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

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Abstract

Objective—

The objectives of this study were to decipher whether age-independent cardiovascular risk is associated with DNA methylation at 5′-cytosine-phosphate-guanine-3′ (CpG) level and to determine whether these differential methylation signatures are associated with the incidence of cardiovascular events.

Approach and Results—

We designed a 2-stage, cross-sectional, epigenome-wide association study. Age-independent cardiovascular risk calculation was based on vascular age and on the residuals of the relationship between age and cardiovascular risk. Blood DNA methylomes from 2 independent populations were profiled using the Infinium HumanMethylation450 BeadChip. The discovery stage of these studies was performed in the REGICOR cohort (REgistre GIroní del COR; n=645). Next, we validated the initial findings in the Framingham Offspring Study (n=2542). Eight CpGs located in 4 genes (AHRR, CPT1A, PPIF, and SBNO2) and 3 intergenic regions showed differential methylation in association with age-independent cardiovascular risk (P≤1.17×10−7). These CpGs explained 12.01% to 15.16% of the variability of age-independent cardiovascular risk in REGICOR and 7.51% to 8.53% in Framingham Offspring Study. Four of them were only related to smoking, 3 were related to smoking and body mass index, and 1 to diabetes mellitus, triglycerides levels, and body mass index (P≤7.81×10−4). In addition, we developed methylation risk scores based on these CpGs and observed an association between these scores and cardiovascular disease incidence (hazard ratio=1.32; 95% confidence interval: 1.16–1.51).

Conclusions—

Age-independent cardiovascular risk was related to different DNA methylation profiles, with 8 CpGs showing differential methylation patterns. Most of these CpGs were associated with smoking, and 3 of them were also related to body mass index. Risk scores based on these differential methylation patterns were associated with cardiovascular events and could be useful predictive indices.

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