Blood and Brain Gene Expression Signatures of Chronic Intermittent Ethanol Consumption in Mice
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA734926 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14720400.fastq.gz | Fastqsanger.gz | |||
| SRR14720500.fastq.gz | Fastqsanger.gz | |||
| SRR14720401.fastq.gz | Fastqsanger.gz | |||
| SRR14720501.fastq.gz | Fastqsanger.gz | |||
| SRR14720402.fastq.gz | Fastqsanger.gz |
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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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Project description:Purpose: Identify the specific transcriptome alterations in astrocytes and microglia isolated from mouse prefrontal cortex (PFC) following a chronic intermittent ethanol vapor exposure paradigm Methods: We performed RNA-sequencing on astrocytes, microglia, and total homogenate tissue isolated from the PFC of C57BL/6J mice following chronic intermittent ethanol vapor exposure Results: We identified common neuroimmune gene expression response between cell types in response to CIE, unique networks of correlated genes differentially expressed in specific cell types, along with candidate pathways, biological processes and highly connected cell-type specific genes Conclusions: This study sheds light on the cell-specific effects of chronic ethanol and provides novel molecular targets for understanding ethanol dependence
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Project description:Cycles of heavy drinking and abstinence can lead to ethanol abuse disorder. We studied the effects of chronic intermittent ethanol exposure (CIE) over three weeks on neuroblastoma cells, using an ethanol concentration frequently attained in binge drinking (40 mM, 184 mg/dl). There were many changes in gene expression but most were small. CIE affected pathways instrumental in the development or plasticity of neurons, including axonal guidance, reelin signaling and synaptogenesis. Genes involved in dopamine and serotonin signaling were also affected. Changes in transporters and receptors could dampen both NMDA and norepinephrine transmissions. Decreased expression of the GABA transporter SLC6A11 could increase GABA transmission and has been associated with a switch from sweet drinking to ethanol consumption in rats. Ethanol increased stress responses such as unfolded protein response. TGF-β and NFκB signaling were increased. Most of the genes involved in cholesterol biosynthesis were decreased in expression. Withdrawal for 24 h after CIE caused most of the CIE-induced expression changes to move back toward unexposed levels.
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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. 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. We found a high degree of preservation (rho range: [0.50, 0.67]) between blood and brain transcript levels. There was small overlap between blood and brain DEGs, and considerable overlap of gene networks perturbed after CIE related to cell-cell signaling (e.g., GABA and glutamate receptor signaling), immune responses (e.g., antigen presentation), and protein processing / mitochondrial functioning (e.g., ubiquitination, oxidative phosphorylation). 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: 90.1%). These results suggest that gene expression profiles from peripheral blood samples contain a biological signature of alcohol dependence that can discriminate between CIE and Air subjects.
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Project description:Glial transcriptome responses to chronic intermittent ethanol exposure
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Project description:Lasting behavioral and physiological changes such as abusive consumption, dependence, and withdrawal are characteristic features of alcohol use disorders (AUD). Mechanistically, persistent changes in gene expression are hypothesized to contribute to these brain adaptations leading to ethanol toxicity and abuse. Here 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 previously been shown to induce progressive ethanol consumption in rodents. Brain regional expression networks contributing to CIE-induced behavioral changes were identified by microarray analysis across five brain regions in the mesolimbic dopamine system and extended amygdala with tissue harvested from 0-120 hours following the last cycle of 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 of CIE vs. air-treated controls showed that long-lasting gene regulation occurred 5-days after the final cycle of ethanol exposure only in prefrontal cortex (PFC) and hippocampus. In the majority of brain-regions, however, ethanol regulated gene expression changes occurred only immediately following CIE or within the first 8-hours of removal from ethanol. Bioinformatics analysis of modules identified by WGCNA 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. Strikingly, 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. In particular, our identification of a potential role for Let-7 miRNAs and a Bdnf-related expression network in long-lasting expression changes after CIE may lead to future druggable gene target identification for novel intervention in AUD.
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Project description:Lasting behavioral and physiological changes such as abusive consumption, dependence, and withdrawal are characteristic features of alcohol use disorders (AUD). Mechanistically, persistent changes in gene expression are hypothesized to contribute to these brain adaptations leading to ethanol toxicity and abuse. Here 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 previously been shown to induce progressive ethanol consumption in rodents. Brain regional expression networks contributing to CIE-induced behavioral changes were identified by microarray analysis across five brain regions in the mesolimbic dopamine system and extended amygdala with tissue harvested from 0-120 hours following the last cycle of 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 of CIE vs. air-treated controls showed that long-lasting gene regulation occurred 5-days after the final cycle of ethanol exposure only in prefrontal cortex (PFC) and hippocampus. In the majority of brain-regions, however, ethanol regulated gene expression changes occurred only immediately following CIE or within the first 8-hours of removal from ethanol. Bioinformatics analysis of modules identified by WGCNA 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. Strikingly, 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. In particular, our identification of a potential role for Let-7 miRNAs and a Bdnf-related expression network in long-lasting expression changes after CIE may lead to future druggable gene target identification for novel intervention in AUD.
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Project description:Lasting behavioral and physiological changes such as abusive consumption, dependence, and withdrawal are characteristic features of alcohol use disorders (AUD). Mechanistically, persistent changes in gene expression are hypothesized to contribute to these brain adaptations leading to ethanol toxicity and abuse. Here 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 previously been shown to induce progressive ethanol consumption in rodents. Brain regional expression networks contributing to CIE-induced behavioral changes were identified by microarray analysis across five brain regions in the mesolimbic dopamine system and extended amygdala with tissue harvested from 0-120 hours following the last cycle of 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 of CIE vs. air-treated controls showed that long-lasting gene regulation occurred 5-days after the final cycle of ethanol exposure only in prefrontal cortex (PFC) and hippocampus. In the majority of brain-regions, however, ethanol regulated gene expression changes occurred only immediately following CIE or within the first 8-hours of removal from ethanol. Bioinformatics analysis of modules identified by WGCNA 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. Strikingly, 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. In particular, our identification of a potential role for Let-7 miRNAs and a Bdnf-related expression network in long-lasting expression changes after CIE may lead to future druggable gene target identification for novel intervention in AUD.
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