DNA Methylation and Age-Independent Cardiovascular Risk, an Epigenome-Wide Approach: The REGICOR Study (REgistre GIroní del COR)

Exploring machine learning strategies for predicting cardiovascular disease risk factors from multi-omic data

BACKGROUND

Machine learning (ML) classifiers are increasingly used for predicting cardiovascular disease (CVD) and related risk factors using omics data, although these outcomes often exhibit categorical nature and class imbalances. However, little is known about which ML classifier, omics data, or upstream dimension reduction strategy has the strongest influence on prediction quality in such settings. Our study aimed to illustrate and compare different machine learning strategies to predict CVD risk factors under different scenarios.

METHODS

We compared the use of six ML classifiers in predicting CVD risk factors using blood-derived metabolomics, epigenetics and transcriptomics data. Upstream omic dimension reduction was performed using either unsupervised or semi-supervised autoencoders, whose downstream ML classifier performance we compared. CVD risk factors included systolic and diastolic blood pressure measurements and ultrasound-based biomarkers of left ventricular diastolic dysfunction (LVDD; E/e' ratio, E/A ratio, LAVI) collected from 1,249 Finnish participants, of which 80% were used for model fitting. We predicted individuals with low, high or average levels of CVD risk factors, the latter class being the most common. We constructed multi-omic predictions using a meta-learner that weighted single-omic predictions. Model performance comparisons were based on the F1 score. Finally, we investigated whether learned omic representations from pre-trained semi-supervised autoencoders could improve outcome prediction in an external cohort using transfer learning.

RESULTS

Depending on the ML classifier or omic used, the quality of single-omic predictions varied. Multi-omics predictions outperformed single-omics predictions in most cases, particularly in the prediction of individuals with high or low CVD risk factor levels. Semi-supervised autoencoders improved downstream predictions compared to the use of unsupervised autoencoders. In addition, median gains in Area Under the Curve by transfer learning compared to modelling from scratch ranged from 0.09 to 0.14 and 0.07 to 0.11 units for transcriptomic and metabolomic data, respectively.

CONCLUSIONS

By illustrating the use of different machine learning strategies in different scenarios, our study provides a platform for researchers to evaluate how the choice of omics, ML classifiers, and dimension reduction can influence the quality of CVD risk factor predictions.

The influence of epigenetics and inflammation on cardiometabolic risks

Cardiometabolic diseases include metabolic syndrome, obesity, type 2 diabetes mellitus, and hypertension. Epigenetic modifications participate in cardiometabolic diseases through several pathways, including inflammation, vascular dysfunction, and insulin resistance. Epigenetic modifications, which encompass alterations to gene expression without mutating the DNA sequence, have gained much attention in recent years, since they have been correlated with cardiometabolic diseases and may be targeted for therapeutic interventions. Epigenetic modifications are greatly influenced by environmental factors, such as diet, physical activity, cigarette smoking, and pollution. Some modifications are heritable, indicating that the biological expression of epigenetic alterations may be observed across generations. Moreover, many patients with cardiometabolic diseases present with chronic inflammation, which can be influenced by environmental and genetic factors. The inflammatory environment worsens the prognosis of cardiometabolic diseases and further induces epigenetic modifications, predisposing patients to the development of other metabolism-associated diseases and complications. A deeper understanding of inflammatory processes and epigenetic modifications in cardiometabolic diseases is necessary to improve our diagnostic capabilities, personalized medicine approaches, and the development of targeted therapeutic interventions. Further understanding may also assist in predicting disease outcomes, especially in children and young adults. This review describes epigenetic modifications and inflammatory processes underlying cardiometabolic diseases, and further discusses advances in the research field with a focus on specific points for interventional therapy.

The Role of Selected Epigenetic Pathways in Cardiovascular Diseases as a Potential Therapeutic Target

Epigenetics is a rapidly developing science that has gained a lot of interest in recent years due to the correlation between characteristic epigenetic marks and cardiovascular diseases (CVDs). Epigenetic modifications contribute to a change in gene expression while maintaining the DNA sequence. The analysis of these modifications provides a thorough insight into the cardiovascular system from its development to its further functioning. Epigenetics is strongly influenced by environmental factors, including known cardiovascular risk factors such as smoking, obesity, and low physical activity. Similarly, conditions affecting the local microenvironment of cells, such as chronic inflammation, worsen the prognosis in cardiovascular diseases and additionally induce further epigenetic modifications leading to the consolidation of unfavorable cardiovascular changes. A deeper understanding of epigenetics may provide an answer to the continuing strong clinical impact of cardiovascular diseases by improving diagnostic capabilities, personalized medical approaches and the development of targeted therapeutic interventions. The aim of the study was to present selected epigenetic pathways, their significance in cardiovascular diseases, and their potential as a therapeutic target in specific medical conditions.

DNA methylation patterns at birth predict health outcomes in young adults born very low birthweight

Background

Individuals born very low birthweight (VLBW) are at increased risk of impaired cardiovascular and respiratory function in adulthood. To identify markers to predict future risk for VLBW individuals, we analyzed DNA methylation at birth and at 28 years in the New Zealand (NZ) VLBW cohort (all infants born < 1500 g in NZ in 1986) compared with age-matched, normal birthweight controls. Associations between neonatal methylation and cardiac structure and function (echocardiography), vascular function and respiratory outcomes at age 28 years were documented.

Results

Genomic DNA from archived newborn heel-prick blood (n = 109 VLBW, 51 controls) and from peripheral blood at ~ 28 years (n = 215 VLBW, 96 controls) was analyzed on Illumina Infinium MethylationEPIC 850 K arrays. Following quality assurance and normalization, methylation levels were compared between VLBW cases and controls at both ages by linear regression, with genome-wide significance set to p < 0.05 adjusted for false discovery rate (FDR, Benjamini-Hochberg). In neonates, methylation at over 16,400 CpG methylation sites differed between VLBW cases and controls and the canonical pathway most enriched for these CpGs was Cardiac Hypertrophy Signaling (p = 3.44E⁻¹¹). The top 20 CpGs that differed most between VLBW cases and controls featured clusters in ARID3A, SPATA33, and PLCH1 and these 3 genes, along with MCF2L, TRBJ2-1 and SRC, led the list of 15,000 differentially methylated regions (DMRs) reaching FDR-adj significance. Fifteen of the 20 top CpGs in the neonate EWAS showed associations between methylation at birth and adult cardiovascular traits (particularly LnRHI). In 28-year-old adults, twelve CpGs differed between VLBW cases and controls at FDR-adjusted significance, including hypermethylation in EBF4 (four CpGs), CFI and UNC119B and hypomethylation at three CpGs in HIF3A and one in KCNQ1. DNA methylation GrimAge scores at 28 years were significantly greater in VLBW cases versus controls and weakly associated with cardiovascular traits. Four CpGs were identified where methylation differed between VLBW cases and controls in both neonates and adults, three reversing directions with age (two CpGs in EBF4, one in SNAI1 were hypomethylated in neonates, hypermethylated in adults). Of these, cg16426670 in EBF4 at birth showed associations with several cardiovascular traits in adults.

Conclusions

These findings suggest that methylation patterns in VLBW neonates may be informative about future adult cardiovascular and respiratory outcomes and have value in guiding early preventative care to improve adult health.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-023-01463-3.

DNA Methylation Alterations in Fractionally Irradiated Rats and Breast Cancer Patients Receiving Radiotherapy

Radiation-Induced CardioVascular Disease (RICVD) is an important concern in thoracic radiotherapy with complex underlying pathophysiology. Recently, we proposed DNA methylation as a possible mechanism contributing to RICVD. The current study investigates DNA methylation in heart-irradiated rats and radiotherapy-treated breast cancer (BC) patients. Rats received fractionated whole heart X-irradiation (0, 0.92, 6.9 and 27.6 Gy total doses) and blood was collected after 1.5, 3, 7 and 12 months. Global and gene-specific methylation of the samples were evaluated; and gene expression of selected differentially methylated regions (DMRs) was validated in rat and BC patient blood. In rats receiving an absorbed dose of 27.6 Gy, DNA methylation alterations were detected up to 7 months with differential expression of cardiac-relevant DMRs. Of those, SLMAP showed increased expression at 1.5 months, which correlated with hypomethylation. Furthermore, E2F6 inversely correlated with a decreased global longitudinal strain. In BC patients, E2F6 and SLMAP exhibited differential expression directly and 6 months after radiotherapy, respectively. This study describes a systemic radiation fingerprint at the DNA methylation level, elucidating a possible association of DNA methylation to RICVD pathophysiology, to be validated in future mechanistic studies.

Association of Cardiovascular Health Through Young Adulthood With Genome-Wide DNA Methylation Patterns in Midlife: The CARDIA Study

BACKGROUND

Cardiovascular health (CVH) from young adulthood is strongly associated with an individual's future risk of cardiovascular disease (CVD) and total mortality. Defining epigenomic biomarkers of lifelong CVH exposure and understanding their roles in CVD development may help develop preventive and therapeutic strategies for CVD.

METHODS

In 1085 CARDIA study (Coronary Artery Risk Development in Young Adults) participants, we defined a clinical cumulative CVH score that combines body mass index, blood pressure, total cholesterol, and fasting glucose measured longitudinally from young adulthood through middle age over 20 years (mean age, 25-45). Blood DNA methylation at >840 000 methylation markers was measured twice over 5 years (mean age, 40 and 45). Epigenome-wide association analyses on the cumulative CVH score were performed in CARDIA and compared in the FHS (Framingham Heart Study). We used penalized regression to build a methylation-based risk score to evaluate the risk of incident coronary artery calcification and clinical CVD events.

RESULTS

We identified 45 methylation markers associated with cumulative CVH at false discovery rate <0.01 (P=4.7E-7-5.8E-17) in CARDIA and replicated in FHS. These associations were more pronounced with methylation measured at an older age. CPT1A, ABCG1, and SREBF1 appeared as the most prominent genes. The 45 methylation markers were mostly located in transcriptionally active chromatin and involved lipid metabolism, insulin secretion, and cytokine production pathways. Three methylation markers located in genes SARS1, SOCS3, and LINC-PINT statistically mediated 20.4% of the total effect between CVH and risk of incident coronary artery calcification. The methylation risk score added information and significantly (P=0.004) improved the discrimination capacity of coronary artery calcification status versus CVH score alone and showed association with risk of incident coronary artery calcification 5 to 10 years later independent of cumulative CVH score (odds ratio, 1.87; P=9.66E-09). The methylation risk score was also associated with incident clinical CVD in FHS (hazard ratio, 1.28; P=1.22E-05).

CONCLUSIONS

Cumulative CVH from young adulthood contributes to midlife epigenetic programming over time. Our findings demonstrate the role of epigenetic markers in response to CVH changes and highlight the potential of epigenomic markers for precision CVD prevention, and earlier detection of subclinical CVD, as well.

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.

Epigenetic Studies of Chinese Herbal Medicine: Pleiotropic Role of DNA Methylation

Accumulating knowledge has been achieved on DNA methylation participating in numerous cellular processes and multiple human diseases; however, few studies have addressed the pleiotropic role of DNA methylation in Chinese herbal medicine (CHM). CHM has been used worldwide for the prevention and treatment of multiple diseases. Newly developed epigenetic techniques have brought great opportunities for the development of CHM. In this review, we summarize the DNA methylation studies and portray the pleiotropic role of DNA methylation in CHM. DNA methylation serves as a mediator participating in plant responses to environmental factors, and thus affecting CHM medicinal plants growth and bioactive compound biosynthesis which are vital for therapeutic effects. Furthermore, DNA methylation helps to uncover the pharmaceutical mechanisms of CHM formulae, herbs, and herbal-derived compounds. It also provides scientific validation for constitution theory and other essential issues of CHM. This newly developed field of DNA methylation is up-and-coming to address many complicated scientific questions of CHM; it thus not only promotes disease treatment but also facilitates health maintenance.

BMPR2 promoter methylation and its expression in valvular heart disease complicated with pulmonary artery hypertension

Valvular heart disease (VHD) is a common heart disease that affects blood flow. It usually requires heart surgery. Valvular heart disease complicated with pulmonary artery hypertension (VHD-PAH) may be lethal due to heart failure that results from increased heart burden. It is important for these patients to seek early treatment in order to minimize the heart damage. However, there is no reliable diagnosis method in VHD. In this study, we found DNA methylation was increased at the promoter of BMPR2 gene in the VHD patients compared with the healthy controls. This finding was confirmed by an independent cohort study of VHD patients and healthy controls. In addition, BMPR2 mRNA levels were reduced in the plasma of the VHD patients. There is strong correlation between BMPR2 promoter DNA methylation and the severity of VHD. Indeed, we found that both BMPR2 promoter DNA methylation and BMPR2 mRNA levels in the plasma are good biomarkers of VHD by themselves, with the respective AUC value of 0.879 and 0.725, respectively. When they were used in combination, the diagnostic value was even better, with the AUC value of 0.93. Consistent with the results in the VHD patients, we observed decreased BMPR2 and increased fibrosis in the lung of a PAH model mouse. BMPR2 was also decreased in the hearts of the PAH mice, whereas BMP4 was increased. Furthermore, BMPR2 was reduced in the heart valve tissue samples of human VHD patients after valve replacement with moderate/severe PAH compared with those with mild PAH. There was also increased apoptosis in the hearts of the PAH mice. BMPR2 promoter DNA methylation and its expression appear to be good biomarkers for VHD. Our results also suggest that DNA methylation may cause PAH through deregulation of BMP signaling and increased apoptosis.

A 6-CpG validated methylation risk score model for metabolic syndrome: The HyperGEN and GOLDN studies

There has been great interest in genetic risk prediction using risk scores in recent years, however, the utility of scores developed in European populations and later applied to non-European populations has not been successful. The goal of this study was to create a methylation risk score (MRS) for metabolic syndrome (MetS), demonstrating the utility of MRS across race groups using cross-sectional data from the Hypertension Genetic Epidemiology Network (HyperGEN, N = 614 African Americans (AA)) and the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN, N = 995 European Americans (EA)). To demonstrate this, we first selected cytosine-guanine dinucleotides (CpG) sites measured on Illumina Methyl450 arrays previously reported to be significantly associated with MetS and/or component conditions in more than one race/ethnic group (CPT1A cg00574958, PHOSPHO1 cg02650017, ABCG1 cg06500161, SREBF1 cg11024682, SOCS3 cg18181703, TXNIP cg19693031). Second, we calculated the parameter estimates for the 6 CpGs in the HyperGEN data (AA) and used the beta estimates as weights to construct a MRS in HyperGEN (AA), which was validated in GOLDN (EA). We performed association analyses using logistic mixed models to test the association between the MRS and MetS, adjusting for covariates. Results showed the MRS was significantly associated with MetS in both populations. In summary, a MRS for MetS was a strong predictor for the condition across two race groups, suggesting MRS may be useful to examine metabolic disease risk or related complications across race/ethnic groups.

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.

Epigenome-wide analysis of DNA methylation and coronary heart disease: a nested case-control study

Background

Identifying environmentally responsive genetic loci where DNA methylation is associated with coronary heart disease (CHD) may reveal novel pathways or therapeutic targets for CHD. We conducted the first prospective epigenome-wide analysis of DNA methylation in relation to incident CHD in the Asian population.

Methods

We did a nested case-control study comprising incident CHD cases and 1:1 matched controls who were identified from the 10 year follow-up of the China Kadoorie Biobank. Methylation level of baseline blood leukocyte DNA was measured by Infinium Methylation EPIC BeadChip. We performed the single cytosine-phosphate-guanine (CpG) site association analysis and network approach to identify CHD-associated CpG sites and co-methylation gene module.

Results

After quality control, 982 participants (mean age 50.1 years) were retained. Methylation level at 25 CpG sites across the genome was associated with incident CHD (genome-wide false discovery rate [FDR] < 0.05 or module-specific FDR < 0.01). One SD increase in methylation level of identified CpGs was associated with differences in CHD risk, ranging from a 47 % decrease to a 118 % increase. Mediation analyses revealed 28.5 % of the excessed CHD risk associated with smoking was mediated by methylation level at the promoter region of ANKS1A gene (P for mediation effect = 0.036). Methylation level at the promoter region of SNX30 was associated with blood pressure and subsequent risk of CHD, with the mediating proportion to be 7.7 % (P = 0.003) via systolic blood pressure and 6.4 % (P = 0.006) via diastolic blood pressure. Network analysis revealed a co-methylation module associated with CHD.

Conclusions

We identified novel blood methylation alterations associated with incident CHD in the Asian population and provided evidence of the possible role of epigenetic regulations in the smoking- and blood pressure-related pathways to CHD risk.

Funding

This work was supported by National Natural Science Foundation of China (81390544 and 91846303). The CKB baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation in Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust (202922/Z/16/Z, 088158/Z/09/Z, 104085/Z/14/Z), grant (2016YFC0900500, 2016YFC0900501, 2016YFC0900504, 2016YFC1303904) from the National Key R&D Program of China, and Chinese Ministry of Science and Technology (2011BAI09B01).

ABCA1, TCF7, NFATC1, PRKCZ, and PDGFA DNA methylation as potential epigenetic-sensitive targets in acute coronary syndrome via network analysis

Acute coronary syndrome (ACS) is the most severe clinical manifestation of coronary heart disease.We performed an epigenome-wide analysis of circulating CD4⁺ and CD8⁺ T cells isolated from ACS patients and healthy subjects (HS), enrolled in the DIANA clinical trial, by reduced-representation bisulphite sequencing (RRBS). In CD4⁺ T cells, we identified 61 differentially methylated regions (DMRs) associated with 57 annotated genes (53% hyper- and 47% hypo-methylated) by comparing ACS patients vs HS. In CD8⁺ T cells, we identified 613 DMRs associated with 569 annotated genes (28% hyper- and 72% hypo-methylated) in ACS patients as compared to HS. In CD4⁺ vs CD8⁺ T cells of ACS patients we identified 175 statistically significant DMRs associated with 157 annotated genes (41% hyper- and 59% hypo-methylated). From pathway analyses, we selected six differentially methylated hub genes (NFATC1, TCF7, PDGFA, PRKCB, PRKCZ, ABCA1) and assessed their expression levels by q-RT-PCR. We found an up-regulation of selected genes in ACS patients vs HS (P < 0.001). ABCA1, TCF7, PDGFA, and PRKCZ gene expression was positively associated with CK-MB serum concentrations (r = 0.75, P = 0.03; r = 0.760, P = 0.029; r = 0.72, P = 0.044; r = 0.74, P = 0.035, respectively).This pilot study is the first single-base resolution map of DNA methylome by RRBS in CD4⁺ and CD8⁺ T cells and provides specific methylation signatures to clarify the role of aberrant methylation in ACS pathogenesis, thus supporting future research for novel epigenetic-sensitive biomarkers in the prevention and early diagnosis of this pathology.

DNA methylation biomarkers of myocardial infarction and cardiovascular disease

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

DNA methylation of blood cells is associated with prevalent type 2 diabetes in a meta-analysis of four European cohorts

BACKGROUND

Type 2 diabetes (T2D) is a heterogeneous disease with well-known genetic and environmental risk factors contributing to its prevalence. Epigenetic mechanisms related to changes in DNA methylation (DNAm), may also contribute to T2D risk, but larger studies are required to discover novel markers, and to confirm existing ones.

RESULTS

We performed a large meta-analysis of individual epigenome-wide association studies (EWAS) of prevalent T2D conducted in four European studies using peripheral blood DNAm. Analysis of differentially methylated regions (DMR) was also undertaken, based on the meta-analysis results. We found three novel CpGs associated with prevalent T2D in Europeans at cg00144180 (HDAC4), cg16765088 (near SYNM) and cg24704287 (near MIR23A) and confirmed three CpGs previously identified (mapping to TXNIP, ABCG1 and CPT1A). We also identified 77 T2D associated DMRs, most of them hypomethylated in T2D cases versus controls. In adjusted regressions among diabetic-free participants in ALSPAC, we found that all six CpGs identified in the meta-EWAS were associated with white cell-types. We estimated that these six CpGs captured 11% of the variation in T2D, which was similar to the variation explained by the model including only the common risk factors of BMI, sex, age and smoking (R2 = 10.6%).

CONCLUSIONS

This study identifies novel loci associated with T2D in Europeans. We also demonstrate associations of the same loci with other traits. Future studies should investigate if our findings are generalizable in non-European populations, and potential roles of these epigenetic markers in T2D etiology or in determining long term consequences of T2D.

Systematic Identification of Key Functional Modules and Genes in Gastric Cancer

Gastric cancer (GC) is associated with high incidence and mortality rates worldwide. Differentially expressed gene (DEG) analysis and weighted gene coexpression network analysis (WGCNA) are important bioinformatic methods for screening core genes. In our study, DEG analysis and WGCNA were combined to screen the hub genes, and pathway enrichment analyses were performed on the DEGs. SBNO2 was identified as the hub gene based on the intersection between the DEGs and the purple module in WGCNA. The expression and prognostic value of SBNO2 were verified in UALCAN, GEPIA2, Human Cancer Metastasis Database, Kaplan–Meier plotter, and TIMER. We identified 1974 DEGs, and 28 modules were uncovered via WGCNA. The purple module was identified as the hub module in WGCNA. SBNO2 was identified as the hub gene, which was upregulated in tumour tissues. Moreover, patients with GC and higher SBNO2 expression had worse prognoses. In addition, SBNO2 was suggested to play an important role in immune cell infiltration. In summary, based on DEGs and key modules related to GC, we identified SBNO2 as a hub gene, thereby offering novel insights into the development and treatment of GC.

Comparison of DNA Methylation Profiles of Hemostatic Genes between Liver Tissue and Peripheral Blood within Individuals

DNA methylation has become increasingly recognized in the etiology of complex diseases, including thrombotic disorders. Blood is often collected in epidemiological studies for genotyping and has recently also been used to examine DNA methylation in epigenome-wide association studies. DNA methylation patterns are often tissue-specific, thus, peripheral blood may not accurately reflect the methylation pattern in the tissue of relevance. Here, we collected paired liver and blood samples concurrently from 27 individuals undergoing liver surgery. We performed targeted bisulfite sequencing for a set of 35 hemostatic genes primarily expressed in liver to analyze DNA methylation levels of >10,000 cytosine-phosphate-guanine (CpG) dinucleotides. We evaluated whether DNA methylation in blood could serve as a proxy for DNA methylation in liver at individual CpGs. Approximately 30% of CpGs were nonvariable and were predominantly hypo- (<25%) or hypermethylated (>70%) in both tissues. While blood can serve as a proxy for liver at these CpGs, the low variability renders these unlikely to explain phenotypic differences. We therefore focused on CpG sites with variable methylation levels in liver. The level of blood-liver tissue correlation varied widely across these variable CpGs; moderate correlations (0.5 ≤ r < 0.75) were detected for 6% and strong correlations (r ≥ 0.75) for a further 4%. Our findings indicate that it is essential to study the concordance of DNA methylation between blood and liver at individual CpGs. This paired blood-liver dataset is intended as a resource to aid interpretation of blood-based DNA methylation results.

Smoking-related changes in DNA methylation and gene expression are associated with cardio-metabolic traits

BACKGROUND

Tobacco smoking is a well-known modifiable risk factor for many chronic diseases, including cardiovascular disease (CVD). One of the proposed underlying mechanism linking smoking to disease is via epigenetic modifications, which could affect the expression of disease-associated genes. Here, we conducted a three-way association study to identify the relationship between smoking-related changes in DNA methylation and gene expression and their associations with cardio-metabolic traits.

RESULTS

We selected 2549 CpG sites and 443 gene expression probes associated with current versus never smokers, from the largest epigenome-wide association study and transcriptome-wide association study to date. We examined three-way associations, including CpG versus gene expression, cardio-metabolic trait versus CpG, and cardio-metabolic trait versus gene expression, in the Rotterdam study. Subsequently, we replicated our findings in The Cooperative Health Research in the Region of Augsburg (KORA) study. After correction for multiple testing, we identified both cis- and trans-expression quantitative trait methylation (eQTM) associations in blood. Specifically, we found 1224 smoking-related CpGs associated with at least one of the 443 gene expression probes, and 200 smoking-related gene expression probes to be associated with at least one of the 2549 CpGs. Out of these, 109 CpGs and 27 genes were associated with at least one cardio-metabolic trait in the Rotterdam Study. We were able to replicate the associations with cardio-metabolic traits of 26 CpGs and 19 genes in the KORA study. Furthermore, we identified a three-way association of triglycerides with two CpGs and two genes (GZMA; CLDND1), and BMI with six CpGs and two genes (PID1; LRRN3). Finally, our results revealed the mediation effect of cg03636183 (F2RL3), cg06096336 (PSMD1), cg13708645 (KDM2B), and cg17287155 (AHRR) within the association between smoking and LRRN3 expression.

CONCLUSIONS

Our study indicates that smoking-related changes in DNA methylation and gene expression are associated with cardio-metabolic risk factors. These findings may provide additional insights into the molecular mechanisms linking smoking to the development of CVD.

AHRR hypomethylation as an epigenetic marker of smoking history predicts risk of myocardial infarction in former smokers

BACKGROUND AND AIMS

Smoking causes cardiovascular disease. AHRR hypomethylation at the cg05575921 site is associated with active and former smoking status at baseline, and cumulative amount of tobacco smoked. We tested the hypothesis that AHRR cg05575921 hypomethylation as an epigenetic marker of smoking history predicts the risk of myocardial infarction in former smokers.

METHODS

We included 10,510 individuals with methylation extent measurements and information on smoking status from the Copenhagen City Heart Study (CCHS), a prospective, cohort study of the general population carried out from 1991 to 2003. The endpoint myocardial infarction was retrieved from the national Danish Patient Registry and the national Danish Causes of Death Registry.

RESULTS

For individuals in the 1st (lowest) quartile of AHRR cg05575921 methylation (≤49% methylation extent), 99% were ever smokers at baseline (active and former smokers combined) compared to 42% in the 4th (highest) quartile (>62% methylation extent). For former smokers, the cumulative incidence of myocardial infarction was higher in the lowest methylation extent (1st-50th percentile) compared to the highest methylation extent (51st-100th percentile). Compared to never smokers, the multivariable adjusted subhazard ratio for myocardial infarction was 1.09 (95%CI:0.88-1.35) for former smokers with the highest methylation degree, 1.38 (1.06-1.80) for active smokers with the highest methylation extent, 1.39 (1.08-1.78) for former smokers with the lowest methylation extent, and 1.61 (1.35-1.92) for active smokers with the lowest methylation extent.

CONCLUSIONS

AHRR cg05575921 hypomethylation as an epigenetic marker of smoking history predicts risk of myocardial infarction, particularly in former smokers. Further, AHRR hypomethylation, regardless of smoking status, was associated with increased risk of myocardial infarction.

Methylation vs. Protein Inflammatory Biomarkers and Their Associations With Cardiovascular Function

DNA methylation data can be used to estimate proportions of leukocyte subsets retrospectively, when directly measured cell counts are unavailable. The methylation-derived neutrophil-to-lymphocyte and lymphocyte-to-monocyte ratios (mdNLRs and mdLMRs) have proven to be particularly useful as indicators of systemic inflammation. As with directly measured NLRs and LMRs, these methylation-derived ratios have been used as prognostic markers for cancer, although little is known about them in relation to other disorders with inflammatory components, such as cardiovascular disease (CVD). Recently, methylation of five genomic cytosine-phosphate-guanine sites (CpGs) was suggested as proxies for mdNLRs, potentially providing a cost-effective alternative when whole-genome methylation data are not available. This study compares seven methylation-derived inflammatory markers (mdNLR, mdLMR, and individual CpG sites) with five conventionally used protein-based inflammatory markers (C-reactive protein, interleukins 6 and 10, tumor-necrosis factor alpha, and interferon-gamma) and a protein-based inflammation score, in their associations with cardiovascular function (CVF) and risk. We found that markers of CVF were more strongly associated with methylation-derived than protein-based markers. In addition, the protein-based and methylation-derived inflammatory markers complemented rather than proxied one another in their contribution to the variance in CVF. There were no strong correlations between the methylation and protein markers either. Therefore, the methylation markers could offer unique information on the inflammatory process and are not just surrogate markers for inflammatory proteins. Although the five CpGs mirrored the mdNLR well in their capacity as proxies, they contributed to CVF above and beyond the mdNLR, suggesting possible added functional relevance. We conclude that methylation-derived indicators of inflammation enable individuals with increased CVD risk to be identified without measurement of protein-based inflammatory markers. In addition, the five CpGs investigated here could be useful surrogates for the NLR when the cost of array data cannot be met. Used in tandem, methylation-derived and protein-based inflammatory markers explain more variance than protein-based inflammatory markers alone.

Identification of common and divergent gene expression signatures in patients with venous and arterial thrombosis using data from public repositories

Cardiovascular disease (CVD) and venous thromboembolism (VTE) figure among the main causes of morbidity and mortality in modern societies. Although associated with distinct pathogenic mechanisms, epidemiological, experimental and clinical trial data suggest that the mechanisms responsible for arterial and venous thrombosis are at least partially overlapped. Herein we aimed to explore shared and discordant pathways involved in the pathogenesis of VTE and CVD at the transcriptomic level and to validate the results in independent cohorts. Five public datasets of gene expression data from VTE and CVD (myocardial infarction, peripheral arterial occlusive disease and stroke) patients were analyzed using an integrative bioinformatic strategy. A machine/statistical learning method was used to derive classifiers for the discrimination of VTE and CVD, and tested in independent datasets. Two sets of genes that were commonly (n = 472) or divergently (n = 124) expressed in CVD and VTE were identified. Genes and pathways associated with innate immune function were over-represented in both conditions, along with pathways associated with complement and hemostasis. Pathways associated with neutrophil activation and with IL-1 signaling were also enriched in CVD compared to VTE. The gene expression signature of VTE more closely resembled the pattern of cardioembolic stroke than the patterns of acute myocardial infarction, ischemic stroke and peripheral arterial occlusive disease. Classifiers derived from these gene lists accurately discriminated patients with VTE and CVD from independent cohorts. In conclusion, our results add a new set of data at the transcriptomic level for future studies between arterial and venous thrombosis.

EWAS Atlas: a curated knowledgebase of epigenome-wide association studies

Epigenome-Wide Association Study (EWAS) has become increasingly significant in identifying the associations between epigenetic variations and different biological traits. In this study, we develop EWAS Atlas (http://bigd.big.ac.cn/ewas), a curated knowledgebase of EWAS that provides a comprehensive collection of EWAS knowledge. Unlike extant data-oriented epigenetic resources, EWAS Atlas features manual curation of EWAS knowledge from extensive publications. In the current implementation, EWAS Atlas focuses on DNA methylation—one of the key epigenetic marks; it integrates a large number of 329 172 high-quality EWAS associations, involving 112 tissues/cell lines and covering 305 traits, 1830 cohorts and 390 ontology entities, which are completely based on manual curation from 649 studies reported in 401 publications. In addition, it is equipped with a powerful trait enrichment analysis tool, which is capable of profiling trait-trait and trait-epigenome relationships. Future developments include regular curation of recent EWAS publications, incorporation of more epigenetic marks and possible integration of EWAS with GWAS. Collectively, EWAS Atlas is dedicated to the curation, integration and standardization of EWAS knowledge and has the great potential to help researchers dissect molecular mechanisms of epigenetic modifications associated with biological traits.

Epigenetic Regulation of Vascular Diseases

Epigenetic regulatory mechanisms, encompassing diverse molecular processes including DNA methylation, histone post-translational modifications, and noncoding RNAs, are essential to numerous processes such as cell differentiation, growth and development, environmental adaptation, aging, and disease states. In many cases, epigenetic changes occur in response to environmental cues and lifestyle factors, resulting in persistent changes in gene expression that affect vascular disease risk during the lifetime of the individual. Biological aging-a powerful cardiovascular risk factor-is partly genetically determined yet strongly influenced by traditional risk factors, reflecting epigenetic modulation. Quantification of specific DNA methylation patterns may serve as an accurate predictor of biological age-a concept known as the epigenetic clock, which could help to refine cardiovascular risk assessment. Epigenetic reprogramming of monocytes rewires cellular immune signaling and induces a metabolic shift toward aerobic glycolysis, thereby increasing innate immune responses. This form of trained epigenetic memory can be maladaptive, thus augmenting vascular inflammation. Somatic mutations in epigenetic regulatory enzymes lead to clonal hematopoiesis of indeterminate potential, a precursor of hematologic malignancies and a recently recognized cardiovascular risk factor; moreover, epigenetic regulators are increasingly being targeted in cancer therapeutics. Thus, understanding epigenetic regulatory mechanisms lies at the intersection between cancer and cardiovascular disease and is of paramount importance to the burgeoning field of cardio-oncology (Graphic Abstract).

DNA Methylation of Candidate Genes (ACE II, IFN-γ, AGTR 1, CKG, ADD1, SCNN1B and TLR2) in Essential Hypertension: A Systematic Review and Quantitative Evidence Synthesis

Physical, chemical, and social environments adversely affect the molecular process and results in cell signal transduction and the subsequent transcription factor dysregulation, leading to impaired gene expression and abnormal protein synthesis. Stressful environments such as social adversity, isolation, sustained social threats, physical inactivity, and highly methylated diets predispose individuals to molecular level alterations such as aberrant epigenomic modulations that affect homeostasis and hemodynamics. With cardiovascular disease as the leading cause of mortality in the US and blacks/African Americans being disproportionately affected by hypertension (HTN) which contributes substantially to these deaths, reflecting the excess mortality and survival disadvantage of this sub-population relative to whites, understanding the molecular events, including epigenomic and socio-epigenomic modulations, is relevant to narrowing the black-white mortality risk differences. We aimed to synthesize epigenomic findings in HTN namely (a) angiotensin-converting enzyme 2 (ACE II) gene, (b) Toll-like receptor 2 (TLR2) gene, (c) interferon γ (IFN-γ) gene, and (d) Capping Actin Protein, Gelosin-Like (CAPG) gene, adducin 1(ADD1) gene, (e) Tissue inhibitor of metalloproteinase 3 (TIMP3), (f) mesoderm specific transcript (MEST) loci, (g) sodium channel epithelial 1 alpha subunit 2 (SCNN1B), (h) glucokinase (CKG) gene (i) angiotensin II receptor, type1 (AGTR1), and DNA methylation (mDNA). A systematic review and quantitative evidence synthesis (QES) was conducted using Google Scholar and PubMed with relevant search terms. Data were extracted from studies on: (a) Epigenomic modulations in HTN based on ACE II (b) TLR2, (c) IFN-γ gene, (d) CAPG, ADD1, TIMP3, MEST loci, and mDNA. The random-effect meta-analysis method was used for a pooled estimate of the common effect size, while z statistic and I^2 were used for the homogeneity of the common effect size and between studies on heterogeneity respectively. Of the 642 studies identified, five examined hypermethylation while seven studies assessed hypomethylation in association with HTN. The hypermethylation of ACE II, SCNN1B, CKG, IFN-γ gene, and miR-510 promoter were associated with hypertension, the common effect size (CES) = 6.0%, 95% CI, −0.002–11.26. In addition, the hypomethylation of TLR2, IFN-γ gene, ADD1, AGTR1, and GCK correlated with hypertension, the CES = 2.3%, 95% CI, −2.51–7.07. The aberrant epigenomic modulation of ACE II, TLR2, IFN-γ, AGTR1, and GCK correlated with essential HTN. Transforming the environments resulting from these epigenomic lesions will facilitate early intervention mapping in reducing HTN in the US population, especially among socially disadvantaged individuals, particularly racial/ethnic minorities.

DNA Methylation Trajectories During Pregnancy

There is emerging evidence on DNA methylation (DNAm) variability over time; however, little is known about dynamics of DNAm patterns during pregnancy. We performed an epigenome-wide longitudinal DNAm study of a well-characterized sample of young women from the Swedish Born into Life study, with repeated blood sampling before, during and after pregnancy (n = 21), using the Illumina Infinium MethylationEPIC array. We conducted a replication in the Isle of Wight third-generation birth cohort (n = 27), using the Infinium HumanMethylation450k BeadChip. We identified 196 CpG sites displaying intra-individual longitudinal change in DNAm with a false discovery rate (FDR) P < .05. Most of these (91%) showed a decrease in average methylation levels over the studied period. We observed several genes represented by ⩾3 differentially methylated CpGs: HOXB3, AVP, LOC100996291, and MicroRNA 10a. Of 36 CpGs available in the replication cohort, 17 were replicated, all but 2 with the same direction of association (replication P < .05). Biological pathway analysis demonstrated that FDR-significant CpGs belong to genes overrepresented in metabolism-related pathways, such as adipose tissue development, regulation of insulin receptor signaling, and mammary gland fat development. These results contribute to a better understanding of the biological mechanisms underlying important physiological alterations and adaptations for pregnancy and lactation.

Relevance of Multi-Omics Studies in Cardiovascular Diseases

Cardiovascular diseases are the leading cause of death around the world. Despite the larger number of genes and loci identified, the precise mechanisms by which these genes influence risk of cardiovascular disease is not well understood. Recent advances in the development and optimization of high-throughput technologies for the generation of “omics data” have provided a deeper understanding of the processes and dynamic interactions involved in human diseases. However, the integrative analysis of “omics” data is not straightforward and represents several logistic and computational challenges. In spite of these difficulties, several studies have successfully applied integrative genomics approaches for the investigation of novel mechanisms and plasma biomarkers involved in cardiovascular diseases. In this review, we summarized recent studies aimed to understand the molecular framework of these diseases using multi-omics data from mice and humans. We discuss examples of omics studies for cardiovascular diseases focused on the integration of genomics, epigenomics, transcriptomics, and proteomics. This review also describes current gaps in the study of complex diseases using systems genetics approaches as well as potential limitations and future directions of this emerging field.

Epigenome-wide methylation differences in a group of lean and obese women - A HUNT Study

Knowledge of epigenetically regulated biomarkers linked to obesity development is still scarce. Improving molecular understanding of the involved factors and pathways would improve obesity phenotype characterization and reveal potentially relevant targets for obesity intervention. The Illumina Infinium HumanMethylation450 BeadChip was used in a leucocyte epigenome-wide association study (EWAS) to quantify differential DNA methylation in 60 lean compared with 60 obese young women. Replication was done in monozygotic twins discordant for obesity. At adolescence and adulthood, the two weight groups differed significantly in obesity-related traits and metabolic risk factors. Differential hypomethylation was overrepresented in obese compared to lean women. In the adjusted model, the EWAS revealed 10 differentially methylated CpG sites linked to 8 gene loci – COX6A1P2/FGD2, SBNO2, TEX41, RPS6KA2, IGHE/IGHG1/IGHD, DMAP1, SOCS3, and SETBP1– and an enhancer locus at chromosome 2 (2p25.1). The sites linked to TEX41, IGHE/IGHG1/IGHD, DMAP1, and SETBP1 were novel findings, while COX6A1P/FGD2, SBNO2, RPS6KA2, and SOCS3 had been identified previously with concordant direction of effects. RPS6KA2, DMAP1, and SETBP1 were replicated in the BMI-discordant monozygotic twin cohort using the FDR of 5%.