Pleiotropy robust Mendelian randomization: Jack Bowden

Programme Overview

The explosion in publicly available data from genome-wide association studies is accelerating the use of Mendelian randomization (MR) in bio-medicine. Summary data estimates of genetic association from large numbers of variants are now being synthesised for causal inference within the two-sample framework. Over the coming years, cohort studies such as UK Biobank will also provide a rich individual-level data resource for MR investigations. In a short time, the field has seen, and will continue to see, a dramatic rise in the power for testing causal hypotheses. There is a justified concern that when large numbers of genetic variants are included in MR analyses, with many lacking a firm biological basis for their association with the exposure, a sizeable proportion of these variants are likely to be invalid instrumental variables.

Aims and Objectives 

A chief concern is that genetic variants may exert an effect on the outcome not through the exposure of interest - which is referred to as horizontal pleiotropy. Programme 2 will focus on the development of statistical methods for MR in the presence of pleiotropy and other associated biases. Building upon recent methodological advancements in this field, we will develop analysis tools that: • Visualise MR data to facilitate the detection of pleiotropy; • Explicitly model and adjust for pleiotropy;

  • Provide natural robustness to pleiotropy;
  • Adjust for non-random selection into (or out of) cohort studies used for MR;
  • Novel methods for data visualisation and analysis will be incorporated into statistical software platforms such as MR-Base

Programme Outcomes 

Programme 2 links key players in methodological research around the world to leading biomedical scientists at the IEU. It will develop the tools to enable epidemiological researchers to fully capitalise on emerging large-scale data sources whilst preserving the principles and rigour of causal inference.

Research Highlights 

Jack Bowden
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