title: Genes and (common) pathways underlying drug addiction.
abstract: Drug addiction is a serious worldwide problem with strong genetic and environmental influences. Different technologies have revealed a variety of genes and pathways underlying addiction; however, each individual technology can be biased and incomplete. We integrated 2,343 items of evidence from peer-reviewed publications between 1976 and 2006 linking genes and chromosome regions to addiction by single-gene strategies, microrray, proteomics, or genetic studies. We identified 1,500 human addiction-related genes and developed KARG (http://karg.cbi.pku.edu.cn), the first molecular database for addiction-related genes with extensive annotations and a friendly Web interface. We then performed a meta-analysis of 396 genes that were supported by two or more independent items of evidence to identify 18 molecular pathways that were statistically significantly enriched, covering both upstream signaling events and downstream effects. Five molecular pathways significantly enriched for all four different types of addictive drugs were identified as common pathways which may underlie shared rewarding and addictive actions, including two new ones, GnRH signaling pathway and gap junction. We connected the common pathways into a hypothetical common molecular network for addiction. We observed that fast and slow positive feedback loops were interlinked through CAMKII, which may provide clues to explain some of the irreversible features of addiction.
authors.affiliation: Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing, People's Republic of China.
authors.forename: Chuan-Yun
authors.initials: CY
authors.lastname: Li
authors.forename: Xizeng
authors.initials: X
authors.lastname: Mao
authors.forename: Liping
authors.initials: L
authors.lastname: Wei
mesh_terms: D015415:Biomarkers / Q000378:metabolism; D054732:Calcium-Calmodulin-Dependent Protein Kinase Type 2 / Q000378:metabolism*; D030562:Databases, Protein; D006801:Humans; D008954:Models, Biological; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction; D019966:Substance-Related Disorders / Q000378:metabolism*
chemical_list: D015415:Biomarkers; D020543:Proteome; D054732:Calcium-Calmodulin-Dependent Protein Kinase Type 2