Exploiting horizontal pleiotropy to search for causal pathways within a Mendelian randomization framework

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...

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Vydáno v:Nature communications Ročník 11; číslo 1; s. 1010 - 13
Hlavní autoři: Cho, Yoonsu, Haycock, Philip C., Sanderson, Eleanor, Gaunt, Tom R., Zheng, Jie, Morris, Andrew P., Davey Smith, George, Hemani, Gibran
Médium: Journal Article
Jazyk:angličtina
Vydáno: London Nature Publishing Group UK 21.02.2020
Nature Publishing Group
Nature Portfolio
Témata:
45
45/43
631/114/2415
631/208/205
692/308/174
692/308/2056
Causality
Computer Simulation
Data analysis
Databases, Genetic
Disease - genetics
Estimates
Exposure
Genetic Pleiotropy
Genetic Variation
Genome-Wide Association Study
Heterogeneity
Humanities and Social Sciences
Humans
Influence
Mendelian Randomization Analysis
Methods
Models, Genetic
multidisciplinary
Outliers (statistics)
Phenotype
Pleiotropy
Polymorphism, Single Nucleotide
Randomization
Risk analysis
Risk Factors
Science
Science (multidisciplinary)
Simulation
ISSN:2041-1723, 2041-1723
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Shrnutí: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. In Mendelian randomization (MR) studies, one typically selects SNPs as instrumental variables that do not directly affect the outcome to avoid violation of MR assumptions. Here, Cho et al. present a framework, MR-TRYX, that leverages knowledge of such outliers of horizontal pleiotropy to identify putative causal relationships between exposure and outcome.
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ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-020-14452-4