Molecular Brain Adaptations to Ethanol: Role of Glycogen Synthase Kinase-3 Beta in the Transition to Excessive Consumption

Alcoholism is a complex neuropsychiatric disease that is characterized by compulsive alcohol use and intensifying cravings and withdrawals, often culminating in physiologic dependency. Fundamental alterations in brain chemistry underlie the transition from initial ethanol exposure to repetitive excessive use. Key mediators of this adaptation include changes in gene expression and signal transduction. Here we investigated gene expression pathways in prefrontal cortex and nucleus accumbens following acute or chronic ethanol treatment, to identify genes with potentially conserved involvement in the long-term response of the corticolimbic system to repeated ethanol exposure. We investigated Gsk3b, which encodes glycogen synthase kinase 3-beta, as a highly ethanol responsive gene associated with risk for long-term maladaptive responses to ethanol. On the level of the protein, we found that GSK3B and to a lesser extent the GSK3A isoform showed robust increases in inhibitory phosphorylation following acute ethanol. This inhibition may underlie aspects of the behavioral response to acute ethanol, as pre-treatment with a GSK3B inhibitor (tideglusib) augmented ethanol’s locomotor effects. Following long term ethanol exposure, we re-tested GSK3B phosphorylation and found that its ethanol response is blunted, consistent with molecular tolerance as a corollary to increased consumption. As the prefrontal cortex (PFC) plays a vital role in the reward pathway via its glutamatergic projections to the nucleus accumbens, we investigated the role of the Gsk3b gene specifically in PFC and in glutamatergic neurons. Overexpression of Gsk3b in the PFC robustly increased ethanol consumption, while deletion in Camk2a-positive neurons significantly attenuated ethanol consumption. Pharmacologic antagonism of GSK3B also decreased drinking in a model of binge-like consumption. Collectively this data implicates GSK3B as a mediator of excessive ethanol intake via its kinase activity, wherein inhibition of the kinase via phosphorylation exerts a protective effect in the context of acute ethanol, but desensitizes with repeated exposure

Selective GSK3B Deletion in Camk2a+ Forebrain Neurons or Inhibition Via Tideglusib, Decreases Ethanol Consumption in C57BL/6J Mice

Purpose: We previously identified glycogen synthase kinase-3 beta (Gsk3b) as a central member of a gene network highly regulated by acute ethanol in medial prefrontal cortex (mPFC) and associated with risk for alcohol dependence in humans. Further, we have demonstrated modulation of Gsk3b alters ethanol consumption in rodent models. GSK3B could thus represent a potential new therapeutic target for the treatment of alcohol use disorder (AUD). Here, we investigate the mechanisms of Gsk3b action in ethanol consumption and report preclinical evidence for the selective GSK3B inhibitor, tideglusib, as a therapeutic agent for AUD. Methods: (1) Selective Cre-induced Gsk3b deletion in Camk2a-neurons within the forebrain using transgenic Camk2a-CreER/Gsk3b floxed mice bred with Gsk3b fl/fl mice to produce Cre/Gsk3b fl/fl mice, which were injected with tamoxifen to induce Gsk3b deletion or (2) selective pharmacological antagonism of GSK3B using Tideglusib delivered via gavage in a corn oil vehicle. Actions on drinking behavior were measured using mouse intermittent ethanol, two-bottle choice self-administration models in C57BL/6J mice. Results: Deletion of Gsk3b in Camk2a-neurons decreased ethanol consumption and preference. There was no significant effects of sex or sex*genotype on either consumption or preference, so sexes were pooled. Gsk3b deletion did not alter basal locomotor activity, anxiety-like behavior (light-dark box), taste preference for quinine or saccharin, or ethanol pharmacokinetics. Initial administration of tideglusib (100mg/kg twice daily) or corn oil vehicle via gavage decreased total fluid consumption in all groups, regardless of ethanol drinking history or tideglusib treatment. However, following prolonged tideglusib, mice decreased binge (2hr) and daily (24hr) ethanol consumption and preference after three weeks of administration relative to vehicle controls. Tideglusib studies were only performed in male mice. Control studies showed no effect of tideglusib on liver fat accumulation in ethanol consuming animals. Ongoing work is assessing alternative oral tideglusib delivery methods in decreasing ethanol consumption. Conclusion: These results suggest GSK3B may be a therapeutic target for treatment of AUD. Deletion of Gsk3b in forebrain Camk2a-neurons showed a regional and cell-type specificity in GSK3B’s modulation of ethanol consumption and preference, providing insight into the mechanisms of Gsk3b action in ethanol consumption. Targeting GSK3B using tideglusib, a selective GSK3B inhibitor, also produced a decrease in ethanol consumption and preference over water during the fourth week of treatment. These findings were consistent with previous work in our lab investigating the delivery of tideglusib through intraperitoneal injections, though these studies were limited to a shorter drug-administration period. Here we have used a more therapeutically translatable route of administration via oral gavage and begun to investigate the longer-term effects of tideglusib on ethanol behaviors and toxicity. Tideglusib is a clinically available agent that warrants investigation in the treatment of AUD. Supported by NIAAA grants P50AA022537 and R01AA027581.https://scholarscompass.vcu.edu/gradposters/1161/thumbnail.jp

Brain deficit patterns of metabolic illnesses overlap with those for major depressive disorder: A new metric of brain metabolic disease

Metabolic illnesses (MET) are detrimental to brain integrity and are common comorbidities in patients with mental illnesses, including major depressive disorder (MDD). We quantified effects of MET on standard regional brain morphometric measures from 3D brain MRI as well as diffusion MRI in a large sample of UK BioBank participants. The pattern of regional effect sizes of MET in non-psychiatric UKBB subjects was significantly correlated with the spatial profile of regional effects reported by the largest meta-analyses in MDD but not in bipolar disorder, schizophrenia or Alzheimer\u27s disease. We used a regional vulnerability index (RVI) for MET (RVI-MET) to measure individual\u27s brain similarity to the expected patterns in MET in the UK Biobank sample. Subjects with MET showed a higher effect size for RVI-MET than for any of the individual brain measures. We replicated elevation of RVI-MET in a sample of MDD participants with MET versus non-MET. RVI-MET scores were significantly correlated with the volume of white matter hyperintensities, a neurological consequence of MET and age, in both groups. Higher RVI-MET in both samples was associated with obesity, tobacco smoking and frequent alcohol use but was unrelated to antidepressant use. In summary, MET effects on the brain were regionally specific and individual similarity to the pattern was more strongly associated with MET than any regional brain structural metric. Effects of MET overlapped with the reported brain differences in MDD, likely due to higher incidence of MET, smoking and alcohol use in subjects with MDD

ACSL6 Is Associated with the Number of Cigarettes Smoked and Its Expression Is Altered by Chronic Nicotine Exposure

Individuals with schizophrenia tend to be heavy smokers and are at high risk for tobacco dependence. However, the nature of the comorbidity is not entirely clear. We previously reported evidence for association of schizophrenia with SNPs and SNP haplotypes in a region of chromosome 5q containing the SPEC2, PDZ-GEF2 and ACSL6 genes. In this current study, analysis of the control subjects of the Molecular Genetics of Schizophrenia (MGS) sample showed similar pattern of association with number of cigarettes smoked per day (numCIG) for the same region. To further test if this locus is associated with tobacco smoking as measured by numCIG and FTND, we conducted replication and meta-analysis in 12 independent samples (n\u3e16,000) for two markers in ACSL6 reported in our previous schizophrenia study. In the meta-analysis of the replication samples, we found that rs667437 and rs477084 were significantly associated with numCIG (p = 0.00038 and 0.00136 respectively) but not with FTND scores. We then used in vitro and in vivo techniques to test if nicotine exposure influences the expression of ACSL6 in brain. Primary cortical culture studies showed that chronic (5-day) exposure to nicotine stimulated ACSL6 mRNA expression. Fourteen days of nicotine administration via osmotic mini pump also increased ACSL6 protein levels in the prefrontal cortex and hippocampus of mice. These increases were suppressed by injection of the nicotinic receptor antagonist mecamylamine, suggesting that elevated expression ofACSL6 requires nicotinic receptor activation. These findings suggest that variations in theACSL6 gene may contribute to the quantity of cigarettes smoked. The independent associations of this locus with schizophrenia and with numCIG in non-schizophrenic subjects suggest that this locus may be a common liability to both conditions

The Association between Systemic Inflammatory Cellular Levels and Lung Function: A Population-Based Study

Background: Lower lung function is associated with an elevated systemic white cell count in men. However, these observations have not been demonstrated in a representative population that includes females and may be susceptible to confounding by recent airway infections or recent cigarette smoking. We tested the hypothesis that lung function is inversely associated with systemic white cell count in a population-based study. Methods: The study population consisted adults aged 17290+ years who participated in the Third National Health and Nutrition Examination Survey who did not report a recent cough, cold or acute illness in a non-smoking and smoking population. Results: In non-smoking adults with the highest quintile of the total white cell count had a FEV1 125.3 ml lower than those in the lowest quintile (95 % confidence interval CI: 2163.1 to –87.5). Adults with the highest quintile of the total white cell count had a FVC 151.1 ml lower than those in the lowest quintile (95 % confidence interval CI: 2195.0 to 2107.2). Similar associations were observed for granulocytes, mononuclear cells and lymphocytes. In current smokers, similar smaller associations observed for total white cell count, granulocytes and mononuclear cells. Conclusions: Systemic cellular inflammation levels are inversely associated with lung function in a population of both nonsmokers and smokers without acute illnesses. This may contribute to the increased mortality observed in individuals with

Hierarchical Bayesian level set inversion

The level set approach has proven widely successful in the study of inverse problems for inter- faces, since its systematic development in the 1990s. Re- cently it has been employed in the context of Bayesian inversion, allowing for the quantification of uncertainty within the reconstruction of interfaces. However the Bayesian approach is very sensitive to the length and amplitude scales in the prior probabilistic model. This paper demonstrates how the scale-sensitivity can be cir- cumvented by means of a hierarchical approach, using a single scalar parameter. Together with careful con- sideration of the development of algorithms which en- code probability measure equivalences as the hierar- chical parameter is varied, this leads to well-defined Gibbs based MCMC methods found by alternating Metropolis-Hastings updates of the level set function and the hierarchical parameter. These methods demon- strably outperform non-hierarchical Bayesian level set methods

ACSL6 Is Associated with the Number of Cigarettes Smoked and Its Expression Is Altered by Chronic Nicotine Exposure

Individuals with schizophrenia tend to be heavy smokers and are at high risk for tobacco dependence. However, the nature of the comorbidity is not entirely clear. We previously reported evidence for association of schizophrenia with SNPs and SNP haplotypes in a region of chromosome 5q containing the SPEC2, PDZ-GEF2 and ACSL6 genes. In this current study, analysis of the control subjects of the Molecular Genetics of Schizophrenia (MGS) sample showed similar pattern of association with number of cigarettes smoked per day (numCIG) for the same region. To further test if this locus is associated with tobacco smoking as measured by numCIG and FTND, we conducted replication and meta-analysis in 12 independent samples (n>16,000) for two markers in ACSL6 reported in our previous schizophrenia study. In the meta-analysis of the replication samples, we found that rs667437 and rs477084 were significantly associated with numCIG (p = 0.00038 and 0.00136 respectively) but not with FTND scores. We then used in vitro and in vivo techniques to test if nicotine exposure influences the expression of ACSL6 in brain. Primary cortical culture studies showed that chronic (5-day) exposure to nicotine stimulated ACSL6 mRNA expression. Fourteen days of nicotine administration via osmotic mini pump also increased ACSL6 protein levels in the prefrontal cortex and hippocampus of mice. These increases were suppressed by injection of the nicotinic receptor antagonist mecamylamine, suggesting that elevated expression of ACSL6 requires nicotinic receptor activation. These findings suggest that variations in the ACSL6 gene may contribute to the quantity of cigarettes smoked. The independent associations of this locus with schizophrenia and with numCIG in non-schizophrenic subjects suggest that this locus may be a common liability to both conditions

Integrating mRNA and miRNA Weighted Gene Co-Expression Networks with eQTLs in the Nucleus Accumbens of Subjects with Alcohol Dependence.

Alcohol consumption is known to lead to gene expression changes in the brain. After performing weighted gene co-expression network analyses (WGCNA) on genome-wide mRNA and microRNA (miRNA) expression in Nucleus Accumbens (NAc) of subjects with alcohol dependence (AD; N = 18) and of matched controls (N = 18), six mRNA and three miRNA modules significantly correlated with AD were identified (Bonferoni-adj. p≤ 0.05). Cell-type-specific transcriptome analyses revealed two of the mRNA modules to be enriched for neuronal specific marker genes and downregulated in AD, whereas the remaining four mRNA modules were enriched for astrocyte and microglial specific marker genes and upregulated in AD. Gene set enrichment analysis demonstrated that neuronal specific modules were enriched for genes involved in oxidative phosphorylation, mitochondrial dysfunction and MAPK signaling. Glial-specific modules were predominantly enriched for genes involved in processes related to immune functions, i.e. cytokine signaling (all adj. p≤ 0.05). In mRNA and miRNA modules, 461 and 25 candidate hub genes were identified, respectively. In contrast to the expected biological functions of miRNAs, correlation analyses between mRNA and miRNA hub genes revealed a higher number of positive than negative correlations (χ2 test p≤ 0.0001). Integration of hub gene expression with genome-wide genotypic data resulted in 591 mRNA cis-eQTLs and 62 miRNA cis-eQTLs. mRNA cis-eQTLs were significantly enriched for AD diagnosis and AD symptom counts (adj. p = 0.014 and p = 0.024, respectively) in AD GWAS signals in a large, independent genetic sample from the Collaborative Study on Genetics of Alcohol (COGA). In conclusion, our study identified putative gene network hubs coordinating mRNA and miRNA co-expression changes in the NAc of AD subjects, and our genetic (cis-eQTL) analysis provides novel insights into the etiological mechanisms of AD

Correction: ACSL6 Is Associated with the Number of Cigarettes Smoked and Its Expression Is Altered by Chronic Nicotine Exposure

The following information was missing from the Acknowledgements section: This study also makes use of data generated by Genome-Wide Association of Schizophrenia Study (PI: Pablo V. Gejman). Funding support for schizophrenia GWAS was provided by the National Institute of Mental Health (R01 MH67257, R01 MH59588, R01 MH59571, R01 MH59565, R01 MH59587, R01 MH60870, R01 MH59566, R01 MH59586, R01 MH61675, R01 MH60879, R01 MH81800, U01 MH46276, U01 MH46289 U01 MH46318, U01 MH79469, and U01 MH79470) and the genotyping of samples was provided through the Genetic Association Information Network (GAIN). The datasets used for the analyses described in this manuscript were obtained from the database of Genotypes and Phenotypes (dbGaP) found at http://www.ncbi.nlm.nih.gov/gap [^] through dbGaP accession number phs000021.v3.p2 and phs000167v1.p1. The SAGE samples (PI: Laura J. Bierut) were GWAS datasets sponsored by the National Human Genome Research Institute. Funding support for the SAGE Study was provided through the NIH Genes, Environment and Health Initiative [GEI] (U01 HG004422). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research, was provided by the NIH GEI (U01HG004438), the National Institute on Alcohol Abuse and Alcoholism, the National Institute on Drug Abuse, and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease" (HHSN268200782096C). The datasets used for the analyses described in this manuscript were obtained from dbGaP at http://www.ncbi.nlm.nih.gov/projects/gap​/cgibin/study.cgi?study_id=phs000092.v1.​p1[^] through dbGaP accession number phs000092.v1.p. The SLD sample (also called EAGLE study, PI: Neil Caporaso) and the PLCO sample (PI: Maria Teresa Landi) were GWAS datasets sponsored by the National Cancer Institute for the study of genome wide scan for lung cancer and smoking. Funding support for the GWAS of Lung Cancer and Smoking was provided through the NIH Genes, Environment and Health Initiative [GEI] (Z01 CP 010200). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research, was provided by the NIH GEI (U01HG004438).The datasets used for the analyses described in this manuscript were obtained from dbGaP at http://www.ncbi.nlm.nih.gov/gap [^] through dbGaP accession number phs000093. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Correction: ACSL6 Is Associated with the Number of Cigarettes Smoked and Its Expression Is Altered by Chronic Nicotine Exposure

The following information was missing from the Acknowledgements section: This study also makes use of data generated by Genome-Wide Association of Schizophrenia Study (PI: Pablo V. Gejman). Funding support for schizophrenia GWAS was provided by the National Institute of Mental Health (R01 MH67257, R01 MH59588, R01 MH59571, R01 MH59565, R01 MH59587, R01 MH60870, R01 MH59566, R01 MH59586, R01 MH61675, R01 MH60879, R01 MH81800, U01 MH46276, U01 MH46289 U01 MH46318, U01 MH79469, and U01 MH79470) and the genotyping of samples was provided through the Genetic Association Information Network (GAIN). The datasets used for the analyses described in this manuscript were obtained from the database of Genotypes and Phenotypes (dbGaP) found at http://www.ncbi.nlm.nih.gov/gap [^] through dbGaP accession number phs000021.v3.p2 and phs000167v1.p1. The SAGE samples (PI: Laura J. Bierut) were GWAS datasets sponsored by the National Human Genome Research Institute. Funding support for the SAGE Study was provided through the NIH Genes, Environment and Health Initiative [GEI] (U01 HG004422). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research, was provided by the NIH GEI (U01HG004438), the National Institute on Alcohol Abuse and Alcoholism, the National Institute on Drug Abuse, and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease" (HHSN268200782096C). The datasets used for the analyses described in this manuscript were obtained from dbGaP at http://www.ncbi.nlm.nih.gov/projects/gap​/cgibin/study.cgi?study_id=phs000092.v1.​p1[^] through dbGaP accession number phs000092.v1.p. The SLD sample (also called EAGLE study, PI: Neil Caporaso) and the PLCO sample (PI: Maria Teresa Landi) were GWAS datasets sponsored by the National Cancer Institute for the study of genome wide scan for lung cancer and smoking. Funding support for the GWAS of Lung Cancer and Smoking was provided through the NIH Genes, Environment and Health Initiative [GEI] (Z01 CP 010200). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research, was provided by the NIH GEI (U01HG004438).The datasets used for the analyses described in this manuscript were obtained from dbGaP at http://www.ncbi.nlm.nih.gov/gap [^] through dbGaP accession number phs000093. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript