We aim to test a novel method for identifying potentially causal associations, which we call the Mendelian randomisation phenome-wide association study (MR-pheWAS) approach. We aim to identify potentially causal effects of BMI, as an exemplar.
We have tested the MR-pheWAS approach using the Avon Longitudinal Study of Parents and Children (ALSPAC) dataset (with ~8K participants). Repeating this with Biobank will greatly improve statistical power, and means we investigate causal effects in adulthood.
Research question: What novel, potentially causal effects of BMI can the MR-pheWAS approach identify?
Health conditions: Body mass index, and several other traits. BMI is associated with a wide range of diseases. This project aims to improve understanding of the complex effects of BMI, by testing for the causal effects of BMI on a wide range of outcomes. Results from this project will prioritize a subset of hypotheses for replication and further investigation.
Identifying potentially causal effects of BMI is important in order to inform policy makers on appropriate interventions. Interventions targeted at BMI are likely to impact a wide range of traits and diseases. This is becoming increasingly important as the UK is now experiencing increasing levels of obesity. We will use data of all participants from Biobank that have measurements for BMI and a set of genetic loci that have previously been found to be associated with BMI.
We will test the causal effect of BMI on a wide range of outcomes. We will do this using a natural experiment (instrumental variable) constructed from the genome (a Mendelian randomization approach), to identify outcomes that may be affected by BMI.
We use a hypothesis-free approach and so will test a large arbitrarily selected set of outcomes, rather than selecting particular outcomes. All participants with a value for BMI (var=21001) and BMI associated genetic loci.