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Trajectories of modifiable risk factors and their influences on disease outcomes: using genetics in life course epidemiology

  • Full or part time
    Dr S Burgess
    Dr J Barrett
  • Application Deadline
    Tuesday, January 07, 2020
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

Questions about how risk factors influence disease outcomes are fundamental to epidemiology. However, these questions are difficult to answer, as relevant data are usually observational, and thus associations are not necessarily a reliable guide for causal relationships. An approach that has gained traction over the past decade is the use of genetic variants as instrumental variables to make causal inferences from observational data. If we can assume that genetic variants behave as if they are randomly distributed in the population, then individuals with genetic variants predisposing them to high levels of a given risk factor should be similar to those with genetically-predisposed lower levels of the risk factor in all respects other than the distribution of the risk factor itself. Hence any difference in outcomes between these groups can be traced to the risk factor under investigation. The use of genetic variants to make causal inferences using genetic variants is known as Mendelian randomization

The aim of this project is to extend this idea to consider risk factors that vary across the life course. For example, we know that there are genetic predictors of birth weight, of pubertal timing, and of adult body mass index (BMI). Each of these overlapping sets of variants affects obesity in a different way. However, as an example, increased adult BMI is observationally associated with increased risk of type 2 diabetes, but increased birth weight is observationally associated with decreased risk of type 2 diabetes. How can we use these different genetic variants to answer causal questions about the timings of causal effects? Or to find critical periods in which changes in the risk factor may particularly impact the outcome? This project will consider both theoretical issues grounded in the causal inference literature about how to express these concepts, and applied issues about how to use available genetic information to answer relevant questions about the origins of disease.

Funding Notes

The MRC Biostatistics Unit offers 4 fulltime PhDs funded by the Medical Research Council for commencement in April 2020 (UK applicants only) or October 2020 (all applicants). Academic and Residence eligibility criteria apply.

In order to be formally considered all applicants must complete a University of Cambridge application form. Informal enquiries are welcome to

Applications received via the University application system will all be considered as a gathered field after the closing date 7th January 2020

For all queries see our website for details View Website

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