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Int J Epidemiol. 2018 Nov 20. doi: 10.1093/ije/dyy204. [Epub ahead of print]

Detecting and correcting for bias in Mendelian randomization analyses using Gene-by-Environment interactions.

Author information

1
Population Health Sciences, University of Bristol, Bristol, UK.
2
Department of Economics, Binghamton University, State University of New York, Binghamton, NY, USA.

Abstract

Background:

Mendelian randomization (MR) has developed into an established method for strengthening causal inference and estimating causal effects, largely due to the proliferation of genome-wide association studies. However, genetic instruments remain controversial, as horizontal pleiotropic effects can introduce bias into causal estimates. Recent work has highlighted the potential of gene-environment interactions in detecting and correcting for pleiotropic bias in MR analyses.

Methods:

We introduce MR using Gene-by-Environment interactions (MRGxE) as a framework capable of identifying and correcting for pleiotropic bias. If an instrument-covariate interaction induces variation in the association between a genetic instrument and exposure, it is possible to identify and correct for pleiotropic effects. The interpretation of MRGxE is similar to conventional summary MR approaches, with a particular advantage of MRGxE being the ability to assess the validity of an individual instrument.

Results:

We investigate the effect of adiposity, measured using body mass index (BMI), upon systolic blood pressure (SBP) using data from the UK Biobank and a single weighted allelic score informed by data from the GIANT consortium. We find MRGxE produces findings in agreement with two-sample summary MR approaches. Further, we perform simulations highlighting the utility of the approach even when the MRGxE assumptions are violated.

Conclusions:

By utilizing instrument-covariate interactions in MR analyses implemented within a linear-regression framework, it is possible to identify and correct for horizontal pleiotropic bias, provided the average magnitude of pleiotropy is constant across interaction-covariate subgroups.

PMID:
30462199
DOI:
10.1093/ije/dyy204

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