DNA Methylation Biomarkers Of Myocardial Infarction And Cardiovascular Disease
Alba Fernández‐SanlésiD, Sergi Sayols-BaixerasiD, Isaac Subirana, Mariano Sentı́iD, Sílvia Pérez-FernándeziD, Manuel de Castro Moura, Manel EstelleriD, Jaume MarrugatiD, Roberto ElosúaiD
Abstract
ObjectiveTo assess the association between DNA methylation and acute myocardial infarction, the predictive added value of the identified methylation marks, and the causality of those associations. Approach and ResultsWe conducted a case-control, two-stage, epigenome-wide association study on acute myocardial infarction (ndiscovery=391, nvalidation=204). DNA methylation was assessed using the Infinium MethylationEPIC BeadChip (over 850,000 CpGs). DNA methylation was the exposure variable and myocardial infarction the outcome of interest. After a fixed-effects meta-analysis, 34 CpGs fulfilled Bonferroni significance. These findings were also analysed in two independent cohort studies (n[~]1,800 and n[~]2,500) with incident coronary (CHD) and cardiovascular disease (CVD). The Infinium HumanMethylation450 BeadChip was used in these two studies (over 480,000 CpGs) and only 12 of the 34 CpGs were available in those samples. Finally, we validated four of them in association with incident CHD: AHRR-mapping cg05575921, PTCD2-mapping cg25769469, intergenic cg21566642 and MPO-mapping cg04988978. The four CpGs were also associated with classical cardiovascular risk factors. A methylation risk score based on those CpGs did not improve the predictive capacity of the Framingham risk function. To assess the causal effects of those CpGs we performed Mendelian randomization analysis but only one metQTL could be identified and the results were not conclusive. ConclusionsWe have identified 34 CpGs related to acute myocardial infarction. These loci highlight the relevance of smoking, lipid metabolism, and inflammation in the biological mechanisms related to myocardial infarction. Four were additionally associated with incident CHD and CVD but did not provide additional predictive information.
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