Genome-wide association studies have yielded thousands of associations for many
common diseases and disease-related complex traits. The identified associations made it …

Genome‐wide association studies, which typically report regression coefficients
summarizing the associations of many genetic variants with various traits, are potentially a …

Mendelian randomization investigations are becoming more powerful and simpler to
perform, due to the increasing size and coverage of genome-wide association studies and …

Mendelian randomization (MR) is a valuable tool for detecting causal effects by using
genetic variant associations. Opportunities to apply MR are growing rapidly with the …

Finding individual-level data for adequately-powered Mendelian randomization analyses
may be problematic. As publicly-available summarized data on genetic associations with …

Mendelian Randomization: Methods For Causal Inference Using Genetic Variants provides
thorough coverage of the methods and practical elements of Mendelian randomization …

Mendelian randomization and colocalization are two statistical approaches that can be
applied to summarized data from genome-wide association studies (GWASs) to understand …

Confounding and reverse causality have prevented us from drawing meaningful clinical
interpretation even in well-powered observational studies. Confounding may be attributed to …

With the increasing availability of large-scale GWAS summary data on various complex traits
and diseases, there have been tremendous interests in applications of Mendelian …

Mendelian randomization (MR) is an approach that uses genetic variants associated with a
modifiable exposure or biological intermediate to estimate the causal relationship between …