Abstract

Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide and also inflict major burdens on morbidity, quality of life, and societal costs. Considering that CVD preventive medications improve vascular outcomes in less than half of patients (often relative risk reductions range from 12% to 20% compared with placebo), precision medicine offers an attractive approach to refine the targeting of CVD medications to responsive individuals in a population and thus allocate resources more wisely and effectively. New tools furnished by advances in basic science and translational medicine could help achieve this goal. This approach could reach beyond the practitioners ‘eyeball’ assessment or venerable markers derived from the physical examination and standard laboratory evaluation. Advances in genetics have identified novel pathways and targets that operate in numerous diseases, paving the way for ‘precision medicine’. Yet the inherited genome determines only part of an individual’s risk profile. Indeed, standard genomic approaches do not take into account the world of regulation of gene expression by modifications of the ‘epi’genome. Epigenetic modifications defined as ‘heritable changes to the genome that do not involve changes in DNA sequence’ have emerged as a new layer of biological regulation in CVD and could advance individualized risk assessment as well as devising and deploying tailored therapies. This review, therefore, aims to acquaint the cardiovascular community with the rapidly advancing and evolving field of epigenetics and its implications in cardiovascular precision medicine.

Customized approaches for the management of cardiovascular disease

Clinicians have always intuitively individualized treatment to match the patient in front of them. But new tools permit far more precise tailoring of therapy beyond the practitioners’ ‘eyeball’ assessment or venerable markers derived from the physical examination and standard laboratory assessment. In early 2016, the then US President Barak Obama launched a Precision Medicine Initiative (https://obamawhitehouse.archives.gov/node/333101). The Mission Statement of this initiative read: ‘To enable a new era of medicine through research, technology, and policies that empower patients, researchers, and providers to work together toward development of individualized care’. This injunction, spurred by the availability of a growing array of novel technologies, incite practitioners to strive for an ever greater level of personalization.

The cardiovascular community takes just pride in the size of the clinical trials that inform medical practice and that dwarf those in many other specialties. Yet a tension prevails between large and ‘dumb’ trials and smaller ‘smarter’ studies. The inclusion criteria of many large-scale trials run countercurrent to the push to personalization. Current standard-of-care background therapy in the cardiovascular community has lowered event rates such that larger numbers or higher risk subjects are needed to see a signal. Thus, the selection of higher risk participants often drives the selection of entry criteria during trial design. These large studies tend to favour a ‘one-size-fits-all’ mentality, even though treated patients often do not match exactly the entry criteria for the randomized clinical trials that current guidelines enshrine.

The field of oncology boasts smaller studies, but much more commonly directed by biomarkers derived from advances in molecular biology and genetics than is the case for cardiovascular trials. The mining of contemporary cancer biology has yielded numerous targeted therapies, whose deployment often depends on companion diagnostic tests that reflect the fundamental mechanisms of the treatment. The successes of this approach have tamed many cancers, converting them into chronic diseases, and even effecting cures in some cases. This example should inspire the cardiovascular community to consider the concepts of development and deployment of therapies guided by biomarkers that narrow rather than broaden the target population. Perhaps it is time to add to the traditional ‘blockbuster drug’ model of broadly applicable therapies, a more targeted and tailored approach. Harnessing new tools furnished by advances in basic science might help in this regard. Advances in genetics have identified novel pathways and targets that operate in numerous diseases, paving the way for ‘precision medicine’. Mendelian randomization approaches can test the causal contribution of various mediators to disease. Yet the inherited genome determines only part of the risk profile and opportunities for personalized therapies that our patients present. Strictly genomic approaches do not take into account the world of regulation of gene expression by ‘epi’genetic changes—acquired modifications to the genome subject to influence by environment—a burgeoning field that adds a new dimension to our understanding of disease and potential new treatments at a growing pace (Figure  1). The application of epigenetics may advance individualized risk assessment and the development and deployment of tailored therapies. This review aims to acquaint the cardiovascular community with the rapidly advancing and evolving field of epigenetics that should contribute to our realizing the promise of ‘precision medicine’.

Figure 1

Impact of genetics and epigenetics on cardiovascular phenotype. Genetic mutations acquired during the life course represent an irreversible process, whereas plastic epigenetic changes of DNA/histone complexes are reversible and amenable to pharmacological reprogramming.

Lessons from genetics

Considerable efforts have evaluated inborn genetic variation, which can certainly influence disease susceptibility.1 Pharmacogenetic research has advanced markedly since the exploration of inherited differences in responses to drugs such as isoniazid and succinylcholine in the 1950s. Several clinical examples demonstrate what we have learned from the analysis of our genetic background and how adopting genetic information can apply to cardiovascular precision medicine.

HDLs have shown several potentially beneficial cardiovascular properties affecting reverse cholesterol transport, endothelial function, and inflammation. Clinical results of several therapies that elevate HDL levels have proved disappointing. In contrast, clinical responses to the cholesteryl ester transfer protein (CETP) inhibitor dalcetrapib appears to depend on a genetic variant in the adenylate cyclase type 9 (ADCY9) gene. In retrospective analysis, patients with the AA genotype at polymorphism rs1967309 benefited from a 39% reduction in the composite cardiovascular endpoint with dalcetrapib compared with placebo (n = 5749 patients).2 The prevalence of the AA genotype is 17%, except for African Americans in whom it is higher. In contrast, patients with the GG genotype had a 27% increase in events with dalcetrapib vs. placebo, whereas heterozygotes had a neutral response. The lack of detectable genetic effect for rs1967309 in the placebo arm alone and the significant gene-by-treatment arm interaction supported that this was primarily a pharmacogenomic marker of response to therapy. There were strikingly concordant findings with dalcetrapib compared with placebo in terms of atherosclerotic changes on imaging in the dal-Plaque-2 study, inflammatory status per the high-sensitivity C-reactive protein level, and cholesterol efflux.3 The ongoing Dal-GenE randomized clinical trial of 5000 patients with the AA genotype at rs1967309 in the ADCY9 gene will test prospectively the genotype-dependent effects of dalcetrapib on cardiovascular clinical outcomes.4

Variants in the genes that encode the beta-1 adrenergic receptor (ADBR1) and, to a lesser extent the beta-2 adrenergic receptor (ADBR2), associate with response to beta-blockers in patients with heart failure and those with hypertension.5–12 Many studies have focused on the ADBR1 Arg389Gly variant. Because the 389Arg allele associates with greater production of cyclic adenosine monophosphate compared with the 399Gly allele,11  ,  13 ‘hyper-responders’ carrying the 399Arg allele might benefit to a greater extent from beta-blockers. An important substudy emerged from the BEST trial, which investigated the effect of the beta-blocker bucindolol in patients with heart failure. This substudy of 1040 patients showed that bucindolol reduced mortality and hospitalization in homozygotes for the Arg389 allele compared with the Gly allele carriers.14 Some studies have reported more equivocal results, including a substudy of 600 patients of MERIT-HF.15 Given the heterogeneity in pharmacological properties of beta-blockers, these inconsistencies could reflect differences between these agents or the analysis of a smaller sample size in the MERIT-HF substudy.

Hepatocyte uptake of statins depends on the solute carrier organic anion transporter family member 1B1 (SLCO1B1) gene, which encodes the organic anion transporting polypeptide (OATP1B1) protein. Reduced entry of statins in hepatocytes may increase the risk of statin-induced myotoxicity. The rs4149056 polymorphism in the SLCO1B1 gene associates with a greatly increased risk of developing rhabdomyolysis in patients treated with simvastatin.16 In contrast, SLCO1B1 variants did not associate with statin-induced myotoxicity in patients treated with rosuvastatin.17

Genetic information has greatly contributed to our understanding of the multifactorial aetiology of type 2 diabetes mellitus (T2D) as well as the individual response to treatment with glucose-lowering agents.18 Individuals with loss of function variants in CYP2C9, a gene encoding for Cytochrome P450 2C9, display greater glycaemic response to sulfonylureas than those carrying wild-type alleles.18 Along the same line, heterozygous mutations in hepatocyte nuclear factor 1 homeobox A (HNF1A)—a transcription factor involved in the regulation of several liver-specific genes—strongly associate with extreme sensitivity to sulfonylureas in T2D patients. Furthermore, a genome-wide association (GWA) study in 1024 Scottish patients with T2D unveiled a variant rs11212617 near the ataxia telangiectasia mutated (ATM) gene that associated significantly with glycaemic response to metformin.18

Taken together, these data indicate that the unveiling of inherited genetic variants can contribute to understanding of clinical drug responsiveness and patient outcome. The application of ‘epi’genetics promises to deepen such genetic insights substantially.

From genomics to post-genomics: the ‘epigenetic revolution’

In 1956, the British developmental biologist, Conrad Waddington, demonstrated the inheritance of a characteristic acquired in a population in response to an environmental stimulus.19 He found that changes in the environmental temperature or chemical stimuli could induce different thorax and wing structures in embryo fruit flies carrying an identical genetic background.20 The term ‘epigenetics’ originally embraced the process by which a fertilized zygote develops into a mature, complex organism, but underwent expansion as findings showed that cells having the same DNA can exhibit differential modulation of gene activity. In this regard, Waddington’s intuition helped to unveil a key biological mechanism whereby heritable traits can associate not only with changes in nucleotide sequence but also with chemical modifications of DNA or of the proteins with which DNA interacts. The discovery of DNA methylation in bacterial genomes followed Waddington’s observations. Experiments in 1975 showed the transmission of epigenetic changes to daughter cells where it actively regulates gene expression.21

Epigenetic modifications fall into three main categories: (i) chemical modifications of DNA (i.e. methylation); (ii) post-translational modifications of histone tails; and (iii) regulation of gene expression by non-coding RNAs [i.e. microRNAs, PIWI-interacting RNAs, endogenous short interfering RNAs, long non-coding RNAs (lncRNAs)] (Figure  2).22 Histones regulation can modify gene expression by altering the accessibility of chromatin to transcription factors. Chromatin comprises chromosomal DNA packaged around histone proteins that form nucleosomes. Multiple interactions tightly link histones to DNA, rendering nucleosomes very stable under physiological conditions.

Figure 2

Environmental factors and epigenetics. Over time, an array of environmental factors significantly contributes to build our individual epigenetic background that includes DNA methylation changes, post-translational histone modifications and altered expression of non-coding RNAs.

DNA methylation

Methylation of DNA mainly occurs through attachment of methyl group to the C5 position in the cytosine-paired-with-guanine (CpG) dinucleotide sequences. CpG sequences localize in promoter regions rather than coding regions of genes.23 CpG methylation suppresses gene transcription by directly impeding the binding of transcription factors to DNA or, indirectly, by recognition of methylated sites by chromatin modifying enzymes.24 DNA methyltransferases (DNMTs: DNMT1, DNMT3a, and DNMT3b) mediate much DNA methylation. DNMT1 recognizes hypermethylated DNA thus maintaining methylation status during replication. In contrast, the methyl-writing enzymes DNMT3a and DNMT3b are responsible for de novo methylation.25

Histone modifications

Post-translational modification of histones includes methylation, acetylation, ubiquitination, and phosphorylation. These modifications may cluster in different patterns to regulate the shift from a compact (heterochromatin) to an open (euchrotmatin) chromatin structure, or vice versa.26 Families of chromatin remodellers acetylate and methylate histones: histone acetyltransferases (HATs) and histone deacetylases (HDAC) for acetylation and histone methyltransferases (HMTs) and demethylases (HDMs) for methylation. These histone-writing and -erasing enzymes interact selectively with DNA-methylated regions and thus enable gene repression or transcription.27 Histone acetylation by HATs generally associates with enhanced gene expression, whereas HDACs exert opposite effects. SIRT1, the most studied mammalian Sirtuin, represents a clear example of how histone modifications impact cellular function by orchestrating key biological processes (i.e. metabolism, longevity) through the deacetylation of a number of enzymes and transcriptional switchers (i.e. PGC-1α, NF-κB, FOXO) as well as histones (i.e. H3K9 and H3K56).28 The more complex process of histone methylation may result in different chromatin states according to the methylated residue and the number of added methyl groups. However, we can now associate specific methylation patterns to activation or silencing of specific genes. For example, mono-methylation of lysine 4 on histone 3 (H3K4me) licences a key pro-inflammatory complex, nuclear factor kappa-B (NF-κB).29

Non-coding RNAs

Recent research has demonstrated a key role for the non-coding genome in genetic programming and gene regulation during development as well as in health and in CVD.30 About 98% of the human genome does not encode proteins but can engage in transcription producing numerous non-coding RNAs (ncRNAs) that exert important regulatory and structural functions.31 Based on size, ncRNAs can be subdivided into 2 major groups: (i) small ncRNAs (sncRNAs, <200 nucleotides long) including microRNAs, PIWI-interacting RNAs, and endogenous short interfering RNAs and (ii) long non-coding RNAs (lncRNAs), which have a length between 0.2 kb and 2 kb. A growing body of evidence implicates ncRNAs in the pathogenesis of CVD and as biomarkers of cardiovascular damage.31 The high inter-individual diversity of chromatin architecture and the ncRNA landscape points to considering epigenetic modifications as tools to individual cardiovascular risk and customize treatments.

The epigenetic landscape in cardiovascular disease

The acquisition of epigenetic signals during an individual’s lifespan results mostly from environmental factors, including the intrauterine milieu, diet, atmospheric pollutants, smoking, urban noise, and, last but not least, the social, cultural, and economic circumstances encountered (Figure  2).23 Most epigenetic modifications show stability and appear durable and thus able to affecting gene expression along the arc of ageing.32  ,  33 Modifications of the epigenetic landscape by environmental cues may perturb cardiovascular homeostasis and influence endothelial dysfunction, vascular ageing, or cardiomyocyte behavior.34 Such modifications may also influence cardiovascular risk factors including dyslipidaemia, hypertension, obesity, and diabetes.

Over the last decades, the availability of relatively inexpensive techniques for genome-scale analysis of both DNA methylation and histone modifications led to an explosion of studies characterizing the impact of the epigenetic variations on CVD. A key contribution to our current understanding of cardiovascular epigenetics comes from gain- and loss-of-function experiments in animals. Genetic disruption of DNMTs (that establish or replicate DNA methylation) or MTHFR (related to methyl donor generation) in mice associate with DNA hypomethylation and subsequent increases in inflammatory mediators and formation of aortic fatty streaks.35 Atherosclerosis-prone apoE    /   mice develop specific changes in DNA methylation of transcribed gene sequences both in peripheral blood leucocytes and in the aorta before developing vascular lesions.36 Along the same line, peripheral blood mononuclear cells (PBMCs) isolated form patients with atherosclerosis exhibit globally reduced DNA methylation.37 Recent observations implicate somatic mutations in demethylases such as Tet2 that accrue with age in spurring the emergence of leucocyte clones that not only confer increased risk of haematological malignancies but also of CVDs.38  ,  39 Indeed, myocardial infarction and stroke account for much more of the increased mortality associated with these haematopoietic clones than do leukaemias.39 Experimental work has established the causality of these methylase mutations in promoting plaque inflammation, probably due to epigenetic regulation of cytokine and chemokine genes.39  ,  40

Over the last few years, an array of studies has begun to link cardiovascular risk factors (i.e. ageing, hypertension, diabetes, and dyslipidaemia) to epigenetic modifications in human subjects. The discussion below provides early examples of such associations. Although their validation will require large prospective studies, the examples cited below provide intriguing glimpses of the potential of epigenetics to broaden our understanding of disease pathogenesis and new clinical tools as well.

Ageing

Alteration of epigenetic patterns in ageing—a phenomenon known as ‘epigenetic drift’—involves primarily a progressive decrease in global DNA methylation. The Normative Ageing Study showed a longitudinal decline in the average blood genomic DNA methylation of repetitive sequences, such as Alu and LINE-1, over 8 years of follow-up.41 Genome-wide studies in aged stem cells revealed a decrease in DNA methylation at the promoter of genes associated with self-renewal, whereas promoters of genes regulating differentiation were hypermethylated.42 Histone modifications such as acetylation of histone 3 at lysine 9 (H3K9Ac) as well as trimethylation of histone 3 at lysine9 (H3K9me3) and lysine 27 (H3K27me3) decrease with age and contribute to haematopoietic stem cells dysfunction and defective vascular repair.43 The miRNA landscape in ageing tends towards increased miRNAs expression, leading to post-transcriptional suppression of many target genes and alterations in endothelial functions. Derailed expression of miR-29, miR-34a, miR-217, and miR-146 associates strongly with a decline of vascular and cardiac function in the elderly.44  ,  45 Age-dependent decreases in several lncRNAs, namely ANRIL, MALAT-1, MIAT, and Meg3, may lessen angiogenic potential.31

Hypertension

Peripheral blood leucocytes of patients with essential hypertension show a loss of global genomic methylation.46 A recent genome-wide association and replication study of blood pressure phenotypes among 320 251 individuals of East Asian, European, and South Asian ancestry revealed that single-nucleotide polymorphisms influencing blood pressure associate strongly with methylation at multiple local CpG.47 Another genome-wide methylation study on essential hypertension conducted in young African American males found increased methylation levels at two CpG sites in the SULF-1 gene involved in apoptosis and decreased methylation of the PRCP gene that regulates cleavage of angiotensin II and III.48 Histone 3 methylation also controls the expression of genes related to hypertension. A polymorphism in DOT1L gene, encoding histone H3K79 methyltransferase, associated tightly with greater systolic and diastolic blood pressure response to hydrochlorothiazide in Caucasians.49 Hypertensive patients have altered expression of miR-9 and miR-126 relative to healthy individuals in association with prognostic indices of hypertensive target-organ damage.50 These miRs may serve as epigenetic biomarkers and therapeutic targets in patients with essential hypertension.

Type 2 diabetes

The involvement of epigenetics in T2D could help explain the long-lasting detrimental effects of hyperglycaemia despite optimal glycaemic control, the so-called ‘metabolic’ or ‘hyperglycaemic memory’. Several studies have shown that epigenetic signatures at the promoter of pro-oxidant and inflammatory genes contribute to persistent endothelial dysfunction, diabetic nephropathy, and retinopathy as well as atherosclerotic features even after restoration of normoglycaemia. 27  ,  51  ,  52 Promoter methylation of the adaptor p66Shc, involved in mitochondrial oxidative stress, is persistently reduced in PBMCs from T2D patients after glycaemic control and correlates with endothelial dysfunction and oxidative stress levels.53 Saliva DNA from T2D patients with end-stage renal disease (ESRD) compared to that from patients with chronic kidney disease who did not progress to ESRD exhibits several differentially methylated genes.54 We have recently reported that T2D patients carry a specific epigenetic pattern on histone 3, namely H3K4me.54 This signature—driven by the methyltrasferase Set7—associates with NF-κB activation and subsequent overexpression of pro-atherosclerotic genes such as iNOS, COX-2, ICAM-1, MCP-1, and VCAM-1.55 The histone 3 deacetylase SIRT1 declines in peripheral blood monocytes from patients with insulin resistance and coronary artery disease as well as in aged individuals, thus representing a key epigenetic route linking longevity, metabolism, and atherosclerosis.56 Plasma miRNA profiling in a cohort of diabetic patients unveiled a profound down-regulation of miR-126.57 Moreover, EPCs isolated from diabetics show reduced miR-126 expression, and exogenous miRNA-126 mimic restored EPCs angiogenic properties.58  ,  59

Dyslipidaemia

Blood lipid profiles reflect both genetic and environmental factors.60 Maternal and paternal dietary habits as well as the influence of intrauterine environment may influence the dietary habits and cholesterol levels of the offspring.61 The inheritance of specific epigenetic modifications on the promoter of genes that regulate glucose and lipid metabolism provides a potentially fascinating contributor to atherogenesis. Participants in the Dutch Hunger Winter Families Study who were exposed in utero to the 1944–45 famine, a condition associated with the development of obesity and insulin resistance in adulthood, displayed subtle blood methylation changes of insulin-like growth factor-2 (IGF-2) and leptin (Lep) genes compared with unexposed siblings.62 Heritable epigenomic changes may also contribute to the unexplained inter-individual postprandial lipaemia (PPL) variability, an independent risk factor for CVD. An epigenome-wide association study on 979 subjects challenged with a high-fat meal revealed that eight methylation sites encompassing five genes (LPP, CPT1A, APOA5, SREBF1, and ABCG1) associated significantly with PPL. Higher methylation at LPP, APOA5, SREBF1, and ABCG1 and lower methylation at CPT1A correlated with an increased TG–PPL response.63 In another study from the same cohort, CPT1A methylation associated robustly with fasting very-low LDL-cholesterol and TG.64 Finally, miR-33a/b may act as post-transcriptional regulators of lipid metabolism and insulin signalling, and their inhibition diminishes atherosclerosis by raising plasma HDL levels.65

Myocardial infarction

Epigenetics may help to understand the considerable variability in mid- and long-term prognosis in patients who sustain myocardial infarction (MI). In the northern Sweden population health study, individuals with a history of MI showed differential DNA methylation at 211 CpG-sites representing genes related to cardiac function, CVD, cardiogenesis, and recovery after ischaemic injury.66 Hence, epigenetic information may explain the alterations in cardiovascular gene expression trajectories and offer biomarkers for the follow-up of these patients. MI also associates with a profound deregulation of circulating miRNAs and lncRNAs. MiRNA-208b and miR-499 are highly increased in MI patients (>105-fold, P < 0.001), whereas they are nearly undetectable in healthy controls.67 Elevation of plasma miRNAs observed during the 1st hour after the onset of symptoms indicates that these alterations might participate causally in the ischaemic event rather than representing a mere reaction to acute ischaemia. Patients presented <3 h after onset of pain showed positive miR-499 in 93% of patients and hs-cTnT in 88% of patients. Overall, miR-499 and hs-cTnT provided comparable diagnostic value with areas under the receiver operating characteristics curves of 0.97.67 Consistently, a variety of studies showed that selected panels of circulating miRNAs may represent useful prognostic biomarkers in MI patients.68  ,  69 Circulating microRNAs may also permit differentiating Takotsubo cardiomyopathy from acute MI.70 The expression of lncRNAs (ANRIL, KCNQ1OT1, MIAT, and MALAT-1) also rises significantly in PBMCs from patients with MI and independently predicts left ventricular dysfunction (ejection fraction ≤ 40%) at 4 months of follow-up.71

Stroke

Lower methylation of the TRAF3 gene—a member of the TNF receptor-associated factor (TRAF) protein family—correlated with increased platelet aggregation in stroke patients treated with clopidogrel (ρ = −0.29, P =0.0075) as well as recurrence of ischaemic events.72 Another study from the same group showed that methylation of PPM1A gene, a member of the PP2C family of Ser/Thr protein phosphatase, associates with recurrent vascular events in aspirin-treated patients.73 These studies provide proof of principle that—beyond genetic information—pharmacoepigenomics may enable precision approaches in cardiovascular medicine. Patients with acute ischaemic stroke show consistently altered circulating microRNAs, namely miR-125 b-2*, -27a*, -422a, -488, and -627, irrespective of age, disease severity, or confounding metabolic complications.74 Profiling of lncRNAs in 266 whole-blood RNA samples from patients with ischaemic stroke and matched controls revealed a significant gender-sensitive dysregulation. Males with stroke compared with the controls showed 299 differentially expressed lncRNAs, whereas females had only 97 differentially expressed lncRNAs. Of note, some differentially expressed lncRNAs mapped close to genomic locations of previously identified stroke-risk genes, including lipoprotein(a)-like 2, ABO blood group, prostaglandin 12 synthase, and α-adducins.75 The latter study furnishes hints for gender-specific epigenetic biomarkers in the setting of CVD.

Heart failure

Genome-wide maps of DNA methylation and histone-3 lysine-36 trimethylation (H3K36me3) in cardiomyopathic and normal human hearts showed a variety of epigenomic patterns in important DNA elements of the cardiac genome in patients with advanced cardiomyopathy.76

Interrogation of the cardiac methylome in patients with idiopathic dilated cardiomyopathy detected methylation differences in pathways related to heart disease, but also in genes with yet unknown function in heart failure, namely lymphocyte antigen 75 (LY75) and adenosine receptor A2A (ADORA2A).77 Advanced heart failure patients have low circulating levels of miRNA-103, miRNA-142-3p, miRNA-30 b, miRNA-342-3p, and miRNA-652-3p and high levels of miRNA-499 and miRNA-508-5p.78  ,  79 Moreover, in such patients, low circulating levels of miRNA-423-5p portend poor long-term outcomes.80

Towards individual epigenetic maps

Contrary to the common belief that an individual’s genome is no different than another, scientists have known for years that not all epigenomes are born equally. When it comes to epigenetic modifications—diversity is the norm rather than the exception. Constructed by way of chemical information specific determinants are codified for health and changed in disease. With this knowledge, precision medicine is evolving because of the significant advances enabling scientists and physicians fundamental and medical insights.81 The completion of the Human Genome Project furnished the cornerstone of the genetic blueprint and the mainstay of genomics research.82  ,  83 Within a decade of announcing the draft sequence, scientists had transitioned from understanding the structure of DNA to major accomplishments in genome biology. Next-generation sequencing technologies rapidly emerged bringing with it unprecedented opportunities to address the unmet need to understand genes in context with biology and disease.84 Critical advances in bioinformatics accompanied those in genomics permitting processing and analysis of ever expanding data sets.85 Despite these strides, the epigenomic world remains largely uncharted about precision medicine in cardiology. Although there remain substantial barriers to overcome, efforts have begun to accelerate the development cardiovascular epigenomics.86

Although technological advances in epigenomics have begun to enable clinical applications, a key challenge remains how to cost-effectively perform whole-genome bisulfite sequencing (WGBS) for epigenome-wide association studies (EWAS, Table  1, Figure  3).

Table 1

Abbreviations list and description of main epigenetic technologies and studies

AcronymDefinitionDescription
ATAC-SeqAssay for transposase-accessible chromatin with high-throughput sequencingATAC-seq is a high-throughput sequencing technology that furnishes a genome-wide map of chromatin accessibility. Specifically, it allows simultaneous, genome-wide information on the positions of: (i) open chromatin, (ii) transcription factor binding, (iii) nucleosomes in regulatory regions, and (iv) information on chromatin state annotation.
WGBSWhole-genome bisulfite sequencingWGBS is a next-generation sequencing technology used to determine the DNA methylation status of single cytosines. For WGBS, DNA samples have to be treated with sodium bisulfite, a chemical compound that converts unmethylated cytosines into uracil but leaves 5-methylcytosine residues unaffected. This technique measures single-cytosine methylation levels genome-wide and directly estimates the ratio of methylated molecules.
RNA-seqRNA sequencingRNA-seq is used to explore the cellular transcriptome. It allows the assessment of alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/single nucleotide polymorphisms and dynamic changes in gene expression, or differences in gene expression in different groups or treatments. In addition to mRNA transcripts, RNA-seq can look at different populations of RNA including total RNA, small RNA, such as miRNA, tRNA, and ribosomal profiling.
ChIP-on-chipChIP-on-chipChIP-on-chip is a technology that combines chromatin immunoprecipitation (ChIP) with DNA microarray (chip). ChIP-on-chip is used to investigate interactions between proteins and DNA in vivo.
COMETCOMETThe COMET package is computational tool that allows to visualize EWAS results in a genomic region of interest. COMET provides a plot of the EWAS association signal and visualisation of the methylation correlation between CpG sites (co-methylation).
EWASEpigenome-wide association studiesEWAS are designed to investigate the association between a genome-wide set of quantifiable epigenetic marks (i.e. DNA methylation) and a particular identifiable phenotype/trait in large human cohorts. These sudies may help to elucidate whether an epigenetic perturbation is associated causally or consequentially with a given phenotype.
IHECInternational Human Epigenome ConsortiumIHEC is a scientific organization, founded in 2010, which helps to co-ordinate global efforts in the field of epigenomics. IHEC member organizations are engaged in efforts to generate at least 1000 reference (baseline) human epigenomes from different types of normal and disease-related human cell types.
GTExGenotype-Tissue Expression projectThis program is providing valuable insights into the mechanisms of gene regulation by studying human gene expression and regulation in multiple tissues from healthy individuals as well as in a variety of human diseases.
AcronymDefinitionDescription
ATAC-SeqAssay for transposase-accessible chromatin with high-throughput sequencingATAC-seq is a high-throughput sequencing technology that furnishes a genome-wide map of chromatin accessibility. Specifically, it allows simultaneous, genome-wide information on the positions of: (i) open chromatin, (ii) transcription factor binding, (iii) nucleosomes in regulatory regions, and (iv) information on chromatin state annotation.
WGBSWhole-genome bisulfite sequencingWGBS is a next-generation sequencing technology used to determine the DNA methylation status of single cytosines. For WGBS, DNA samples have to be treated with sodium bisulfite, a chemical compound that converts unmethylated cytosines into uracil but leaves 5-methylcytosine residues unaffected. This technique measures single-cytosine methylation levels genome-wide and directly estimates the ratio of methylated molecules.
RNA-seqRNA sequencingRNA-seq is used to explore the cellular transcriptome. It allows the assessment of alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/single nucleotide polymorphisms and dynamic changes in gene expression, or differences in gene expression in different groups or treatments. In addition to mRNA transcripts, RNA-seq can look at different populations of RNA including total RNA, small RNA, such as miRNA, tRNA, and ribosomal profiling.
ChIP-on-chipChIP-on-chipChIP-on-chip is a technology that combines chromatin immunoprecipitation (ChIP) with DNA microarray (chip). ChIP-on-chip is used to investigate interactions between proteins and DNA in vivo.
COMETCOMETThe COMET package is computational tool that allows to visualize EWAS results in a genomic region of interest. COMET provides a plot of the EWAS association signal and visualisation of the methylation correlation between CpG sites (co-methylation).
EWASEpigenome-wide association studiesEWAS are designed to investigate the association between a genome-wide set of quantifiable epigenetic marks (i.e. DNA methylation) and a particular identifiable phenotype/trait in large human cohorts. These sudies may help to elucidate whether an epigenetic perturbation is associated causally or consequentially with a given phenotype.
IHECInternational Human Epigenome ConsortiumIHEC is a scientific organization, founded in 2010, which helps to co-ordinate global efforts in the field of epigenomics. IHEC member organizations are engaged in efforts to generate at least 1000 reference (baseline) human epigenomes from different types of normal and disease-related human cell types.
GTExGenotype-Tissue Expression projectThis program is providing valuable insights into the mechanisms of gene regulation by studying human gene expression and regulation in multiple tissues from healthy individuals as well as in a variety of human diseases.
Table 1

Abbreviations list and description of main epigenetic technologies and studies

AcronymDefinitionDescription
ATAC-SeqAssay for transposase-accessible chromatin with high-throughput sequencingATAC-seq is a high-throughput sequencing technology that furnishes a genome-wide map of chromatin accessibility. Specifically, it allows simultaneous, genome-wide information on the positions of: (i) open chromatin, (ii) transcription factor binding, (iii) nucleosomes in regulatory regions, and (iv) information on chromatin state annotation.
WGBSWhole-genome bisulfite sequencingWGBS is a next-generation sequencing technology used to determine the DNA methylation status of single cytosines. For WGBS, DNA samples have to be treated with sodium bisulfite, a chemical compound that converts unmethylated cytosines into uracil but leaves 5-methylcytosine residues unaffected. This technique measures single-cytosine methylation levels genome-wide and directly estimates the ratio of methylated molecules.
RNA-seqRNA sequencingRNA-seq is used to explore the cellular transcriptome. It allows the assessment of alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/single nucleotide polymorphisms and dynamic changes in gene expression, or differences in gene expression in different groups or treatments. In addition to mRNA transcripts, RNA-seq can look at different populations of RNA including total RNA, small RNA, such as miRNA, tRNA, and ribosomal profiling.
ChIP-on-chipChIP-on-chipChIP-on-chip is a technology that combines chromatin immunoprecipitation (ChIP) with DNA microarray (chip). ChIP-on-chip is used to investigate interactions between proteins and DNA in vivo.
COMETCOMETThe COMET package is computational tool that allows to visualize EWAS results in a genomic region of interest. COMET provides a plot of the EWAS association signal and visualisation of the methylation correlation between CpG sites (co-methylation).
EWASEpigenome-wide association studiesEWAS are designed to investigate the association between a genome-wide set of quantifiable epigenetic marks (i.e. DNA methylation) and a particular identifiable phenotype/trait in large human cohorts. These sudies may help to elucidate whether an epigenetic perturbation is associated causally or consequentially with a given phenotype.
IHECInternational Human Epigenome ConsortiumIHEC is a scientific organization, founded in 2010, which helps to co-ordinate global efforts in the field of epigenomics. IHEC member organizations are engaged in efforts to generate at least 1000 reference (baseline) human epigenomes from different types of normal and disease-related human cell types.
GTExGenotype-Tissue Expression projectThis program is providing valuable insights into the mechanisms of gene regulation by studying human gene expression and regulation in multiple tissues from healthy individuals as well as in a variety of human diseases.
AcronymDefinitionDescription
ATAC-SeqAssay for transposase-accessible chromatin with high-throughput sequencingATAC-seq is a high-throughput sequencing technology that furnishes a genome-wide map of chromatin accessibility. Specifically, it allows simultaneous, genome-wide information on the positions of: (i) open chromatin, (ii) transcription factor binding, (iii) nucleosomes in regulatory regions, and (iv) information on chromatin state annotation.
WGBSWhole-genome bisulfite sequencingWGBS is a next-generation sequencing technology used to determine the DNA methylation status of single cytosines. For WGBS, DNA samples have to be treated with sodium bisulfite, a chemical compound that converts unmethylated cytosines into uracil but leaves 5-methylcytosine residues unaffected. This technique measures single-cytosine methylation levels genome-wide and directly estimates the ratio of methylated molecules.
RNA-seqRNA sequencingRNA-seq is used to explore the cellular transcriptome. It allows the assessment of alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/single nucleotide polymorphisms and dynamic changes in gene expression, or differences in gene expression in different groups or treatments. In addition to mRNA transcripts, RNA-seq can look at different populations of RNA including total RNA, small RNA, such as miRNA, tRNA, and ribosomal profiling.
ChIP-on-chipChIP-on-chipChIP-on-chip is a technology that combines chromatin immunoprecipitation (ChIP) with DNA microarray (chip). ChIP-on-chip is used to investigate interactions between proteins and DNA in vivo.
COMETCOMETThe COMET package is computational tool that allows to visualize EWAS results in a genomic region of interest. COMET provides a plot of the EWAS association signal and visualisation of the methylation correlation between CpG sites (co-methylation).
EWASEpigenome-wide association studiesEWAS are designed to investigate the association between a genome-wide set of quantifiable epigenetic marks (i.e. DNA methylation) and a particular identifiable phenotype/trait in large human cohorts. These sudies may help to elucidate whether an epigenetic perturbation is associated causally or consequentially with a given phenotype.
IHECInternational Human Epigenome ConsortiumIHEC is a scientific organization, founded in 2010, which helps to co-ordinate global efforts in the field of epigenomics. IHEC member organizations are engaged in efforts to generate at least 1000 reference (baseline) human epigenomes from different types of normal and disease-related human cell types.
GTExGenotype-Tissue Expression projectThis program is providing valuable insights into the mechanisms of gene regulation by studying human gene expression and regulation in multiple tissues from healthy individuals as well as in a variety of human diseases.

Figure 3

Epigenetic-based technologies with potential application in cardiovascular patients. PBMCs, peripheral blood mononuclear cells; WGBS, whole-genome bisulfite sequencing; MSREs, methylation sensitive restriction enzymes; HPLC, high-performance liquid chromatography; ChIP, chromatin immunoprecipitation; miRNAs, microRNAs; RNA-seq, RNA sequencing.

The high cost of constructing reference methylomes encountered by the International Human Epigenome Consortium (IHEC) has represented a challenge.87 The standard sequencing coverage misses many differential methylation sites. A technical advance in the quest to recover methylation sites from low-coverage WGBS uses an algorithm that captures almost twice the amount of informative bisulfite sequencing data.88 Saturation analysis of WGBS that constructs reference methylomes assesses multiple features involving blocks of comethylation (COMET) and improves detection from existing data, through the development of computational tools such as COMETgazer and COMETvintage. Indeed, the improved identification and recovery of methylation sites combined with advances in computational analyses advance the goal of translating EWAS into clinical practice. Despite the development of WGBS and new informatic tools considerable challenges remain. The validation of informative differential methylation sites remains incomplete due to limitations in assay performance and standardization. To help close this gap, a multicentre study organized by the BLUEPRINT Project assessed the accuracy and robustness of methylation assays tailored for cost-effective, high-throughput biomarker development designed for large population studies.89 This extraordinarily comprehensive resource identified strong concordance in assays based on amplicon-based bisulfite sequencing as well as bisulfite pyrosequencing. The reliable identification of epigenetic determinants for clinical applications could sharpen precision medicine.90

The technological accomplishments made in recent years to construct reference methylomes requires dismantling sequences before genome reconstruction or ‘shaping’ as it pertains to chemical epigenetic information. Personal epi(genomics) is emerging from major projects that provide significant resources like those already described and the Genotype-Tissue Expression (GTEx) project.91 Mapping our epigenomic differences with technologies that catalogue sequence similarity is an important move forward for personal therapeutic design. Intense interest surrounds the clinical development of pharmacological compounds that chemically modify key epigenetic determinants. Mapping a new route borrowed from the field of oncology, histone deacetylase inhibitors show therapeutic potential in heart disease.92 However, our view of the regulatory determinants that control transcription are largely derived from cell experiments and small animal studies that draw mechanistic parallels but highlight important differences. Indeed, while fundamental discoveries can chart a course to understanding pathology, human data are still necessary to answer the remaining critical questions about cardiac disease. The existing gap for epigenomics is person-centred cardiovascular information93 and the unmet need to distinguish gender-specific epigenetic differences.94 In an emerging era of epi(genomic) medicine, the potential to inform on evidence-based responses can lead to significant advances in personalized cardiovascular care. For example, epigenetic variability exists between genders and this is evident when assessing response to pharmacological HDAC inhibitors.95

Epigenetic therapies in the cardiovascular patient

The recent advances in epigenetic tools and the movement towards big data to dissect patient heterogeneity also raises the real need to assess distinct tissue types and specific cell lineages. This consideration has become more evident in the cardiac regeneration field. The highly specialized transcriptional programme during cardiomyocyte maturation remains poorly understood because of cellular heterogeneity. Single-cell RNA sequencing (RNA-seq) and unbiased clustering were recently used to characterize cardiomyocytes, fibroblasts, and endothelial cells from different regions of the heart throughout development.96

The limited and modest gain in cardiac function observed in randomized clinical trials of cell therapy for myocardial ischaemia indicates the need for better fundamental understanding of the cells being transferred and the environment which receives them. Disease-mediated epigenetic alteration of functional genes in transferred cells might contribute to the disappointing functional outcomes in clinical trials of myocardial cell therapy. Epigenetic silencing of gene expression through chromatin remodelling depends largely on chromatin condensation resulting from DNA methylation of CpG residues by DNMTs and post-translational modifications in the histone tails including specific alterations in acetylation and methylation of specific lysine residues. Generally, DNA methylation of gene regulatory regions along with H3K9 deacetylation by HDACs alters chromatin structure and limits gene transcription.97 Such repressive epigenetic modifications in autologous adult stem cells might compromise both their differentiation and functional activities and contribute to the general lack of substantive therapeutic benefit of cellular therapies. Indeed epigenetic silencing of genes via aberrant DNA methylation can occur in diabetes, hypertension, obesity, and heart failure.98 Since many patients with heart disease also have such co-morbidities, epigenetic silencing of functional genes in their autologous stem cells may impair their ability to effect myocardial repair. Epigenetic reprogramming to modulate gene repressive epigenetic marks by the use of small molecules might mitigate such limitations to the functions of adult stem cells in ischaemic myocardial repair (Figure  4).

Figure 4

Epigenetics in cardiovascular precision medicine. Unveiling the individual epigenetic landscape provides an important snapshot of the epigenetic machinery that can be eventually employed to customize diagnostic and therapeutic approaches in primary and secondary prevention of cardiovascular disease. Available technologies for the study of the epigenome may furnish detailed epigenetic maps based on DNA–histone interactions and non-coding RNAs landscape. Individual epigenetic maps could represent a novel tool in the clinical practice to stratify cardiovascular risk beyond traditional or genome-based risk calculators. Epigenetic information also helps in deciphering inter- and intra-personal variation in individual drug response. Finally, adverse epigenetic patterns are amenable to pharmacological reprogramming of chromatin modifying drugs or non-coding RNAs.

Chemical modifiers of DNA demethylation (5-azacytidine) and histone acetylation (e.g. Trichostatin A, valproic acid) can induce multipotency by enhanced reprogramming of somatic cells for somatic cell nuclear transfer (SCNT) or induced pluripotent stem cell (iPSc) derivation.99–101 Both drugs can change the fate of a given cell by chromatin remodelling, thus restoring the transcription of silenced genes including those that might reactivate pluripotency in somatic cells.101–103 Specifically in the cardiovascular system, treatment with 5-azacytidine increases cardiomyocyte differentiation of mesenchymal stem cells (MSCs) yielding improved cardiac function after transplantation of 5-azacytidine–treated MSCs compared with control MSCs.104–107 Similarly, inhibition of both DNA methylation and histone deacetylation by combined treatment of 5-azacytidine and valproic acid can enhance both the plasticity and function of endothelial progenitor cells and transplantation of treated cells boosting myocardial repair.108 Multiple studies have reported similar strategies of epigenetic modification of various kinds of stem/progenitor cells using inhibitors of HDACs.109–113 Specific inhibition of Class I HDACs by mocetinostat, augmented cardiac c-kit progenitor cell function including increased cardiomyogenic gene transcription and improved functional repair of ischaemic myocardium upon transplantation.114 Similarly, loss of HDAC4 function using interfering RNA improved functions of cardiac stem cells.115 Furthermore, inhibition of HDAC also enhanced differentiation of induced pluripotent stem cells into cardiomyocytes.116

Thus, ample evidence in the literature suggests that in vitro epigenetic reprogramming of a variety of stem progenitor cells can improve their functions including their ability to augment post-infarction myocardial function. Although not yet tried in the setting of clinical cell therapy, this approach of using small molecule modifier of DNA methylation and HDAC inhibition might enhance the clinical benefits of cell therapies for repair of the myocardium as well as other ischaemic tissues.

Conclusions

Environmental factors potently influence epigenetic variations and altered gene expression over the life course. Cigarette smoking, pollution, and high-fat diets all contribute to altered chromatin architecture, DNA methylation, as well as circulating and tissue levels of non-coding RNAs. Over the last decade, the launching of precision medicine initiatives aims to tailor health care on the basis of a person’s genes, lifestyle, and environment.117 Such personalized approaches usually employ panomics analyses to unmask the cause of individual patient’s disease and to develop specific therapeutic strategies. In this regard, patient-level ‘epigenomic’ information may contribute to sharpen risk assessments beyond traditional calculators and direct the use of chromatin-modifying drugs to restore the expression of salutary genes in endothelial cells, cardiomyocytes, and bone marrow-derived angiogenic cells (Figure  4).

Epigenetic marks in cardiovascular precision medicine should not be considered as self-standing layers of biological regulation but should be always interpreted in light of the individual genetic background. A growing body of evidence suggests the existence of a dynamic cross-talk between genetics and epigenetics. DNA methylation changes connect directly with genetically regulated gene expression variation, and, in turn, genetic variation significantly impacts on epigenetic routes and chromatin architecture.118  ,  119 Hence, future personalized approaches should arise from a full integration of genetic and epigenetic maps in an attempt to build a multidimensional view of our genome.

The causality of presumed epigenetic events and cardiovascular phenotype requires careful consideration. Indeed, epigenetic markers, like any other molecular marker, are vulnerable to confounding and reverse causation. In this respect, framework of Mendelian randomization—a process that interrogates the causal relationships between exposure, epigenetic marks, and outcome—can serve to establish meaningful hierarchies, thus helping to discriminate between epigenetic phenomena and epiphenomena.120  ,  121 The results of large epigenomic studies over the upcoming years will help to decipher the complex link between genetics, epigenetics, and CVD and define and validate the added value of epigenetic information into personalized cardiovascular therapies.

Acknowledgements

F.P. is the recipient of a Sheikh Khalifa’s Foundation Assistant Professorship in Cardiovascular Regenerative Medicine at the Faculty of Medicine, University of Zürich. This work is supported by the Foundation for Cardiovascular Research (Zürich Heart House, Zürich Switzerland), the University of Zürich and Jubiläumsstiftung der Schweizerischen to F.P.; the Holcim Foundation to S.C.; the U.S. National Institutes of Health (RO1 HL080472) and RRM Charitable Fund to P.L; the US National Institutes of Health grants HL091983 and HL126186 to R.K.; and a National Health and Medical Research Council (NHMRC) program grant (1070386 and APP0526681) to A.E.-O.

Conflict of interest: none declared.

References

1

Genome variation in precision medicine
.
Nat Genet
 
2016
;
48
:
701
.

2

Tardif
 
J-C
,
Rhéaume
 
E
,
Lemieux Perreault
 
L-P
,
Grégoire
 
JC
,
Feroz Zada
 
Y
,
Asselin
 
G
,
Provost
 
S
,
Barhdadi
 
A
,
Rhainds
 
D
,
L’Allier
 
PL
,
Ibrahim
 
R
,
Upmanyu
 
R
,
Niesor
 
EJ
,
Benghozi
 
R
,
Suchankova
 
G
,
Laghrissi-Thode
 
F
,
Guertin
 
M-C
,
Olsson
 
AG
,
Mongrain
 
I
,
Schwartz
 
GG
,
Dubé
 
M-P.
 
Pharmacogenomic determinants of the cardiovascular effects of dalcetrapib
.
Circ Cardiovasc Genet
 
2015
;
8
:
372
382
.

3

Tardif
 
JC
,
Rhainds
 
D
,
Brodeur
 
M
,
Feroz Zada
 
Y
,
Fouodjio
 
R
,
Provost
 
S
,
Boule
 
M
,
Alem
 
S
,
Gregoire
 
JC
,
L’Allier
 
PL
,
Ibrahim
 
R
,
Guertin
 
MC
,
Mongrain
 
I
,
Olsson
 
AG
,
Schwartz
 
GG
,
Rheaume
 
E
,
Dube
 
MP.
 
Genotype-dependent effects of dalcetrapib on cholesterol efflux and inflammation: concordance with clinical outcomes
.
Circ Cardiovasc Genet
 
2016
;
9
:
340
348
.

4

Tardif
 
JC
,
Rhainds
 
D
,
Rheaume
 
E
,
Dube
 
MP.
 
CETP: pharmacogenomics-based response to the CETP inhibitor dalcetrapib
.
Arterioscler Thromb Vasc Biol
 
2017
;
37
:
396
400
.

5

Sofowora
 
GG
,
Dishy
 
V
,
Muszkat
 
M
,
Xie
 
HG
,
Kim
 
RB
,
Harris
 
PA
,
Prasad
 
HC
,
Byrne
 
DW
,
Nair
 
UB
,
Wood
 
AJ
,
Stein
 
CM.
 
A common beta1-adrenergic receptor polymorphism (Arg389Gly) affects blood pressure response to beta-blockade
.
Clin Pharmacol Ther
 
2003
;
73
:
366
371
.

6

Liu
 
J
,
Liu
 
ZQ
,
Yu
 
BN
,
Xu
 
FH
,
Mo
 
W
,
Zhou
 
G
,
Liu
 
YZ
,
Li
 
Q
,
Zhou
 
HH.
 
beta1-Adrenergic receptor polymorphisms influence the response to metoprolol monotherapy in patients with essential hypertension
.
Clin Pharmacol Ther
 
2006
;
80
:
23
32
.

7

Liu
 
J
,
Liu
 
ZQ
,
Tan
 
ZR
,
Chen
 
XP
,
Wang
 
LS
,
Zhou
 
G
,
Zhou
 
HH.
 
Gly389Arg polymorphism of beta1-adrenergic receptor is associated with the cardiovascular response to metoprolol
.
Clin Pharmacol Ther
 
2003
;
74
:
372
379
.

8

Lobmeyer
 
MT
,
Gong
 
Y
,
Terra
 
SG
,
Beitelshees
 
AL
,
Langaee
 
TY
,
Pauly
 
DF
,
Schofield
 
RS
,
Hamilton
 
KK
,
Herbert Patterson
 
J
,
Adams
 
KF
 Jr
,
Hill
 
JA
,
Aranda
 
JM
 Jr
,
Johnson
 
JA.
 
Synergistic polymorphisms of beta1 and alpha2C-adrenergic receptors and the influence on left ventricular ejection fraction response to beta-blocker therapy in heart failure
.
Pharmacogenet Genomics
 
2007
;
17
:
277
282
.

9

Terra
 
SG
,
Hamilton
 
KK
,
Pauly
 
DF
,
Lee
 
CR
,
Patterson
 
JH
,
Adams
 
KF
,
Schofield
 
RS
,
Belgado
 
BS
,
Hill
 
JA
,
Aranda
 
JM
,
Yarandi
 
HN
,
Johnson
 
JA.
 
Beta1-adrenergic receptor polymorphisms and left ventricular remodeling changes in response to beta-blocker therapy
.
Pharmacogenet Genomics
 
2005
;
15
:
227
234
.

10

Johnson
 
JA
,
Zineh
 
I
,
Puckett
 
BJ
,
McGorray
 
SP
,
Yarandi
 
HN
,
Pauly
 
DF.
 
Beta 1-adrenergic receptor polymorphisms and antihypertensive response to metoprolol
.
Clin Pharmacol Ther
 
2003
;
74
:
44
52
.

11

Mialet Perez
 
J
,
Rathz
 
DA
,
Petrashevskaya
 
NN
,
Hahn
 
HS
,
Wagoner
 
LE
,
Schwartz
 
A
,
Dorn
 
GW
,
Liggett
 
SB.
 
Beta 1-adrenergic receptor polymorphisms confer differential function and predisposition to heart failure
.
Nat Med
 
2003
;
9
:
1300
1305
.

12

Kaye
 
DM
,
Smirk
 
B
,
Williams
 
C
,
Jennings
 
G
,
Esler
 
M
,
Holst
 
D.
 
Beta-adrenoceptor genotype influences the response to carvedilol in patients with congestive heart failure
.
Pharmacogenetics
 
2003
;
13
:
379
382
.

13

Mason
 
DA
,
Moore
 
JD
,
Green
 
SA
,
Liggett
 
SBA
,
Gain
 
O.
 
Function polymorphism in a G-protein coupling domain of the human beta1-adrenergic receptor
.
J Biol Chem
 
1999
;
274
:
12670
12674
.

14

Liggett
 
SB
,
Mialet-Perez
 
J
,
Thaneemit-Chen
 
S
,
Weber
 
SA
,
Greene
 
SM
,
Hodne
 
D
,
Nelson
 
B
,
Morrison
 
J
,
Domanski
 
MJ
,
Wagoner
 
LE
,
Abraham
 
WT
,
Anderson
 
JL
,
Carlquist
 
JF
,
Krause-Steinrauf
 
HJ
,
Lazzeroni
 
LC
,
Port
 
JD
,
Lavori
 
PW
,
Bristow
 
MR.
 
A polymorphism within a conserved beta(1)-adrenergic receptor motif alters cardiac function and beta-blocker response in human heart failure
.
Proc Natl Acad Sci U S A
 
2006
;
103
:
11288
11293
.

15

White
 
HL
,
de Boer
 
RA
,
Maqbool
 
A
,
Greenwood
 
D
,
van Veldhuisen
 
DJ
,
Cuthbert
 
R
,
Ball
 
SG
,
Hall
 
AS
,
Balmforth
 
AJ
,
Group
 
M-HS.
 
An evaluation of the beta-1 adrenergic receptor Arg389Gly polymorphism in individuals with heart failure: a MERIT-HF sub-study
.
Eur J Heart Fail
 
2003
;
5
:
463
468
.

16

Group
 
SC
,
Link
 
E
,
Parish
 
S
,
Armitage
 
J
,
Bowman
 
L
,
Heath
 
S
,
Matsuda
 
F
,
Gut
 
I
,
Lathrop
 
M
,
Collins
 
R.
 
SLCO1B1 variants and statin-induced myopathy–a genomewide study
.
N Engl J Med
 
2008
;
359
:
789
799
.

17

Chasman
 
DI
,
Giulianini
 
F
,
MacFadyen
 
J
,
Barratt
 
BJ
,
Nyberg
 
F
,
Ridker
 
PM.
 
Genetic determinants of statin-induced low-density lipoprotein cholesterol reduction: the Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin (JUPITER) trial
.
Circ Cardiovasc Genet
 
2012
;
5
:
257
264
.

18

Zhou
 
K
,
Pedersen
 
HK
,
Dawed
 
AY
,
Pearson
 
ER.
 
Pharmacogenomics in diabetes mellitus: insights into drug action and drug discovery
.
Nat Rev Endocrinol
 
2016
;
12
:
337
346
.

19

Slack
 
JM.
 
Conrad Hal Waddington: the last Renaissance biologist?
 
Nat Rev Genet
 
2002
;
3
:
889
895
.

20

Noble
 
D.
 
Conrad Waddington and the origin of epigenetics
.
J Exp Biol
 
2015
;
218
:
816
818
.

21

Gonzalez-Recio
 
O
,
Toro
 
MA
,
Bach
 
A.
 
Past, present, and future of epigenetics applied to livestock breeding
.
Front Genet
 
2015
;
6
:
305
.

22

Handy
 
DE
,
Castro
 
R
,
Loscalzo
 
J.
 
Epigenetic modifications: basic mechanisms and role in cardiovascular disease
.
Circulation
 
2011
;
123
:
2145
2156
.

23

Baccarelli
 
A
,
Ghosh
 
S.
 
Environmental exposures, epigenetics and cardiovascular disease
.
Curr Opin Clin Nutr Metab Care
 
2012
;
15
:
323
329
.

24

Miranda
 
TB
,
Jones
 
PA.
 
DNA methylation: the nuts and bolts of repression
.
J Cell Physiol
 
2007
;
213
:
384
390
.

25

Matouk
 
CC
,
Marsden
 
PA.
 
Epigenetic regulation of vascular endothelial gene expression
.
Circ Res
 
2008
;
102
:
873
887
.

26

Jenuwein
 
T
,
Allis
 
CD.
 
Translating the histone code
.
Science
 
2001
;
293
:
1074
1080
.

27

Cooper
 
ME
,
El-Osta
 
A.
 
Epigenetics: mechanisms and implications for diabetic complications
.
Circ Res
 
2010
;
107
:
1403
1413
.

28

Winnik
 
S
,
Auwerx
 
J
,
Sinclair
 
DA
,
Matter
 
CM.
 
Protective effects of sirtuins in cardiovascular diseases: from bench to bedside
.
Eur Heart J
 
2015
;
36
:
3404
3412
.

29

Keating
 
ST
,
El-Osta
 
A.
 
Transcriptional regulation by the Set7 lysine methyltransferase
.
Epigenetics
 
2013
;
8
:
361
372
.

30

Poller
 
W
,
Dimmeler
 
S
,
Heymans
 
S
,
Zeller
 
T
,
Haas
 
J
,
Karakas
 
M
,
Leistner
 
DM
,
Jakob
 
P
,
Nakagawa
 
S
,
Blankenberg
 
S
,
Engelhardt
 
S
,
Thum
 
T
,
Weber
 
C
,
Meder
 
B
,
Hajjar
 
R
,
Landmesser
 
U.
 
Non-coding RNAs in cardiovascular diseases: diagnostic and therapeutic perspectives
.
Eur Heart J
 
2017
doi: 10.1093/eurheartj/ehx165.

31

Boon
 
RA
,
Jae
 
N
,
Holdt
 
L
,
Dimmeler
 
S.
 
Long noncoding RNAs: from clinical genetics to therapeutic targets?
 
J Am Coll Cardiol
 
2016
;
67
:
1214
1226
.

32

Brunet
 
A
,
Berger
 
SL.
 
Epigenetics of aging and aging-related disease
.
J Gerontol A Biol Sci Med Sci
 
2014
;
69
(Suppl 1):
S17
S20
.

33

Paneni
 
F
,
Diaz Canestro
 
C
,
Libby
 
P
,
Luscher
 
TF
,
Camici
 
GG.
 
The aging cardiovascular system: understanding it at the cellular and clinical levels
.
J Am Coll Cardiol
 
2017
;
69
:
1952
1967
.

34

Baccarelli
 
A
,
Rienstra
 
M
,
Benjamin
 
EJ.
 
Cardiovascular epigenetics: basic concepts and results from animal and human studies
.
Circ Cardiovasc Genet
 
2010
;
3
:
567
573
.

35

Chen
 
Z
,
Karaplis
 
AC
,
Ackerman
 
SL
,
Pogribny
 
IP
,
Melnyk
 
S
,
Lussier-Cacan
 
S
,
Chen
 
MF
,
Pai
 
A
,
John
 
SW
,
Smith
 
RS
,
Bottiglieri
 
T
,
Bagley
 
P
,
Selhub
 
J
,
Rudnicki
 
MA
,
James
 
SJ
,
Rozen
 
R.
 
Mice deficient in methylenetetrahydrofolate reductase exhibit hyperhomocysteinemia and decreased methylation capacity, with neuropathology and aortic lipid deposition
.
Hum Mol Genet
 
2001
;
10
:
433
443
.

36

Lund
 
G
,
Andersson
 
L
,
Lauria
 
M
,
Lindholm
 
M
,
Fraga
 
MF
,
Villar-Garea
 
A
,
Ballestar
 
E
,
Esteller
 
M
,
Zaina
 
S.
 
DNA methylation polymorphisms precede any histological sign of atherosclerosis in mice lacking apolipoprotein E
.
J Biol Chem
 
2004
;
279
:
29147
29154
.

37

Turunen
 
MP
,
Aavik
 
E
,
Yla-Herttuala
 
S.
 
Epigenetics and atherosclerosis
.
Biochim Biophys Acta
 
2009
;
1790
:
886
891
.

38

Jaiswal
 
S
,
Fontanillas
 
P
,
Flannick
 
J
,
Manning
 
A
,
Grauman
 
PV
,
Mar
 
BG
,
Lindsley
 
RC
,
Mermel
 
CH
,
Burtt
 
N
,
Chavez
 
A
,
Higgins
 
JM
,
Moltchanov
 
V
,
Kuo
 
FC
,
Kluk
 
MJ
,
Henderson
 
B
,
Kinnunen
 
L
,
Koistinen
 
HA
,
Ladenvall
 
C
,
Getz
 
G
,
Correa
 
A
,
Banahan
 
BF
,
Gabriel
 
S
,
Kathiresan
 
S
,
Stringham
 
HM
,
McCarthy
 
MI
,
Boehnke
 
M
,
Tuomilehto
 
J
,
Haiman
 
C
,
Groop
 
L
,
Atzmon
 
G
,
Wilson
 
JG
,
Neuberg
 
D
,
Altshuler
 
D
,
Ebert
 
BL.
 
Age-related clonal hematopoiesis associated with adverse outcomes
.
N Engl J Med
 
2014
;
371
:
2488
2498
.

39

Jaiswal
 
S
,
Natarajan
 
P
,
Silver
 
AJ
,
Gibson
 
CJ
,
Bick
 
AG
,
Shvartz
 
E
,
McConkey
 
M
,
Gupta
 
N
,
Gabriel
 
S
,
Ardissino
 
D
,
Baber
 
U
,
Mehran
 
R
,
Fuster
 
V
,
Danesh
 
J
,
Frossard
 
P
,
Saleheen
 
D
,
Melander
 
O
,
Sukhova
 
GK
,
Neuberg
 
D
,
Libby
 
P
,
Kathiresan
 
S
,
Ebert
 
BL.
 
Clonal hematopoiesis and risk of atherosclerotic cardiovascular disease
.
N Engl J Med
 
2017
;
377
:
111
121
.

40

Fuster
 
JJ
,
MacLauchlan
 
S
,
Zuriaga
 
MA
,
Polackal
 
MN
,
Ostriker
 
AC
,
Chakraborty
 
R
,
Wu
 
CL
,
Sano
 
S
,
Muralidharan
 
S
,
Rius
 
C
,
Vuong
 
J
,
Jacob
 
S
,
Muralidhar
 
V
,
Robertson
 
AA
,
Cooper
 
MA
,
Andres
 
V
,
Hirschi
 
KK
,
Martin
 
KA
,
Walsh
 
K.
 
Clonal hematopoiesis associated with TET2 deficiency accelerates atherosclerosis development in mice
.
Science
 
2017
;
355
:
842
847
.

41

Bollati
 
V
,
Schwartz
 
J
,
Wright
 
R
,
Litonjua
 
A
,
Tarantini
 
L
,
Suh
 
H
,
Sparrow
 
D
,
Vokonas
 
P
,
Baccarelli
 
A.
 
Decline in genomic DNA methylation through aging in a cohort of elderly subjects
.
Mech Ageing Dev
 
2009
;
130
:
234
239
.

42

Beerman
 
I
,
Bock
 
C
,
Garrison
 
BS
,
Smith
 
ZD
,
Gu
 
H
,
Meissner
 
A
,
Rossi
 
DJ.
 
Proliferation-dependent alterations of the DNA methylation landscape underlie hematopoietic stem cell aging
.
Cell Stem Cell
 
2013
;
12
:
413
425
.

43

Sun
 
D
,
Luo
 
M
,
Jeong
 
M
,
Rodriguez
 
B
,
Xia
 
Z
,
Hannah
 
R
,
Wang
 
H
,
Le
 
T
,
Faull
 
KF
,
Chen
 
R
,
Gu
 
H
,
Bock
 
C
,
Meissner
 
A
,
Gottgens
 
B
,
Darlington
 
GJ
,
Li
 
W
,
Goodell
 
MA.
 
Epigenomic profiling of young and aged HSCs reveals concerted changes during aging that reinforce self-renewal
.
Cell Stem Cell
 
2014
;
14
:
673
688
.

44

Menghini
 
R
,
Casagrande
 
V
,
Federici
 
M.
 
MicroRNAs in endothelial senescence and atherosclerosis
.
J Cardiovasc Transl Res
 
2013
;
6
:
924
930
.

45

Gorospe
 
M
,
Abdelmohsen
 
K.
 
MicroRegulators come of age in senescence
.
Trends Genet
 
2011
;
27
:
233
241
.

46

Friso
 
S
,
Pizzolo
 
F
,
Choi
 
SW
,
Guarini
 
P
,
Castagna
 
A
,
Ravagnani
 
V
,
Carletto
 
A
,
Pattini
 
P
,
Corrocher
 
R
,
Olivieri
 
O.
 
Epigenetic control of 11 beta-hydroxysteroid dehydrogenase 2 gene promoter is related to human hypertension
.
Atherosclerosis
 
2008
;
199
:
323
327
.

47

Kato
 
N
,
Loh
 
M
,
Takeuchi
 
F
,
Verweij
 
N
,
Wang
 
X
,
Zhang
 
W
,
Kelly
 
TN
,
Saleheen
 
D
,
Lehne
 
B
,
Mateo Leach
 
I
,
Drong
 
AW
,
Abbott
 
J
,
Wahl
 
S
,
Tan
 
ST
,
Scott
 
WR
,
Campanella
 
G
,
Chadeau-Hyam
 
M
,
Afzal
 
U
,
Ahluwalia
 
TS
,
Bonder
 
MJ
,
Chen
 
P
,
Dehghan
 
A
,
Edwards
 
TL
,
Esko
 
T
,
Go
 
MJ
,
Harris
 
SE
,
Hartiala
 
J
,
Kasela
 
S
,
Kasturiratne
 
A
,
Khor
 
CC
,
Kleber
 
ME
,
Li
 
H
,
Mok
 
ZY
,
Nakatochi
 
M
,
Sapari
 
NS
,
Saxena
 
R
,
Stewart
 
AF
,
Stolk
 
L
,
Tabara
 
Y
,
Teh
 
AL
,
Wu
 
Y
,
Wu
 
JY
,
Zhang
 
Y
,
Aits
 
I
,
Da Silva Couto Alves
 
A
,
Das
 
S
,
Dorajoo
 
R
,
Hopewell
 
JC
,
Kim
 
YK
,
Koivula
 
RW
,
Luan
 
J
,
Lyytikainen
 
LP
,
Nguyen
 
QN
,
Pereira
 
MA
,
Postmus
 
I
,
Raitakari
 
OT
,
Scannell Bryan
 
M
,
Scott
 
RA
,
Sorice
 
R
,
Tragante
 
V
,
Traglia
 
M
,
White
 
J
,
Yamamoto
 
K
,
Zhang
 
Y
,
Adair
 
LS
,
Ahmed
 
A
,
Akiyama
 
K
,
Asif
 
R
,
Aung
 
T
,
Barroso
 
I
,
Bjonnes
 
A
,
Braun
 
TR
,
Cai
 
H
,
Chang
 
LC
,
Chen
 
CH
,
Cheng
 
CY
,
Chong
 
YS
,
Collins
 
R
,
Courtney
 
R
,
Davies
 
G
,
Delgado
 
G
,
Do
 
LD
,
Doevendans
 
PA
,
Gansevoort
 
RT
,
Gao
 
YT
,
Grammer
 
TB
,
Grarup
 
N
,
Grewal
 
J
,
Gu
 
D
,
Wander
 
GS
,
Hartikainen
 
AL
,
Hazen
 
SL
,
He
 
J
,
Heng
 
CK
,
Hixson
 
JE
,
Hofman
 
A
,
Hsu
 
C
,
Huang
 
W
,
Husemoen
 
LL
,
Hwang
 
JY
,
Ichihara
 
S
,
Igase
 
M
,
Isono
 
M
,
Justesen
 
JM
,
Katsuya
 
T
,
Kibriya
 
MG
,
Kim
 
YJ
,
Kishimoto
 
M
,
Koh
 
WP
,
Kohara
 
K
,
Kumari
 
M
,
Kwek
 
K
,
Lee
 
NR
,
Lee
 
J
,
Liao
 
J
,
Lieb
 
W
,
Liewald
 
DC
,
Matsubara
 
T
,
Matsushita
 
Y
,
Meitinger
 
T
,
Mihailov
 
E
,
Milani
 
L
,
Mills
 
R
,
Mononen
 
N
,
Muller-Nurasyid
 
M
,
Nabika
 
T
,
Nakashima
 
E
,
Ng
 
HK
,
Nikus
 
K
,
Nutile
 
T
,
Ohkubo
 
T
,
Ohnaka
 
K
,
Parish
 
S
,
Paternoster
 
L
,
Peng
 
H
,
Peters
 
A
,
Pham
 
ST
,
Pinidiyapathirage
 
MJ
,
Rahman
 
M
,
Rakugi
 
H
,
Rolandsson
 
O
,
Rozario
 
MA
,
Ruggiero
 
D
,
Sala
 
CF
,
Sarju
 
R
,
Shimokawa
 
K
,
Snieder
 
H
,
Sparso
 
T
,
Spiering
 
W
,
Starr
 
JM
,
Stott
 
DJ
,
Stram
 
DO
,
Sugiyama
 
T
,
Szymczak
 
S
,
Tang
 
WH
,
Tong
 
L
,
Trompet
 
S
,
Turjanmaa
 
V
,
Ueshima
 
H
,
Uitterlinden
 
AG
,
Umemura
 
S
,
Vaarasmaki
 
M
,
van Dam
 
RM
,
van Gilst
 
WH
,
van Veldhuisen
 
DJ
,
Viikari
 
JS
,
Waldenberger
 
M
,
Wang
 
Y
,
Wang
 
A
,
Wilson
 
R
,
Wong
 
TY
,
Xiang
 
YB
,
Yamaguchi
 
S
,
Ye
 
X
,
Young
 
RD
,
Young
 
TL
,
Yuan
 
JM
,
Zhou
 
X
,
Asselbergs
 
FW
,
Ciullo
 
M
,
Clarke
 
R
,
Deloukas
 
P
,
Franke
 
A
,
Franks
 
PW
,
Franks
 
S
,
Friedlander
 
Y
,
Gross
 
MD
,
Guo
 
Z
,
Hansen
 
T
,
Jarvelin
 
MR
,
Jorgensen
 
T
,
Jukema
 
JW
,
Kahonen
 
M
,
Kajio
 
H
,
Kivimaki
 
M
,
Lee
 
JY
,
Lehtimaki
 
T
,
Linneberg
 
A
,
Miki
 
T
,
Pedersen
 
O
,
Samani
 
NJ
,
Sorensen
 
TI
,
Takayanagi
 
R
,
Toniolo
 
D
 
BIOS-consortium, CARDio GRAMplusCD, LifeLines Cohort Study, InterAct Consortium
 
Ahsan
 
H
,
Allayee
 
H
,
Chen
 
YT
,
Danesh
 
J
,
Deary
 
IJ
,
Franco
 
OH
,
Franke
 
L
,
Heijman
 
BT
,
Holbrook
 
JD
,
Isaacs
 
A
,
Kim
 
BJ
,
Lin
 
X
,
Liu
 
J
,
Marz
 
W
,
Metspalu
 
A
,
Mohlke
 
KL
,
Sanghera
 
DK
,
Shu
 
XO
,
van Meurs
 
JB
,
Vithana
 
E
,
Wickremasinghe
 
AR
,
Wijmenga
 
C
,
Wolffenbuttel
 
BH
,
Yokota
 
M
,
Zheng
 
W
,
Zhu
 
D
,
Vineis
 
P
,
Kyrtopoulos
 
SA
,
Kleinjans
 
JC
,
McCarthy
 
MI
,
Soong
 
R
,
Gieger
 
C
,
Scott
 
J
,
Teo
 
YY
,
He
 
J
,
Elliott
 
P
,
Tai
 
ES
,
van der Harst
 
P
,
Kooner
 
JS
,
Chambers
 
JC.
 
Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation
.
Nat Genet
 
2015
;
47
:
1282
1293
.

48

Wang
 
X
,
Falkner
 
B
,
Zhu
 
H
,
Shi
 
H
,
Su
 
S
,
Xu
 
X
,
Sharma
 
AK
,
Dong
 
Y
,
Treiber
 
F
,
Gutin
 
B
,
Harshfield
 
G
,
Snieder
 
H
,
Christensen
 
BC.
 
A genome-wide methylation study on essential hypertension in young African American males
.
PLoS One
 
2013
;
8
:
e53938.

49

Duarte
 
JD
,
Zineh
 
I
,
Burkley
 
B
,
Gong
 
Y
,
Langaee
 
TY
,
Turner
 
ST
,
Chapman
 
AB
,
Boerwinkle
 
E
,
Gums
 
JG
,
Cooper-Dehoff
 
RM
,
Beitelshees
 
AL
,
Bailey
 
KR
,
Fillingim
 
RB
,
Kone
 
BC
,
Johnson
 
JA.
 
Effects of genetic variation in H3K79 methylation regulatory genes on clinical blood pressure and blood pressure response to hydrochlorothiazide
.
J Transl Med
 
2012
;
10
:
56.

50

Kontaraki
 
JE
,
Marketou
 
ME
,
Zacharis
 
EA
,
Parthenakis
 
FI
,
Vardas
 
PE.
 
MicroRNA-9 and microRNA-126 expression levels in patients with essential hypertension: potential markers of target-organ damage
.
J Am Soc Hypertens
 
2014
;
8
:
368
375
.

51

Paneni
 
F
,
Volpe
 
M
,
Luscher
 
TF
,
Cosentino
 
F.
 
SIRT1, p66(Shc), and Set7/9 in vascular hyperglycemic memory: bringing all the strands together
.
Diabetes
 
2013
;
62
:
1800
1807
.

52

Paneni
 
F
,
Costantino
 
S
,
Cosentino
 
F.
 
Molecular pathways of arterial aging
.
Clin Sci (Lond)
 
2015
;
128
:
69
79
.

53

Costantino
 
S
,
Paneni
 
F
,
Battista
 
R
,
Castello
 
L
,
Capretti
 
G
,
Chiandotto
 
S
,
Tanese
 
L
,
Russo
 
G
,
Pitocco
 
D
,
Lanza
 
GA
,
Volpe
 
M
,
Luscher
 
TF
,
Cosentino
 
F.
 
Impact of glycemic variability on chromatin remodeling, oxidative stress and endothelial dysfunction in type 2 diabetic patients with target HbA1c levels
.
Diabetes
 
2017
;
66
:
2472
2482
.

54

Sapienza
 
C
,
Lee
 
J
,
Powell
 
J
,
Erinle
 
O
,
Yafai
 
F
,
Reichert
 
J
,
Siraj
 
ES
,
Madaio
 
M.
 
DNA methylation profiling identifies epigenetic differences between diabetes patients with ESRD and diabetes patients without nephropathy
.
Epigenetics
 
2011
;
6
:
20
28
.

55

Paneni
 
F
,
Costantino
 
S
,
Battista
 
R
,
Castello
 
L
,
Capretti
 
G
,
Chiandotto
 
S
,
Scavone
 
G
,
Villano
 
A
,
Pitocco
 
D
,
Lanza
 
G
,
Volpe
 
M
,
Luscher
 
TF
,
Cosentino
 
F.
 
Adverse epigenetic signatures by histone methyltransferase Set7 contribute to vascular dysfunction in patients with type 2 diabetes mellitus
.
Circ Cardiovasc Genet
 
2015
;
8
:
150
158
.

56

Avogaro
 
A
,
de Kreutzenberg
 
SV
,
Federici
 
M
,
Fadini
 
GP.
 
The endothelium abridges insulin resistance to premature aging
.
J Am Heart Assoc
 
2013
;
2
:
e000262.

57

Zampetaki
 
A
,
Kiechl
 
S
,
Drozdov
 
I
,
Willeit
 
P
,
Mayr
 
U
,
Prokopi
 
M
,
Mayr
 
A
,
Weger
 
S
,
Oberhollenzer
 
F
,
Bonora
 
E
,
Shah
 
A
,
Willeit
 
J
,
Mayr
 
M.
 
Plasma microRNA profiling reveals loss of endothelial miR-126 and other microRNAs in type 2 diabetes
.
Circ Res
 
2010
;
107
:
810
817
.

58

Meng
 
S
,
Cao
 
JT
,
Zhang
 
B
,
Zhou
 
Q
,
Shen
 
CX
,
Wang
 
CQ.
 
Downregulation of microRNA-126 in endothelial progenitor cells from diabetes patients, impairs their functional properties, via target gene Spred-1
.
J Mol Cell Cardiol
 
2012
;
53
:
64
72
.

59

Mocharla
 
P
,
Briand
 
S
,
Giannotti
 
G
,
Dorries
 
C
,
Jakob
 
P
,
Paneni
 
F
,
Luscher
 
T
,
Landmesser
 
U.
 
AngiomiR-126 expression and secretion from circulating CD34(+) and CD14(+) PBMCs: role for proangiogenic effects and alterations in type 2 diabetics
.
Blood
 
2013
;
121
:
226
236
.

60

Sayols-Baixeras
 
S
,
Irvin
 
MR
,
Arnett
 
DK
,
Elosua
 
R
,
Aslibekyan
 
SW.
 
Epigenetics of lipid phenotypes
.
Curr Cardiovasc Risk Rep
 
2016
;
10
.

61

Paneni
 
F
,
Costantino
 
S
,
Volpe
 
M
,
Luscher
 
TF
,
Cosentino
 
F.
 
Epigenetic signatures and vascular risk in type 2 diabetes: a clinical perspective
.
Atherosclerosis
 
2013
;
230
:
191
197
.

62

Tobi
 
EW
,
Lumey
 
LH
,
Talens
 
RP
,
Kremer
 
D
,
Putter
 
H
,
Stein
 
AD
,
Slagboom
 
PE
,
Heijmans
 
BT.
 
DNA methylation differences after exposure to prenatal famine are common and timing- and sex-specific
.
Hum Mol Genet
 
2009
;
18
:
4046
4053
.

63

Lai
 
CQ
,
Wojczynski
 
MK
,
Parnell
 
LD
,
Hidalgo
 
BA
,
Irvin
 
MR
,
Aslibekyan
 
S
,
Province
 
MA
,
Absher
 
DM
,
Arnett
 
DK
,
Ordovas
 
JM.
 
Epigenome-wide association study of triglyceride postprandial responses to a high-fat dietary challenge
.
J Lipid Res
 
2016
;
57
:
2200
2207
.

64

Irvin
 
MR
,
Zhi
 
D
,
Joehanes
 
R
,
Mendelson
 
M
,
Aslibekyan
 
S
,
Claas
 
SA
,
Thibeault
 
KS
,
Patel
 
N
,
Day
 
K
,
Jones
 
LW
,
Liang
 
L
,
Chen
 
BH
,
Yao
 
C
,
Tiwari
 
HK
,
Ordovas
 
JM
,
Levy
 
D
,
Absher
 
D
,
Arnett
 
DK.
 
Epigenome-wide association study of fasting blood lipids in the genetics of lipid-lowering drugs and diet network study
.
Circulation
 
2014
;
130
:
565
572
.

65

Ono
 
K.
 
Functions of microRNA-33a/b and microRNA therapeutics
.
J Cardiol
 
2016
;
67
:
28
33
.

66

Rask-Andersen
 
M
,
Martinsson
 
D
,
Ahsan
 
M
,
Enroth
 
S
,
Ek
 
WE
,
Gyllensten
 
U
,
Johansson
 
A.
 
Epigenome-wide association study reveals differential DNA methylation in individuals with a history of myocardial infarction
.
Hum Mol Genet
 
2016
;
25
:
4739
4748
.

67

Devaux
 
Y
,
Vausort
 
M
,
Goretti
 
E
,
Nazarov
 
PV
,
Azuaje
 
F
,
Gilson
 
G
,
Corsten
 
MF
,
Schroen
 
B
,
Lair
 
ML
,
Heymans
 
S
,
Wagner
 
DR.
 
Use of circulating microRNAs to diagnose acute myocardial infarction
.
Clin Chem
 
2012
;
58
:
559
567
.

68

D’Alessandra
 
Y
,
Devanna
 
P
,
Limana
 
F
,
Straino
 
S
,
D, Carlo
 
A
,
Brambilla
 
PG
,
Rubino
 
M
,
Carena
 
MC
,
Spazzafumo
 
L
,
De Simone
 
M
,
Micheli
 
B
,
Biglioli
 
P
,
Achilli
 
F
,
Martelli
 
F
,
Maggiolini
 
S
,
Marenzi
 
G
,
Pompilio
 
G
,
Capogrossi
 
MC.
 
Circulating microRNAs are new and sensitive biomarkers of myocardial infarction
.
Eur Heart J
 
2010
;
31
:
2765
2773
.

69

Fiedler
 
J
,
Thum
 
T.
 
MicroRNAs in myocardial infarction
.
Arterioscler Thromb Vasc Biol
 
2013
;
33
:
201
205
.

70

Jaguszewski
 
M
,
Osipova
 
J
,
Ghadri
 
JR
,
Napp
 
LC
,
Widera
 
C
,
Franke
 
J
,
Fijalkowski
 
M
,
Nowak
 
R
,
Fijalkowska
 
M
,
Volkmann
 
I
,
Katus
 
HA
,
Wollert
 
KC
,
Bauersachs
 
J
,
Erne
 
P
,
Luscher
 
TF
,
Thum
 
T
,
Templin
 
C.
 
A signature of circulating microRNAs differentiates takotsubo cardiomyopathy from acute myocardial infarction
.
Eur Heart J
 
2014
;
35
:
999
1006
.

71

Vausort
 
M
,
Wagner
 
DR
,
Devaux
 
Y.
 
Long noncoding RNAs in patients with acute myocardial infarction
.
Circ Res
 
2014
;
115
:
668
677
.

72

Gallego-Fabrega
 
C
,
Carrera
 
C
,
Reny
 
J-L
,
Fontana
 
P
,
Slowik
 
A
,
Pera
 
J
,
Pezzini
 
A
,
Serrano-Heras
 
G
,
Segura
 
T
,
Martí-Fàbregas
 
J
,
Muiño
 
E
,
Cullell
 
N
,
Montaner
 
J
,
Krupinski
 
J
,
Fernandez-Cadenas
 
I.
 
TRAF3 epigenetic regulation is associated with vascular recurrence in patients with ischemic stroke
.
Stroke
 
2016
;
47
:
1180
1186
.

73

Gallego-Fabrega
 
C
,
Carrera
 
C
,
Reny
 
J-L
,
Fontana
 
P
,
Slowik
 
A
,
Pera
 
J
,
Pezzini
 
A
,
Serrano-Heras
 
G
,
Segura
 
T
,
Bin Dukhyil
 
A-AA
,
Martí-Fàbregas
 
J
,
Muiño
 
E
,
Cullell
 
N
,
Montaner
 
J
,
Krupinski
 
J
,
Fernandez-Cadenas
 
I.
 
PPM1A methylation is associated with vascular recurrence in aspirin-treated patients
.
Stroke
 
2016
;
47
:
1926
1929
.

74

Sepramaniam
 
S
,
Tan
 
JR
,
Tan
 
KS
,
DeSilva
 
DA
,
Tavintharan
 
S
,
Woon
 
FP
,
Wang
 
CW
,
Yong
 
FL
,
Karolina
 
DS
,
Kaur
 
P
,
Liu
 
FJ
,
Lim
 
KY
,
Armugam
 
A
,
Jeyaseelan
 
K.
 
Circulating microRNAs as biomarkers of acute stroke
.
Int J Mol Sci
 
2014
;
15
:
1418
1432
.

75

Dykstra-Aiello
 
C
,
Jickling
 
GC
,
Ander
 
BP
,
Shroff
 
N
,
Zhan
 
X
,
Liu
 
D
,
Hull
 
H
,
Orantia
 
M
,
Stamova
 
BS
,
Sharp
 
FR.
 
Altered expression of long noncoding RNAs in blood after ischemic stroke and proximity to putative stroke risk loci
.
Stroke
 
2016
;
47
:
2896
2903
.

76

Movassagh
 
M
,
Choy
 
MK
,
Knowles
 
DA
,
Cordeddu
 
L
,
Haider
 
S
,
Down
 
T
,
Siggens
 
L
,
Vujic
 
A
,
Simeoni
 
I
,
Penkett
 
C
,
Goddard
 
M
,
Lio
 
P
,
Bennett
 
MR
,
Foo
 
RS.
 
Distinct epigenomic features in end-stage failing human hearts
.
Circulation
 
2011
;
124
:
2411
2422
.

77

Haas
 
J
,
Frese
 
KS
,
Park
 
YJ
,
Keller
 
A
,
Vogel
 
B
,
Lindroth
 
AM
,
Weichenhan
 
D
,
Franke
 
J
,
Fischer
 
S
,
Bauer
 
A
,
Marquart
 
S
,
Sedaghat-Hamedani
 
F
,
Kayvanpour
 
E
,
Kohler
 
D
,
Wolf
 
NM
,
Hassel
 
S
,
Nietsch
 
R
,
Wieland
 
T
,
Ehlermann
 
P
,
Schultz
 
JH
,
Dosch
 
A
,
Mereles
 
D
,
Hardt
 
S
,
Backs
 
J
,
Hoheisel
 
JD
,
Plass
 
C
,
Katus
 
HA
,
Meder
 
B.
 
Alterations in cardiac DNA methylation in human dilated cardiomyopathy
.
EMBO Mol Med
 
2013
;
5
:
413
429
.

78

Ovchinnikova
 
ES
,
Schmitter
 
D
,
Vegter
 
EL
,
Ter Maaten
 
JM
,
Valente
 
MA
,
Liu
 
LC
,
van der Harst
 
P
,
Pinto
 
YM
,
de Boer
 
RA
,
Meyer
 
S
,
Teerlink
 
JR
,
O’Connor
 
CM
,
Metra
 
M
,
Davison
 
BA
,
Bloomfield
 
DM
,
Cotter
 
G
,
Cleland
 
JG
,
Mebazaa
 
A
,
Laribi
 
S
,
Givertz
 
MM
,
Ponikowski
 
P
,
van der Meer
 
P
,
van Veldhuisen
 
DJ
,
Voors
 
AA
,
Berezikov
 
E.
 
Signature of circulating microRNAs in patients with acute heart failure
.
Eur J Heart Fail
 
2016
;
18
:
414
423
.

79

Ellis
 
KL
,
Cameron
 
VA
,
Troughton
 
RW
,
Frampton
 
CM
,
Ellmers
 
LJ
,
Richards
 
AM.
 
Circulating microRNAs as candidate markers to distinguish heart failure in breathless patients
.
Eur J Heart Fail
 
2013
;
15
:
1138
1147
.

80

Seronde
 
MF
,
Vausort
 
M
,
Gayat
 
E
,
Goretti
 
E
,
Ng
 
LL
,
Squire
 
IB
,
Vodovar
 
N
,
Sadoune
 
M
,
Samuel
 
JL
,
Thum
 
T
,
Solal
 
AC
,
Laribi
 
S
,
Plaisance
 
P
,
Wagner
 
DR
,
Mebazaa
 
A
,
Devaux
 
Y
,
Network
 
G.
 
Circulating microRNAs and outcome in patients with acute heart failure
.
PLoS One
 
2015
;
10
:
e0142237.

81

Fox
 
CS
,
Hall
 
JL
,
Arnett
 
DK
,
Ashley
 
EA
,
Delles
 
C
,
Engler
 
MB
,
Freeman
 
MW
,
Johnson
 
JA
,
Lanfear
 
DE
,
Liggett
 
SB
,
Lusis
 
AJ
,
Loscalzo
 
J
,
MacRae
 
CA
,
Musunuru
 
K
,
Newby
 
LK
,
O’Donnell
 
CJ
,
Rich
 
SS
,
Terzic
 
A
;
American Heart Association Council on Functional G, Translational Biology CoC, Stroke Nursing CoCCCoQoC, Outcomes R, Council on E, Prevention
.
Future translational applications from the contemporary genomics era: a scientific statement from the American Heart Association
.
Circulation
 
2015
;
131
:
1715
1736
.

82

International Human Genome Sequencing Consortium
.
Finishing the euchromatic sequence of the human genome
.
Nature
 
2004
;
431
:
931
945
.

83

Lander
 
ES
,
Linton
 
LM
,
Birren
 
B
,
Nusbaum
 
C
,
Zody
 
MC
,
Baldwin
 
J
,
Devon
 
K
,
Dewar
 
K
,
Doyle
 
M
,
FitzHugh
 
W
,
Funke
 
R
,
Gage
 
D
,
Harris
 
K
,
Heaford
 
A
,
Howland
 
J
,
Kann
 
L
,
Lehoczky
 
J
,
LeVine
 
R
,
McEwan
 
P
,
McKernan
 
K
,
Meldrim
 
J
,
Mesirov
 
JP
,
Miranda
 
C
,
Morris
 
W
,
Naylor
 
J
,
Raymond
 
C
,
Rosetti
 
M
,
Santos
 
R
,
Sheridan
 
A
,
Sougnez
 
C
,
Stange
 
TY
,
Stojanovic
 
N
,
Subramanian
 
A
,
Wyman
 
D
,
Rogers
 
J
,
Sulston
 
J
,
Ainscough
 
R
,
Beck
 
S
,
Bentley
 
D
,
Burton
 
J
,
Clee
 
C
,
Carter
 
N
,
Coulson
 
A
,
Deadman
 
R
,
Deloukas
 
P
,
Dunham
 
A
,
Dunham
 
I
,
Durbin
 
R
,
French
 
L
,
Grafham
 
D
,
Gregory
 
S
,
Hubbard
 
T
,
Humphray
 
S
,
Hunt
 
A
,
Jones
 
M
,
Lloyd
 
C
,
McMurray
 
A
,
Matthews
 
L
,
Mercer
 
S
,
Milne
 
S
,
Mullikin
 
JC
,
Mungall
 
A
,
Plumb
 
R
,
Ross
 
M
,
Shownkeen
 
R
,
Sims
 
S
,
Waterston
 
RH
,
Wilson
 
RK
,
Hillier
 
LW
,
McPherson
 
JD
,
Marra
 
MA
,
Mardis
 
ER
,
Fulton
 
LA
,
Chinwalla
 
AT
,
Pepin
 
KH
,
Gish
 
WR
,
Chissoe
 
SL
,
Wendl
 
MC
,
Delehaunty
 
KD
,
Miner
 
TL
,
Delehaunty
 
A
,
Kramer
 
JB
,
Cook
 
LL
,
Fulton
 
RS
,
Johnson
 
DL
,
Minx
 
PJ
,
Clifton
 
SW
,
Hawkins
 
T
,
Branscomb
 
E
,
Predki
 
P
,
Richardson
 
P
,
Wenning
 
S
,
Slezak
 
T
,
Doggett
 
N
,
Cheng
 
JF
,
Olsen
 
A
,
Lucas
 
S
,
Elkin
 
C
,
Uberbacher
 
E
,
Frazier
 
M
,
Gibbs
 
RA
,
Muzny
 
DM
,
Scherer
 
SE
,
Bouck
 
JB
,
Sodergren
 
EJ
,
Worley
 
KC
,
Rives
 
CM
,
Gorrell
 
JH
,
Metzker
 
ML
,
Naylor
 
SL
,
Kucherlapati
 
RS
,
Nelson
 
DL
,
Weinstock
 
GM
,
Sakaki
 
Y
,
Fujiyama
 
A
,
Hattori
 
M
,
Yada
 
T
,
Toyoda
 
A
,
Itoh
 
T
,
Kawagoe
 
C
,
Watanabe
 
H
,
Totoki
 
Y
,
Taylor
 
T
,
Weissenbach
 
J
,
Heilig
 
R
,
Saurin
 
W
,
Artiguenave
 
F
,
Brottier
 
P
,
Bruls
 
T
,
Pelletier
 
E
,
Robert
 
C
,
Wincker
 
P
,
Smith
 
DR
,
Doucette-Stamm
 
L
,
Rubenfield
 
M
,
Weinstock
 
K
,
Lee
 
HM
,
Dubois
 
J
,
Rosenthal
 
A
,
Platzer
 
M
,
Nyakatura
 
G
,
Taudien
 
S
,
Rump
 
A
,
Yang
 
H
,
Yu
 
J
,
Wang
 
J
,
Huang
 
G
,
Gu
 
J
,
Hood
 
L
,
Rowen
 
L
,
Madan
 
A
,
Qin
 
S
,
Davis
 
RW
,
Federspiel
 
NA
,
Abola
 
AP
,
Proctor
 
MJ
,
Myers
 
RM
,
Schmutz
 
J
,
Dickson
 
M
,
Grimwood
 
J
,
Cox
 
DR
,
Olson
 
MV
,
Kaul
 
R
,
Raymond
 
C
,
Shimizu
 
N
,
Kawasaki
 
K
,
Minoshima
 
S
,
Evans
 
GA
,
Athanasiou
 
M
,
Schultz
 
R
,
Roe
 
BA
,
Chen
 
F
,
Pan
 
H
,
Ramser
 
J
,
Lehrach
 
H
,
Reinhardt
 
R
,
McCombie
 
WR
,
de la Bastide
 
M
,
Dedhia
 
N
,
Blocker
 
H
,
Hornischer
 
K
,
Nordsiek
 
G
,
Agarwala
 
R
,
Aravind
 
L
,
Bailey
 
JA
,
Bateman
 
A
,
Batzoglou
 
S
,
Birney
 
E
,
Bork
 
P
,
Brown
 
DG
,
Burge
 
CB
,
Cerutti
 
L
,
Chen
 
HC
,
Church
 
D
,
Clamp
 
M
,
Copley
 
RR
,
Doerks
 
T
,
Eddy
 
SR
,
Eichler
 
EE
,
Furey
 
TS
,
Galagan
 
J
,
Gilbert
 
JG
,
Harmon
 
C
,
Hayashizaki
 
Y
,
Haussler
 
D
,
Hermjakob
 
H
,
Hokamp
 
K
,
Jang
 
W
,
Johnson
 
LS
,
Jones
 
TA
,
Kasif
 
S
,
Kaspryzk
 
A
,
Kennedy
 
S
,
Kent
 
WJ
,
Kitts
 
P
,
Koonin
 
EV
,
Korf
 
I
,
Kulp
 
D
,
Lancet
 
D
,
Lowe
 
TM
,
McLysaght
 
A
,
Mikkelsen
 
T
,
Moran
 
JV
,
Mulder
 
N
,
Pollara
 
VJ
,
Ponting
 
CP
,
Schuler
 
G
,
Schultz
 
J
,
Slater
 
G
,
Smit
 
AF
,
Stupka
 
E
,
Szustakowki
 
J
,
Thierry-Mieg
 
D
,
Thierry-Mieg
 
J
,
Wagner
 
L
,
Wallis
 
J
,
Wheeler
 
R
,
Williams
 
A
,
Wolf
 
YI
,
Wolfe
 
KH
,
Yang
 
SP
,
Yeh
 
RF
,
Collins
 
F
,
Guyer
 
MS
,
Peterson
 
J
,
Felsenfeld
 
A
,
Wetterstrand
 
KA
,
Patrinos
 
A
,
Morgan
 
MJ
,
de Jong
 
P
,
Catanese
 
JJ
,
Osoegawa
 
K
,
Shizuya
 
H
,
Choi
 
S
,
Chen
 
YJ
,
Szustakowki
 
J
,
International Human Genome Sequencing
 
C.
 
Initial sequencing and analysis of the human genome
.
Nature
 
2001
;
409
:
860
921
.

84

Green
 
ED
,
Guyer
 
MS
;
National Human Genome Research Institute
.
Charting a course for genomic medicine from base pairs to bedside
.
Nature
 
2011
;
470
:
204
213
.

85

Altman
 
RB
,
Ashley
 
EA.
 
Using ‘big data’ to dissect clinical heterogeneity
.
Circulation
 
2015
;
131
:
232
233
.

86

Antman
 
EM
,
Loscalzo
 
J.
 
Precision medicine in cardiology
.
Nat Rev Cardiol
 
2016
;
13
:
591
602
.

87

Libertini
 
E
,
Heath
 
SC
,
Hamoudi
 
RA
,
Gut
 
M
,
Ziller
 
MJ
,
Herrero
 
J
,
Czyz
 
A
,
Ruotti
 
V
,
Stunnenberg
 
HG
,
Frontini
 
M
,
Ouwehand
 
WH
,
Meissner
 
A
,
Gut
 
IG
,
Beck
 
S.
 
Saturation analysis for whole-genome bisulfite sequencing data
.
Nat Biotechnol
 
2016
; doi: 10.1038/nbt.3524. Published online ahead of print 27 June 2016.

88

Libertini
 
E
,
Heath
 
SC
,
Hamoudi
 
RA
,
Gut
 
M
,
Ziller
 
MJ
,
Czyz
 
A
,
Ruotti
 
V
,
Stunnenberg
 
HG
,
Frontini
 
M
,
Ouwehand
 
WH
,
Meissner
 
A
,
Gut
 
IG
,
Beck
 
S.
 
Information recovery from low coverage whole-genome bisulfite sequencing
.
Nat Commun
 
2016
;
7
:
11306.

89

Bock
 
C
,
Halbritter
 
F
,
Carmona
 
FJ
,
Tierling
 
S
,
Datlinger
 
P
,
Assenov
 
Y
,
Berdasco
 
M
,
Bergmann
 
AK
,
Booher
 
K
,
Busato
 
F
,
Campan
 
M
,
Dahl
 
C
,
Dahmcke
 
CM
,
Diep
 
D
,
Fernández
 
AF
,
Gerhauser
 
C
,
Haake
 
A
,
Heilmann
 
K
,
Holcomb
 
T
,
Hussmann
 
D
,
Ito
 
M
,
Kläver
 
R
,
Kreutz
 
M
,
Kulis
 
M
,
Lopez
 
V
,
Nair
 
SS
,
Paul
 
DS
,
Plongthongkum
 
N
,
Qu
 
W
,
Queirós
 
AC
,
Reinicke
 
F
,
Sauter
 
G
,
Schlomm
 
T
,
Statham
 
A
,
Stirzaker
 
C
,
Strogantsev
 
R
,
Urdinguio
 
RG
,
Walter
 
K
,
Weichenhan
 
D
,
Weisenberger
 
DJ
,
Beck
 
S
,
Clark
 
SJ
,
Esteller
 
M
,
Ferguson-Smith
 
AC
,
Fraga
 
MF
,
Guldberg
 
P
,
Hansen
 
LL
,
Laird
 
PW
,
Martín-Subero
 
JI
,
Nygren
 
AOH
,
Peist
 
R
,
Plass
 
C
,
Shames
 
DS
,
Siebert
 
R
,
Sun
 
X
,
Tost
 
J
,
Walter
 
J
,
Zhang
 
K.
 
Quantitative comparison of DNA methylation assays for biomarker development and clinical applications
.
Nat Biotechnol
 
2016
;
34
:
726
737
.

90

Swan
 
M.
 
The quantified self: fundamental disruption in big data science and biological discovery
.
Big Data
 
2013
;
1
:
85
99
.

91

Ardlie
 
KG
,
Deluca
 
DS
,
Segre
 
AV
,
Sullivan
 
TJ
,
Young
 
TR
,
Gelfand
 
ET
,
Trowbridge
 
CA
,
Maller
 
JB
,
Tukiainen
 
T
,
Lek
 
M
,
Ward
 
LD
,
Kheradpour
 
P
,
Iriarte
 
B
,
Meng
 
Y
,
Palmer
 
CD
,
Esko
 
T
,
Winckler
 
W
,
Hirschhorn
 
JN
,
Kellis
 
M
,
MacArthur
 
DG
,
Getz
 
G
,
Shabalin
 
AA
,
Li
 
G
,
Zhou
 
Y-H
,
Nobel
 
AB
,
Rusyn
 
I
,
Wright
 
FA
,
Lappalainen
 
T
,
Ferreira
 
PG
,
Ongen
 
H
,
Rivas
 
MA
,
Battle
 
A
,
Mostafavi
 
S
,
Monlong
 
J
,
Sammeth
 
M
,
Mele
 
M
,
Reverter
 
F
,
Goldmann
 
JM
,
Koller
 
D
,
Guigo
 
R
,
McCarthy
 
MI
,
Dermitzakis
 
ET
,
Gamazon
 
ER
,
Im
 
HK
,
Konkashbaev
 
A
,
Nicolae
 
DL
,
Cox
 
NJ
,
Flutre
 
T
,
Wen
 
X
,
Stephens
 
M
,
Pritchard
 
JK
,
Tu
 
Z
,
Zhang
 
B
,
Huang
 
T
,
Long
 
Q
,
Lin
 
L
,
Yang
 
J
,
Zhu
 
J
,
Liu
 
J
,
Brown
 
A
,
Mestichelli
 
B
,
Tidwell
 
D
,
Lo
 
E
,
Salvatore
 
M
,
Shad
 
S
,
Thomas
 
JA
,
Lonsdale
 
JT
,
Moser
 
MT
,
Gillard
 
BM
,
Karasik
 
E
,
Ramsey
 
K
,
Choi
 
C
,
Foster
 
BA
,
Syron
 
J
,
Fleming
 
J
,
Magazine
 
H
,
Hasz
 
R
,
Walters
 
GD
,
Bridge
 
JP
,
Miklos
 
M
,
Sullivan
 
S
,
Barker
 
LK
,
Traino
 
HM
,
Mosavel
 
M
,
Siminoff
 
LA
,
Valley
 
DR
,
Rohrer
 
DC
,
Jewell
 
SD
,
Branton
 
PA
,
Sobin
 
LH
,
Barcus
 
M
,
Qi
 
L
,
McLean
 
J
,
Hariharan
 
P
,
Um
 
KS
,
Wu
 
S
,
Tabor
 
D
,
Shive
 
C
,
Smith
 
AM
,
Buia
 
SA
,
Undale
 
AH
,
Robinson
 
KL
,
Roche
 
N
,
Valentino
 
KM
,
Britton
 
A
,
Burges
 
R
,
Bradbury
 
D
,
Hambright
 
KW
,
Seleski
 
J
,
Korzeniewski
 
GE
,
Erickson
 
K
,
Marcus
 
Y
,
Tejada
 
J
,
Taherian
 
M
,
Lu
 
C
,
Basile
 
M
,
Mash
 
DC
,
Volpi
 
S
,
Struewing
 
JP
,
Temple
 
GF
,
Boyer
 
J
,
Colantuoni
 
D
,
Little
 
R
,
Koester
 
S
,
Carithers
 
LJ
,
Moore
 
HM
,
Guan
 
P
,
Compton
 
C
,
Sawyer
 
SJ
,
Demchok
 
JP
,
Vaught
 
JB
,
Rabiner
 
CA
,
Lockhart
 
NC
,
Ardlie
 
KG
,
Getz
 
G
,
Wright
 
FA
,
Kellis
 
M
,
Volpi
 
S
,
Dermitzakis
 
ET.
 
Human genomics. The genotype-tissue expression (GTEx) pilot analysis: multitissue gene regulation in humans
.
Science
 
2015
;
348
:
648
660
.

92

McKinsey
 
TA.
 
Therapeutic potential for HDAC inhibitors in the heart
.
Annu Rev Pharmacol Toxicol
 
2012
;
52
:
303
319
.

93

Khan
 
AW
,
Ziemann
 
M
,
Corcoran
 
SJ
,
K
 
NH
,
Okabe
 
J
,
Rafehi
 
H
,
Maxwell
 
SS
,
Esler
 
MD
,
El-Osta
 
A.
 
NET silencing by let-7i in postural tachycardia syndrome
.
JCI Insight
 
2017
;
2
:
e90183.

94

Heidecker
 
B
,
Lamirault
 
G
,
Kasper
 
EK
,
Wittstein
 
IS
,
Champion
 
HC
,
Breton
 
E
,
Russell
 
SD
,
Hall
 
J
,
Kittleson
 
MM
,
Baughman
 
KL
,
Hare
 
JM.
 
The gene expression profile of patients with new-onset heart failure reveals important gender-specific differences
.
Eur Heart J
 
2010
;
31
:
1188
1196
.

95

Keating
 
ST
,
Plutzky
 
J
,
El-Osta
 
A.
 
Epigenetic changes in diabetes and cardiovascular risk
.
Circ Res
 
2016
;
118
:
1706
1722
.

96

DeLaughter
 
DM
,
Bick
 
AG
,
Wakimoto
 
H
,
McKean
 
D
,
Gorham
 
JM
,
Kathiriya
 
IS
,
Hinson
 
JT
,
Homsy
 
J
,
Gray
 
J
,
Pu
 
W
,
Bruneau
 
BG
,
Seidman
 
JG
,
Seidman
 
CE.
 
Single-cell resolution of temporal gene expression during heart development
.
Dev Cell
 
2016
;
39
:
480
490
.

97

Adams
 
RL.
 
Eukaryotic DNA methyltransferases–structure and function
.
Bioessays
 
1995
;
17
:
139
145
.

98

Chaturvedi
 
P
,
Tyagi
 
SC.
 
Epigenetic mechanisms underlying cardiac degeneration and regeneration
.
Int J Cardiol
 
2014
;
173
:
1
11
.

99

Ding
 
X
,
Wang
 
Y
,
Zhang
 
D
,
Wang
 
Y
,
Guo
 
Z
,
Zhang
 
Y.
 
Increased pre-implantation development of cloned bovine embryos treated with 5-aza-2'-deoxycytidine and trichostatin A
.
Theriogenology
 
2008
;
70
:
622
630
.

100

Huangfu
 
D
,
Osafune
 
K
,
Maehr
 
R
,
Guo
 
W
,
Eijkelenboom
 
A
,
Chen
 
S
,
Muhlestein
 
W
,
Melton
 
DA.
 
Induction of pluripotent stem cells from primary human fibroblasts with only Oct4 and Sox2
.
Nat Biotechnol
 
2008
;
26
:
1269
1275
.

101

Maalouf
 
WE
,
Liu
 
Z
,
Brochard
 
V
,
Renard
 
JP
,
Debey
 
P
,
Beaujean
 
N
,
Zink
 
D.
 
Trichostatin A treatment of cloned mouse embryos improves constitutive heterochromatin remodeling as well as developmental potential to term
.
BMC Dev Biol
 
2009
;
9
:
11.

102

Milhem
 
M
,
Mahmud
 
N
,
Lavelle
 
D
,
Araki
 
H
,
DeSimone
 
J
,
Saunthararajah
 
Y
,
Hoffman
 
R.
 
Modification of hematopoietic stem cell fate by 5aza 2'deoxycytidine and trichostatin A
.
Blood
 
2004
;
103
:
4102
4110
.

103

Teng
 
HF
,
Kuo
 
YL
,
Loo
 
MR
,
Li
 
CL
,
Chu
 
TW
,
Suo
 
H
,
Liu
 
HS
,
Lin
 
KH
,
Chen
 
SL.
 
Valproic acid enhances Oct4 promoter activity in myogenic cells
.
J Cell Biochem
 
2010
;
110
:
995
1004
.

104

Makino
 
S
,
Fukuda
 
K
,
Miyoshi
 
S
,
Konishi
 
F
,
Kodama
 
H
,
Pan
 
J
,
Sano
 
M
,
Takahashi
 
T
,
Hori
 
S
,
Abe
 
H
,
Hata
 
J
,
Umezawa
 
A
,
Ogawa
 
S.
 
Cardiomyocytes can be generated from marrow stromal cells in vitro
.
J Clin Invest
 
1999
;
103
:
697
705
.

105

Burlacu
 
A
,
Rosca
 
AM
,
Maniu
 
H
,
Titorencu
 
I
,
Dragan
 
E
,
Jinga
 
V
,
Simionescu
 
M.
 
Promoting effect of 5-azacytidine on the myogenic differentiation of bone marrow stromal cells
.
Eur J Cell Biol
 
2008
;
87
:
173
184
.

106

Ye
 
NS
,
Chen
 
J
,
Luo
 
GA
,
Zhang
 
RL
,
Zhao
 
YF
,
Wang
 
YM.
 
Proteomic profiling of rat bone marrow mesenchymal stem cells induced by 5-azacytidine
.
Stem Cells Dev
 
2006
;
15
:
665
676
.

107

Yoon
 
J
,
Min
 
BG
,
Kim
 
YH
,
Shim
 
WJ
,
Ro
 
YM
,
Lim
 
DS.
 
Differentiation, engraftment and functional effects of pre-treated mesenchymal stem cells in a rat myocardial infarct model
.
Acta Cardiol
 
2005
;
60
:
277
284
.

108

Thal
 
MA
,
Krishnamurthy
 
P
,
Mackie
 
AR
,
Hoxha
 
E
,
Lambers
 
E
,
Verma
 
S
,
Ramirez
 
V
,
Qin
 
G
,
Losordo
 
DW
,
Kishore
 
R.
 
Enhanced angiogenic and cardiomyocyte differentiation capacity of epigenetically reprogrammed mouse and human endothelial progenitor cells augments their efficacy for ischemic myocardial repair
.
Circ Res
 
2012
;
111
:
180
190
.

109

Moore
 
JBt
,
Zhao
 
J
,
Keith
 
MC
,
Amraotkar
 
AR
,
Wysoczynski
 
M
,
Hong
 
KU
,
Bolli
 
R.
 
The epigenetic regulator HDAC1 modulates transcription of a core cardiogenic program in human cardiac mesenchymal stromal cells through a p53-dependent mechanism
.
Stem Cells
 
2016
;
34
:
2916
2929
.

110

Zhang
 
L
,
Chen
 
B
,
Zhao
 
Y
,
Dubielecka
 
PM
,
Wei
 
L
,
Qin
 
GJ
,
Chin
 
YE
,
Wang
 
Y
,
Zhao
 
TC.
 
Inhibition of histone deacetylase-induced myocardial repair is mediated by c-kit in infarcted hearts
.
J Biol Chem
 
2012
;
287
:
39338
39348
.

111

Burba
 
I
,
Colombo
 
GI
,
Staszewsky
 
LI
,
De Simone
 
M
,
Devanna
 
P
,
Nanni
 
S
,
Avitabile
 
D
,
Molla
 
F
,
Cosentino
 
S
,
Russo
 
I
,
De Angelis
 
N
,
Soldo
 
A
,
Biondi
 
A
,
Gambini
 
E
,
Gaetano
 
C
,
Farsetti
 
A
,
Pompilio
 
G
,
Latini
 
R
,
Capogrossi
 
MC
,
Pesce
 
M
,
Kaufman
 
D.
 
Histone deacetylase inhibition enhances self renewal and cardioprotection by human cord blood-derived CD34 cells
.
PLoS One
 
2011
;
6
:
e22158.

112

Vecellio
 
M
,
Meraviglia
 
V
,
Nanni
 
S
,
Barbuti
 
A
,
Scavone
 
A
,
DiFrancesco
 
D
,
Farsetti
 
A
,
Pompilio
 
G
,
Colombo
 
GI
,
Capogrossi
 
MC
,
Gaetano
 
C
,
Rossini
 
A
,
Hosoda
 
T.
 
In vitro epigenetic reprogramming of human cardiac mesenchymal stromal cells into functionally competent cardiovascular precursors
.
PLoS One
 
2012
;
7
:
e51694.

113

Rajasingh
 
J
,
Thangavel
 
J
,
Siddiqui
 
MR
,
Gomes
 
I
,
Gao
 
X-P
,
Kishore
 
R
,
Malik
 
AB
,
Bonini
 
MG.
 
Improvement of cardiac function in mouse myocardial infarction after transplantation of epigenetically-modified bone marrow progenitor cells
.
PLoS One
 
2011
;
6
:
e22550.

114

Zakharova
 
L
,
Nural-Guvener
 
H
,
Feehery
 
L
,
Popovic-Sljukic
 
S
,
Gaballa
 
MA.
 
Transplantation of epigenetically modified adult cardiac c-Kit+ cells retards remodeling and improves cardiac function in ischemic heart failure model
.
Stem Cells Transl Med
 
2015
;
4
:
1086
1096
.

115

Zhang
 
LX
,
DeNicola
 
M
,
Qin
 
X
,
Du
 
J
,
Ma
 
J
,
Tina Zhao
 
Y
,
Zhuang
 
S
,
Liu
 
PY
,
Wei
 
L
,
Qin
 
G
,
Tang
 
Y
,
Zhao
 
TC.
 
Specific inhibition of HDAC4 in cardiac progenitor cells enhances myocardial repairs
.
Am J Physiol Cell Physiol
 
2014
;
307
:
C358
C372
.

116

Lim
 
SY
,
Sivakumaran
 
P
,
Crombie
 
DE
,
Dusting
 
GJ
,
Pebay
 
A
,
Dilley
 
RJ.
 
Enhancing human cardiomyocyte differentiation from induced pluripotent stem cells with Trichostatin A
.
Methods Mol Biol
 
2016
;
1357
:
415
421
.

117

Hodson
 
R.
 
Precision medicine
.
Nature
 
2016
;
537
:
S49.

118

Zhang
 
D
,
Cheng
 
L
,
Badner
 
JA
,
Chen
 
C
,
Chen
 
Q
,
Luo
 
W
,
Craig
 
DW
,
Redman
 
M
,
Gershon
 
ES
,
Liu
 
C.
 
Genetic control of individual differences in gene-specific methylation in human brain
.
Am J Hum Genet
 
2010
;
86
:
411
419
.

119

Costantino
 
S
,
Paneni
 
F
,
Cosentino
 
F.
 
Targeting chromatin remodeling to prevent cardiovascular disease in diabetes
.
Curr Pharm Biotechnol
 
2015
;
16
:
531
543
.

120

Relton
 
CL
,
Davey Smith
 
G.
 
Two-step epigenetic Mendelian randomization: a strategy for establishing the causal role of epigenetic processes in pathways to disease
.
Int J Epidemiol
 
2012
;
41
:
161
176
.

121

Mendelson
 
MM
,
Marioni
 
RE
,
Joehanes
 
R
,
Liu
 
C
,
Hedman
 
AK
,
Aslibekyan
 
S
,
Demerath
 
EW
,
Guan
 
W
,
Zhi
 
D
,
Yao
 
C
,
Huan
 
T
,
Willinger
 
C
,
Chen
 
B
,
Courchesne
 
P
,
Multhaup
 
M
,
Irvin
 
MR
,
Cohain
 
A
,
Schadt
 
EE
,
Grove
 
ML
,
Bressler
 
J
,
North
 
K
,
Sundstrom
 
J
,
Gustafsson
 
S
,
Shah
 
S
,
McRae
 
AF
,
Harris
 
SE
,
Gibson
 
J
,
Redmond
 
P
,
Corley
 
J
,
Murphy
 
L
,
Starr
 
JM
,
Kleinbrink
 
E
,
Lipovich
 
L
,
Visscher
 
PM
,
Wray
 
NR
,
Krauss
 
RM
,
Fallin
 
D
,
Feinberg
 
A
,
Absher
 
DM
,
Fornage
 
M
,
Pankow
 
JS
,
Lind
 
L
,
Fox
 
C
,
Ingelsson
 
E
,
Arnett
 
DK
,
Boerwinkle
 
E
,
Liang
 
L
,
Levy
 
D
,
Deary
 
IJ.
 
Association of body mass index with dna methylation and gene expression in blood cells and relations to cardiometabolic disease: a mendelian randomization approach
.
PLoS Med
 
2017
;
14
:
e1002215
.

This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

Comments

1 Comment
Epigenetic and platelet adaptome
6 February 2019
Fabio M. Pulcinelli
Sapienza University of Rome
We have read with great interest the paper by Costantino et al., which purpose is demonstrating that the miRNAs landscape points to consider epigenetic modification as a tool to individual cardiovascular risk, a customizable treatment, and furthermore, how can some therapies lead to epigenetic changes.1
In addition to the data reported in the article, we would like to add another point.
Recently, the discovery of the existence of a phenomenon called adaptome, and the exposure of eukaryotic cells to certain drugs, are both able to trigger modifications in the expression of mechanisms susceptible to favour their elimination.
Platelets are very sensitive to this phenomenon in response to pharmacological treatment with antiplatelet agents;2, 3 in fact, aspirin can trigger modifications in gene expression,4, 5 can act through the increase of PPARα expression and leads to MRP4 overexpression3. MRP4 expression favours aspirin elimination in eukaryotic cells, bounding its inhibitory effect on COX-1 activity. Moreover, MRP4 over-expression induced by drugs treatment, mediates a hyper-reactive platelet phenotype.6
In addition, others researches showed that people affected by HIV have hyper-reactive platelet phenotype, identified with MRP4 overexpression.7 The same group also demonstrated that, in a randomized trial, low dose aspirin did not improve significantly vascular health in HIV patients.8
Aspirin can induce genomic changes in megakaryocytes leading to platelet P2Y1 up-regulation, and PPARα is the nuclear receptor involved in this regulation. Since P2Y1 is coupled to the same Gq-protein of thromboxane-A2 receptor, platelet adaptation in response to pharmacological inhibition seems not to be receptor specific. However, it appears to involve other receptors with the same biochemical pathway.9
Interestingly, platelets from patients under chronic aspirin treatment loss of specific miRNAs; in fact, in a recent study, we showed that aspirin can decrease platelet miR-21 level leading to increased PPAR-α; this transcriptional effect occurs on megakaryocytes which are responsible of platelet gene expression of adaptome.10
All these data showed that there is an association between platelet miRNAs and cardiovascular disease, even after pharmacological treatments. In fact, aspirin reduces miR21 expression, which will result in MRP4 and P2Y1 expression in human platelets. These factors can influence platelets’ activity.
Therefore, pharmacological treatments can determine different phenotypes in patients. We believe that this aspect should be considered in regards of precision medicine.

References

1. Costantino S, Libby P, Kishore R, Tardif JC, El-Osta A, Paneni F. Epigenetics and precision medicine in cardiovascular patients: from basic concepts to the clinical arena. Eur Heart J 2018; 39:4150-4158.
2. Angiolillo DJ, Cho JR. Aspirin treatment and outcomes in patients undergoing percutaneous coronary intervention: is there a role for pharmacodynamic testing? J Am Coll Cardiol 2014; 64:872-874.
3. Massimi I, Guerriero R, Lotti LV, Lulli V, Borgognone A, Romani F, Barilla F, Gaudio C, Gabbianelli M, Frati L, Pulcinelli FM. Aspirin influences megakaryocytic gene expression leading to upregulation of Multidrug Resistance Protein-4 in human platelets. Br J Clin Pharmacol 2014; 78:1343-1353.
4. Floyd CN, Goodman T, Becker S, Chen N, Mustafa A, Schofield E, Campbell J, Ward M, Sharma P, Ferro A. Increased platelet expression of glycoprotein IIIa following aspirin treatment in aspirin-resistant but not aspirin-sensitive subjects. Br J Clin Pharmacol 2014; 78:320-328.
5. Voora D, Cyr D, Lucas J, Chi JT, Dungan J, McCaffrey TA, Katz R, Newby LK, Kraus WE, Becker RC, Ortel TL, Ginsburg GS. Aspirin exposure reveals novel genes associated with platelet function and cardiovascular events. J Am Coll Cardiol 2013; 62:1267-1276.
6. Massimi I, Lotti LV, Temperilli F, Mancone M, Sardella G, Calcagno S, Turriziani O, Frati L, Pulcinelli FM. Enhanced platelet MRP4 expression and correlation with platelet function in patients under chronic aspirin treatment. Thromb Haemost 2016; 116:1100-1110.
7. Marcantoni E, Allen N, Cambria MR, Dann R, Cammer M, Lhakhang T, O’Brien MP, Kim B, Worgall T, Heguy A, Tsirigos A, J.S. B. Platelet Transcriptome Profiling in HIV and ATP-Binding Cassette Subfamily C Member 4 (ABCC4) as a Mediator of Platelet Activity. JACC: Basic To Translational Science 2018; 3:9-22.
8. O'Brien MP, Hunt PW, Kitch DW, Klingman K, Stein JH, Funderburg NT, Berger JS, Tebas P, Clagett B, Moisi D, Utay NS, Aweeka F, Aberg JA. A Randomized Placebo Controlled Trial of Aspirin Effects on Immune Activation in Chronically Human Immunodeficiency Virus-Infected Adults on Virologically Suppressive Antiretroviral Therapy. Open Forum Infect Dis 2017; 4:ofw278.
9. Massimi I, Alemanno L, Guarino ML, Guerriero R, Mancone M, Ceccacci A, Frati L, Angiolillo DJ, Pulcinelli FM. Aspirin-dependent effects on Purinergic P2Y1 receptor expression. Thromb Haemost 2019; Epub ahead of print.
10. Massimi I, Alemanno L, Guarino ML, Guerriero R, Frati L, Biasucci LM, Pulcinelli FM. MiR-21 role in aspirin-dependent PPARα and MRP4 up-regulation. Research and Practice in Thrombosis and Haemostasis 2018; 2:596-606.

Isabella Massimi a, PhD
Luigi M. Biasucci b, MD
Fabio M. Pulcinelli a, *, MD

a. Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy
b. Department of Cardiovascular Sciences, Catholic University of the Sacred Heart of Rome, Rome, Italy
*Sapienza University of Rome, Department of Experimental Medicine,Viale Regina Elena 324, Rome 00161, Italy
E-mail: fabio.pulcinelli@uniroma1.it
Conflict of interest: none declared.
Submitted on 06/02/2019 12:31 PM GMT