Mendelian-Randomization

A latent mixture model for heterogeneous causal mechanisms in Mendelian randomization

There is a general lack of awareness that MR can be used to discover multiple biological mechanisms, partly due to the wide usage of the broad terminology 'effect heterogeneity' to refer to several different phenomena. This article introduces the concept of mechanistic heterogeneity and proposes a latent mixture model to make inference about the causal mechanisms.

Causal inference for heritable phenotypic risk factors using heterogeneous genetic instruments.

We greatly improve the applicability of MR-RAPS. The new GRAPPLE framework can handle multiple exposures and overlapping exposure and outcomes GWAS, and is able to detect multiple pleiotropic pathways. A large-scale experiment was done to understand …

Profile-likelihood Bayesian model averaging for two-sample summary data Mendelian randomization in the presence of horizontal pleiotropy

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.

Using sparsity to overcome unmeasured confounding: Two examples

Sparsity is often used to improve the interpretability of a statistical analysis and/or reduce the variance of a statistical estimator. This talk will explore another aspect—the utility of sparsity in model identifiability through two problems …

Resources for Mendelian randomization

Software and tutorials for Mendelian randomization.

MR Data Challenge 2019

This report entered the 2019 MR Data Challenge and contains reproducible R code for our analysis.

IV & MR

Project page for the statistical methods for instrumental variables and Mendelian randomization.

The statistics of summary-data Mendelian randomization

Invited talk giving an overview of my research on summary-data Mendelian randomization.

Mendelian randomization: A tutorial

Tutorial talk for the theory, methods, and practice of Mendelian randomization.

A Mendelian randomization study of the role of lipoprotein subfractions in coronary artery disease

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.