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.

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.

Metrics

  • 1,778
    views
  • 224
    downloads
  • 6
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  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

Further reading

    1. Cell Biology
    2. Medicine
    Judith Hüttemeister, Franziska Rudolph ... Michael Gotthardt
    Research Article

    The giant striated muscle protein titin integrates into the developing sarcomere to form a stable myofilament system that is extended as myocytes fuse. The logistics underlying myofilament assembly and disassembly have started to emerge with the possibility to follow labeled sarcomere components. Here, we generated the mCherry knock-in at titin’s Z-disk to study skeletal muscle development and remodeling. We find titin’s integration into the sarcomere tightly regulated and its unexpected mobility facilitating a homogeneous distribution of titin after cell fusion – an integral part of syncytium formation and maturation of skeletal muscle. In adult mCherry-titin mice, treatment of muscle injury by implantation of titin-eGFP myoblasts reveals how myocytes integrate, fuse, and contribute to the continuous myofilament system across cell boundaries. Unlike in immature primary cells, titin proteins are retained at the proximal nucleus and do not diffuse across the whole syncytium with implications for future cell-based therapies of skeletal muscle disease.

    1. Medicine
    2. Neuroscience
    Chi Zhang, Qian Huang ... Yun Guan
    Research Article

    Pain after surgery causes significant suffering. Opioid analgesics cause severe side effects and accidental death. Therefore, there is an urgent need to develop non-opioid therapies for managing post-surgical pain. Local application of Clarix Flo (FLO), a human amniotic membrane (AM) product, attenuated established post-surgical pain hypersensitivity without exhibiting known side effects of opioid use in mice. This effect was achieved through direct inhibition of nociceptive dorsal root ganglion (DRG) neurons via CD44-dependent pathways. We further purified the major matrix component, the heavy chain-hyaluronic acid/pentraxin 3 (HC-HA/PTX3) from human AM that has greater purity and water solubility than FLO. HC-HA/PTX3 replicated FLO-induced neuronal and pain inhibition. Mechanistically, HC-HA/PTX3-induced cytoskeleton rearrangements to inhibit sodium current and high-voltage activated calcium current on nociceptive DRG neurons, suggesting it is a key bioactive component mediating pain relief. Collectively, our findings highlight the potential of naturally derived biologics from human birth tissues as an effective non-opioid treatment for post-surgical pain. Moreover, we unravel the underlying neuronal mechanisms of pain inhibition induced by FLO and HC-HA/PTX3.