Harnessing DNA methylation variation between populations to understand disease discordance across ancestries

DNA methylation (DNAm) is an epigenetic mechanism that plays a central role in gene regulation. It helps to define how cells respond to genetic and environmental signals and, ultimately, contributes to whole system health and disease status.

Levels of DNAm differ from one person to another. However, it is unclear how much of the variation in DNAm levels is caused by genetic or environmental factors and if such effects also relate to human phenotypes. Understanding the relationships between DNAm, genetics and environment is essential for both understanding pathways of health and disease and disease consequences.

Prior research has been limited to populations of European ancestry, restricting understanding of DNAm variation to limited contexts. This is a crucial knowledge gap because there are known genetic and environmental differences in drug response and disease risk factors across population groups worldwide which may be attributable to DNAm variation.

Evaluating DNAm variation in diverse population groups allows comparison across varying genetic and environmental exposure profiles. Identification of disease pathways common to all populations will represent mechanisms of health and disease that are common across all humans. This allows identification of drug targets that will be effective in any population group.

Identification of disease pathways restricted to specific genetic and/or environmental exposure profile will reflect adaptation to environmental and genetic context. This will allow identification of molecular mechanisms that underpin the disease discordance that we observe across global populations and highlight opportunities for targeted treatments.

Our first project aim is to map genetic and environmental determinants of human DNAm variation to understand mechanisms of DNAm variability. We will generate a catalog of genetic associations with DNAm across populations worldwide. This catalog will be used to assess which of the identified genetic associations with DNAm are also associated with human complex traits. This is important because the findings can inform the functional role of phenotype-associated genetic variation, and ultimately - our understanding of the mechanisms underlying human phenotype variation.

The second aim of the project is to understand mechanisms of disease and disease discordance observed between population groups for childhood and cardiometabolic disease related phenotypes.

This project focusses on childhood and cardiometabolic disease for which there is substantial disease discordance and health disparity across populations. For example, diabetes risk is substantially higher in individuals of South Asian origin even after accounting for known genetic and environmental risk factors. Identification of DNAm variation associated with type 2 diabetes that is context specific will contribute to explaining excess type 2 diabetes risk in the South Asian population group. In doing so, Identification of disease pathways restricted to specific genetic and/or environmental exposure profiles brings the opportunity to target treatment or intervention where it is effective.

This research builds a global partnership of teams to bring together genetic and epigenetic data collected from individuals worldwide. A key aspect of this proposal is building equitable partnerships between these teams. This is essential in order to build capacity for research in genetically diverse datasets and to provide internationally relevant research on cardiometabolic and child health phenotypes
Identification of common and context specific mechanisms of health and disease mediated by DNAm is of high health impact because it will enable actions to reduce global health disparity and inequity via targeted interventions or treatments.

DNA methylation (DNAm) variation plays a key role in gene regulation, helps cells to respond to environmental signals and ultimately contributes to whole system health and disease status. Inter-individual DNAm variation is influenced by both genetic and environmental factors. Understanding the relationships between DNAm, genetics and environment is essential for both understanding pathways of health and disease and disease consequences.

In aim 1, we address a key knowledge gap by using diverse global datasets to identify genetic and environmental determinants of DNAm variation in diverse environmental and genetic contexts. Prior research is heavily biased towards relatively homogeneous European populations. A key output is an open source mQTL resource which will be used to identify functional pathways of multi-ancestry GWAS and EWAS within the project and is likely to be a resource of international interest.

In aim 2, we delineate mechanisms of disease and disease discordance observed between population groups for childhood and cardiovascular related phenotypes using multi-ancestry EWAS. Identification of disease pathways common to all populations will represent essential mechanisms of health and disease, uncovering potentially generalizable drug targets. Identification of disease pathways restricted to specific genetic and/or environmental exposures will reflect adaptation to environmental and genetic context. This will enable discovery of novel disease aetiology and molecular mechanisms underpinning disease discordance observed across global populations. It will also potentially predict differences in response to treatment or intervention between population groups. This aim also tackles generalizability of DNAm predictors to improve exposure and risk prediction which is only possible using diverse data.

A further key objective is to form equitable collaborator partnerships, enabling further research initiatives that additionally impact health outcomes.