Abstract:
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In genetic association studies, Mendelian Randomization (MR) has gained in popularity as a concept to assess the causal relationship between two phenotypes. The MR Steiger approach has been proposed as tools that can infer the causal direction between two phenotypes. Through simulation studies, we extend our previous work to examine the ability of the MR Steiger approach to correctly determine the effect direction in the presence of pleiotropy, measurement error, unmeasured confounding, and selection bias. In order to examine the role of smoking on lung function in the presence of pleiotropy, measurement error, and/or selection bias, we applied the Steiger approach to the COPDGene study, a case-control study of Chronic Obstructive Pulmonary Disease (COPD) in current and former smokers, and the UK Biobank, a large-scale biomedical database containing in-depth genetic and health information from half a million UK participants.
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