Different molecular layers often have complementary roles to jointly perform a certain biological function . Population-based studies adopted the multiomics approach by integrating these molecular layers into their studies. Whereas this approach has been successfully used for available transcriptome, metabolome, or genetic data, studies are sparse that systematically investigate the interaction of epigenetic mechanisms such as regulatory RNAs or histone modifications .
The variance of lipid levels explained by the currently known genetic variants is modest. All lipid-associated single-nucleotide polymorphisms (SNPs) together explain 12% or less of the variation in plasma lipid traits , although the estimated heritable variance of lipids is reported to be at least 50% . This missing heritability may be partly explained by epigenetic processes such as DNA methylation . SNP allele frequencies are known to differ among populations with varying geographic ancestries, suggesting that ethnic differences in DNA methylation could be due to differences in population-specific alleles that shape CpG and global methylation levels. Regulation of gene expression via DNA methylation may explain an additional component of interindividual variation in lipid levels beyond genetic sequence variants. Linking DNA methylation data with gene expression is a promising avenue to see potential downstream effects in lipid metabolism.
Epigenetics continues to be a promising area of research in lipid-related diseases. Current scientific knowledge does not completely explain the molecular mechanisms behind lipid metabolism and lipid-related diseases. Epigenetic modifications, such as DNA methylation, might form an additional path to understanding the mechanisms of lipid-related diseases. However, many challenges regarding the design, conduct, and interpretation of EWAS persist. The main challenges include accounting for variation in cellular heterogeneity, potential confounding effects, and resolving whether blood samples do indeed mirror relevant targeted tissues. Therefore, longitudinal cohort studies and larger sample sizes are key points for further investigations. Moreover, in addition to the development of cost-effective sequencing applications, a new array has been developed covering more than 850 000 methylation sites across the genome.
Another important task is to assess, and functionally validate, causality of the reported associations, and, if we propose that a change in DNA methylation status is causal for a lipid phenotype, to assess when these changes occur . For example, it has been indicated that for a growing fetus, malnutrition can have harmful effects on prenatal programming and contribute to the development of diseases later in life [63,64]. Perhaps, the greatest challenge is to understand the functional consequences of the confirmed loci. Biological insights can then be translated to clinical benefits, including reliable biomarkers and effective strategies for disease prevention. Functional follow-up studies of confirmed loci will help unravel the precise molecular mechanisms at specific CpG sites, including the identification of methylation-specific binding proteins and characterization of their mode of action.
Papers of particular interest, published within the annual period of review, have been highlighted as:
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