Identifying fast-onset antidepressants using rodent models

心理学 啮齿动物模型 啮齿动物 医学 精神药理学 神经科学 精神科 生物 内科学 生态学
作者
Marcia J. Ramaker,Stephanie C. Dulawa
出处
期刊:Molecular Psychiatry [Springer Nature]
卷期号:22 (5): 656-665 被引量:161
标识
DOI:10.1038/mp.2017.36
摘要

Depression is a leading cause of disability worldwide and a major contributor to the burden of suicide. A major limitation of classical antidepressants is that 2–4 weeks of continuous treatment is required to elicit therapeutic effects, prolonging the period of depression, disability and suicide risk. Therefore, the development of fast-onset antidepressants is crucial. Preclinical identification of fast-onset antidepressants requires animal models that can accurately predict the delay to therapeutic onset. Although several well-validated assay models exist that predict antidepressant potential, few thoroughly tested animal models exist that can detect therapeutic onset. In this review, we discuss and assess the validity of seven rodent models currently used to assess antidepressant onset: olfactory bulbectomy, chronic mild stress, chronic forced swim test, novelty-induced hypophagia (NIH), novelty-suppressed feeding (NSF), social defeat stress, and learned helplessness. We review the effects of classical antidepressants in these models, as well as six treatments that possess fast-onset antidepressant effects in the clinic: electroconvulsive shock therapy, sleep deprivation, ketamine, scopolamine, GLYX-13 and pindolol used in conjunction with classical antidepressants. We also discuss the effects of several compounds that have yet to be tested in humans but have fast-onset antidepressant-like effects in one or more of these antidepressant onset sensitive models. These compounds include selective serotonin (5-HT)2C receptor antagonists, a 5-HT4 receptor agonist, a 5-HT7 receptor antagonist, NMDA receptor antagonists, a TREK-1 receptor antagonist, mGluR antagonists and (2R,6R)-HNK. Finally, we provide recommendations for identifying fast-onset antidepressants using rodent behavioral models and molecular approaches.

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