Secondary Data Analyses for Substance Abuse Research

描述(申请人提供)：反复接触滥用药物会导致大脑奖赏回路的稳定变化，这将进一步导致依赖、敏感化和渴望等行为异常。了解药物成瘾的分子生物学将为治疗药物成瘾和预防新成瘾者的流行提供改进的治疗方法。已有研究表明，大脑中基因表达的变化有助于稳定调节参与药物成瘾的大脑奖赏回路。然而，这种调控背后的特定基因和转录机制仍然知之甚少。这项应用的总体目标是通过对与药物成瘾相关的丰富生物数据集的综合分析，为药物成瘾的分子机制提供更深入的见解。已经积累了大量的全基因组分子图谱数据集来研究药物成瘾。这些大规模数据提供了产生重大科学发现的巨大机会，但也给数据分析带来了巨大挑战。其他研究领域，特别是癌症研究领域的研究表明，有效地整合各种分子图谱数据集不仅可以增加数据分析的能力，还可以更全面地了解生物过程。这项研究的中心假设是，综合分析与药物成瘾相关的分子图谱数据集，将导致系统地了解与药物成瘾有关的重要基因和途径的分子机制和新发现。这项研究将重点放在可卡因成瘾上，因为可卡因是最突出的非法滥用药物之一，而且在可卡因成瘾方面已经积累了相当多的分子图谱数据。然而，建议的方法将是通用的，并适用于其他成瘾药物的研究。总而言之，该项目将提供：(1)更好地从机制上了解可卡因成瘾；(2)为综合分析吸毒成瘾数据提供强大的统计/计算工具；(3)为加强吸毒成瘾研究更广泛的知识基础设施提供一个全面的数据库。 公共卫生相关性：了解药物成瘾的分子生物学将为治疗药物成瘾和防止新成瘾者的流行提供改进的疗法。该项目将提供对可卡因成瘾更好的机械理解，并提供一个全面的数据库，以加强毒品成瘾研究的更广泛的知识基础设施。

DESCRIPTION (provided by applicant): Repeated exposure to a drug of abuse causes stable changes in the reward circuitry of the brain, which will further lead to behavioral abnormalities such as dependence, sensitization and craving. Understanding the molecular biology of drug addiction will provide improved therapies to treat drug addiction and prevent the epidemic of new addicts. It has been shown that gene expression changes in brain contribute to the stable regulation of the brain's reward circuitry involved in drug addiction. However, the specific genes and the transcriptional mechanisms underlying such regulation remain poorly understood. The overall goal of this application is to provide deeper insights into the molecular mechanisms of drug addiction by integrated analysis of rich biological data sets related to drug addiction. A large amount of genome-wide molecular profiling datasets have been accumulated to study drug addiction. These large scale data provide great opportunities to generate significant scientific findings, but also great challenges for data analysis. Studies from other research areas, especially cancer research, have shown that integrating the various molecular profiling datasets effectively can not only increase the power of data analysis, but also give more comprehensive knowledge of the biological process. The central hypothesis of this study is that integrated analysis of drug addiction related molecular profiling datasets will lead to a systematic understanding of the molecular mechanisms and novel findings of important genes and pathways involved in drug addiction. This study will focus on cocaine addiction because cocaine is among the most prominent illicit drugs of abuse, and considerable molecular profiling data have been accumulated in cocaine addiction. The proposed methods, however, will be general and applicable to study other drugs of addiction. In summary, this project will provide: (1) better mechanistic understanding of cocaine addiction; (2) powerful statistical/computational tools for the integrated analysis of drug addiction data; and (3) a comprehensive database for strengthening the broader knowledge infrastructure for drug addiction research. PUBLIC HEALTH RELEVANCE: Understanding the molecular biology of drug addiction will provide improved therapies to treat drug addiction and prevent the epidemic of new addicts. This project will provide better mechanistic understanding of cocaine addiction, and a comprehensive database for strengthening the broader knowledge infrastructure for drug addiction research.