Evidence map›Paper›PMID 38326457›Full record

ArticleNeuropsychopharmacology : official publication of the American College of Neuropsychopharmacology2024

Two polygenic mouse models of major depressive disorders identify TMEM161B as a potential biomarker of disease in humans.

Malika El Yacoubi, Claire Altersitz, Violaine Latapie, Elari Rizkallah, Sébastien Arthaud, Laure Bougarel, Marcela Pereira, Anne Wierinckx, Wissam El-Hage, Raoul Belzeaux and 6 more

Open access · greenAbstract read
In one paragraph

Article in Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 50% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 7 institutions in 3 countries.

Malika El YacoubiUniv Paris Est Créteil, INSERM, IMRB, Translational Neuropsychiatry, F-94010, Créteil, France.
Claire AltersitzUniv Paris Est Créteil, INSERM, IMRB, Translational Neuropsychiatry, F-94010, Créteil, France.ORCID http://orcid.org/0009-0002-0815-6133
Violaine LatapieUniv Paris Est Créteil, INSERM, IMRB, Translational Neuropsychiatry, F-94010, Créteil, France.
Elari RizkallahUniv Paris Est Créteil, INSERM, IMRB, Translational Neuropsychiatry, F-94010, Créteil, France.
Sébastien ArthaudSLEEP Team, CNRS UMR5292; INSERM U1028; Lyon Neuroscience Research; Center, Lyon, F-69372, France.ORCID http://orcid.org/0000-0001-7271-5468
Laure BougarelUniv Paris Est Créteil, INSERM, IMRB, Translational Neuropsychiatry, F-94010, Créteil, France.
Marcela PereiraDepartment of Clinical Neuroscience, Karolinska Institute, Solna, Sweden.ORCID http://orcid.org/0000-0002-0809-780X
Anne WierinckxProfileXpert, SFR Santé Lyon-Est, UCBL UMS 3453 CNRS, US7 INSERM, Lyon, France.
Wissam El-HageUMR 1253, iBrain, Université de Tours, CHRU de Tours, INSERM, Tours, France.ORCID http://orcid.org/0000-0003-3877-0855
Raoul BelzeauxPôle Universitaire de Psychiatrie, CHU de Montpellier, Montpellier, France.
Gustavo TureckiMcGill Group for Suicide Studies, Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada.ORCID http://orcid.org/0000-0003-4075-2736
Per SvenningssonDepartment of Clinical Neuroscience, Karolinska Institute, Solna, Sweden.ORCID http://orcid.org/0000-0001-6727-3802
Benoît MartinUniv Rennes, Inserm, LTSI (Laboratoire de Traitement du Signal et de l'Image), UMR-1099, F-35000, Rennes, France.
Joël LachuerProfileXpert, SFR Santé Lyon-Est, UCBL UMS 3453 CNRS, US7 INSERM, Lyon, France.
Jean-Marie Vaugeois *Univ Rouen Normandie, Université Caen Normandie, Normandie Univ, ABTE UR 4651, F-76000, Rouen, France.ORCID http://orcid.org/0000-0001-8296-672X
Stéphane Jamain *Univ Paris Est Créteil, INSERM, IMRB, Translational Neuropsychiatry, F-94010, Créteil, France. stephane.jamain@inserm.fr.ORCID http://orcid.org/0000-0002-4321-4100
Inserm · FRUniversité Claude Bernard Lyon 1 · FRKarolinska Institutet · SECentre Hospitalier Universitaire de Montpellier · FRDouglas Mental Health University Institute · CANormandie Université · FRUniversité de Tours · FR

Funding

Agence Nationale de la Recherche (French National Research Agency) ANR-12-SAMA-0012-01Fondation de France 00081240 and 00091264
6 · The paper itself

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 Tmem161b in brain and blood of our two mouse models. Changes in TMEM161B expression 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.

Indexed as

Antidepressive AgentsBiomarkersDisease Models, AnimalMajor Depressive DisorderMultifactorial InheritanceAdultAnimalsBrainFemaleHumansMaleMembrane ProteinsMiceMice, Inbred C57BLMiddle AgedAntidepressive AgentsBiomarkersMembrane Proteins

Identifiers

PMID38326457
PMCPMC11109134
OpenAlexW4391604125

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.