Evidence map›Paper›PMID 29674951›Full record

ArticleFrontiers in molecular neuroscience2018

Integrating Genetic and Gene Co-expression Analysis Identifies Gene Networks Involved in Alcohol and Stress Responses.

Jie Luo, Pei Xu, Peijian Cao, Hongjian Wan, Xiaonan Lv, Shengchun Xu, Gangjun Wang, Melloni N Cook, Byron C Jones, Lu Lu and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in molecular neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.6field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 14 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 5 institutions in 2 countries.

Jie LuoCentral Laboratory of Zhejiang Academy of Agricultural Sciences, Zhejiang Academy of Agricultural Sciences Hangzhou, China.
Pei XuInstitute of Vegetables, Zhejiang Academy of Agricultural Sciences Hangzhou, China.
Peijian CaoChina Tobacco Gene Research Center, Zhengzhou Tobacco Research Institute of CNTC Zhengzhou, China.
Hongjian WanInstitute of Vegetables, Zhejiang Academy of Agricultural Sciences Hangzhou, China.
Xiaonan LvInstitute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences Hangzhou, China.
Shengchun XuCentral Laboratory of Zhejiang Academy of Agricultural Sciences, Zhejiang Academy of Agricultural Sciences Hangzhou, China.
Gangjun WangCentral Laboratory of Zhejiang Academy of Agricultural Sciences, Zhejiang Academy of Agricultural Sciences Hangzhou, China.
Melloni N CookDepartment of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center Memphis, TN, United States.
Byron C JonesDepartment of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center Memphis, TN, United States.
Lu LuDepartment of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center Memphis, TN, United States.
Xusheng WangSt. Jude Proteomics Facility, St. Jude Children's Research Hospital Memphis, TN, United States.
ZheJiang Academy of Agricultural Sciences · CNUniversity of Tennessee Health Science Center · USAffiliated Hospital of Nantong University · CNChina Tobacco · CNSt. Jude Children's Research Hospital · US

Funding

Genetic Analysis of Ethanol-Mediated Stress ReductionU01AA014425 · NIAAA · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI LU, LU · 2004 to 2008
$2.1M
Genetics of Chronic Mild Stress and Alcohol ConsumptionR01AA021951 · NIAAA · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI JONES, BYRON C, LU, LU · 2014 to 2017
$1.5M
NIAAA NIH HHS R01 AA021951NIAAA NIH HHS U01 AA014425
6 · The paper itself

Abstract

Although the link between stress and alcohol is well recognized, the underlying mechanisms of how they interplay at the molecular level remain unclear. The purpose of this study is to identify molecular networks underlying the effects of alcohol and stress responses, as well as their interaction on anxiety behaviors in the hippocampus of mice using a systems genetics approach. Here, we applied a gene co-expression network approach to transcriptomes of 41 BXD mouse strains under four conditions: stress, alcohol, stress-induced alcohol and control. The co-expression analysis identified 14 modules and characterized four expression patterns across the four conditions. The four expression patterns include up-regulation in no restraint stress and given an ethanol injection (NOE) but restoration in restraint stress followed by an ethanol injection (RSE; pattern 1), down-regulation in NOE but rescue in RSE (pattern 2), up-regulation in both restraint stress followed by a saline injection (RSS) and NOE, and further amplification in RSE (pattern 3), and up-regulation in RSS but reduction in both NOE and RSE (pattern 4). We further identified four functional subnetworks by superimposing protein-protein interactions (PPIs) to the 14 co-expression modules, including γ-aminobutyric acid receptor (GABA) signaling, glutamate signaling, neuropeptide signaling, cAMP-dependent signaling. We further performed module specificity analysis to identify modules that are specific to stress, alcohol, or stress-induced alcohol responses. Finally, we conducted causality analysis to link genetic variation to these identified modules, and anxiety behaviors after stress and alcohol treatments. This study underscores the importance of integrative analysis and offers new insights into the molecular networks underlying stress and alcohol responses.

Indexed as

alcoholBXD mice strainscausality analysisnetwork analysisstresstranscriptome

Identifiers

PMID29674951
PMCPMC5895640
OpenAlexW2795467131

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.