Genetics and causality: towards more accessible and more reliable Mendelian randomisation investigations

Year of award: 2016


  • Dr Stephen Burgess

    University of Cambridge

Project summary

An observational correlation between a suspected risk factor and a disease outcome does not imply that changes in the risk factor will necessarily have a causal impact on disease risk. This is often discussed as ‘correlation is not causation’. One way to assess whether a relationship is causal is to look at genetics, as genetic variants do not tend to be associated with differences in socio-economic or environmental factors that make observations of causality unreliable. If genetic predictors of the risk factor are also associated with the outcome, this increases the plausibility that the risk factor is a causal determinant of disease risk. However, if the genetic variants in the analysis do not have a specific biological link to the risk factor, then the same problems in inferring a causal relationship remain.

My research aims to develop methods using genetic variants for making causal inferences that are more accessible and reliable. I will work with clinicians and epidemiologists to apply these methods to assess the causal effects of a range of risk factors on disease outcomes and to discover risk factors that may be good targets for drug development.