Gene-specific DNA methylation profiles and LINE-1 hypomethylation are associated with myocardial infarction risk

Abstract

BACKGROUND: DNA methylation profiles are responsive to environmental stimuli and metabolic shifts. This makes DNA methylation a potential biomarker of environmental-related and lifestyle-driven diseases of adulthood. Therefore, we investigated if white blood cells' (WBCs) DNA methylation profiles are associated with myocardial infarction (MI) occurrence. Whole-genome DNA methylation was investigated by microarray analysis in 292 MI cases and 292 matched controls from the large prospective Italian European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (EPICOR study). Significant signals (false discovery rate (FDR) adjusted P < 0.05) were replicated by mass spectrometry in 317 MI cases and 262 controls from the Dutch EPIC cohort (EPIC-NL). Long interspersed nuclear element-1 (LINE-1) methylation profiles were also evaluated in both groups. RESULTS: A differentially methylated region (DMR) within the zinc finger and BTB domain-containing protein 12 (ZBTB12) gene body and LINE-1 hypomethylation were identified in EPICOR MI cases and replicated in the EPIC-NL sample (ZBTB12-DMR meta-analysis: effect size ± se = -0.016 ± 0.003, 95 % CI = -0.021;-0.011, P = 7.54 × 10(-10); LINE-1 methylation meta-analysis: effect size ± se = -0.161 ± 0.040, 95 % CI = -0.239;-0.082, P = 6.01 × 10(-5)). Moreover, cases with shorter time to disease had more pronounced ZBTB12-DMR hypomethylation (meta-analysis, men: effect size ± se = -0.0059 ± 0.0017, P TREND = 5.0 × 10(-4); women: effect size ± se = -0.0053 ± 0.0019, P TREND = 6.5 × 10(-3)) and LINE-1 hypomethylation (meta-analysis, men: effect size ± se = -0.0010 ± 0.0003, P TREND = 1.6 × 10(-3); women: effect size ± se = -0.0008 ± 0.0004, P TREND = 0.026) than MI cases with longer time to disease. In the EPIC-NL replication panel, DNA methylation profiles improved case-control discrimination and reclassification when compared with traditional MI risk factors only (net reclassification improvement (95 % CI) between 0.23 (0.02-0.43), P = 0.034, and 0.89 (0.64-1.14), P < 1 × 10(-5)). CONCLUSIONS: Our data suggest that specific methylation profiles can be detected in WBCs, in a preclinical condition, several years before the occurrence of MI, providing an independent signature of cardiovascular risk. We showed that prediction accuracy can be improved when DNA methylation is taken into account together with traditional MI risk factors, although further confirmation on a larger sample is warranted. Our findings support the potential use of DNA methylation patterns in peripheral blood white cells as promising early biomarkers of MI.