Multivariable Mendelian randomization: the use of pleiotropic genetic variants to estimate causal effects.
Bottom Line: A conventional Mendelian randomization analysis assesses the causal effect of a risk factor on an outcome by using genetic variants that are solely associated with the risk factor of interest as instrumental variables.In this paper, we propose an extension of Mendelian randomization that uses multiple genetic variants associated with several measured risk factors to simultaneously estimate the causal effect of each of the risk factors on the outcome.Subject to these assumptions, we demonstrate that triglyceride-related pathways have a causal effect on the risk of coronary heart disease independent of the effects of low-density lipoprotein cholesterol and high-density lipoprotein cholesterol.
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Mentions: There are several causal mechanisms by which a genetic variant may be associated with multiple risk factors (11). We divide the possible mechanisms into 2 cases (Figure 2): 1) vertical pleiotropy, where a variant is associated with multiple risk factors due to the causal effect of the primary risk factor on a secondary trait, and 2) functional pleiotropy, where the genetic variant is associated with multiple pathways. These 2 cases are not mutually exclusive; it is possible for both of them to exist for the same variant.Figure 2.