Identifying causal pathways to disease using DNA methylation derived scores.

Rationale

DNA methylation is an epigenetic biomarker that has been shown to reflect lifestyle and biological factors (smoking, alcohol use, chronological age). To date the majority of studies used to link behavioral phenotypes such as cigarette smoking, and alcohol use to health outcomes typically employ self-reported questionnaire data. Multiple DNA methylation (DNAm) sites are strongly associated with (behavioural) traits. DNAm derived scores have been used to predict (or proxy for) these traits providing greater precision and biological proximity than self-reported measures. The DNAm derived smoking score is a widely used biomarker of lifetime exposure to tobacco smoke and may explain the molecular mechanism of the long-term risk of diseases following smoking cessation. There is growing interest in conducting genome-wide association studies (GWAS) and Mendelian randomization (MR) analysis on DNAm scores to identify novel genetic and causal factors influencing behavioural traits. To date, several GWAS on DNAm derived scores of aging have been published (Lu et al. 2018, McCartney et al. 2021). The many benefits to identify novel loci and biological pathways for other phenotypes have yet to be gained. This studentship will provide cross-disciplinary training in state-of-the-art genetic and genomic epidemiological approaches (under the supervision of Dr. Josine Min and Prof Caroline Relton at the Medical Research Council Integrative Epidemiology Unit at the University of Bristol and Prof Jonathan Mill and Dr. Eilis Hannon at the University of Exeter Medical School) to address questions about the molecular mechanism underlying established disease risk factors. The student will combine epigenetic, genetic and causal inference analyses in large-scale epidemiological datasets.

Aims & Objectives

The overall aim of this PhD is to identify genetic variants and biological pathways associated with disease risk factors using DNAm scores. The specific risk factors/diseases for this project would depend on the candidate's research interests, but could include cell counts, smoking or alcohol use. The Genetics of DNA Methylation Consortium (GoDMC; http://www.godmc.org.uk/) has collected genetic and DNAm data across multiple cohorts offering the student an excellent platform for these analyses.

Methods

1) Novel methodology can be used (and potentially developed) to construct DNAm scores on disease risk factors

2) GWAS on DNAm derived phenotype datasets will be conducted followed by meta-analyses. There will be several challenges with this type of analysis including heterogeneity of datasets in age, sex and tissue type.

3) To understand what aspect of the phenotype is captured by the DNAm phenotype, GWAS meta-analysis results will be compared to GWA results of detailed (self-reported) phenotypes (eg. in UK Biobank) and methylation quantitative loci from blood and brain.

4) MR analysis will be used to investigate causal relationships between DNAm derived measures and self-reported measures and other diseases/risk factors.

5) The heritability component of DNAm derived phenotypes will be estimated.

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.