TY - JOUR T1 - Robust inference in two-sample Mendelian randomisation via the zero modal pleiotropy assumption JF - bioRxiv DO - 10.1101/126102 SP - 126102 AU - Fernando Pires Hartwig AU - George Davey Smith AU - Jack Bowden Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/04/10/126102.abstract N2 - Background Mendelian randomisation (MR) is being increasingly used as a strategy to improve 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 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 estimator – is proposed to obtain a single causal effect estimate from multiple genetic instruments. The mode estimate 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 evaluated 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 mode estimates presented less bias and type-I error rates than other methods under the null in many situations. Its power to detect a causal effect was smaller compared to 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 mode estimator relaxes the instrumental variable assumptions, and should be used in combination with other approaches in a sensitivity analysis. ER -