The factors that contribute to the development of common diseases have been challenging to define. Epigenetic mechanisms may play a role and the field is hopeful that epigenome-wide association studies (EWAS) studies will gain new insights. However, EWAS studies face challenges that genome-wide association studies studies do not. First, the epigenome has a dizzying array of components involving different forms of methylated DNA, numerous histone modifications and various non-coding RNAs. Second, these components assemble in a highly cell-type specific manner. Finally, some elements of the epigenome change in response to disease, making it challenging to find epigenetic signatures with a causal role. Nonetheless, the first signs that EWAS studies have potential are upon us.
A recent study by Liu and colleagues undertook an EWAS study of rheumatoid arthritis (RA) to uncover DNA methylation changes that interact with genetic factors to mediate disease risk. The authors note that RA is an ideal test case for EWAS because the cell-types involved (leukocytes) are well defined and easily isolated. In addition, the disease state can be ascertained by measures of anti-citrullinated protein (CP) antibodies. The authors performed a genome-wide DNA methylation analysis of whole blood from 354 rheumatoid arthritis patients and 335 healthy controls for which genome-wide SNP and CP antibody data were also available. They first correct for cellular heterogeneity in their blood samples by effectively normalizing the data using available DNA methylation signatures for major blood cell types. Second, the authors use a clever series of conditional correlation analyses involving genotype, methylation and phenotype data to filter out differentially methylated positions (DMPs) that are not likely to be causally related to RA. Remarkably, this revealed significant associations between a set of SNPs and DMPs located in the MHC gene cluster, which has previously been linked to rheumatoid arthritis. In a final step, the authors used a causal inference test to define 9 DMPs that mediate the genetic risk for RA through interactions with 264 SNPs in the MHC region and one SNP-DMP pair outside of the MHC region.
This study not only reveals the importance of understanding the relationships between genetic and epigenetic factors in common diseases, but also establishes a clear methodology to overcome many of the issues inherent to EWAS studies.
Liu et al. Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis. Nature Biotechnology, published online January 2013