Mouse models of diabetes-related ulcers: a systematic review and network meta-analysis.

Animal models Diabetes Diabetic foot ulcers Network meta-analysis Wound healing

Journal

EBioMedicine
ISSN: 2352-3964
Titre abrégé: EBioMedicine
Pays: Netherlands
ID NLM: 101647039

Informations de publication

Date de publication:
Dec 2023
Historique:
received: 24 04 2023
revised: 09 10 2023
accepted: 13 10 2023
medline: 22 1 2024
pubmed: 22 1 2024
entrez: 22 1 2024
Statut: ppublish

Résumé

Diabetic foot ulcers (DFUs) are a common complication of diabetes, associated with important morbidity. Appropriate animal models of DFUs may improve drug development, and subsequently the success rate of clinical trials. However, while many models have been proposed, they are extremely heterogeneous, and no standard has emerged. We thus propose a systematic review with a network meta-analysis (NMA) to gather direct and indirect evidence, and compare the different mouse models of diabetes-related ulcers. The systematic search was performed in Pubmed and Embase. The main outcomes were wound size measurement at days 3, 7, 11 and 15 (±1 day). The risk of bias and methodological quality of all included studies was assessed by using the Systematic Review Center for Laboratory animal Experimentation (SYRCLE) risk of bias tool. Meta-regressions were done on prespecified variables, including mouse strain, type of ulcer, sex, age, and use of a splint. We included 295 studies. Among all models, only db/db, ob/ob, streptozotocin (STZ), and STZ + high fat diet mice showed a significantly delayed wound healing, compared with controls, at each time point. Age, sex and ulcer type had influence on wound healing, although not at all time points. In conclusion, the db/db model is associated with the largest delay in wound healing The STZ model also exhibits significantly decreased wound healing. STZ + high fat diet and ob/ob mice may also be relevant models of diabetes-related ulcers, although the results rely on a more limited number of studies. This work was funded by the Agence Nationale de la Recherche (grant ANR-18-CE17-0017).

Sections du résumé

BACKGROUND BACKGROUND
Diabetic foot ulcers (DFUs) are a common complication of diabetes, associated with important morbidity. Appropriate animal models of DFUs may improve drug development, and subsequently the success rate of clinical trials. However, while many models have been proposed, they are extremely heterogeneous, and no standard has emerged. We thus propose a systematic review with a network meta-analysis (NMA) to gather direct and indirect evidence, and compare the different mouse models of diabetes-related ulcers.
METHODS METHODS
The systematic search was performed in Pubmed and Embase. The main outcomes were wound size measurement at days 3, 7, 11 and 15 (±1 day). The risk of bias and methodological quality of all included studies was assessed by using the Systematic Review Center for Laboratory animal Experimentation (SYRCLE) risk of bias tool. Meta-regressions were done on prespecified variables, including mouse strain, type of ulcer, sex, age, and use of a splint.
FINDINGS RESULTS
We included 295 studies. Among all models, only db/db, ob/ob, streptozotocin (STZ), and STZ + high fat diet mice showed a significantly delayed wound healing, compared with controls, at each time point. Age, sex and ulcer type had influence on wound healing, although not at all time points.
INTERPRETATION CONCLUSIONS
In conclusion, the db/db model is associated with the largest delay in wound healing The STZ model also exhibits significantly decreased wound healing. STZ + high fat diet and ob/ob mice may also be relevant models of diabetes-related ulcers, although the results rely on a more limited number of studies.
FUNDING BACKGROUND
This work was funded by the Agence Nationale de la Recherche (grant ANR-18-CE17-0017).

Identifiants

pubmed: 38251464
pii: S2352-3964(23)00422-X
doi: 10.1016/j.ebiom.2023.104856
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

104856

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of interests The authors declare no conflict of interest.

Auteurs

Axel Couturier (A)

Univ. Grenoble Alpes, Inserm U1300, HP2, Grenoble 38000, France.

Clément Calissi (C)

Univ. Grenoble Alpes, Inserm U1300, HP2, Grenoble 38000, France.

Jean-Luc Cracowski (JL)

Univ. Grenoble Alpes, Inserm U1300, HP2, Grenoble 38000, France; Univ. Grenoble Alpes, Inserm CIC1406, CHU Grenoble Alpes, Grenoble 38000, France.

Dominique Sigaudo-Roussel (D)

University of Lyon, CNRS, UMR 5305, LBTI, Lyon 69000, France.

Charles Khouri (C)

Univ. Grenoble Alpes, Inserm U1300, HP2, Grenoble 38000, France; Univ. Grenoble Alpes, Inserm CIC1406, CHU Grenoble Alpes, Grenoble 38000, France.

Matthieu Roustit (M)

Univ. Grenoble Alpes, Inserm U1300, HP2, Grenoble 38000, France; Univ. Grenoble Alpes, Inserm CIC1406, CHU Grenoble Alpes, Grenoble 38000, France. Electronic address: MRoustit@chu-grenoble.fr.

Classifications MeSH