Literature DB >> 20491071

Network analysis of EtOH-related candidate genes.

An-Yuan Guo1, Jingchun Sun, Peilin Jia, Zhongming Zhao.   

Abstract

Recently, we collected many large-scale datasets for alcohol dependence and EtOH response in five organisms and deposited them in our EtOH-related gene resource database (ERGR, http://bioinfo.mc.vanderbilt.edu/ERGR/). Based on multidimensional evidence among these datasets, we prioritized 57 EtOH-related candidate genes. To explore their biological roles, and the molecular mechanisms of EtOH response and alcohol dependence, we examined the features of these genes by the Gene Ontology (GO) term-enrichment test and network/pathway analysis. Our analysis revealed that these candidate genes were highly enriched in alcohol dependence/alcoholism and highly expressed in brain or liver tissues. All the significantly enriched GO terms were related to neurotransmitter systems or EtOH metabolic processes. Using the Ingenuity Pathway Analysis system, we found that these genes were involved in networks of neurological disease, cardiovascular disease, inflammatory response, and small molecular metabolism. Many key genes in signaling pathways were in the central position of these networks. Furthermore, our protein-protein interaction (PPI) network analysis suggested some novel candidate genes which also had evidence in the ERGR database. This study demonstrated that our candidate gene selection is effective and our network/pathway analysis is useful for uncovering the molecular mechanisms of EtOH response and alcohol dependence. This approach can be applied to study the features of candidate genes of other complex traits/phenotypes.

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Year:  2010        PMID: 20491071      PMCID: PMC2935470          DOI: 10.1002/cbdv.200900318

Source DB:  PubMed          Journal:  Chem Biodivers        ISSN: 1612-1872            Impact factor:   2.408


  24 in total

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Authors:  Danielle M Dick; Tatiana Foroud
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Review 3.  Candidate genes for alcohol dependence: animal studies.

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5.  Gene expression in human alcoholism: microarray analysis of frontal cortex.

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  3 in total

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Journal:  Neuropsychopharmacology       Date:  2013-07-31       Impact factor: 7.853

2.  Dynamic protein interaction modules in human hepatocellular carcinoma progression.

Authors:  Hui Yu; Chen-Ching Lin; Yuan-Yuan Li; Zhongming Zhao
Journal:  BMC Syst Biol       Date:  2013-12-09

3.  Multi-species data integration and gene ranking enrich significant results in an alcoholism genome-wide association study.

Authors:  Zhongming Zhao; An-Yuan Guo; Edwin J C G van den Oord; Fazil Aliev; Peilin Jia; Howard J Edenberg; Brien P Riley; Danielle M Dick; Jill C Bettinger; Andrew G Davies; Michael S Grotewiel; Marc A Schuckit; Arpana Agrawal; John Kramer; John I Nurnberger; Kenneth S Kendler; Bradley T Webb; Michael F Miles
Journal:  BMC Genomics       Date:  2012-12-17       Impact factor: 3.969

  3 in total

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