生物谷报道:来自北京大学生命科学学院植物基因工程和蛋白质工程国家重点实验室(National Laboratory of Protein Engineering and Plant Genetic Engineering,生物谷注)生物信息学中心的研究人员发现,人体大约400种基因似乎更容易使人对毒品上瘾。这一发现对治疗吸毒者以及对毒品上瘾的控制开创了新的方法。这一研究成果公布在PLoS Comput Biol上。
在对复杂病症的研究中,找出路线图非常重要,因为这种做法缩小了对基因和蛋白质的研究范围。在一些癌症的治疗研究中,路线图能够帮助医生更加准确地诊断并且预测疾病的发展。
在这篇研究中,研究人员就四类上瘾物质(可卡因、鸦片、酒精以及尼古丁)进行了研究,并且构建出导致毒品上瘾的五种路线图,或称“分子路径”。 他们认为在各种使人容易毒品上瘾的因素中,遗传基因占60%,剩下40%跟环境因素有关。“这些常见的路径潜藏在回应机制之下,很可能成为有效治疗各种上瘾症状的着眼点和目标”。
通过分析过去30年中同行发表的1,000多份有关毒瘾与基因和染色体区域联系的医疗出版物,研究人员也列出与吸毒成瘾相关的1,500个基因的清单。在路径图中,其中一些基因比其他基因出现更频繁,科学家们已经将清单缩小至396个。
生物谷推荐原始出处:
Genes and (Common) Pathways Underlying Drug Addiction
Chuan-Yun Li, Xizeng Mao, Liping Wei*
1 Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing, People's Republic of China
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.
Received: July 18, 2007; Accepted: November 19, 2007; Published: January 4, 2008
附:
魏丽萍 博士
北京大学生命科学学院生物信息中心 教授、主任
蛋白质工程与植物基因工程国家重点实验室 副主任
Liping Wei, Ph.D.
Professor, Director
Center for Bioinformatics, College of Life Sciences
Peking University
Phone:010-6275-5206
Fax: 010-6276-4970
E-mail:weilp@mail.cbi.pku.edu.cn