The ultimate aim of EWAS, like GWAS, is to provide a better understanding of disease aetiology, and to lead to the development of novel therapeutics and diagnostics. Typical follow-up experiments to determine the etiological role of disease-associated epigenetic variation could include correlation with other epigenetic modifications and collectively how they impact on gene expression. This could be achieved using ChIP-seq experiments, either for the many histone modifications known to correlate with DNAm68
or for transcription factors whose binding may be modulated – positively or negatively – by methylation at their target sites69
. If a large effect size can be determined for a single site, then one could validate the link to the disease-associated phenotype by modulating the expression of the gene in question either in in vitro
systems or model organism studies. However, a more likely scenario is of many disease-associated epigenetic variants each conferring only a small disease risk, as is suggested by the few small-scale EWAS to date22,23,40-42
. In this case, it may be more fruitful to use approaches that integrate both computational and experimental methodologies to look at perturbations of entire transcriptional networks. The issue of reverse causation is also important in post-EWAS experiments, both in terms of which variants to follow-up, and the experimental approaches.
Even if the etiological role of any identified epigenetic variant proves elusive, it may still be possible to use them as predictive biomarkers. In this regard, the combination of chemical stability and ontogenetic plasticity make DNAm ideally suited as a biomarker. Translating any molecular marker including DNAm differences into clinically informative biomarkers has turned out to be more challenging70
than had been expected but progress has been made. Following earlier setbacks, a multi centre study identified, validated and replicated hypermethylation at SEPT9 as a blood-based DNAm biomarker for colorectal cancer in 200871
, leading to a commercial test in early 201072
. But enthusiasm is tempered with caution, as illustrated by the problems encountered by the cancer community in identifying biomarkers that predict which patients would benefit from a particular therapy70
. The main problem has been the inability to select patients with a molecularly well-defined disease phenotypedue in large part to the heterogeneity of cancer tissues. Molecular heterogeneity is also an issue, though expected to be less important, for the common diseases that are being targeted by the first wave of EWAS.
Based on this experience, a systematic approach such as the recently launched OncoTrack project (see under Links) is needed to advance the field. Two bodies in particular - the Biomarkers Consortium and the AACR-FDA-NCI Cancer Biomarkers Collaborative - have recently issued a comprehensive report on the current state of affairs and future directions73
. The response of the community has been positive with calls like ‘Bring on the biomarkers74
” and pledging to replace the patched framework of fragmented research by a co-ordinated ‘big-science’ approach (such as OncoTrack) which has proved successful for efforts like the human and cancer genome projects. Based on this and other efforts, we can be cautiously optimistic that similar progress will also be made for epigenetic biomarkers.