4.2 Article

Emerging evidence for the antidepressant effect of cannabidiol and the underlying molecular mechanisms

期刊

JOURNAL OF CHEMICAL NEUROANATOMY
卷 98, 期 -, 页码 104-116

出版社

ELSEVIER
DOI: 10.1016/j.jchemneu.2019.04.006

关键词

Cannabidiol; Antidepressant; BDNF; Depression; Neuroplasticity; Neurochemical

资金

  1. National Institute of Science and Translational Medicine, CNPq [465458/2014-9]
  2. Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior - Brazil (CAPES) [001]
  3. FAPESP [2012/17626-7]
  4. Independent Research Fund Denmark [8020-00310B]
  5. Aarhus University Research Foundation, Denmark (AU-IDEAS initiative (eMOOD))
  6. EU Horizon 2020 (ExEDE)
  7. Marie Sklodowska-Curie aclons under the European Union's Horizon 2020 [754513]
  8. Aarhus University Research Foundation

向作者/读者索取更多资源

Significant limitations with the currently available antidepressant treatment strategies have inspired research on finding new and more efficient drugs to treat depression. Cannabidiol (CBD) is a non-psychotomimetic component of Cannabis sativa, and emerges in this regard as a promising compound. In 2010, we were the first laboratory to demonstrate that CBD is effective in animal models of predictive of antidepressant effect, a finding now confirmed by several other groups. Recent evidence suggests that CBD promotes both a rapid and a sustained antidepressant effect in animal models. CBD has a complex pharmacology, with the ability to interact with multiple neurotransmitter systems involved in depression, including the serotonergic, glutamatergic, and endocannabinoid systems. Moreover, CBD induces cellular and molecular changes in brain regions related to depression neurobiology, such as increased Brain Derived Neurotrophic Factor (BDNF) levels and synaptogenesis in the medial prefrontal cortex, as well as it increases neurogenesis in the hippocampus. This review presents a comprehensive critical overview of the current literature related to the antidepressant effects of CBD, with focus at the possible mechanisms. Finally, challenges and perspectives for future research are discussed.

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