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

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http://hdl.handle.net/10138/319105

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Within-family Consortium , 23andMe Res Team , Brumpton , B , Sanderson , E , Heilbron , K , Kaprio , J & Davies , N M 2020 , ' Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses ' , Nature Communications , vol. 11 , no. 1 , 3519 . https://doi.org/10.1038/s41467-020-17117-4

Title: Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses
Author: Within-family Consortium; 23andMe Res Team; Brumpton, Ben; Sanderson, Eleanor; Heilbron, Karl; Kaprio, Jaakko; Davies, Neil M.
Contributor: University of Helsinki, Institute for Molecular Medicine Finland
Date: 2020-07-14
Language: eng
Number of pages: 13
Belongs to series: Nature Communications
ISSN: 2041-1723
URI: http://hdl.handle.net/10138/319105
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-TrOndelag 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. Family-based study designs have been applied to resolve confounding by population stratification, dynastic effects and assortative mating in genetic association analyses. Here, Brumpton et al. describe theory and simulations for overcoming such biases in Mendelian randomization through within-family studies.
Subject: BODY-MASS INDEX
EDUCATIONAL-ATTAINMENT
ASSOCIATION
HEIGHT
INFERENCE
LINKAGE
TRAITS
COMMON
DISEQUILIBRIUM
TRANSMISSION
3141 Health care science
3142 Public health care science, environmental and occupational health
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