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Apparent latent structure within the UK Biobank sample has implications for epidemiological analysis

Author

Listed:
  • Simon Haworth

    (University of Bristol)

  • Ruth Mitchell

    (University of Bristol)

  • Laura Corbin

    (University of Bristol)

  • Kaitlin H. Wade

    (University of Bristol)

  • Tom Dudding

    (University of Bristol)

  • Ashley Budu-Aggrey

    (University of Bristol)

  • David Carslake

    (University of Bristol)

  • Gibran Hemani

    (University of Bristol)

  • Lavinia Paternoster

    (University of Bristol)

  • George Davey Smith

    (University of Bristol)

  • Neil Davies

    (University of Bristol)

  • Daniel J. Lawson

    (University of Bristol)

  • Nicholas Timpson

    (University of Bristol
    Avon Longitudinal Study of Parents and Children)

Abstract

Large studies use genotype data to discover genetic contributions to complex traits and infer relationships between those traits. Co-incident geographical variation in genotypes and health traits can bias these analyses. Here we show that single genetic variants and genetic scores composed of multiple variants are associated with birth location within UK Biobank and that geographic structure in genotype data cannot be accounted for using routine adjustment for study centre and principal components derived from genotype data. We find that major health outcomes appear geographically structured and that coincident structure in health outcomes and genotype data can yield biased associations. Understanding and accounting for this phenomenon will be important when making inference from genotype data in large studies.

Suggested Citation

  • Simon Haworth & Ruth Mitchell & Laura Corbin & Kaitlin H. Wade & Tom Dudding & Ashley Budu-Aggrey & David Carslake & Gibran Hemani & Lavinia Paternoster & George Davey Smith & Neil Davies & Daniel J. , 2019. "Apparent latent structure within the UK Biobank sample has implications for epidemiological analysis," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-018-08219-1
    DOI: 10.1038/s41467-018-08219-1
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    Cited by:

    1. Gianmarco Mignogna & Caitlin E. Carey & Robbee Wedow & Nikolas Baya & Mattia Cordioli & Nicola Pirastu & Rino Bellocco & Kathryn Fiuza Malerbi & Michel G. Nivard & Benjamin M. Neale & Raymond K. Walte, 2023. "Patterns of item nonresponse behaviour to survey questionnaires are systematic and associated with genetic loci," Nature Human Behaviour, Nature, vol. 7(8), pages 1371-1387, August.
    2. Mingxuan Cai & Zhiwei Wang & Jiashun Xiao & Xianghong Hu & Gang Chen & Can Yang, 2023. "XMAP: Cross-population fine-mapping by leveraging genetic diversity and accounting for confounding bias," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    3. 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.
    4. Dixon, Padraig & Harrison, Sean & Hollingworth, William & Davies, Neil M. & Davey Smith, George, 2022. "Estimating the causal effect of liability to disease on healthcare costs using Mendelian Randomization," Economics & Human Biology, Elsevier, vol. 46(C).
    5. Hyeokmoon Kweon & Casper A.P. Burik & Richard Karlsson Linner & Ronald de Vlaming & Aysu Okbay & Daphne Martschenko & Kathryn Paige Harden & Thomas A. DiPrete & Philipp D. Koellinger, 2020. "Genetic Fortune: Winning or Losing Education, Income, and Health," Tinbergen Institute Discussion Papers 20-053/V, Tinbergen Institute, revised 01 Dec 2020.
    6. Dixon, Padraig & Hollingworth, William & Harrison, Sean & Davies, Neil M. & Davey Smith, George, 2020. "Mendelian Randomization analysis of the causal effect of adiposity on hospital costs," Journal of Health Economics, Elsevier, vol. 70(C).
    7. Maria Niarchou & Daniel E. Gustavson & J. Fah Sathirapongsasuti & Manuel Anglada-Tort & Else Eising & Eamonn Bell & Evonne McArthur & Peter Straub & J. Devin McAuley & John A. Capra & Fredrik Ullén & , 2022. "Genome-wide association study of musical beat synchronization demonstrates high polygenicity," Nature Human Behaviour, Nature, vol. 6(9), pages 1292-1309, September.
    8. 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).

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