REVIEW published: 09 October 2019 doi: 10.3389/fgene.2019.00950 Epigenetic Biomarkers in Cardiovascular Diseases Carolina Soler-Botija 1,2*, Carolina Gálvez-Montón 1,2 and Antoni Bayés-Genís 1,2,3,4 1 Heart Failure and Cardiac Regeneration (ICREC) Research Program, Health Science Research Institute Germans Trias i Pujol (IGTP), Badalona, Spain, 2 CIBERCV, Instituto de Salud Carlos III, Madrid, Spain, 3 Cardiology Service, HUGTiP, Badalona, Spain, 4 Department of Medicine, Barcelona Autonomous University (UAB), Badalona, Spain Cardiovascular diseases are the number one cause of death worldwide and greatly impact quality of life and medical costs. Enormous effort has been made in research to obtain new tools for efficient and quick diagnosis and predicting the prognosis of these diseases. Discoveries of epigenetic mechanisms have related several pathologies, including cardiovascular diseases, to epigenetic dysregulation. This has implications on disease progression and is the basis for new preventive strategies. Advances in methodology and big data analysis have identified novel mechanisms and targets involved in numerous diseases, allowing more individualized epigenetic maps for personalized diagnosis and treatment. This paves the way for what is called pharmacoepigenetics, which predicts the drug response and develops a tailored therapy based on differences Edited by: in the epigenetic basis of each patient. Similarly, epigenetic biomarkers have emerged Yun Liu, as a promising instrument for the consistent diagnosis and prognosis of cardiovascular Fudan University, China diseases. Their good accessibility and feasible methods of detection make them suitable Reviewed by: for use in clinical practice. However, multicenter studies with a large sample population Daniel B. Lipka, German Cancer Research Center are required to determine with certainty which epigenetic biomarkers are reliable for (DKFZ), Germany clinical routine. Therefore, this review focuses on current discoveries regarding epigenetic Jeffrey Mark Craig, Murdoch Childrens Research Institute biomarkers and its controversy aiming to improve the diagnosis, prognosis, and therapy (MCRI), Australia in cardiovascular patients. *Correspondence: Keywords: epigenetics, biomarker, microRNA, cardiovascular diseases, myocardial infarction, heart failure, Carolina Soler-Botija atherosclerosis, hypertension csoler@igtp.cat Specialty section: This article was submitted to INTRODUCTION Epigenomics and Epigenetics, a section of the journal Cardiovascular diseases (CVDs) are one of the leading causes of mortality in developed countries. Frontiers in Genetics Cardiovascular diseases refer to disorders affecting the structures or function of the heart and blood vessels, including hypertension, atherosclerosis, myocardial infarction (MI), ischemia/ Received: 12 May 2019 Accepted: 05 September 2019 reperfusion injury, stroke, and heart failure (HF), among others (Wang et al., 2016a; Thomas et al., Published: 09 October 2019 Abbreviations: AMI, acute myocardial infarction; ApoE, apolipoprotein E; BNP B-type natriuretic peptide; CK, creatine kinase; Citation: cTnI, cardiac troponin I; cTnT, cardiac troponin T; DOT1L, disruptor of telomeric silencing-1; ENaC, epithelial sodium channel; Soler-Botija C, Gálvez-Montón C and EZH2, enhancer of zeste homolog 2; GEO, Gene Expression Omnibus; HDAC, histone deacetylase; HF, heart failure; HFrEF, Bayés-Genís A (2019) Epigenetic heart failure with reduced ejection fraction; HFpEF, heart failure with preserved ejection fraction; hs-cTnT, high-sensitivity Biomarkers in Cardiovascular cardiac troponin T; hs-CRP, high-sensitivity C-reactive protein; lncRNAs, long noncoding RNAs; LV, left ventricular; MI, Diseases. myocardial infarction; miRNAs, microRNAs; ncRNAs, noncoding RNAs; NSTEMI, non- ST-segment elevation myocardial Front. Genet. 10:950. infarction; STEMI, ST-segment elevation myocardial infarction; pmiRNAs, platelet miRNAs; piRNAs, p-element-induced doi: 10.3389/fgene.2019.00950 wimpy testis (PIWI)-interacting RNAs; tRNA, transfer RNA; ZEB1, zinc finger E-box binding homeobox 1. Frontiers in Genetics | www.frontiersin.org 1 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases 2018). Mechanisms underlying the complex pathophysiology are not strictly considered epigenetic factors, they contribute that leads to CVDs are of great interest but still far from clear. to the modulation of gene expression through epigenetics. Progress in the field of epigenetics have opened a new world Disruption of this complex regulation may participate in the for the comprehension and management of human diseases, development of different diseases (Iorio et al., 2010; Hoareau- including the prevalence of CVDs, based on the role of genetics Aveilla and Meggetto, 2017; Moutinho and Esteller, 2017; Wang and its environmental interaction in pathological conditions et al., 2017a) (Figure 1). DNA and histone proteins comprise the (Jaenisch and Bird, 2003). Significant evidence suggests that chromatin, which can be remodeled into a tightly condensed the environment and lifestyle can define epigenetic patterns state (heterochromatin) or an open conformation (euchromatin) throughout life. These epigenetic patterns are a cellular memory that would allow access to transcription factors or DNA of further environmental exposure. Epigenetic modifications are binding proteins, allowing the regulation of gene expression reversible, different among cell types, and can potentially lead to (Kouzarides, 2007). Thus, epigenetics involves changes in disease susceptibility by producing long-term changes in gene gene expression due to chromatin adjustments that change the transcription (Fraga et al., 2005; Beekman et al., 2010). accessibility of DNA without changing its sequence, leading to Epigenetic modifications include DNA methylation and silencing or downregulation/upregulation of gene expression posttranslational modifications of histone tails. However, in (Baccarelli et al., 2010). Chromatin modifications, such as this review, posttranscriptional regulation of gene expression DNA methylation, consist of the transfer of a methyl group to by noncoding RNAs (ncRNAs) is also considered a part of the carbon 5 of the cytosine residues [5-methylcytosine (5mC)] epigenetic machinery. MicroRNAs (miRNAs) are small ncRNAs in CpG dinucleotides sites. CpG dinucleotides are localized that contribute to regulation of the expression of different throughout the genome but are more abundant in certain epigenetic regulators such as DNA methyltransferases (DNMTs) regions, such as gene promoters, forming so-called CpG islands. and histone deacetylases (HDACs), among others. Similarly, CpG methylation causes transcriptional repression by directly DNA methylation and histone modifications can regulate the blocking transcription factor access to the DNA or indirectly via expression of some miRNAs, forming a feedback loop. Thus, chromatin-modifying proteins (methyl-binding proteins) that miRNAs and epigenetic regulators cooperate to modulate the recognize the methylated regions and recruit corepressors. DNA expression of mutual targets. Therefore, although miRNAs methyltransferases catalyze DNA methylation by recognizing FIGURE 1 | Epigenetic regulatory mechanisms. Posttranslational modifications of histone tails by acetylation, deacetylation, ubiquitination, methylation, and phosphorylation. DNA methylation by DNA methyltransferases (DNMTs). Posttranscriptional regulation of gene expression by microRNAs. Epigenetic modifications involve silencing or downregulation/upregulation of gene expression. Dysregulation of the epigenetic machinery could lead to gene expression dysregulation and cardiovascular diseases. Ubiquitin (Ub), methionine (Me), acetyl group (Ac), phosphate (P), deubiquitinating enzyme (DUB), histone methyltransferase (HMTs), histone demethylase (HDMTs), histone acetyltransferase (HAT), histone deacetylase (HDAC), a cytosine followed by a guanine (CpG), microRNAs (miRNAs), and messenger RNA (mRNA). Frontiers in Genetics | www.frontiersin.org 2 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases and maintaining hypermethylated DNA during replication response to a therapeutic treatment (Strimbu and Tavel, 2010). (DNMT1) or by de novo methylation (DNMT3a and DNMT3b). Ideally, biomarkers should have easy accessibility, predictable Moreover, gene bodies of actively transcribed genes normally detection, and reliability (Sun et al., 2017). It is mandatory to show slightly higher DNA methylation levels as compared to gene present a specific measurable change that clearly associates with bodies of nontranscribed genes. In contrast, hypomethylation is a diagnosis or a predictable outcome. Thus, biomarkers provide usually found in enhancer regions and promoters (Costantino information to physicians when evaluating the probability of et al., 2018). Posttranslational modification of histone tails is developing a disease, making a diagnosis, evaluating the severity another epigenetic modification that regulates gene expression of a disease and its progression; during therapeutic decision by chromatin remodeling. Histone acetylation, deacetylation, making; or when monitoring a patient’s response and may methylation, phosphorylation and ubiquitination change DNA result in significant cost reduction (Baccarelli et al., 2010). Their accessibility, regulating gene transcription. The acetylation of classification can be based on their application (predisposition, histone tails is regulated by histone acetyltransferases (HATs) diagnosis, monitoring, safety, prognostic, or predictive and HDACs. Histone acetyltransferase enzymes acetylate the biomarkers). Predisposition biomarkers determine how likely it lysine residues of the histones, whereas HDACs deacetylate is for a patient to develop a certain disease and are usually utilized them, promoting gene activation or silencing, respectively. when there is a personal or family history that indicates a disease Histone methylation is regulated by histone methyltransferases risk, and the results can help guide medical care. Diagnostic (HMTs) and histone demethylases (HDMT). Methylation occurs biomarkers are used to detect or confirm the existence of a at the lysine or arginine residues and can activate or repress health disorder and may assist its early detection. Monitoring gene transcription depending on the degree of methylation and biomarkers evaluate the status of a disease or determine exposure which residue is methylated (Li et al., 2017c; Sabia et al., 2017). to an environmental agent or medical product. Safety biomarkers The serine, threonine, and tyrosine residues of histone tails can indicate the probability, presence, or extent of toxicity of a certain also be phosphorylated and dephosphorylated by protein kinases medical product or environmental agent. Prognostic biomarkers and phosphatases, respectively. Histone tail phosphorylation indicate how a disease may progress in patients who already modulates chromatin structure, taking part in transcription, have the particular disease. These biomarkers do not predict the DNA repair, and chromatin compaction in cell division and treatment response but can be useful when selecting patients for apoptosis (Rossetto et al., 2012). Lastly, histone tail ubiquitination treatment. Predictive biomarkers identify patients who are most is sequentially catalyzed by ligases enzymes, which attach likely to have a favorable or unfavorable response to a specific ubiquitin to lysine residues. Ubiquitination and deubiquitination treatment. Thus, they can predict treatment success or undesired are involved in the activation of transcription and are usually side effects in a particular patient. A particular disease can have associated with histone methylation. Their effect on repressing different biological mechanisms in different patients. Predictive or activating transcription generally depends on what histone is biomarkers can be associated with the specific mechanism of a modified (Cao and Yan, 2012). Finally, miRNAs regulate gene health disorder. This facilitates a targeted therapy, which uses expression via degradation of the transcript or repression of drugs specific for a particular biological mechanism associated translation when binding to the 3′-untranslated region of the with a disease, increasing its effectiveness (FDA-NIH Biomarker target mRNA. Thus, miRNA represses mRNA translation without Working Group, 2016). Specifically, epigenetic biomarkers changing the DNA sequence of the gene. MicroRNA binding to belonging to most of these classifications are discussed in this mRNA is imperfect, so each miRNA has multiple targets. This review, with a focus on CVDs. Among the epigenetic biomarkers, allows the regulation of a great part of the human genome (Bartel, miRNAs are the most attractive, as they can be detected in small 2009). The miRNAs are 19-25 nucleotides in length, encoded in sample volumes, are stable, and can be obtained from plasma, the genome and transcribed into primary miRNA (pri-miRNA). serum, saliva, and urine. Interestingly, they are highly conserved, Pri-miRNAs derive into miRNAs precursors (pre-miRNA) by and this allows a reliable comparison between patients and the nuclear RNase III called Dorsha and are transferred to the animal models of disease (Matsumoto et al., 2013). Therefore, cytoplasm and processed by the endonuclease Dicer to generate although all epigenetic mechanisms are being intensively a double-stranded miRNA duplex. This product is incorporated investigated, miRNAs are evaluated the most for their use as into an RNA-induced silencer complex (RISC)–loading complex. predictive biomarkers. This review presents an overview of Then, one strand is removed from the complex, and the other current research on epigenetic biomarkers in CVDs and how this strand forms a mature RISC, serving as a template for target knowledge can benefit the diagnosis, prognosis, and therapy for mRNAs (Sato et al., 2011; Nishiguchi et al., 2015). cardiovascular patients. Due to this important function in gene regulation, epigenetic modifications and miRNA may play a crucial role in the development of pathological conditions, including EPIGENETIC BIOMARKERS IN CVDS CVDs. Understanding the epigenetic machinery underlying cardiac disorders and how these epigenetic mechanisms can Over the last few years, numerous studies have linked be introduced into diagnostics (i.e., biomarkers) and therapies cardiovascular risk factors to epigenetic modifications in human is fundamental to improving the quality of life of patients. In patients. Modification of the epigenetic environment alters medicine, a biomarker is defined as a measurable characteristic cardiovascular homeostasis and impacts cardiovascular disorders. that indicates a particular physiological or pathological state or a The function of epigenetic mechanisms in the regulation of Frontiers in Genetics | www.frontiersin.org 3 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases gene expression is well known, although the role of epigenetic disrupted by aldosterone and causes hypomethylation of H3K79 marks in CVDs is not clearly understood. Thus, the exploration at specific regions, disinhibiting the ENaC promoter and leading of epigenetic biomarkers may lead to a deep comprehension of to hypertension. Thus, the Dot1a-Af9 pathway may also be the molecular mechanisms and pathways associated with CVDs. involved in the control of genes implicated in hypertension In this section, we focus on major CVDs, such as hypertension, (Zhang et al., 2009). Hypomethylation of the α-adducin gene atherosclerosis, MI, and HF, and the epigenetic biomarkers (ADD1) promoter has been found to be connected to the risk associated with them. of essential hypertension. However, differences between females and males have been found (Zhang et al., 2013a). Moreover, histone 3 (H3K4 or H3K9) demethylation is induced by Hypertension lysine-specific demethylase-1 (LSD1), which modifies gene Arterial hypertension is a multifactorial disease with several transcription. Hypermethylation of histone 3 has been associated mechanisms and metabolic systems involved in its pathogenesis. with hypertension, increased vascular contraction, and decreased Genetic factors and environmental background may lead to relaxation via the nitric oxide-cGMP (NO-cGMP) pathway in alterations in multiple pathways that can eventually trigger heterozygous LSD1 knockout mice fed a high-salt diet (Pojoga development of the disease (Franceschini and Le, 2014). et al., 2011). Histone deacetylation is also important in the Intrauterine alterations, such as malnutrition, starvation, obesity, development of pulmonary arterial hypertension. HDAC1 and alcohol, drugs, nicotine, or environmental toxins, are some HDAC5 protein levels have been demonstrated to be elevated of the environmental factors directly related to hypertension in the lungs of patients and hypoxic rats. Inhibition of these development in the progeny (Bogdarina et al., 2007; Nuyt and proteins by valproic acid and suberoylanilide hydroxamic acid Alexander, 2009). In addition, individuals who have aerobic diminished the development of hypoxia-induced pulmonary training present with lower blood pressure than nontrained hypertension in rats. Thus, HDAC1 and HDAC5 levels could individuals (Fagard, 2006). This has an important impact on be useful predictive biomarkers for the treatment of pulmonary CVD risk factor control and is a nonpharmacological way hypertension in patients (Zhao et al., 2012). to treat patients. There are also epigenetic factors that can In a study evaluating alterations in the global DNA methylation influence the appearance of hypertension in adults, such as status of patients with essential hypertension, the level of the hypermethylation of genes, including superoxide dismutase-2 epigenetic marker 5mC was lower in hypertensive patients (SOD2) or Granulysin, or increased levels of histone acetylation than in healthy people (Smolarek et al., 2010). In an in vivo at the promoter of the endothelial oxide synthetase gene (eNOS) model of hypertension using Dahl salt-sensitive rats, the levels (Wang et al., 2018b). Environmental factors are important to of 5mC and 5-hydroxymethylcytosine (5hmC) were evaluated determining an individual’s predisposition to developing major in the outer renal medulla. In response to salt administration, cardiovascular risk factors by means of epigenetic modifications, the 5mC levels were significantly higher for genes with low and identification of the epigenetic mechanisms that participate transcription and 5hmC levels higher in genes with higher in hypertension development may help generate new treatments. expression. This study revealed important features of 5mC and This is of great interest because hypertension is a key risk factor 5hmC for understanding the role of epigenetic modifications in for CVDs, including MI, HF, stroke, and end-stage renal disease the regulation of hypertension (Liu et al., 2014). (Table 1 and Figure 2). Rivière et al. (2011) analyzed the regulation of somatic Essential hypertension is a multifactorial disease with no angiotensin-converting enzyme gene (sACE) expression by identifiable cause that is affected by environmental and epigenetic promoter methylation. sACE regulates blood pressure by factors. Environmental stressors cause acetylation of histone 3 catalyzing the conversion of angiotensin I into angiotensin II, in the neurons of the area postrema, leading to an increase in a potent vasopressor. Hypermethylation of sACE promoter in pressure that results in hypertension (Irmak and Sizlan, 2006). cultures of human endothelial cells and rats was associated Low activity of the 11 beta-hydroxysteroid dehydrogenase 2 with transcriptional repression, suggesting an epigenetic (HSD11B2) induces hypertension. In a study performed in mechanism in hypertension regulation (Rivière et al., 2011). patients with essential hypertension or glucocorticoid-induced More recently, Fan et al. (2017) demonstrated opposite results in hypertension, the HSD11B2 promoter was highly methylated. patients with essential hypertension. The authors indicated that These changes may reflect a global status, with methylation of hypermethylation of the ACE2 promoter may increase essential gene promoter being a potentially useful molecular biomarker hypertension risk, with variabilities in CpG islands methylation to characterize hypertensive patients (Alikhani-Koopaei in males and females (Fan et al., 2017). et al., 2004; Friso et al., 2008). Moreover, a polymorphism in Moreover, a genome-wide methylation study on essential the disruptor of telomeric silencing-1 gene (DOT1L), which hypertension revealed that changes in the DNA methylation of encodes a methyltransferase that enhances methylation of leukocytes are involved in the pathogenesis of hypertension. They histone 3 (H3K79) in the renal epithelial sodium channel gene found increased methylation in the gene encoding sulfatase 1 (ENaC) promoter, is associated with blood pressure regulation (SULF1), which is involved in apoptosis, and decreased (Duarte et al., 2012). It has also been reported that a DOT1A methylation in the gene encoding prolylcarboxypeptidase (PRCP), and ALL1 (fused gene from chromosome 9 [Af9]) interaction is a regulator of angiotensin II and III cleavage (Wang et al., 2013b). associated with H3K79 hypermethylation of the ENaC promoter, Another genome-wide study of blood pressure characteristics suppressing its transcriptional activity. This interaction is found new genetic variants that influence blood pressure and are Frontiers in Genetics | www.frontiersin.org 4 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases TABLE 1 | Epigenetic biomarkers in hypertension. Epigenetic Biomarker Regulation in Sample source Study type References modification hypertension DNA HSD11B2 promoter Highly methylated Rat’s urine and tissues Experimental: in vitro (Alikhani-Koopaei et al., methylation and human cell lines and rat model 2004) SERPIN3 CpG island Hypomethylation Placental tissue Clinical (Chelbi et al., 2007) HSD11B2 promoter Highly methylated Blood and urine Clinical (Friso et al., 2008) 5mC Lower levels Blood Clinical (Smolarek et al., 2010) NKCC1 promoter Hypomethylation Aorta, heart and kidney Experimental: (Lee et al., 2010; Cho et spontaneously al., 2011) hypertensive rodent model sACE promoter Hypermethylation Blood Clinical and (Rivière et al., 2011) experimental: in vitro ERα promoter Methylation Uterine arteries Clinical (Dasgupta et al., 2012) SULF1, PRCP SULF1: hypermethylation; Blood Clinical (Wang et al., 2013b) PRCP: hypomethylation ADD1 promoter Hypomethylation Plasma Clinical (Zhang et al., 2013a) 5mC, 5hmC Higher levels Tissue Experimental: Dahl salt- (Liu et al., 2014) sensitive rats AGT promoter Demethylation H295R cells and Experimental: in vitro (Wang et al., 2014a) visceral adipose tissue and rat model DSCR3 Hypermethylation Maternal blood and Clinical (Kim et al., 2015) placental tissue miRNA-34a gene promoter Hypomethylation Placental tissue Clinical (Rezaei et al., 2018) ACE2 promoter Hypermethylation Plasma Clinical (Fan et al., 2017) CBS promoter Hypermethylation Maternal blood and Clinical (Kim et al., 2015) placental tissue MTHFD1 promoter Hypermethylation Plasma Clinical (Xu et al., 2019) Histone H3K79 Hypermethylation NA Clinical (Rodriguez-Iturbe, 2006; modifications Duarte et al., 2012) Histone 3 Acetylation Germ cells Review (Irmak and Sizlan, 2006) H3K79 DNA methylation Bibliography Review (Zhang et al., 2009) HDAC8 Inhibition mDCT cells and tissues Experimental: rat (Mu et al., 2011) models of salt-sensitive hypertension H3K4 or H3K9 Hypermethylation Tissue, plasma, and Experimental: LSD1 (Pojoga et al., 2011) urine knockout mice with a high-salt diet HDAC1, HDAC5 High levels Lung tissue and Clinical and (Zhao et al., 2012) adventitial fibroblasts experimental: in vitro and hypoxic rat miRNA miR-18a, miR-210, miR- miR-18a, miR-363, miR- Placental tissue Clinical (Zhu et al., 2009) 152, miR-363, miR-377, 377, miR-411, miR-542-3p: miR-411, miR-518b, underexpression; miR-210, miR-542-3p miR-152, miR-518b: overexpression 22 miRNAs 15 upregulated and 7 Serum Clinical (Yang et al., 2011) downregulated let-7b, miR-302*, miR-104, Overexpression Placental tissue Clinical (Noack et al., 2011) miR-128a, miR-182*, miR-133b miR-92b, miR-197, miR- miR-92b, miR-197, miR- Placental tissue Clinical (Choi et al., 2013) 342-3p, miR-296-5p, 342-3p, miR-296-5p, miR-26b, miR-25, miR- miR-26b, miR-25, miR- 296-3p, miR-26a, miR-198, 296-3p, miR-26a, miR-198, miR-202, miR-191, miR-95, miR-202, miR-191, miR-95, miR-204, miR-21, miR-223 miR-204: overexpression; miR-21, miR-223: underexpression miR-9, miR-126 Lower levels Peripheral blood Clinical (Kontaraki et al., 2014) mononuclear cells miR1233 Higher levels Serum Clinical (Ura et al., 2014) (Continued) Frontiers in Genetics | www.frontiersin.org 5 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases TABLE 1 | Continued Epigenetic Biomarker Regulation in Sample source Study type References modification hypertension miR-18a, miR-19b1, miR- miR-210: upregulation; Plasma and placental Clinical (Xu et al., 2014) 92a1, miR-210 miR-18a, miR-19b1, and tissue miR-92a1: downregulation miR-505 Upregulation Plasma Clinical (Yang et al., 2014) miR-106a, miR-18b, Dysregulation Placental tissue Clinical (Zhang et al., 2015a) miR-20b, miR-19b-2, miR- 92a-2, miR-363 miR-515-5p, miR-518b, Downregulation Placental tissue Clinical (Hromadnikova et al., miR-518f-5p, miR-519d, 2015) miR-520h miR-335, miR-584 Upregulation Placental tissue and Clinical and (Jiang F. et al., 2015) HTR8/Svneo cells experimental: in vitro miR-125b Overexpression Plasma and placental Clinical (Yang et al., 2016b) tissue miR-215, miR-155, miR- MiR-215, miR-155, miR- Plasma Clinical (Jairajpuri et al., 2017) 650, miR-210, miR-21, 650, miR-210, miR-21: miR-18a, miR-19b1 upregulation; miR-18a, miR-19b1: downregulation miR-204-5p Higher levels Serum Clinical (Mei et al., 2017) let-7b*, let-7f-1*, miR-1183, miR-1183: upregulation; Plasma and placental Clinical (Gunel et al., 2017) miR-23c, miR-425* let-7b*, miR-23c, miR-425*, tissue let-7f-1*: downregulation miR-145 Downregulation Placental tissue Clinical (Han et al., 2017) miR-202-3p Upregulation Placental tissue Clinical (Singh et al., 2017) let-7 Higher Plasma Clinical (Huang et al., 2017b) miRNA Dysregulation Bibliography: Maternal Bibliography review (Laganà et al., 2018) serum and placental tissue miR-19a Upregulation Plasma and lung tissue Clinical (Chen and Li, 2017) miR-21 Upregulation Peripheral blood Clinical (Parthenakis et al., 2017) mononuclear cells miR-21 Upregulation Bibliography review Bibliography review (Sekar et al., 2017) miR-510 Upregulation Serum Clinical (Krishnan et al., 2017) miR-206 Lower levels Serum Clinical (Jin et al., 2017) miR-424(322) Upregulation Plasma Clinical (Baptista et al., 2018) miR-199a-3p, miR- Downregulation Serum Clinical (Zhang et al., 2018c) 208a-3p, miR-122-5p, miR-223-3p miR-431-5p Upregulation Tissue Experimental: mice (Huo et al., 2019) made hypertensive and in vitro miR-143, NR_034083, miR-143: upregulation; Peripheral blood Clinical (Chen et al., 2018b) NR_104181, NR_034083: leucocytes downregulation and NR_104181 and NA, not available. strongly associated with local CpG island methylation. This study regulates the Na(+)-Cl(−)-cotransporter (NCC) and ENaC. This demonstrated the role of DNA methylation in the regulation of would affect the distal nephron, increasing the reabsorption blood pressure (Kato et al., 2015). of sodium. Stimulation of β(2)-adrenergic receptor (β(2)AR) The pathogenesis of hypertension is affected by in salt intake conditions would reduce WNK4 transcription, alterations in ion flux mechanisms. Hypomethylation of the resulting in inhibition of HDAC8 activity and increased histone Na/K/2Cl cotransporter 1 gene (NKCC1) promoter results acetylation. In the rat models of salt-sensitive hypertension, in overexpression in a rodent model with spontaneous salt diet repressed renal WNK4 expression, activating the hypertension (Lee et al., 2010). DNA methyltransferase activity NCC and inducing salt-dependent hypertension. Thus, WNK4 maintained hypomethylation in the NKCC1 promoter, playing transcription is epigenetically modulated in the course of salt- an important role in NKCC1 upregulation during the course sensitive hypertension, with the β(2)AR-WNK4 pathway as a of the disease. This encourages evaluation of the NKCC1 potential therapeutic target for this disease (Mu et al., 2011). methylation status in hypertensive patients (Cho et al., 2011). Goyal et al. (2010) demonstrated that a low protein diet in Furthermore, WNK4 is a serine-threonine kinase that negatively pregnant mice leads to alterations in DNA methylation, miRNA, Frontiers in Genetics | www.frontiersin.org 6 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases FIGURE 2 | Epigenetic modifications and microRNAs biomarkers dysregulated in atherosclerosis and hypertension. Ascending arrows indicate higher levels or upregulation, and descending arrows denote lower levels or downregulation, both compared to control conditions. Those miRNAs presenting opposite results are shown in orange. and gene expression in the brain renin–angiotensin system, a key are significantly higher in essential hypertensive patients than regulator of hypertension in adults (Goyal et al., 2010). Along the controls, whereas NR_027032 and NR_034083 are significantly same lines, in a study carried out in vitro and in a rat model, DNA reduced. After evaluating cardiovascular risk factors, they demethylation of the angiotensinogen gene (AGT) promoter concluded that lower expression levels of NR_034083 and higher activated its expression. AGT is an important substrate of the expression levels of NR_104181 and miR-143 were risk factors renin–angiotensin–aldosterone system and an important target for essential hypertension (Chen et al., 2018b). Another study in hypertension research. Elevated concentrations of circulating evaluated the correlation between miRNA let-7 expression and aldosterone and high consumption of salt stimulate the AGT subclinical atherosclerosis in untreated patients with newly gene expression in adipose-induced hypertension (Wang diagnosed essential hypertension and found increased levels in et al., 2014a). In addition, cystathionine β-synthase (CBS), an hypertensive patients, suggesting that plasma let-7 could be an important enzyme in the metabolism of plasma homocysteine, indicator for monitoring end-organ damage and a biomarker for is associated with hypertension and stroke. Hypermethylation atherosclerosis in these patients (Huang et al., 2017b). Similarly, of the CBS promoter has been demonstrated to increase the risk upregulation of miR-505, miR-19a, miR-21, miR-510, or miR- of both diseases, especially in male patients (Wang et al., 2019a). 424(322) in blood from hypertensive patients suggests a possible Similarly, hypermethylation of the methylenetetrahydrofolate use for miR-510 as a diagnostic biomarker and therapeutic dehydrogenase 1 gene (MTHFD1) promoter, which is also target (Yang et al., 2014; Chen and Li, 2017; Krishnan et al., associated with homocysteine metabolism, was observed 2017; Parthenakis et al., 2017; Sekar et al., 2017; Baptista et al., in hypertensive patients, and proposed as a potential 2018). Lower levels of the combination of miR-199a-3p, miR- diagnostic biomarker in patients with essential hypertension 208a-3p, miR-122-5p, and miR-223-3p have also been shown to (Xu et al., 2019). be suitable for diagnosis of hypertension (Zhang et al., 2018c). In addition to the previous classic epigenetic modifications, Decreased miR-206 levels might also be especially useful in the miRNAs often regulate hypertension and are attractive detection of pulmonary hypertension in patients with left heart biomarkers for the disease. The miR-9 and miR-126 expression disease (Jin et al., 2017). Furthermore, a study in hypertensive levels are significantly lower in hypertensive patients than mice produced by infusion of angiotensin II concluded that miR- healthy individuals and are related to hypertension prognosis 431-5p knockdown delays the increase in blood pressure induced and organ damage. Thus, miR-9 and miR-126 may be possible by angiotensin II and reduces vascular injury. This demonstrates biomarkers in essential hypertension (Kontaraki et al., 2014). its potential as a target for the treatment of hypertension and Moreover, ncRNAs, such as miR-143, miR-145, and NR_104181, vascular injury (Huo et al., 2019). Frontiers in Genetics | www.frontiersin.org 7 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases Preeclampsia is an important pregnancy-induced syndrome medium-sized arteries, the accumulation of extracellular matrix characterized by hypertension and proteinuria. Chronic hypoxia is and lipids, and smooth muscle cell proliferation. This process a common pregnancy stress that increases the risk of preeclampsia leads to the infiltration of immune cells (mostly macrophages) and is associated with changes in methylation of the estrogen and endothelial dysfunction, forming a plaque, and eventually receptor α gene (ERα) promoter. ERα is involved in adjustments to developing into acute cardiovascular events, such as MI, the uterine blood flow, and promoter methylation results in gene peripheral vascular disease, aneurysms, and stroke (Wissler, 1991). repression in uterine arteries, increasing blood pressure (Dasgupta Proatherogenic stimuli, such as low-density lipoprotein (LDL) et al., 2012). Preeclampsia also modifies the expression profile cholesterol and oxidized LDL, have been suggested to stimulate of several serine protease inhibitors (SERPINs) in the placenta. a long-term epigenetic reprogramming of innate immune system Specifically, SERPIN3 CpG islands have a significantly low level of cells. This induces a constant activation, even after the removal methylation in preeclampsia, providing a new potential marker for of atherosclerotic stimuli (Bekkering et al., 2016). Emerging early diagnosis (Chelbi et al., 2007). Another study demonstrated evidence supports epigenetic modifications being involved in the a positive association between placenta global DNA methylation initiation and progression of atherosclerosis, playing an important and hypertension in preeclampsia (Kulkarni et al., 2011). Next- role in plaque development and vulnerability, and highlighting generation sequencing technology and microarray assay analyses the importance of epigenetic biomarkers as predictors of CVDs of the miRNA expression pattern in preeclamptic placentas (Table 2 and Figure 2) (Xu et al., 2018). versus healthy placentas have revealed that miRNAs expression is Regarding histone modifications, HDAC3 is reported to have dysregulated in preeclampsia (Zhu et al., 2009; Noack et al., 2011; a protective effect in apolipoprotein E deficient (apoE−/−) mice. Yang et al., 2011; Choi et al., 2013; Xu et al., 2014; Hromadnikova HDAC3 maintains the endothelial integrity, and its deficiency et al., 2015; Zhang et al., 2015a; Gunel et al., 2017; Han et al., 2017). results in atherosclerosis (Zampetaki et al., 2010). Similarly, These results were in agreement with those found in the miRNA increased histone acetylation has been proposed to play some role database from cell and tissue analyses. Thus, circulating miRNAs in in the progression of atherogenesis by modulating the expressions the serum of pregnant women could be used as biomarkers for the of proatherogenic genes (Choi et al., 2005). Histone deacetylases diagnosis and prognosis of preeclampsia. To further demonstrate are upregulated in aortic smooth muscle cells when they were that miRNAs could be good predictors of preeclampsia, as well as stimulated with mitogens. In contrast, inhibition of HDACs its severity, circulating miRNA signatures were evaluated in women reduces aortic smooth muscle cell proliferation by changing divided into groups based on preeclampsia severity. MiR-21, miR- cell cycle genes expression. This suggests a protective effect 29a, miR-125b, miR-155, miR-202-3p, miR-204-5p, miR-210, against atherosclerosis (Findeisen et al., 2011). Investigations of miR-215, miR‑335, miR-518b, miR‑584, miR-650, and miR-1233 the association between changes in lysine 27 trimethylation of were upregulated, whereas miR-15b, miR-18a, miR-19b1, and histone 3 (H3K27Me3), and atherosclerotic plaque development miR-144 were downregulated in women with severe preeclampsia revealed a reduction in global levels of H3K27Me3 modification compared to mild preeclampsia (Ura et al., 2014; Jiang et al., 2015; in vessels with advanced atherosclerotic plaques. This does not Yang et al., 2016b; Jairajpuri et al., 2017; Mei et al., 2017; Singh correlate with a reduction in the corresponding HMT, enhancer et al., 2017). In addition, a recent data recompilation supported of zeste homolog 2 (EZH2). There was a relationship between a direct association between high or low expression of miRNAs the repression of H3K27Me3 mark in the vessels with advanced in pregnancy serum and placenta in preeclamptic pregnancies atherosclerotic plaques and the dynamic differentiation and (Laganà et al., 2018). Interestingly, an association has also been proliferation of smooth muscle cells associated with atherosclerotic demonstrated between hypomethylation of the miR-34a promoter disease (Wierda et al., 2015). Histone acetylation, methylation, and preeclampsia severity (Rezaei et al., 2018). Another study and the expression of their corresponding transferases in the analyzed the concentrations of Down syndrome critical region 3 atherosclerotic plaques of patients with carotid artery stenosis (DSCR3), Ras association domain family 1 isoform A (RASSF1A), have been analyzed. Greißel et al. (2016) analyzed the expression and sex-determining region Y (SRY) cell-free fetal DNA in of HATs GCN5L, P300, MYST1, and MYST2 and HMTs MLL2/4, maternal plasma from preeclamptic pregnancies and found that SET7/9, hSET1A, SUV39H1, SUV39H2, ESET/SETDB1, EHMT1, all of the markers significantly correlated with gestational age. The EZH2, and G9a and described an enhancement in histone authors demonstrated that DSCR3 is a novel epigenetic biomarker acetylation on H3K9 and H3K27 in the smooth muscle cells from and an alternative to RASSF1A for the prediction of early-onset severe atherosclerotic lesions that correlated with plaque severity. preeclampsia (Kim et al., 2015). However, no association was In addition, H3K9 and H3K27 methylation were significantly found between the methylation status of the cortisol-controlling lower in atherosclerotic plaques and significantly associated with gene (HSD11B2), tumor suppressor gene (RUNX3), or long disease severity (Greißel et al., 2016). interspersed nucleotide element-1 gene (LINE-1) and hypertensive DNA methylation is also involved in atherosclerosis. disorders of pregnancy when placental DNA methylation was To identify CpG methylation profiles in the progression of analyzed (Majchrzak-Celińska et al., 2017). atherosclerosis in the human aorta, Valencia-Morales et al. (2015) performed DNA methylation microarray analyses. They Atherosclerosis detected a correlation between histological pathology and the Atherosclerosis is a chronic inflammatory disease characterized differential methylation of numerous autosomal genes in vascular by the accumulation of cholesterol in the walls of large- and tissue, providing potential biomarkers of damage severity and Frontiers in Genetics | www.frontiersin.org 8 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases TABLE 2 | Epigenetic biomarkers in atherosclerosis. Epigenetic Biomarker Regulation in Sample source Study type References modification atherosclerosis DNA KLF2 promoter Methylation HUVEC cells Experimental: in vitro (Kumar et al., 2013) methylation KLF4 promoter Methylation HAEC cells Experimental: in vitro (Jiang et al., 2014) HECA, EBF1, NOD2, HECA, EBF1, NOD2: Human aortic intima and Clinical and (Yamada et al., 2014) MAP4K4, ZEB1, FYN Hypomethylated; HEK293 cells experimental: in vitro MAP4K4, ZEB1, FYN: Hypermethylated TIMP1, ABCA1, ACAT1 Altered methylation status Peripheral blood Clinical (Ma et al., 2016) promoters SMAD7 promoter Hypermethylation Peripheral blood and Clinical (Wei et al., 2018) atherosclerotic plaques 5mC, 5-hmC Higher levels Peripheral blood Clinical (Jiang et al., 2019) Histone HDAC3 Deficiency Aorta and HUVEC cells Experimental: apoE−/− (Zampetaki et al., 2010) modifications mice and in vitro H3K27Me3 Reduction in H3K27Me3 Perirenal aortic tissue Clinical (Wierda et al., 2015) modification patches H3K9, H3K27 Higher histone acetylation Carotid tissue Clinical (Greißel et al., 2016) and lower histone methylation miRNA miR-130a, miR-27b, Higher levels Serum and intima tissue Clinical (Li et al., 2011) miR-210 miR-17-5p Higher levels Plasma Clinical (Chen et al., 2015a) miR-143-3p, Lower levels Microparticles Clinical (de Gonzalo-Calvo et al., miR-222-3p 2016) miR-30 Lower levels Plasma Clinical (Huang et al., 2016b) miR-92a Higher levels Plasma Clinical (Huang et al., 2017a) miR-18a-5p, miR- Lower levels Plasma Clinical (Vegter et al., 2017) 27a-3p, miR-199a-3p, miR-223-3p, miR-652-3p miR-33a Higher levels Plasma Clinical (Kim et al., 2017) miR-126 Lower levels Plasma Experimental: (Hao and Fan, 2017) apoE−/− mice miR-212 Overexpression Serum Clinical (Jeong et al., 2017) miRNA let-7 Higher levels Plasma Clinical (Huang et al., 2017b) miR-1254 Higher levels Plasma Clinical (de Gonzalo-Calvo et al., 2018) miR-200c Overexpression Carotid plaques and plasma Clinical (Magenta et al., 2018) miR-29c Higher levels Plasma Clinical (Huang et al., 2018) miR-221, miR-222 Lower expression levels Serum Clinical (Yilmaz et al., 2018) miR-638 Lower levels Serum Clinical (Luque et al., 2018) miR-122 Higher levels Serum Clinical (Wang and Yu, 2018) miR-221, miR-222 Higher levels in tissue Coronary artery Clinical (Bildirici et al., 2018) samples and lower levels in atherosclerotic plaques, and whole blood internal mammary arteries and whole blood miR-664a-3p Downregulation Serum Clinical (Li et al., 2018b) miR-155 Higher levels Serum Clinical (Qiu and Ma, 2018) miR-19A, miR-19B, Differential levels GEO dataset High throughput (Mao et al., 2018) miR-126, miR-155 miR-126, miR-143 Higher levels Plasma Clinical (Gao et al., 2019) treatment targets (Valencia-Morales et al., 2015). Genes such (Yamada et al., 2014). Another study described differentially as Drosophila headcase (HECA), early B-cell factor 1 (EBF1), methylated regions in genes associated with atherosclerosis in and nucleotide-binding oligomerization domain containing 2 swine aorta endothelial cells (Jiang et al., 2015). Low-density (NOD2) are significantly hypomethylated, whereas mitogen- lipoprotein cholesterol risk factor upregulates DNMT1, which activated protein kinase kinase kinase kinase 4 (MAP4K4), methylates and represses the Krüppel-like factor 2 gene (KLF2) zinc finger E-box binding homeobox 1 (ZEB1), and proto- promoter. KLF2 is a transcription factor essential for endothelium oncogene tyrosine-protein kinase (FYN) are hypermethylated in homeostasis, and its repression results in endothelial dysfunction atheromatous plaque lesions compared to the plaque-free intima (Kumar et al., 2013). Similarly, DNMT3a upregulation in human Frontiers in Genetics | www.frontiersin.org 9 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases aortic endothelial cells exposed to disturbed flow induces the a consistent trend between a high number of atherosclerosis methylation and repression of the Krüppel-like factor 4 gene manifestations and lower levels of miR-18a-5p, miR-27a-3p, (KLF4) promoter, increasing regional atherosusceptibility miR-199a-3p, miR-223-3p, and miR-652-3p. Thus, lower levels (Jiang et al., 2014). In an attempt to determine biomarkers of of circulating miRNAs in HF patients with atherosclerotic atherosclerosis in the primary stages, the DNA methylation disease and an elevated probability of cardiovascular-related status was determined in a selection of gene promoters rehospitalization were described (Vegter et al., 2017). High associated with the disease. They analyzed the promoter levels of miR-33a have also been demonstrated to be a potential methylation of ATP binding cassette subfamily A member 1 cause of cholesterol accumulation and to exacerbate vessel walls (ABCA1), TIMP metallopeptidase inhibitor 1 (TIMP1), inflammation in atherosclerotic disease. Thus, plasma miR-33a and acetyl-CoA acetyltransferase 1 (ACAT1) and observed has been proposed as a suitable biomarker in atherosclerosis significant alterations in the peripheral blood of atherosclerosis (Kim et al., 2017). patients (Ma et al., 2016). A recent study found that SMAD7 In an attempt to identify more atherosclerosis biomarkers, expression is decreased and its promoter highly methylated in Hao and Fan (2017) performed microarray analysis using the atherosclerotic plaques compared to normal artery walls. There plasma from apoE−/− mice and discovered that a reduction was also increased DNA methylation of the SMAD7 promoter in miR-126 levels is a good indicator of atherosclerotic disease. in the peripheral blood of atherosclerosis patients. Thus, the They also determined that miR-126 is involved in the mitogen- SMAD7 promoter is hypermethylated in atherosclerosis patients associated protein kinase (MAPK) signaling pathway, reducing and their atherosclerotic plaques, with a positive association cytokine release and progressing atherosclerotic pathogenesis with homocysteine levels (Wei et al., 2018). Moreover, increased (Hao and Fan, 2017). In contrast, Gao et al. (2019) determined 5mC and 5-hmC levels, which indicate DNA methylation and that higher expression levels of miR-126 and miR-143 correlate hydroxymethylation, respectively, have been demonstrated in with the presence and severity of cerebral atherosclerosis (Gao peripheral blood mononuclear cells from elderly patients with et al., 2019). In another study, the authors evaluated the synergy of coronary heart disease. These results positively correlate with the circulating miRNAs with cardiovascular risk factors to estimate severity of coronary atherosclerosis (Jiang et al., 2019). the presence of atherosclerosis in ischemic stroke patients. MicroRNAs have also been identified as attractive epigenetic They identified miR-212 as a novel marker that enhances the biomarkers for atherosclerosis. Li et al. (2011) examined miRNA estimation of atherosclerosis presence in combination with levels in serum samples and the intima of atherosclerosis hemoglobin A1c, high-density lipoprotein cholesterol, and obliterans patients and compared them to controls. They lipoprotein(a) (Jeong et al., 2017). Another candidate biomarker observed increased levels of miR-27b, miR-130a, and miR-210 for atherosclerosis is miR-200c. The authors analyzed plaque in serum and sclerotic tissue from patients, proposing these instability in the carotid arteries of patients undergoing carotid miRNAs as epigenetic biomarkers for early stages of the disease endarterectomy by examining the expression of miR-200c. Higher (Li et al., 2011). Later, a study with a reduced number of patients expression of miR-200c positively correlated with instability suggested that elevated levels of circulating miR-17-5p may be biomarkers, such as monocyte chemoattractant protein-1, a useful biomarker in the diagnosis of coronary atherosclerosis cyclooxygenase-2, interleukin 6 (IL-6), metalloproteinases, and (Chen et al., 2015a). miR-33a/b, and negatively correlated with stability biomarkers, Microparticles secreted by human coronary artery such as ZEB1, endothelial nitric oxide synthase, forkhead smooth muscle cells are a different source of cardiovascular boxO1, and Sirtuin1. Thus, miR-200c could be a biomarker biomarkers. These extracellular vesicles can contain miRNAs, of atherosclerotic plaque progression and clinically useful for such as miR-21-5p, miR-143-3p, miR-145-5p, miR-221-3p, identifying patients at high embolic risk (Magenta et al., 2018). and miR-222-3p. Lower levels of miR-143-3p and miR- Along the same lines, lower serum levels of miR-638 may be a 222-3p have been found in microparticles derived from suitable biomarker of plaque vulnerability and ischemic stroke atherosclerotic plaque areas compared to nonatherosclerotic in individuals with high cardiovascular risk (Luque et al., 2018). areas (de Gonzalo-Calvo et al., 2016). With the intention to explore the role of miRNAs associated Huang et al. (2016b) evaluated the expression of miR-30 with carotid atherosclerosis, Mao et al. (2018) analyzed the in patients with essential hypertension compared to control genes differentially expressed between primary and advanced individuals. They observed a reduction in miR-30 levels in the atherosclerotic plaques using two public datasets from the Gene hypertensive patients and in the increased carotid intima-media Expression Omnibus (GEO) databases. The authors found a total thickness group. Thus, the authors suggested that circulating of 23 miRNAs and focused on miR-19A, miR-19B, miR-126, miR-30 may be a useful noninvasive atherosclerosis biomarker for and miR-155, which may be considered biomarkers of carotid patients with essential hypertension (Huang et al., 2016b). Later, atherosclerosis (Mao et al., 2018). In addition, Li et al. (2018b) the authors also identified higher levels of miR-92a as a possible identified downregulation of specific circulating miR-664a-3p as biomarker of atherosclerosis in the same type of patients (Huang a biomarker of atherosclerosis in patients with obstructive sleep et al., 2017a).With the aim of investigating correlations between apnea and enlarged maximum carotid intima-media thickness circulating miRNAs specific for HF and atherosclerosis in HF (Li et al., 2018b). patients, Vegter et al. (2017) assessed miRNAs levels and related Circulating miR-221 and miR-222 could also be suitable them to biomarkers associated with atherosclerotic disease and biomarkers for the diagnosis of atherosclerosis, as lower levels rehospitalizations of cardiovascular patients. They demonstrated of these miRNAs correlate with the disease (Bildirici et al., 2018; Frontiers in Genetics | www.frontiersin.org 10 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases Yilmaz et al., 2018). However, higher levels have been found in DNA methylation. The authors observed differential DNA in samples from coronary atherosclerotic plaques and internal methylation at 211 CpG sites in individuals with MI, and some mammary arteries (Bildirici et al., 2018). On the other hand, of these sites represented genes related to cardiac function, CVD, higher circulating levels of miR-29c, miR-122, and miR-155 cardiogenesis, and recovery after ischemic injury. Their results in coronary atherosclerosis patients might allow noninvasive highlight genes that might be important in the pathogenesis of MI detection of the disease and its severity (Huang et al., 2018; or in recovery (Rask-Andersen et al., 2016). Along the same lines, Qiu and Ma, 2018; Wang and Yu, 2018). In another interesting a genome-wide DNA methylation and gene ontology analysis of study that assessed whether atherosclerosis of different arterial white blood cells from a population-based study identified four territories, not including the coronary artery, is associated with differentially methylated sites in individuals who had a previous specific circulating miRNAs, the investigators were able to identify MI. Interestingly, they found a correlation between differences specific miRNA profiles for each territory with atherosclerotic in DNA methylation in blood cells and the levels of growth disease. These findings may provide a pathophysiological differentiation factor 15 (GDF-15), which was overexpressed in understanding and be useful for selecting potential biomarkers the myocardium of MI patients (Ek et al., 2016). Later, a genome- for clinical practice (Pereira-da-Silva et al., 2018). wide DNA methylation study of whole blood samples from MI patients and controls identified two methylated regions in zinc finger homeobox 3 (ZFHX3) and SWI/SNF-related, matrix- Myocardial Infarction associated, actin-dependent regulator of chromatin, subfamily a, Acute MI (AMI) is a threatening disease worldwide. Early and member 4 (SMARCA4) that were independently related to MI accurate differential diagnosis is critical for immediate medical (Nakatochi et al., 2017). intervention and improved prognosis (Reed et al., 2017). In Histone modifications are also involved in the pathological particular, it is important to notice that patients with ST-segment process of MI. To investigate the role of the HAT p300 in elevation MI (STEMI) have different requirements than patients adverse left ventricular (LV) remodeling, Miyamoto et al. (2006) with non-STEMI (NSTEMI). For the first group, reperfusion generated transgenic mice overexpressing wild-type p300 or therapy should be administered quickly to reduce infarct size its mutant in the heart. They subjected these mice to surgical and mortality (Authors/Task Force members et al., 2014). MI and demonstrated that cardiac overexpression of p300 However, in NSTEMI patients, revascularization strategies are stimulated adverse LV remodeling. They concluded that the HAT recommended based on individual clinical characteristics (Reed activity of p300 is fundamental for the pathological course of et al., 2017). Therefore, biomarkers with the capacity to diagnose MI (Miyamoto et al., 2006). Moreover, the class III deacetylase and personalize a therapeutic schedule in AMI would be of great sirtuin 1 (SIRT1) is well known to confer a cardioprotective interest. Currently, the favored diagnostic biomarkers of AMI effect and is downregulated after cardiac injury. To understand are cardiac troponin I (cTnI) and T (cTnT), both of which are the underlying mechanism, primary rat neonatal ventricular released from necrotic cardiomyocytes within 2 to 4 h post-MI myocytes were exposed to ischemic or oxidative stress, leading (Babuin and Jaffe, 2005), with maximum levels at 24 to 48 h and to upregulation of the histone H3K9 methyltransferase SUV39H lasting for more than 1 week (Jaffe et al., 2006). For this reason, and downregulation of SIRT1. In addition, inhibition of small repeat infarctions after the main infarction are difficult SUV39H activity by chaetocin in wild-type mice and SUV39H- to detect. Thus, it is fundamental to identify biomarkers for knockout mice protected against induced MI. SUV39H and very early diagnosis of STEMI and for monitoring the entire heterochromatin protein 1 gamma cooperate to methylate the pathological process of AMI (Table 3 and Figure 3). SIRT1 promoter and repress its transcription. Thus, the authors Regarding methylation as an indicator of MI, Talens et al. (2012) described a role for SUV39H linking SIRT1 repression to MI (Yang investigated the association between MI and DNA methylation at et al., 2017a). To examine the role of HDAC4 in the modulation six loci described to be sensitive to prenatal nutrition. As a result, of cardiac function after an MI, Zhang et al. (2018b) generated the researchers demonstrated that the risk of MI in women is a myocyte-specific activated HDAC4-transgenic mouse. They associated with DNA hypermethylation at INS and GNASAS- found that HDAC4 overexpression increases myocardial fibrosis specific loci (Talens et al., 2012). Moreover, microarray analyses and hypertrophy, leading to cardiac dysfunction. Furthermore, investigating whole-genome DNA methylation using cases from the overexpression of activated HDAC4 aggravated cardiac the EPICOR study and EPIC-NL cohort (Fiorito et al., 2014) dysfunction and increased adverse remodeling and apoptosis in identified a hypomethylated region in the zinc finger and BTB the infarcted myocardium. Thus, HDAC4 is an indicator of heart domain-containing protein 12 (ZBTB12) and LINE-1, concluding injury (Zhang et al., 2018b). More recently, the role of HDAC6 in that it is possible to detect specific methylation profiles in the development of HF following MI was investigated using a rat white blood cells a few years before MI occurs. This provides a model. The authors found that the deacetylase activity of HDAC6 promising early biomarker of MI (Guarrera et al., 2015). Another is increased after MI (Nagata et al., 2019). example is the hypermethylation of the aldehyde dehydrogenase Abundant research has focused on miRNAs as novel 2 gene (ALDH2) promoter, which is associated with myocardial biomarkers for MI. MiR-1 levels have been analyzed in plasma injury after MI in rats. The hypermethylation downregulates from patients with AMI and found to be significantly elevated, ALDH2, inhibiting its cardioprotective role (Wang et al., but decreased to normal levels with medication (Ai et al., 2010; 2015). Rask-Andersen et al. (2016) performed an epigenome- Long et al., 2012a). MiR-1, miR-126, and cTnI expression levels wide association study to identify disease-specific alterations exhibited a similar tendency. Thus, circulating miR-1 and Frontiers in Genetics | www.frontiersin.org 11 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases TABLE 3 | Epigenetic biomarkers in myocardial infarction. Epigenetic Biomarker Regulation in myocardial Sample source Study type References modification infarction DNA INS, GNASAS Hypermethylation Leukocytes Clinical (Talens et al., 2012) methylation LINE-1, ZBTB12 Hypomethylation White blood cells Clinical (Guarrera et al., 2015) ALDH2 promoter Hypermethylation Experimental: rat model Experimental: rat model (Wang et al., 2015) of MI of MI ZFHX3, SMARCA4 Methylation Whole blood Clinical (Nakatochi et al., 2017) Histone p300 Overexpression Myocardium Experimental: mouse (Miyamoto et al., 2006) modifications model of MI in HATmut p300-Tg mice SUV39H, SIRT1 SUV39H upregulation H9C2 cells primary rat Experimental: mouse (Yang et al., 2017a) and SIRT1 downregulation neonatal ventricular model of MI in myocytes SUV39H−/− mice HDAC4 Overexpression Myocardium Experimental: mouse (Zhang et al., 2018b) model of MI in MHC- HDAC4-Tg mice HDAC6 Higher levels Myocardium Experimental: rat model (Nagata et al., 2019) of MI miRNA miR-1 Higher levels Plasma Clinical (Ai et al., 2010) miR-31, miR-126, miR-214, miR-31, miR-214: Myocardium Experimental: rat model (Shi et al., 2010) miR-499-5p upregulation; miR- of MI 126, miR-499-5p: downregulation miR-499 Higher levels Tissues and plasma Clinical (Adachi et al., 2010) miR-1, miR-133a, miR- miR-1, miR-133a, Plasma Clinical and (D’Alessandra et al., 133b, miR-499-5p, miR- miR-133b, miR- experimental: mouse 2010) 122, miR-375 499-5p: upregulation; model of MI miR-122, miR-375: downregulation miR-1, miR-126 miR-1: increased; miR-126: Plasma Clinical (Long et al., 2012a) decreased miR-133a Higher levels Plasma Clinical (Eitel et al., 2012) miR-30a, miR-195, let-7b miR-30a, miR- Plasma Clinical (Long et al., 2012b) 195: increased; let-7: decreased miR-499-5p Higher levels Plasma Clinical (Olivieri et al., 2013) miR-1, miR-133a, miR- Higher levels Plasma Clinical (Li et al., 2013) 208b, miR-499 miR-150 Downregulation plasma Clinical (Devaux et al., 2013) miR-133a Higher levels Plasma Clinical (Wang et al., 2013a) miR-21-5p, miR-361-5p, miR-21-5p, miR-361-5p: Plasma Clinical (Wang et al., 2014b) miR-519e-5p increased; miR-519e-5p: reduced miR-208a, miR-499 Higher levels in serum; Serum and heart Experimental: mouse (Xiao et al., 2014) miR-499: lower levels tissues model of MI in scar, miR-208a: unchanged in scar miR-208b, miR-34a Higher levels Plasma Clinical (Lv et al., 2014) miR-328, miR-134 Higher levels Plasma Clinical (He et al., 2014) miR-133, miR-1291, Higher levels Plasma Clinical (Peng et al., 2014) miR-663b miR-497 Upregulation Plasma Clinical (Li et al., 2014b) miR-1 Higher levels Plasma Clinical (Li et al., 2014a) miR-19a Higher levels Plasma Clinical (Zhong et al., 2014) miR-486-3p, miR-150-3p, miR-486-3p, miR- Serum Clinical (Hsu et al., 2014) miR-126-3p, miR-26a-5p, 150-3p: upregulation; and miR-191-5p miR-126-3p, miR- 26a-5p, miR-191-5p: downregulation miR-145 Higher levels Serum Clinical (Dong et al., 2015) (Continued) Frontiers in Genetics | www.frontiersin.org 12 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases TABLE 3 | Continued Epigenetic Biomarker Regulation in myocardial Sample source Study type References modification infarction hsa-miR-493-5p, hsa-miR- hsa-miR-493-5p, hsa-miR- Plasma Clinical (Liang et al., 2015) 369-3p, hsa-miR-495, 369-3p, hsa-miR-495, hsa- hsa-miR-3615, hsa- miR-3615, hsa-miR-433: miR-433, hsa-miR-877-3p, upregulation, hsa-miR- hsa-miR-1306-3p, hsv1- 877-3p, hsa-miR-1306-3p, miR-H2, hsa-miR-3130-5p, hsv1-miR-H2, hsa-miR- hcmv-miR-UL22A 3130-5p, hcmv-miR- UL22A: downregulation miR-499 Higher levels Plasma Clinical (Zhang et al., 2015b) miR-486, miR-150 Higher levels Plasma Clinical (Zhang et al., 2015c) miR-499 Higher levels Plasma Clinical (Chen et al., 2015b) miR-146a, miR-21 Higher levels Plasma Clinical (Liu et al., 2015a) miR-1, miR-208, miR-499 Higher levels Plasma Clinical (Liu et al., 2015b) miR-208a Higher levels Plasma Clinical (Białek et al., 2015) miR-208 Overexpression Plasma Clinical (Han et al., 2015) miR-122-5p Higher levels Plasma Clinical (Yao et al., 2015) miR-21 Higher levels Plasma Clinical (Zhang et al., 2016) miR-99a Downregulation Plasma Clinical (Yang et al., 2016a) miR-19b-3p, miR-134-5p Higher levels Plasma Clinical (Wang et al., 2016b) and miR-186-5p miR-106a-5p, miR-424-5p, Higher levels Blood Clinical (Bye et al., 2016) let-7g-5p, miR-144-3p, miR-660-5p miR-19b-3p, miR-134-5p Overexpression Plasma Clinical (Wang et al., 2016b) and miR-186-5p miR-125b-5p, miR-30d-5p Overexpression Plasma Clinical (Jia et al., 2016) miR-423-5p, miR-30d Overexpression Plasma Clinical (Eryılmaz et al., 2016) miR-221-3p Overexpression Plasma Clinical (Coskunpinar et al., 2016) miR-208a Overexpression in Myocardium and serum Experimental: rat model (Feng et al., 2016) myocardium and high levels of MI in serum miR-133b, miR-22-5p Upregulation Serum/plasma Clinical (Maciejak et al., 2016) miR-103a Higher levels in plasma Plasma and peripheral Clinical and (Huang et al., 2016a) blood mononuclear experimental: in vitro cells miR-122-5p/133b High ratio Serum Clinical (Cortez-Dias et al., 2016) miR499a-5p Higher levels Plasma Clinical (O’Sullivan et al., 2016) miR-181a Higher levels Plasma Clinical (Zhu et al., 2016) miR-145 Decreased Plasma Clinical (Zhang et al., 2017b) miR-133a Higher levels Plasma Clinical (Yuan et al., 2016) miR-208b Higher levels Plasma Clinical (Liu et al., 2017) miR-1, miR-92a, miR-99a, miR-143: increased; miR-1, Monocytes Clinical (Parahuleva et al., 2017) miR-143, miR-223 miR-92a, miR-99a, miR- 223: decreased miR-92a Higher levels Plasma Clinical (Zhang et al., 2017c) miR-208b Overexpression Plasma Clinical (Zhang and Xie, 2017) miR-124 Higher levels Peripheral blood Clinical (Guo et al., 2017) miR-1, miR-21, miR-29b miR-1, miR-21, miR-29b: Plasma Clinical (Grabmaier et al., 2017) and miR-92a increased miR-874-3p Downregulation Plasma Clinical (Yan et al., 2017) pmiR-126 Lower levels Platelet Clinical (Li et al., 2017b) miR-133a Lower levels Serum/Plasma Clinical (Zhu et al., 2018) miR-21 Upregulation Serum Clinical (Wang et al., 2017b) miR-4478 Higher levels Serum Clinical (Gholikhani-Darbroud et al., 2017) miR-23b Higher levels Plasma Clinical (Zhang et al., 2018a) MiR-27a, miR-31, miR- Higher levels GEO database High throughput (Wu et al., 2018a) 1291, miR-139-5p, miR- 204, miR-375 miR-1, miR-133a, miR-34a Lower levels Myocardium Experimental: mouse (Qipshidze Kelm et al., model of MI 2018) (Continued) Frontiers in Genetics | www.frontiersin.org 13 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases TABLE 3 | Continued Epigenetic Biomarker Regulation in myocardial Sample source Study type References modification infarction miR-19b, miR-223, Higher levels Plasma Clinical (Li et al., 2019) miR-483-5p miR-17-5p, miR-126-5p, Higher levels Plasma Clinical (Xue et al., 2019) miR-145-3p miR-150 Lower levels Serum Clinical (Lin et al., 2019) miR-208b, miR-499 Higher levels Plasma Clinical (Devaux et al., 2012) FIGURE 3 | Epigenetic modifications and microRNAs biomarkers dysregulated in myocardial infarction and heart failure. Ascending arrows indicate higher levels or upregulation, and descending arrows denote lower levels or downregulation, both compared to control conditions. Those miRNAs presenting opposite results are shown in orange. miR-126 may be useful indicators of AMI (Long et al., 2012a). biomarker for MI and a predictor of myocardial ischemia risk However, when miR-1 was compared to cTnT, the authors found (Adachi et al., 2010; Chen et al., 2015b; Zhang et al., 2015b). These that cTnT was more specific and sensitive than miR-1 (Li et al., results were confirmed in the mouse model of MI, with elevated 2014a). Experiments performed in a rat model of MI revealed serum miR-208a levels. However, the expression of miR-499 dysregulation of several miRNAs in the myocardium. Specifically, was significantly reduced in the MI region, whereas miR-208a miR-31, miR-208, and miR-214 were upregulated, and miR-126 remained unchanged in the same area. One explanation is that the and miR-499-5p were downregulated in infarcted rats compared damaged heart might release miR-499 into the circulation (Xiao to sham-operated animals (Ji et al., 2009; Shi et al., 2010). MiR- et al., 2014). Other authors observed a high correlation between 499 has been widely analyzed as a possible biomarker of MI. circulating miRNA-208a in STEMI patients and the levels of cTnI MiR-499 has been reported to be produced almost exclusively in and CK-MB mass liberated from the infarcted zone (Białek et al., the heart and plasma and is significantly increased in individuals 2015). Thus, cardiac miR-208 and miR-499 seemed to be better with AMI (Adachi et al., 2010; Devaux et al., 2012). MiR-499 biomarkers for predicting AMI than miR-1 (Liu et al., 2015b; Liu positively correlates with serum creatine kinase-MB (CK-MB) et al., 2018a). Another study analyzed the expression of miR- and cTnI increasing their diagnostic accuracy (Chen et al., 208a in the myocardium and serum of infarcted rats compared 2015b; Zhang et al., 2015b). Thus, miR-499 might be a suitable to control groups, as well as the expression of cAMP-PKA to Frontiers in Genetics | www.frontiersin.org 14 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases evaluate the effect of this signaling pathway in the primary stages markers (Goldbergova et al., 2018). Moreover, elevated circulating of MI; they found increased expression of miR-208a and cAMP- miR-1254 was described as predicting adverse LV remodeling in PKA. Moreover, the transfection of human myocardial cells STEMI patients when compared to magnetic resonance imaging. with the miR-208a analog significantly increased the amount However, the diagnosis and prognosis values of miR-1254 of cAMP-PKA protein. Thus, higher expression of miR-208a in require further research (de Gonzalo-Calvo et al., 2018). Other the infarcted myocardium and serum may play a role in MI by investigations have described miR-150-3p and miR-486-3p as affecting the cAMP-PKA signaling pathway (Feng et al., 2016). being upregulated, whereas miR-26a-5p, miR-126-3p, and miR- D’Alessandra et al. (2010) investigated plasma levels of miRNAs 191-5p were significantly downregulated in STEMI patients (Hsu in acute STEMI patients and infarcted mice and found higher et al., 2014). In the same manner, circulating miR-19b-3p, miR- levels of miR-1, miR-133a, miR-133b, and miR-499-5p compared 134-5p, and miR-186-5p have been reported to be significantly to controls, whereas miR-122 and miR-375 levels were lower elevated in the initial stages of AMI. The expression of miR- only in STEMI patients. Peak miR-1, miR-133a, and miR-133b 19b-3p and miR-134-5p in the plasma reached a maximum expression correlated with cTnI levels in time, whereas the time earlier than miR-186-5p. However, all three positively correlated course of miR-499-5p was slower (D’Alessandra et al., 2010). This with cTnI and achieved peak expression before cTnI, which was 8 was later confirmed in an exhaustive meta-analysis of relevant h after admission. Interestingly, the expression of these circulating publications (Cheng et al., 2014). Similarly, geriatric patients miRNAs was not altered by heparin and medications for AMI, and with acute NSTEMI had greater miR-499-5p levels, exhibiting the combination of all three miRNAs increased their diagnostic greater precision in diagnosis than cTnT in patients with mild efficacy (Wang et al., 2016b). Moreover, a higher miR-122-5p/133b ST elevation (Olivieri et al., 2013). On the other hand, increased ratio was found in serum from STEMI patients (Cortez-Dias et levels of miR-1, miR-133a, miR-208b, and miR-499 in patients al., 2016). The NSTEMI patients presented higher serum levels of with AMI have been demonstrated to not be superior to cTnT (Li miR-4478, soluble leptin receptor, cTnI, CKMB, urea, creatinine, et al., 2013). The use of miR-133a as a biomarker in reperfused glucose, cholesterol, TG, and ALP but lower levels of ALT STEMI has been evaluated and compared to cardiovascular compared to healthy individuals (Gholikhani-Darbroud et al., magnetic resonance imaging; high levels of miR-133a correlated 2017). Moreover, there was an increase in miR-143 expression with an increased infarct scar size, worse myocardial recovery, in monocytes from STEMI patients, whereas miR-1, miR-92a, and prominent reperfusion injury. Nevertheless, miR-133a miR-99a, and miR-223 expression was significantly reduced. did not add further predictive information to cardiovascular Also, monocytic expression of miR-143 positively correlated with magnetic resonance and conventional markers used in clinical high-sensitivity C-reactive protein (hs-CRP), but not cTnT. These practice in high-risk STEMI patients (Eitel et al., 2012). Moreover, findings demonstrated that circulating monocytes could also be the circulating levels of miR-133a were significantly enhanced in suitable biomarkers (Parahuleva et al., 2017). AMI patients compared to coronary heart disease and myocardial Interestingly, cell-specific miRNA patterns are able to ischemia patients, presenting a similar trend as plasma cTnI distinguish STEMI and NSTEMI patients. A correlation was concentration. Remarkably, we found a positive correlation found between miRNA 30d-5p and plasma, platelets, and between circulating miR-133a levels and the severity of coronary leukocytes in patients with STEMI and NSTEMI. Furthermore, artery stenosis. Thus, circulating miR-133a may be a suitable tool miR-221-3p and miR-483-5p were associated with plasma and for AMI diagnosis and predicting the presence and severity of platelets, but only in NSTEMI patients (Ward et al., 2013). coronary damage in coronary heart disease patients (Wang et al., High levels of plasma miR-134 and miR-328 are described as 2013a). These results were later confirmed (Yuan et al., 2016; Zhu being possible AMI biomarkers, as they correlate with a superior et al., 2018). Nevertheless, in another study analyzing miR-133a risk of developing HF and mortality. However, the miRNA and miR-423-5p and their relationship with cardiac biomarkers, levels were not superior to high-sensitivity cTnT (hs-cTnT) such as B-type natriuretic peptide (BNP), C-reactive protein, concentrations (He et al., 2014). In addition, elevated levels of and cTnI in MI patients, an increase in circulating levels of both miR-19a, miR-22-5p, miR-27a, miR-30a, miR-30a-5p, miR- miRNAs was observed, but these changes were not associated 30d-5p, miR-31, miR-34a, miR-122-5p, miR-125b-5p, miR-133, with LV remodeling or BNP. The authors claimed that miR-133a miR-133b, miR-139-5p, miR-150, miR-181a, miR-195, miR-204, and miR-423-5p are not useful biomarkers of LV remodeling miR-208, miR-208b, miR-221-3p, miR-375, miR-486, miR-497, after MI (Bauters et al., 2013). Another controversial pair of miR-499a-5p, miR-663b, miR-1291, and let-7b can be potential biomarkers is miR-423-5p and miR-30d, which were found to be biomarkers for AMI, increased risk of mortality, or HF (Devaux higher in STEMI patients without a significant correlation with et al., 2012; Long et al., 2012b; Devaux et al., 2013; Li et al., cTnI (Eryılmaz et al., 2016). In addition, the analysis of circulating 2014b; Lv et al., 2014; Peng et al., 2014; Zhong et al., 2014; Han miR-124a and miR-133 in STEMI and cardiogenic shock patients et al., 2015; Yao et al., 2015; Zhang et al., 2015c; Coskunpinar revealed a significant upregulation of both molecules. A negative et al., 2016; Jia et al., 2016; Maciejak et al., 2016; O’Sullivan et al., correlation was found between miR-133 and MMP-9 levels, 2016; Zhu et al., 2016; Liu et al., 2017; Zhang and Xie, 2017; and a relationship between miR-124 and soluble ST2 levels, a Alavi-Moghaddam et al., 2018; Maciejak et al., 2018; Wu et al., marker associated with cardiac damage. Surprisingly, this study 2018a; Wang et al., 2019b). Other potential biomarkers for AMI did not connect any of the miRNAs to the extent of the injury, are downregulated in patients’ plasma, such as miR-99a, miR- disease progression, or the prognosis of patient outcomes. In this 122-5p, and miR-874-3p (Yang et al., 2016a; Yan et al., 2017; case, miRNAs would not bring any benefit compared to current Wang et al., 2019b). Interestingly, high levels of the combination Frontiers in Genetics | www.frontiersin.org 15 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases of miR-21-5p, miR-361-5p, and miR-519e-5p or the reduction protein, which diminished the capacity to produce capillary of miR-519e-5p correlates with cTnI concentrations, significantly tubes and the viability of human umbilical vein endothelial cells increasing the diagnostic accuracy in AMI patients (Wang et al., (HUVECs). Thus, miR-103a may take part in the development of 2014b; Liu et al., 2015a ). Similarly, miR-21 and miR-124 have high blood pressure and the initiation of AMI via regulation of similar diagnostic ability compared to CK, CK-MB, and cTnI Piezo1 expression (Huang et al., 2016a). (Zhang et al., 2016; Guo et al., 2017). In a study based on samples from the HUNT study biobank, In an attempt to predict HF and cardiovascular death after Bye et al. (2016) analyzed the utility of circulating miRNAs to AMI, circulating miR-145, the N-terminal fragment of the predict future fatal AMI in healthy participants. MiR-424-5p and precursor BNP, myocardial-band CK, and cTnI concentrations miR-26a-5p were associated exclusively with risk in men and were analyzed for short- and long-term clinical outcomes. As women, respectively, suggesting a gender-specific association. They a result, the authors concluded that miR-145 was a significant discovered that the best model for predicting future AMI consisted independent predictor of cardiac events, predicting long-term of miR-106a-5p, miR-424-5p, let-7g-5p, miR-144-3p, and miR- outcomes after AMI (Dong et al., 2015). Later, another group 660-5p, and these miRNAs were proposed as a panel to enhance found that miR-145 levels were significantly lower in AMI the prediction of AMI risk in healthy individuals (Bye et al., 2016). patients and correlate with increased serum BNP and cTnT and Platelet activation is critical for AMI pathogenesis, but the role decreased LV ejection fraction (Zhang et al., 2017b). of platelet miRNAs (pmiRNAs) as biomarkers in AMI and their An miRNA array revealed differences in the miRNA correlation with indices of platelet activity are unclear. Assessment expression patterns in patients with different phases of HF after of pmiR-126 expression in STEMI patients revealed reduced MI. Specifically, human miR-369-3p, miR-433, miR-493-5p, levels and a correlation with plasma cTnI. However, pmiR-126 miR-495, and miR-3615 were overexpressed, whereas miR- expression did not correlate well with platelet activity indices, and 877-3p, miR-1306-3p, hsv1-miR-H2, miR-3130-5p, and hcmv- its potential diagnostic utility is limited (Li et al., 2017b). miR-UL22A were underexpressed in these patients. Thus, these MiR-1, miR-133a, and miR-34a induce adverse structural circulating miRNAs are novel candidates as biomarkers of MI remodeling to impair cardiac contractile function. Increased levels and HF (Liang et al., 2015). of all three miRNAs have been shown in the hearts of old MI mice An important aspect of circulating miRNAs as biomarkers compared to young MI mice, and the miR-1 increase was more is their temporal release, source, and transportation. Using prolonged and corresponded to LV wall thinning. This suggests the ischemia–reperfusion injury model, Deddens et al. (2016) that significantly increased levels of miR-1 in the aged post-MI showed that the ischemic myocardium releases extracellular heart could be a biomarker for high-risk prediction (Qipshidze vesicles. They also demonstrated that these extracellular vesicles Kelm et al., 2018). In addition, miRNA-21 has been reported to transported specific miRNAs from the heart and muscle and be overexpressed in the serum of ancient patients with AMI and were quickly detected in plasma. Interestingly, these vesicles to positively correlate with serum levels of CK-MB and cTnI. In had a high miRNAs content and rapid detection compared to vitro experiments with human cardiomyocytes transfected with traditional injury markers. This makes them a promising tool for the miR-21 mimic short hairpin RNA have shown that, following the early detection of MI (Deddens et al., 2016). Along the same tumor necrosis factor α (TNF-α) induction, apoptosis rates are lines, microparticles and the expression levels of miR-92a were downregulated. The upregulation of miR-21 expression in the serum investigated in AMI and stable coronary artery disease patients of elderly patients with AMI inhibited apoptosis induced by TNF-α and compared to cTnI. The number of microparticles and in human cardiomyocytes via activation of the JNK/p38/caspase-3 expression levels of miR-92a were higher in AMI patients than signaling pathway (Wang et al., 2017b). Along the same lines, in the stable coronary artery disease patients and control groups, cardiomyocyte apoptosis and hypoxic reduction of cell growth can with a positive correlation between the levels of microparticles be promoted by miR-23b overexpression, suggesting that it could be and cTnI. Thus, microparticles containing miR-92a may be a potential biomarker for STEMI (Zhang et al., 2018a). suitable for MI diagnosis and possibly regulate dysfunctional A recent study explored the diagnostic use of circulating endothelial tissue in AMI patients (Zhang et al., 2017c). However, miRNAs in patients with acute chest pain in the emergency according to Grabmaier et al. (2017), miR-92a seems to not be a department. They found that higher circulating miR-19b, miR- good biomarker of adverse ventricular remodeling in post-AMI 223, and miR-483-5p levels may be clinically useful for AMI patients. The authors evaluated circulating miR-1, miR-21, miR- diagnosis in early phases (Li et al., 2019). Similarly, circulating 29b, and miR-92a from the SITAGRAMI trial population and miR-17-5p, miR-126-5p, and miR-145-3p levels are elevated found that miR-1, miR-21, and miR-29b expression was higher in in plasma from AMI patients. Combining these three miRNAs AMI patients. The levels of miR-1 and miR-29b in plasma post- achieves a more precise AMI diagnosis (Xue et al., 2019). AMI correlated with variations in infarct volume, and the levels Interestingly, next-generation miRNA sequencing from whole of miR-29b and changes in LV ejection fraction over time were blood samples has been useful for identifying new biomarkers of also associated (Grabmaier et al., 2017). MI (Kanuri et al., 2018). Investigation of the expression of miR-103a in AMI patients with and without high blood pressure and the effect on endothelial cell function revealed increased levels of miR-103a Heart Failure in all patients but no changes in peripheral blood mononuclear Heart failure is a chronic and progressive condition that hampers cells. Moreover, miR-103a suppressed the expression of Piezo1 the ability of the heart to pump enough blood to the body and Frontiers in Genetics | www.frontiersin.org 16 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases fulfill its needs. Heart failure is caused by multiple disorders, such the gene activity (Gorski et al., 2019). All of this knowledge as hypertension, cardiomyopathy, MI, arrhythmias, or valvular would be fundamental to identifying potential biomarkers and diseases, among others (Khatibzadeh et al., 2013). Numerous new epigenetic drugs in HF therapy. Interestingly, an association scientific reports connect HF and epigenetic modifications has been reported between epigenetic remodeling in the atrial (Table 4 and Figure 3). High-density epigenome-wide mapping natriuretic peptide (ANP) and BNP promoters and reactivation of DNA methylation in the myocardium and blood from of the fetal gene program in HF. Their reported upregulation in dilated cardiomyopathy patients and healthy individuals has HF patients did not respond to an increase in histone acetylation been analyzed. This technology has been used to find regions but HDAC4, which is exported from the nucleus. In contrast, of epigenetic susceptibility and new biomarkers related to HF demethylation of H3K9 and dissociation of heterochromatin and heart dysfunction; they recognized different patterns of protein 1 from gene promoters were regulated by HDAC4. epigenetic methylation that were preserved through tissues—the Thus, HDAC4 is fundamental to histone methylation in HF CpGs regions identified as novel biomarkers of HF (Meder et al., caused by increased cardiac load and a potential target for 2017; Rau and Vondriska, 2017). Differentially methylated DNA treatment (Hohl et al., 2013). More recently, Glezeva et al. regions were also identified in blood leukocytes from HF patients (2019) performed targeted DNA methylation sequencing to (Li et al., 2017a). Dilated cardiomyopathy is an important cause of detect DNA methylation alterations in coding and ncRNA in HF. Genome-wide cardiac DNA methylation in idiopathic dilated cardiac interventricular septal tissue from HF patients. They cardiomyopathy patients revealed abnormal DNA methylation, found hypermethylation in HEY2, MSR1, MYOM3, COX17, which was related to important variations in the expression of and miR-24-1 and hypomethylation in CTGF, MMP2, and miR- lymphocyte antigen 75 (LY75) and adenosine receptor A2A 155. Therefore, they defended a unique cohort of loci useful as (ADORA2A) mRNA (Haas et al., 2013). Similarly, genome-wide diagnostic and therapeutic targets in HF (Glezeva et al., 2019). maps of DNA methylation and enrichment of histone 3 lysine-36 More than 10 years ago, few reports suggested that specific trimethylation (H3K36me3) in pathological and healthy hearts miRNAs are differentially regulated in the failing heart were analyzed. Differences in DNA methylation were found (Divakaran and Mann, 2008; Small and Olson, 2011). Since in promoter CpG islands, genes, intragenic CpG islands, and then, an extensive evidence base has been published in the H3K36me3-rich regions of the genome. The promoters of literature regarding the use of miRNAs as possible biomarkers upregulated genes had altered DNA methylation, but not the for HF diagnosis and prognosis. In evaluating whether miRNAs promoters of downregulated genes. In particular, an abundance can differentiate clinical HF from healthy individuals and from of DUX4 transcripts was associated with differences in DNA non-HF dyspnea, miRNA arrays have revealed miR423-5p methylation and H3K36me3 enrichment. Although further enrichment in the blood of HF patients (Tijsen et al., 2010). studies need to be carried out, there is evidence that the expression However, criticisms have been raised in this study regarding age of genes critical for the development of cardiomyopathies differences between groups, reduced sample size, and statistics may be controlled by the epigenome (Movassagh et al., 2011). (Kumarswamy et al., 2010). Moreover, patients with HF of Moreover, in patients with dilated cardiomyopathy, there is an different etiologies presented with different expression levels of altered methylation pattern in the regulatory regions of cardiac circulating miRNAs. Ischemic HF patients were found to have development genes, such as T-box protein 5 (TBX5), heart a positive transcoronary gradient for miR-423-5p, miR-423, and neural crest derivatives expressed 1 (HAND1), and NK2 and miR-34a, but the nonischemic HF group was positive only homeobox 5 (NKX2.5) (Jo et al., 2016). Koczor et al. (2013) also for miR-21-3p and miR-30a. The transcoronary concentration studied the differential methylation patterns in patients with gradient suggests that the failing heart may selectively release the dilated cardiomyopathy, which is characterized by congestive HF. miRNAs into the coronary circulation. These miRNAs could be Computational analysis detected few differentially methylated useful for discriminating different etiologies of HF (Goldraich gene promoters (AURKB, BTNL9, CLDN5, and TK1). This et al., 2014; De Rosa et al., 2018). study provides relevant information on DNA methylation and Circulating miRNAs have been screened in an attempt to altered expression in dilated cardiomyopathy that would help in identify any that could be used for the prognosis of ischemic HF treatment (Koczor et al., 2013). in post-AMI patients. Knowing that p53 has been involved in HF Furthermore, epigenetic modifications have been proposed to development in mice (Sano et al., 2007), the authors took great play an important role in HF progression in the murine model interest in p53-responsive miRNAs. The serum levels of miR- of pressure overload. The researchers observed a reduction 34a, miR-192, and miR-194 were significantly and coordinately in sarcoplasmic reticulum Ca2+ATPase (Atp2a2) levels and a upregulated in AMI patients with ischemic HF progression, significant induction of β-myosin-heavy chain (Myh7) mRNA and all three were p53-responsive. Interestingly, these miRNAs levels. They also detected H3K4me2, H3K9me2, H3K27me3, and were contained in extracellular vesicles, suggesting that they are H3K36me2 and a reduction in the lysine-specific demethylase circulating regulators of HF. Furthermore, there was a significant KDM2A after 8 weeks of transverse aortic constriction correlation between the LV end-diastolic dimension 1 year after (Angrisano et al., 2014). Atp2a2 is a determinant of cardiac AMI and the miR-194 and miR-34a expression levels. Thus, function, and its reduced activity is a clear feature of HF. Gorski although further investigations are needed, these results suggest et al. (2019) investigated the role of lysine acetylation in Atp2a2 the usefulness of miR-34a, miR-192, and miR-194 in predicting function in HF patients and found that acetylation at lysine 492 the risk of HF progression after AMI (Evans and Mann, 2013; is regulated by SIRT1 and HAT p300 and significantly reduced Matsumoto et al., 2013; Klenke et al., 2018). Frontiers in Genetics | www.frontiersin.org 17 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases TABLE 4 | Epigenetic biomarkers in heart failure. Epigenetic Biomarker Regulation in heart Sample source Study type References modification failure DNA LY75 and ADORA2A Aberrant DNA methylation Left ventricle Clinical and (Haas et al., 2013) methylation myocardium and experimental: zebrafish zebrafish TBX5, HAND1, and NKX2.5 Altered DNA methylation Myocardium Clinical (Jo et al., 2016) HEY2, MSR1, MYOM3, HEY2, MSR1, MYOM3, Myocardium Clinical (Glezeva et al., 2019) COX17, miR-24-1, CTGF, COX17, and miR-24-1: MMP2, miR-155 hypermethylation; CTGF, MMP2, and miR-155: hypomethylation Histone H3K36me3 H3K36me3 enhancement Myocardium Clinical (Movassagh et al., 2011) modifications HDAC4 HDAC4 activation Myocardium Clinical and (Hohl et al., 2013) experimental: mouse model of pressure overload H3K4me2, H3K9me2, H3K4me2, H3K9me2, Myocardium Experimental: mouse (Angrisano et al., 2014) H3K27me3, H3K36me2, H3K27me3, and model of pressure KDM2A H3K36me2 methylation overload and KDM2A reduction Atp2a2 Atp2a2 acetylation Ventricular myocytes Clinical and (Gorski et al., 2019) and myocardium experimental: mouse model of pressure overload in MHC- SIRT1−/− Tg mice and swine model of MI miRNA miR423-5p Higher levels Plasma Clinical (Tijsen et al., 2010) miR-192 Upregulation Serum Clinical (Matsumoto et al., 2013) miR-122*, miR-200b, miR-122*, miR-200b, Whole peripheral blood Clinical (Vogel et al., 2013) miR-520d-5p, miR-622, miR-520d-5p, miR-622, miR-1228*, miR-558 miR-1228*: upregulation; miR-558: downregulation miR-103, miR-142-3p, Differentially expressed Plasma Clinical (Ellis et al., 2013) miR-30b, miR-342-3p miR-210, miR-30a Upregulation Serum Clinical (Zhao et al., 2013) miR-210 Higher levels Plasma, mononuclear Clinical and (Endo et al., 2013) cells, and skeletal experimental: Dahl salt- muscles sensitive rats miR-1 Higher levels Plasma Clinical (Zhang et al., 2013b) miR-423-5p Positive transcoronary Transcoronary gradients Clinical (Goldraich et al., 2014) gradients miR-423-5p Lower levels Plasma Clinical (Seronde et al., 2015) MiR-30c, miR-146a, miR- Downregulation Serum Clinical (Watson et al., 2015) 221, miR-328, miR-375 miR-21, miR-650, miR-744, miR-21, miR-650, miR-744, Serum Clinical (Cakmak et al., 2015) miR-516-5p, miR-1292, miR-516-5p, miR-1292, miR-182, miR-1228, miR- miR-182, miR-1228, miR- 595, miR-663b, miR-1296, 595, miR-663b, miR-1296, miR-1825, miR-299-3p, miR-1825, miR-299-3p, miR-662 miR-122, miR-662 miR-122, miR-3148, miR-518e, miR- miR-3148, miR-518e: 129-3p, miR-3155, miR- increased; miR-129-3p, 3175, miR-583, miR-568, miR-3155, miR-3175, miR- miR-30d, miR-200a-star, 583, miR-568, miR-30d, miR-1979, miR-371-3p, miR-200a-star, miR-1979, miR-155-star, miR-502-5p miR-371-3p, miR-155-star, miR-502-5p: decreased miR-1233, miR-671-5p, miR-1233, miR-671-5p: Whole blood and Clinical (Wong et al., 2015) miR-183-3p, miR-190a, Upregulation; miR-183-3p, plasma miR-193b-3p, miR- miR-190a, miR-193b-3p, 193b-5p, miR-211-5p, miR-193b-5p, miR-211-5p, miR-494 miR-494: downregulation (Continued) Frontiers in Genetics | www.frontiersin.org 18 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases TABLE 4 | Continued Epigenetic Biomarker Regulation in heart Sample source Study type References modification failure miR-1, miR-21 miR-1: downregulation; Serum Clinical (Sygitowicz et al., 2015) miR-21: upregulation miR-126 Downregulation Serum Clinical (Wei et al., 2015) miR-1, miR-21, miR-23, Upregulation Myocardial biopsy Clinical (Lai et al., 2015) miR-29, miR-130, miR-195, miR-199 miR-106a-5p, miR-223-3p, Downregulation Plasma Clinical (Vegter et al., 2016) miR-652-3p, miR-199a-3p, miR-18a-5p miR-148b-3p, miR-409-3p Downregulation Serum and left atrial Clinical (Chen et al., 2016) tissue miR-122-5p, miR-184 Upregulation H9C2 cells and blood Experimental: in vitro (Liu et al., 2016) and myocardium and rat model of post-MI HF miR-660-3p, miR-665, Upregulation Plasma and heart Clinical (Li et al., 2016) miR-1285-3p, miR-4491 miR-18a-5p, miR-26b-5p, Lower levels Plasma Clinical (Ovchinnikova et al., miR-27a-3p, miR-30e-5p, 2016) miR-106a-5p, miR- 199a-3p, miR-652-3p miR-19b Lower levels Serum and myocardial Clinical and (Beaumont et al., 2017) experimental: in vitro miR-30d Lower levels Serum Clinical (Xiao et al., 2017) miR-195-3p Higher levels Plasma Clinical (He et al., 2017) miR-22-3p Higher levels Blood Clinical (van Boven et al., 2017) miR-150-5p Downregulation Blood Clinical (Scrutinio et al., 2017) miR-133b-3p, miR- Upregulation Blood Experimental: sheep (Wong et al., 2017) 208b-3p, miR-125a-5p, model of HF miR-125b-5p, miR-126-3p, miR-21-5p, miR-210-3p, miR-29a-3p, miR-320a, miR-494-3p miR-146a Upregulation Exosomal and total Clinical and (Beg et al., 2017) plasma experimental: in vitro miR-9, miR-495, miR-599, ex-miR-9, ex-miR-181c, Exosomal and total Experimental: dogs (Yang et al., 2017b) miR-181c ex-miR-495: increased; plasma with myxomatous mitral ex-miR-599: decreased valve disease, mitral valve prolapse miR-21-5p, miR-23a-3p, Higher levels Plasma Clinical and (Dubois-Deruy et al., miR-222-3p experimental: rat model 2017) of post-MI HF miRNA-21 Higher levels Serum Clinical (Zhang et al., 2017a) miR-132 Higher levels Plasma Clinical (Masson et al., 2018) miR-1254, miR-1306-5p Higher levels Blood Clinical (Bayés-Genis et al., 2018) miR-423, miR-34a, miR- miR-21-3p, miR-30a: Transcoronary gradients Clinical (De Rosa et al., 2018) 21-3p, miR-30a Positive transcoronary gradient in non-ischemic HF; miR-423, miR-34a: Negative transcoronary gradient in ischemic HF miR-3135b, miR-3908, Upregulation Plasma Clinical (Chen et al., 2018a) miR-5571-5p miR-302b-3p Higher levels Plasma Clinical (Li et al., 2018a) exo-miR-92b-5p increased Serum Clinical (Wu et al., 2018c) miR-26b, miR-208b, Higher levels Peripheral blood Clinical (Marketou et al., 2018) miR-499 mononuclear cells miR-423-5p, miR-221-5p, Upregulation Plasma, mouse Clinical and (Shah et al., 2018b) miR-212-5p, miR-193b-5p, myocardium and experimental: in vitro, miR-15a-5p, miR-208a-3p NRVMs cells and murine model of hypertrophy and HF miR-192 Upregulation Serum Clinical (Klenke et al., 2018) (Continued) Frontiers in Genetics | www.frontiersin.org 19 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases TABLE 4 | Continued Epigenetic Biomarker Regulation in heart Sample source Study type References modification failure miR-34a, miR-208b, miR- miR-34a, miR-208b, miR- Serum Clinical (Lakhani et al., 2018) 126, miR-24, miR-29a 126: upregulation; miR-24, miR-29a: downregulation miR-17, miR-20a, Lower levels Plasma Clinical (Shah et al., 2018a) miR-106b miR-197-5p Upregulation Plasma Clinical (Liu et al., 2018b) miR-133a, miR-221 Higher levels Plasma Clinical (Guo et al., 2018) exo-miR-92b-5p Higher levels Serum Clinical (Wu et al., 2018b; Wu et al., 2018c) Vogel et al. (2013) assessed the genome-wide miRNA miR-744, miR-1228, miR-1292, miR-1296, miR-1825, and miR- expression profiles in HF patients with reduced ejection 3148 and decreased expression of miR-30d, miR-129-3p, and fraction (HFrEF). They demonstrated that dysregulated levels miR-502-5p, miR-155-star miR-200a-star, miR-371-3p, miR-583, of miRNAs, such as miR-122*, miR-200b, miR-520d-5p, miR- miR-568, miR-1979, miR-3155, and miR-3175. Among these 622, miR-1228* (upregulated), or miR-558 (downregulated) miRNAs, miR-182 seemed to have a better prognostic value than significantly correlate with disease severity, as indicated by hs-CRP (Cakmak et al., 2015). Furthermore, miR-30c, miR-146a, LV ejection fraction (Vogel et al., 2013). Moreover, Ellis et al. miR-221, miR-328, and miR-375 had different expression levels (2013) tried to find differences between HF patients and non– in HFrEF and HFpEF. The combination of two or more miRNAs HF-related breathlessness, and between HFrEF and HF with with BNP could significantly improve the discrimination of these preserved ejection fraction (HFpEF); although they found a pathological conditions compared to BNP alone (Watson et al., differential expression of miR-103, miR-142-3p, miR-30b, and 2015). Additional miRNAs have been identified as promising miR-342-3p in HF and breathless patients, individually, classical biomarkers to discriminate HF from healthy individuals biomarkers such as NT-proBNP and hs-cTnT exhibited greater and to differentiate HFrEF from HFpEF: miR-125a-5p, miR- sensitivity and specificity. However, the combination of miRNAs 183-3p, miR-190a, miR-193b-3p, miR-193b-5p, miR-211-5p, with NT-proBNP significantly improved prediction performance miR-494, miR-545-5p, miR-550a-5p, miR-638, miR-671-5p, (Ellis et al., 2013). Similarly, elevated plasma levels of miR-210 miR-1233, miR-3135b, miR-3908, and miR-5571-5p. The use were reported in congestive HF patients, although no significant of a combination of miRNAs and NT-proBNP increases its correlation was observed with BNP. However, patients with discernment capacity (Schulte et al., 2015; Wong et al., 2015; Chen an improved BNP profile presented with low plasma miR- et al., 2018a). Similarly, increased levels of miR-133a and miR- 210 levels. MiR-210 might reflect a mismatch between heart 221 can be used as suitable HF diagnostic biomarkers in elderly contraction and oxygen demand in the peripheral tissues (Endo HF patients, and the combination of NT-proBNP and miR-133a et al., 2013). Interestingly, miR-210 and miR-30a expression is can improve the diagnostic accuracy (Guo et al., 2018). Serum upregulated in HF patients, with a tendency toward fetal values levels of miR-1, miR-21, and miR-208a have also been analyzed (Zhao et al., 2013). Moreover, changes in myocardial miRNA in symptomatic HF patients. Expression of miR-1 is reduced in patients with stable and end-stage HF partially resemble the in symptomatic HF patients, with decreasing levels correlating fetal myocardium. Target mRNA levels negatively correlate with with increasing severity. In contrast, miR-21 has been shown to changes in highly expressed miRNAs in HF and fetal hearts. The be overexpressed with no relation to HF severity. No circulating circulation is dominated by miRNAs, fragments of tRNAs, and miR-208a has been observed in symptomatic HF patients. A small cytoplasmic RNAs. Heart- and muscle-specific circulating negative correlation between miR-1 expression and NT-proBNP miRNAs (myomirs) are also increased in advanced HF, correlating has been reported in HF patients, whereas miR-21 and galectin-3 with cTnI levels. These findings support miRNA-based therapies have been positively correlated. Therefore, dysregulated levels and the use of circulating miRNAs as biomarkers for heart injury of miR-1 and miR-21 may be fundamental for HF progression (Akat et al., 2014). Cardiac fibroblast–derived miRNAs, such as (Sygitowicz et al., 2015). An inverse correlation between miR-1 miR-660-3p, miR-665, miR-1285-3p, and miR-4491, have also levels and ejection fraction has also been reported. Thus, elevated been found to be significantly upregulated in heart and plasma levels of miR-1 may inhibit cardiac function and be a predictor of during HF, discriminating patients from controls (Li et al., the onset of HF secondary to AMI (Zhang et al., 2013b). 2016). However, miRNAs in the pericardial fluid are not related MiR-126 has also been studied in atrial fibrillation and/or HF to cardiovascular pathologies or clinically assessed stages of HF. patients, with downregulated expression in patients and positive MicroRNAs may be paracrine signaling factors that intervene in correlation with LV ejection fraction but a negative association cardiac cells crosstalk (Kuosmanen et al., 2015). with the cardiothoracic ratio and NT-proBNP. Thus, the reduction In another study performed in patients with chronic in miR-126 expression is a potential indicator of severity in atrial congestive HF, microarray profiling demonstrated increased fibrillation and HF (Wei et al., 2015). A significant negative expression of miR-21, miR-122, miR-182, miR-299-3p, miR- correlation has also been found between several miRNAs 516-5p, miR-518e, miR-595, miR-650, miR-662, miR-663b, and classical clinical biomarkers indicative of a worse clinical Frontiers in Genetics | www.frontiersin.org 20 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases outcome in HF patients. MiR-16-5p has been correlated to CRP, miR-125b-5p, miR-126-3p, miR-133b-3p, miR-195-3p, miR- miR-106a-5p to creatinine, miR-223-3p to growth differentiation 197-5P, miR-208b-3p, miR-210-3p, miR-302b-3p, miR-320a, factor 15, miR-652-3p to soluble ST-2, miR-199a-3p to and miR-494-3p (Zhang et al., 2013b; He et al., 2017; van Boven procalcitonin and galectin-3, and miR-18a-5p to procalcitonin et al., 2017; Wong et al., 2017; Xiao et al., 2017; Zhang et al., (Vegter et al., 2016). Furthermore, an analysis of myocyte and 2017a; Li et al., 2018a; Liu et al., 2018b;) or decreased levels of fibroblast-related miRNAs and mRNAs in myocardium samples miR-17, miR-18a-5p, miR-20a, miR-150, miR-26b-5p, miR- from HF patients and control individuals revealed that miR-1, 27a-3p, miR-30e-5p, miR-106a-5p, miR-106b, miR-150-5p, miR- miR-21, miR-23, miR-29, miR-130, miR-195, and miR-199 are 199a-3p, miR-423-5p, and miR-652-3p (Seronde et al., 2015; significantly upregulated in HF patients, whereas miR-30, miR- Ovchinnikova et al., 2016; Scrutinio et al., 2017; Shah et al., 2018a; 133, miR-208, and miR-320 do not significantly change. Related Lin et al., 2019) have been described as potential biomarkers in mRNAs, such as caspase 3, collagenase I, collagenase III, and HF patients. These discoveries may serve to develop miRNA- transforming growth factor (TGF), are also upregulated in HF based therapies and to identify new pharmacological targets. patients. MicroRNAs involved in apoptosis, hypertrophy, and Beg et al. (2017) measured exosomal and total plasma fibrosis are upregulated in the myocardium of HF patients and miRNAs separately in HF patients to distinguish between the may be suitable biomarkers in the early stages of chronic HF and transfer of biological materials for signaling alteration in distant future therapeutic targets (Lai et al., 2015). organs (exosomal) and the level of tissue damage (plasma). They Evaluation of miR-148b-3p and miR-409-3p in mitral found that the circulating exosomal miR-146a/miR-16 ratio was regurgitation patients, asymptomatic mitral regurgitation higher in HF patients, with miR-146a induced in response to patients, and controls revealed that circulating and tissue inflammation. These results suggest circulating exosomal miR- miR-148b-3p and circulating miR-409-3p are significantly 146a as a biomarker of HF (Beg et al., 2017). Moreover, elevation downregulated in mitral regurgitation patients with HF, and of exosomal miRNA exo-miR-92b-5p has been suggested as a miR-148b-3p is significantly downregulated only in the mitral potential biomarker for the diagnosis of HF (Wu et al., 2018b; regurgitation patients without HF. Notably, the mRNAs of target Wu et al., 2018c). In a preclinical study in dogs with myxomatous genes of both miRNAs have been shown to be upregulated in mitral valve disease, dysregulation of exosomal miR-9, miR- HF patients with mitral regurgitation. Thus, circulating miR- 495, and miR-599 was observed as the dogs aged. In addition, 148b-3p may be used as a biomarker of HF and miR-409-3p for levels of miR-9, miR-599, miR-181c, and miR-495 changed in incident HF in mitral regurgitation patients (Chen et al., 2016). myxomatous mitral valve disease. Thus, the exosomal miRNA Specific overexpression of miR-221 in the hearts of transgenic expression level appears to be more specific to disease states mice has been shown to induce cardiac dysfunction and HF by than total plasma miRNA (Yang et al., 2017b). Furthermore, the impairing autophagy. In addition, in vitro miR-221 upregulation downregulation of miR-425 and miR-744 in the plasma exosomes inhibits autophagic vesicle formation. Thus, autophagy balance has been shown to induce cardiac fibrosis by suppressing TGFβ1 and cardiac remodeling are regulated by miR-221 levels through expression (Wang et al., 2018a). modulation of the p27/CDK2/mTOR axis, and miR-221 might Circulating miR-132 levels increased in chronic HF with be a therapeutic target in HF (Su et al., 2015). Furthermore, disease severity, and lower levels improve risk prediction for HF high-throughput sequencing has been used to determine the readmission beyond traditional risk factors, but not for mortality. differential miRNA pattern in a rat model of post-MI HF. MiR-132 may be useful for finding strategies that would reduce Upregulation of miR-122-5p and miR-184 was found in HF rats, rehospitalization in HF patients (Masson et al., 2018; Panico and describing a proapoptotic role of both miRNAs (Liu et al., 2016). Condorelli, 2018). Moreover, in an exhaustive analysis of two In another study using the same model, the authors identified a independent cohorts using a strict quality evaluation for miRNA significant increase in miR-21-5p, miR-23a-3p, and miR-222-3p testing, an association was found between high levels of miR- and their target SOD2 in the plasma and myocardium of HF 1254 and miR-1306-5p and mortality and HF hospitalization in rats. They showed a direct interaction between miR-222-3p and HF patients. However, these two circulating miRNAs were not SOD2. An inhibition or increase in SOD2 expression was found shown to improve standard predictors of prognostication, such when human cardiomyocytes were transfected with miR-222-3p as age, sex, hemoglobin, renal function, and NT-proBNP (Bayés- mimic or inhibitor, respectively (Dubois-Deruy et al., 2017). Genis et al., 2018). Myocardial fibrosis–related miRNAs, such as miR-19b, are MiR-26b, miR-208b, and miR-499 expression levels have been reduced in the myocardium and serum of HF patients with aortic assessed in peripheral blood mononuclear cells from hypertensive stenosis. Inhibition of miR-19b in cultured human fibroblasts HFpEF patients to evaluate their association with their exercise increases the expression of connective tissue growth factor capacity. All three miRNAs were expressed at higher levels in the protein and the enzyme lysyl oxidase (LOX). This could lead to patients group, but miR-208b showed the strongest correlations excessive collagen fibril cross-linking and a subsequent increase with cardiopulmonary exercise test parameters, including oxygen in LV stiffness in aortic stenosis patients, particularly those with uptake, exercise duration, and the minute ventilation–carbon HF. Thus, miR-19b could be a biomarker of alterations in the dioxide production relationship (Marketou et al., 2018). In a myocardial collagen network (Beaumont et al., 2017). study performed in patients and a mice model of hypertrophy Numerous studies have been performed to find miRNAs with and HF, miRNAs dysregulation was shown to occur during HF a predictive value in HF patients. Increased levels of miR-1, miR- development in animals, with downregulation of target genes. 21, miR-21-5p, miR-22-3p, miR-29a-3p, miR30d, miR-125a-5p, These miRNAs were associated with adverse LV remodeling in Frontiers in Genetics | www.frontiersin.org 21 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases humans, suggesting coordinated regulation of miRNA-mRNA. et al., 2012; Wong et al., 2014). In other cases, it is important to They also revealed target clusters of genes, such as autophagy, carefully adjust the protocol. It is also important to consider that metabolism, and inflammation, implicated in HF mechanisms, frozen and paraffin-preserved samples may have different results, (Shah et al., 2018b). and they should not be compared without appropriate correction With the intention to establish a biomarkers panel useful for (García-Giménez et al., 2017). early detection of HF resulting from MI, Lakhani et al. (2018) Among the epigenetic biomarkers, miRNAs are the most found significant upregulation of miR-34a, miR-208b, miR- promising, and numerous studies have been carried out in the 126, TGFβ-1, TNF-α, IL-6, and MMP-9 and reduced miR-24 last few years. The relatively easy detection and accessibility to and miR-29a levels. A positive association between IL-10 and samples in fluids, such as blood, urine, or saliva, make them very ejection fraction in MI patients also suggested an important role attractive. However, a few issues should be solved before their of IL-10 in predicting HF (Lakhani et al., 2018). implementation in the clinical practice. The main problem is that Systems biology analyses of LV remodeling after MI allow miRNAs usually target multiple mRNAs from different genes, molecular comprehensions; for example, miRNA modulation and one gene can be targeted by several miRNAs. This complex may be used as a marker of HF evolution. Two systems biology network should be deeply investigated before determining the strategies were used to define an miRNA mark of LV remodeling use of a specific miRNA as a biomarker for the diagnosis or in MI. They integrated either multiomics data (proteins and treatment of a particular disease (Akhtar et al., 2016). Regarding ncRNAs) produced from post-MI plasma or proteomic data sample preparation, it is highly recommended to use plasma generated from a rat model of MI. As a result, several miRNAs instead of whole blood, because if it is hemolyzed, the circulating were associated with LV remodeling: miR-21-5p, miR-23a-3p, miRNA content can be altered. Increasing the centrifugation miR-222-3p, miR-17-5p, miR-21-5p, miR-26b-5p, miR-222-3p, time is also important in order to reduce platelet contamination miR-335-5p, and miR-375. These outcomes support the use of (de Gonzalo-Calvo et al., 2017; García-Giménez et al., 2017). integrative systems biology analyses for the definition of miRNA Recently, great advances have been made to implement the marks of HF evolution (Charrier et al., 2019). new technology in the detection of new epigenetic biomarkers. However, a few concerns should be alleviated before their clinical implementation. Studies with big cohorts in different independent LIMITATIONS AND PERSPECTIVES OF laboratories, using the same experimental design, sample THE EPIGENETIC BIOMARKERS preparation, methodology, and disease specifications, are necessary. Small patient cohorts should be considered as pilot studies before Limitations of the current field include the lack of large the validation of results in bigger sample analysis. The method multicenter studies to provide convincing evidence for clinical of detection should be standardized for clinical application, applicability. Rather than a single ncRNA, it is likely that there and the clinical trials have to be randomized and prospective. will be patterns of different ncRNAs and other biomarkers (e.g., It is also important to compare the new biomarkers with the protein-based) that, together with machine-learning algorithms, classical biomarkers in order to validate them and determine their will provide more sensitive and specific diagnostic and prognostic usefulness. The sensitivity and specificity for a certain disease also approaches to CVDs. Also, several technical challenges must be have to be determined for each biomarker (Engelhardt, 2012; overcome before CE-marked ncRNA biomarkers will enter the García-Giménez et al., 2017). Regarding the method of DNA clinical realm. DNA methylation and histone modifications are methylation detection, the luminometric methylation assay and the epigenetic mechanisms that have been reported to be sources of methylation analysis of CpG islands in repeatable elements (LINE-1) potential biomarkers useful in clinical practice. However, each are widely used. Although there is a certain correlation with the CVD is regulated by multiple epigenetic pathways, and different measurements obtained with both methods, the comparison is not CVDs are regulated by the same epigenetic mechanism, most of recommended, since a consistent bias between the results has been which are still under study. For example, hypermethylation of described (Knothe et al., 2016). Interestingly, a large multicenter H3K79 (Rodriguez-Iturbe, 2006; Duarte et al., 2012) and ACE2 study comparing DNA methylation assays compatible with routine promoter (Fan et al., 2017) in hypertensive patients has been clinical use has been performed. According to the authors, good described. Moreover, H3K4 and H3K9 were also hypermethylated agreement was observed between DNA methylation assays, which in both mouse models of hypertension (Pojoga et al., 2011) and can be implemented in large-scale validation studies, development HF (Angrisano et al., 2014). This makes it difficult to select and of new biomarkers, and clinical diagnostics (BLUEPRINT implement a set of biomarkers for a particular CVD. Another Consortium, 2016). The most used system to detect miRNAs is potential problem is the quality of the samples, especially those quantitative PCR, being the normalization protocol critical. Most obtained from collections in the pathology department. These laboratories use housekeeping genes or miRNAs as normalizers, samples are usually preserved in formaldehyde and paraffin, changing their expression levels within serums. Another approach which highly degrades DNA. The stability, size, and integrity employs identical volumes of serum for all samples, generating of a sample depend on the duration of fixation and storage different amounts of total RNA (Chen et al., 2008; Wang et al., (Kristensen et al., 2009). Thus, assessment of the quality of 2009; Rockenbach et al., 2012). Both approaches include spike-in DNA is fundamental. However, the DNA methylation analysis normalization, which consists of adding RNA of known sequence can be performed successfully using polymerase chain reaction and quantity to calibrate measurements. However, spike-in (PCR) methods with small amplicons in old samples (Tournier normalization does not consider internal variation in circulating Frontiers in Genetics | www.frontiersin.org 22 October 2019 | Volume 10 | Article 950 Soler-Botija et al. Epigenetic Biomarkers in Cardiovascular Diseases miRNA between different individuals. Thus, a combination of with multiple research centers and a big sample size, mandatory. both methods should always be performed to guarantee results All of this will lead to a standardized clinical application in the reliability (van Empel et al., 2012). Polymerase chain reaction near future. technology has to be performed with rigorous controls to avoid artifacts in the amplification step. To overcome this problem, digital PCR based on the amplification of one single molecule AUTHOR CONTRIBUTIONS per reaction constitutes a valuable option (Hindson et al., 2013). Another attractive alternative for accurate measuring RNAs is the CS-B and AB-G conceived the idea and wrote the manuscript direct nucleic acid sequencing, although it is still expensive when with support from CG-M. CG-M performed the drawings and considering large screening analysis (Kozomara and Griffiths- structure of the figures. All authors contributed to manuscript Jones, 2011). Finally, it is also important to understand the revision, read and approved the submitted version. processes controlling miRNAs release and stability. The correlation between circulating and tissue miRNAs is not clear, and several studies indicate that miRNA levels in blood are not a reflection of FUNDING changes in the tissue of origin. The reason is that miRNAs can also This work was supported by grants from the Spanish Ministry of be produced by immune cells (Zheng et al., 2018). Economy and Competitiveness-MINECO (SAF2017-84324-C2- 1-R), the Instituto de Salud Carlos III (PIC18/0014, PI18/00256), the Red de Terapia Celular–TerCel (RD16/0011/0006) and the CONCLUDING REMARKS CIBER Cardiovascular (CB16/11/00403) projects, as part of the Plan Nacional de I+D+I, and it was co-funded by ISCIII- Over the past few years, a great amount of research has focused on Sudirección General de Evaluación y el Fondo Europeo de epigenetics and its dynamic cross-talk with genetics. Unveiling a Desarrollo Regional (FEDER). This work was also funded by personalized epigenetic pattern can provide a large amount of the Fundació La MARATÓ de TV3 (201516-10, 201502-20), the information on epigenetic machinery that could be employed Generalitat de Catalunya (SGR2017 00483, SLT002/16/00234), to tailor diagnosis and therapeutic strategies in CVDs. Recent the CERCA Programme/Generalitat de Catalunya, and “la advances in technology and data analysis have made it possible Caixa” Banking Foundation. to create detailed epigenetic maps, which may represent a new tool in the clinical practice to discern cardiovascular risk beyond traditional risk determinants. Epigenetic information can also ACKNOWLEDGMENTS help in predicting individual drug responses. Importantly, epigenetic biomarkers are gaining ground in the scientific We apologize to all authors whose work could not be mentioned community as tools for the diagnosis and prognosis of CVDs. because of space limitations or inadvertent omissions. We However, discrepancies in specific diagnostic biomarkers make are greatly grateful to Sonia V Forcales for her comments and replication of the current results in independent laboratories, discussion on epigenetic regulation. REFERENCES overload-induced heart failure. PLoS One 9, e106024. doi: 10.1371/journal. pone.0106024 Adachi, T., Nakanishi, M., Otsuka, Y., Nishimura, K., Hirokawa, G., Goto, Y., et al. Authors/Task Force members, Windecker, S., Kolh, P., Alfonso, F., Collet, J.-P., (2010). Plasma microRNA 499 as a biomarker of acute myocardial infarction. Cremer, J., et al. (2014). 2014 ESC/EACTS guidelines on myocardial Clin. 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The use, distribution or reproduction in other forums is permitted, provided Zheng, B., Xi, Z., Liu, R., Yin, W., Sui, Z., Ren, B., et al. (2018). The function of the original author(s) and the copyright owner(s) are credited and that the original microRNAs in B-cell development, lymphoma, and their potential in clinical publication in this journal is cited, in accordance with accepted academic practice. No practice. Front. Immunol. 9, 936. doi: 10.3389/fimmu.2018.00936 use, distribution or reproduction is permitted which does not comply with these terms. Frontiers in Genetics | www.frontiersin.org 31 October 2019 | Volume 10 | Article 950