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

Developmental validation of an mRNA kit: A 5-dye multiplex assay designed for body-fluid identification

Identifying the sources of biosamples found at crime scenes is crucial for forensic investigations. Among the markers used for body fluid identification (BFI), mRNA has emerged as a well-studied marker because of its high specificity and remarkable stability. Despite this potential, commercially available mRNA kits specifically designed for BFI are lacking. Therefore, we developed an mRNA kit that includes 21 specific mRNA markers of body fluids, along with three housekeeping genes for BFI, to identify four forensic-relevant fluids (blood, semen, saliva, and vaginal fluids). In this study, we tested 451 single-body-fluid samples, validated the universality of the mRNA kit, and obtained a gene expression profile. We performed the validation studies in triplicates and determined the sensitivity, specificity, stability, precision, and repeatability of the mRNA kit. The sensitivity of the kit was found to be 0.1 ng. Our validation process involved the examination of 59 RNA mixtures, 60 body fluids mixtures, and 20 casework samples, which further established the reliability of the kit. Furthermore, we constructed five classifiers that can handle single-body fluids and mixtures using this kit. The classifiers output possibility values and identify the specific body fluids of interest. Our results showed the reliability and suitability of the BFI kit, and the Random Forest classifier performed the best, with 94% precision. In conclusion, we developed an mRNA kit for BFI which can be a promising tool for forensic practice.

Effect of care bundles based on importance degree analysis on postoperative comorbid state, coping style and disease management ability of patients with coronary heart disease

Coronary heart disease (CHD) is a significant global health concern, particularly among the elderly. While care bundles present a comprehensive strategy for clinical disorders, their application in CHD rehabilitation remains understudied. This research addresses this gap by investigating the effectiveness of care bundles in CHD patients. By analyzing important performance degrees, we aim to contribute valuable insights to bridge existing knowledge deficiencies. Our study strives to establish a theoretical foundation for the broader implementation of care bundles, potentially improving the quality of care and patient outcomes in CHD rehabilitation. This is a retrospective study. 360 patients with CHD who were admitted to our hospital from January 2019 to October 2022 were enrolled in this retrospective study and divided into the observation group (n = 180) and control group (n = 180) according to the different care that they received. All cases were given routine nursing after CHD operation, and the observation group was given care bundles on the basis of the analysis of important performance degrees. The perioperative indexes, self-management ability score, depression, anxiety, stress scale (DASS), coping styles, medical compliance and the incidence of complications were compared between the 2 groups. Aftercare, the time of hospitalization and getting out-of-bed in the observation group was notably shorter (P < .05). Aftercare, the scores of self-management ability and related dimensions in the observation group were notably higher (P < .05). After care, the score of depression (P < .001), anxiety (P = .003) and stress (P = .017) of the observation group were notably lower. Aftercare, the observation group face score was significantly higher than the control group (P = .005), while the observation group avoidance score (P = .028) and yield score (P < .001) were significantly lower than the control group scores. Aftercare, the compliance behavior of patients in the observation group was notably better (P = .013). Aftercare, the incidence of complications in the observation group was notably lower (P = .039). Care bundles based on the degree of importance analysis can play a positive role in postoperative comorbid state, coping styles and self-management ability of patients with CHD, which can improve the rehabilitation effects on patients.

Prognostic signature and immune efficacy of m1A-, m5C-, m6A-, m7G-, and DNA methylation-related regulators in hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is the main type of primary liver cancer, and its related death ranks third worldwide. The curative methods and progress prediction markers of HCC are not sufficient enough. Nevertheless, little progress has been made in the signature of m1A-, m5C-, m6A-, m7G-, and DNA methylation of HCC. Results: We calibrated a risk gene signature model that can be used to categorize HCC patients based on univariate, multivariate, and LASSO Cox regression analysis. This gene signature classified the patients into high- and low-risk subgroups. Patients in the high-risk group showed significantly reduced overall survival (OS) compared with patients in the low-risk group. The gene set variation analysis (GSVA), immune infiltration, and immunotherapy response were analyzed. The results demonstrated that an immunosuppressive environment was exited and the high-risk group had higher sensitivity to 5-fluorouracil, cisplatin, sorafenib, tamoxifen, and epirubicin. These results indicated personalized therapy should be taken into consideration. Conclusions: Our findings enriched our understanding of the molecular heterogeneity, tumor microenvironment (TME), and drug susceptibility of HCC. m1A-, m5C-, m6A-, m7G-, and DNA methylation-related regulators may be promising biomarkers for future research.

The Use of Precision Epigenetic Methods for the Diagnosis and Care of Stable Coronary Heart Disease Reduces Healthcare Costs

INTRODUCTION

The cost of secondary prevention of coronary heart disease (CHD) is continuing to increase, with a substantial portion of this acceleration being driven by the expense of confirmatory diagnostic testing. Conceivably, newly developed precision epigenetic technologies could drive down these costs. However, at the current time, their impact on overall expense for CHD care is poorly understood. We hypothesized that the use of a newly developed, highly sensitive, and specific epigenetic test, PrecisionCHD, could decrease the costs of secondary prevention.

METHODS

To test this hypothesis, we constructed a budget impact analysis using a cost calculation model that examined the effects of substituting PrecisionCHD for conventional CHD diagnostic tests on the expenses of the initial evaluation and first year of care of stable CHD using a 1-year time horizon with no discounting.

RESULTS

The model projected that for a commercial insurer with one million members, full adoption of PrecisionCHD as the primary method of initial CHD assessment would save approximately $113.6 million dollars in the initial year.

CONCLUSION

These analyses support the use of precision epigenetic methods as part of the initial diagnosis and care of stable CHD and can meaningfully reduce cost. Real-world pilots to test the reliability of these analyses are indicated.

Effects of quercetin on the DNA methylation pattern in tumor therapy: an updated review

Quercetin is a unique bioactive flavonoid, and is an excellent antioxidant and has anti-tumor effects by regulating different tumor-related processes like proliferation, apoptosis, invasion, and spread. The latest investigations reveal that quercetin may have the capability to influence DNA methylation modification, one of the primary factors in the development of tumors. Despite the fact that quercetin has significant therapeutic properties, its use as an anti-tumor medicine is constrained by its poor solubility, short half-life, and ineffective tumor targeting. Here, we review the structure and properties of quercetin, its capacity for DNA methylation modification in tumors, and the possibility of nanoscale delivery of quercetin for future tumor treatment.

CYP4V2 rs56413992 C > T was associated with the risk of coronary heart disease in the Chinese Han population: a case-control study

PURPOSE

The research aimed to detect the association between single nucleotide polymorphisms (SNPs) in CYP4V2 gene and coronary heart disease (CHD) risk.

METHODS

This case-control study included 487 CHD subjects and 487 healthy individuals. Logistic regression was performed to analyze the connection between five SNPs in CYP4V2 (rs1398007, rs13146272, rs3736455, rs1053094, and rs56413992) and CHD risk, and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to evaluate the connection.

RESULTS

As a result, we found that rs56413992 T allele (OR = 1.36, 95% CI = 1.09-1.70, p = 0.007) and CT genotype (OR = 1.40, 95% CI = 1.06-1.83, p = 0.017) were significantly associated with an increased risk of CHD in the overall analysis. Precisely, rs56413992 was linked to an elevated risk of CHD in people aged > 60, males, smokers and drinkers. The study also indicated that rs1398007 was linked to an increased CHD risk in drinkers. In addition, rs1053094 was correlated with a decreased risk of CHD complicated with diabetes mellitus (DM), and rs1398007 was correlated with a decreased risk of CHD complicated with hypertension (HTN).

CONCLUSION

This study was the first to experimentally demonstrate that CYP4V2 rs56413992 was associated with the risk of CHD, which will provide a certain reference for revealing the pathogenesis of CHD.

Monitoring Social Determinants of Health Assessing Patients and Communities

Because of the devastating health effects of social determinants of health (SDoH), it is important for the primary care provider to assess and monitor these types of stressors. This can be done via surveys, geomapping, or various biomarkers. To date, however, each of these methods is fraught with obstacles. There are currently are no validated "best" SDoH screening tools for use in clinical practice. Nor is geomapping, a perfect solution. Although mapping can collect location specific factors, it does not account for the fact that patients may live in one area, work in another and travel frequently to a third.

Multiomics tools for improved atherosclerotic cardiovascular disease management

Multiomics studies offer accurate preventive and therapeutic strategies for atherosclerotic cardiovascular disease (ASCVD) beyond traditional risk factors. By using artificial intelligence (AI) and machine learning (ML) approaches, it is possible to integrate multiple 'omics and clinical data sets into tools that can be utilized for the development of personalized diagnostic and therapeutic approaches. However, currently multiple challenges in data quality, integration, and privacy still need to be addressed. In this opinion, we emphasize that joined efforts, exemplified by the AtheroNET COST Action, have a pivotal role in overcoming the challenges to advance multiomics approaches in ASCVD research, with the aim to foster more precise and effective patient care.

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.

Metabolomic biomarkers of habitual B vitamin intakes unveil novel differentially methylated positions in the human epigenome

BACKGROUND

B vitamins such as folate (B9), B6, and B12 are key in one carbon metabolism, which generates methyl donors for DNA methylation. Several studies have linked differential methylation to self-reported intakes of folate and B12, but these estimates can be imprecise, while metabolomic biomarkers can offer an objective assessment of dietary intakes. We explored blood metabolomic biomarkers of folate and vitamins B6 and B12, to carry out epigenome-wide analyses across up to three European cohorts. Associations between self-reported habitual daily B vitamin intakes and 756 metabolites (Metabolon Inc.) were assessed in serum samples from 1064 UK participants from the TwinsUK cohort. The identified B vitamin metabolomic biomarkers were then used in epigenome-wide association tests with fasting blood DNA methylation levels at 430,768 sites from the Infinium HumanMethylation450 BeadChip in blood samples from 2182 European participants from the TwinsUK and KORA cohorts. Candidate signals were explored for metabolite associations with gene expression levels in a subset of the TwinsUK sample (n = 297). Metabolomic biomarker epigenetic associations were also compared with epigenetic associations of self-reported habitual B vitamin intakes in samples from 2294 European participants.

RESULTS

Eighteen metabolites were associated with B vitamin intakes after correction for multiple testing (Bonferroni-adj. p < 0.05), of which 7 metabolites were available in both cohorts and tested for epigenome-wide association. Three metabolites - pipecolate (metabolomic biomarker of B6 and folate intakes), pyridoxate (marker of B6 and folate) and docosahexaenoate (DHA, marker of B6) - were associated with 10, 3 and 1 differentially methylated positions (DMPs), respectively. The strongest association was observed between DHA and DMP cg03440556 in the SCD gene (effect = 0.093 ± 0.016, p = 4.07E-09). Pyridoxate, a catabolic product of vitamin B6, was inversely associated with CpG methylation near the SLC1A5 gene promoter region (cg02711608 and cg22304262) and with SLC7A11 (cg06690548), but not with corresponding changes in gene expression levels. The self-reported intake of folate and vitamin B6 had consistent but non-significant associations with the epigenetic signals.

CONCLUSION

Metabolomic biomarkers are a valuable approach to investigate the effects of dietary B vitamin intake on the human epigenome.

Accelerated DNA methylation age plays a role in the impact of cardiovascular risk factors on the human heart

BACKGROUND

DNA methylation (DNAm) age acceleration (AgeAccel) and cardiac age by 12-lead advanced electrocardiography (A-ECG) are promising biomarkers of biological and cardiac aging, respectively. We aimed to explore the relationships between DNAm age and A-ECG heart age and to understand the extent to which DNAm AgeAccel relates to cardiovascular (CV) risk factors in a British birth cohort from 1946.

RESULTS

We studied four DNAm ages (AgeHannum, AgeHorvath, PhenoAge, and GrimAge) and their corresponding AgeAccel. Outcomes were the results from two publicly available ECG-based cardiac age scores: the Bayesian A-ECG-based heart age score of Lindow et al. 2022 and the deep neural network (DNN) ECG-based heart age score of Ribeiro et al. 2020. DNAm AgeAccel was also studied relative to results from two logistic regression-based A-ECG disease scores, one for left ventricular (LV) systolic dysfunction (LVSD), and one for LV electrical remodeling (LVER). Generalized linear models were used to explore the extent to which any associations between biological cardiometabolic risk factors (body mass index, hypertension, diabetes, high cholesterol, previous cardiovascular disease [CVD], and any CV risk factor) and the ECG-based outcomes are mediated by DNAm AgeAccel. We derived the total effects, average causal mediation effects (ACMEs), average direct effects (ADEs), and the proportion mediated [PM] with their 95% confidence intervals [CIs]. 498 participants (all 60-64 years) were included, with the youngest ECG heart age being 27 and the oldest 90. When exploring the associations between cardiometabolic risk factors and Bayesian A-ECG cardiac age, AgeAccelPheno appears to be a partial mediator, as ACME was 0.23 years [0.01, 0.52] p = 0.028 (i.e., PM≈18%) for diabetes, 0.34 [0.03, 0.74] p = 0.024 (i.e., PM≈15%) for high cholesterol, and 0.34 [0.03, 0.74] p = 0.024 (PM≈15%) for any CV risk factor. Similarly, AgeAccelGrim mediates ≈30% of the relationship between diabetes or high cholesterol and the DNN ECG-based heart age. When exploring the link between cardiometabolic risk factors and the A-ECG-based LVSD and LVER scores, it appears that AgeAccelPheno or AgeAccelGrim mediate 10-40% of these associations.

CONCLUSION

By the age of 60, participants with accelerated DNA methylation appear to have older, weaker, and more electrically impaired hearts. We show that the harmful effects of CV risk factors on cardiac age and health, appear to be partially mediated by DNAm AgeAccelPheno and AgeAccelGrim. This highlights the need to further investigate the potential cardioprotective effects of selective DNA methyltransferases modulators.

A Transcriptomic Analysis of Smoking-Induced Gene Expression Alterations in Coronary Artery Disease Patients

Smoking is a well established risk factor for coronary artery disease (CAD). Despite this, there have been no previous studies investigating the effects of smoking on blood gene expression in CAD patients. This single-centre cross-sectional study was designed with clearly defined inclusion criteria to address this gap. We conducted a high-throughput approach using next generation sequencing analysis with a single-end sequencing protocol and a read length of 75-cycles. Sixty-one patients with a median age of 67 years (range: 28-88 years) were recruited, and only 44 subjects were included for further analyses. Our investigation revealed 120 differentially expressed genes (DEGs) between smokers and nonsmokers, with a fold change (FC) of ≥1.5 and a p-value < 0.05. Among these DEGs, 15 were upregulated and 105 were downregulated. Notably, when applying a more stringent adjusted FC ≥ 2.0, 31 DEGs (5 upregulated, annotated to immune response pathways, and 26 downregulated, involving oxygen and haem binding or activity, with FDR ≤ 0.03) remained statistically significant at an alpha level of <0.05. Our results illuminate the molecular mechanisms underlying CAD, fortifying existing epidemiological evidence. Of particular interest is the unexplored overexpression of RCAN3, TRAV4, and JCHAIN genes, which may hold promising implications for the involvement of these genes in CAD among smokers.

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.

Epigenetic modifications as therapeutic targets in atherosclerosis: a focus on DNA methylation and non-coding RNAs

Significant progress in the diagnosis and treatment of cardiovascular disease (CVD) has been made in the past decade, yet it remains a leading cause of morbidity and mortality globally, claiming an estimated 17.9 million deaths per year. Although encompassing any condition that affects the circulatory system, including thrombotic blockage, stenosis, aneurysms, blood clots and arteriosclerosis (general hardening of the arteries), the most prevalent underlying hallmark of CVD is atherosclerosis; the plaque-associated arterial thickening. Further, distinct CVD conditions have overlapping dysregulated molecular and cellular characteristics which underlie their development and progression, suggesting some common aetiology. The identification of heritable genetic mutations associated with the development of atherosclerotic vascular disease (AVD), in particular resulting from Genome Wide Association Studies (GWAS) studies has significantly improved the ability to identify individuals at risk. However, it is increasingly recognised that environmentally-acquired, epigenetic changes are key factors associated with atherosclerosis development. Increasing evidence suggests that these epigenetic changes, most notably DNA methylation and the misexpression of non-coding, microRNAs (miRNAs) are potentially both predictive and causal in AVD development. This, together with their reversible nature, makes them both useful biomarkers for disease and attractive therapeutic targets potentially to reverse AVD progression. We consider here the association of aberrant DNA methylation and dysregulated miRNA expression with the aetiology and progression of atherosclerosis, and the potential development of novel cell-based strategies to target these epigenetic changes therapeutically.

Integration of epigenetic regulatory mechanisms in heart failure

The number of "omics" approaches is continuously growing. Among others, epigenetics has appeared as an attractive area of investigation by the cardiovascular research community, notably considering its association with disease development. Complex diseases such as cardiovascular diseases have to be tackled using methods integrating different omics levels, so called "multi-omics" approaches. These approaches combine and co-analyze different levels of disease regulation. In this review, we present and discuss the role of epigenetic mechanisms in regulating gene expression and provide an integrated view of how these mechanisms are interlinked and regulate the development of cardiac disease, with a particular attention to heart failure. We focus on DNA, histone, and RNA modifications, and discuss the current methods and tools used for data integration and analysis. Enhancing the knowledge of these regulatory mechanisms may lead to novel therapeutic approaches and biomarkers for precision healthcare and improved clinical outcomes.

Associations between residential greenness and the predicted 10-year risk for atherosclerosis cardiovascular disease among Chinese adults

BACKGROUND

Exposure to build environments, especially residential greenness, offers benefits to reduce the development of atherosclerotic cardiovascular diseases (ASCVD). The 10-year ASCVD risk is a useful indicator for long-term ASCVD risk, but the evidence on the association and potential pathway of residential greenness in mitigating its development remains unclear.

OBJECTIVES

This study aimed to investigate the associations between residential greenness and the 10-year predicted ASCVD risks, and potentially mediation effect on this association by air pollution, body mass index (BMI) and physical activity (PA).

METHODS

The baseline of the China Multi-Ethnic Cohort (CMEC) study, enrolling 99,556 adults during 2018-2019, was used in this cross-sectional study. The participants' 10-year ASCVD risks were predicted as low-, moderate-, and high-risk groups, based on the six risk factors: age, smoking, hypertension, low-density lipoprotein cholesterol (LDL-C), high high-density lipoprotein cholesterol (HDL-C), and high total cholesterol (TC). The 3-year mean value within the circular buffer of 500 m and 1000 m of Enhanced Vegetation Index (EVI_500m and EVI_1000m) were used to assess greenness exposure. Multiple logistic regression was used to evaluate the association between residential greenness and the 10-year ASCVD risks. Stratified analyses by sex, age and smoking status were performed to identify susceptible populations. Causal mediation analysis was used to explore the mediation effects of air pollution, BMI and PA.

RESULTS

A total of 75,975 participants were included, of which 17.9 % (n = 13,614) and 5.6 % (n = 4253) had the moderate and high 10-year ASCVD risks, respectively. Compared to the low-risk group, each interquartile increase in EVI_500m and EVI_1000m reduced the ASCVD risk of the moderate-risk group by 4 % (OR = 0.96 [0.94, 0.98]) and 4 % (OR = 0.96 [0.94, 0.98]), respectively; and reduced the risk of the high-risk group by 8 % (OR = 0.92 [0.90, 0.96]) and 7 % (OR = 0.93 [0.90, 0.97]), respectively. However, the increased greenness did not affect the ASCVD risk of the high-risk group when compared to the moderate-risk group. Effects of residential greenness on the ASCVD risk were stronger in women than in men (p < 0.05), and were not observed in those aged ≥55. PA and BMI partially mediated the association between greenness and the 10-year ASCVD risk.

CONCLUSIONS

ASCVD prevention strategies should be tailored to maximize the effectiveness within the groups with different ASCVD risks, better at early stages when the ASCVD risk is low.

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.

Rural-urban disparities in the associations of residential greenness with diabetes and prediabetes among adults in southeastern China

AIMS

Greenness offers health benefits to prevent diabetes in urban areas. However, urban-rural disparities in this association have not been explored, with the underlying pathways understudied as well. We aimed to investigate and compare the associations and potential pathways between residential greenness and the risks for diabetes and prediabetes in urban and rural areas.

METHODS

Diabetes and prediabetes were diagnosed by fasting blood glucose (FBG). The participants' residential greenness exposure was estimated by the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). The association of residential greenness with the risks for diabetes and prediabetes was estimated by logistic regression and the generalized additive model. The potential mediation effects of air pollution, body mass index (BMI), and physical activity (PA) were examined by causal mediation analysis.

RESULTS

Of the 50,593 included participants, and the prevalence of prediabetes and diabetes were 21.22 % and 5.63 %, respectively. Each 0.1-unit increase in EVI_500m and NDVI_500m for healthy people reduced the risk for prediabetes by 12 % and 8 %, respectively, and substantially reduced the risk for diabetes by 23 % and 19 %, respectively. For those with prediabetes, each 0.1-unit increase in EVI_500m and NDVI_500m reduced the diabetes risk by 14 % and 12 %, respectively. Compared to the risks for diabetes at the 25th percentile of EVI_500m/NDVI_500m, such risks significantly reduced when EVI_500m (NDVI_500m) increased over 0.43 (0.48) and 0.28 (0.39) in urban and rural areas, respectively. The residential greenness-prediabetes/diabetes associations were mediated by air pollution and PA in urban areas and by air pollution and BMI in rural areas.

CONCLUSIONS

Exposure to residential greenness was associated with a lower risk for prediabetes and diabetes in urban areas and, more strongly, in rural areas, which were partly mediated by air pollution, PA, and BMI.

Identification of differentially methylated regions in rare diseases from a single-patient perspective

BACKGROUND

DNA methylation (5-mC) is being widely recognized as an alternative in the detection of sequence variants in the diagnosis of some rare neurodevelopmental and imprinting disorders. Identification of alterations in DNA methylation plays an important role in the diagnosis and understanding of the etiology of those disorders. Canonical pipelines for the detection of differentially methylated regions (DMRs) usually rely on inter-group (e.g., case versus control) comparisons. However, these tools might perform suboptimally in the context of rare diseases and multilocus imprinting disturbances due to small cohort sizes and inter-patient heterogeneity. Therefore, there is a need to provide a simple but statistically robust pipeline for scientists and clinicians to perform differential methylation analyses at the single patient level as well as to evaluate how parameter fine-tuning may affect differentially methylated region detection.

RESULT

We implemented an improved statistical method to detect differentially methylated regions in correlated datasets based on the Z-score and empirical Brown aggregation methods from a single-patient perspective. To accurately assess the predictive power of our method, we generated semi-simulated data using a public control population of 521 samples and investigated how the size of the control population, methylation difference, and region size affect DMR detection. In addition, we validated the detection of methylation events in patients suffering from rare multi-locus imprinting disturbance and evaluated how this method could complement existing tools in the context of clinical diagnosis.

CONCLUSION

In this study, we present a robust statistical method to perform differential methylation analysis at the single patient level and describe its optimal parameters to increase DMRs identification performance. Finally, we show its diagnostic utility when applied to rare disorders.

Why epigenetics is (not) a biosocial science and why that matters

Epigenetic modifications offer compelling evidence of the environmental etiology of complex diseases. Social and biographical conditions, as well as material exposures, all modulate our biology with consequences for risk predispositions and health conditions. Elucidating these complex biosocial loops is one of the main challenges animating epigenetics. Yet, research on the development of epigenetic biomarkers often pulls in a direction that departs from a view of biological determinants of health embedded in their social and material environment. Taking the example of the epigenetics of cardiovascular diseases, this paper illustrates how common understandings of epigenetic biomarkers strongly lean toward considering them as mere targets for molecular intervention, rather than as correlates of a complex biological and social patterning of disease. This reductionism about biosocial dynamics of disease, we argue, hampers the pursuit of the goals epigenetics has given itself (in cardiology and beyond). If epigenetic mechanisms point to the deep socio-environmental embeddedness of our health, we conclude, future designs and methods of this research may require an improved methodological consideration of a biosocial perspective.

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.

Prenatal exposure to environmental pro-oxidants induces mitochondria-mediated epigenetic changes: a cross-sectional pilot study

Mitochondria play a central role in maintaining cellular and metabolic homeostasis during vital development cycles of foetal growth. Optimal mitochondrial functions are important not only to sustain adequate energy production but also for regulated epigenetic programming. However, these organelles are subtle targets of environmental exposures, and any perturbance in the defined mitochondrial machinery during the developmental stage can lead to the re-programming of the foetal epigenetic landscape. As these modifications can be transferred to subsequent generations, we herein performed a cross-sectional study to have an in-depth understanding of this intricate phenomenon. The study was conducted with two arms: whereas the first group consisted of in utero pro-oxidant exposed individuals and the second group included controls. Our results showed higher levels of oxidative mtDNA damage and associated integrated stress response among the exposed individuals. These disturbances were found to be closely related to the observed discrepancies in mitochondrial biogenesis. The exposed group showed mtDNA hypermethylation and changes in allied mitochondrial functioning. Altered expression of mitomiRs and their respective target genes in the exposed group indicated the possibilities of a disturbed mitochondrial-nuclear cross talk. This was further confirmed by the modified activity of the mitochondrial stress regulators and pro-inflammatory mediators among the exposed group. Importantly, the disturbed DNMT functioning, hypermethylation of nuclear DNA, and higher degree of post-translational histone modifications established the existence of aberrant epigenetic modifications in the exposed individuals. Overall, our results demonstrate the first molecular insights of in utero pro-oxidant exposure associated changes in the mitochondrial-epigenetic axis. Although, our study might not cement an exposure-response relationship for any particular environmental pro-oxidant, but suffice to establish a dogma of mito-epigenetic reprogramming at intrauterine milieu with chronic illness, a hitherto unreported interaction.

Identification of DNA methylation-regulated genes as potential biomarkers for coronary heart disease via machine learning in the Framingham Heart Study

Background

DNA methylation-regulated genes have been demonstrated as the crucial participants in the occurrence of coronary heart disease (CHD). The machine learning based on DNA methylation-regulated genes has tremendous potential for mining non-invasive predictive biomarkers and exploring underlying new mechanisms of CHD.

Results

First, the 2085 age-gender-matched individuals in Framingham Heart Study (FHS) were randomly divided into training set and validation set. We then integrated methylome and transcriptome data of peripheral blood leukocytes (PBLs) from the training set to probe into the methylation and expression patterns of CHD-related genes. A total of five hub DNA methylation-regulated genes were identified in CHD through dimensionality reduction, including ATG7, BACH2, CDKN1B, DHCR24 and MPO. Subsequently, methylation and expression features of the hub DNA methylation-regulated genes were used to construct machine learning models for CHD prediction by LightGBM, XGBoost and Random Forest. The optimal model established by LightGBM exhibited favorable predictive capacity, whose AUC, sensitivity, and specificity were 0.834, 0.672, 0.864 in the validation set, respectively. Furthermore, the methylation and expression statuses of the hub genes were verified in monocytes using methylation microarray and transcriptome sequencing. The methylation statuses of ATG7, DHCR24 and MPO and the expression statuses of ATG7, BACH2 and DHCR24 in monocytes of our study population were consistent with those in PBLs from FHS.

Conclusions

We identified five DNA methylation-regulated genes based on a predictive model for CHD using machine learning, which may clue the new epigenetic mechanism for CHD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01343-2.

Targeting DNA methylation can reduce cardiac injury associated with ischemia reperfusion: One step closer to clinical translation with blood-borne assessment

Ischemia reperfusion (I/R) injury is one of the main clinical challenges for cardiac surgeons. No effective strategies or therapy targeting the molecular and cellular mechanisms to reduce I/R exists to date, despite altered gene expression and cellular metabolism/physiology. We aimed to identify whether DNA methylation, an unexplored target, can be a potential site to curb I/R-associated cell death by using the left anterior descending artery occlusion model in male Wistar rats. I/R rat heart exhibited global DNA hypermethylation with a corresponding decline in the mitochondrial genes (PGC-1α, TFAM, POLG, ND1, ND3, ND4, Cyt B, COX1, and COX2), antioxidant genes (SOD2, catalase, and Gpx2) and elevation in apoptotic genes (Casp3, Casp7, and Casp9) expression with corresponding changes in their activity, resulting in injury. Targeting global DNA methylation in I/R hearts by using its inhibitor significantly reduced the I/R-associated infarct size by 45% and improved dysferlin levels via modulating the genes involved in cell death apoptotic pathway (Casp3, Casp7, and PARP), inflammation (IL-1β, TLR4, ICAM1, and MyD88), oxidative stress (SOD1, catalase, Gpx2, and NFkB) and mitochondrial function and its regulation (MT-ND1, ND3, COX1, ATP6, PGC1α, and TFAM) in the cardiac tissue. The corresponding improvement in the genes’ function was reflected in the respective hearts via the reduction in apoptotic TUNEL positive cells and ROS levels, thereby improving myocardial architecture (H&E staining), antioxidant enzymes (SOD, catalase activity) and mitochondrial electron transport chain activities and ATP levels. The analysis of blood from the I/R animals in the presence and absence of methylation inhibition exhibited a similar pattern of changes as that observed in the cardiac tissue with respect to global DNA methylation level and its enzymes (DNMT and TET) gene expression, where the blood cardiac injury markers enzymes like LDH and CK-MB were elevated along with declined tissue levels. Based on these observations, we concluded that targeting DNA methylation to reduce the level of DNA hypermethylation can be a promising approach in ameliorating I/R injury. Additionally, the blood-borne changes reflected I/R-associated myocardial tissue alteration, making it suitable to predict I/R-linked pathology.

A bibliometric analysis of DNA methylation in cardiovascular diseases from 2001 to 2021

BACKGROUND

DNA methylation is a dynamically reversible form of epigenetics. Dynamic regulation plays an important role in cardiovascular diseases (CVDs). However, there have been few bibliometric studies in this field. We aimed to visualize the research results and hotspots of DNA methylation in CVDs using a bibliometric analysis to provide a scientific direction for future research.

METHODS

Publications related to DNA methylation in CVDs from January 1, 2001, to September 15, 2021, were searched and confirmed from the Web of Science Core Collection. CiteSpace 5.7 and VOSviewer 1.6.15 were used for bibliometric and knowledge-map analyses.

RESULTS

A total of 2617 publications were included in 912 academic journals by 15,584 authors from 963 institutions from 85 countries/regions. Among them, the United States of America, China, and England were the top 3 countries contributing to the field of DNA methylation. Harvard University, Columbia University, and University of Cambridge were the top 3 contributing institutions in terms of publications and were closely linked. PLoS One was the most published and co-cited journal. Baccarelli Andrea A published the most content, while Barker DJP had the highest frequency of co-citations. The keyword cluster focused on the mechanism, methyl-containing substance, exposure/risk factor, and biomarker. In terms of research hotspots, references with strong bursts, which are still ongoing, recently included "epigenetic clock" (2017-2021), "obesity, smoking, aging, and DNA methylation" (2017-2021), and "biomarker and epigenome-wide association study" (2019-2021).

CONCLUSIONS

We used bibliometric and visual methods to identify research hotspots and trends in DNA methylation in CVDs. Epigenetic clocks, biomarkers, environmental exposure, and lifestyle may become the focus and frontier of future research.

The association between ACTB methylation in peripheral blood and coronary heart disease in a case-control study

Background

Coronary heart disease (CHD) brings a heavy burden to society worldwide. Novel and minimally invasive biomarkers for the risk evaluation of CHD are urgently needed. Previous study has revealed that blood-based hypomethylation of β-actin (ACTB) was associated with increased risk of stroke, but not reported in CHD yet.

Objectives

We aimed to explore the association between blood-based ACTB methylation and the risk of CHD in a case-control study in the Chinese population.

Methods

The methylation level of ACTB was quantitatively determined by mass spectrometry in 281 CHD patients and 272 controls. The association between ACTB methylation and CHD risk was estimated by logistic regression analyses adjusted for possible confounding effects.

Results

We found a significant association between hypermethylation of ACTB in peripheral blood and increased risk of CHD (odds ratios (ORs) per +10% methylation: 1.19–1.45, p < 0.013 for nine out of thirteen CpG sites), especially in male subjects and heart failure (HF) patients (ORs per +10% methylation: 1.20–1.43, 1.38–1.46; p < 0.030, 1.52 × 10⁻⁴, respectively). Hypermethylation of ACTB_CpG_2.3, ACTB_CpG_7.8, and ACTB_CpG_9.10 was observed in the CHD patients with minor to medium cardiac function impairment (NYHA I&II CHD cases) (ORs per +10% methylation: 1.38–1.44; p < 0.001). The combination of ACTB_CpG_2.3, ACTB_CpG_7.8, and ACTB_CpG_9.10 methylation levels could efficiently discriminate CHD cases, male CHD patients, HF and NYHA I&II CHD patients from controls (area under curve (AUC) = 0.75, 0.74, 0.73, and 0.77, respectively).

Conclusions

Our study reveals a strong association between blood-based ACTB hypermethylation and CHD risk. The combination of ACTB methylation and conventional risk factors might provide a novel strategy to improve risk assessment of CHD.

Association of lipid metabolism-related gene promoter methylation with risk of coronary artery disease

BACKGROUND

Coronary artery disease (CAD) is a complex disease that is influenced by environmental and genetic factors. Lipid levels are regarded as a major risk factor for CAD, and epigenetic mechanisms might be involved in the regulation of CAD development. This study was designed to investigate the association between the DNA methylation status of 8 lipid metabolism-related genes and the risk of CAD in the Chinese Han population.

METHODS

A total of 260 individuals were sampled in this study, including 120 CAD cases and 140 normal healthy controls. DNA methylation status was tested via targeted bisulfite sequencing.

RESULTS

The results indicated a significant association between hypomethylation of the APOC3, CETP and APOC1 gene promoters and the risk of CAD. Individuals with higher methylation levels of the APOA5 and LIPC gene promoters had increased risks for CAD. In addition, ANGPTL4 methylation level was significantly associated with CAD in males but not females. There were no significant differences in the methylation levels of the APOB and PCSK9 gene promoters between CAD patients and controls.

CONCLUSIONS

The methylation status of the APOC3, APOA5, LIPC, CETP and APOC1 gene promoters may be associated with the development of CAD.

Predicting risk of lung function impairment and all-cause mortality using a DNA methylation-based classifier of tobacco smoke exposure

BACKGROUND

The Epigenetic Smoking Status Estimator (EpiSmokEr) predicts smoking phenotypes based on DNA methylation at 121 CpG sites.

OBJECTIVE

Evaluate associations of EpiSmokEr-predicted versus self-reported smoking phenotypes with lung function and all-cause mortality in a cohort of older adults.

METHODS

The prospective Normative Aging Study collected DNA methylation measurements from 1999 to 2012 with follow-up through 2016. The R package EpiSmokEr derived predicted smoking phenotypes based on DNA methylation levels assayed by the Illumina HumanMethylation450 Beadchip. Spirometry was collected every 3-5 years. Airflow limitation was defined as forced expiratory volume in 1 s/forced vital capacity <0.7. Vital status was monitored through periodic mailings.

RESULTS

Among 784 participants contributing 5414 person-years of follow-up, the EpiSmokEr-predicted smoking phenotypes matched the self-reported phenotypes for 228 (97%) never smokers and 22 (71%) current smokers. In contrast, EpiSmokEr classified 407 (79%) self-reported former smokers as never smokers. Nonetheless, the EpiSmokEr-predicted former smoking phenotype was more strongly associated with incident airflow limitation (hazard ratio [HR] = 3.15, 95% confidence interval [CI] = 1.50-6.59) and mortality (HR = 2.11, 95% CI = 1.56-2.85) compared to the self-reported former smoking phenotype (airflow limitation: HR = 2.21, 95% CI = 1.13-4.33; mortality: HR = 1.08, 95% CI = 0.86-1.36). Risk of airflow limitation and death did not differ among self-reported never smokers and former smokers who were classified as never smokers. The discriminative accuracy of EpiSmokEr-predicted phenotypes for incident airflow limitation and mortality was improved compared to self-reported phenotypes.

CONCLUSIONS

The DNA methylation-based EpiSmokEr classifier may be a useful surrogate of smoking-induced lung damage and may identify former smokers most at risk of adverse smoking-related health effects.

Genetics and Epigenetics in Personalized Nutrition: Evidence, Expectations and Experiences

With the presentation of the blueprint of the first human genome in 2001 and the advent of technologies for high-throughput genetic analysis, personalized nutrition (PN) became a new scientific field and the first commercial offerings of genotype-based nutrition advice emerged at the same time. Here, we summarize the state of evidence for the effect of genetic and epigenetic factors in the development of obesity, the metabolic syndrome and resulting illnesses such as non-insulin-dependent diabetes mellitus and cardiovascular diseases. We also critically value the concepts of PN that were built around the new genetic avenue from both the academic and a commercial perspective and their effectiveness in causing sustained changes in diet, lifestyle and for improving health. Despite almost 20 years of research and commercial direct-to-consumer offerings, evidence for the success of gene-based dietary recommendations is still generally lacking. This calls for new concepts of future PN solutions that incorporate more phenotypic measures and provide a panel of instruments (e.g., self- and bio-monitoring tools, feedback systems, algorithms based on artificial intelligence) that increases compliance based on the individual´s physical and social environment and value system. This article is protected by copyright. All rights reserved.

DNA Methylation Aberrant in Atherosclerosis

Atherosclerosis (AS) is a pathological process involving lipid oxidation, immune system activation, and endothelial dysfunction. The activated immune system could lead to inflammation and oxidative stress. Risk factors like aging and hyperhomocysteinemia also promote the progression of AS. Epigenetic modifications, including DNA methylation, histone modification, and non-coding RNA, are involved in the modulation of genes between the environment and AS formation. DNA methylation is one of the most important epigenetic mechanisms in the pathogenesis of AS. However, the relationship between the progression of AS and DNA methylation is not completely understood. This review will discuss the abnormal changes of DNA methylation in AS, including genome-wide hypermethylation dominating in AS with an increase of age, hypermethylation links with methyl supply and generating hyperhomocysteinemia, and the influence of oxidative stress with the demethylation process by interfering with the hydroxyl-methylation of TET proteins. The review will also summarize the current status of epigenetic treatment, which may provide new direction and potential therapeutic targets for AS.

The Relationship between Epigenetic Age and Myocardial Infarction/Acute Coronary Syndrome in a Population-Based Nested Case-Control Study

We investigated the relationship between ‘epigenetic age’ (EA) derived from DNA methylation (DNAm) and myocardial infarction (MI)/acute coronary syndrome (ACS). A random population sample was examined in 2003/2005 (n = 9360, 45–69, the HAPIEE project) and followed up for 15 years. From this cohort, incident MI/ACS (cases, n = 129) and age- and sex-stratified controls (n = 177) were selected for a nested case-control study. Baseline EA (Horvath’s, Hannum’s, PhenoAge, Skin and Blood) and the differences between EA and chronological age (CA) were calculated (ΔAHr, ΔAHn, ΔAPh, ΔASB). EAs by Horvath’s, Hannum’s and Skin and Blood were close to CA (median absolute difference, MAD, of 1.08, –1.91 and –2.03 years); PhenoAge had MAD of −9.29 years vs. CA. The adjusted odds ratios (ORs) of MI/ACS per 1–year increments of ΔAHr, ΔAHn, ΔASB and ΔAPh were 1.01 (95% CI 0.95–1.07), 1.01 (95% CI 0.95–1.08), 1.02 (95% CI 0.97–1.06) and 1.01 (0.93–1.09), respectively. When classified into tertiles, only the highest tertile of ΔAPh showed a suggestion of increased risk of MI/ACS with OR 2.09 (1.11–3.94) independent of age and 1.84 (0.99–3.52) in the age- and sex-adjusted model. Metabolic modulation may be the likely mechanism of this association. In conclusion, this case-control study nested in a prospective population-based cohort did not find strong associations between accelerated epigenetic age markers and risk of MI/ACS. Larger cohort studies are needed to re-examine this important research question.