Epigenetics replacing single gene based disease research!

Epigenetic pathology are the one of the biggest hot spots for genome scale studies of epigenetic diseases because of its ability to reveal more than the candidate gene approaches.For example, methylation changes can affect large genomic regions in colorectal cancer, and widespread methylation changes are even more striking outside of the usually examined CpG islands (i.e., in shores and gene bodies).
Stem cells, the focus for a wide range of both basic and applied research on disease, have shown promiscuous methylation differences from somatic cells on a genome-wide scale, notably including differences at non-CpG sites.  sites of differential methylation largely overlap, with strong statistical significance, across physiological states—the same sites appear, for example, in normal cells compared with cancer cells, in stem cells compared with differentiated cells and in comparisons of tissues derived from different germ layers. Thus, the language of epigenomic organization seems to be common for normal development and for disease, just as the language of anatomy is common for normal and abnormal physiology.

The influence of epigenetic control has definitely influenced how the disease based studies are being organized.Only  2% of cancer epigenetics are published genome scale studies , the rate of increase over the past five years of cancer epigenomic studies is more than double that of conventional gene-based analyses of cancer . A similar kind of trend is also picking up in other fields of noncancer human disease epigenetics, such as epigenetics of cardiovascular, immunological and neuropsychiatric disease. These differences are driven in part by the availability of new technology, of course, but also by the growing realization that variation in both DNA methylation and chromatin are widespread across the genome and may be organized into large genomic domains.
Another important factor driving such 'disease epigenomics' is the relatively limited yield to date of conventional single-nucleotide polymorphism (SNP)–based genetic analysis in explaining most common human diseases. As has been widely described in both scientific and lay publications, it was anticipated a decade ago that genetic analysis would be much more successful at attributing risk of disease to specific genetic markers. the actual 'genome anatomy' target for disease is probably much larger than scientists previously realized—perhaps involving more than half of the genome—and because understanding of the normal function of this genome anatomy requires epigenomics, it is possible that much of what appears to be negative genetic-association data could become meaningful in an epigenomic context . For example, most genome-wide association studies (GWAS) identify not genes, but nearby regions or intergenic deserts. Yet these same regions frequently harbor differentially methylated regions that discriminate tissue types or distinguish cancer from normal cells. They are also the canonical regions for lincRNAs that help establish chromatin structure and normal gene function. Furthermore, gene deserts may promote trans associations of chromosomes in epigenetic regulation. Another way in which disease-associated DNA sequence variants might affect disease risk is through their linkage to DNA sequences that regulate DNA methylation, chromatin modification or binding factors. Substantial association of SNPs with DNA methylation has already been found.
So Epigenetics  is all set to over take single gene based disease research.