DNA methylation patterns in (sub)clinical atherosclerosis and their relationship to cardiovascular risk factors

Markus Ingold (Mainz)1, V. ten Cate (Mainz)2, C. Müller (Mainz)1, M. Krolevets (Mainz)3, E. Yapici (Mainz)2, S. Rapp (Mainz)1, T. Koeck (Mainz)1, P. S. Wild (Mainz)1

1Universitätsmedizin der Johannes Gutenberg-Universität Mainz Präventive Kardiologie und Medizinische Prävention Mainz, Deutschland; 2Universitätsmedizin der Johannes Gutenberg-Universität Mainz Preventive Cardiology and Preventive Medicine Mainz, Deutschland; 3Universitätsmedizin der Johannes Gutenberg-Universität Mainz Centrum für Thrombose und Hämostase Mainz, Deutschland


Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide and continues to rise in the face of globally increasing life expectancy. Epigenetic modifications, particularly DNA methylation at CpG sites, have been linked to CVD. The aim of this project is to identify differentially methylated sites related to subtypes of atherosclerosis (AS) and cardiovascular risk factors (CVRF) to assess epigenetic mechanisms of CVD development and progression due to smoking and other risk factors. 
CpG site methylation was assessed in whole blood from study participants (n=3,688) from the population-based prospective Gutenberg Health Study and the prospective MyoVasc study using the MethylationEPIC array (Illumina, USA). Carotid, coronary and peripheral AS was assessed via prior diagnoses, ultrasonography-assessed carotid plaque presence and ankle-brachial index, respectively. Additionally, laboratory biomarkers representing CVRFs were available. Epigenome-wide association studies (EWAS) adjusted for age, sex, study cohort and inferred blood cell composition were performed to explore the relationship between DNA methylation patterns and these traits. The false discovery rate (FDR) was controlled at 5% by the Benjamini-Hochberg procedure.
Epigenetic risk scores for atherosclerosis subtypes were created using elastic net-regularized logistic regression models. These scores were compared to established risk scores, as well as epigenetic aging clocks, in terms of their prognostic ability for incident cardiovascular endpoints, including myocardial infarction, cardiac death, stroke, and the composite endpoint MACCE (major adverse cardiac and cerebrovascular events), using multivariable Cox regression models.
EWAS on carotid, coronary and peripheral AS yielded 1,687, 3,131 and 5,852 FDR-significantly differentially methylated CpG sites, many of which novel. Methylation scores derived from these markers using elastic net regularization proved significantly predictive (all p<0.0001) for all-cause death and 3-point MACCE. Loci with strong peaks included the intergenic region around chr2:233284934 as well as the genes AHRR, PRSS23, F2RL3 and, in coronary AS, ABCG1. Genes to which CpGs mapped were significantly enriched in relevant KEGG or Reactome pathways such as lipid and atherosclerosis, insulin signalling, AGE-RAGE signalling and platelet activation, signalling and aggregation. The majority of identified CpGs overlapped with 42,437, 43,804, 30,554, 23,683 and 1,021 FDR-significant markers respectively detected in smoking, HbA1c, ApoA, BMI and LDL/HDL ratio, suggesting that CVRFs may account for most of the differential methylation at the AS-linked sites of interest.
This study has provided valuable insights into the pathomechanisms involved in the epigenetic landscape associated with AS and its risk factors. By investigating the CpG sites, genes, and pathways that overlap between these markers, the epigenetic pathomechanisms involved in CVD development and progression will be elucidated. The creation of epigenetic risk scores will provide a potential tool for personalized risk assessment in CVD, and comparisons to epigenetic clocks will examine the role of premature aging. These epigenome-wide investigations will be further expanded and integrated with further –omics levels as part of the curATime cluster (www.curatime.org). 
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