DNA methylation modules associate with incident cardiovascular disease and cumulative risk factor exposure

Deciphering epigenetic regulations in the inflammatory pathways of atopic dermatitis

Atopic dermatitis, commonly referred to as atopic eczema, is a persistent inflammatory skin disorder that predominantly manifests in children but may endure into adulthood. Its clinical management poses challenges due to the absence of a definitive cure, and its prevalence varies across ethnicities, genders, and geographic locations. The epigenetic landscape of AD includes changes in DNA methylation, changes in histone acetylation and methylation, and regulation by non-coding RNAs. These changes affect inflammatory and immune mechanisms, and research has identified AD-specific variations in DNA methylation, particularly in the affected epidermis. Histone modifications, including acetylation, have been associated with the disruption of skin barrier function in AD, suggesting the potential therapeutic benefit of histone deacetylase inhibitors such as belinostat. Furthermore, non-coding RNAs, particularly microRNAs and long non-coding RNAs (lncRNAs), have been implicated in modulating various cellular processes central to AD pathogenesis. Therapeutic implications in AD include the potential use of DNA methylation inhibitors and histone deacetylase inhibitors to correct aberrant methylation patterns and modulate gene expression related to immune responses and skin barrier functions. Additionally, the emerging role of lncRNAs suggests the possibility of using small interfering RNAs or antisense oligonucleotides to inhibit lncRNAs and adjust their regulatory impact on gene expression. In conclusion, the importance of epigenetic elements in AD is becoming increasingly clear as studies highlight the contribution of DNA methylation, histone modifications and, control by non-coding RNAs to the onset and progression of the disease. Understanding these epigenetic changes provides valuable insights for developing targeted therapeutic strategies.

Causal Associations of DNA Methylation and Cardiovascular Disease: A Two-Sample Mendelian Randomization Study

Background

There is growing evidence that concentrations of DNA methylation are associated with cardiovascular disease; however, it is unclear whether this association reflects a causal relationship.

Methods

We utilized a two-sample Mendelian randomization (MR) approach to investigate whether DNA methylation can affect the risk of developing cardiovascular disease in human life. We primarily performed the inverse variance weighted (IVW) method to analyze the causal effect of DNA methylation on multiple cardiovascular diseases. Additionally, to ensure the robustness of our findings, we conducted several sensitivity analyses using alternative methodologies. These analysis methods included maximum likelihood, MR-Egger regression, weighted median method, and weighted model methods.

Results

Inverse variance weighted estimates suggested that an SD increase in DNA methylation Hannum age acceleration exposure increased the risk of cardiac arrhythmias (OR = 1.03, 95% CI 1.00-1.05, p = 0.0290) and atrial fibrillation (OR = 1.03, 95% CI 1.00-1.05, p = 0.0022). We also found that an SD increase in DNA methylation PhenoAge acceleration exposure increased the risk of heart failure (OR = 1.01, 95% CI 1.00-1.03, p = 0.0362). Exposure to DNA methylation-estimated granulocyte proportions was found to increase the risk of hypertension (OR = 1.00, 95% CI 1.00-1.0001, p = 0.0291). Exposure to DNA methylation-estimated plasminogen activator inhibitor-1 levels was found to increase the risk of heart failure (OR = 1.00, 95% CI 1.00-1.00, p = 0.0215).

Conclusion

This study reveals a causal relationship between DNA methylation and CVD. Exposed to high levels of DNA methylation Hannum age acceleration inhabitants with an increased risk of cardiac arrhythmias and atrial fibrillation. DNA methylation PhenoAge acceleration levels exposure levels were positively associated with the increased risk of developing heart failure. This has important implications for the prevention of cardiovascular diseases.

Epigenome-wide perspective of cadmium-associated DNA methylation and its mediation role in the associations of cadmium with lipid levels and dyslipidemia risk

BACKGROUND

Studies demonstrated the associations of cadmium (Cd) with lipid levels and dyslipidemia risk, but the mechanisms involved need further exploration.

OBJECTIVES

We aimed to explore the role of DNA methylation (DNAM) in the relationship of Cd with lipid levels and dyslipidemia risk.

METHODS

Urinary cadmium levels (UCd) were measured by inductively coupled plasma mass spectrometry, serum high-density lipoprotein (HDL), total cholesterol, triglyceride, and low-density lipoprotein were measured with kits, and DNAM was measured using the Infinium MethylationEPIC BeadChip. Robust linear regressions were conducted for epigenome-wide association study. Multivariate linear and logistic regressions were performed to explore the associations of UCd with lipid levels and dyslipidemia risk, respectively. Mediation analyses were conducted to explore potential mediating role of DNAM in the associations of Cd with lipid levels and dyslipidemia risk.

RESULTS

UCd was negatively associated with HDL levels (p = 0.01) and positively associated with dyslipidemia (p < 0.01). There were 92/11 DMPs/DMRs (FDR<0.05) associated with UCd. Cd-associated DNAM and pathways were connected with cardiometabolic diseases and immunity. Cg07829377 (LINC01060) mediated 42.05%/22.88% of the UCd-HDL/UCd-dyslipidemia associations (p = 0.02 and 0.01, respectively).

CONCLUSIONS

Cadmium caused site-specific DNAM alterations and the associations of UCd with lipid levels and dyslipidemia risk may be partially mediated by DNAM.

Arsenic Exposure and Epigenetic Aging: The Association with Cardiovascular Disease and All-Cause Mortality in the Strong Heart Study

BACKGROUND

Inorganic arsenic (As) may increase the risk of cardiovascular disease (CVD) and all-cause mortality through accelerated aging, which can be estimated using epigenetic-based measures.

OBJECTIVES

We evaluated three DNA methylation-based aging measures (PhenoAge, GrimAge, DunedinPACE) (epigenetic aging measures) as potential mediators of the previously reported association of As exposure with CVD incidence, CVD mortality, and all-cause mortality in the Strong Heart Study (SHS), an epidemiological cohort of American Indian adults.

METHODS

Blood DNA methylation and urinary As levels were measured in 2,323 SHS participants (41.5% men, mean age of 55 years old). PhenoAge and GrimAge values were calculated using a residual-based method. We tested the association of urinary As with epigenetic aging measures using linear regression, the association of epigenetic aging measures with the three health outcomes using additive hazards models, and the mediation of As-related CVD incidence, CVD mortality, and all-cause mortality by epigenetic aging measures using the product of coefficients method.

RESULTS

SHS participants with higher vs. lower urinary As levels had similar PhenoAge age, older GrimAge age, and faster DunedinPACE. An interquartile range increase in urinary As was associated with higher of PhenoAge age acceleration [mean difference  ( 95 %  confidence interval ) = 0.48 (0.17, 0.80) years], GrimAge age acceleration [0.80 (0.60, 1.00) years], and DunedinPACE [0.011 (0.005, 0.018)], after adjusting for age, sex, center location, genetic components, smoking status, and body mass index. Of the 347 incident CVD events per 100,000 person-years associated with a doubling in As exposure, 21.3% (9.1, 57.1) and 22.6% (9.5, 56.9), were attributable to differences in GrimAge and DunedinPACE, respectively.

DISCUSSION

Arsenic exposure was associated with older GrimAge and faster DunedinPACE measures of biological age. Furthermore, accelerated biological aging measured from DNA methylation accounted for a relevant fraction of As-associated risk for CVD, CVD mortality, and all-cause mortality in the SHS, supporting the role of As in accelerated aging. Research of the biological underpinnings can contribute to a better understanding of the role of aging in arsenic-related disease. https://doi.org/10.1289/EHP11981.

Next Generation, Modifiable Cardiometabolic Biomarkers: Mitochondrial Adaptation and Metabolic Resilience: A Scientific Statement From the American Heart Association

Cardiometabolic risk is increasing in prevalence across the life span with disproportionate ramifications for youth at socioeconomic disadvantage. Established risk factors and associated disease progression are harder to reverse as they become entrenched over time; if current trends are unchecked, the consequences for individual and societal wellness will become untenable. Interrelated root causes of ectopic adiposity and insulin resistance are understood but identified late in the trajectory of systemic metabolic dysregulation when traditional cardiometabolic risk factors cross current diagnostic thresholds of disease. Thus, children at cardiometabolic risk are often exposed to suboptimal metabolism over years before they present with clinical symptoms, at which point life-long reliance on pharmacotherapy may only mitigate but not reverse the risk. Leading-edge indicators are needed to detect the earliest departure from healthy metabolism, so that targeted, primordial, and primary prevention of cardiometabolic risk is possible. Better understanding of biomarkers that reflect the earliest transitions to dysmetabolism, beginning in utero, ideally biomarkers that are also mechanistic/causal and modifiable, is critically needed. This scientific statement explores emerging biomarkers of cardiometabolic risk across rapidly evolving and interrelated "omic" fields of research (the epigenome, microbiome, metabolome, lipidome, and inflammasome). Connections in each domain to mitochondrial function are identified that may mediate the favorable responses of each of the omic biomarkers featured to a heart-healthy lifestyle, notably to nutritional interventions. Fuller implementation of evidence-based nutrition must address environmental and socioeconomic disparities that can either facilitate or impede response to therapy.

Sex differences in the genetic and molecular mechanisms of coronary artery disease

Sex differences in coronary artery disease (CAD) presentation, risk factors and prognosis have been widely studied. Similarly, studies on atherosclerosis have shown prominent sex differences in plaque biology. Our understanding of the underlying genetic and molecular mechanisms that drive these differences remains fragmented and largely understudied. Through reviewing genetic and epigenetic studies, we identified more than 40 sex-differential candidate genes (13 within known CAD loci) that may explain, at least in part, sex differences in vascular remodeling, lipid metabolism and endothelial dysfunction. Studies with transcriptomic and single-cell RNA sequencing data from atherosclerotic plaques highlight potential sex differences in smooth muscle cell and endothelial cell biology. Especially, phenotypic switching of smooth muscle cells seems to play a crucial role in female atherosclerosis. This matches the known sex differences in atherosclerotic phenotypes, with men being more prone to lipid-rich plaques, while women are more likely to develop fibrous plaques with endothelial dysfunction. To unravel the complex mechanisms that drive sex differences in CAD, increased statistical power and adjustments to study designs and analysis strategies are required. This entails increasing inclusion rates of women, performing well-defined sex-stratified analyses and the integration of multi-omics data.

Impact of Geroscience on Therapeutic Strategies for Older Adults With Cardiovascular Disease: JACC Scientific Statement

Geroscience posits that cardiovascular disease (CVD) and other chronic diseases result from progressive erosion of the effectiveness of homeostatic mechanisms that oppose age-related accumulation of molecular damage. This hypothetical common root to chronic diseases explains why patients with CVD are often affected by multimorbidity and frailty and why older age negatively affects CVD prognosis and treatment response. Gerotherapeutics enhance resilience mechanisms that counter age-related molecular damage to prevent chronic diseases, frailty, and disability, thereby extending healthspan. Here, we describe the main resilience mechanisms of mammalian aging, with a focus on how they can affect CVD pathophysiology. We next present novel gerotherapeutic approaches, some of which are already used in management of CVD, and explore their potential to transform care and management of CVD. The geroscience paradigm is gaining traction broadly in medical specialties, with potential to mitigate premature aging, reduce health care disparities, and improve population healthspan.

Transcriptomic Context of RUNX3 Expression in Monocytes: A Cross-Sectional Analysis

The runt-related transcription factor 3 (RUNX3) regulates the differentiation of monocytes and their response to inflammation. However, the transcriptomic context of RUNX3 expression in blood monocytes remains poorly understood. We aim to learn about RUNX3 from its relationships within transcriptomes of bulk CD14+ cells in adults. This study used immunomagnetically sorted CD14+ cell gene expression microarray data from the Multi-Ethnic Study of Atherosclerosis (MESA, n = 1202, GSE56047) and the Correlated Expression and Disease Association Research (CEDAR, n = 281, E-MTAB-6667) cohorts. The data were preprocessed, subjected to RUNX3-focused correlation analyses and random forest modeling, followed by the gene ontology analysis. Immunity-focused differential ratio analysis with intermediary inference (DRAIMI) was used to integrate the data with protein-protein interaction network. Correlation analysis of RUNX3 expression revealed the strongest positive association for EVL (r_mean = 0.75, p_FDR-MESA = 5.37 × 10^-140, p_FDR-CEDAR = 5.52 × 10^-80), ARHGAP17 (r_mean = 0.74, p_FDR-MESA = 1.13 × 10^-169, p_FDR-CEDAR = 9.20 × 10^-59), DNMT1 (r_mean = 0.74, p_FDR-MESA = 1.10 × 10^-169, p_FDR-CEDAR = 1.67 × 10^-58), and CLEC16A (r_mean = 0.72, p_FDR-MESA = 3.51 × 10^-154, p_FDR-CEDAR = 2.27 × 10^-55), while the top negative correlates were C2ORF76 (r_mean = -0.57, p_FDR-MESA = 8.70 × 10^-94, p_FDR-CEDAR = 1.31 × 10^-25) and TBC1D7 (r_mean = -0.55, p_FDR-MESA = 1.36 × 10^-69, p_FDR-CEDAR = 7.81 × 10^-30). The RUNX3-associated transcriptome signature was involved in mRNA metabolism, signal transduction, and the organization of cytoskeleton, chromosomes, and chromatin, which may all accompany mitosis. Transcriptomic context of RUNX3 expression in monocytes hints at its relationship with cell growth, shape maintenance, and aspects of the immune response, including tyrosine kinases.

Epigenetic Mechanisms of Aging and Aging-Associated Diseases

Aging is an inevitable outcome of life, characterized by a progressive decline in tissue and organ function. At a molecular level, it is marked by the gradual alterations of biomolecules. Indeed, important changes are observed on the DNA, as well as at a protein level, that are influenced by both genetic and environmental parameters. These molecular changes directly contribute to the development or progression of several human pathologies, including cancer, diabetes, osteoporosis, neurodegenerative disorders and others aging-related diseases. Additionally, they increase the risk of mortality. Therefore, deciphering the hallmarks of aging represents a possibility for identifying potential druggable targets to attenuate the aging process, and then the age-related comorbidities. Given the link between aging, genetic, and epigenetic alterations, and given the reversible nature of epigenetic mechanisms, the precisely understanding of these factors may provide a potential therapeutic approach for age-related decline and disease. In this review, we center on epigenetic regulatory mechanisms and their aging-associated changes, highlighting their inferences in age-associated diseases.

Mitochondrial miRNA as epigenomic signatures: Visualizing aging-associated heart diseases through a new lens

Aging bears many hard knocks, but heart disorders earn a particular allusion, being the most widespread. Cardiovascular diseases (CVDs) are becoming the biggest concern to mankind due to sundry health conditions directly or indirectly related to heart-linked abnormalities. Scientists know that mitochondria play a critical role in the pathophysiology of cardiac diseases. Both environment and genetics play an essential role in modulating and controlling mitochondrial functions. Even a minor abnormality may prove detrimental to heart function. Advanced age combined with an unhealthy lifestyle can cause most cardiomyocytes to be replaced by fibrotic tissue which upsets the conducting system and leads to arrhythmias. An aging heart encounters far more heart-associated comorbidities than a young heart. Many state-of-the-art technologies and procedures are already being used to prevent and treat heart attacks worldwide. However, it remains a mystery when this heart bomb would explode because it lacks an alarm. This calls for a novel and effective strategy for timely diagnosis and a sure-fire treatment. This review article provides a comprehensive overture of prospective potentials of mitochondrial miRNAs that predict complicated and interconnected pathways concerning heart ailments and signature compilations of relevant miRNAs as biomarkers to plot the role of miRNAs in epigenomics. This article suggests that analysis of DNA methylation patterns in age-associated heart diseases may determine age-impelled biomarkers of heart disease.

Multiomics Network Medicine Approaches to Precision Medicine and Therapeutics in Cardiovascular Diseases

Cardiovascular diseases (CVD) are the leading cause of death worldwide and display complex phenotypic heterogeneity caused by many convergent processes, including interactions between genetic variation and environmental factors. Despite the identification of a large number of associated genes and genetic loci, the precise mechanisms by which these genes systematically influence the phenotypic heterogeneity of CVD are not well understood. In addition to DNA sequence, understanding the molecular mechanisms of CVD requires data from other omics levels, including the epigenome, the transcriptome, the proteome, as well as the metabolome. Recent advances in multiomics technologies have opened new precision medicine opportunities beyond genomics that can guide precise diagnosis and personalized treatment. At the same time, network medicine has emerged as an interdisciplinary field that integrates systems biology and network science to focus on the interactions among biological components in health and disease, providing an unbiased framework through which to integrate systematically these multiomics data. In this review, we briefly present such multiomics technologies, including bulk omics and single-cell omics technologies, and discuss how they can contribute to precision medicine. We then highlight network medicine-based integration of multiomics data for precision medicine and therapeutics in CVD. We also include a discussion of current challenges, potential limitations, and future directions in the study of CVD using multiomics network medicine approaches.

DNA methylation and cardiovascular disease in humans: a systematic review and database of known CpG methylation sites

BACKGROUND

Cardiovascular disease (CVD) is the leading cause of death worldwide and considered one of the most environmentally driven diseases. The role of DNA methylation in response to the individual exposure for the development and progression of CVD is still poorly understood and a synthesis of the evidence is lacking.

RESULTS

A systematic review of articles examining measurements of DNA cytosine methylation in CVD was conducted in accordance with PRISMA (preferred reporting items for systematic reviews and meta-analyses) guidelines. The search yielded 5,563 articles from PubMed and CENTRAL databases. From 99 studies with a total of 87,827 individuals eligible for analysis, a database was created combining all CpG-, gene- and study-related information. It contains 74,580 unique CpG sites, of which 1452 CpG sites were mentioned in ≥ 2, and 441 CpG sites in ≥ 3 publications. Two sites were referenced in ≥ 6 publications: cg01656216 (near ZNF438) related to vascular disease and epigenetic age, and cg03636183 (near F2RL3) related to coronary heart disease, myocardial infarction, smoking and air pollution. Of 19,127 mapped genes, 5,807 were reported in ≥ 2 studies. Most frequently reported were TEAD1 (TEA Domain Transcription Factor 1) and PTPRN2 (Protein Tyrosine Phosphatase Receptor Type N2) in association with outcomes ranging from vascular to cardiac disease. Gene set enrichment analysis of 4,532 overlapping genes revealed enrichment for Gene Ontology molecular function "DNA-binding transcription activator activity" (q = 1.65 × 10^-11) and biological processes "skeletal system development" (q = 1.89 × 10^-23). Gene enrichment demonstrated that general CVD-related terms are shared, while "heart" and "vasculature" specific genes have more disease-specific terms as PR interval for "heart" or platelet distribution width for "vasculature." STRING analysis revealed significant protein-protein interactions between the products of the differentially methylated genes (p = 0.003) suggesting that dysregulation of the protein interaction network could contribute to CVD. Overlaps with curated gene sets from the Molecular Signatures Database showed enrichment of genes in hemostasis (p = 2.9 × 10^-6) and atherosclerosis (p = 4.9 × 10^-4).

CONCLUSION

This review highlights the current state of knowledge on significant relationship between DNA methylation and CVD in humans. An open-access database has been compiled of reported CpG methylation sites, genes and pathways that may play an important role in this relationship.

DNA Methylation Is a Potential Biomarker for Cardiometabolic Health in Mexican Children and Adolescents

DNA methylation (DNAm) is a plausible mechanism underlying cardiometabolic abnormalities, but evidence is limited among youth. This analysis included 410 offspring of the Early Life Exposure in Mexico to Environmental Toxicants (ELEMENT) birth cohort followed up to two time points in late childhood/adolescence. At Time 1, DNAm was quantified in blood leukocytes at long interspersed nuclear elements (LINE-1), H19, and 11β-hydroxysteroid dehydrogenase type 2 (11β-HSD-2), and at Time 2 in peroxisome proliferator-activated receptor alpha (PPAR-α). At each time point, cardiometabolic risk factors were assessed including lipid profiles, glucose, blood pressure, and anthropometry. Linear mixed effects models were used for LINE-1, H19, and 11β-HSD-2 to account for the repeated-measure outcomes. Linear regression models were conducted for the cross-sectional association between PPAR-α with the outcomes. DNAm at LINE-1 was associated with log glucose at site 1 [β = -0.029, p = 0.0006] and with log high-density lipoprotein cholesterol at site 3 [β = 0.063, p = 0.0072]. 11β-HSD-2 DNAm at site 4 was associated with log glucose (β = -0.018, p = 0.0018). DNAm at LINE-1 and 11β-HSD-2 was associated with few cardiometabolic risk factors among youth in a locus-specific manner. These findings underscore the potential for epigenetic biomarkers to increase our understanding of cardiometabolic risk earlier in life.

Research on the pathological mechanism of rectal adenocarcinoma based on DNA methylation

Colorectal cancer is one of the 3 most common cancers worldwide. In this study, a weighted network-based analysis method was proposed to explore the pathological mechanisms and prognostic targets of rectal adenocarcinoma (READ) at the deoxyribonucleic acid (DNA) methylation level. In this study, we downloaded clinical information and DNA methylation data from The Cancer Genome Atlas database. Differentially methylated gene analysis was used to identify the differential methylated genes in READ. Canonical correlation analysis was used to construct the weighted gene regulatory network for READ. Multilevel analysis and association analyses between gene modules and clinical information were used to mine key modules related to tumor metastasis evaluation. Genetic significance analysis was used to identify methylation sites in key modules. Finally, the importance of these methylation sites was confirmed using survival analysis. DNA methylation datasets from 90 cancer tissue samples and 6 paracancerous tissue samples were selected. A weighted gene regulatory network was constructed, and a multilevel algorithm was used to divide the gene co-expression network into 20 modules. From gene ontology enrichment analysis, characteristic M was related to biological processes such as the chemotaxis of fibroblast growth factors and the activation and regulation of immune cells etc and characteristic N was associated with the regulation of cytoskeleton formation, mainly microtubules and flagella, regulation of synapses, and regulation of cell mitosis. Based on the results of survival analysis, 7 key methylation sites were found closely correlated to the survival rate of READ, such as cg04441191 (microtubule-associated protein 4 [MAP4]), cg05658717 (KSR2), cg09622330 (GRIN2A), cg10698404 (YWHAG), cg17047993 (SPAG9), cg24504843 (CEP135), and cg24531267 (CEP250). Mutational and transcriptomic level studies revealed significant differences in DNA methylation, single nucleotide polymorphism, and transcript levels between YWHAG and MAP4 in normal tissues compared to tumor tissues, and differential expression of the 2 proteins in immunohistochemistry. Therefore, potential targeting drugs were screened for these 2 proteins for molecular docking, and artenimol was found to bind to MAP4 protein and 27-hydroxycholesterol to YWHAG. Our study found that key methylation sites played an important role in tumor metastasis and were associated with the prognosis of READ. Mutations and methylation may jointly regulate the transcription and translation of related genes, which in turn affect cancer progression. This may provide some new potential therapeutic targets and thoughts for the prognosis of READ.

DNA methylation differences in monozygotic twins with Van der Woude syndrome

Introduction

Van der Woude Syndrome (VWS) is an autosomal dominant disorder responsible for 2% of all syndromic orofacial clefts (OFCs) with IRF6 being the primary causal gene (70%). Cases may present with lip pits and either cleft lip, cleft lip with cleft palate, or cleft palate, with marked phenotypic discordance even among individuals carrying the same mutation. This suggests that genetic or epigenetic modifiers may play additional roles in the syndrome's etiology and variability in expression. We report the first DNA methylation profiling of 2 pairs of monozygotic twins with VWS. Our goal is to explore epigenetic contributions to VWS etiology and variable phenotypic expressivity by comparing DNAm profiles in both twin pairs. While the mutations that cause VWS in these twins are known, the additional mechanism behind their phenotypic risk and variability in expression remains unclear.

Methods

We generated whole genome DNAm data for both twin pairs. Differentially methylated positions (DMPs) were selected based on: (1) a coefficient of variation in DNAm levels in unaffected individuals < 20%, and (2) intra-twin pair absolute difference in DNAm levels >5% (delta beta > | 0.05|). We then divided the DMPs in two subgroups for each twin pair for further analysis: (1) higher methylation levels in twin A (Twin A > Twin B); and (2) higher methylation levels in twin B (Twin B >Twin A).

Results and Discussion

Gene ontology analysis revealed a list of enriched genes that showed significant differential DNAm, including clef-associated genes. Among the cleft-associated genes, TP63 was the most significant hit (p=7.82E-12). Both twin pairs presented differential DNAm levels in CpG sites in/near TP63 (Twin 1A > Twin 1B and Twin 2A < Twin 2B). The genes TP63 and IRF6 function in a biological regulatory loop to coordinate epithelial proliferation and differentiation in a process that is critical for palatal fusion. The effects of the causal mutations in IRF6 can be further impacted by epigenetic dysregulation of IRF6 itself, or genes in its pathway. Our data shows evidence that changes in DNAm is a plausible mechanism that can lead to markedly distinct phenotypes, even among individuals carrying the same mutation.

Epigenetic regulation in myocardial infarction: Non-coding RNAs and exosomal non-coding RNAs

Myocardial infarction (MI) is one of the leading causes of deaths globally. The early diagnosis of MI lowers the rate of subsequent complications and maximizes the benefits of cardiovascular interventions. Many efforts have been made to explore new therapeutic targets for MI, and the therapeutic potential of non-coding RNAs (ncRNAs) is one good example. NcRNAs are a group of RNAs with many different subgroups, but they are not translated into proteins. MicroRNAs (miRNAs) are the most studied type of ncRNAs, and have been found to regulate several pathological processes in MI, including cardiomyocyte inflammation, apoptosis, angiogenesis, and fibrosis. These processes can also be modulated by circular RNAs and long ncRNAs via different mechanisms. However, the regulatory role of ncRNAs and their underlying mechanisms in MI are underexplored. Exosomes play a crucial role in communication between cells, and can affect both homeostasis and disease conditions. Exosomal ncRNAs have been shown to affect many biological functions. Tissue-specific changes in exosomal ncRNAs contribute to aging, tissue dysfunction, and human diseases. Here we provide a comprehensive review of recent findings on epigenetic changes in cardiovascular diseases as well as the role of ncRNAs and exosomal ncRNAs in MI, focusing on their function, diagnostic and prognostic significance.

Mendelian Randomization Analysis of the Association of SOCS3 Methylation with Abdominal Obesity

This study was conducted to evaluate the potential causality association of SOCS3 methylation with abdominal obesity using Mendelian randomization. A case-control study, including 1064 participants, was carried out on Chinese subjects aged 18 to 79. MethylTargetTM was used to detect the methylation level for each CpG site of SOCS3, and SNPscan^® was applied to measure the single-nucleotide polymorphism (SNP) genotyping. The logistic regression was used to assess the relationship of SOCS3 methylation level and SNP genotyping with abdominal obesity. Three types of Mendelian randomization methods were implemented to examine the potential causality between SOCS3 methylation and obesity based on the SNP of SOCS3 as instrumental variables. SOCS3 methylation levels were inversely associated with abdominal obesity in five CpG sites (effect estimates ranged from 0.786 (Chr17:76356054) to 0.851 (Chr17:76356084)), and demonstrated positively association in 18 CpG sites (effect estimates ranged from 1.243 (Chr17:76354990) to 1.325 (Chr17:76355061)). The causal relationship between SOCS3 methylation and abdominal obesity was found using the maximum-likelihood method and Mendelian randomization method of penalized inverse variance weighted (MR-IVW), and the β values (95% CI) were 5.342 (0.215, 10.469) and 4.911 (0.259, 9.564), respectively. The causality was found between the SOCS3 methylation level and abdominal obesity in the Chinese population.

Arsenic Exposure, Blood DNA Methylation, and Cardiovascular Disease

BACKGROUND

Epigenetic dysregulation has been proposed as a key mechanism for arsenic-related cardiovascular disease (CVD). We evaluated differentially methylated positions (DMPs) as potential mediators on the association between arsenic and CVD.

METHODS

Blood DNA methylation was measured in 2321 participants (mean age 56.2, 58.6% women) of the Strong Heart Study, a prospective cohort of American Indians. Urinary arsenic species were measured using high-performance liquid chromatography coupled to inductively coupled plasma mass spectrometry. We identified DMPs that are potential mediators between arsenic and CVD. In a cross-species analysis, we compared those DMPs with differential liver DNA methylation following early-life arsenic exposure in the apoE knockout (apoE^-/-) mouse model of atherosclerosis.

RESULTS

A total of 20 and 13 DMPs were potential mediators for CVD incidence and mortality, respectively, several of them annotated to genes related to diabetes. Eleven of these DMPs were similarly associated with incident CVD in 3 diverse prospective cohorts (Framingham Heart Study, Women's Health Initiative, and Multi-Ethnic Study of Atherosclerosis). In the mouse model, differentially methylated regions in 20 of those genes and DMPs in 10 genes were associated with arsenic.

CONCLUSIONS

Differential DNA methylation might be part of the biological link between arsenic and CVD. The gene functions suggest that diabetes might represent a relevant mechanism for arsenic-related cardiovascular risk in populations with a high burden of diabetes.

Studying Epigenetics of Cardiovascular Diseases on Chip Guide

Epigenetics is defined as the study of inheritable changes in the gene expressions and phenotypes that occurs without altering the normal DNA sequence. These changes are mainly due to an alteration in chromatin or its packaging, which changes the DNA accessibility. DNA methylation, histone modification, and noncoding or microRNAs can best explain the mechanism of epigenetics. There are various DNA methylated enzymes, histone-modifying enzymes, and microRNAs involved in the cause of various CVDs (cardiovascular diseases) such as cardiac hypertrophy, heart failure, and hypertension. Moreover, various CVD risk factors such as diabetes mellitus, hypoxia, aging, dyslipidemia, and their epigenetics are also discussed together with CVDs such as CHD (coronary heart disease) and PAH (pulmonary arterial hypertension). Furthermore, different techniques involved in epigenetic chromatin mapping are explained. Among these techniques, the ChIP-on-chip guide is explained with regard to its role in cardiac hypertrophy, a final form of heart failure. This review focuses on different epigenetic factors that are involved in causing cardiovascular diseases.

Epigenetic regulation in cardiovascular disease: mechanisms and advances in clinical trials

Epigenetics is closely related to cardiovascular diseases. Genome-wide linkage and association analyses and candidate gene approaches illustrate the multigenic complexity of cardiovascular disease. Several epigenetic mechanisms, such as DNA methylation, histone modification, and noncoding RNA, which are of importance for cardiovascular disease development and regression. Targeting epigenetic key enzymes, especially the DNA methyltransferases, histone methyltransferases, histone acetylases, histone deacetylases and their regulated target genes, could represent an attractive new route for the diagnosis and treatment of cardiovascular diseases. Herein, we summarize the knowledge on epigenetic history and essential regulatory mechanisms in cardiovascular diseases. Furthermore, we discuss the preclinical studies and drugs that are targeted these epigenetic key enzymes for cardiovascular diseases therapy. Finally, we conclude the clinical trials that are going to target some of these processes.

DNA methylation-based predictors of health: applications and statistical considerations

DNA methylation data have become a valuable source of information for biomarker development, because, unlike static genetic risk estimates, DNA methylation varies dynamically in relation to diverse exogenous and endogenous factors, including environmental risk factors and complex disease pathology. Reliable methods for genome-wide measurement at scale have led to the proliferation of epigenome-wide association studies and subsequently to the development of DNA methylation-based predictors across a wide range of health-related applications, from the identification of risk factors or exposures, such as age and smoking, to early detection of disease or progression in cancer, cardiovascular and neurological disease. This Review evaluates the progress of existing DNA methylation-based predictors, including the contribution of machine learning techniques, and assesses the uptake of key statistical best practices needed to ensure their reliable performance, such as data-driven feature selection, elimination of data leakage in performance estimates and use of generalizable, adequately powered training samples.

DNA Methylation Mediates the Association Between Individual and Neighborhood Social Disadvantage and Cardiovascular Risk Factors

Low socioeconomic status (SES) and living in a disadvantaged neighborhood are associated with poor cardiovascular health. Multiple lines of evidence have linked DNA methylation to both cardiovascular risk factors and social disadvantage indicators. However, limited research has investigated the role of DNA methylation in mediating the associations of individual- and neighborhood-level disadvantage with multiple cardiovascular risk factors in large, multi-ethnic, population-based cohorts. We examined whether disadvantage at the individual level (childhood and adult SES) and neighborhood level (summary neighborhood SES as assessed by Census data and social environment as assessed by perceptions of aesthetic quality, safety, and social cohesion) were associated with 11 cardiovascular risk factors including measures of obesity, diabetes, lipids, and hypertension in 1,154 participants from the Multi-Ethnic Study of Atherosclerosis (MESA). For significant associations, we conducted epigenome-wide mediation analysis to identify methylation sites mediating the relationship between individual/neighborhood disadvantage and cardiovascular risk factors using the JT-Comp method that assesses sparse mediation effects under a composite null hypothesis. In models adjusting for age, sex, race/ethnicity, smoking, medication use, and genetic principal components of ancestry, epigenetic mediation was detected for the associations of adult SES with body mass index (BMI), insulin, and high-density lipoprotein cholesterol (HDL-C), as well as for the association between neighborhood socioeconomic disadvantage and HDL-C at FDR q < 0.05. The 410 CpG mediators identified for the SES-BMI association were enriched for CpGs associated with gene expression (expression quantitative trait methylation loci, or eQTMs), and corresponding genes were enriched in antigen processing and presentation pathways. For cardiovascular risk factors other than BMI, most of the epigenetic mediators lost significance after controlling for BMI. However, 43 methylation sites showed evidence of mediating the neighborhood socioeconomic disadvantage and HDL-C association after BMI adjustment. The identified mediators were enriched for eQTMs, and corresponding genes were enriched in inflammatory and apoptotic pathways. Our findings support the hypothesis that DNA methylation acts as a mediator between individual- and neighborhood-level disadvantage and cardiovascular risk factors, and shed light on the potential underlying epigenetic pathways. Future studies are needed to fully elucidate the biological mechanisms that link social disadvantage to poor cardiovascular health.

Epigenetics in Precision Nutrition

Precision nutrition is an emerging area of nutrition research, with primary focus on the individual variability in response to dietary and lifestyle factors, which are mainly determined by an individual’s intrinsic variations, such as those in genome, epigenome, and gut microbiome. The current research on precision nutrition is heavily focused on genome and gut microbiome, while epigenome (DNA methylation, non-coding RNAs, and histone modification) is largely neglected. The epigenome acts as the interface between the human genome and environmental stressors, including diets and lifestyle. Increasing evidence has suggested that epigenetic modifications, particularly DNA methylation, may determine the individual variability in metabolic health and response to dietary and lifestyle factors and, therefore, hold great promise in discovering novel markers for precision nutrition and potential targets for precision interventions. This review summarized recent studies on DNA methylation with obesity, diabetes, and cardiovascular disease, with more emphasis put in the relations of DNA methylation with nutrition and diet/lifestyle interventions. We also briefly reviewed other epigenetic events, such as non-coding RNAs, in relation to human health and nutrition, and discussed the potential role of epigenetics in the precision nutrition research.

A deep learning model for early risk prediction of heart failure with preserved ejection fraction by DNA methylation profiles combined with clinical features

Background

Heart failure with preserved ejection fraction (HFpEF), affected collectively by genetic and environmental factors, is the common subtype of chronic heart failure. Although the available risk assessment methods for HFpEF have achieved some progress, they were based on clinical or genetic features alone. Here, we have developed a deep learning framework, HFmeRisk, using both 5 clinical features and 25 DNA methylation loci to predict the early risk of HFpEF in the Framingham Heart Study Cohort.

Results

The framework incorporates Least Absolute Shrinkage and Selection Operator and Extreme Gradient Boosting-based feature selection, as well as a Factorization-Machine based neural network-based recommender system. Model discrimination and calibration were assessed using the AUC and Hosmer–Lemeshow test. HFmeRisk, including 25 CpGs and 5 clinical features, have achieved the AUC of 0.90 (95% confidence interval 0.88–0.92) and Hosmer–Lemeshow statistic was 6.17 (P = 0.632), which outperformed models with clinical characteristics or DNA methylation levels alone, published chronic heart failure risk prediction models and other benchmark machine learning models. Out of them, the DNA methylation levels of two CpGs were significantly correlated with the paired transcriptome levels (R < −0.3, P < 0.05). Besides, DNA methylation locus in HFmeRisk were associated with intercellular signaling and interaction, amino acid metabolism, transport and activation and the clinical variables were all related with the mechanism of occurrence of HFpEF. Together, these findings give new evidence into the HFmeRisk model.

Conclusion

Our study proposes an early risk assessment framework for HFpEF integrating both clinical and epigenetic features, providing a promising path for clinical decision making.

Epigenetic dysregulation in cardiovascular aging and disease

Cardiovascular disease (CVD) is the leading cause of mortality and morbidity for all sexes, racial and ethnic groups. Age, and its associated physiological and pathological consequences, exacerbate CVD incidence and progression, while modulation of biological age with interventions track with cardiovascular health. Despite the strong link between aging and CVD, surprisingly few studies have directly investigated heart failure and vascular dysfunction in aged models and subjects. Nevertheless, strong correlations have been found between heart disease, atherosclerosis, hypertension, fibrosis, and regeneration efficiency with senescent cell burden and its proinflammatory sequelae. In agreement, senotherapeutics have had success in reducing the detrimental effects in experimental models of cardiovascular aging and disease. Aside from senotherapeutics, cellular reprogramming strategies targeting epigenetic enzymes remain an unexplored yet viable option for reversing or delaying CVD. Epigenetic alterations comprising local and global changes in DNA and histone modifications, transcription factor binding, disorganization of the nuclear lamina, and misfolding of the genome are hallmarks of aging. Limited studies in the aging cardiovascular system of murine models or human patient samples have identified strong correlations between the epigenome, age, and senescence. Here, we compile the findings in published studies linking epigenetic changes to CVD and identify clear themes of epigenetic deregulation during aging. Pending direct investigation of these general mechanisms in aged tissues, this review predicts that future work will establish epigenetic rejuvenation as a potent method to delay CVD.

DNA methylation signatures of incident coronary heart disease: findings from epigenome-wide association studies

Coronary heart disease (CHD) is a type of cardiovascular disease (CVD) that affects the coronary arteries, which provide oxygenated blood to the heart. It is a major cause of mortality worldwide. Various prediction methods have been developed to assess the likelihood of developing CHD, including those based on clinical features and genetic variation. Recent epigenome-wide studies have identified DNA methylation signatures associated with the development of CHD, indicating that DNA methylation may play a role in predicting future CHD. This narrative review summarises recent findings from DNA methylation studies of incident CHD (iCHD) events from epigenome-wide association studies (EWASs). The results suggest that DNA methylation signatures may identify new mechanisms involved in CHD progression and could prove a useful adjunct for the prediction of future CHD.

Cis-Acting Factors Causing Secondary Epimutations: Impact on the Risk for Cancer and Other Diseases

Epigenetics affects gene expression and contributes to disease development by alterations known as epimutations. Hypermethylation that results in transcriptional silencing of tumor suppressor genes has been described in patients with hereditary cancers and without pathogenic variants in the coding region of cancer susceptibility genes. Although somatic promoter hypermethylation of these genes can occur in later stages of the carcinogenic process, constitutional methylation can be a crucial event during the first steps of tumorigenesis, accelerating tumor development. Primary epimutations originate independently of changes in the DNA sequence, while secondary epimutations are a consequence of a mutation in a cis or trans-acting factor. Secondary epimutations have a genetic basis in cis of the promoter regions of genes involved in familial cancers. This highlights epimutations as a novel carcinogenic mechanism whose contribution to human diseases is underestimated by the scarcity of the variants described. In this review, we provide an overview of secondary epimutations and present evidence of their impact on cancer. We propose the necessity for genetic screening of loci associated with secondary epimutations in familial cancer as part of prevention programs to improve molecular diagnosis, secondary prevention, and reduce the mortality of these diseases.

The association of epigenetic clocks in brain tissue with brain pathologies and common aging phenotypes

Epigenetic clocks are calculated by combining DNA methylation states across select CpG sites to estimate biologic age, and have been noted as the most successful markers of biologic aging to date. Yet, limited research has considered epigenetic clocks calculated in brain tissue. We used DNA methylation states in dorsolateral prefrontal cortex specimens from 721 older participants of the Religious Orders Study and Rush Memory and Aging Project, to calculate DNA methylation age using four established epigenetic clocks: Hannum, Horvath, PhenoAge, GrimAge, and a new Cortical clock. The four established clocks were trained in blood samples (Hannum, PhenoAge, GrimAge) or using 51 human tissue and cell types (Horvath); the recent Cortical clock is the first trained in postmortem cortical tissue. Participants were recruited beginning in 1994 (Religious Orders Study) and 1997 (Memory and Aging Project), and followed annually with questionnaires and clinical evaluations; brain specimens were obtained for 80-90% of participants. Mean age at death was 88.0 (SD 6.7) years. We used linear regression, logistic regression, and linear mixed models, to examine relations of epigenetic clock ages to neuropathologic and clinical aging phenotypes, controlling for chronologic age, sex, education, and depressive symptomatology. Hannum, Horvath, PhenoAge and Cortical clock ages were related to pathologic diagnosis of Alzheimer's disease (AD), as well as to Aβ load (a hallmark pathology of Alzheimer's disease). However, associations were substantially stronger for the Cortical than other clocks; for example, each standard deviation (SD) increase in Hannum, Horvath, and PhenoAge clock age was related to approximately 30% greater likelihood of pathologic AD (all p < 0.05), while each SD increase in Cortical age was related to 90% greater likelihood of pathologic AD (odds ratio = 1.91, 95% confidence interval 1.38, 2.62). Moreover, Cortical age was significantly related to other AD pathology (eg, mean tau tangle density, p = 0.003), and to odds of neocortical Lewy body pathology (for each SD increase in Cortical age, odds ratio = 2.00, 95% confidence 1.27, 3.17), although no clocks were related to cerebrovascular neuropathology. Cortical age was the only epigenetic clock significantly associated with the clinical phenotypes examined, from dementia to cognitive decline (5 specific cognitive systems, and a global cognitive measure averaging 17 tasks) to Parkinsonian signs. Overall, our findings provide evidence of the critical necessity for bespoke clocks of brain aging for advancing research to understand, and eventually prevent, neurodegenerative diseases of aging.

Prognostic targets recognition of rectal adenocarcinoma based on transcriptomics

Colorectal cancer is currently the third most common cancer around the world. In this study, we chose a bioinformatics analysis method based on network analysis to dig out the pathological mechanism and key prognostic targets of rectal adenocarcinoma (READ).In this study, we downloaded the clinical information data and transcriptome data from the Cancer Genome Atlas database. Differentially expressed genes analysis was used to identify the differential expressed genes in READ. Community discovery algorithm analysis and Correlation analysis between gene modules and clinical data were performed to mine the key modules related to tumor proliferation, metastasis, and invasion. Genetic significance (GS) analysis and PageRank algorithm analysis were applied for find key genes in the key module. Finally, the importance of these genes was confirmed by survival analysis.Transcriptome datasets of 165 cancer tissue samples and 9 paracancerous tissue samples were selected. Gene coexpression networks were constructed, multilevel algorithm was used to divide the gene coexpression network into 11 modules. From GO enrichment analysis, module 11 significantly associated with clinical characteristic N, T, and event, mainly involved in 2 types of biological processes which were highly related to tumor metastasis, invasion, and tumor microenvironment regulation: cell development and differentiation; the development of vascular and nervous systems. Based on the results of survival analysis, 7 key genes were found negatively correlated to the survival rate of READ, such as MMP14, SDC2, LAMC1, ELN, ACTA2, ZNF532, and CYBRD1.Our study found that these key genes were predicted playing an important role in tumor invasion and metastasis, and being associated with the prognosis of READ. This may provide some new potential therapeutic targets and thoughts for the prognosis of READ.

The epigenetic etiology of cardiovascular disease in a longitudinal Swedish twin study

BACKGROUND

Studies on DNA methylation have the potential to discover mechanisms of cardiovascular disease (CVD) risk. However, the role of DNA methylation in CVD etiology remains unclear.

RESULTS

We performed an epigenome-wide association study (EWAS) on CVD in a longitudinal sample of Swedish twins (535 individuals). We selected CpGs reaching the Bonferroni-corrected significance level (2 [Formula: see text] 10-7) or the top-ranked 20 CpGs with the lowest P values if they did not reach this significance level in EWAS analysis associated with non-stroke CVD, overall stroke, and ischemic stroke, respectively. We further applied a bivariate autoregressive latent trajectory model with structured residuals (ALT-SR) to evaluate the cross-lagged effect between DNA methylation of these CpGs and cardiometabolic traits (blood lipids, blood pressure, and body mass index). Furthermore, mediation analysis was performed to evaluate whether the cross-lagged effects had causal impacts on CVD. In the EWAS models, none of the CpGs we selected reached the Bonferroni-corrected significance level. The ALT-SR model showed that DNA methylation levels were more likely to predict the subsequent level of cardiometabolic traits rather than the other way around (numbers of significant cross-lagged paths of methylation → trait/trait → methylation were 84/4, 45/6, 66/1 for the identified three CpG sets, respectively). Finally, we demonstrated significant indirect effects from DNA methylation on CVD mediated by cardiometabolic traits.

CONCLUSIONS

We present evidence for a directional association from DNA methylation on cardiometabolic traits and CVD, rather than the opposite, highlighting the role of epigenetics in CVD development.

Cardiovascular disease risk and pathophysiology in South Asians: can longitudinal multi-omics shed light?

Cardiovascular disease (CVD) is the leading cause of mortality in South Asia, with rapidly increasing prevalence of hypertension, type 2 diabetes (T2DM) and hyperlipidemia over the last two decades. Atherosclerotic CVD (ASCVD) affects South Asians earlier in life and at lower body weights, which is not fully explained by differential burden of conventional risk factors. Heart failure (HF) is a complex clinical syndrome of heterogeneous structural phenotypes including two major clinical subtypes, HF with preserved (HFpEF) and reduced ejection fraction (HFrEF). The prevalence of HF in South Asians is also rising with other metabolic diseases, and HFpEF develops at younger age and leaner body mass index in South Asians than in Whites. Recent genome-wide association studies, epigenome-wide association studies and metabolomic studies of ASCVD and HF have identified genes, metabolites and pathways associated with CVD traits. However, these findings were mostly driven by samples of European ancestry, which may not accurately represent the CVD risk at the molecular level, and the unique risk profile of CVD in South Asians. Such bias, while formulating hypothesis-driven research studies, risks missing important causal or predictive factors unique to South Asians. Importantly, a longitudinal design of multi-omic markers can capture the life-course risk and natural history related to CVD, and partially disentangle putative causal relationship between risk factors, multi-omic markers and subclinical and clinical ASCVD and HF. In conclusion, combining high-resolution untargeted metabolomics with epigenomics of rigorous, longitudinal design will provide comprehensive unbiased molecular characterization of subclinical and clinical CVD among South Asians. A thorough understanding of CVD-associated metabolomic profiles, together with advances in epigenomics and genomics, will lead to more accurate estimates of CVD progression and stimulate new strategies for improving cardiovascular health.

DNA Methylation, Preterm Birth and Blood Pressure in African American Children: The DPREG Study

Preterm birth (< 37 weeks) has been associated with high blood pressure (BP) and cardiovascular disease in adulthood. Epigenetic mechanisms may explain how preterm birth influences later BP. In this study, we examined the association between DNA methylation (DNAm), preterm birth and BP in African American children. We recruited 100 children and collected clinical and birth history data. DNA was extracted from saliva and the Illumina EPIC BeadChip was used for epigenetic analyses. Preterm birth was not associated with systolic or diastolic BP. No significant DNAm sites were associated with preterm birth in candidate gene methylation analyses. Body mass index was associated with systolic BP (p = 0.01). We did not observe an effect of preterm birth on DNAm or BP in early childhood. Our study is one of the few, however, to examine these associations among African Americans.

DNA methylation biomarkers of myocardial infarction and cardiovascular disease

BACKGROUND

The epigenetic landscape underlying cardiovascular disease (CVD) is not completely understood and the clinical value of the identified biomarkers is still limited. We aimed to identify differentially methylated loci associated with acute myocardial infarction (AMI) and assess their validity as predictive and causal biomarkers.

RESULTS

We designed a case-control, two-stage, epigenome-wide association study on AMI (n_discovery = 391, n_validation = 204). DNA methylation was assessed using the Infinium MethylationEPIC BeadChip. We performed a fixed-effects meta-analysis of the two samples. 34 CpGs were associated with AMI. Only 12 of them were available in two independent cohort studies (n ~ 1800 and n ~ 2500) with incident coronary and cardiovascular disease (CHD and CVD, respectively). The Infinium HumanMethylation450 BeadChip was used in those two studies. Four of the 12 CpGs were validated in association with incident CHD: AHRR-mapping cg05575921, PTCD2-mapping cg25769469, intergenic cg21566642 and MPO-mapping cg04988978. We then assessed whether methylation risk scores based on those CpGs improved the predictive capacity of the Framingham risk function, but they did not. Finally, we aimed to study the causality of those associations using a Mendelian randomization approach but only one of the CpGs had a genetic influence and therefore the results were not conclusive.

CONCLUSIONS

We have identified 34 CpGs related to AMI. These loci highlight the relevance of smoking, lipid metabolism, and inflammation in the biological mechanisms related to AMI. Four were additionally associated with incident CHD and CVD but did not provide additional predictive information.

Clinical epigenetics settings for cancer and cardiovascular diseases: real-life applications of network medicine at the bedside

Despite impressive efforts invested in epigenetic research in the last 50 years, clinical applications are still lacking. Only a few university hospital centers currently use epigenetic biomarkers at the bedside. Moreover, the overall concept of precision medicine is not widely recognized in routine medical practice and the reductionist approach remains predominant in treating patients affected by major diseases such as cancer and cardiovascular diseases. By its' very nature, epigenetics is integrative of genetic networks. The study of epigenetic biomarkers has led to the identification of numerous drugs with an increasingly significant role in clinical therapy especially of cancer patients. Here, we provide an overview of clinical epigenetics within the context of network analysis. We illustrate achievements to date and discuss how we can move from traditional medicine into the era of network medicine (NM), where pathway-informed molecular diagnostics will allow treatment selection following the paradigm of precision medicine.

Association of cardiovascular health and epigenetic age acceleration

Background

Cardiovascular health (CVH) has been defined by the American Heart Association (AHA) as the presence of the “Life’s Simple 7” ideal lifestyle and clinical factors. CVH is known to predict longevity and freedom from cardiovascular disease, the leading cause of death for women in the United States. DNA methylation markers of aging have been aggregated into a composite epigenetic age score, which is associated with cardiovascular morbidity and mortality. However, it is unknown whether poor CVH is associated with acceleration of aging as measured by DNA methylation markers in epigenetic age.

Methods and results

We performed a cross-sectional analysis of racially/ethnically diverse post-menopausal women enrolled in the Women’s Health Initiative cohort recruited between 1993 and 1998. Epigenetic age acceleration (EAA) was calculated using DNA methylation data on a subset of participants and the published Horvath and Hannum methods for intrinsic and extrinsic EAA. CVH was calculated using the AHA measures of CVH contributing to a 7-point score. We examined the association between CVH score and EAA using linear regression modeling adjusting for self-reported race/ethnicity and education. Among the 2,170 participants analyzed, 50% were white and mean age was 64 (7 SD) years. Higher or more favorable CVH scores were associated with lower extrinsic EAA (~ 6 months younger age per 1 point higher CVH score, p < 0.0001), and lower intrinsic EAA (3 months younger age per 1 point higher CVH score, p < 0.028).

Conclusions

These cross-sectional observations suggest a possible mechanism by which ideal CVH is associated with greater longevity.

Cardiovascular disease risk and pathophysiology in South Asians: can longitudinal multi-omics shed light?

Cardiovascular disease (CVD) is the leading cause of mortality in South Asia, with rapidly increasing prevalence of hypertension, type 2 diabetes and hyperlipidemia over the last two decades. Atherosclerotic CVD (ASCVD) affects South Asians earlier in life and at lower body weights, which is not fully explained by differential burden of conventional risk factors. Heart failure (HF) is a complex clinical syndrome of heterogeneous structural phenotypes including two major clinical subtypes, HF with preserved (HFpEF) and reduced ejection fraction (HFrEF). The prevalence of HF in South Asians is also rising with other metabolic diseases, and HFpEF develops at younger age and leaner body mass index in South Asians than in Whites. Recent genome-wide association studies, epigenome-wide association studies and metabolomic studies of ASCVD and HF have identified genes, metabolites and pathways associated with CVD traits. However, these findings were mostly driven by samples of European ancestry, which may not accurately represent the CVD risk at the molecular level, and the unique risk profile of CVD in South Asians. Such bias, while formulating hypothesis-driven research studies, risks missing important causal or predictive factors unique to South Asians. Importantly, a longitudinal design of multi-omic markers can capture the life-course risk and natural history related to CVD, and partially disentangle putative causal relationship between risk factors, multi-omic markers and subclinical and clinical ASCVD and HF. In conclusion, combining high-resolution untargeted metabolomics with epigenomics of rigorous, longitudinal design will provide comprehensive unbiased molecular characterization of subclinical and clinical CVD among South Asians. A thorough understanding of CVD-associated metabolomic profiles, together with advances in epigenomics and genomics, will lead to more accurate estimates of CVD progression and stimulate new strategies for improving cardiovascular health.

Use of an Exposome Approach to Understand the Effects of Exposures From the Natural, Built, and Social Environments on Cardio-Vascular Disease Onset, Progression, and Outcomes

Obesity, diabetes, and hypertension have increased by epidemic proportions in recent years among African Americans in comparison to Whites resulting in significant adverse cardiovascular disease (CVD) disparities. Today, African Americans are 30% more likely to die of heart disease than Whites and twice as likely to have a stroke. The causes of these disparities are not yet well-understood. Improved methods for identifying underlying risk factors is a critical first step toward reducing Black:White CVD disparities. This article will focus on environmental exposures in the external environment and how they can lead to changes at the cellular, molecular, and organ level to increase the personal risk for CVD and lead to population level CVD racial disparities. The external environment is defined in three broad domains: natural (air, water, land), built (places you live, work, and play) and social (social, demographic, economic, and political). We will describe how environmental exposures in the natural, built, and social environments "get under the skin" to affect gene expression though epigenetic, pan-omics, and related mechanisms that lead to increased risk for adverse CVD health outcomes and population level disparities. We also will examine the important role of metabolomics, proteomics, transcriptomics, genomics, and epigenomics in understanding how exposures in the natural, built, and social environments lead to CVD disparities with implications for clinical, public health, and policy interventions. In this review, we apply an exposome approach to Black:White CVD racial disparities. The exposome is a measure of all the exposures of an individual across the life course and the relationship of those exposures to health effects. The exposome represents the totality of exogenous (external) and endogenous (internal) exposures from conception onwards, simultaneously distinguishing, characterizing, and quantifying etiologic, mediating, moderating, and co-occurring risk and protective factors and their relationship to disease. Specifically, it assesses the biological mechanisms and underlying pathways through which chemical and non-chemical environmental exposures are associated with CVD onset, progression and outcomes. The exposome is a promising approach for understanding the complex relationships among environment, behavior, biology, genetics, and disease phenotypes that underlie population level, Black: White CVD disparities.

DNA methylation and incident cardiovascular disease

PURPOSE OF REVIEW

DNA methylation is an epigenetic mark that reflects both genetic and environmental influences over the life course and has the potential to be a robust biomarker for cardiovascular disease (CVD) risk. However, standard association studies linking DNA methylation and CVD are susceptible to reverse causation and may not directly translate into useful biomarkers of future disease. Studies of incident CVD represent a crucial tool for improving this evidence base.

RECENT FINDINGS

Recent investigations have started to provide links between DNA methylation and incident CVD. Epigenome-wide association studies have suggested individual genetic loci in which differential methylation exists prior to disease onset, while multivariate predictive modeling approaches have made progress towards realizing the potential for DNA methylation as a predictive biomarker of CVD risk. Meanwhile, complementary analysis strategies such as Mendelian randomization have provided clues as to the causality of these epigenomic associations.

SUMMARY

Taken together, this wave of studies provides the basis for a better understanding of CVD pathophysiology and the development of more confident biomarkers of CVD risk.

Epigenomic Assessment of Cardiovascular Disease Risk and Interactions With Traditional Risk Metrics

Background Epigenome-wide association studies for cardiometabolic risk factors have discovered multiple loci associated with incident cardiovascular disease (CVD). However, few studies have sought to directly optimize a predictor of CVD risk. Furthermore, it is challenging to train multivariate models across multiple studies in the presence of study- or batch effects. Methods and Results Here, we analyzed existing DNA methylation data collected using the Illumina HumanMethylation450 microarray to create a predictor of CVD risk across 3 cohorts: Women's Health Initiative, Framingham Heart Study Offspring Cohort, and Lothian Birth Cohorts. We trained Cox proportional hazards-based elastic net regressions for incident CVD separately in each cohort and used a recently introduced cross-study learning approach to integrate these individual scores into an ensemble predictor. The methylation-based risk score was associated with CVD time-to-event in a held-out fraction of the Framingham data set (hazard ratio per SD=1.28, 95% CI, 1.10-1.50) and predicted myocardial infarction status in the independent REGICOR (Girona Heart Registry) data set (odds ratio per SD=2.14, 95% CI, 1.58-2.89). These associations remained after adjustment for traditional cardiovascular risk factors and were similar to those from elastic net models trained on a directly merged data set. Additionally, we investigated interactions between the methylation-based risk score and both genetic and biochemical CVD risk, showing preliminary evidence of an enhanced performance in those with less traditional risk factor elevation. Conclusions This investigation provides proof-of-concept for a genome-wide, CVD-specific epigenomic risk score and suggests that DNA methylation data may enable the discovery of high-risk individuals who would be missed by alternative risk metrics.

DNA Methylation Biomarkers in Aging and Age-Related Diseases

Recent research efforts provided compelling evidence of genome-wide DNA methylation alterations in aging and age-related disease. It is currently well established that DNA methylation biomarkers can determine biological age of any tissue across the entire human lifespan, even during development. There is growing evidence suggesting epigenetic age acceleration to be strongly linked to common diseases or occurring in response to various environmental factors. DNA methylation based clocks are proposed as biomarkers of early disease risk as well as predictors of life expectancy and mortality. In this review, we will summarize key advances in epigenetic clocks and their potential application in precision health. We will also provide an overview of progresses in epigenetic biomarker discovery in Alzheimer's, type 2 diabetes, and cardiovascular disease. Furthermore, we will highlight the importance of prospective study designs to identify and confirm epigenetic biomarkers of disease.