MR method that controls for horizontal pleiotropy and provides bounds for the causal effect of an exposure on an outcome in the presence of such pleiotropy.
The method can be split into conditional or unconditional GIV. Conditional GIV involves estimating the effects of genetic variants being used as instrumental variables (IVs) on the outcome that are independent from the exposure (i.e., horizontally pleiotropic) by using a genome-wide association study (GWAS) of the outcome that has conditioned on the exposure. These conditional effects are then included in the model estimation of the causal effect of the exposure on the outcome, theoretically removing bias arising from horizontal pleiotropy. Where a GWAS of the outcome conditioning on the exposure is not available, unconditional GIV can be used, which includes the genetic variants associated with the outcome in the MR analysis. Whilst the unconditional GIV corrects for bias arising from horizontal pleiotropy, it will likely bias the causal effect estimates towards the null as the unconditional summary statistics of the outcome also include genetic variants that also impact the outcome via the exposure.
References
Other terms in 'Pleiotropy-robust two-sample MR methods':
- Bayes MR
- Bayesian implementation of the MR-Egger Estimator (BMRE)
- Bayesian multi-instrument Mendelian randomization (MIMR)
- Bayesian network analysis
- Causal Analysis Using Summary Effect estimates (MR-CAUSE)
- Contamination mixture models
- Generalized Summary MR (GSMR)
- Hierarchical joint Analysis of Marginal summary statistics (hJAM)
- Inverse variance weighted (IVW) random effects model
- Iterative Mendelian Randomization and Pleiotropy (IMRP)
- Leave-one-out analysis
- Median-based estimate
- Mode-based estimate
- MR accounting for Correlated and Idiosyncratic Pleiotropy (MRCIP)
- MR accounting for Linkage Disequilibrium and Pleiotropy (MR-LDP)
- MR Lasso
- MR Mixture (MRMix)
- MR using Robust regression (MR Robust)
- MR with penalized weights
- MR with regularization
- MR-Clust
- MR-Egger regression and extensions
- MR-Link
- MR-Path
- Multivariable MR (MVMR) and extensions
- Welch-weighted Egger regression (WWER)