| Title |
Dissecting Brain Networks Underlying Alcohol Binge Drinking Using a Systems Genomics Approach
|
|---|---|
| Published in |
Molecular Neurobiology, July 2018
|
| DOI | 10.1007/s12035-018-1252-0 |
| Pubmed ID | |
| Authors |
Laura B. Ferguson, Lingling Zhang, Daniel Kircher, Shi Wang, R. Dayne Mayfield, John C. Crabbe, Richard A. Morrisett, R. Adron Harris, Igor Ponomarev |
| Abstract |
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. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 80% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 40% |
| Scientists | 2 | 40% |
| Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 34 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 9 | 26% |
| Student > Ph. D. Student | 6 | 18% |
| Student > Bachelor | 4 | 12% |
| Student > Doctoral Student | 3 | 9% |
| Professor | 2 | 6% |
| Other | 3 | 9% |
| Unknown | 7 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 18% |
| Neuroscience | 4 | 12% |
| Psychology | 3 | 9% |
| Agricultural and Biological Sciences | 2 | 6% |
| Medicine and Dentistry | 2 | 6% |
| Other | 5 | 15% |
| Unknown | 12 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 August 2019.
All research outputs
#8,060,302
of 25,641,627 outputs
Outputs from Molecular Neurobiology
#1,548
of 4,002 outputs
Outputs of similar age
#126,985
of 341,652 outputs
Outputs of similar age from Molecular Neurobiology
#51
of 134 outputs
Altmetric has tracked 25,641,627 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 4,002 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has gotten more attention than average, scoring higher than 60% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 341,652 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.
We're also able to compare this research output to 134 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.