A Review published in GenomeBiology discusses the motivations, methods, and applications of DNA methylation-based trait prediction, with a focus on common diseases.
] method uses a linear mixed model in a Bayesian framework to model any epigenetic genetic architecture and genetic architecture simultaneously in discovery samples that have both GWAS and MWAS data. BayesRR was applied to BMI and smoking behavior measured in 9,488 individuals in Generation Scotland to give estimates of genetic and epigenetic architecture from the same traits [
]. Their statistics were all provided with 95% confidence intervals, here, for simplicity, we report the rounded point estimates ). For smoking behavior defined as the number of pack-years, they reported that 46% of the phenotypic variance was captured by methylation probes and 6% by genome-wide SNPs =16%. For BMI, the number of contributing probes was higher, and the effect size attributed to each was smaller.
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