A Further Analysis and Commentary on: Profiling Changes in Cortical Astroglial Cells Following Chronic Stress. (August 2019)

• Record Type: Journal Article
• Authors: Coppola, Gianfilippo; Rurak, Gareth M; Simard, Stephanie; Salmaso, Natalina
• Is Part Of: Journal of experimental neuroscience. Volume 13(2019)
• Publication Date: 2019-08
• Subjects: Stress -- plasticity -- mouse -- translatome -- glia -- cortex; Neurosciences -- Periodicals; Nervous system -- Periodicals; Nervous System Diseases; Neurosciences; Nervous system; Neurosciences; Periodicals; Electronic journals; Periodicals; 573.8
• DOI: 10.1177/1179069519870182
• Languages: English
• ISSNs: 1179-0695

Abstract

The neuroplasticity hypothesis of depression proposes that major depressive disorders are related to decreased hippocampal and cortical neural plasticity, which is reversed by antidepressant treatment. Astroglial cells have emerged as key mediators of neural plasticity and are involved in the cause and treatment of depression and anxiety-like behaviors. One of the ways that astroglia modulate neuroplasticity is through the formation and maintenance of perineuronal nets (PNNs). Perineuronal nets are important extracellular matrix components that respond to stress and are implicated in anxiety-like behaviors. Normally, astroglial cells continuously turnover PNNs by degrading and donating PNN proteins; however, chronic stress slows PNN protein degradation and increases cortical PNN expression overall. In this report, we used weighted gene co-expression network analysis and eigengene analysis to further delineate the pathways and key regulators involved in the astroglial-PNN relationship following chronic stress. Our analyses indicate that chronic variable stress induces the expression of PNNs through inhibition of trophic pathways and key transcription factors in astroglial cells. These data further support the integral role of astroglial cells in the neuroplasticity hypothesis of depression through their modulation of anxiety-like behaviors and PNNs.