Early implementations of the Mendelian randomization approach were largely constrained by limitations of power as investigations were undertaken in small sample sizes, and used only a handful of genetic variants (each explaining a small proportion of the variance in the exposure). However, a revolution in the field is under way led by the identification of increasing numbers of genetic variants robustly associated with particular traits, and the public release by many large consortia of summary association estimates for hundreds of thousands of genetic variants with exposures and disease outcomes (Burgess et al., 2015b), such as the Global Lipids Genetics Consortium (GLGC) for lipid fractions [GLGC, 2013] and the CARDIoGRAM consortium for coronary artery disease (CAD) risk (CARDIoGRAMplusC4D Consortium, 2013). The availability of such summary data has facilitated powerful Mendelian randomization investigations to be conducted in a two‐sample framework by providing genetic associations precisely estimated in large sample sizes (Burgess et al., 2013).
