Gene network analysis shows immune-signaling and ERK1/2 as novel genetic markers for multiple addiction phenotypes: alcohol, smoking and opioid addiction

BMC Systems Biology

Sanjay Shete¹  Sai-Ching J. Yeung²  Jian Wang¹  Christine Yuan²  Cielito C. Reyes-Gibby² 

[1]Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston 77030, TX, USA

[2]Department of Emergency Medicine, The University of Texas MD Anderson Cancer Center, Houston 77030, TX, USA

关键词: Cancer;    Inflammation;    Genes;    Addiction;    Alcohol;    Smoking;    Opioid;    Pain;   

Others  :  1233564
DOI  :  10.1186/s12918-015-0167-x

 received in 2014-09-30, accepted in 2015-05-12,  发布年份 2015

【 摘 要 】

Background

Addictions to alcohol and tobacco, known risk factors for cancer, are complex heritable disorders. Addictive behaviors have a bidirectional relationship with pain. We hypothesize that the associations between alcohol, smoking, and opioid addiction observed in cancer patients have a genetic basis. Therefore, using bioinformatics tools, we explored the underlying genetic basis and identified new candidate genes and common biological pathways for smoking, alcohol, and opioid addiction.

Results

Literature search showed 56 genes associated with alcohol, smoking and opioid addiction. Using Core Analysis function in Ingenuity Pathway Analysis software, we found that ERK1/2 was strongly interconnected across all three addiction networks. Genes involved in immune signaling pathways were shown across all three networks. Connect function from IPA My Pathway toolbox showed that DRD2 is the gene common to both the list of genetic variations associated with all three addiction phenotypes and the components of the brain neuronal signaling network involved in substance addiction. The top canonical pathways associated with the 56 genes were: 1) calcium signaling, 2) GPCR signaling, 3) cAMP-mediated signaling, 4) GABA receptor signaling, and 5) G-alpha i signaling.

Conlusions

Cancer patients are often prescribed opioids for cancer pain thus increasing their risk for opioid abuse and addiction. Our findings provide candidate genes and biological pathways underlying addiction phenotypes, which may be future targets for treatment of addiction. Further study of the variations of the candidate genes could allow physicians to make more informed decisions when treating cancer pain with opioid analgesics.

【 授权许可】

   
2015 Reyes-Gibby et al.

【 图 表 】

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