Seminar: Dr Jack Bowden, The University of Bristol

Speaker:

Dr Jack Bowden, MRC Integrative Epidemiology Unit, University of Bristol

Presentation Title:

Accounting for heterogeneity and bias in two-sample Mendelian randomization

Mendelian randomization (MR) uses genetic data to probe questions of causality in epidemiological research, by invoking the Instrumental Variable (IV) assumptions. In recent years it has become commonplace to attempt MR analyses by synthesising summary data estimates of genetic association gleaned from large and independent study populations. This is referred to as two-sample summary data MR. Unfortunately, due to the sheer number of variants that can be easily included into summary data MR analyses, it is increasingly likely that some do not meet the IV assumptions, due to pleiotropy. There is a pressing need to develop methods that can both detect and correct for pleiotropy, in order to preserve the validity of the MR approach in this context. In this paper we aim to clarify how established methods of meta-regression and random effects modelling from mainstream meta-analysis are being adapted to perform this task. Specifically, we focus on two contrasting approaches: the Inverse Variance Weighted (IVW) method which assumes in its simplest form that all genetic variants are valid IVs, and the method of MR-Egger regression that allows all variants to violate the IV assumptions, albeit in a specific way. We investigate the ability of two popular random effects models to provide robustness to pleiotropy under the IVW approach, and propose a statistic to quantify the relative goodness-of-fit of the IVW approach over MR-Egger regression.

From 2007-10 and 2011-15 Dr Bowden worked as a post-doctoral fellow and then senior investigator statistician at the MRC Biostatistics Unit in Cambridge. In 2014 he was awarded a four year MRC Methodology Research Fellowship (title: Bias adjusted inference in biostatistics). His fellowship objective is to develop methods for bias-adjusted inference to support cutting-edge medical science at the intersections of causal inference, adaptive clinical trials and evidence synthesis.  In 2015 he transferred his fellowship to the MRC Integrative Epidemiology Unit, to help focus his immediate research into methods for Mendelian randomization.

He has always retained a soft spot for Manchester, which he remembers fondly from his undergraduate days!

All welcome.  No need to book, just turn up.