How disease-related genetic variation impacts on the epigenome and, thereby, leads to pathological functional changes in disease-relevant cell-types. This, for example, has included defining obligatory or facilitative allelic DNA methylome variation within disease-associated loci in the human genome.

The robust biomarker ability of DNA methylation to capture and quantitate both internal and external chronic disease-related exposures. We are investigating their predictive power in combination with ageing- and phenotype-related DNA methylation ‘clocks’ (constructed with ML methodology) and genetic risk scores. The aim is to determine the potential clinical utility of these biomarkers, with the analysis of longitudinal datasets taking advantage of the long-term stability of DNA modifications.

This research into metabolic disorders, type 2 diabetes and cardiovascular and other ageing-related diseases encompasses the broad themes of epigenomics; functional genomics; computational medicine; statistical genomics, bioinformatics, and genomic medicine.