Identifying causal pathways to disease using DNA methylation predicted blood traits.

Project Background

Blood cell types have been implicated in pathogenesis of chronic diseases. Genome wide association studies have identified thousands of variants associated with blood trait variation. Genetic risk scores of cell counts associate to disease. For example, genetic risk scores of eosinophils associate with asthma. However, for other cell types such as memory and naïve T and B cells evidence for a causal role in chronic diseases is scarce. This is because these cell types are not measured at an epidemiological scale.

DNA methylation (DNAm) sites have been widely measured in cohorts and are cell type specific. DNAm profiles of cell-sorted samples have been used to predict 12 cell types providing much greater coverage of blood cell types in epidemiological cohorts(1). These DNAm derived cell type proportions have been associated with many health outcomes and all-cause mortality (2) whereas their ratios (neutrophil-lymphocyte ratio) have been associated with inflammation.

Yet understanding of the genetic and environmental factors (infection, smoking and diet) contributing to these blood cell traits is limited as are their potential causal links with disease. 

Project Aims

The aim is to get a better understanding of the genetic architecture of blood cell variation of understudied cell types and to identify causal influences between blood cell variation and disease.

Examples of research questions are:

1. Identify genetic factors for cell types on DNAm predicted cell type proportions

2. Identify causal associations between blood cell traits and health outcomes, such as T cell proportions and atopic dermatitis

3. Identify genetic factors influencing the variance of blood cell traits and investigate their underlying gene environmental interactions. 

Project Methods

This studentship will provide cross-disciplinary training in state-of-the-art epigenetic, genetic and causal inference analyses. The student will use innovative software and methods to analyse genetic and DNAm data by collaborating with academic centres that participate in the Genetics of DNA Methylation Consortium (GoDMC; http://www.godmc.org.uk/).

The student will conduct genome wide association studies of 12 DNAm predicted cell type proportions and on cell type variance. GoDMC promotes a federated analysis protocol which means that the PhD student has an excellent platform to develop analysis skills for genetic and DNAm analysis. The student will apply Mendelian randomization (MR) analysis to identify novel causal factors influencing chronic diseases(3). Mendelian Randomization is a genetic epidemiological approach that uses genetic variants as proxies to interrogate potential causal links between exposure (eg cellular proportion) and outcome (disease). The student will use PHESANT, an automated tool to leverage thousands of environmental factors to test for gene environmental interactions on variance GWAS signals of blood cell traits.

How to apply for this project

This project will be based in Bristol Medical School - Population Health Sciences in the Faculty of Health Sciences at the University of Bristol.

If you have secured your own sponsorship or can self-fund this PhD please visit our information page here for further information on the department of Population Health Science and how to apply.