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

Published version
Peer-reviewed

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Authors

Heilbron, Karl 
Howe, Laura D. 
Hughes, Amanda 
Boomsma, Dorret I. 
Hopper, John 

Abstract

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.

Description

Keywords

Article, /631/208, /692/308, /692/308/174, /692/308/2056, /692/499, /45/43, article

Journal Title

Nature Communications

Conference Name

Journal ISSN

2041-1723

Volume Title

11

Publisher

Nature Publishing Group UK