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Genome wide association studies (GWAS) have discovered many genetic associations for traits and diseases. However, most GWAS signals reside in non-coding regions (outside genes), and it is likely that GWAS variants confer their effects through modulating regulatory mechanism. DNA methylation (DNAm) plays a central role in gene regulation and genetic variants associated with DNAm (methylation quantitative trait loci) have been used to provide a candidate mechanism underlying GWAS associations. However so far only a small proportion of GWA signals have been causally linked to mQTLs. One explanation for this could be that many of these mQTLs are context specific. For example most mQTL studies have identified mQTLs in blood. However, blood has a variety of cell-types which may obscure cell-type specific DNAm differences.
In addition to tissue or cell type as a context, many other contexts (eg. sex, age or smoking habits) can also have an influence. These context specific effects may operate by changing your DNAm levels and inducing interactions between genetics and DNAm. These context-specific interactions may then contribute to the development of disease in individuals with a genetic predisposition. However, the effect of context-specific mQTLs on health outcomes is unknown.
This project aims to get a better understanding of context-specific gene regulation and to identify causal influences between context-specific DNA methylation and health outcomes.
The following are examples of specific research questions that the student may wish to address as part of their PhD.
The student will analyse genetic and DNAm data on cohorts that participate in the Genetics of DNA methylation Consortium (GoDMC; http://www.godmc.org.uk/). The student will identify context-specific mQTLs by modelling genotype environmental interactions where cell type, smoking, sex or BMI and can be taken as a proxy for the environment. 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 and develop his/her own research questions.
The student will apply Mendelian randomization (MR) analysis to identify novel causal factors influencing chronic diseases(2). Mendelian Randomization is a genetic epidemiological approach that uses genetic variants as proxies to interrogate potential causal links between exposure (eg cell counts) and outcome (disease).
Supervisors: Dr Josine Min (primary supervisor), Prof Jonathan Mill, Dr Eilis Hannon, Dr Genevieve Leyden
This project will be based in Bristol Medical School - Translational Health Sciences in the Faculty of Health Sciences at the University of Bristol. Use this information to search for the relevant programme in our online application system.
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