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Genome-wide association study of body fat distribution identifies adiposity loci and sex-specific genetic effects

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  • Mathias Rask-Andersen

    (Uppsala University)

  • Torgny Karlsson

    (Uppsala University)

  • Weronica E. Ek

    (Uppsala University)

  • Åsa Johansson

    (Uppsala University)

Abstract

Body mass and body fat composition are of clinical interest due to their links to cardiovascular- and metabolic diseases. Fat stored in the trunk has been suggested to be more pathogenic compared to fat stored in other compartments. In this study, we perform genome-wide association studies (GWAS) for the proportion of body fat distributed to the arms, legs and trunk estimated from segmental bio-electrical impedance analysis (sBIA) for 362,499 individuals from the UK Biobank. 98 independent associations with body fat distribution are identified, 29 that have not previously been associated with anthropometric traits. A high degree of sex-heterogeneity is observed and the effects of 37 associated variants are stronger in females compared to males. Our findings also implicate that body fat distribution in females involves mesenchyme derived tissues and cell types, female endocrine tissues as well as extracellular matrix maintenance and remodeling.

Suggested Citation

  • Mathias Rask-Andersen & Torgny Karlsson & Weronica E. Ek & Åsa Johansson, 2019. "Genome-wide association study of body fat distribution identifies adiposity loci and sex-specific genetic effects," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-018-08000-4
    DOI: 10.1038/s41467-018-08000-4
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    Cited by:

    1. Katherine Carbeck & Peter Arcese & Irby Lovette & Christin Pruett & Kevin Winker & Jennifer Walsh, 2023. "Candidate genes under selection in song sparrows co-vary with climate and body mass in support of Bergmann’s Rule," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    2. Katherine A. Kentistou & Jian’an Luan & Laura B. L. Wittemans & Catherine Hambly & Lucija Klaric & Zoltán Kutalik & John R. Speakman & Nicholas J. Wareham & Timothy J. Kendall & Claudia Langenberg & J, 2023. "Large scale phenotype imputation and in vivo functional validation implicate ADAMTS14 as an adiposity gene," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    3. Alan Le Goallec & Samuel Diai & Sasha Collin & Jean-Baptiste Prost & Théo Vincent & Chirag J. Patel, 2022. "Using deep learning to predict abdominal age from liver and pancreas magnetic resonance images," Nature Communications, Nature, vol. 13(1), pages 1-13, December.

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