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