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      Chronic adolescent exposure to cannabis in mice leads to sex-biased changes in gene expression networks across brain regions

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          Abstract

          During adolescence, frequent and heavy cannabis use can lead to serious adverse health effects and cannabis use disorder (CUD). Rodent models of adolescent exposure to the main psychoactive component of cannabis, delta-9-tetrahydrocannabinol (THC), mimic the behavioral alterations observed in adolescent users. However, the underlying molecular mechanisms remain largely unknown. Here, we treated female and male C57BL6/N mice with high doses of THC during early adolescence and assessed their memory and social behaviors in late adolescence. We then profiled the transcriptome of five brain regions involved in cognitive and addiction-related processes. We applied gene coexpression network analysis and identified gene coexpression modules, termed cognitive modules, that simultaneously correlated with THC treatment and memory traits reduced by THC. The cognitive modules were related to endocannabinoid signaling in the female dorsal medial striatum, inflammation in the female ventral tegmental area, and synaptic transmission in the male nucleus accumbens. Moreover, cross-brain region module-module interaction networks uncovered intra- and inter-region molecular circuitries influenced by THC. Lastly, we identified key driver genes of gene networks associated with THC in mice and genetic susceptibility to CUD in humans. This analysis revealed a common regulatory mechanism linked to CUD vulnerability in the nucleus accumbens of females and males, which shared four key drivers ( Hapln4, Kcnc1, Elavl2, Zcchc12). These genes regulate transcriptional subnetworks implicated in addiction processes, synaptic transmission, brain development, and lipid metabolism. Our study provides novel insights into disease mechanisms regulated by adolescent exposure to THC in a sex- and brain region-specific manner.

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          WGCNA: an R package for weighted correlation network analysis

          Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. Results The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. Conclusion The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at .
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            The endocannabinoid system and the brain.

            The psychoactive constituent in cannabis, Δ(9)-tetrahydrocannabinol (THC), was isolated in the mid-1960s, but the cannabinoid receptors, CB1 and CB2, and the major endogenous cannabinoids (anandamide and 2-arachidonoyl glycerol) were identified only 20 to 25 years later. The cannabinoid system affects both central nervous system (CNS) and peripheral processes. In this review, we have tried to summarize research--with an emphasis on recent publications--on the actions of the endocannabinoid system on anxiety, depression, neurogenesis, reward, cognition, learning, and memory. The effects are at times biphasic--lower doses causing effects opposite to those seen at high doses. Recently, numerous endocannabinoid-like compounds have been identified in the brain. Only a few have been investigated for their CNS activity, and future investigations on their action may throw light on a wide spectrum of brain functions.
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              An Introduction to the Endogenous Cannabinoid System.

              The endocannabinoid system (ECS) is a widespread neuromodulatory system that plays important roles in central nervous system development, synaptic plasticity, and the response to endogenous and environmental insults. The ECS comprises cannabinoid receptors, endogenous cannabinoids (endocannabinoids), and the enzymes responsible for the synthesis and degradation of the endocannabinoids. The most abundant cannabinoid receptors are the CB1 cannabinoid receptors; however, CB2 cannabinoid receptors, transient receptor potential channels, and peroxisome proliferator activated receptors are also engaged by some cannabinoids. Exogenous cannabinoids, such as tetrahydrocannabinol, produce their biological effects through their interactions with cannabinoid receptors. The best-studied endogenous cannabinoids are 2-arachidonoyl glycerol and arachidonoyl ethanolamide (anandamide). Despite similarities in chemical structure, 2-arachidonoyl glycerol and anandamide are synthesized and degraded by distinct enzymatic pathways, which impart fundamentally different physiologic and pathophysiologic roles to these two endocannabinoids. As a result of the pervasive social use of cannabis and the involvement of endocannabinoids in a multitude of biological processes, much has been learned about the physiologic and pathophysiologic roles of the ECS. This review provides an introduction to the ECS with an emphasis on its role in synaptic plasticity and how the ECS is perturbed in schizophrenia.
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                Author and article information

                Contributors
                ftelese@ucsd.edu
                Journal
                Neuropsychopharmacology
                Neuropsychopharmacology
                Neuropsychopharmacology
                Springer International Publishing (Cham )
                0893-133X
                1740-634X
                22 August 2022
                22 August 2022
                November 2022
                : 47
                : 12
                : 2071-2080
                Affiliations
                [1 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Department of Integrative Biology and Physiology, , University of California, ; Los Angeles, CA USA
                [2 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Neuroscience Interdepartmental Program, , University of California Los Angeles, ; Los Angeles, CA USA
                [3 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Department of Medicine, , University of California, ; San Diego, CA USA
                [4 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Institute for Quantitative and Computational Biosciences, , University of California, ; Los Angeles, CA USA
                [5 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, Brain Research Institute, , University of California, ; Los Angeles, CA USA
                Author information
                http://orcid.org/0000-0003-3877-0628
                Article
                1413
                10.1038/s41386-022-01413-2
                9556757
                35995972
                d2c4d32c-21c7-4cc1-9069-93e7e3b3abc8
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 19 April 2022
                : 6 July 2022
                : 25 July 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/100006108, U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences (NCATS);
                Award ID: UL1TR001881
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000026, U.S. Department of Health & Human Services | NIH | National Institute on Drug Abuse (NIDA);
                Award ID: U01DA050239
                Award ID: DP1DA042232
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Drug Abuse (NIDA)
                Categories
                Article
                Custom metadata
                © The Author(s), under exclusive licence to American College of Neuropsychopharmacology 2022

                Pharmacology & Pharmaceutical medicine
                gene expression,gene expression analysis,addiction
                Pharmacology & Pharmaceutical medicine
                gene expression, gene expression analysis, addiction

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