We propose a Bayesian model averaging method to account for the uncertainty about instrument validity in Mendelian randomization. This model is extended to allow for a large fraction of SNPs violating the InSIDE assumption.
We apply the MR-RAPS method we developed in previous articles to infer the potential causal role of lipoprotein subfractions in CAD. This is motivated by the finding in our earlier IJE paper that the association between genetically-determined HDL-C and CAD is heterogeneous according to instrument strength. In this study, We find that HDL subfraction traits, unlike LDL and VLDL subfractions, appear to have heterogeneous effects on coronary artery disease according to particle size. The concentration of medium HDL particles may have a protective effect on CAD that is independent of traditional lipid factors.
We propose a falsification test for the IV assumptions using sub-populations of the data with overwhelming proportion of treated or untreated units. If the IV assumptions hold, we should find the intention-to-treat effect is zero within these …
This research letter proposes a new diagnostic plot for IV analysis, so large bias ratios (compared to OLS estimator) are not over-interpreted when the covariate is unrelated to the outcome.
We extend the MR-RAPS method in our previous paper using the empirical partially Bayes framework described by Lindsay, allowing a true genome-wide design for Mendelian randomization.