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Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression
An adaption of Egger regression can detect some violations of the standard instrumental variable assumptions, and provide an effect estimate which is not subject to these violations, and provides a sensitivity analysis for the robustness of the findings from a Mendelian randomization investigation.
The MR-Base platform supports systematic causal inference across the human phenome
MR-Base is a platform that integrates a curated database of complete GWAS results (no restrictions according to statistical significance) with an application programming interface, web app and R packages that automate 2SMR, and includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions.
Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator
A novel weighted median estimator for combining data on multiple genetic variants into a single causal estimate is presented, which is consistent even when up to 50% of the information comes from invalid instrumental variables.
Mendelian Randomization Analysis With Multiple Genetic Variants Using Summarized Data
It is concluded that Mendelian randomization investigations using summarized data from uncorrelated variants are similarly efficient to those using individual‐level data, although the necessary assumptions cannot be so fully assessed.
Genomic atlas of the human plasma proteome
The genetic architecture of the human plasma proteome in healthy blood donors from the INTERVAL study is characterized, and it is shown that protein quantitative trait loci overlap with gene expression quantitative traits, as well as with disease-associated loci, and evidence that protein biomarkers have causal roles in disease is found.
Interpreting findings from Mendelian randomization using the MR-Egger method
There are several reasons why causal estimates from the MR-Egger method may be biased and have inflated Type 1 error rates in practice, including violations of the InSIDE assumption and the influence of outlying variants.
MendelianRandomization: an R package for performing Mendelian randomization analyses using summarized data
MendelianRandomization is a software package for the R open-source software environment that performs Mendelian randomization analyses using summarized data to implement the inverse-variance weighted, MR-Egger and weighted median methods for multiple genetic variants.
PhenoScanner: a database of human genotype–phenotype associations
Abstract Summary: PhenoScanner is a curated database of publicly available results from large-scale genetic association studies. This tool aims to facilitate ‘phenome scans’, the cross-referencing of…
A review of instrumental variable estimators for Mendelian randomization
- S. Burgess, D. Small, S. Thompson
- Economics, MathematicsStatistical methods in medical research
- 17 August 2015
Settings particularly relevant to Mendelian randomization are prioritized in the paper, notably the scenario of a continuous exposure and a continuous or binary outcome.
Multivariable Mendelian Randomization: The Use of Pleiotropic Genetic Variants to Estimate Causal Effects
It is demonstrated that triglyceride-related pathways have a causal effect on the risk of coronary heart disease independent of the effects of low-density cholesterol and high-density lipoprotein cholesterol.