RT Journal Article
SR Electronic
T1 Within-family studies for Mendelian randomization: avoiding dynastic, assortative mating, and population stratification biases
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 602516
DO 10.1101/602516
A1 Ben Brumpton
A1 Eleanor Sanderson
A1 Fernando Pires Hartwig
A1 Sean Harrison
A1 Gunnhild Åberge Vie
A1 Yoonsu Cho
A1 Laura D Howe
A1 Amanda Hughes
A1 Dorret I Boomsma
A1 Alexandra Havdahl
A1 John Hopper
A1 Michael Neale
A1 Michel G Nivard
A1 Nancy L Pedersen
A1 Chandra A Reynolds
A1 Elliot M Tucker-Drob
A1 Andrew Grotzinger
A1 Laurence Howe
A1 Tim Morris
A1 Shuai Li
A1 MR within-family Consortium
A1 Wei-Min Chen
A1 Johan Håkon Bjørngaard
A1 Kristian Hveem
A1 Cristen Willer
A1 David M Evans
A1 Jaakko Kaprio
A1 Bjørn Olav Åsvol
A1 George Davey Smith
A1 Bjørn Olav Åsvold
A1 Gibran Hemani
A1 Neil M Davies
YR 2019
UL http://biorxiv.org/content/early/2019/07/05/602516.abstract
AB Mendelian randomization (MR) is a widely-used method for causal inference using genetic data. Mendelian randomization studies of unrelated individuals may be susceptible to bias from family structure, for example, through dynastic effects which occur when parental genotypes directly affect offspring phenotypes. Here we describe methods for within-family Mendelian randomization and through simulations show that family-based methods can overcome bias due to dynastic effects. We illustrate these issues empirically using data from 61,008 siblings from the UK Biobank and Nord-Trøndelag Health Study. Both within-family and population-based Mendelian randomization analyses reproduced established effects of lower BMI reducing risk of diabetes and high blood pressure. However, while MR estimates from population-based samples of unrelated individuals suggested that taller height and lower BMI increase educational attainment, these effects largely disappeared in within-family MR analyses. We found differences between population-based and within-family based estimates, indicating the importance of controlling for family effects and population structure in Mendelian randomization studies.