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Here we examine the association between DNA methylation in circulating leukocytes and blood lipids in a multi-ethnic sample of 16,265 subjects. We identify 148, 35, and 4 novel associations among Europeans, African Americans, and Hispanics, respectively, and an additional 186 novel associations through a trans-ethnic meta-analysis. We observe a high concordance in the direction of effects across racial/ethnic groups, a high correlation of effect sizes between high-density lipoprotein and triglycerides, a modest overlap of associations with epigenome-wide association studies of other cardio-metabolic traits, and a largely non-overlap with lipid loci identified to date through genome-wide association studies. Thirty CpGs reached significance in at least 2 racial/ethnic groups including 7 that showed association with the expression of an annotated gene. CpGs annotated to CPT1A showed evidence of being influenced by triglycerides levels. DNA methylation levels of circulating leukocytes show robust and consistent association with blood lipid levels across multiple racial/ethnic groups., Abnormal blood lipid levels are important risk factors for cardiovascular and other various diseases. Here the authors conduct a large-scale multi-ethnic epigenome-wide association study combined with epigenetic (cis-QTL and eQTM) data, and identify CpG-lipid traits associations that are specific to or common across racial/ethnic groups.

Additional file 4: Supplemental Results and Methods. In the Supplemental Results section a detailed comparison of the results obtained across cohorts can be found. In the Supplemental Methods section a detailed description of data processing for each of the population based cohorts can be found, as well as detailed specification on statistical and multi-omics analyses.

Additional file 18: Figure S4. ROC curves for significant CpG-outcome associations: Presented are the receiver operating characteristic (ROC) curves for each outcome-CpG pair for which there exists a statistically significant association for either M1 or M2 (Table 3). The red line is the ROC curve for the model without the CpG, and the green line is the model with the CpG. Presented are also the areas under the curve (AUC) for the respective ROCs, and a p value for the null hypothesis that the addition of the CpG to the model has no effect on the predictive performance of the model. The p value was determined using the R package pROC [87], command roc.test, method “bootstrap”. The analysis was run in the KORA F4 dataset, and, to ensure comparability of the results, the ROC curves were generated using individuals with no missing values in any of the outcomes or covariates, and the methylation data were mean imputed.

Additional file 7: Figure S2. Explained variance of the first 30 principal components of the metabolite measure principal component analysis, performed in the discovery cohort KORA F4.

Additional file 8: Figure S3. Presented are the first 8 principal components (PCs) of the metabolite data in KORA F4 (after scaling of the individual metabolites) coloured according to sex, intake of lipid-lowering drugs, and smoking habits. “Expl. Var” is the variance explained by the given PC. Some clustering is observed for sex within the first 2 PCs, but no other obvious clusters emerge for any of the other phenotypes or PCs.

Here we examine the association between DNA methylation in circulating leukocytes and blood lipids in a multi-ethnic sample of 16,265 subjects. We identify 148, 35, and 4 novel associations among Europeans, African Americans, and Hispanics, respectively, and an additional 186 novel associations through a trans-ethnic meta-analysis. We observe a high concordance in the direction of effects across racial/ethnic groups, a high correlation of effect sizes between high-density lipoprotein and triglycerides, a modest overlap of associations with epigenome-wide association studies of other cardio-metabolic traits, and a largely non-overlap with lipid loci identified to date through genome-wide association studies. Thirty CpGs reached significance in at least 2 racial/ethnic groups including 7 that showed association with the expression of an annotated gene. CpGs annotated to CPT1A showed evidence of being influenced by triglycerides levels. DNA methylation levels of circulating leukocytes show robust and consistent association with blood lipid levels across multiple racial/ethnic groups.

This work investigates the association between genome-wide DNA methylation patterns and human blood lipid levels (HDL-C, LDL-C, triglycerides, total cholesterol) as well as lipoprotein subfractions by carrying out epigenome-wide association studies (EWAS). The results reveal associations between lipids and methylation of CpG sites located in genes which are involved in lipid, fatty acid and amino acid metabolism. Moreover, functional analyses of lipid-associated CpG sites detected methylation-dependent gene regulation. Diese Arbeit untersucht den Zusammenhang zwischen genomweiten DNA-Methylierungsmustern und humanen Blutlipid-Spiegeln (HDL-C, LDL-C, Triglyzeride, Gesamtcholesterol) wie auch Lipoprotein Subfraktionen mittels epigenomweiter Assoziationsstudien (EWAS). Die Ergebnisse zeigen Assoziationen zwischen Lipiden und Methylierung von CpG sites die in Genen lokalisiert sind, die im Lipid-, Fettsäure- und Aminosäure Metabolismus beteiligt sind. Funktionelle Analysen von Lipid-assoziierten CpG sites zeigten zudem methylierungsabhängige Genregulation.

Boxplots of the methylation values for the CS-CS individuals (current smokers at both baseline and follow-up) and the NS-NS individuals (never smokers at both baseline and follow-up). Figure S4a shows the technically adjusted beta values and Figure S4b shows the methylation beta values after residualization to account for confounding (see Statistical Methods). (PDF 23 kb)

Background: Most research into myocardial infarctions (MIs) have focused on preventative efforts. For survivors, the occurrence of an MI represents a major clinical event that can have long-lasting consequences. There has been little to no research into the molecular changes that can occur as a result of an incident MI. Here, we use three cohorts to identify epigenetic changes that are indicative of an incident MI and their association with gene expression and metabolomics. Results: Using paired samples from the KORA cohort, we screened for DNA methylation loci (CpGs) whose change in methylation is potentially indicative of the occurrence of an incident MI between the baseline and follow-up exams. We used paired samples from the NAS cohort to identify 11 CpGs which were predictive in an independent cohort. After removing two CpGs associated with medication usage, we were left with an “epigenetic fingerprint” of MI composed of nine CpGs. We tested this fingerprint in the InCHIANTI cohort where it moderately discriminated incident MI occurrence (AUC = 0.61, P = 6.5 × 10−3). Returning to KORA, we associated the epigenetic fingerprint loci with cis-gene expression and integrated it into a gene expression-metabolomic network, which revealed links between the epigenetic fingerprint CpGs and branched chain amino acid (BCAA) metabolism. Conclusions: There are significant changes in DNA methylation after an incident MI. Nine of these CpGs show consistent changes in multiple cohorts, significantly discriminate MI in independent cohorts, and were independent of medication usage. Integration with gene expression and metabolomics data indicates a link between MI-associated epigenetic changes and BCAA metabolism.