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: Here we address the question of the causal effects of LDL-C, HDL-C, and triglycerides on CHD risk by multivariable Mendelian randomization using published data. Waterworth et al. (24) reported genetic associations from univariate regression analyses of 28 genetic variants with log-transformed LDL-C, HDL-C, and triglyceride concentrations and with the log odds of CHD. Details on the variants and the β coefficients for the associations are given in Web Table 1. Figures 4 and 5 depict the associations of each of the variants with the lipid fractions and CHD risk.Figure 4.