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Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis [version 2; peer review: 1 approved, 2 approved with reservations]

Authors :
Spyridon Siafis
Johannes Schneider-Thoma
Alexandra Bannach-Brown
Oliver D. Howes
Virginia Chiocchia
Ulf Tölch
Natascha I. Drude
Sabine M. Hölter
Andrea de Bartolomeis
Anthony C. Vernon
Georgia Salanti
Sridhar Natesan
Stefan Leucht
Irene Bighelli
Sameer Jauhar
Ioannis Mantas
Josef Priller
Francesca Tinsdeall
Wulf-Peter Hansen
Fiona J. Ramage
Nobuyuki Nomura
Malcolm R. Macleod
Source :
F1000Research, Vol 13 (2025)
Publication Year :
2025
Publisher :
F1000 Research Ltd, 2025.

Abstract

Background Muscarinic receptor agonism and positive allosteric modulation is a promising mechanism of action for treating psychosis, not present in most D2R-blocking antipsychotics. Xanomeline, an M1/M4-preferring agonist, has shown efficacy in late-stage clinical trials, with more compounds being investigated. Therefore, we aim to synthesize evidence on the preclinical efficacy of muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis to provide unique insights and evidence-based information to guide drug development. Methods We plan a systematic review and meta-analysis of in vivo animal studies comparing muscarinic receptor agonists or positive allosteric modulators with control conditions and existing D2R-blocking antipsychotics in animals subjected to any method that induces behavioural changes of relevance for psychosis. We will identify eligible studies by searching multiple electronic databases. At least two independent reviewers will conduct the study selection and data extraction using prespecified forms and assess the risk of bias with the SYRCLE’s tool. Our primary outcomes include locomotor activity and prepulse inhibition measured with standardized mean differences. We will examine other behavioural readouts of relevance for psychosis as secondary outcomes, such as social interaction and cognitive function. We will synthesize the data using multi-level meta-analysis with a predefined random-effects structure, considering the non-independence of the data. In meta-regressions we will explore potential sources of heterogeneity from a predefined list of characteristics of the animal population, model, and intervention. We will assess the confidence in the evidence considering a self-developed instrument thatconsiders the internal and external validity of the evidence. Protocol registration PROSPERO-ID: CRD42024520914

Details

Language :
English
ISSN :
20461402
Volume :
13
Database :
Directory of Open Access Journals
Journal :
F1000Research
Publication Type :
Academic Journal
Accession number :
edsdoj.701c1c0279bb45f2861c199cba7cbd42
Document Type :
article
Full Text :
https://doi.org/10.12688/f1000research.155356.2