MRC Integrative Epidemiology Unit (IEU) Seminar Series

Title: Selecting causal risk factors from high-throughput experiments using multivariable Mendelian randomization 

Abstract: Modern high-throughput experiments provide a rich resource to investigate causal determinants of disease risk. Mendelian randomization (MR) is the use of genetic variants as instrumental variables to infer the causal effect of a specific risk factor on an outcome. Multivariable MR is an extension of the standard MR framework to consider multiple potential risk factors in a single model. However, current implementations of multivariable MR use standard linear regression and hence perform poorly with many risk factors. Here, we propose a novel approach to multivariable MR based on Bayesian model averaging (MR-BMA) that scales to high-throughput experiments and can select biomarker as causal risk factors for disease. In a realistic simulation study we show that MR-BMA can detect true causal risk factors even when the candidate risk factors are highly correlated. We illustrate MR-BMA by analysing publicly-available summarized data on metabolites to prioritise likely causal biomarkers for age-related macular degeneration. 

Biography: Verena is Lecturer in Biostatistics at the Department of Epidemiology and Biostatistics at Imperial College London. She holds a visiting position at the MRC Biostatistics Unit, University of Cambridge, where she has been a research associate working with Steve Burgess on causal inference and Mendelian Randomisation. 
 
She has a background in Statistics (BSc, MSc, LMU Munich) and she worked on high-dimensional variable selection for biomarkers discovery during her PhD in Biostatistics under the supervision of Korbinian Strimmer. As research associate, she has gained experience in statistical genetics, in particular in molecular epidemiology and functional annotation (University of Oslo, under the supervision of Ian Mills and Ole Andreassen), and fine-mapping to detect genetic variants causing disease (EBI, Hinxton under the supervision of Oliver Stegle). 

All welcome