Pulse Brain · Growing Health Evidence Index
Peer-reviewed

Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic

Jack Bowden, Fabiola Del Greco M, Cosetta Minelli, George Davey Smith, Nuala A. Sheehan, John R. Thompson

International Journal of Epidemiology · 2016

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Summary

Background: : MR-Egger regression has recently been proposed as a method for Mendelian randomization (MR) analyses incorporating summary data estimates of causal effect from multiple individual variants, which is robust to invalid instruments. It can be used to test for directional pleiotropy and provides an estimate of the causal effect adjusted for its presence. MR-Egger regression provides a useful additional sensitivity analysis to the standard inverse variance weighted (IVW) approach that assumes all variants are valid instruments. Both methods use weights that consider the single nucleotide polymorphism (SNP)-exposure associations to be known, rather than estimated. We call this the `NO Measurement Error' (NOME) assumption. Causal effect estimates from the IVW approach exhibit weak i

Source type
Peer-reviewed study
DOI
10.1093/ije/dyw220
Catalogue ID
BFmokjo8sc-5hjwu2
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