biostudies-literatureBrumpton BNICHD NIH HHSNIA NIH HHSMedical Research CouncilWellcome Trust3519https://www.ebi.ac.uk/biostudies/studies/S-EPMC7360778biostudies-literatureUnknown11(1)Estimates from Mendelian randomization studies of unrelated individuals can be biased due to uncontrolled confounding from familial effects. Here we describe methods for within-family Mendelian randomization analyses and use simulation studies to show that family-based analyses can reduce such biases. We illustrate empirically how familial effects can affect estimates using data from 61,008 siblings from the Nord-Trøndelag Health Study and UK Biobank and replicated our findings using 222,368 siblings from 23andMe. Both Mendelian randomization estimates using unrelated individuals and within family methods reproduced established effects of lower BMI reducing risk of diabetes and high blood pressure. However, while Mendelian randomization estimates from samples of unrelated individuals suggested that taller height and lower BMI increase educational attainment, these effects were strongly attenuated in within-family Mendelian randomization analyses. Our findings indicate the necessity of controlling for population structure and familial effects in Mendelian randomization studies.Nature communicationsAvoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses.PMC7360778R01 HD083613R01 AG060470MR/M020894/1MC_UU_00011/1R01 AG059329R01 AG046938R01 AG054628208806/Z/17/ZR01 AG018386WT104150Harrison SBrumpton BHeilbron KHavdahl AReynolds CAKaprio JWithin-family ConsortiumNivard MGEvans DMHowe LHveem KAuton A23andMe Research TeamPedersen NLNeale MHopper JCho YGrotzinger ATucker-Drob EMBjorngaard JHWiller CHartwig FPHowe LDHughes ABoomsma DIHemani GWindmeijer FMorris TDavies NMSmith GDChen WMLi SDavey Smith GAsvold BOSanderson EVie GAfalseAvoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses.Estimates from Mendelian randomization studies of unrelated individuals can be biased due to uncontrolled confounding from familial effects. Here we describe methods for within-family Mendelian randomization analyses and use simulation studies to show that family-based analyses can reduce such biases. We illustrate empirically how familial effects can affect estimates using data from 61,008 siblings from the Nord-Trøndelag Health Study and UK Biobank and replicated our findings using 222,368 siblings from 23andMe. Both Mendelian randomization estimates using unrelated individuals and within family methods reproduced established effects of lower BMI reducing risk of diabetes and high blood pressure. However, while Mendelian randomization estimates from samples of unrelated individuals suggested that taller height and lower BMI increase educational attainment, these effects were strongly attenuated in within-family Mendelian randomization analyses. Our findings indicate the necessity of controlling for population structure and familial effects in Mendelian randomization studies.2020-01-01T00:00:00Z2020 Jul2021-02-21T05:00:36Z2020-07-31T09:17:08ZS-EPMC73607783266558710.1038/s41467-020-17117-4