East London genetic diversity and cell-type-specific DNA methylation

Code: BC-DTP_2026_69

Title: East London genetic diversity and cell-type-specific DNA methylation

Primary Supervisor: Tommy Kaplan

Email: tommy.kaplan@qmul.ac.uk

Institute: Barts Cancer Institute

Secondary Supervisor: Chris Bell

Email: c.bell@qmul.ac.uk

Institute: William Harvey Research Institute

Lay Summary:

Epigenetic regulation plays a central role in determining how genes are switched on or off in different conditions. One of the most important epigenetic marks is DNA methylation, which is highly stable and almost identical across all humans, regardless of ancestry. This ensures that every cell maintains its identity and function. However, a small fraction of methylation sites is influenced by nearby genetic variants, affecting gene activity and disease risk.

This project will investigate how genetic variants, common among East London British Bangladeshi and British Pakistani communities, may affect gene regulation through DNA methylation. We will use genetic data from the Genes & Health study, including tens of thousands of volunteers with linked NHS health records. Using a high-resolution atlas of cell-type-specific DNA methylation recently generated by our group, we will predict how particular genetic variants might alter methylation in specific cell types and tissues. These predictions will allow us to identify biological pathways that may be influenced by population-specific genetic variation.

By identifying which genetic variants affect DNA methylation, we will shed light on regulatory mechanisms that contribute to conditions that disproportionately affect British South Asian communities, such as diabetes and cardiovascular disease. The project uses advanced computational and machine learning methods to integrate genetic data with detailed epigenetic maps, and may help ensure that future genomic and epigenetic diagnostic tests and technologies work equitably across diverse populations.

Aims:

Aim 1: Evaluate the relevance of known sequence-dependent methylation loci in British South Asian populations.

Aim 2: Identify novel population-specific genetic variants that overlap methylation-sensitive regions.

Aim 3: Map predicted methylation-mediated effects to biological pathways and disease phenotypes.

Aim 4: Integrate predictions with health outcomes to generate mechanistic hypotheses for disease inequalities.