Medical genetics

The researches find that the Biomarkers of DNA methylation, which regulate gene expression, can be a predictor of breast cancer risk, according to a study published in Journal of the National Cancer Institute. Therefore Vanderbilt’s Jirong Long, Ph.D., associate professor of Medicine; Division of Epidemiology; and colleagues conducted a methylation-wide association (MeWAS) study of data from 228,951 women of European descent with the goal of identifying new genes and methylation markers associated with breast cancer risk.

Biomarkers of DNA methylation

They discovered 450 DNA methylation sites associated with breast cancer, including 45 sites located in novel chromosome regions that had not been previously reported for breast cancer. Because Integrative analyses of genetic DNA methylation and gene expression data found that 38 CpGs may affect breast cancer risk through regulating expression of 21 genes.

Gene expression is the process by which information from a gene is used in the synthesis of a functional gene product. These products are often proteins; but in non-protein coding genes such as rRNA genes or tRNA genes; the product is a functional RNA. Therefore Several steps in the gene expression process may be modulated; including the transcription; RNA splicing, translation, and post-translational modification of a protein.

Gene regulation gives the cell control over structure and function; and is the basis for cellular differentiation, morphogenesis and the versatility and adaptability of any organism. Gene regulation may also serve as a substrate for evolutionary change, since control of the timing, location; and amount of gene expression can have a profound effect on the functions (actions) of the gene in the organism.

Cellular differentiation

“This study used a novel approach to investigate DNA methylation in hundreds of thousands of participants;” Long said. In conducting the Me WAS study; Long and colleagues came up with a new methodology for identifying novel DNA methylation biomarkers that can be applied to other diseases.

They first built statistical models to predict DNA methylation levels via multiple genetic variants in a reference dataset; then validated the models in independent samples; and then applied the prediction models to a large genetic dataset to test the genetically-determined methylation level with disease risk.

“Our novel methodology overcomes limitations of traditional epidemiological studies and is more accurate and powerful than studies based on a single meQTL approach;” the researchers wrote. Therefore “This ground-breaking work is not only helpful for women from families with many cases of breast cancer; it will improve breast cancer risk prediction for all women; and pave the way for the development of epigenetic therapeutics for breast cancer.”

Epigenetic therapeutics

The study, published in Nature Communications, looks at epigenetic changes called DNA methylation, where methyl group chemicals modify DNA without changing its sequence. But DNA methylation can mimic genetic variation, predisposing a family to breast cancer.