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

Ben Brumpton*, Eleanor Sanderson, Karl Heilbron, Fernando Pires Hartwig, Sean Harrison, Gunnhild Åberge Vie, Yoonsu Cho, Laura D Howe, Amanda Hughes, Dorret I Boomsma, Alexandra Havdahl, John L Hopper, Michael Neale, Michel G Nivard, Nancy L Pedersen, Chandra Reynolds, Elliot M. Tucker-Drob, Laurence Howe, Tim Morris, Shuai LinThe Within-family Consortium, the 23 and Me Research Team, Adam Auton, Frank Windmeijer, Wei-Min Chen, Johan Håkon Bjørngaard, Kristian Hveem, Cristen J Willer, David M Evans, Jaakko A Kaprio, George Davey Smith, Bjørn Olav Åsvold, Gibran Hemani, Neil M Davies*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

39 Citations (Scopus)
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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.
Original languageEnglish
Article number3519 (2020)
Number of pages13
JournalNature Communications
Publication statusPublished - 14 Jul 2020


  • gene-environment correlation
  • BMI
  • height
  • educational attainment
  • genetics
  • confounding


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