noncoding RNAs in diagnosis and prognosis of coronary artery disease. Aging Dis. 2019, 10, 353–366. [Google Scholar] [CrossRef] [Green Version]
  84. Elmén, J.; Lindow, M.; Silahtaroglu, A.; Bak, M.; Christensen, M.; Lind-Thomsen, A.; Hedtjärn, M.; Hansen, J.B.; Hansen, H.F.; Straarup, E.M.; et al. Antagonism of microRNA-122 in mice by systemically administered LNA-antimiR leads to up-regulation of a large set of predicted target mRNAs in the liver. Nucleic Acids Res. 2008, 36, 1153–1162. [Google Scholar] [CrossRef] [Green Version]
  85. Dong, J.; Liang, Y.Z.; Zhang, J.; Wu, L.J.; Wang, S.; Hua, Q.; Yan, Y.X. Potential role of lipometabolism-related microRNAs in peripheral blood mononuclear cells as biomarkers for coronary artery disease. J. Atheroscler. Thromb. 2017, 24, 430–441. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  86. Moore, K.J.; Rayner, K.J.; Suárez, Y.; Fernández-Hernando, C. The role of microRNAs in cholesterol efflux and hepatic lipid metabolism. Annu. Rev. Nutr. 2011, 31, 49–63. [Google Scholar] [CrossRef] [Green Version]
  87. Marquart, T.J.; Allen, R.M.; Ory, D.S.; Baldán, Á. miR-33 links SREBP-2 induction to repression of sterol transporters. Proc. Natl. Acad. Sci. USA 2010, 107, 12228–12232. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  88. Iliopoulos, D.; Drosatos, K.; Hiyama, Y.; Goldberg, I.J.; Zannis, V.I. MicroRNA-370 controls the expression of MicroRNA-122 and Cpt1α and affects lipid metabolism. J. Lipid Res. 2010, 51, 1513–1523. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  89. Faccini, J.; Ruidavets, J.B.; Cordelier, P.; Martins, F.; Maoret, J.J.; Bongard, V.; Ferrières, J.; Roncalli, J.; Elbaz, M.; Vindis, C. Circulating MIR-155, MIR-145 and let-7c as diagnostic biomarkers of the coronary artery disease. Sci. Rep. 2017, 7, 42916. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  90. Li, X.; Kong, D.; Chen, H.; Liu, S.; Hu, H.; Wu, T.; Wang, J.; Chen, W.; Ning, Y.; Li, Y.; et al. MiR-155 acts as an anti-inflammatory factor in atherosclerosis-Associated foam cell formation by repressing calcium-regulated heat stable protein 1. Sci. Rep. 2016, 6, 21789. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  91. Cheng, H.S.; Sivachandran, N.; Lau, A.; Boudreau, E.; Zhao, J.L.; Baltimore, D.; Delgado-Olguin, P.; Cybulsky, M.I.; Fish, J.E. MicroRNA-146 represses endothelial activation by inhibiting pro-inflammatory pathways. EMBO Mol. Med. 2013, 5, 949–966. [Google Scholar] [CrossRef]
  92. Huang, R.S.; Gamazon, E.R.; Ziliak, D.; Wen, Y.; Im, H.K.; Zhang, W.; Wing, C.; Duan, S.; Bleibel, W.K.; Cox, N.J.; et al. Population differences in microRNA expression and biological implications. RNA Biol. 2011, 8, 692–701. [Google Scholar] [CrossRef] [Green Version]
  93. Rawlings-Goss, R.A.; Campbell, M.C.; Tishkoff, S.A. Global population-specific variation in miRNA associated with cancer risk and clinical biomarkers. BMC Med. Genomics 2014, 7, 53. [Google Scholar] [CrossRef] [Green Version]
  94. Meder, B.; Backes, C.; Haas, J.; Leidinger, P.; Stähler, C.; Großmann, T.; Vogel, B.; Frese, K.; Giannitsis, E.; Katus, H.A.; et al. Influence of the confounding factors age and sex on microRNA profiles from peripheral blood. Clin. Chem. 2014, 60, 1200–1208. [Google Scholar] [CrossRef] [PubMed]
  95. Simon, L.M.; Edelstein, L.C.; Nagalla, S.; Woodley, A.B.; Chen, E.S.; Kong, X.; Ma, L.; Fortina, P.; Kunapuli, S.; Holinstat, M.; et al. Human platelet microRNA-mRNA networks associated with age and gender revealed by integrated plateletomics. Blood 2014, 123, 37–45. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  96. Sayed, A.S.M.; Xia, K.; Li, F.; Deng, X.; Salma, U.; Li, T.; Deng, H.; Yang, D.; Haoyang, Z.; Yang, T.L.; et al. The diagnostic value of circulating microRNAs for middle-aged (40–60-year-old) coronary artery disease patients. Clinics 2015, 70, 257–263. [Google Scholar] [CrossRef]
  97. Olivieri, F.; Bonafè, M.; Spazzafumo, L.; Gobbi, M.; Prattichizzo, F.; Recchioni, R.; Marcheselli, F.; La Sala, L.; Galeazzi, R.; Rippo, M.R.; et al. Age- and glycemia-related miR-126-3p levels in plasma and endothelial cells. Aging 2014, 6, 771–786. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  98. Ultimo, S.; Zauli, G.; Martelli, A.M.; Vitale, M.; McCubrey, J.A.; Capitani, S.; Neri, L.M. Cardiovascular disease-related miRNAs expression: Potential role as biomarkers and effects of training exercise. Oncotarget 2018, 9, 17238–17254. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  99. Gupta, S.K.; Foinquinos, A.; Thum, S.; Remke, J.; Zimmer, K.; Bauters, C.; de Groote, P.; Boon, R.A.; de Windt, L.J.; Preissl, S.; et al. Preclinical Development of a MicroRNA-Based Therapy for Elderly Patients With Myocardial Infarction. J. Am. Coll. Cardiol. 2016, 68, 1557–1571. [Google Scholar] [CrossRef] [Green Version]
  100. De Lucia, C.; Komici, K.; Borghetti, G.; Femminella, G.D.; Bencivenga, L.; Cannavo, A.; Corbi, G.; Ferrara, N.; Houser, S.R.; Koch, W.J.; et al. MicroRNA in cardiovascular aging and age-related cardiovascular diseases. Front. Med. Lausanne 2017, 4, 74. [Google Scholar] [CrossRef] [Green Version]
  101. Van Almen, G.C.; Verhesen, W.; van Leeuwen, R.E.W.; van de Vrie, M.; Eurlings, C.; Schellings, M.W.M.; Swinnen, M.; Cleutjens, J.P.M.; van Zandvoort, M.A.M.J.; Heymans, S.; et al. MicroRNA-18 and microRNA-19 regulate CTGF and TSP-1 expression in age-related heart failure. Aging Cell 2011, 10, 769–779. [Google Scholar] [CrossRef] [Green Version]
  102. Zhou, M.; Cai, J.; Tang, Y.; Zhao, Q. MiR-17-92 cluster is a novel regulatory gene of cardiac ischemic/reperfusion injury. Med. Hypotheses 2013, 81, 108–110. [Google Scholar] [CrossRef]
  103. Zhong, Z.; Hou, J.; Zhang, Q.; Zhong, W.; Li, B.; Li, C.; Liu, Z.; Yang, M.; Zhao, P. Circulating microRNA expression profiling and bioinformatics analysis of dysregulated microRNAs of patients with coronary artery disease. Medicine 2018, 97, e11428. [Google Scholar] [CrossRef]
  104. Wang, K.; Yuan, Y.; Cho, J.H.; McClarty, S.; Baxter, D.; Galas, D.J. Comparing the MicroRNA spectrum between serum and plasma. PLoS ONE 2012, 7, e41561. [Google Scholar] [CrossRef] [PubMed]
  105. Blondal, T.; Jensby Nielsen, S.; Baker, A.; Andreasen, D.; Mouritzen, P.; Wrang Teilum, M.; Dahlsveen, I.K. Assessing sample and miRNA profile quality in serum and plasma or other biofluids. Methods 2013, 59, 1–6. [Google Scholar] [CrossRef] [PubMed]
  106. Kroh, E.M.; Parkin, R.K.; Mitchell, P.S.; Tewari, M. Analysis of circulating microRNA biomarkers in plasma and serum using quantitative reverse transcription-PCR (qRT-PCR). Methods 2010, 50, 298–301. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  107. Sunderland, N.; Skroblin, P.; Barwari, T.; Huntley, R.P.; Lu, R.; Joshi, A.; Lovering, R.C.; Mayr, M. MicroRNA Biomarkers and Platelet Reactivity: The Clot Thickens. Circ. Res. 2017, 120, 418–435. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  108. Peirson, S.N.; Butler, J.N. RNA Extraction From Mammalian Tissues. In Methods in Molecular Biology; Rosato, E., Ed.; Humana Press: Totowa, NJ, USA, 2007; pp. 315–327. ISBN 978-1-59745-257-1. [Google Scholar]
  109. Glinge, C.; Clauss, S.; Boddum, K.; Jabbari, R.; Jabbari, J.; Risgaard, B.; Tomsits, P.; Hildebrand, B.; Kääb, S.; Wakili, R.; et al. Stability of Circulating Blood-Based MicroRNAs—Pre-Analytic Methodological Considerations. PLoS ONE 2017, 12, e0167969. [Google Scholar] [CrossRef]
  110. Mayeux, R. Biomarkers: Potential Uses and Limitations. NeuroRx 2004, 1, 182–188. [Google Scholar] [CrossRef]
  111. Jansen, F.; Yang, X.; Proebsting, S.; Hoelscher, M.; Przybilla, D.; Baumann, K.; Schmitz, T.; Dolf, A.; Endl, E.; Franklin, B.S.; et al. MicroRNA expression in circulating microvesicles predicts cardiovascular events in patients with coronary artery disease. J. Am. Heart Assoc. 2014, 3, e001249. [Google Scholar] [CrossRef] [Green Version]
  112. Calin, G.A.; Dumitru, C.D.; Shimizu, M.; Bichi, R.; Zupo, S.; Noch, E.; Aldler, H.; Rattan, S.; Keating, M.; Rai, K.; et al. Frequent deletions and down-regulation of micro-RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proc. Natl. Acad. Sci. USA 2002, 99, 15524–15529. [Google Scholar] [CrossRef] [Green Version]
  113. Hayes, J.; Peruzzi, P.P.; Lawler, S. MicroRNAs in cancer: Biomarkers, functions and therapy. Trends Mol. Med. 2014, 20, 460–469. [Google Scholar] [CrossRef]
  114. Hongyan, Z.; Guo-chang, F. Extracellular/circulating microRNAs and their potential role in cardiovascular disease. Am. J. Cardiovasc. Dis. 2011, 1, 138–149. [Google Scholar]
  115. Trzybulska, D.; Vergadi, E.; Tsatsanis, C. MiRNA and other non-coding RNAs as promising diagnostic markers. Electron. J. Int. Fed. Clin. Chem. Lab. Med. 2018, 29, 221–226. [Google Scholar]
  116. Pogribny, I.P. MicroRNAs as biomarkers for clinical studies. Exp. Biol. Med. 2018, 243, 283–290. [Google Scholar] [CrossRef] [PubMed]
  117. Kreth, S.; Hübner, M.; Hinske, L.C. MicroRNAs as clinical biomarkers and therapeutic tools in perioperative medicine. Anesth. Analg. 2018, 126, 670–681. [Google Scholar] [CrossRef]
  118. Wang, J.; Yan, Y.; Song, D.; Liu, B. Reduced Plasma miR-146a is a Predictor of Poor Coronary Collateral Circulation in Patients with Coronary Artery Disease. Biomed Res. Int. 2016, 2016, 4285942. [Google Scholar] [CrossRef] [PubMed]
  119. Li, S.; Lee, C.; Song, J.; Lu, C.; Liu, J.; Cui, Y.; Liang, H.; Cao, C.; Zhang, F.; Chen, H. Circulating microRNAs as potential biomarkers for coronary plaque rupture. Oncotarget 2017, 8, 48145–48156. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  120. Li, X.D.; Yang, Y.J.; Wang, L.Y.; Qiao, S.B.; Lu, X.F.; Wu, Y.J.; Xu, B.; Li, H.F.; Gu, D.F. Elevated plasma miRNA-122, -140-3p, -720, -2861, and -3149 during early period of acute coronary syndrome are derived from peripheral blood mononuclear cells. PLoS ONE 2017, 12, e0184256. [Google Scholar] [CrossRef] [Green Version]
  121. Jansen, F.; Schäfer, L.; Wang, H.; Schmitz, T.; Flender, A.; Schueler, R.; Hammerstingl, C.; Nickenig, G.; Sinning, J.; Werner, N. Kinetics of Circulating MicroRNAs in Response to Cardiac Stress in Patients With Coronary Artery Disease. J. Am. Heart Assoc. 2017, 6, e005270. [Google Scholar] [CrossRef]
  122. Soeki, T.; Yamaguchi, K.; Niki, T.; Uematsu, E.; Bando, S.; Matsuura, T.; Ise, T.; Kusunose, K.; Hotchi, J.; Tobiume, T.; et al. Plasma microRNA-100 is associated with coronary plaque vulnerability. Circ. J. 2015, 79, 413–418. [Google Scholar] [CrossRef] [Green Version]
  123. Liu, C.Z.; Zhong, Q.; Huang, Y.Q. Elevated plasma miR-29a levels are associated with increased carotid intima-media thickness in atherosclerosis patients. Tohoku J. Exp. Med. 2017, 241, 183–188. [Google Scholar] [CrossRef] [Green Version]
  124. Wang, X.; Lian, Y.; Wen, X.; Guo, J.; Wang, Z.; Jiang, S.; Hu, Y. Expression of miR-126 and its potential function in coronary artery disease. Afr. Health Sci. 2017, 17, 474–480. [Google Scholar] [CrossRef] [Green Version]
  125. Al-Kafaji, G.; Al-Mahroos, G.; Abdulla Al-Muhtaresh, H.; Sabry, M.A.; Abdul Razzak, R.; Salem, A.H. Circulating endothelium-enriched microRNA-126 as a potential biomarker for coronary artery disease in type 2 diabetes mellitus patients. Biomarkers 2017, 22, 268–278. [Google Scholar] [CrossRef] [PubMed]
  126. Al-Muhtaresh, H.A.; Salem, A.H.; Al-Kafaji, G. Upregulation of Circulating Cardiomyocyte-Enriched miR-1 and miR-133 Associate with the Risk of Coronary Artery Disease in Type 2 Diabetes Patients and Serve as Potential Biomarkers. J. Cardiovasc. Transl. Res. 2019, 12, 347–357. [Google Scholar] [CrossRef]
  127. Boon, R.A. Non-coding RNAs in cardiovascular health and disease. Non Coding RNA Res. 2018, 3, 99. [Google Scholar] [CrossRef]
  128. Wang, H.W.; Huang, T.S.; Lo, H.H.; Huang, P.H.; Lin, C.C.; Chang, S.J.; Liao, K.H.; Tsai, C.H.; Chan, C.H.; Tsai, C.F.; et al. Deficiency of the MicroRNA-31-MicroRNA-720 pathway in the plasma and endothelial progenitor cells from patients with coronary artery disease. Arterioscler. Thromb. Vasc. Biol. 2014, 34, 857–869. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  129. Zhang, Y.; Li, H.-H.; Yang, R.; Yang, B.-J.; Gao, Z.-Y. Association between circulating microRNA-208a and severity of coronary heart disease. Scand. J. Clin. Lab. Investig. 2017, 77, 379–384. [Google Scholar] [CrossRef] [PubMed]
  130. Han, H.; Qu, G.; Han, C.; Wang, Y.; Sun, T.; Li, F.; Wang, J.; Luo, S. MiR-34a, miR-21 and miR-23a as potential biomarkers for coronary artery disease: A pilot microarray study and confirmation in a 32 patient cohort. Exp. Mol. Med. 2015, 47, 138. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  131. Gao, H.; Guddeti, R.R.; Matsuzawa, Y.; Liu, L.P.; Su, L.X.; Guo, D.; Nie, S.P.; Du, J.; Zhang, M. Plasma levels of microRNA-145 are associated with severity of coronary artery disease. PLoS ONE 2015, 10, e0123477. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  132. Ren, J.; Zhang, J.; Xu, N.; Han, G.; Geng, Q.; Song, J.; Li, S.; Zhao, J.; Chen, H. Signature of circulating MicroRNAs As potential biomarkers in vulnerable coronary artery disease. PLoS ONE 2013, 8, e80738. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  133. Chen, J.; Xu, L.; Hu, Q.; Yang, S.; Zhang, B.; Jiang, H. MiR-17-5p as circulating biomarkers for the severity of coronary atherosclerosis in coronary artery disease. Int. J. Cardiol. 2015, 197, 123–124. [Google Scholar] [CrossRef] [PubMed]
  134. Lin, B.; Feng, D.-G.; Wang, F.; Wang, J.-X.; Xu, C.-G.; Zhao, H.; Cheng, Z.-Y. MiR-365 participates in coronary atherosclerosis through regulating IL-6. Eur. Rev. Med. Pharmacol. Sci. 2016, 20, 5186–5192. [Google Scholar]
  135. Cipollone, F.; Felicioni, L.; Sarzani, R.; Ucchino, S.; Spigonardo, F.; Mandolini, C.; Malatesta, S.; Bucci, M.; Mammarella, C.; Santovito, D.; et al. A unique MicroRNA signature associated with plaque instability in humans. Stroke 2011, 42, 2556–2563. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  136. Kumar, S.; Kim, C.W.; Simmons, R.D.; Jo, H. Role of flow-sensitive microRNAs in endothelial dysfunction and atherosclerosis—“Mechanosensitive Athero-miRs”. Arter. Thromb Vasc Biol. 2014, 22, 313–333. [Google Scholar] [CrossRef] [Green Version]
  137. Tian, F.J.; An, L.N.; Wang, G.K.; Zhu, J.Q.; Li, Q.; Zhang, Y.Y.; Zeng, A.; Zou, J.; Zhu, R.F.; Han, X.S.; et al. Elevated microRNA-155 promotes foam cell formation by targeting HBP1 in atherogenesis. Cardiovasc. Res. 2014, 103, 100–110. [Google Scholar] [CrossRef]
  138. Horie, T.; Baba, O.; Kuwabara, Y.; Chujo, Y.; Watanabe, S.; Kinoshita, M.; Horiguchi, M.; Nakamura, T.; Chonabayashi, K.; Hishizawa, M.; et al. MicroRNA-33 deficiency reduces the progression of atherosclerotic plaque in ApoE−/− mice. J. Am. Heart Assoc. 2012, 1, e003376. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  139. Fang, Y.; Shi, C.; Manduchi, E.; Civelek, M.; Davies, P.F. MicroRNA-10a regulation of proinflammatory phenotype in athero-susceptible endothelium in vivo and in vitro. Proc. Natl. Acad. Sci. USA 2010, 107, 13450–13455. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  140. Shan, Z.; Qin, S.; Li, W.; Wu, W.; Yang, J.; Chu, M.; Li, X.; Huo, Y.; Schaer, G.L.; Wang, S.; et al. An Endocrine Genetic Signal Between Blood Cells and Vascular Smooth Muscle Cells: Role of MicroRNA-223 in Smooth Muscle Function and Atherogenesis. J. Am. Coll. Cardiol. 2015, 65, 2526–2537. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  141. Bidzhekov, K.; Gan, L.; Denecke, B.; Rostalsky, A.; Hristov, M.; Koeppel, T.A.; Zernecke, A.; Weber, C. microRNA expression signatures and parallels between monocyte subsets and atherosclerotic plaque in humans. Thromb. Haemost. 2012, 107, 619–625. [Google Scholar] [CrossRef] [PubMed]
  142. Jansen, F.; Yang, X.; Hoelscher, M.; Cattelan, A.; Schmitz, T.; Proebsting, S.; Wenzel, D.; Vosen, S.; Franklin, B.S.; Fleischmann, B.K.; et al. Endothelial microparticle-mediated transfer of microRNA-126 promotes vascular endothelial cell repair via spred1 and is abrogated in glucose-damaged endothelial microparticles. Circulation 2013, 128, 2026–2038. [Google Scholar] [CrossRef] [Green Version]
  143. Schulte, C.; Molz, S.; Appelbaum, S.; Karakas, M.; Ojeda, F.; Lau, D.M.; Hartmann, T.; Lackner, K.J.; Westermann, D.; Schnabel, R.B.; et al. MiRNA-197 and miRNA-223 predict cardiovascular death in a cohort of patients with symptomatic coronary artery disease. PLoS ONE 2015, 10, e0145930. [Google Scholar] [CrossRef] [Green Version]
  144. Hulsmans, M.; Sinnaeve, P.; Van Der Schueren, B.; Mathieu, C.; Janssens, S.; Holvoet, P. Decreased miR-181a expression in monocytes of obese patients is associated with the occurrence of metabolic syndrome and coronary artery disease. J. Clin. Endocrinol. Metab. 2012, 97, 1213–1218. [Google Scholar] [CrossRef] [Green Version]
Figure 1. MiRNA biogenesis and their means of transcriptional silencing. RNA Pol II: RNA polymerase II; miRNA: microRNA; RanGTP: Ran coupled to guanosine triphosphate; RISC: RNA-induced silencing complex; Poly(A) tail: poly-adenosine tail; 80S ribosome: eukaryotic ribosome. (A) Within the nucleus (blue area), miRNA are initially transcribed (e.g., from an miRNA gene) from DNA by RNA polymerase II (yellow) in the form of primary miRNA, or pri-miRNA, which contain stem-loop structures. The enzyme Drosha (purple) proceeds to cleave these stem–loop structures from the rest of the transcript, and these structures are now defined as precursor miRNA, or pre-miRNA. These are then exported from the nucleus via exportin 5 coupled to the Ran cycle. (B) Once in the cytosol (yellow area), the enzyme Dicer recognises pre-miRNA and cleaves them to produce mature miRNA molecules with two nucleotide overhangs on their 3′ ends. This molecule is then incorporated into an RNA-induced silencing complex (RISC, green) and the passenger strand (red backbone) is destroyed. This results in an active RISC complex. (C) The active RISC complex uses the guide strand of the miRNA (blue backbone) to target mRNA transcripts, specifically those that are complementary to the seed sequence of the guide strand. Through translational repression and RNA decay, miRNA reduce the expression of certain genes through RISC. Also note that the poly(A) tail is shown in pink. Ago2: Argonaute 2; DGCR8: DiGeorge syndrome critical region 8.
Figure 1. MiRNA biogenesis and their means of transcriptional silencing. RNA Pol II: RNA polymerase II; miRNA: microRNA; RanGTP: Ran coupled to guanosine triphosphate; RISC: RNA-induced silencing complex; Poly(A) tail: poly-adenosine tail; 80S ribosome: eukaryotic ribosome. (A) Within the nucleus (blue area), miRNA are initially transcribed (e.g., from an miRNA gene) from DNA by RNA polymerase II (yellow) in the form of primary miRNA, or pri-miRNA, which contain stem-loop structures. The enzyme Drosha (purple) proceeds to cleave these stem–loop structures from the rest of the transcript, and these structures are now defined as precursor miRNA, or pre-miRNA. These are then exported from the nucleus via exportin 5 coupled to the Ran cycle. (B) Once in the cytosol (yellow area), the enzyme Dicer recognises pre-miRNA and cleaves them to produce mature miRNA molecules with two nucleotide overhangs on their 3′ ends. This molecule is then incorporated into an RNA-induced silencing complex (RISC, green) and the passenger strand (red backbone) is destroyed. This results in an active RISC complex. (C) The active RISC complex uses the guide strand of the miRNA (blue backbone) to target mRNA transcripts, specifically those that are complementary to the seed sequence of the guide strand. Through translational repression and RNA decay, miRNA reduce the expression of certain genes through RISC. Also note that the poly(A) tail is shown in pink. Ago2: Argonaute 2; DGCR8: DiGeorge syndrome critical region 8.
Biomolecules 10 01354 g001
Figure 2. Export pathways for miRNA and means of interaction with other cells/cell of origin as a potential means of signalling. (A) The autocrine pathway, whereby extracellular miRNAs re-enter the cell from which they originated. (B) The paracrine pathway, whereby extracellular miRNAs are transported towards and enter cells of the same or different type to the miRNA’s cell of origin. (C) The endocrine pathway, whereby extracellular miRNAs enter the circulation and are thus transported to cells in other tissues/organs. Ago2: Argonaute 2; miRNA: microRNA.
Figure 2. Export pathways for miRNA and means of interaction with other cells/cell of origin as a potential means of signalling. (A) The autocrine pathway, whereby extracellular miRNAs re-enter the cell from which they originated. (B) The paracrine pathway, whereby extracellular miRNAs are transported towards and enter cells of the same or different type to the miRNA’s cell of origin. (C) The endocrine pathway, whereby extracellular miRNAs enter the circulation and are thus transported to cells in other tissues/organs. Ago2: Argonaute 2; miRNA: microRNA.
Biomolecules 10 01354 g002
Figure 3. Associations between miRNA in different cells and constituent pathways in coronary artery disease (CAD) pathogenesis. Pathological alterations in the phenotypes of particular cells of the circulatory system, in addition to normal homeostatic processes, are core to the development of CAD (shown in blue, phenotypes in red, pathophysiological processes in purple). Various miRNAs have been identified as being associated with these pathological developments (shown in green), with previous studies showing that they may be implicated in particular contributing mechanisms. VSMC: vascular smooth muscle cell.
Figure 3. Associations between miRNA in different cells and constituent pathways in coronary artery disease (CAD) pathogenesis. Pathological alterations in the phenotypes of particular cells of the circulatory system, in addition to normal homeostatic processes, are core to the development of CAD (shown in blue, phenotypes in red, pathophysiological processes in purple). Various miRNAs have been identified as being associated with these pathological developments (shown in green), with previous studies showing that they may be implicated in particular contributing mechanisms. VSMC: vascular smooth muscle cell.
Biomolecules 10 01354 g003
Table 1. miRNAs as active factors/potential biomarkers in CAD and associated pathologies. Methodologies of miRNA identification, quantification, sample location, experimental model, and time course of disease pathology are indicated. Where the quoted reference is a review article synthesizing several sources of evidence, this has been indicated.
Table 1. miRNAs as active factors/potential biomarkers in CAD and associated pathologies. Methodologies of miRNA identification, quantification, sample location, experimental model, and time course of disease pathology are indicated. Where the quoted reference is a review article synthesizing several sources of evidence, this has been indicated.
ReferencesmiRNAQuantitative EffectOutcomeSample TypemiRNA Identification/Quantification MethodCell Lines/Study PopulationAcute/Chronic Disease Status
Wang et al., 2016 [118]miRNA-146aUpregulatedThis miRNA may be a potential biomarker for poor coronary collateral circulation in CAD patients.PlasmaqRT-PCRHuman patientsChronic (1-month cut-off)
Li et al., 2017 [119]miRNA-155-5p
miRNA-483-5p
miRNA-451a
MiRNA-155-5p and miRNA-483-5p are upregulated;
miRNA-451a is down-regulated
Potential biomarkers for the early detection of atherosclerotic plaque rupture.PlasmaqRT-PCRHuman patientsStable CAD
Zhao et al., 2015 [37]miRNA-143
miRNA-145
ContestedAltered in CAD. Potentially released from vascular walls.Plasma(Review article)(Review article)(Review article)
Li et al., 2017 [120]miRNA-122
miRNA-140-3p
miRNA-720
miRNA-2861
miRNA-3149
UpregulatedElevated during the early stages of ACS.PlasmaqRT-PCRBama male minipigs and human patientsMinipigs: normal and acute MI.
Human patients: Stable angina, unstable angina and acute MI.
Jansen et al., 2017 [121]miRNA-21
miRNA-126-3p
miRNA-222
UpregulatedThese miRNAs increased in concentration following periods of cardiac stress in patients with stenosed coronary arteries.PlasmaqRT-PCRHuman patientsStable CAD
Soeki et al., 2015 [122]miRNA-100-Associated with coronary plaque instability. Potentially released from plaques.PlasmaqRT-PCRHuman patientsUnknown
Liu et al., 2017 [123]miRNA-29aUpregulatedModerates expression of mRNAs of extracellular matrix proteins. Associated with atherosclerosis and intima-media thickness of carotid arteries.PlasmaqRT-PCRHuman patientsUnknown
Wang et al., 2017 [124]miRNA-126Downregulated A potential biomarker for CAD. Inversely correlated to placenta growth factor.PlasmaqRT-PCRHuman patientsCAD for 15–24 months
Al-Kafaji et al., 2017 [125]miRNA-126DownregulatedA potential biomarker for CAD. Inversely correlated with LDL concentration.PlasmaqRT-PCRHuman patientsType 2 diabetics, some with CAD diagnoses
Al-Muhtaresh et al., 2019 [126]miRNA-1
miRNA-133
Upregulated Potential biomarkers. Both correlate with LDL-C levels;
miR-1 is known to negatively regulate Bcl2 [127].
PlasmaqRT-PCRHuman patientsType 2 diabetics, some with CAD diagnoses
Zernecke et al., 2009 [14]miRNA-126-Released from apoptotic bodies derived from endothelial cells from atherosclerotic plaques. Reduces inflammatory activity/plaque development.Plasma/PlaqueqRT-PCRHuman aortic smooth muscle cell culture. Human atherosclerotic plaques. ApoE−/− murine endothelial cell cultures. HUVEC cell lineUnknown
Wang et al., 2014 [128]miRNA-31
miRNA-720
DownregulatedPotential biomarkers for early CAD.Plasma/endothelial progenitor cellsqRT-PCRHuman patientsUnknown CAD
Zhang et al., 2017 [129]miRNA-208a-Significant association with Gensini score, and by extension the severity of atherosclerosis. Potential biomarker for CAD severity.PlasmaqRT-PCRHuman patientsUnknown CAD
Jansen et al., 2014 [111]miRNA-126
miRNA-199a
-The levels of these miRNA, which occur in circulating microvesicles, are potentially prognostic for major adverse cardiovascular events in patients with stable CAD.PlasmaqRT-PCRHuman patientsStable CAD
Han et al., 2015 [130]miRNA-21
miRNA-23a
miRNA-30a
miRNA-34a
miRNA-106b
UpregulatedThese miRNAs occur at higher levels in ApoE−/− mice, which models hypercholesterolaemia.
MiRNA-21, -23a, and -34a are potential biomarkers for CAD.
MiRNA-21 has been linked to CAD-derived ACS.
PlasmaqRT-PCR and miRNA microarraysApoE−/− mice and human CAD patientsUnknown
Zhou et al., 2016 [70]miRNA-206
miRNA-564-5p
UpregulatedPotential biomarkers for CADPlasmaqRT-PCR and miRNA microarraysHuman patientsUnknown
Sayed et al., 2015 [96]miRNA-149
miRNA-424
miRNA-765
MiRNA-149 and miRNA-424 were upregulated, miRNA-765 was downregulatedPotential biomarkers for CAD in middle-aged patientsPlasmaqRT-PCRHuman patientsStable and unstable CAD
Gao et al., 2015 [131]miRNA-145DownregulatedThis miRNA regulates VSMC fate, inhibiting proliferation. It is the modal miRNA in healthy vessel walls, though in atherosclerotic plaques it may not even be detected. Plasma concentration levels are significantly reduced in CAD patients, and those with three-vessel disease have a significantly lower quantity as well. Potential biomarker for CAD.Plasma/plaqueqRT-PCRHuman patientsUnknown (patients diagnosed with CAD for more than a year)
Ren et al., 2013 [132]miRNA-106b/25 cluster
miRNA-17/92a cluster
miRNA-21/590-5p cluster
miRNA-126
miRNA-451
Upregulated in patients with unstable angina, though there is evidence that miRNA-17/92a was actually downregulated in CAD patients [83]These miRNAs are elevated in CAD patients relative to those with stable AP. MiRNA-17/92a is involved in angiogenesis, which further complicates plaques. Increased miRNA-21 can yield increased MMP activity, which can hinder plaque progression. Potential biomarkers for CAD.PlasmaqRT-PCRHuman patientsCAD and unstable angina
Chen et al., 2015 [133]miRNA-17-5pUpregulatedPotential biomarker for early CAD.PlasmaqRT-PCRHuman patientsUnknown
Faccini et al., 2017 [89]miRNA-155
miRNA-145
let-7c
DownregulatedPotential biomarkers for CADPlasmaqRT-PCR and miRNA microarraysHuman patientsUnknown
Koroleva et al., 2017 [51]miRNA-21
miRNA-100
miRNA-127
miRNA-133
miRNA-143/145
miRNA-221/222
miRNA-494
All upregulated apart from miRNA-221/222, which was downregulatedThe expression of these miRNA may influence plaque stability:
miRNA-21, -143, and -221 are pro-stability; miRNA-100, -127, -133, and -494 are pro-instability.
Plaque(Review article)(Review article)(Review article)
Lin et al., 2016 [134]miRNA-365DownregulatedRegulation of the inflammatory response, specifically IL-6 activity, such that IL-6 expression increases as miRNA-365 expression decreases.Plaque, serum, and circulating monocytesqRT-PCRHuman patientsUnknown (patients with atherosclerosis)
Cipollone et al., 2011 [135]miRNA-100
miRNA-127
miRNA-145
miRNA-133a/b
UpregulatedThe expression of these miRNA varies with plaque stability.
MiRNA-133 is relevant to stroke-related proteins and is thought to be vascular smooth muscle-specific.
PlaqueqRT-PCRHuman patientsUnknown
Kumar et al., 2014 [136]miRNA-712
miRNA-205
Upregulated in atherosclerosisThese miRNA target and reduce expression of metalloproteinase inhibitor 3 (TIMP3), increasing the activity of matrix metalloproteinases (MMPs), which affects inflammatory processes and VSMC/leukocyte migration in atherosclerosis.Endothelial cells (Plaque)Review (qRT-PCR, microarrays, and fluorescent in situ hybridisation)Review (mice (C57BL/6 and ApoE−/−))Review (unknown)
Tian et al., 2014 [137]miRNA-155Upregulated Raised inflammatory response and foam cell differentiation.Monocytes (plaque)qRT-PCRApoE−/− miceUnknown
Horie et al., 2012 [138]miRNA-33-Deficiency in ApoE knockout mice suppressed atherogenesis/plaque progression.Monocytes/macrophages (plaque)qRT-PCRApoE−/− miceUnknown
Fang et al., 2010 [139]miRNA-10aDownregulatedExpression levels were reduced in endothelial cells that are thought to be pre-atherosclerotic, affecting inflammation signalling.Endothelial cells (plaque)qRT-PCR, miRNA microarrays, and fluorescent in situ hybridisationAdult pigsUnknown
Zernecke et al., 2009 [14]miRNA-126-Released from apoptotic bodies derived from endothelial cells from atherosclerotic plaques. MiRNAs reduce inflammatory activity/plaque development.Plasma/plaqueqRT-PCRHuman aortic smooth muscle cell culture. Human atherosclerotic plaques.
ApoE−/− murine endothelial cell cultures. HUVEC cell line.
Unknown
Raitoharju et al., 2011 [62]miRNA-21
miRNA-34a
miRNA-146a
miRNA-146b-5p
miRNA-210
UpregulatedThese miRNAs were upregulated in plaques compared to left internal thoracic arteries that were not atherosclerotic. This has been linked to VSMC changes seen in atherogenesis.PlaquemiRNA microarrays and qRT-PCRHuman patientsUnknown
Shan et al., 2015 [140]miRNA-223UpregulatedThis miRNAs seems to be secreted from cells in the circulation. Their levels are elevated in the serum and atherosclerotic lesions in apolipoprotein-E knockout mice.Plaque serum/blood cellsqRT-PCRSprague–Dawley rat VSMC cultures and C67BL/6 murine plateletsUnknown
Bidzhekov et al., 2012 [141]miRNA-26b
miRNA30e-5p
miRNA-105
miRNA125a-5p
miRNA-520b
MiRNA-26b, -30e-5p, and -125a-5p were upregulated.
MiRNA-105 and miRNA-520b were downregulated.
These miRNAs had altered expression in CAD patients relative to healthy controls. Plaque, monocytesqRT-PCR and miRNA microarraysHuman patientsUnknown
Jansen et al., 2013 [142]miRNA-126DownregulatedCirculating levels of miRNA-126 decreased in CAD patients.Circulating microparticlesqRT-PCRMice and human patientsStable CAD since 2003
Schulte et al., 2015 [143]miRNA-197
miRNA-223
-Strong prognostic value in CAD patients for cardiac death.SerumqRT-PCRHuman patientsUnknown CAD
Hulsmans et al., 2012 [144]miRNA-181aDownregulatedPotential biomarker for CAD, as well as metabolic syndromeMonocytesqRT-PCR and miRNA microarraysHuman patientsUnknown
ACS: acute coronary syndrome, ApoE: Apolipoprotein E, CAD: coronary artery disease, HUVEC: human umbilical vein endothelial cells, MI: myocardial infarction, qRT-PCR: quantitative real time polymerase chain reaction.

Share and Cite

MDPI and ACS Style

Fazmin, I.T.; Achercouk, Z.; Edling, C.E.; Said, A.; Jeevaratnam, K. Circulating microRNA as a Biomarker for Coronary Artery Disease. Biomolecules 2020, 10, 1354. https://doi.org/10.3390/biom10101354

AMA Style

Fazmin IT, Achercouk Z, Edling CE, Said A, Jeevaratnam K. Circulating microRNA as a Biomarker for Coronary Artery Disease. Biomolecules. 2020; 10(10):1354. https://doi.org/10.3390/biom10101354

Chicago/Turabian Style

Fazmin, Ibrahim T., Zakaria Achercouk, Charlotte E. Edling, Asri Said, and Kamalan Jeevaratnam. 2020. "Circulating microRNA as a Biomarker for Coronary Artery Disease" Biomolecules 10, no. 10: 1354. https://doi.org/10.3390/biom10101354

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop