Abstract Background While height is a highly heritable trait with strong polygenic prediction, previous studies have postulated that minimal variation of its individual differences can be captured by DNA methylation (DNAm). We investigated the role of blood-based genome-wide DNAm in capturing the variance in adult height in a large population-based cohort of 7,654 unrelated individuals from Generation Scotland using DNAm profiled on the Illumina EPIC array. The posterior DNAm probe effects were used to construct a DNAm profile score (Methylation Profile Score—MPS) which was evaluated in three independent cohorts. Results Genome-wide DNAm captures 25.0% (95% credible interval (CrI) 17.2–31.9) of the phenotypic variation in height when applying Bayesian penalised regression using BayesR + conditional on genetic effects. The total variation captured jointly by DNAm and genetic effects (80.3%, 95% CrI 70.1–87.2) is larger than the marginal estimate based on genetic effects only (56.3%, 95% CrI 45.8–66.8). Out-of-sample prediction shows that the MPS is weakly correlated with measured height (Pearson correlation ranging from 0.14–0.26), as well as being associated with several health and lifestyle factors in the LBC1936 that are established correlates of height. Conclusion With the advent of larger sample sizes in epigenomics anticipated to improve the power to detect associations between DNAm and complex traits, we urge caution when making assumptions around “null traits” based solely on methylome-wide association study results and encourage the use of whole-genome methods to assess the proportion of variation in a trait that may be captured by DNAm.
Hatton et al. (Tue,) studied this question.