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

Abstract

Background Epigenome-wide association studies using DNA methylation have the potential to uncover novel biomarkers and mechanisms of cardiovascular disease (CVD) risk. However, the direction of causation for these associations is not always clear, and investigations to-date have generally failed to replicate at the level of individual loci. Here, we undertook module-and region-based DNA methylation analyses of incident CVD in the Women's Health Initiative (WHI) and Framingham Heart Study Offspring Cohort (FHS) in order to find more robust epigenetic biomarkers for cardiovascular risk. Methods and FindingsWe applied weighted gene correlation network analysis (WGCNA) and the Comb-p algorithm to find methylation modules and regions associated with incident CVD in the WHI dataset. We discovered two modules whose activation correlated with CVD risk and replicated across cohorts. One of these modules was enriched for development-related processes and overlaps strongly with epigenetic aging sites. For the other, we showed preliminary evidence for monocyte-specific effects and statistical links to cumulative exposure to traditional cardiovascular risk factors. Additionally, we found three regions (associated with the genes SLC9A1, SLC1A5, and TNRC6C) whose methylation associates with CVD risk. ConclusionsIn sum, we present several epigenetic associations with incident CVD that reveal potential monocyte biology-related mechanisms for CVD risk as well as a novel link between DNA methylation and cumulative cardiovascular risk factor exposure.

Association of cardiovascular health and epigenetic age acceleration

“…Furthermore, it is difficult to assess causality between DNA methylation age acceleration and outcome. As such, additional methods to establish causal relationships have been utilized to explore the causality [15,16].…”

“…Inclusion and exclusion criteria for participation in the WHI study have been described [17]. From the overall WHI cohort, a stratified, racially/ethnically diverse sample of 2200 WHI clinical trial participants with available stored serum were selected for DNA methylation analysis at either the screening visit or annual visits [15]. A description of the clinical trials has been published [17].…”

DNA Methylation Biomarkers in Aging and Age-Related Diseases

“…Nakatochi et al (2017) also performed an EWAS analyses on blood DNA of patients suffering from MI which revealed three differentially methylated CpG sites in SGK1, SMARC4, and ZFHX3. A large EWAS study on the Women's Health Initiative (discovery set) and Framingham Heart Study (FHS) -(replication set) identified three DMRs in SLC9A1, SLC1A5, and TNRC6C linked to CVD incidence (Westerman et al, 2018). The authors also performed a module based epigenetic analysis, which revealed three modules associated with CVD and its risk factors out of which two had strong concordance in both cohorts (Westerman et al, 2018).…”

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

“…Hypomethylation of a specific fragment of CGI-associated HLA-G gene positively correlated with coronary calcium score and was predictive for disease severity suggesting that methylation might not only have a critical role in disease severity but also a role as noninvasive biomarker(s) improving the prognostic value of CCTA [ 116 ]. The WGCNA and Comb-p algorithms have been applied to the identification of blood-based differentially methylated regions (DMRs) and disease modules associated with incident CHD events in two independent cohorts (discovery set: 2129 women, replication set: 2726 subjects) [ 137 ]. This study has identified two modules highly enriched for development and immune-related processes.…”

“…In addition, a multivariate analysis has revealed a positive correlation with BMI, highly sensitive C reactive protein (hsCRP), and TG [ 137 ]. Three DMRs annotated to the sodium/hydrogen exchanger 1 (SLC9A1), solute carrier family 1 neutral amino acid transporter member 5 (SLC1A5), and trinucleotide repeat containing adaptor 6C (TNRC6C) genes significantly replicated across the two cohorts, providing possible useful predictive biomarkers [ 137 ]. However, the possible cause–effect relationship between methylation changes in these genes and CV risk needs to be determined.…”