Diagnostics for Pleiotropy in Mendelian Randomization Studies: Global and Individual Tests for Direct Effects

Abstract

Diagnosing pleiotropy is critical for assessing the validity of Mendelian randomization (MR) analyses. The popular MR-Egger method evaluates whether there is evidence of bias-generating pleiotropy among a set of candidate genetic instrumental variables. In this article, we propose a statistical method-global and individual tests for direct effects (GLIDE)-for systematically evaluating pleiotropy among the set of genetic variants (e.g., single nucleotide polymorphisms (SNPs)) used for MR. As a global test, simulation experiments suggest that GLIDE is nearly uniformly more powerful than the MR-Egger method. As a sensitivity analysis, GLIDE is capable of detecting outliers in individual variant-level pleiotropy, in order to obtain a refined set of genetic instrumental variables. We used GLIDE to analyze both body mass index and height for associations with colorectal cancer risk in data from the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colon Cancer Family Registry (multiple studies). Among the body mass index-associated SNPs and the height-associated SNPs, several individual variants showed evidence of pleiotropy. Removal of these potentially pleiotropic SNPs resulted in attenuation of respective estimates of the causal effects. In summary, the proposed GLIDE method is useful for sensitivity analyses and improves the validity of MR.

Figure 1.

Causal diagram for Mendelian randomization. The goal is to use genotypes as instrumental variables to infer the causal effect of an exposure on a disease outcome. One critical assumption is that there is no direct effect from the genotype to the disease (no pleiotropy).

Figure 2.

Statistical power, in simulations, of the global and individual tests for direct effects (GLIDE) and Mendelian randomization (MR)-Egger methods to test the global null hypothesis that there is no direct effect for any genetic variant. The sold line represents results of the GLIDE test, and the dotted-dashed line represents results of the MR-Egger test. A) The direct effects are all positive; B) some direct effects are positive and some are negative; C) a proportion of single nucleotide polymorphisms (SNPs) (60%) have pleiotropic effects; D) all SNPs have direct effects that are correlated with the genetic associations with the intermediate exposure. RR, relative risk.

Figure 3.

Application of Menedelian randomization (MR)-Egger regression and the proposed global and individual tests for direct effects (GLIDE) test to data from the Genetics and Epidemiology of Colorectal Cancer (GECCO) Consortium in a study of body mass index (BMI; weight (kg)/height (m)²) and height in colorectal cancer (CRC) risk. The solid squares represent single nucleotide polymorphisms (SNPs) with some evidence of pleiotropy detected by GLIDE; the open circles represent SNPs which did not exhibit evidence of pleiotropy. A) MR-Egger regression results showing the intercept and slope for 77 SNPs previously shown to be linked to BMI in the Genetic Investigation of Anthropometric Traits (GIANT) Consortium (30, 31). B) Proposed GLIDE test results showing the quantile-quantile (Q-Q) plot for P values derived from assessment of surrogate direct effects for BMI. C) MR-Egger regression results showing the intercept and slope for 696 SNPs previously shown to be linked to height in the GIANT consortium. D) Proposed GLIDE test results showing the Q-Q plot for P values derived from assessment of surrogate direct effects for height. RR, relative risk.