While researchers commonly compare the genomes of healthy and ill populations, they seldom compare epigenomes in the same way. As a result, researchers have had difficulty pinpointing genetic predispositions for disease. Many genetic diseases have their origins in either the genome or the epigenome, which consists of potentially reversible chemical changes to DNA.
Now, thanks to a study conducted by researchers at Johns Hopkins University, it appears that there may be ways to correlate information about genetic variants and epigenetic patterns. These researchers have identified epigenetic patterns they call GeMes. They define GeMes as “potentially noncontiguous methylation clusters under the control of one or more methylation quantitative trait loci.” Or, more simply, GeMes may be thought of as methylation blocks controlled by genes.
GeMes, the Johns Hopkins team discovered, overlap with haplotypes, long genetic blocks, but are much shorter. This finding led the researchers to suspect that the protein-coding genes within a particular block that are turned on or off by epigenetic tags must be at the root of the disease associated with a particular genetic variant found elsewhere in the block.
The researchers detailed their work in an article entitled “GeMes, Clusters of DNA Methylation under Genetic Control, Can Inform Genetic and Epigenetic Analysis of Disease.” This article, which appeared March 20 in the American Journal of Human Genetics, contains insights that could help disease trackers “read” correlations. That is, these correlations could serve as clues to the causes of (and possible treatments for) complex genetic conditions, including many cancers and metabolic disorders. Or, as the authors wrote, correlated methylation structures could have “implications for both biological functions of DNA methylation and for the design, analysis, and interpretation of epigenome-wide association studies.”
The Johns Hopkins team analyzed genetic data from hundreds of healthy participants in three studies to first figure out what a normal epigenetic pattern looks like. (The researchers zoomed in on one type of epigenetic change, the attachment of a chemical tag called a methyl group to a particular site on DNA. Known as methylation, these tags affect whether genes produce any protein, and if so, how much.) Then the team looked for the relationship between the resulting epigenetic data and genetic data.
The authors explained that clustering of correlated DNA methylation at CpGs was similar to that of linkage-disequilibrium (LD) correlation in genetic SNP variation but for much shorter distances. “A set of correlated methylated CpGs related to a single SNP-based LD block was not always physically contiguous,” the authors added. “Segments of uncorrelated methylation as long as 300 kb could be interspersed in the cluster.” These sets of correlated CpGs are the so-called GeMes.
“By showing the connections between genetic variants and epigenetic information, we're providing epidemiologists with a road map,” said Andrew Feinberg, M.D., M.P.H., the director of the Center for Epigenetics in the Institute for Basic Biomedical Sciences at the Johns Hopkins University School of Medicine. “Epigenetic tags show how disease-causing genetic variants might affect distant genes that in turn contribute to the disease.”
“Previously, people could not pinpoint the variants within a long stretch of DNA that were responsible for the disease,” noted Yun Liu, Ph.D., a postdoctoral fellow in Feinberg's laboratory. “But now, by detecting just one variation in DNA methylation, or one GeMe, a researcher will know that one or more of the few hundred methylated nucleotides are possibly causing the disease.”
“These corresponding genetic and epigenetic maps provide new insights about the architecture of the genome and its regulatory epigenetic marks. This can inform the integration of multiple types of data in future large-scale epidemiologic studies,” added Dani Fallin, Ph.D., professor and chair of the Department of Mental Health at the Bloomberg School of Public Health and director of the Wendy Klag Center for Autism and Developmental Disabilities.