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Brain regional gene expression network analysis identifies unique interactions between chronic ethanol exposure and consumption.

ABSTRACT: Progressive increases in ethanol consumption is a hallmark of alcohol use disorder (AUD). Persistent changes in brain gene expression are hypothesized to underlie the altered neural signaling producing abusive consumption in AUD. To identify brain regional gene expression networks contributing to progressive ethanol consumption, we performed microarray and scale-free network analysis of expression responses in a C57BL/6J mouse model utilizing chronic intermittent ethanol by vapor chamber (CIE) in combination with limited access oral ethanol consumption. This model has previously been shown to produce long-lasting increased ethanol consumption, particularly when combining oral ethanol access with repeated cycles of intermittent vapor exposure. The interaction of CIE and oral consumption was studied by expression profiling and network analysis in medial prefrontal cortex, nucleus accumbens, hippocampus, bed nucleus of the stria terminalis, and central nucleus of the amygdala. Brain region expression networks were analyzed for ethanol-responsive gene expression, correlation with ethanol consumption and functional content using extensive bioinformatics studies. In all brain-regions studied the largest number of changes in gene expression were seen when comparing ethanol naïve mice to those exposed to CIE and drinking. In the prefrontal cortex, however, unique patterns of gene expression were seen compared to other brain-regions. Network analysis identified modules of co-expressed genes in all brain regions. The prefrontal cortex and nucleus accumbens showed the greatest number of modules with significant correlation to drinking behavior. Across brain-regions, however, many modules with strong correlations to drinking, both baseline intake and amount consumed after CIE, showed functional enrichment for synaptic transmission and synaptic plasticity.

SUBMITTER: Smith ML

PROVIDER: S-EPMC7259766 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Brain regional gene expression network analysis identifies unique interactions between chronic ethanol exposure and consumption.

Smith Maren L ML Lopez Marcelo F MF Wolen Aaron R AR Becker Howard C HC Miles Michael F MF

PloS one 20200529 5

Progressive increases in ethanol consumption is a hallmark of alcohol use disorder (AUD). Persistent changes in brain gene expression are hypothesized to underlie the altered neural signaling producing abusive consumption in AUD. To identify brain regional gene expression networks contributing to progressive ethanol consumption, we performed microarray and scale-free network analysis of expression responses in a C57BL/6J mouse model utilizing chronic intermittent ethanol by vapor chamber (CIE) i ...[more]

PMID: 32469986

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Project description:Long lasting abusive consumption, dependence, and withdrawal are characteristic features of alcohol use disorders (AUD). Mechanistically, persistent changes in gene expression are hypothesized to contribute to brain adaptations leading to ethanol toxicity and AUD. We employed repeated chronic intermittent ethanol (CIE) exposure by vapor chamber as a mouse model to simulate the cycles of ethanol exposure and withdrawal commonly seen with AUD. This model has been shown to induce progressive ethanol consumption in rodents. Brain CIE-responsive expression networks were identified by microarray analysis across five regions of the mesolimbic dopamine system and extended amygdala with tissue harvested from 0-hours to 7-days following CIE. Weighted Gene Correlated Network Analysis (WGCNA) was used to identify gene networks over-represented for CIE-induced temporal expression changes across brain regions. Differential gene expression analysis showed that long-lasting gene regulation occurred 7-days after the final cycle of ethanol exposure only in prefrontal cortex (PFC) and hippocampus. Across all brain regions, however, ethanol-responsive expression changes occurred mainly within the first 8-hours after removal from ethanol. Bioinformatics analysis showed that neuroinflammatory responses were seen across multiple brain regions at early time-points, whereas co-expression modules related to neuroplasticity, chromatin remodeling, and neurodevelopment were seen at later time-points and in specific brain regions (PFC or HPC). In PFC a module containing Bdnf was identified as highly CIE responsive in a biphasic manner, with peak changes at 0 hours and 5 days following CIE, suggesting a possible role in mechanisms underlying long-term molecular and behavioral response to CIE. Bioinformatics analysis of this network and several other modules identified Let-7 family microRNAs as potential regulators of gene expression changes induced by CIE. Our results suggest a complex temporal and regional pattern of widespread gene network responses involving neuroinflammatory and neuroplasticity related genes as contributing to physiological and behavioral responses to chronic ethanol.

Project description:Individuals with post-traumatic stress disorder (PTSD) often use alcohol to cope with their distress. This aberrant use of alcohol often develops into alcohol use disorder (AUD) leading to high rates of PTSD-AUD co-occurrence. Individuals with comorbid PTSD-AUD have more intense alcohol cravings and increased relapse rates during withdrawal than those with AUD alone. Also, individuals with PTSD or AUD alone often show similar psychological behaviors, such as impulsivity and anhedonia. Extensive clinical studies on the behavioral effects of PTSD-AUD comorbidity, namely alcohol use, have been performed. However, these effects have not been well studied or mechanistically explored in animal models. Therefore, the present study evaluated the effects of traumatic stress comorbid with alcohol exposures on ethanol intake, impulsivity, and anhedonia in mice. Adult male C57Bl/6 mice were first exposed to either mouse single-prolonged stress (mSPS), an animal model that has been validated for characteristics akin to PTSD symptoms, or control conditions. Baseline two-bottle choice ethanol consumption and preference tests were conducted after a 7-day isolation period, as part of the mSPS exposure. Next, mice were exposed to air or chronic intermittent ethanol (CIE), a vapor-induced ethanol dependence and withdrawal model, for 4 weeks. Two-bottle choice ethanol drinking was used to measure dependence-induced ethanol consumption and preference during periods intervening CIE cycles. The novelty suppressed feeding (NSF) test was used to evaluate impulsivity and anhedonia behaviors 48 h after mSPS and/or repeated CIE exposure. Results showed that, compared to control conditions, mSPS did not affect baseline ethanol consumption and preference. However, mSPS-CIE mice increased Post-CIE ethanol consumption compared to Control-Air mice. Mice exposed to mSPS had a shorter latency to feed during the NSF, whereas CIE-exposed mice consumed less palatable food reward in their home cage after the NSF. These results demonstrate that mice exposed to both mSPS and CIE are more vulnerable to ethanol withdrawal effects, and those exposed to mSPS have increased impulsivity, while CIE exposure increases anhedonia. Future studies to examine the relationship between behavioral outcomes and the molecular mechanisms in the brain after PTSD-AUD are warranted.

Project description:Alcohol Use Disorder (AUD) is a chronic, relapsing syndrome diagnosed by a heterogeneous set of behavioral signs and symptoms. There are no laboratory tests that provide direct objective evidence for diagnosis. Microarray and RNA-Seq technologies enable genome-wide transcriptome profiling at low costs and provide an opportunity to identify biomarkers to facilitate diagnosis, prognosis, and treatment of patients. Brain gene expression patterns can discriminate alcohol-dependent and non-dependent people and predict drugs that reduce drinking in rodents. However, access to brain tissue in living patients is not possible. Blood contains cellular and extracellular RNAs that provide disease-relevant information for some brain diseases. We hypothesized that blood gene expression profiles can be used to diagnose AUD. We profiled brain (prefrontal cortex, amygdala, and hypothalamus) and blood gene expression levels in C57BL/6J mice using RNA-seq one week after chronic intermittent ethanol (CIE) exposure, a mouse model of alcohol dependence. To determine the preservation of gene expression levels between blood and brain, we calculated the Spearman correlation coefficient between blood and brain mean gene expression levels across all subjects and found a high degree of preservation (rho range: [0.50, 0.67]) with hundreds of transcripts in blood correlated with their brain transcript levels. To determine whether the transcriptional response to alcohol dependence was similar in blood and brain, we studied the overlapping differentially expressed genes (DEGs) and gene coexpression networks. Although there was small overlap between blood and brain DEGs, there was considerable overlap of gene networks perturbed after CIE related to cell-cell signaling (e.g., GABA and glutamate receptor signaling, endocannabinoid signaling, synaptogenesis), immune responses (e.g., antigen presentation, communication between innate and adaptive immune systems), and protein processing / mitochondrial functioning (e.g., ubiquitination, unfolded protein responses, oxidative phosphorylation). To determine whether blood gene expression can predict alcohol dependence status, blood gene expression data were used to train classifiers (logistic regression, random forest, and partial least squares discriminant analysis), which were highly accurate at predicting alcohol dependence status (maximum AUC for females: 90.1%; males: 80.5%). These results suggest that gene expression profiles from peripheral blood samples contain a biological signature of alcohol dependence that can discriminate between alcohol-dependent and non-dependent subjects.

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Brain regional gene expression network analysis identifies unique interactions between chronic ethanol exposure and consumption.

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Brain regional gene expression network analysis identifies unique interactions between chronic ethanol exposure and consumption.

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