Data from our previous funding period and supporting evidence from other INIA-Neuroimmune (INIA-N) laboratories provide the foundation for the overall hypothesis of this proposal: Behavioral changes characteristic of excessive alcohol consumption and alcohol use disorder (AUD) are due, in part, to neuroimmune mechanisms that significantly reshape the transcriptome. Drug repurposing algorithms can analyze cross-species transcriptome changes to predict compounds that reduce alcohol consumption. We propose that brain dysfunction in alcoholics is the result of dysregulation in both the protein coding and non-coding transcriptome. Advances in genomic studies by our research team and INIA-N collaborators have enabled us to generate transcriptome data on an unprecedented scale. Devising methods to visualize and analyze these data to produce meaningful biological interpretation is one of the next important steps.
We aim to take full advantage of the emerging technologies, allowing us to move forward in the post- genomic, ?big data? era. We previously used RNA sequencing (RNA-Seq) to define the transcriptome in four brain regions of 90 human cases (alcoholics and matched controls). In addition to identifying novel splice variants and co-variation with lifetime alcohol consumption, we identified novel changes in long non-coding RNAs (lncRNAs) in human brain and propose that these play an important role in gene expression changes. Differentially expressed lncRNAs that are correlated with alcohol consumption and have syntenic conservation between humans and mice will be prioritized for genetic and behavioral testing in mice in collaboration with INIA-N investigators. Other interactions involve mining the RNA-Seq transcriptome profiles in human subjects and macaque to link expression changes with genetic differences found in the Collaborative Studies on Genetics of Alcoholism (COGA). This will allow us to define, in unprecedented detail, changes in RNA splicing and pathways constructed from detected single-nucleotide polymorphisms. Finally, we will study the convergence of transcriptome changes in human, macaque, and rodent brain to determine which rodent models reflect the gene expression changes seen in human AUD. The overlapping changes in expression and associated networks produced by excessive alcohol consumption can be used to predict drugs that will normalize the network using cutting-edge computational analyses. Thus, we and INIA-N collaborators will utilize our combined transcriptome data to predict novel therapeutics based on cross-species convergence of gene networks and then test FDA-approved drugs predicted to target the affected networks in mouse and rat models of excessive alcohol consumption. The most promising drugs will then be selected for testing in human alcoholics. These efforts integrate advanced computational, genomic, molecular, functional system, and behavioral studies to be integrated into a systematic framework designed to advance treatment strategies for AUD.
We propose that alcohol-induced changes in brain function are due to alterations in gene expression. Together with other INIA-Neuroimmune investigators, we will explore these expression changes in different species using several innovative approaches, including next-generation sequencing, study of long non-coding RNAs, and bioinformatic strategies, to identify potential treatment options for excessive alcohol drinking from existing FDA-approved drugs. This work will focus on neuroimmune-related genes and drug candidates and will provide new strategies and guidelines for gene-based diagnosis and treatment of alcohol use disorder.
| Ferguson, Laura B; Zhang, Lingling; Kircher, Daniel et al. (2018) Dissecting Brain Networks Underlying Alcohol Binge Drinking Using a Systems Genomics Approach. Mol Neurobiol : |
| Farris, Sean P; Riley, Brien P; Williams, Robert W et al. (2018) Cross-species molecular dissection across alcohol behavioral domains. Alcohol 72:19-31 |
| McCarthy, Gizelle M; Farris, Sean P; Blednov, Yuri A et al. (2018) Microglial-specific transcriptome changes following chronic alcohol consumption. Neuropharmacology 128:416-424 |
| Wang, Bi-Cheng; Lin, Guo-He; Wang, Bo et al. (2018) UHRF1 suppression promotes cell differentiation and reduces inflammatory reaction in anaplastic thyroid cancer. Oncotarget 9:31945-31957 |
| Mayfield, R Dayne; Harris, R Adron (2018) Persistence of Drug Memories: Melting Transcriptomes. Biol Psychiatry 84:860-861 |
| Erickson, Emma K; Farris, Sean P; Blednov, Yuri A et al. (2018) Astrocyte-specific transcriptome responses to chronic ethanol consumption. Pharmacogenomics J 18:578-589 |
| Most, Dana; Salem, Nihal A; Tiwari, Gayatri R et al. (2018) Silencing synaptic MicroRNA-411 reduces voluntary alcohol consumption in mice. Addict Biol : |
| Ferguson, Laura B; Harris, R Adron; Mayfield, Roy Dayne (2018) From gene networks to drugs: systems pharmacology approaches for AUD. Psychopharmacology (Berl) 235:1635-1662 |
| Ferguson, Laura B; Ozburn, Angela R; Ponomarev, Igor et al. (2018) Genome-Wide Expression Profiles Drive Discovery of Novel Compounds that Reduce Binge Drinking in Mice. Neuropsychopharmacology 43:1257-1266 |
| Osterndorff-Kahanek, Elizabeth A; Tiwari, Gayatri R; Lopez, Marcelo F et al. (2018) Long-term ethanol exposure: Temporal pattern of microRNA expression and associated mRNA gene networks in mouse brain. PLoS One 13:e0190841 |
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