Differential-Expression Comparison of Mutant SOD1 Microglia RNA-Seq Data Relative to Control Microglia at D100 with an FDR<0.05, uploaded with p-value.
Authors:
Chiu IM, Morimoto ET, Goodarzi H, Liao JT, O\'Keeffe S, Phatnani HP, Muratet M, Carroll MC, Levy S, Tavazoie S, Myers RM, Maniatis T
Alcohol Use Disorder (AUD) is a chronic, relapsing syndrome diagnosed by a heteroge- neous 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 bio- markers 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., anti- gen presentation), and protein processing / mitochondrial functioning (e.g., ubiquitination, oxidative phosphorylation). Blood gene expression data were used to train classifiers (logis- tic 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 bio- logical signature of alcohol dependence that can discriminate between CIE and Air subjects.
Authors:
Laura B Ferguson, Amanda J Roberts, R Dayne Mayfield, Robert O Messing
Alcohol Use Disorder (AUD) is a chronic, relapsing syndrome diagnosed by a heteroge- neous 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 bio- markers 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., anti- gen presentation), and protein processing / mitochondrial functioning (e.g., ubiquitination, oxidative phosphorylation). Blood gene expression data were used to train classifiers (logis- tic 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 bio- logical signature of alcohol dependence that can discriminate between CIE and Air subjects.
Authors:
Laura B Ferguson, Amanda J Roberts, R Dayne Mayfield, Robert O Messing
Alcohol prefrontal cortex gene expression in females logFC
Description:
Alcohol Use Disorder (AUD) is a chronic, relapsing syndrome diagnosed by a heteroge- neous 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 bio- markers 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., anti- gen presentation), and protein processing / mitochondrial functioning (e.g., ubiquitination, oxidative phosphorylation). Blood gene expression data were used to train classifiers (logis- tic 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 bio- logical signature of alcohol dependence that can discriminate between CIE and Air subjects.
Authors:
Laura B Ferguson, Amanda J Roberts, R Dayne Mayfield, Robert O Messing
Gene expression in female mice PFC associated with chronic alcohol exposure
Description:
Alcohol Use Disorder (AUD) is a chronic, relapsing syndrome diagnosed by a heteroge- neous 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 bio- markers 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., anti- gen presentation), and protein processing / mitochondrial functioning (e.g., ubiquitination, oxidative phosphorylation). Blood gene expression data were used to train classifiers (logis- tic 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 bio- logical signature of alcohol dependence that can discriminate between CIE and Air subjects.
Authors:
Laura B Ferguson, Amanda J Roberts, R Dayne Mayfield, Robert O Messing
Alcohol prefrontal cortex gene expression in males logFC
Description:
Alcohol Use Disorder (AUD) is a chronic, relapsing syndrome diagnosed by a heteroge- neous 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 bio- markers 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., anti- gen presentation), and protein processing / mitochondrial functioning (e.g., ubiquitination, oxidative phosphorylation). Blood gene expression data were used to train classifiers (logis- tic 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 bio- logical signature of alcohol dependence that can discriminate between CIE and Air subjects.
Authors:
Laura B Ferguson, Amanda J Roberts, R Dayne Mayfield, Robert O Messing
Alcohol hypothalamus gene expression in females logFC
Description:
Alcohol Use Disorder (AUD) is a chronic, relapsing syndrome diagnosed by a heteroge- neous 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 bio- markers 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., anti- gen presentation), and protein processing / mitochondrial functioning (e.g., ubiquitination, oxidative phosphorylation). Blood gene expression data were used to train classifiers (logis- tic 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 bio- logical signature of alcohol dependence that can discriminate between CIE and Air subjects.
Authors:
Laura B Ferguson, Amanda J Roberts, R Dayne Mayfield, Robert O Messing
Alcohol hypothalamus gene expression in females q-value
Description:
Alcohol Use Disorder (AUD) is a chronic, relapsing syndrome diagnosed by a heteroge- neous 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 bio- markers 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., anti- gen presentation), and protein processing / mitochondrial functioning (e.g., ubiquitination, oxidative phosphorylation). Blood gene expression data were used to train classifiers (logis- tic 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 bio- logical signature of alcohol dependence that can discriminate between CIE and Air subjects.
Authors:
Laura B Ferguson, Amanda J Roberts, R Dayne Mayfield, Robert O Messing
Alcohol hypothalamus gene expression in males logFC
Description:
Alcohol Use Disorder (AUD) is a chronic, relapsing syndrome diagnosed by a heteroge- neous 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 bio- markers 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., anti- gen presentation), and protein processing / mitochondrial functioning (e.g., ubiquitination, oxidative phosphorylation). Blood gene expression data were used to train classifiers (logis- tic 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 bio- logical signature of alcohol dependence that can discriminate between CIE and Air subjects.
Authors:
Laura B Ferguson, Amanda J Roberts, R Dayne Mayfield, Robert O Messing
Alcohol hypothalamus gene expression in males q-value
Description:
Alcohol Use Disorder (AUD) is a chronic, relapsing syndrome diagnosed by a heteroge- neous 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 bio- markers 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., anti- gen presentation), and protein processing / mitochondrial functioning (e.g., ubiquitination, oxidative phosphorylation). Blood gene expression data were used to train classifiers (logis- tic 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 bio- logical signature of alcohol dependence that can discriminate between CIE and Air subjects.
Authors:
Laura B Ferguson, Amanda J Roberts, R Dayne Mayfield, Robert O Messing
We investigated the role of microglia in a mouse model of alcohol dependence using a colony stimulating factor 1 receptor inhibitor (PLX5622) to deplete microglia and a chronic intermittent ethanol vapor two-bottle choice drinking procedure. Additionally, we examined anxiety-like behavior during withdrawal. We then analyzed synaptic neuroadaptations in the central nucleus of the amygdala (CeA) and gene expression changes in the medial prefrontal cortex (mPFC) and CeA from the same animals used for behavioral studies.
Alcohol Microglia depletion in the medial prefrontal cortex q-value
Description:
dependence using a colony stimulating factor 1 receptor inhibitor (PLX5622) to deplete microglia and a chronic intermittent ethanol vapor two-bottle choice drinking procedure. Additionally, we examined anxiety-like behavior during withdrawal. We then analyzed synaptic neuroadaptations in the central nucleus of the amygdala (CeA) and gene expression changes in the medial prefrontal cortex (mPFC) and CeA from the same animals used for behavioral studies.
Alcohol dependence in the medial prefrontal cortex logFC
Description:
We investigated the role of microglia in a mouse model of alcohol dependence using a colony stimulating factor 1 receptor inhibitor (PLX5622) to deplete microglia and a chronic intermittent ethanol vapor two-bottle choice drinking procedure. Additionally, we examined anxiety-like behavior during withdrawal. We then analyzed synaptic neuroadaptations in the central nucleus of the amygdala (CeA) and gene expression changes in the medial prefrontal cortex (mPFC) and CeA from the same animals used for behavioral studies.
Alcohol interaction of dependence and MG depletion the medial prefrontal cortex logFC
Description:
We investigated the role of microglia in a mouse model of alcohol dependence using a colony stimulating factor 1 receptor inhibitor (PLX5622) to deplete microglia and a chronic intermittent ethanol vapor two-bottle choice drinking procedure. Additionally, we examined anxiety-like behavior during withdrawal. We then analyzed synaptic neuroadaptations in the central nucleus of the amygdala (CeA) and gene expression changes in the medial prefrontal cortex (mPFC) and CeA from the same animals used for behavioral studies.
Alcohol use disorder (AUD) is a complex psychiatric disorder with strong genetic and environmental risk factors. We studied the molecular perturbations underlying risky drinking behavior by measuring transcriptome changes across the neurocircuitry of addiction in a genetic mouse model of binge drinking. Sixteen generations of selective breeding for high blood alcohol levels after a binge drinking session produced global changes in brain gene expression in alcohol-naïve High Drinking in the Dark (HDID-1) mice. Using gene expression profiles to generate circuit-level hypotheses, we developed a systems approach that integrated regulation of gene coexpression networks across multiple brain regions, neuron-specific transcriptional signatures, and knowledgebase analytics. Whole-cell, voltage-clamp recordings from nucleus accumbens shell neurons projecting to the ventral tegmental area showed differential ethanol-induced plasticity in HDID-1 and control mice and provided support for one of the hypotheses. There were similarities in gene networks between HDID-1 mouse brains and postmortem brains of human alcoholics, suggesting that some gene expression patterns associated with high alcohol consumption are conserved across species. This study demonstrated the value of gene networks for data integration across biological modalities and species to study mechanisms of disease.
Authors:
Laura B Ferguson, Lingling Zhang, Daniel Kircher, Shi Wang, R Dayne Mayfield, John C Crabbe, Richard A Morrisett, R Adron Harris, Igor Ponomarev
Alcohol use disorder (AUD) is a complex psychiatric disorder with strong genetic and environmental risk factors. We studied the molecular perturbations underlying risky drinking behavior by measuring transcriptome changes across the neurocircuitry of addiction in a genetic mouse model of binge drinking. Sixteen generations of selective breeding for high blood alcohol levels after a binge drinking session produced global changes in brain gene expression in alcohol-naïve High Drinking in the Dark (HDID-1) mice. Using gene expression profiles to generate circuit-level hypotheses, we developed a systems approach that integrated regulation of gene coexpression networks across multiple brain regions, neuron-specific transcriptional signatures, and knowledgebase analytics. Whole-cell, voltage-clamp recordings from nucleus accumbens shell neurons projecting to the ventral tegmental area showed differential ethanol-induced plasticity in HDID-1 and control mice and provided support for one of the hypotheses. There were similarities in gene networks between HDID-1 mouse brains and postmortem brains of human alcoholics, suggesting that some gene expression patterns associated with high alcohol consumption are conserved across species. This study demonstrated the value of gene networks for data integration across biological modalities and species to study mechanisms of disease.
Authors:
Laura B Ferguson, Lingling Zhang, Daniel Kircher, Shi Wang, R Dayne Mayfield, John C Crabbe, Richard A Morrisett, R Adron Harris, Igor Ponomarev
Alcohol use disorder (AUD) is a complex psychiatric disorder with strong genetic and environmental risk factors. We studied the molecular perturbations underlying risky drinking behavior by measuring transcriptome changes across the neurocircuitry of addiction in a genetic mouse model of binge drinking. Sixteen generations of selective breeding for high blood alcohol levels after a binge drinking session produced global changes in brain gene expression in alcohol-naïve High Drinking in the Dark (HDID-1) mice. Using gene expression profiles to generate circuit-level hypotheses, we developed a systems approach that integrated regulation of gene coexpression networks across multiple brain regions, neuron-specific transcriptional signatures, and knowledgebase analytics. Whole-cell, voltage-clamp recordings from nucleus accumbens shell neurons projecting to the ventral tegmental area showed differential ethanol-induced plasticity in HDID-1 and control mice and provided support for one of the hypotheses. There were similarities in gene networks between HDID-1 mouse brains and postmortem brains of human alcoholics, suggesting that some gene expression patterns associated with high alcohol consumption are conserved across species. This study demonstrated the value of gene networks for data integration across biological modalities and species to study mechanisms of disease.
Authors:
Laura B Ferguson, Lingling Zhang, Daniel Kircher, Shi Wang, R Dayne Mayfield, John C Crabbe, Richard A Morrisett, R Adron Harris, Igor Ponomarev
Alcohol use disorder (AUD) is a complex psychiatric disorder with strong genetic and environmental risk factors. We studied the molecular perturbations underlying risky drinking behavior by measuring transcriptome changes across the neurocircuitry of addiction in a genetic mouse model of binge drinking. Sixteen generations of selective breeding for high blood alcohol levels after a binge drinking session produced global changes in brain gene expression in alcohol-naïve High Drinking in the Dark (HDID-1) mice. Using gene expression profiles to generate circuit-level hypotheses, we developed a systems approach that integrated regulation of gene coexpression networks across multiple brain regions, neuron-specific transcriptional signatures, and knowledgebase analytics. Whole-cell, voltage-clamp recordings from nucleus accumbens shell neurons projecting to the ventral tegmental area showed differential ethanol-induced plasticity in HDID-1 and control mice and provided support for one of the hypotheses. There were similarities in gene networks between HDID-1 mouse brains and postmortem brains of human alcoholics, suggesting that some gene expression patterns associated with high alcohol consumption are conserved across species. This study demonstrated the value of gene networks for data integration across biological modalities and species to study mechanisms of disease.
Authors:
Laura B Ferguson, Lingling Zhang, Daniel Kircher, Shi Wang, R Dayne Mayfield, John C Crabbe, Richard A Morrisett, R Adron Harris, Igor Ponomarev
Alcohol use disorder (AUD) is a complex psychiatric disorder with strong genetic and environmental risk factors. We studied the molecular perturbations underlying risky drinking behavior by measuring transcriptome changes across the neurocircuitry of addiction in a genetic mouse model of binge drinking. Sixteen generations of selective breeding for high blood alcohol levels after a binge drinking session produced global changes in brain gene expression in alcohol-naïve High Drinking in the Dark (HDID-1) mice. Using gene expression profiles to generate circuit-level hypotheses, we developed a systems approach that integrated regulation of gene coexpression networks across multiple brain regions, neuron-specific transcriptional signatures, and knowledgebase analytics. Whole-cell, voltage-clamp recordings from nucleus accumbens shell neurons projecting to the ventral tegmental area showed differential ethanol-induced plasticity in HDID-1 and control mice and provided support for one of the hypotheses. There were similarities in gene networks between HDID-1 mouse brains and postmortem brains of human alcoholics, suggesting that some gene expression patterns associated with high alcohol consumption are conserved across species. This study demonstrated the value of gene networks for data integration across biological modalities and species to study mechanisms of disease.
Authors:
Laura B Ferguson, Lingling Zhang, Daniel Kircher, Shi Wang, R Dayne Mayfield, John C Crabbe, Richard A Morrisett, R Adron Harris, Igor Ponomarev
Alcohol use disorder (AUD) is a complex psychiatric disorder with strong genetic and environmental risk factors. We studied the molecular perturbations underlying risky drinking behavior by measuring transcriptome changes across the neurocircuitry of addiction in a genetic mouse model of binge drinking. Sixteen generations of selective breeding for high blood alcohol levels after a binge drinking session produced global changes in brain gene expression in alcohol-naïve High Drinking in the Dark (HDID-1) mice. Using gene expression profiles to generate circuit-level hypotheses, we developed a systems approach that integrated regulation of gene coexpression networks across multiple brain regions, neuron-specific transcriptional signatures, and knowledgebase analytics. Whole-cell, voltage-clamp recordings from nucleus accumbens shell neurons projecting to the ventral tegmental area showed differential ethanol-induced plasticity in HDID-1 and control mice and provided support for one of the hypotheses. There were similarities in gene networks between HDID-1 mouse brains and postmortem brains of human alcoholics, suggesting that some gene expression patterns associated with high alcohol consumption are conserved across species. This study demonstrated the value of gene networks for data integration across biological modalities and species to study mechanisms of disease.
Authors:
Laura B Ferguson, Lingling Zhang, Daniel Kircher, Shi Wang, R Dayne Mayfield, John C Crabbe, Richard A Morrisett, R Adron Harris, Igor Ponomarev
Alcohol use disorder (AUD) is a complex psychiatric disorder with strong genetic and environmental risk factors. We studied the molecular perturbations underlying risky drinking behavior by measuring transcriptome changes across the neurocircuitry of addiction in a genetic mouse model of binge drinking. Sixteen generations of selective breeding for high blood alcohol levels after a binge drinking session produced global changes in brain gene expression in alcohol-naïve High Drinking in the Dark (HDID-1) mice. Using gene expression profiles to generate circuit-level hypotheses, we developed a systems approach that integrated regulation of gene coexpression networks across multiple brain regions, neuron-specific transcriptional signatures, and knowledgebase analytics. Whole-cell, voltage-clamp recordings from nucleus accumbens shell neurons projecting to the ventral tegmental area showed differential ethanol-induced plasticity in HDID-1 and control mice and provided support for one of the hypotheses. There were similarities in gene networks between HDID-1 mouse brains and postmortem brains of human alcoholics, suggesting that some gene expression patterns associated with high alcohol consumption are conserved across species. This study demonstrated the value of gene networks for data integration across biological modalities and species to study mechanisms of disease.
Authors:
Laura B Ferguson, Lingling Zhang, Daniel Kircher, Shi Wang, R Dayne Mayfield, John C Crabbe, Richard A Morrisett, R Adron Harris, Igor Ponomarev
Alcohol use disorder (AUD) is a complex psychiatric disorder with strong genetic and environmental risk factors. We studied the molecular perturbations underlying risky drinking behavior by measuring transcriptome changes across the neurocircuitry of addiction in a genetic mouse model of binge drinking. Sixteen generations of selective breeding for high blood alcohol levels after a binge drinking session produced global changes in brain gene expression in alcohol-naïve High Drinking in the Dark (HDID-1) mice. Using gene expression profiles to generate circuit-level hypotheses, we developed a systems approach that integrated regulation of gene coexpression networks across multiple brain regions, neuron-specific transcriptional signatures, and knowledgebase analytics. Whole-cell, voltage-clamp recordings from nucleus accumbens shell neurons projecting to the ventral tegmental area showed differential ethanol-induced plasticity in HDID-1 and control mice and provided support for one of the hypotheses. There were similarities in gene networks between HDID-1 mouse brains and postmortem brains of human alcoholics, suggesting that some gene expression patterns associated with high alcohol consumption are conserved across species. This study demonstrated the value of gene networks for data integration across biological modalities and species to study mechanisms of disease.
Authors:
Laura B Ferguson, Lingling Zhang, Daniel Kircher, Shi Wang, R Dayne Mayfield, John C Crabbe, Richard A Morrisett, R Adron Harris, Igor Ponomarev
Alcohol use disorder (AUD) is a complex psychiatric disorder with strong genetic and environmental risk factors. We studied the molecular perturbations underlying risky drinking behavior by measuring transcriptome changes across the neurocircuitry of addiction in a genetic mouse model of binge drinking. Sixteen generations of selective breeding for high blood alcohol levels after a binge drinking session produced global changes in brain gene expression in alcohol-naïve High Drinking in the Dark (HDID-1) mice. Using gene expression profiles to generate circuit-level hypotheses, we developed a systems approach that integrated regulation of gene coexpression networks across multiple brain regions, neuron-specific transcriptional signatures, and knowledgebase analytics. Whole-cell, voltage-clamp recordings from nucleus accumbens shell neurons projecting to the ventral tegmental area showed differential ethanol-induced plasticity in HDID-1 and control mice and provided support for one of the hypotheses. There were similarities in gene networks between HDID-1 mouse brains and postmortem brains of human alcoholics, suggesting that some gene expression patterns associated with high alcohol consumption are conserved across species. This study demonstrated the value of gene networks for data integration across biological modalities and species to study mechanisms of disease.
Authors:
Laura B Ferguson, Lingling Zhang, Daniel Kircher, Shi Wang, R Dayne Mayfield, John C Crabbe, Richard A Morrisett, R Adron Harris, Igor Ponomarev
Alcohol use disorder (AUD) is a complex psychiatric disorder with strong genetic and environmental risk factors. We studied the molecular perturbations underlying risky drinking behavior by measuring transcriptome changes across the neurocircuitry of addiction in a genetic mouse model of binge drinking. Sixteen generations of selective breeding for high blood alcohol levels after a binge drinking session produced global changes in brain gene expression in alcohol-naïve High Drinking in the Dark (HDID-1) mice. Using gene expression profiles to generate circuit-level hypotheses, we developed a systems approach that integrated regulation of gene coexpression networks across multiple brain regions, neuron-specific transcriptional signatures, and knowledgebase analytics. Whole-cell, voltage-clamp recordings from nucleus accumbens shell neurons projecting to the ventral tegmental area showed differential ethanol-induced plasticity in HDID-1 and control mice and provided support for one of the hypotheses. There were similarities in gene networks between HDID-1 mouse brains and postmortem brains of human alcoholics, suggesting that some gene expression patterns associated with high alcohol consumption are conserved across species. This study demonstrated the value of gene networks for data integration across biological modalities and species to study mechanisms of disease.
Authors:
Laura B Ferguson, Lingling Zhang, Daniel Kircher, Shi Wang, R Dayne Mayfield, John C Crabbe, Richard A Morrisett, R Adron Harris, Igor Ponomarev
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