1
|
Im YR, Hunter H, de Gracia Hahn D, Duret A, Cheah Q, Dong J, Fairey M, Hjalmarsson C, Li A, Lim HK, McKeown L, Mitrofan CG, Rao R, Utukuri M, Rowe IA, Mann JP. A Systematic Review of Animal Models of NAFLD Finds High-Fat, High-Fructose Diets Most Closely Resemble Human NAFLD. Hepatology 2021; 74:1884-1901. [PMID: 33973269 DOI: 10.1002/hep.31897] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 04/29/2021] [Accepted: 05/04/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND AND AIMS Animal models of human disease are a key component of translational hepatology research, yet there is no consensus on which model is optimal for NAFLD. APPROACH AND RESULTS We generated a database of 3,920 rodent models of NAFLD. Study designs were highly heterogeneous, and therefore, few models had been cited more than once. Analysis of genetic models supported the current evidence for the role of adipose dysfunction and suggested a role for innate immunity in the progression of NAFLD. We identified that high-fat, high-fructose diets most closely recapitulate the human phenotype of NAFLD. There was substantial variability in the nomenclature of animal models: a consensus on terminology of specialist diets is needed. More broadly, this analysis demonstrates the variability in preclinical study design, which has wider implications for the reproducibility of in vivo experiments both in the field of hepatology and beyond. CONCLUSIONS This systematic analysis provides a framework for phenotypic assessment of NAFLD models and highlights the need for increased standardization and replication.
Collapse
Affiliation(s)
- Yu Ri Im
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Harriet Hunter
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Dana de Gracia Hahn
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Amedine Duret
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Qinrong Cheah
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Jiawen Dong
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Madison Fairey
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | | | - Alice Li
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Hong Kai Lim
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Lorcán McKeown
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | | | - Raunak Rao
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Mrudula Utukuri
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Ian A Rowe
- Leeds Institute for Medical Research and Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom
| | - Jake P Mann
- Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| |
Collapse
|
2
|
Hunter H, de Gracia Hahn D, Duret A, Im YR, Cheah Q, Dong J, Fairey M, Hjalmarsson C, Li A, Lim HK, McKeown L, Mitrofan CG, Rao R, Utukuri M, Rowe IA, Mann JP. Weight loss, insulin resistance, and study design confound results in a meta-analysis of animal models of fatty liver. eLife 2020; 9:56573. [PMID: 33063664 PMCID: PMC7647398 DOI: 10.7554/elife.56573] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Accepted: 10/15/2020] [Indexed: 12/30/2022] Open
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.
Collapse
Affiliation(s)
- Harriet Hunter
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Dana de Gracia Hahn
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Amedine Duret
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Yu Ri Im
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Qinrong Cheah
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Jiawen Dong
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Madison Fairey
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | | | - Alice Li
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Hong Kai Lim
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Lorcan McKeown
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | | | - Raunak Rao
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Mrudula Utukuri
- School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Ian A Rowe
- Leeds Institute for Medical Research & Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom
| | - Jake P Mann
- Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
| |
Collapse
|