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Dissecting Brain Networks Underlying Alcohol Binge Drinking Using a Systems Genomics Approach

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 drink...

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Autores principales: Ferguson, Laura B., Zhang, Lingling, Kircher, Daniel, Wang, Shi, Mayfield, R. Dayne, Crabbe, John C., Morrisett, Richard A., Harris, R. Adron, Ponomarev, Igor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6459809/
https://www.ncbi.nlm.nih.gov/pubmed/30062672
http://dx.doi.org/10.1007/s12035-018-1252-0
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author Ferguson, Laura B.
Zhang, Lingling
Kircher, Daniel
Wang, Shi
Mayfield, R. Dayne
Crabbe, John C.
Morrisett, Richard A.
Harris, R. Adron
Ponomarev, Igor
author_facet Ferguson, Laura B.
Zhang, Lingling
Kircher, Daniel
Wang, Shi
Mayfield, R. Dayne
Crabbe, John C.
Morrisett, Richard A.
Harris, R. Adron
Ponomarev, Igor
author_sort Ferguson, Laura B.
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s12035-018-1252-0) contains supplementary material, which is available to authorized users.
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spelling pubmed-64598092019-05-03 Dissecting Brain Networks Underlying Alcohol Binge Drinking Using a Systems Genomics Approach Ferguson, Laura B. Zhang, Lingling Kircher, Daniel Wang, Shi Mayfield, R. Dayne Crabbe, John C. Morrisett, Richard A. Harris, R. Adron Ponomarev, Igor Mol Neurobiol Article 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s12035-018-1252-0) contains supplementary material, which is available to authorized users. Springer US 2018-07-30 2019 /pmc/articles/PMC6459809/ /pubmed/30062672 http://dx.doi.org/10.1007/s12035-018-1252-0 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Ferguson, Laura B.
Zhang, Lingling
Kircher, Daniel
Wang, Shi
Mayfield, R. Dayne
Crabbe, John C.
Morrisett, Richard A.
Harris, R. Adron
Ponomarev, Igor
Dissecting Brain Networks Underlying Alcohol Binge Drinking Using a Systems Genomics Approach
title Dissecting Brain Networks Underlying Alcohol Binge Drinking Using a Systems Genomics Approach
title_full Dissecting Brain Networks Underlying Alcohol Binge Drinking Using a Systems Genomics Approach
title_fullStr Dissecting Brain Networks Underlying Alcohol Binge Drinking Using a Systems Genomics Approach
title_full_unstemmed Dissecting Brain Networks Underlying Alcohol Binge Drinking Using a Systems Genomics Approach
title_short Dissecting Brain Networks Underlying Alcohol Binge Drinking Using a Systems Genomics Approach
title_sort dissecting brain networks underlying alcohol binge drinking using a systems genomics approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6459809/
https://www.ncbi.nlm.nih.gov/pubmed/30062672
http://dx.doi.org/10.1007/s12035-018-1252-0
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