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Sex differences in allometry for phenotypic traits in mice indicate that females are not scaled males

Author

Listed:
  • Laura A. B. Wilson

    (University of New South Wales
    The Australian National University)

  • Susanne R. K. Zajitschek

    (University of New South Wales
    Liverpool John Moores University)

  • Malgorzata Lagisz

    (University of New South Wales)

  • Jeremy Mason

    (Melio Healthcare Ltd.
    European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus)

  • Hamed Haselimashhadi

    (European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus)

  • Shinichi Nakagawa

    (University of New South Wales)

Abstract

Sex differences in the lifetime risk and expression of disease are well-known. Preclinical research targeted at improving treatment, increasing health span, and reducing the financial burden of health care, has mostly been conducted on male animals and cells. The extent to which sex differences in phenotypic traits are explained by sex differences in body weight remains unclear. We quantify sex differences in the allometric relationship between trait value and body weight for 363 phenotypic traits in male and female mice, recorded in >2 million measurements from the International Mouse Phenotyping Consortium. We find sex differences in allometric parameters (slope, intercept, residual SD) are common (73% traits). Body weight differences do not explain all sex differences in trait values but scaling by weight may be useful for some traits. Our results show sex differences in phenotypic traits are trait-specific, promoting case-specific approaches to drug dosage scaled by body weight in mice.

Suggested Citation

  • Laura A. B. Wilson & Susanne R. K. Zajitschek & Malgorzata Lagisz & Jeremy Mason & Hamed Haselimashhadi & Shinichi Nakagawa, 2022. "Sex differences in allometry for phenotypic traits in mice indicate that females are not scaled males," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-35266-6
    DOI: 10.1038/s41467-022-35266-6
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    1. Anna Heath & Petros Pechlivanoglou, 2022. "Prioritizing Research in an Era of Personalized Medicine: The Potential Value of Unexplained Heterogeneity," Medical Decision Making, , vol. 42(5), pages 649-660, July.
    2. Alison M. Kim & Candace M. Tingen & Teresa K. Woodruff, 2010. "Sex bias in trials and treatment must end," Nature, Nature, vol. 465(7299), pages 688-689, June.
    3. Holger Schielzeth & Wolfgang Forstmeier, 2009. "Conclusions beyond support: overconfident estimates in mixed models," Behavioral Ecology, International Society for Behavioral Ecology, vol. 20(2), pages 416-420.
    4. Joost van Hoof, 2015. "Female thermal demand," Nature Climate Change, Nature, vol. 5(12), pages 1029-1030, December.
    5. Viechtbauer, Wolfgang, 2010. "Conducting Meta-Analyses in R with the metafor Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i03).
    6. Andrea Cardini & P. David Polly, 2013. "Larger mammals have longer faces because of size-related constraints on skull form," Nature Communications, Nature, vol. 4(1), pages 1-7, December.
    7. Janine A. Clayton & Francis S. Collins, 2014. "Policy: NIH to balance sex in cell and animal studies," Nature, Nature, vol. 509(7500), pages 282-283, May.
    8. Jessica Gurevitch & Julia Koricheva & Shinichi Nakagawa & Gavin Stewart, 2018. "Meta-analysis and the science of research synthesis," Nature, Nature, vol. 555(7695), pages 175-182, March.
    9. Irving Zucker & Annaliese K. Beery, 2010. "Males still dominate animal studies," Nature, Nature, vol. 465(7299), pages 690-690, June.
    10. Natasha A. Karp & Jeremy Mason & Arthur L. Beaudet & Yoav Benjamini & Lynette Bower & Robert E. Braun & Steve D.M. Brown & Elissa J. Chesler & Mary E. Dickinson & Ann M. Flenniken & Helmut Fuchs & Mar, 2017. "Prevalence of sexual dimorphism in mammalian phenotypic traits," Nature Communications, Nature, vol. 8(1), pages 1-12, August.
    11. Mary E. Dickinson & Ann M. Flenniken & Xiao Ji & Lydia Teboul & Michael D. Wong & Jacqueline K. White & Terrence F. Meehan & Wolfgang J. Weninger & Henrik Westerberg & Hibret Adissu & Candice N. Baker, 2016. "High-throughput discovery of novel developmental phenotypes," Nature, Nature, vol. 537(7621), pages 508-514, September.
    12. Takuji Usui & Malcolm R Macleod & Sarah K McCann & Alistair M Senior & Shinichi Nakagawa, 2021. "Meta-analysis of variation suggests that embracing variability improves both replicability and generalizability in preclinical research," PLOS Biology, Public Library of Science, vol. 19(5), pages 1-20, May.
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