Neocortex Gene Expression Correlates for HARGREAVES_MEANBOTH measured in BXD RI Females & Males obtained using GeneNetwork Neocortex ILM6v1.1 (Feb08) RankInv. The HARGREAVES_MEANBOTH measures Thermal Nociception Hargreaves' Test under the domain Pain. The correlates were thresholded at a p-value of less than 0.001.
Authors:
Philip VM, Duvvuru S, Gomero B, Ansah TA, Blaha CD, Cook MN, Hamre KM, Lariviere WR, Matthews DB, Mittleman G, Goldowitz D, Chesler EJ
Neocortex Gene Expression Correlates for SPD_TIMEDOWEL0SEC measured in BXD RI Females obtained using GeneNetwork Neocortex ILM6v1.1 (Feb08) RankInv. The SPD_TIMEDOWEL0SEC measures Dowel Test - Time 0 Sec under the domain Porsolt. The correlates were thresholded at a p-value of less than 0.001.
Authors:
Philip VM, Duvvuru S, Gomero B, Ansah TA, Blaha CD, Cook MN, Hamre KM, Lariviere WR, Matthews DB, Mittleman G, Goldowitz D, Chesler EJ
Genes that are differentially expressed in adult male C57BL/6J mice given acute cocaine vs. acute saline. Tissue was collected from the ventral tegmental area (VTA) of the brain. Gene expression was evaluated via RNA-seq, and differential gene expression was determined via linear regression (LR).D13 Values presented are p-values. Data taken from Supplementary Table 1. Data available from GEO with accession number GSE155313."
Authors:
Rianne R Campbell, Siwei Chen, Joy H Beardwood, Alberto J López, Lilyana V Pham, Ashley M Keiser, Jessica E Childs, Dina P Matheos, Vivek Swarup, Pierre Baldi, Marcelo A Wood
640 Diversity Outbred (DO) mice were exposed to 4 weeks of intermittent ethanol access (IEA) via 3-bottle choice (H20, 15% EtOH, 30% EtOH). 200 prefrontal cortex (PFC) samples were sent for RNA-seq. After QC and GBRS alignment, Pearson correlations were calculated for all genes with variant-stabilized transcript counts >1 and whole study mean ethanol consumption. This gene set provides the list of genes for which FDR-corrected p-values < 0.05 and their Pearson correlation scores.
640 Diversity Outbred (DO) mice were exposed to 4 weeks of intermittent ethanol access (IEA) via 3-bottle choice (H20, 15% EtOH, 30% EtOH). 200 prefrontal cortex (PFC) samples were sent for RNA-seq. After QC and GBRS alignment, Pearson correlations were calculated for all genes with variant-stabilized transcript counts >1 and week four mean ethanol consumption. This gene set provides the list of genes for which FDR-corrected p-values < 0.05 and their Pearson correlation scores.
640 Diversity Outbred (DO) mice were exposed to 4 weeks of intermittent ethanol access (IEA) via 3-bottle choice (H20, 15% EtOH, 30% EtOH). 200 prefrontal cortex (PFC) samples were sent for RNA-seq. After QC and GBRS alignment, Pearson correlations were calculated for all genes with variant-stabilized transcript counts >1 and week four mean ethanol preference over water. This gene set provides the list of genes for which FDR-corrected p-values < 0.05 and their Pearson correlation scores.
Genes identified as expressed higher (up) in the AJ strain than in the PWK strain. Differentially expressed genes had a Q-value < 0.05 following the Benjamini-Hochberg methodology for false discovery rates in the limma+voom pipeline within edgeR. Q-value is reported from the topTable function.
Genes identified as expressed higher (up) in the AJ strain than in the PWK strain. Differentially expressed genes had a Q-value < 0.05 following the Benjamini-Hochberg methodology for false discovery rates in the limma+voom pipeline within edgeR. Q-value is reported from the topTable function.
Genes identified as expressed lower (down) in the AJ strain than in the NZO strain. Differentially expressed genes had a Q-value < 0.05 following the Benjamini-Hochberg methodology for false discovery rates in the limma+voom pipeline within edgeR. Q-value is reported from the topTable function.
Genes identified as expressed lower (down) in the AJ strain than in the WSB strain. Differentially expressed genes had a Q-value < 0.05 following the Benjamini-Hochberg methodology for false discovery rates in the limma+voom pipeline within edgeR. Q-value is reported from the topTable function.
Genes identified as expressed lower (down) in the AJ strain than in the NOD strain. Differentially expressed genes had a Q-value < 0.05 following the Benjamini-Hochberg methodology for false discovery rates in the limma+voom pipeline within edgeR. Q-value is reported from the topTable function.
Genes identified as expressed lower (down) in the AJ strain than in the S129 strain. Differentially expressed genes had a Q-value < 0.05 following the Benjamini-Hochberg methodology for false discovery rates in the limma+voom pipeline within edgeR. Q-value is reported from the topTable function.
Genes identified as expressed lower (down) in the AJ strain than in the WSB strain. Differentially expressed genes had a Q-value < 0.05 following the Benjamini-Hochberg methodology for false discovery rates in the limma+voom pipeline within edgeR. Q-value is reported from the topTable function.
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 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
Microglia depletion and alcohol gene expression logFC
Description:
Alcohol abuse induces changes in microglia morphology and immune function, but whether microglia initiate or simply amplify the harmful effects of alcohol exposure is still a matter of debate. Here, we determine microglia function in acute and voluntary drinking behaviors using a colony-stimulating factor 1 receptor inhibitor (PLX5622). We show that microglia depletion does not alter the sedative or hypnotic effects of acute intoxication. Microglia depletion also does not change the escalation or maintenance of chronic voluntary alcohol consumption. Transcriptomic analysis revealed that although many immune genes have been implicated in alcohol abuse, down regulation of microglia genes does not necessitate changes in alcohol intake. Instead, microglia depletion and chronic alcohol result in compensatory upregulation of alcohol-responsive, reactive astrocyte genes, indicating astrocytes may play a role in regulation of these alcohol behaviors. Taken together, our behavioral and transcriptional data indicate that microglia are not theprimary effector cell responsible for regulation of acute and voluntary alcohol behaviors. Because microglia depletion did not regulate acute or voluntary alcohol behaviors, we hypothesized that these doses were insufficient to activate microglia and recruit them to an effector phenotype. Therefore, we used a model of repeated immune activation using polyinosinic:polycytidylic acid
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