Abstract
In Mendelian randomization (MR) analysis, variants that exert horizontal pleiotropy are typically treated as a nuisance. However, they could be valuable in identifying alternative pathways to the traits under investigation. Here, we develop MR-TRYX, a framework that exploits horizontal pleiotropy to discover putative risk factors for disease. We begin by detecting outliers in a single exposure–outcome MR analysis, hypothesising they are due to horizontal pleiotropy. We search across hundreds of complete GWAS summary datasets to systematically identify other (candidate) traits that associate with the outliers. We develop a multi-trait pleiotropy model of the heterogeneity in the exposure–outcome analysis due to pathways through candidate traits. Through detailed investigation of several causal relationships, many pleiotropic pathways are uncovered with already established causal effects, validating the approach, but also alternative putative causal pathways. Adjustment for pleiotropic pathways reduces the heterogeneity across the analyses.
Highlights
This outlier-adjustment method should be treated as a new approach to be used in conjunction with other methods that already exist in the Mendelian randomization (MR) sensitivity analysis toolkit
We provide extensive discussion on the context, advantages and potential pitfalls that come with trying to use a data-driven approach to adjust for horizontal pleiotropy at the end of the paper
As has been previously reported the estimate from inverse-variance weighted (IVW) suggested a weak association between urate and the risk of coronary heart disease (CHD) using all variants (OR per 1 SD: 1.08; 95% CI: 1.00, 1.17), while there was a large intercept in the MR-Egger analysis with a muchattenuated causal effect estimate (Table 2)
Summary
The adjustment model indicated an attenuated IVW estimate in comparison to the ‘raw’ approach, with confidence intervals spanning the null (OR per 1 SD: 1.07; 95% CI: 0.99, 1.16) while the degree of heterogeneity was reduced by half by accounting for the pleiotropic pathways through two outlier SNPs. The adjusted scatter plot showed that outliers moved towards the fitted line after controlling for the SNP effect on the candidate traits (Fig. 4b). The adjusted scatter plot showed that outliers moved towards the fitted line after controlling for the SNP effect on the candidate traits (Fig. 4b) The results in this analysis suggest that it is unlikely that urate has a strong causal influence on CHD. We observed weak evidence for any association between sleep duration and schizophrenia
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