Variation in Genotype and DNA Methylation Patterns Based on Alcohol Use and CVD in the Korean Genome and Epidemiology Study (KoGES)

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Abstract

Alcohol consumption can increase the risk of chronic diseases, such as myocardial infarction, coronary artery disease, hyperlipidemia, and hypertension. We aimed to assess the association between genotype, DNA methylation patterns, alcohol consumption, and chronic diseases in Korean population. We analyzed 8840 subjects for genotypes and 446 for DNA methylation among the 9351 subjects from the Korean Genome and Epidemiology Study (KoGES). We further divided both groups into two sub-groups according to the presence/absence of chronic diseases. We selected genes whose methylation varied significantly with alcohol consumption, and visualized genotype and DNA methylation patterns specific to each group. Genome-wide association study (GWAS) revealed single nucleotide polymorphisms (SNPs) rs2074356 and rs11066280 in HECT domain E3 ubiquitin protein ligase 4 (HECTD4) to be significantly associated with alcohol consumption in both the presence. The rs12229654 genotype also displayed significantly different patterns with alcohol consumption. Furthermore, we retrieved differentially methylated regions (DMRs) from four groups based on sex and chronic diseases and compared them by drinking status. In genotype analysis, cardiovascular diseases (CVDs) showed a higher proportion in drinker than in non-drinker, but not in DMR analysis. Additionally, we analyzed the enriched Gene Ontology terms and Kyoto Gene and Genome Encyclopedia (KEGG) pathways and visualized the network, heatmap, and upset plot. We show that the pattern of DNA methylation associated with CVD is strongly influenced by alcoholism. Overall, this study identified genetic and epigenetic variants influenced by alcohol consumption and chronic diseases.

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Jung, M., Ahn, Y. S., Chang, S. J., Kim, C. B., Jeong, K. S., Koh, S. B., & Gim, J. A. (2022). Variation in Genotype and DNA Methylation Patterns Based on Alcohol Use and CVD in the Korean Genome and Epidemiology Study (KoGES). Genes, 13(2). https://doi.org/10.3390/genes13020172

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