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    Author summary Uncovering causal mechanisms between risk factors and disease is challenging with observational data because of unobserved confounding. Mendelian randomization offers a potential solution by replacing an individual’s observed risk factor data with an unconfounded genetic proxy measure. Over the last decade an array of methods for performing Mendelian randomization studies (MR)…

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    • Barry et al @jack_bowdenjack present a method for applying summary data #Mendelian randomization methods using individual level data from one cohort study The method intentionally creates collider bias, which can be estimated to correct results https://t.co/rvgIjM1X3N