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

Author

Listed:
  • Ben Brumpton

    (Norwegian University of Science and Technology
    University of Bristol
    Trondheim University Hospital)

  • Eleanor Sanderson

    (University of Bristol
    University of Bristol, Barley House, Oakfield Grove)

  • Karl Heilbron

    (23andMe, Inc.)

  • Fernando Pires Hartwig

    (University of Bristol
    Federal University of Pelotas)

  • Sean Harrison

    (University of Bristol
    University of Bristol, Barley House, Oakfield Grove)

  • Gunnhild Åberge Vie

    (Norwegian University of Science and Technology)

  • Yoonsu Cho

    (University of Bristol
    University of Bristol, Barley House, Oakfield Grove)

  • Laura D. Howe

    (University of Bristol
    University of Bristol, Barley House, Oakfield Grove)

  • Amanda Hughes

    (University of Bristol
    University of Bristol, Barley House, Oakfield Grove)

  • Dorret I. Boomsma

    (Vrije Universiteit Amsterdam)

  • Alexandra Havdahl

    (University of Bristol
    Lovisenberg Diaconal Hospital
    Norwegian Institute of Public Health)

  • John Hopper

    (The University of Melbourne)

  • Michael Neale

    (Virginia Commonwealth University)

  • Michel G. Nivard

    (Vrije Universiteit Amsterdam)

  • Nancy L. Pedersen

    (Karolinska Institutet)

  • Chandra A. Reynolds

    (University of California Riverside)

  • Elliot M. Tucker-Drob

    (University of Texas at Austin)

  • Andrew Grotzinger

    (University of Texas at Austin)

  • Laurence Howe

    (University of Bristol
    University of Bristol, Barley House, Oakfield Grove)

  • Tim Morris

    (University of Bristol
    University of Bristol, Barley House, Oakfield Grove)

  • Shuai Li

    (The University of Melbourne
    University of Cambridge, Strangeways Research Laboratory, Worts Causeway)

  • Adam Auton

    (23andMe, Inc.)

  • Frank Windmeijer

    (University of Bristol
    University of Bristol)

  • Wei-Min Chen

    (University of Virginia)

  • Johan Håkon Bjørngaard

    (Norwegian University of Science and Technology
    Nord University)

  • Kristian Hveem

    (Norwegian University of Science and Technology)

  • Cristen Willer

    (University of Michigan
    University of Michigan
    University of Michigan)

  • David M. Evans

    (University of Bristol
    University of Queensland)

  • Jaakko Kaprio

    (University of Helsinki
    University of Helsinki)

  • George Davey Smith

    (University of Bristol
    University of Bristol, Barley House, Oakfield Grove)

  • Bjørn Olav Åsvold

    (Norwegian University of Science and Technology
    Trondheim University Hospital)

  • Gibran Hemani

    (University of Bristol
    University of Bristol, Barley House, Oakfield Grove)

  • Neil M. Davies

    (Norwegian University of Science and Technology
    University of Bristol
    University of Bristol, Barley House, Oakfield Grove)

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.

Suggested Citation

  • 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 & J, 2020. "Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses," Nature Communications, Nature, vol. 11(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-17117-4
    DOI: 10.1038/s41467-020-17117-4
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    Cited by:

    1. Fartein Ask Torvik & Espen Moen Eilertsen & Laurie J. Hannigan & Rosa Cheesman & Laurence J. Howe & Per Magnus & Ted Reichborn-Kjennerud & Ole A. Andreassen & Pål R. Njølstad & Alexandra Havdahl & Eiv, 2022. "Modeling assortative mating and genetic similarities between partners, siblings, and in-laws," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    2. Liza Darrous & Gibran Hemani & George Davey Smith & Zoltán Kutalik, 2024. "PheWAS-based clustering of Mendelian Randomisation instruments reveals distinct mechanism-specific causal effects between obesity and educational attainment," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    3. Thomas Battram & Tom R. Gaunt & Caroline L. Relton & Nicholas J. Timpson & Gibran Hemani, 2022. "A comparison of the genes and genesets identified by GWAS and EWAS of fifteen complex traits," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    4. Xie, Tao & Zhu, Bin & Li, Hao-ran & Xu, Jin-feng & Mao, Ying, 2024. "Educational attainment, income, and attention deficit hyperactivity disorder: A mediation analysis based on two-step Mendelian randomization," Social Science & Medicine, Elsevier, vol. 345(C).
    5. Daniel J. Benjamin & David Cesarini & Patrick Turley & Alexander Strudwick Young, 2024. "Social-Science Genomics: Progress, Challenges, and Future Directions," NBER Working Papers 32404, National Bureau of Economic Research, Inc.
    6. Hazewinkel, Audinga-Dea & Richmond, Rebecca C. & Wade, Kaitlin H. & Dixon, Padraig, 2022. "Mendelian randomization analysis of the causal impact of body mass index and waist-hip ratio on rates of hospital admission," Economics & Human Biology, Elsevier, vol. 44(C).
    7. Mattia Marchi & Anne Alkema & Charley Xia & Chris H. L. Thio & Li-Yu Chen & Winni Schalkwijk & Gian M. Galeazzi & Silvia Ferrari & Luca Pingani & Hyeokmoon Kweon & Sara Evans-Lacko & W. David Hill & M, 2024. "Investigating the impact of poverty on mental illness in the UK Biobank using Mendelian randomization," Nature Human Behaviour, Nature, vol. 8(9), pages 1771-1783, September.
    8. Jaakko Pehkonen & Jutta Viinikainen & Jaana T. Kari & Petri Böckerman & Terho Lehtimäki & Olli Raitakari, 2021. "Birth weight and adult income: An examination of mediation through adult height and body mass," Health Economics, John Wiley & Sons, Ltd., vol. 30(10), pages 2383-2398, September.

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