Weight loss, insulin resistance, and study design confound results in a meta-analysis of animal models of fatty liver

Abstract

The classical drug development pipeline necessitates studies using animal models of human disease to gauge future efficacy in humans, however there is a low conversion rate from success in animals to humans. Non-alcoholic fatty liver disease (NAFLD) is a complex chronic disease without any established therapies and a major field of animal research. We performed a meta-analysis with meta-regression of 603 interventional rodent studies (10,364 animals) in NAFLD to assess which variables influenced treatment response. Weight loss and alleviation of insulin resistance were consistently associated with improvement in NAFLD. Multiple drug classes that do not affect weight in humans caused weight loss in animals. Other study design variables, such as age of animals and dietary composition, influenced the magnitude of treatment effect. Publication bias may have increased effect estimates by 37-79%. These findings help to explain the challenge of reproducibility and translation within the field of metabolism.

Data availability

The raw dataset used for analysis, including references to individual studies, are available Figure 1 - Source Data and deposited in the Dryad repository at https://doi.org/10.5061/dryad.pzgmsbcgc.R code used for analysis are available in Supplementary Data.Source data files have been provided for Figures 2-8.

The following data sets were generated

Article and author information

Author details

  1. Harriet Hunter

    School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  2. Dana de Gracia Hahn

    School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Amedine Duret

    School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Yu Ri Im

    School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  5. Qinrong Cheah

    School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  6. Jiawen Dong

    School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  7. Madison Fairey

    School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  8. Clarissa Hjalmarsson

    School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  9. Alice Li

    School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  10. Hong Kai Lim

    School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7266-7790
  11. Lorcan McKeown

    School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  12. Claudia-Gabriela Mitrofan

    School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  13. Raunak Rao

    School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6954-575X
  14. Mrudula Utukuri

    School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1510-469X
  15. Ian A Rowe

    Leeds Institute for Medical Research & Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  16. Jake P Mann

    Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
    For correspondence
    jm2032@cam.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4711-9215

Funding

Wellcome Trust (216329/Z/19/Z)

  • Jake P Mann

European Society for Paediatric Research (Young Investigator Start-Up Grant)

  • Jake P Mann

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Joel K Elmquist, University of Texas Southwestern Medical Center, United States

Version history

  1. Received: March 3, 2020
  2. Accepted: October 15, 2020
  3. Accepted Manuscript published: October 16, 2020 (version 1)
  4. Version of Record published: November 6, 2020 (version 2)

Copyright

© 2020, Hunter et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Harriet Hunter
  2. Dana de Gracia Hahn
  3. Amedine Duret
  4. Yu Ri Im
  5. Qinrong Cheah
  6. Jiawen Dong
  7. Madison Fairey
  8. Clarissa Hjalmarsson
  9. Alice Li
  10. Hong Kai Lim
  11. Lorcan McKeown
  12. Claudia-Gabriela Mitrofan
  13. Raunak Rao
  14. Mrudula Utukuri
  15. Ian A Rowe
  16. Jake P Mann
(2020)
Weight loss, insulin resistance, and study design confound results in a meta-analysis of animal models of fatty liver
eLife 9:e56573.
https://doi.org/10.7554/eLife.56573

Share this article

https://doi.org/10.7554/eLife.56573

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