Events and Meetings of Italian Statistical Society, Advances in Latent Variables - Methods, Models and Applications

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Investigation of pleiotropy in Mendelian randomisation studies with continuous outcome using aggregate genetic data
Fabiola Del Greco, Elinor Jones, Peter Pramstaller, Nuala Sheehan, John Thompson

Last modified: 2013-06-16

Abstract


Mendelian randomisation (MR) allows estimation of the effect of a modifiable phenotype on a disease outcome using genes as instrumental variables, based on estimates of the gene-phenotype and gene-disease associations. MR estimates are unconfounded provided that some assumptions are met. The main assumption is the absence of pleiotropy, i.e. the gene influences the outcome only through the given phenotype. Excluding pleiotropy may be difficult even for well-studied genes, and the use of multiple instruments can indirectly address the issue: if all genes represent valid instruments, their MR estimates will vary only by chance. Formal testing of pleiotropy can be performed with the Sargan over-identification test, but the test requires individual data on both gene-phenotype and gene-disease associations for each gene. Through simulations, we investigate an alternative approach to test for the possible presence of pleiotropy, based on the use of the between-instrument heterogeneity in a meta-analysis of MR estimates from multiple instruments. This approach can be used with aggregate data, that is estimates and standard errors of both gene-phenotype and gene-disease associations for each instrument.


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