A comparison of three methods of Mendelian randomization when the genetic instrument, the risk factor and the outcome are all binary.
Details
State: Public
Version: Final published version
Serval ID
serval:BIB_B746A7A2E72E
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
A comparison of three methods of Mendelian randomization when the genetic instrument, the risk factor and the outcome are all binary.
Journal
Plos One
ISSN
1932-6203 (Electronic)
ISSN-L
1932-6203
Publication state
Published
Issued date
2012
Peer-reviewed
Oui
Volume
7
Number
5
Pages
art. e35951 [11 p.]
Language
english
Notes
Publication types: Journal Article
Abstract
The method of instrumental variable (referred to as Mendelian randomization when the instrument is a genetic variant) has been initially developed to infer on a causal effect of a risk factor on some outcome of interest in a linear model. Adapting this method to nonlinear models, however, is known to be problematic. In this paper, we consider the simple case when the genetic instrument, the risk factor, and the outcome are all binary. We compare via simulations the usual two-stages estimate of a causal odds-ratio and its adjusted version with a recently proposed estimate in the context of a clinical trial with noncompliance. In contrast to the former two, we confirm that the latter is (under some conditions) a valid estimate of a causal odds-ratio defined in the subpopulation of compliers, and we propose its use in the context of Mendelian randomization. By analogy with a clinical trial with noncompliance, compliers are those individuals for whom the presence/absence of the risk factor X is determined by the presence/absence of the genetic variant Z (i.e., for whom we would observe X = Z whatever the alleles randomly received at conception). We also recall and illustrate the huge variability of instrumental variable estimates when the instrument is weak (i.e., with a low percentage of compliers, as is typically the case with genetic instruments for which this proportion is frequently smaller than 10%) where the inter-quartile range of our simulated estimates was up to 18 times higher compared to a conventional (e.g., intention-to-treat) approach. We thus conclude that the need to find stronger instruments is probably as important as the need to develop a methodology allowing to consistently estimate a causal odds-ratio.
Pubmed
Web of science
Open Access
Yes
Create date
21/05/2012 9:04
Last modification date
20/08/2019 16:25