Association of Methylation Signals With Incident Coronary Heart Disease in an Epigenome-Wide Assessment of Circulating Tumor Necrosis Factor α

A novel framework to build saliva-based DNA methylation biomarkers: Quantifying systemic chronic inflammation as a case study

Accessible and non-invasive biomarkers that measure human ageing processes and the risk of developing age-related disease are paramount in preventative healthcare. Here, we describe a novel framework to train saliva-based DNA methylation (DNAm) biomarkers that are reproducible and biologically interpretable. By leveraging a reliability dataset with replicates across tissues, we demonstrate that it is possible to transfer knowledge from blood DNAm to saliva DNAm data using DNAm proxies of blood proteins (EpiScores). We apply these methods to create a new saliva-based epigenetic clock (InflammAge) that quantifies systemic chronic inflammation (SCI) in humans. Using a large blood DNAm human cohort with linked electronic health records and over 18,000 individuals (Generation Scotland), we demonstrate that InflammAge significantly associates with all-cause mortality, disease outcomes, lifestyle factors, and immunosenescence; in many cases outperforming the widely used SCI biomarker C-reactive protein (CRP). We propose that our biomarker discovery framework and InflammAge will be useful to improve understanding of the molecular mechanisms underpinning human ageing and to assess the impact of gero-protective interventions.

DNA methylation-based telomere length is more strongly associated with cardiovascular disease and long-term mortality than quantitative polymerase chain reaction-based telomere length: evidence from the NHANES 1999-2002

BACKGROUND

Telomere length (TL) serves as a pivotal gauge of cellular aging, with shorter TL linked to various age-related ailments. Recently, a DNA methylation-based TL estimator, known as DNAmTL, has emerged as a novel TL measurement tool. Our current investigation scrutinized the correlation between DNAmTL and the risks of cardiovascular disease (CVD) and enduring mortality among middle-aged and elderly individuals.

METHODS

We enrolled a nationwide, population-based cohort of subjects from the National Health and Nutrition Examination Survey spanning 1999 to 2002, possessing data on both DNAmTL and quantitative polymerase chain reaction-based TL (qPCRTL). Logistic regression models and Cox proportional hazards models were employed to evaluate the associations of DNAmTL with CVD risk and mortality, respectively.

RESULTS

The cohort comprised 2532 participants, with a weighted CVD prevalence of 19.06%. Notably, each one-kilobase increase in DNAmTL was linked to a 53% diminished CVD risk [odds ratio (OR): 0.47, 95% confidence interval (CI): 0.23-0.95, P = 0.035]. Over a median follow-up period of 206 months, 1361 deaths were recorded (53.75%), with 590 (23.30%) ascribable to CVD. Individuals with the lengthiest DNAmTL exhibited a 36% lower risk of all-cause mortality (hazard ratio (HR): 0.64, 95% CI: 0.49-0.85, P = 0.002) and a 35% decrease in CVD mortality (HR: 0.65, 95% CI: 0.43-0.98, P = 0.044) compared to those with shortest DNAmTL. Notably, a stronger association with age was observed for DNAmTL compared to qPCRTL (r = -0.58 vs. r = - 0.25). Analysis of receiver operating characteristic (ROC) curves suggested superior predictive performance of DNAmTL over qPCRTL for CVD (area under curve (AUC): 0.63 vs. 0.55, P < 0.001), all-cause (AUC: 0.74 vs. 0.62, P < 0.001), and CVD mortality (AUC: 0.75 vs. 0.64, P < 0.001).

CONCLUSION

Longer DNAmTL was positively correlated with reduced CVD risk and long-term mortality in middle-aged and elderly cohorts. Notably, DNAmTL outperformed qPCRTL as an aging biomarker in the stratification of CVD risks and mortality.

The Application of Mendelian Randomization in Cardiovascular Disease Risk Prediction: Current Status and Future Prospects

Cardiovascular disease (CVD), a leading cause of death and disability worldwide, and is associated with a wide range of risk factors, and genetically associated conditions. While many CVDs are preventable and early detection alongside treatment can significantly mitigate complication risks, current prediction models for CVDs need enhancements for better accuracy. Mendelian randomization (MR) offers a novel approach for estimating the causal relationship between exposure and outcome by using genetic variation in quasi-experimental data. This method minimizes the impact of confounding variables by leveraging the random allocation of genes during gamete formation, thereby facilitating the integration of new predictors into risk prediction models to refine the accuracy of prediction. In this review, we delve into the theory behind MR, as well as the strengths, applications, and limitations behind this emerging technology. A particular focus will be placed on MR application to CVD, and integration into CVD prediction frameworks. We conclude by discussing the inclusion of various populations and by offering insights into potential areas for future research and refinement.

Identification of an association between coronary heart disease and ITGB2 methylation in peripheral blood by a case-control study

BACKGROUND

Blood DNA methylation was associated with coronary heart disease (CHD) risk in Caucasians. We investigated the association between DNA methylation in peripheral blood at the reported loci and CHD in the Chinese population.

METHODS

The integrin subunit beta 2 (ITGB2) gene was identified in 196 CHD cases and 184 controls, and its methylation level was determined by mass spectrometry. Logistic regression was used to assess the association.

RESULTS

Hypomethylation of ITGB2 was significantly associated with heart failure CHD and NYHA Ⅰ&Ⅱ CHD patients with minor to medium cardiac function impairment (ITGB2_CpG_11/cg08422803, OR per -10 % methylation = 1.15 and 1.16; p = 0.012 and 0.018 by Bonferroni correction, respectively). Hypomethylation of ITGB2_CpG_11/cg08422803 was a risk factor for CHD in people < 65 years and males (p < 0.05 after Bonferroni correction). The combination of ITGB2 methylation and conventional CHD risk factors could efficiently discriminate CHD, heart failure CHD, NYHA I&II CHD, and myocardial infarction CHD patients from controls (AUC = 0.78, 0.81, 0.80, and 0.81, respectively).

CONCLUSION

Blood-based ITGB2 methylation has the potential as a biomarker for CHD. The combination of ITGB2 methylation and conventional CHD risk factors may improve the risk assessment and detection of CHD.

Precision epigenetics provides a scalable pathway for improving coronary heart disease care globally

Coronary heart disease (CHD) is the world's leading cause of death. Up to 90% of all CHD deaths are preventable, but effective prevention of this mortality requires more scalable, precise methods for assessing CHD status and monitoring treatment response. Unfortunately, current diagnostic methods have barriers to implementation, particularly in rural areas and lower-income countries. This gap may be bridged by highly scalable advances in DNA methylation testing methods and artificial intelligence. Herein, we review prior studies of CHD related to methylation alone and in combination with other biovariables. We compare these new methods with established methods for diagnosing CHD. Finally, we outline pathways through which methylation-based testing methods may allow the democratization of improved methods for assessing CHD globally.

Hypomethylation of ABCG1 in peripheral blood as a potential marker for the detection of coronary heart disease

BACKGROUND

Novel molecular biomarkers for the risk assessment and early detection of coronary heart disease (CHD) are urgently needed for disease prevention. Altered methylation of ATP-binding cassette subfamily G member 1 (ABCG1) has been implicated in CHD but was mostly studied in Caucasians. Exploring the potential relationship between ABCG1 methylation in blood and CHD among the Chinese population would yield valuable insights.

METHODS

Peripheral blood samples were obtained from a case-control study (287 CHD patients vs. 277 controls) and a prospective nested case-control study (171 CHD patients and 197 matched controls). DNA extraction and bisulfite-specific PCR amplification techniques were employed for sample processing. Quantitative assessment of methylation levels was conducted using mass spectrometry. Statistical analyses involved the utilization of logistic regression and nonparametric tests.

RESULTS

We found hypomethylation of ABCG1 in whole blood was associated with the risk of CHD in both studies, which was enhanced in heart failure (HF) patients, female and younger subjects. When combined with baseline characteristics, altered ABCG1 methylation showed improved predictive effect for differentiating CHD cases, ischemic cardiomyopathy (ICM) cases, younger than 60 years CHD cases, and female CHD cases from healthy controls (area under the curve (AUC) = 0.68, 0.71, 0.74, and 0.73, respectively).

CONCLUSIONS

We demonstrated a robust link between ABCG1 hypomethylation in whole blood and CHD risk in the Chinese population and provided novel evidence indicating that aberrant ABCG1 methylation in peripheral blood can serve as an early detection biomarker for CHD patients.

Levels and clinical significance of the m6A methyltransferase METTL14 in patients with coronary heart disease

Objective

To investigate the association of methyltransferase-like protein 14 (METTL14) expression with coronary heart disease (CHD).

Methods

Three hundred and sixteen patients who attended Henan Provincial People's Hospital between June 2019 and February 2021 with principal symptoms of pain or tightness in the chest and who underwent coronary angiography for definitive diagnosis were enrolled. The uric acid, TG, TC, LDL-C, HDL-C, apolipoprotein A1, free fatty acid, lipoprotein a, homocysteine, CRP, and SAA levels were examined. The levels of METTL14, TNF-α, MCP-1, VCAM-1, ICAM-1, and IL-6 were evaluated by ELISA.

Results

Patients with CHD had significantly higher m6A methyltransferase activity. In addition, the incidence of diabetes and hypertension, as well as the concentrations of TC, CRP, and SAA were higher in CHD patients. Patients with coronary lesion branches also had significantly increased TG, LDL-C, CRP, and SAA levels. TNF-α, MCP-1, VCAM-1, ICAM-1, and IL-6 expression was also markedly increased in the CHD group (P < 0.001) as was the expression of METTL14 (P < 0.001). The METTL14 expression levels also differed significantly in relation to the number of branches with lesions (P < 0.01) and were correlated with SAA, VCAM-1, ICAM-1, IL-6, and the Gensini score. ROC curve analyses of METTL14 in CHD indicated an AUC of 0.881 (0.679, 0.894) with a cut-off value of 342.37, a sensitivity of 77%, and a specificity of 84%. MCP-1, VCAM-1, IL-6, SAA, and METTL14 were found to independently predict CHD risk.

Conclusions

METTL14 levels were found to be positively associated with inflammatory markers and to be an independent predictor of CHD risk.

DNA methylation-based biomarkers for cardiometabolic-related traits and their importance for risk stratification

Recent findings

The prevalence of cardiometabolic syndrome in adults is increasing worldwide, highlighting the importance of biomarkers for individuals' classification based on their health status. Although cardiometabolic risk scores and diagnostic criteria have been developed aggregating adverse health effects of individual conditions on the overall syndrome, none of them has gained unanimous acceptance. Therefore, novel molecular biomarkers have been developed to better understand the risk, onset and progression of both individual conditions and the overall cardiometabolic syndrome.

Summary

Consistent associations between whole blood DNA methylation (DNAm) levels at several single genomic (i.e. CpG) sites and both individual and aggregated cardiometabolic conditions supported the creation of second-generation DNAm-based cardiometabolic-related biomarkers. These biomarkers linearly combine individual DNAm levels from key CpG sites, selected by a two-step machine learning procedures. They can be used, even retrospectively, in populations with extant whole blood DNAm levels and without observed cardiometabolic phenotypes.

Purpose of review

Here we offer an overview of the second-generation DNAm-based cardiometabolic biomarkers, discussing methodological advancements and implications on the interpretation and generalizability of the findings. We finally emphasize the contribution of DNAm-based biomarkers for risk stratification beyond traditional factors and discuss limitations and future directions of the field.

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.

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.

Association of Promoter Methylation and Expression of Inflammatory Genes IL-6 and TNF-α with the Risk of Coronary Artery Disease in Diabetic and Obese Subjects among Asian Indians

The inflammatory cytokines such as interleukin-6 (IL-6) and tumour necrosis factor-alpha (TNF-α) are considered as the most important contributors to the endothelial dysfunction in subjects with type 2 diabetes mellitus (T2DM) and obesity. The hypomethylation of CpG sites in the promoter region of the IL-6 and TNF-α have shown to be associated with the increased expression of IL-6 and TNF-α. However, there are no studies on the methylation and expression of IL-6 and TNF-α with the risk of coronary artery disease (CAD) in subjects with T2DM and obesity in Asian Indians. Hence, the present study was aimed to investigate whether the IL-6, TNF-α promoter methylation and expression in blood leukocyte DNA is associated with the risk of CAD in diabetic and obese subjects in Asian Indians. For this study, we recruited 574 subjects which includes, 207 angiographically confirmed CAD patients, 100 T2DM patients, 82 obese subjects and 185 healthy controls. The methylation status of IL-6 and TNF-α gene loci was determined by methylation specific PCR (MPCR) and gene expression was determined by qPCR. We found significant hypomethylation of IL-6 in CAD and T2DM subjects (OR 1.98 95% CI: 1.32-2.97, p = 0.001, OR: 2.23 95% CI:1.34-3.76, p = 0.001, respectively). Further, a significant increase in the expression of IL-6 in CAD and T2DM subjects (fold change: 26.39 & 14.7, p = 0.0001) compared to the control subjects was observed. A significant increase in the hypomethylation of TNF-α in CAD, T2DM and obese subjects was observed as compared to the control (OR: 2.04 95% CI: 1.36-3.05, p = 0.0005, OR: 1.81 95% CI 1.10-2.96, p = 0.01, and OR: 2.1 95% CI 1.24-3.57, p = 0.007, respectively).We also found an increased expression of TNF-α in CAD, T2DM and obese subjects as compared to controls. In addition, presence of low folate, and hyperhomocysteinemia was observed in the present study, may be the contributing factors for the hypomethylation of IL-6 and TNF-α and oxidative stress. In conclusion, increased expression of IL-6 and TNF-α due to hypomethylation in T2DM and obese individuals may contribute to CAD risk in these subjects. The presence of hyperhomocysteinemia and increased oxidative risk may enhance the CAD risk further.

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.

How Are Epigenetic Modifications Related to Cardiovascular Disease in Older Adults?

The rate of aging has increased globally during recent decades and has led to a rising burden of age-related diseases such as cardiovascular disease (CVD). At the molecular level, epigenetic modifications have been shown recently to alter gene expression during the life course and impair cellular function. In this regard, several CVD risk factors, such as lifestyle and environmental factors, have emerged as key factors in epigenetic modifications within the cardiovascular system. In this study, we attempted to summarized recent evidence related to epigenetic modification, inflammation response, and CVD in older adults as well as the effect of lifestyle modification as a preventive strategy in this age group. Recent evidence showed that lifestyle and environmental factors may affect epigenetic mechanisms, such as DNA methylation, histone acetylation, and miRNA expression. Several substances or nutrients such as selenium, magnesium, curcumin, and caffeine (present in coffee and some teas) could regulate epigenetics. Similarly, physical inactivity, alcohol consumption, air pollutants, psychological stress, and shift working are well-known modifiers of epigenetic patterns. Understanding the exact ways that lifestyle and environmental factors could affect the expression of genes could help to influence the time of incidence and severity of aging-associated diseases. This review highlighted that a healthy lifestyle throughout the life course, such as a healthy diet rich in fibers, vitamins, and essential elements, and specific fatty acids, adequate physical activity and sleep, smoking cessation, and stress control, could be useful tools in preventing epigenetic changes that lead to impaired cardiovascular function.

Association between ABO and Duffy blood types and circulating chemokines and cytokines

Blood group antigens are inherited traits that may play a role in immune and inflammatory processes. We investigated associations between blood groups and circulating inflammation-related molecules in 3537 non-Hispanic white participants selected from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Whole-genome scans were used to infer blood types for 12 common antigen systems based on well-characterized single-nucleotide polymorphisms. Serum levels of 96 biomarkers were measured on multiplex fluorescent bead-based panels. We estimated marker associations with blood type using weighted linear or logistic regression models adjusted for age, sex, smoking status, and principal components of population substructure. Bonferroni correction was used to control for multiple comparisons, with two-sided p values < 0.05 considered statistically significant. Among the 1152 associations tested, 10 were statistically significant. Duffy blood type was associated with levels of CXCL6/GCP2, CXCL5/ENA78, CCL11/EOTAXIN, CXCL1/GRO, CCL2/MCP1, CCL13/MCP4, and CCL17/TARC, whereas ABO blood type was associated with levels of sVEGFR2, sVEGFR3, and sGP130. Post hoc pairwise t-tests showed that individuals with type Fy(a+b−) had the lowest mean levels of all Duffy-associated markers, while individuals with type A blood had the lowest mean levels of all ABO-associated markers. Additional work is warranted to explore potential clinical implications of these differences.

Framingham Heart Study: JACC Focus Seminar, 1/8

The Framingham Heart Study is the longest-running cardiovascular epidemiological study, starting in 1948. This paper gives an overview of the various cohorts, collected data, and most important research findings to date. In brief, the Framingham Heart Study, funded by the National Institutes of Health and managed by Boston University, spans 3 generations of well phenotyped White persons and 2 cohorts comprised of racial and ethnic minority groups. These cohorts are densely phenotyped, with extensive longitudinal follow-up, and they continue to provide us with important information on human cardiovascular and noncardiovascular physiology over the lifespan, as well as to identify major risk factors for cardiovascular disease. This paper also summarizes some of the more recent progress in molecular epidemiology and discusses the future of the study.

DNA methylation as the link between migration and the major noncommunicable diseases: the RODAM study

Aim: We assessed epigenome-wide DNA methylation (DNAm) differences between migrant and non-migrant Ghanaians. Materials & methods: We used the Illumina Infinium® HumanMethylation450 BeadChip to profile DNAm of 712 Ghanaians in whole blood. We used linear models to detect differentially methylated positions (DMPs) associated with migration. We performed multiple post hoc analyses to validate our findings. Results: We identified 13 DMPs associated with migration (delta-beta values: 0.2-4.5%). Seven DMPs in CPLX2, EIF4E3, MEF2D, TLX3, ST8SIA1, ANG and CHRM3 were independent of extrinsic genomic influences in public databases. Two DMPs in NLRC5 were associated with duration of stay in Europe among migrants. All DMPs were biologically linked to migration-related factors. Conclusion: Our findings provide the first insights into DNAm differences between migrants and non-migrants.

The Molecular Basis of Predicting Atherosclerotic Cardiovascular Disease Risk

Atherosclerotic cardiovascular disease (ASCVD) proceeds through a series of stages: initiation, progression (or regression), and complications. By integrating known biology regarding molecular signatures of each stage with recent advances in high-dimensional molecular data acquisition platforms (to assay the genome, epigenome, transcriptome, proteome, metabolome, and gut microbiome), snapshots of each phase of atherosclerotic cardiovascular disease development can be captured. In this review, we will summarize emerging approaches for assessment of atherosclerotic cardiovascular disease risk in humans using peripheral blood molecular signatures and molecular imaging approaches. We will then discuss the potential (and challenges) for these snapshots to be integrated into a personalized movie providing dynamic readouts of an individual's atherosclerotic cardiovascular disease risk status throughout the life course.

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.

Blood DNA methylation sites predict death risk in a longitudinal study of 12, 300 individuals

DNA methylation has fundamental roles in gene programming and aging that may help predict mortality. However, no large-scale study has investigated whether site-specific DNA methylation predicts all-cause mortality. We used the Illumina-HumanMethylation450-BeadChip to identify blood DNA methylation sites associated with all-cause mortality for 12, 300 participants in 12 Cohorts of the Heart and Aging Research in Genetic Epidemiology (CHARGE) Consortium. Over an average 10-year follow-up, there were 2,561 deaths across the cohorts. Nine sites mapping to three intergenic and six gene-specific regions were associated with mortality (P < 9.3x10-7) independently of age and other mortality predictors. Six sites (cg14866069, cg23666362, cg20045320, cg07839457, cg07677157, cg09615688)-mapping respectively to BMPR1B, MIR1973, IFITM3, NLRC5, and two intergenic regions-were associated with reduced mortality risk. The remaining three sites (cg17086398, cg12619262, cg18424841)-mapping respectively to SERINC2, CHST12, and an intergenic region-were associated with increased mortality risk. DNA methylation at each site predicted 5%-15% of all deaths. We also assessed the causal association of those sites to age-related chronic diseases by using Mendelian randomization, identifying weak causal relationship between cg18424841 and cg09615688 with coronary heart disease. Of the nine sites, three (cg20045320, cg07839457, cg07677157) were associated with lower incidence of heart disease risk and two (cg20045320, cg07839457) with smoking and inflammation in prior CHARGE analyses. Methylation of cg20045320, cg07839457, and cg17086398 was associated with decreased expression of nearby genes (IFITM3, IRF, NLRC5, MT1, MT2, MARCKSL1) linked to immune responses and cardiometabolic diseases. These sites may serve as useful clinical tools for mortality risk assessment and preventative care.

DNA methylation patterns from peripheral blood separate coronary artery disease patients with and without heart failure

Aims

Natriuretic peptides are useful for diagnosis and prognostication of heart failure of any cause. Now, research aims to discover novel biomarkers that will more specifically define the heart failure phenotype. DNA methylation plays a critical role in the development of cardiovascular disease with the potential to predict fundamental pathogenic processes. There is a lack of data relating DNA methylation in heart failure that specifically focuses on patients with severe multi‐vessel coronary artery disease. To begin to address this, we conducted a pilot study uniquely exploring the utility of powerful whole‐genome methyl‐binding domain‐capture sequencing in a cohort of cardiac surgery patients, matched for the severity of their coronary artery disease, aiming to identify candidate peripheral blood DNA methylation markers of ischaemic cardiomyopathy and heart failure.

Methods and results

We recruited a cohort of 20 male patients presenting for coronary artery bypass graft surgery with phenotypic extremes of heart failure but who otherwise share a similar coronary ischaemic burden, age, sex, and ethnicity. Methylation profiling in patient blood samples was performed using methyl‐binding domain‐capture sequencing. Differentially methylated regions were validated using targeted bisulfite sequencing. Gene set enrichment analysis was performed to identify differences in methylation at or near gene promoters in certain known Reactome pathways. We detected 567 188 methylation peaks of which our general linear model identified 68 significantly differentially methylated regions in heart failure with a false discovery rate <0.05. Of these regions, 48 occurred within gene bodies and 25 were located near enhancer elements, some within coding genes and some in non‐coding genes. Gene set enrichment analyses identified 103 significantly enriched gene sets (false discovery rate <0.05) in heart failure. Validation analysis of regions with the strongest differential methylation data was performed for two genes: HDAC9 and the uncharacterized miRNA gene MIR3675. Genes of particular interest as novel candidate markers of the heart failure phenotype with reduced methylation were HDAC9, JARID2, and GREM1 and with increased methylation PDSS2.

Conclusions

We demonstrate the utility of methyl‐binding domain‐capture sequencing to evaluate peripheral blood DNA methylation markers in a cohort of cardiac surgical patients with severe multi‐vessel coronary artery disease and phenotypic extremes of heart failure. The differential methylation status of specific coding genes identified are candidates for larger longitudinal studies. We have further demonstrated the value and feasibility of examining DNA methylation during the perioperative period to highlight biological pathways and processes contributing to complex phenotypes.

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.

Objectives, design and main findings until 2020 from the Rotterdam Study

The Rotterdam Study is an ongoing prospective cohort study that started in 1990 in the city of Rotterdam, The Netherlands. The study aims to unravel etiology, preclinical course, natural history and potential targets for intervention for chronic diseases in mid-life and late-life. The study focuses on cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. Since 2016, the cohort is being expanded by persons aged 40 years and over. The findings of the Rotterdam Study have been presented in over 1700 research articles and reports. This article provides an update on the rationale and design of the study. It also presents a summary of the major findings from the preceding 3 years and outlines developments for the coming period.

Deary I, Liu Q, Liu S, Elosua R, DeMeo DL, Ordovás JM. 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.

Epigenetics meets proteomics in an epigenome-wide association study with circulating blood plasma protein traits

DNA methylation and blood circulating proteins have been associated with many complex disorders, but the underlying disease-causing mechanisms often remain unclear. Here, we report an epigenome-wide association study of 1123 proteins from 944 participants of the KORA population study and replication in a multi-ethnic cohort of 344 individuals. We identify 98 CpG-protein associations (pQTMs) at a stringent Bonferroni level of significance. Overlapping associations with transcriptomics, metabolomics, and clinical endpoints suggest implication of processes related to chronic low-grade inflammation, including a network involving methylation of NLRC5, a regulator of the inflammasome, and associated pQTMs implicating key proteins of the immune system, such as CD48, CD163, CXCL10, CXCL11, LAG3, FCGR3B, and B2M. Our study links DNA methylation to disease endpoints via intermediate proteomics phenotypes and identifies correlative networks that may eventually be targeted in a personalized approach of chronic low-grade inflammation.

Epigenome-Wide Association Study for All-Cause Mortality in a Cardiovascular Cohort Identifies Differential Methylation in Castor Zinc Finger 1 (CASZ1)

Background DNA methylation is implicated in many chronic diseases and may contribute to mortality. Therefore, we conducted an epigenome-wide association study (EWAS) for all-cause mortality with whole-transcriptome data in a cardiovascular cohort (CATHGEN [Catheterization Genetics]). Methods and Results Cases were participants with mortality≥7 days postcatheterization whereas controls were alive with≥2 years of follow-up. The Illumina Human Methylation 450K and EPIC arrays (Illumina, San Diego, CA) were used for the discovery and validation sets, respectively. A linear model approach with empirical Bayes estimators adjusted for confounders was used to assess difference in methylation (Δβ). In the discovery set (55 cases, 49 controls), 25 629 (6.5%) probes were differently methylated (P<0.05). In the validation set (108 cases, 108 controls), 3 probes were differentially methylated with a false discovery rate-adjusted P<0.10: cg08215811 (SLC4A9; log2 fold change=-0.14); cg17845532 (MATK; fold change=-0.26); and cg17944110 (castor zinc finger 1 [CASZ1]; FC=0.26; P<0.0001; false discovery rate-adjusted P=0.046-0.080). Meta-analysis identified 6 probes (false discovery rate-adjusted P<0.05): the 3 above, cg20428720 (intergenic), cg17647904 (NCOR2), and cg23198793 (CAPN3). Messenger RNA expression of 2 MATK isoforms was lower in cases (fold change=-0.24 [P=0.007] and fold change=-0.61 [P=0.009]). The CASZ1, NCOR2, and CAPN3 transcripts did not show differential expression (P>0.05); the SLC4A9 transcript did not pass quality control. The cg17944110 probe is located within a potential regulatory element; expression of predicted targets (using GeneHancer) of the regulatory element, UBIAD1 (P=0.01) and CLSTN1 (P=0.03), were lower in cases. Conclusions We identified 6 novel methylation sites associated with all-cause mortality. Methylation in CASZ1 may serve as a regulatory element associated with mortality in cardiovascular patients. Larger studies are necessary to confirm these observations.

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

BACKGROUND

Epigenome-wide association studies using DNA methylation have the potential to uncover novel biomarkers and mechanisms of cardiovascular disease (CVD) risk. However, the direction of causation for these associations is not always clear, and investigations to-date have often failed to replicate at the level of individual loci.

METHODS

Here, we undertook module- and region-based DNA methylation analyses of incident CVD in the Women's Health Initiative (WHI) and Framingham Heart Study Offspring Cohort (FHS) in order to find more robust epigenetic biomarkers for cardiovascular risk. We applied weighted gene correlation network analysis (WGCNA) and the Comb-p algorithm to find methylation modules and regions associated with incident CVD in the WHI dataset.

RESULTS

We discovered two modules whose activation correlated with CVD risk and replicated across cohorts. One of these modules was enriched for development-related processes and overlaps strongly with epigenetic aging sites. For the other, we showed preliminary evidence for monocyte-specific effects and statistical links to cumulative exposure to traditional cardiovascular risk factors. Additionally, we found three regions (associated with the genes SLC9A1, SLC1A5, and TNRC6C) whose methylation associates with CVD risk.

CONCLUSIONS

In sum, we present several epigenetic associations with incident CVD which reveal disease mechanisms related to development and monocyte biology. Furthermore, we show that epigenetic modules may act as a molecular readout of cumulative cardiovascular risk factor exposure, with implications for the improvement of clinical risk prediction.