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Two polygenic mouse models of major depressive disorders identify TMEM161Bas a potential biomarker of disease in humans

Authors :
El Yacoubi, Malika
Altersitz, Claire
Latapie, Violaine
Rizkallah, Elari
Arthaud, Sébastien
Bougarel, Laure
Pereira, Marcela
Wierinckx, Anne
El-Hage, Wissam
Belzeaux, Raoul
Turecki, Gustavo
Svenningsson, Per
Martin, Benoît
Lachuer, Joël
Vaugeois, Jean-Marie
Jamain, Stéphane
Source :
Neuropsychopharmacology; 20240101, Issue: Preprints p1-11, 11p
Publication Year :
2024

Abstract

Treatments are only partially effective in major depressive disorders (MDD) but no biomarker exists to predict symptom improvement in patients. Animal models are essential tools in the development of antidepressant medications, but while recent genetic studies have demonstrated the polygenic contribution to MDD, current models are limited to either mimic the effect of a single gene or environmental factor. We developed in the past a model of depressive-like behaviors in mice (H/Rouen), using selective breeding based on behavioral reaction after an acute mild stress in the tail suspension test. Here, we propose a new mouse model of depression (H-TST) generated from a more complex genetic background and based on the same selection process. We first demonstrated that H/Rouen and H-TST mice had similar phenotypes and were more sensitive to glutamate-related antidepressant medications than selective serotonin reuptake inhibitors. We then conducted an exome sequencing on the two mouse models and showed that they had damaging variants in 174 identical genes, which have also been associated with MDD in humans. Among these genes, we showed a higher expression level of Tmem161bin brain and blood of our two mouse models. Changes in TMEM161Bexpression level was also observed in blood of MDD patients when compared with controls, and after 8-week treatment with duloxetine, mainly in good responders to treatment. Altogether, our results introduce H/Rouen and H-TST as the two first polygenic animal models of MDD and demonstrate their ability to identify biomarkers of the disease and to develop rapid and effective antidepressant medications.

Details

Language :
English
ISSN :
0893133X and 1740634X
Issue :
Preprints
Database :
Supplemental Index
Journal :
Neuropsychopharmacology
Publication Type :
Periodical
Accession number :
ejs65446055
Full Text :
https://doi.org/10.1038/s41386-024-01811-8