Instrumental Heterogeneity in Sex-Specific Two-Sample Mendelian Randomization: Empirical Results From the Relationship Between Anthropometric Traits and Breast/Prostate Cancer - Gao, Yixin; Zhang, Jinhui; Zhao, Huashuo; Guan, Fengjun; Zeng, Ping (Frontiers in Genetics, 2021)
Background: In two-sample Mendelian randomization (MR) studies sex instrumental heterogeneity is an important problem needed to address carefully, which however is often overlooked and may lead to misleading causal inference. Methods: We first employed cross-trait linkage disequilibrium score regression (LDSC), Pearson’s correlation analysis and the Cochran’s Q test to examine sex genetic similarity and heterogeneity in instrumental variables of exposures. Simulation was further performed to explore the influence of sex instrumental heterogeneity on causal effect estimation in sex-specific two-sample MR analyses. Furthermore, we chose breast/prostate cancer as outcome and four anthropometric traits as exposures as an illustrative example to illustrate the importance of taking sex heterogeneity of instruments into account in MR studies. Results: The simulation definitively demonstrated sex-combined instrumental variables can lead to biased causal effect estimates in sex-specific two-sample MR studies. In our real applications both LDSC and Pearson’s correlation analyses showed high genetic correlation between sex-combined and sex-specific instrumental variables of the four anthropometric traits, while nearly all the correlation coefficients were larger than zero but less than one. The Cochran’s Q test also displayed sex heterogeneity for some instruments. When applying sex-specific instruments, significant discrepancies in the magnitude of estimated causal effects were detected for BMI on breast cancer (P=1.63E-6), for HIP on breast cancer (P=1.25E-20) and for WC on prostate cancer (P=0.007) compared with those generated with sex-combined instruments. Conclusion: Our study reveals that the sex instrumental heterogeneity has non-ignorable impact on sex-specific two-sample MR studies and the causal effects of anthropometric traits on breast/prostate cancer would be biased if sex-combined instrumental variables are incorrectly employed.