Abstract
The implication of DNA methylation in the pathogenesis of obesity is increasingly recognized as candidate gene and epigenome-wide association studies have shown DNA methylation differences with obesity-related traits. However, issues of genomic coverage, lack of statistical power, small effect sizes, confounding by differences in cell type proportions, wrong annotation of methylated regions, and difficulty to disentangle causal relationships have called for advanced bioinformatic methods for DNA methylome analysis of obesity. With international consortia, it is now possible to annotate the epigenome with better accuracy; with Mendelian randomization, it is now possible to infer causal relationships between DNA methylation differences and obesity-related traits; with advanced algorithms, it is now possible to account for differences in cell type proportions with or without reference epigenomes. This chapter gives some insights into these recent developments, and methods are constantly improving to better address the issues associated with DNA methylome analysis of obesity.
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