Repeated cannabidiol treatment affects neuroplasticity and endocannabinoid signaling in the prefrontal cortex of the Flinders Sensitive Line (FSL) rat model of depression.

Delayed therapeutic responses and limited efficacy are the main challenges of existing antidepressant drugs, thereby incentivizing the search for new potential treatments. Cannabidiol (CBD), non-psychotomimetic component of cannabis, has shown promising antidepressant effects in different rodent models, but its mechanism of action remains unclear. Herein, we investigated the antidepressant-like effects of repeated CBD treatment on behavior, neuroplasticity markers and lipidomic profile in the prefrontal cortex (PFC) of Flinders Sensitive Line (FSL), a genetic animal model of depression, and their control counterparts Flinders Resistant Line (FRL) rats. Male FSL animals were treated with CBD (10 mg/kg; i.p.) or vehicle (7 days) followed by Open Field Test (OFT) and the Forced Swimming Test (FST). The PFC was analyzed by a) western blotting to assess markers of synaptic plasticity and cannabinoid signaling in synaptosome and cytosolic fractions; b) mass spectrometry-based lipidomics to investigate endocannabinoid levels (eCB). CBD attenuated the increased immobility observed in FSL, compared to FRL in FST, without changing the locomotor behavior in the OFT. In synaptosomes, CBD increased ERK1, mGluR5, and Synaptophysin, but failed to reverse the reduced CB1 and CB2 levels in FSL rats. In the cytosolic fraction, CBD increased ERK2 and decreased mGluR5 expression in FSL rats. Surprisingly, there were no significant changes in eCB levels in response to CBD treatment. These findings suggest that CBD effects in FSL animals are associated with changes in synaptic plasticity markers involving mGluR5, ERK1, ERK2, and synaptophysin signaling in the PFC, without increasing the levels of endocannabinoids in this brain region.

Quantitative proteomics for investigating psychiatric disorders.

The underlying pathophysiology of psychiatric disorders remains elusive. The use of quantitative proteomics to investigate disease-specific protein signatures holds great promise to improve the understanding of psychiatric disorders and identify relevant biomarkers. In this review, we discuss quantitative proteomic approaches for elucidating molecular mechanisms of psychiatric disorders, i.e. anxiety, schizophrenia, bipolar disorder and depression, by studying specimens from animal models and patients. We present gel-based, label-free and stable isotope-labeling methodologies and evaluate their strengths and limitations in the context of psychiatric research, with a focus on (15)N metabolic labeling of live animals due to its increased accuracy and potential for future applications. We also review biomarker candidate validation methods and present quantitative proteomic studies from the literature that aim to disentangle the molecular pathobiology of psychiatric disorders and identify candidate biomarkers. Finally, we explore the applicability of implementing proteomic methods as a routine diagnostic tool in the clinical laboratory.