DEG male mouse forebrain 3-tri morphine vs saline_pvalue
Description:
To examine forebrain transcriptomic changes that might elucidate mechanisms of withdrawal, delayed development, and any long-term behavior changes, we generated transcriptomic signatures following our “3-trimester” exposure model (3-Tri). In addition, we also examined transcriptomes from animals that received opioids only during the gestational period (PND1) or only during the last trimester from PND 1–14 (PND 14). We sought to determine whether transcriptomic signatures vary based on the window of exposure, perhaps contributing to the discrepancies in the literature regarding acute and long-term outcomes. Brains were dissected from PND 1 pups 6 h after discovery. Brains were dissected from post-natal exposure only (PND 14) or 3-trimester exposure (3-tri) 6 h after the last morphine or saline injection. The number of animals per group was similar (N = 5–7 animals, male and female C57Bl/6NTac mice), and the quality controls, library construction and sequence parameters were also identical across all groups. Libraries were sequenced on a NovaSeq 6000 at a depth of 30 million total reads/sample using paired-end sequencing of 150 base pairs (PE150), to a depth of 30 million total reads/sample. Reads were then mapped to the mouse reference genome (Mus Musculus, GRCm38/mm10) using HISAT2 (version 2.2.1), and duplicated fragments were removed using Picard MarkDuplicates. Differential expression analysis between two conditions (e.g., Morphine and Saline) was performed in R (version 4.1.1) with DESeq2 (v1.32.0) package. Genes were assigned by the authors as differentially expressed if the (adjusted) (nominal) p-value < 0.05. All genes/scores are presented here.
Authors:
Amelia D Dunn, Shivon A Robinson, Chiso Nwokafor, Molly Estill, Julia Ferrante, Li Shen, Crystal O Lemchi, Jordi Creus-Muncunill, Angie Ramirez, Juliet Mengaziol, Julia K Brynildsen, Mark Leggas, Jamie Horn, Michelle E Ehrlich, Julie A Blendy
DEG female mouse forebrain PND14 morphine vs saline_pvalue
Description:
To examine forebrain transcriptomic changes that might elucidate mechanisms of withdrawal, delayed development, and any long-term behavior changes, we generated transcriptomic signatures following our “3-trimester” exposure model (3-Tri). In addition, we also examined transcriptomes from animals that received opioids only during the gestational period (PND1) or only during the last trimester from PND 1–14 (PND 14). We sought to determine whether transcriptomic signatures vary based on the window of exposure, perhaps contributing to the discrepancies in the literature regarding acute and long-term outcomes. Brains were dissected from PND 1 pups 6 h after discovery. Brains were dissected from post-natal exposure only (PND 14) or 3-trimester exposure (3-tri) 6 h after the last morphine or saline injection. The number of animals per group was similar (N = 5–7 animals, male and female C57Bl/6NTac mice), and the quality controls, library construction and sequence parameters were also identical across all groups. Libraries were sequenced on a NovaSeq 6000 at a depth of 30 million total reads/sample using paired-end sequencing of 150 base pairs (PE150), to a depth of 30 million total reads/sample. Reads were then mapped to the mouse reference genome (Mus Musculus, GRCm38/mm10) using HISAT2 (version 2.2.1), and duplicated fragments were removed using Picard MarkDuplicates. Differential expression analysis between two conditions (e.g., Morphine and Saline) was performed in R (version 4.1.1) with DESeq2 (v1.32.0) package. Genes were assigned by the authors as differentially expressed if the (adjusted) (nominal) p-value < 0.05. All genes/scores are presented here.
Authors:
Amelia D Dunn, Shivon A Robinson, Chiso Nwokafor, Molly Estill, Julia Ferrante, Li Shen, Crystal O Lemchi, Jordi Creus-Muncunill, Angie Ramirez, Juliet Mengaziol, Julia K Brynildsen, Mark Leggas, Jamie Horn, Michelle E Ehrlich, Julie A Blendy
Alcohol transcriptome changes in mice microglia total homogenate log2FC
Description:
Microglia are fundamentally important immune cells within the central nervous system (CNS) that respond to environmental challenges to maintain normal physiological processes. Alterations in steady-state cellular function and over-activation of microglia can facilitate the initiation and progression of neuropathological conditions such as Alzheimer’s disease, Multiple Sclerosis, and Major Depressive Disorder. Alcohol consumption disrupts signaling pathways including both innate and adaptive immune responses that are necessary for CNS homeostasis. Coordinate expression of these genes is not ascertained from an admixture of CNS cell-types, underscoring the importance of examining isolated cellular populations to reveal systematic gene expression changes arising from mature microglia. Unbiased RNA-Seq profiling was used to identify gene expression changes in isolated prefrontal cortical microglia in response to recurring bouts of voluntary alcohol drinking behavior. The voluntary ethanol paradigm utilizes long-term consumption ethanol that results in escalated alcohol intake and altered cortical plasticity that is seen in humans. Gene coexpression analysis identified a coordinately regulated group of genes, unique to microglia, that collectively are associated with alcohol consumption. Genes within this group are involved in toll-like receptor signaling and transforming growth factor beta signaling. Network connectivity of this group identified Siglech as a putative hub gene and highlighted the potential importance of proteases in the microglial response to chronic ethanol. In conclusion, we identified a distinctive microglial gene expression signature for neuroimmune responses related to alcohol consumption that provides valuable insight into microglia-specific changes underlying the development of substance abuse, and possibly other CNS disorders.
Authors:
Gizelle M McCarthy, Sean P Farris, Yuri A Blednov, R Adron Harris, R Dayne Mayfield
DEG male mouse forebrain PND14 morphine vs saline_pvalue
Description:
To examine forebrain transcriptomic changes that might elucidate mechanisms of withdrawal, delayed development, and any long-term behavior changes, we generated transcriptomic signatures following our “3-trimester” exposure model (3-Tri). In addition, we also examined transcriptomes from animals that received opioids only during the gestational period (PND1) or only during the last trimester from PND 1–14 (PND 14). We sought to determine whether transcriptomic signatures vary based on the window of exposure, perhaps contributing to the discrepancies in the literature regarding acute and long-term outcomes. Brains were dissected from PND 1 pups 6 h after discovery. Brains were dissected from post-natal exposure only (PND 14) or 3-trimester exposure (3-tri) 6 h after the last morphine or saline injection. The number of animals per group was similar (N = 5–7 animals, male and female C57Bl/6NTac mice), and the quality controls, library construction and sequence parameters were also identical across all groups. Libraries were sequenced on a NovaSeq 6000 at a depth of 30 million total reads/sample using paired-end sequencing of 150 base pairs (PE150), to a depth of 30 million total reads/sample. Reads were then mapped to the mouse reference genome (Mus Musculus, GRCm38/mm10) using HISAT2 (version 2.2.1), and duplicated fragments were removed using Picard MarkDuplicates. Differential expression analysis between two conditions (e.g., Morphine and Saline) was performed in R (version 4.1.1) with DESeq2 (v1.32.0) package. Genes were assigned by the authors as differentially expressed if the (adjusted) (nominal) p-value < 0.05. All genes/scores are presented here.
Authors:
Amelia D Dunn, Shivon A Robinson, Chiso Nwokafor, Molly Estill, Julia Ferrante, Li Shen, Crystal O Lemchi, Jordi Creus-Muncunill, Angie Ramirez, Juliet Mengaziol, Julia K Brynildsen, Mark Leggas, Jamie Horn, Michelle E Ehrlich, Julie A Blendy
DEG female mouse forebrain 3-tri morphine vs saline_pvalue
Description:
To examine forebrain transcriptomic changes that might elucidate mechanisms of withdrawal, delayed development, and any long-term behavior changes, we generated transcriptomic signatures following our “3-trimester” exposure model (3-Tri). In addition, we also examined transcriptomes from animals that received opioids only during the gestational period (PND1) or only during the last trimester from PND 1–14 (PND 14). We sought to determine whether transcriptomic signatures vary based on the window of exposure, perhaps contributing to the discrepancies in the literature regarding acute and long-term outcomes. Brains were dissected from PND 1 pups 6 h after discovery. Brains were dissected from post-natal exposure only (PND 14) or 3-trimester exposure (3-tri) 6 h after the last morphine or saline injection. The number of animals per group was similar (N = 5–7 animals, male and female C57Bl/6NTac mice), and the quality controls, library construction and sequence parameters were also identical across all groups. Libraries were sequenced on a NovaSeq 6000 at a depth of 30 million total reads/sample using paired-end sequencing of 150 base pairs (PE150), to a depth of 30 million total reads/sample. Reads were then mapped to the mouse reference genome (Mus Musculus, GRCm38/mm10) using HISAT2 (version 2.2.1), and duplicated fragments were removed using Picard MarkDuplicates. Differential expression analysis between two conditions (e.g., Morphine and Saline) was performed in R (version 4.1.1) with DESeq2 (v1.32.0) package. Genes were assigned by the authors as differentially expressed if the (adjusted) (nominal) p-value < 0.05. All genes/scores are presented here.
Authors:
Amelia D Dunn, Shivon A Robinson, Chiso Nwokafor, Molly Estill, Julia Ferrante, Li Shen, Crystal O Lemchi, Jordi Creus-Muncunill, Angie Ramirez, Juliet Mengaziol, Julia K Brynildsen, Mark Leggas, Jamie Horn, Michelle E Ehrlich, Julie A Blendy
DEG microarray ICR mouse hypothalamus chronic alcohol vs. control_pvalue
Description:
We used a two-bottle free-choice paradigm to measure alcohol drinking [42], and studied effect of chronic alcohol consumption during adolescent development. Male adolescent ICR (outbred) mice (3 weeks of age) were divided into two alcohol groups, one with free access to 5% alcohol, and the other to 10% alcohol, so as to determine if there was a difference in alcohol consumption behavior due to difference in alcohol concentration. In addition, a water-only control group (each mouse had 2 bottles, both filled with water) was used. For brain tissue processing for gene expression analysis, 19 mice with 7 weeks alcohol exposure were selected and grouped into alcohol sample groups (n=1–3 per sample group). Samples A1-A3 had mice with relatively less alcohol consumed (0.50±0.38 g/kg/day); samples A4-A9 had mice with relatively more alcohol consumed (4.80±0.36 g/kg/day); these were significantly different (p<0.05, Unpaired t test with Welch's correction). The rationale for such an approach of sample pooling was to cover the spectrum of mouse alcohol consumption behavior, so that the underlying gene expression patterns may be discernible. For water-only controls, nine mice were selected randomly, and grouped into water sample groups (n=3 per sample group), designated samples C1-C3. RNA samples extracted from hypothalamus were used in gene expression analysis, using the Agilent mouse whole genome microarray chip set.
Authors:
Hong Zou, Ke Wang, Yang Gao, Huaiguang Song, Qinglian Xie, Meilei Jin, Guoping Zhao, Huasheng Xiao, Lei Yu
DEG microarray ICR mouse hypothalamus chronic alcohol vs. control_logFC
Description:
We used a two-bottle free-choice paradigm to measure alcohol drinking [42], and studied effect of chronic alcohol consumption during adolescent development. Male adolescent ICR (outbred) mice (3 weeks of age) were divided into two alcohol groups, one with free access to 5% alcohol, and the other to 10% alcohol, so as to determine if there was a difference in alcohol consumption behavior due to difference in alcohol concentration. In addition, a water-only control group (each mouse had 2 bottles, both filled with water) was used. For brain tissue processing for gene expression analysis, 19 mice with 7 weeks alcohol exposure were selected and grouped into alcohol sample groups (n=1–3 per sample group). Samples A1-A3 had mice with relatively less alcohol consumed (0.50±0.38 g/kg/day); samples A4-A9 had mice with relatively more alcohol consumed (4.80±0.36 g/kg/day); these were significantly different (p<0.05, Unpaired t test with Welch's correction). The rationale for such an approach of sample pooling was to cover the spectrum of mouse alcohol consumption behavior, so that the underlying gene expression patterns may be discernible. For water-only controls, nine mice were selected randomly, and grouped into water sample groups (n=3 per sample group), designated samples C1-C3. RNA samples extracted from hypothalamus were used in gene expression analysis, using the Agilent mouse whole genome microarray chip set.
Authors:
Hong Zou, Ke Wang, Yang Gao, Huaiguang Song, Qinglian Xie, Meilei Jin, Guoping Zhao, Huasheng Xiao, Lei Yu
Whole Brain Gene Expression Correlates for LM_BASELINE measured in BXD RI Males obtained using INIA Brain mRNA M430 (Jun06) RMA. The LM_BASELINE measures Baseline activity in fear conditioning apparatus under the domain Basal Behavior. 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
GSE27786_LSK_VS_ERYTHROBLAST_DN
Genes down-regulated in comparison of LSK versus erythroblasts.
c7 - Genesets containing immunologic signatures defined directly from microarray gene expression data from immunologic studies.
Molecular Signatures Database (MSigDB) Geneset. This geneset was imported from one of the MSigDB collections.
gene2msig v. 0.1.0
Last updated 2015.08.31
GSE17721_PAM3CSK4_VS_CPG_12H_BMDM_UP
Genes up-regulated in comparison of dendritic cells (DC) stimulated with Pam3Csk4 (TLR1/2 agonist) at 12 h versus DC cells stimulated with CpG DNA (TLR9 agonist) at 12 h.
c7 - Genesets containing immunologic signatures defined directly from microarray gene expression data from immunologic studies.
Molecular Signatures Database (MSigDB) Geneset. This geneset was imported from one of the MSigDB collections.
gene2msig v. 0.1.0
Last updated 2015.08.31
GSE17721_CPG_VS_GARDIQUIMOD_12H_BMDM_DN
Genes down-regulated in comparison of dendritic cells (DC) stimulated with CpG DNA (TLR9 agonist) at 12 h versus DC cells stimulated with Gardiquimod (TLR7 agonist) at 12 h.
c7 - Genesets containing immunologic signatures defined directly from microarray gene expression data from immunologic studies.
Molecular Signatures Database (MSigDB) Geneset. This geneset was imported from one of the MSigDB collections.
gene2msig v. 0.1.0
Last updated 2015.08.31
GSE27786_LIN_NEG_VS_ERYTHROBLAST_DN
Genes down-regulated in comparison of lineage negative versus erythroblasts.
c7 - Genesets containing immunologic signatures defined directly from microarray gene expression data from immunologic studies.
Molecular Signatures Database (MSigDB) Geneset. This geneset was imported from one of the MSigDB collections.
gene2msig v. 0.1.0
Last updated 2015.08.31
GSE32423_CTRL_VS_IL7_MEMORY_CD8_TCELL_UP
Genes up-regulated in comparison of memory CD8 T cells versus those treated with IL7 <a href='http://www.ncbi.nlm.nih.gov/gene/3574'>[GeneID=3574]</a>.
c7 - Genesets containing immunologic signatures defined directly from microarray gene expression data from immunologic studies.
Molecular Signatures Database (MSigDB) Geneset. This geneset was imported from one of the MSigDB collections.
gene2msig v. 0.1.0
Last updated 2015.08.31
Differential gene expression in nucleus accumbens somatostatin interneurons_cocaine_mice_logFC
Description:
To characterize transcriptional alterations that cocaine induces in these cells, we perform cell type-specific RNA-sequencing on FACS-isolated nuclei of somatostatin interneurons and identified 1100 DETs enriched for processes related to neural plasticity. To profile the entire (non poly-A selected) transcriptome of NAc somatostatin interneurons, we generated a transgenic reporter line (SST-TLG498 mice) to label the nuclei of these cells with a modified form of EGFP that is retained in the nuclear membrane (EGFP-F)22, enabling their isolation from NAc dissections using FACS. We succeeded in FACS-isolating nuclei suitable for RNA-sequencing from individual SST-TLG498 mice. We proceeded with differential expression analysis of the RNA-sequencing data to identify differentially expressed transcripts (DETs) in NAc somatostatin interneurons in response to repeated cocaine exposure: 778 transcripts were upregulated by cocaine and 322 were downregulated.
Authors:
Efrain A Ribeiro, Marine Salery, Joseph R Scarpa, Erin S Calipari, Peter J Hamilton, Stacy M Ku, Hope Kronman, Immanuel Purushothaman, Barbara Juarez, Mitra Heshmati, Marie Doyle, Casey Lardner, Dominicka Burek, Ana Strat, Stephen Pirpinias, Ezekiell Mouzon, Ming-Hu Han, Rachael L Neve, Rosemary C Bagot, Andrew Kasarskis, Ja Wook Koo, Eric J Nestler
DEG female mouse forebrain PND1 morphine vs saline_pvalue
Description:
To examine forebrain transcriptomic changes that might elucidate mechanisms of withdrawal, delayed development, and any long-term behavior changes, we generated transcriptomic signatures following our “3-trimester” exposure model (3-Tri). In addition, we also examined transcriptomes from animals that received opioids only during the gestational period (PND1) or only during the last trimester from PND 1–14 (PND 14). We sought to determine whether transcriptomic signatures vary based on the window of exposure, perhaps contributing to the discrepancies in the literature regarding acute and long-term outcomes. Brains were dissected from PND 1 pups 6 h after discovery. Brains were dissected from post-natal exposure only (PND 14) or 3-trimester exposure (3-tri) 6 h after the last morphine or saline injection. The number of animals per group was similar (N = 5–7 animals, male and female C57Bl/6NTac mice), and the quality controls, library construction and sequence parameters were also identical across all groups. Libraries were sequenced on a NovaSeq 6000 at a depth of 30 million total reads/sample using paired-end sequencing of 150 base pairs (PE150), to a depth of 30 million total reads/sample. Reads were then mapped to the mouse reference genome (Mus Musculus, GRCm38/mm10) using HISAT2 (version 2.2.1), and duplicated fragments were removed using Picard MarkDuplicates. Differential expression analysis between two conditions (e.g., Morphine and Saline) was performed in R (version 4.1.1) with DESeq2 (v1.32.0) package. Genes were assigned by the authors as differentially expressed if the (adjusted) (nominal) p-value < 0.05. All genes/scores are presented here.
Authors:
Amelia D Dunn, Shivon A Robinson, Chiso Nwokafor, Molly Estill, Julia Ferrante, Li Shen, Crystal O Lemchi, Jordi Creus-Muncunill, Angie Ramirez, Juliet Mengaziol, Julia K Brynildsen, Mark Leggas, Jamie Horn, Michelle E Ehrlich, Julie A Blendy
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 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
Peroxisome proliferator-activated receptors (PPARs) are nuclear hormone receptors that act as ligand-activated transcription factors. Although prescribed for dyslipidemia and type-II diabetes, PPAR agonists also possess anti-addictive characteristics. PPAR agonists decrease ethanol consumption and reduce withdrawal severity and susceptibility to stress-induced relapse in rodents. However, the cellular and molecular mechanisms facilitating these properties have yet to be investigated. We tested three PPAR agonists in a continuous access two-bottle choice (2BC) drinking paradigm and found that tesaglitazar (PPARα/γ; 1.5 mg/kg) and fenofibrate (PPARα; 150 mg/kg) decreased ethanol consumption in male C57BL/6J mice while bezafibrate (PPARα/γ/β; 75 mg/kg) did not. We hypothesized that changes in brain gene expression following fenofibrate and tesaglitazar treatment lead to reduced ethanol drinking. We studied unbiased genomic profiles in areas of the brain known to be important for ethanol dependence, the prefrontal cortex (PFC) and amygdala, and also profiled gene expression in liver. Genomic profiles from the non-effective bezafibrate treatment were used to filter out genes not associated with ethanol consumption. Because PPAR agonists are anti-inflammatory, they would be expected to target microglia and astrocytes. Surprisingly, PPAR agonists produced a strong neuronal signature in mouse brain, and fenofibrate and tesaglitazar (but not bezafibrate) targeted a subset of GABAergic interneurons in the amygdala. Weighted gene co-expression network analysis (WGCNA) revealed co-expression of treatment-significant genes. Functional annotation of these gene networks suggested that PPAR agonists might act via neuropeptide and dopaminergic signaling pathways in the amygdala. Our results reveal gene targets through which PPAR agonists can affect alcohol consumption behavior.
Authors:
Laura B Ferguson, Dana Most, Yuri A Blednov, R Adron Harris
Peroxisome proliferator-activated receptors (PPARs) are nuclear hormone receptors that act as ligand-activated transcription factors. Although prescribed for dyslipidemia and type-II diabetes, PPAR agonists also possess anti-addictive characteristics. PPAR agonists decrease ethanol consumption and reduce withdrawal severity and susceptibility to stress-induced relapse in rodents. However, the cellular and molecular mechanisms facilitating these properties have yet to be investigated. We tested three PPAR agonists in a continuous access two-bottle choice (2BC) drinking paradigm and found that tesaglitazar (PPARα/γ; 1.5 mg/kg) and fenofibrate (PPARα; 150 mg/kg) decreased ethanol consumption in male C57BL/6J mice while bezafibrate (PPARα/γ/β; 75 mg/kg) did not. We hypothesized that changes in brain gene expression following fenofibrate and tesaglitazar treatment lead to reduced ethanol drinking. We studied unbiased genomic profiles in areas of the brain known to be important for ethanol dependence, the prefrontal cortex (PFC) and amygdala, and also profiled gene expression in liver. Genomic profiles from the non-effective bezafibrate treatment were used to filter out genes not associated with ethanol consumption. Because PPAR agonists are anti-inflammatory, they would be expected to target microglia and astrocytes. Surprisingly, PPAR agonists produced a strong neuronal signature in mouse brain, and fenofibrate and tesaglitazar (but not bezafibrate) targeted a subset of GABAergic interneurons in the amygdala. Weighted gene co-expression network analysis (WGCNA) revealed co-expression of treatment-significant genes. Functional annotation of these gene networks suggested that PPAR agonists might act via neuropeptide and dopaminergic signaling pathways in the amygdala. Our results reveal gene targets through which PPAR agonists can affect alcohol consumption behavior.
Authors:
Laura B Ferguson, Dana Most, Yuri A Blednov, R Adron Harris
Peroxisome proliferator-activated receptors (PPARs) are nuclear hormone receptors that act as ligand-activated transcription factors. Although prescribed for dyslipidemia and type-II diabetes, PPAR agonists also possess anti-addictive characteristics. PPAR agonists decrease ethanol consumption and reduce withdrawal severity and susceptibility to stress-induced relapse in rodents. However, the cellular and molecular mechanisms facilitating these properties have yet to be investigated. We tested three PPAR agonists in a continuous access two-bottle choice (2BC) drinking paradigm and found that tesaglitazar (PPARα/γ; 1.5 mg/kg) and fenofibrate (PPARα; 150 mg/kg) decreased ethanol consumption in male C57BL/6J mice while bezafibrate (PPARα/γ/β; 75 mg/kg) did not. We hypothesized that changes in brain gene expression following fenofibrate and tesaglitazar treatment lead to reduced ethanol drinking. We studied unbiased genomic profiles in areas of the brain known to be important for ethanol dependence, the prefrontal cortex (PFC) and amygdala, and also profiled gene expression in liver. Genomic profiles from the non-effective bezafibrate treatment were used to filter out genes not associated with ethanol consumption. Because PPAR agonists are anti-inflammatory, they would be expected to target microglia and astrocytes. Surprisingly, PPAR agonists produced a strong neuronal signature in mouse brain, and fenofibrate and tesaglitazar (but not bezafibrate) targeted a subset of GABAergic interneurons in the amygdala. Weighted gene co-expression network analysis (WGCNA) revealed co-expression of treatment-significant genes. Functional annotation of these gene networks suggested that PPAR agonists might act via neuropeptide and dopaminergic signaling pathways in the amygdala. Our results reveal gene targets through which PPAR agonists can affect alcohol consumption behavior.
Authors:
Laura B Ferguson, Dana Most, Yuri A Blednov, R Adron Harris
Peroxisome proliferator-activated receptors (PPARs) are nuclear hormone receptors that act as ligand-activated transcription factors. Although prescribed for dyslipidemia and type-II diabetes, PPAR agonists also possess anti-addictive characteristics. PPAR agonists decrease ethanol consumption and reduce withdrawal severity and susceptibility to stress-induced relapse in rodents. However, the cellular and molecular mechanisms facilitating these properties have yet to be investigated. We tested three PPAR agonists in a continuous access two-bottle choice (2BC) drinking paradigm and found that tesaglitazar (PPARα/γ; 1.5 mg/kg) and fenofibrate (PPARα; 150 mg/kg) decreased ethanol consumption in male C57BL/6J mice while bezafibrate (PPARα/γ/β; 75 mg/kg) did not. We hypothesized that changes in brain gene expression following fenofibrate and tesaglitazar treatment lead to reduced ethanol drinking. We studied unbiased genomic profiles in areas of the brain known to be important for ethanol dependence, the prefrontal cortex (PFC) and amygdala, and also profiled gene expression in liver. Genomic profiles from the non-effective bezafibrate treatment were used to filter out genes not associated with ethanol consumption. Because PPAR agonists are anti-inflammatory, they would be expected to target microglia and astrocytes. Surprisingly, PPAR agonists produced a strong neuronal signature in mouse brain, and fenofibrate and tesaglitazar (but not bezafibrate) targeted a subset of GABAergic interneurons in the amygdala. Weighted gene co-expression network analysis (WGCNA) revealed co-expression of treatment-significant genes. Functional annotation of these gene networks suggested that PPAR agonists might act via neuropeptide and dopaminergic signaling pathways in the amygdala. Our results reveal gene targets through which PPAR agonists can affect alcohol consumption behavior.
Authors:
Laura B Ferguson, Dana Most, Yuri A Blednov, R Adron Harris
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