This is cross-disciplinary project that provides a unique opportunity at the interface of data science, psychology and epidemiology. You will be supervised by Dr Louise Millard (epidemiology data science; MRC Integrative Epidemiology Unit [IEU], Univ. Bristol), Dr Esther Walton (psychology; Univ. Bath), Prof. Kate Tilling (medical statistics; MRC IEU, Univ. Bristol) and Prof. George Davey Smith (clinical epidemiology; MRC IEU, Univ. Bristol).
Assessing whether one trait affects another has typically been difficult in epidemiology since it is difficult to separate non-causal correlation from a causal effect. Mendelian randomization is a method for testing causal effects by using genetic variants as instrumental variables for modifiable non-genetic risk factors and was pioneered by academics at the MRC IEU where it continues to be developed. While Mendelian randomization studies usually test specific hypotheses, the hypothesis-free Mendelian randomization approach instead searches for effects across many traits. To date this has involved searching for effects of a risk factor of interest using an approach called MR-pheWAS which has also been pioneered in Bristol, by Dr Millard and colleagues [1,2,3]. Unlike hypothesis-driven analyses that test specific hypotheses, hypothesis-free MR-pheWAS provides an unbiased view of the landscape of possible causal effects of an exposure on many outcomes.
Instead of searching for effects of a single exposure (using MR-pheWAS) it would also be useful, given a particular outcome of interest (e.g. a specific psychological trait or illness), to be able to search across a number of modifiable risk factors. This would enable identification of novel determinants of this outcome for which it may be possible to develop interventions to improve health. Searching across many exposures could be highly useful to further understand which factors cause adverse psychological outcomes (e.g. psychiatric disorders).
Aim and approach
There are two key aims:
Aim 1: To develop a Mendelian Randomization exposure Wide Association Study (MR-exposureWAS) approach, to search across many exposure phenotypes to test whether they affect a particular outcome of interest.
Aim 2: To apply the MR-exposureWAS approach in the UK Biobank cohort, to search for potential determinants of one or a small number of psychological / psychiatric traits or illnesses. This will enable improved interventions to reduce risk.
The specific focus of aim 2 will depend on the student’s interests, but could include:
1) Psychiatric disorders e.g. anxiety, depression.
2) Psychological traits e.g. wellbeing, loneliness.
3) Brain phenotypes measured by a MRI scan e.g. hippocampal volume or measures from task functional MRI scans .
Depending on the MR-exposureWAS results this project may involve follow-up of identified associations to 1) replicate results in independent data (e.g. ALSPAC, MoBa, iPSYCH) and 2) triangulate results using other causal methods (e.g. sibling analyses ). This could include a research visit to the MoBa study (Oslo, Norway) in year 2 of this PhD.
The student will be based in the MRC IEU in the Bristol Medical School, spending one day a week at the University of Bath. The IEU is a world-class research centre in the field of integrative epidemiology. The IEU is a highly collaborative and supportive research environment where the PhD student will be part of the cross-disciplinary cohort of PhD students and will be able to take advantage of the training opportunities within the IEU including journal clubs, reading groups, and researcher meetings. The Bristol Medical School has an internationally recognised programme of short courses throughout each year. The Advanced Computing Resource Centre at The University of Bristol runs a variety of workshops on the Linux operating system, programming and high performance computing (using the BlueCrystal high performance compute resource).
Applications are welcome from high performing individuals across a wide range of disciplines closely related to natural sciences, biostatistics, genetics, bio-chemistry, mathematics and computer science who have, or are expected to obtain, a 2.1 or higher degree. Applications are particularly welcome from individuals with a relevant research Masters degree.
How to apply: Please make an online application for this project here: https://www.findaphd.com/phds/program/the-gw4-biomed-mrc-dtp-is-offering-up-to-18-fully-funded-studentships-across-a-range-of-biomedical-disciplines-with-a-start-date-of-october-2020/?p2940