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Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses.


ABSTRACT: 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.

SUBMITTER: Brumpton B 

PROVIDER: S-EPMC7360778 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses.

Brumpton Ben B   Sanderson Eleanor E   Heilbron Karl K   Hartwig Fernando Pires FP   Harrison Sean S   Vie Gunnhild Åberge GÅ   Cho Yoonsu Y   Howe Laura D LD   Hughes Amanda A   Boomsma Dorret I DI   Havdahl Alexandra A   Hopper John J   Neale Michael M   Nivard Michel G MG   Pedersen Nancy L NL   Reynolds Chandra A CA   Tucker-Drob Elliot M EM   Grotzinger Andrew A   Howe Laurence L   Morris Tim T   Li Shuai S   Auton Adam A   Windmeijer Frank F   Chen Wei-Min WM   Bjørngaard Johan Håkon JH   Hveem Kristian K   Willer Cristen C   Evans David M DM   Kaprio Jaakko J   Davey Smith George G   Åsvold Bjørn Olav BO   Hemani Gibran G   Davies Neil M NM  

Nature communications 20200714 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 sib  ...[more]

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