Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption

Int J Epidemiol. 2017 Dec 1;46(6):1985-1998. doi: 10.1093/ije/dyx102.


Background: Mendelian randomization (MR) is being increasingly used to strengthen causal inference in observational studies. Availability of summary data of genetic associations for a variety of phenotypes from large genome-wide association studies (GWAS) allows straightforward application of MR using summary data methods, typically in a two-sample design. In addition to the conventional inverse variance weighting (IVW) method, recently developed summary data MR methods, such as the MR-Egger and weighted median approaches, allow a relaxation of the instrumental variable assumptions.

Methods: Here, a new method - the mode-based estimate (MBE) - is proposed to obtain a single causal effect estimate from multiple genetic instruments. The MBE is consistent when the largest number of similar (identical in infinite samples) individual-instrument causal effect estimates comes from valid instruments, even if the majority of instruments are invalid. We evaluate the performance of the method in simulations designed to mimic the two-sample summary data setting, and demonstrate its use by investigating the causal effect of plasma lipid fractions and urate levels on coronary heart disease risk.

Results: The MBE presented less bias and lower type-I error rates than other methods under the null in many situations. Its power to detect a causal effect was smaller compared with the IVW and weighted median methods, but was larger than that of MR-Egger regression, with sample size requirements typically smaller than those available from GWAS consortia.

Conclusions: The MBE relaxes the instrumental variable assumptions, and should be used in combination with other approaches in sensitivity analyses.

Keywords: Causality; Mendelian randomization; genetic pleiotropy; genetic variation; instrumental variables.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Causality
  • Genetic Pleiotropy*
  • Genome-Wide Association Study
  • Humans
  • Mendelian Randomization Analysis*
  • Models, Statistical
  • Sample Size