The In Silico Genetic Analysis of Opioid Adaptations

阿片类药物适应的计算机遗传学分析

• 批准号: 8675823
• 负责人: DAVID J. CLARK
• 金额: $ 18.36万
• 依托单位: PALO ALTO VETERANS INSTIT FOR RESEARCH
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2016-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8675823
• 关键词: Acute Pain; Analgesics; Area; Candidate Disease Gene; Centers for Disease Control and Prevention (U.S.); Chromosome Mapping; Chronic; Collaborations; Complex; Computer Simulation; Computer software; Data; Data Set; Databases; Development; Drug usage; Effectiveness; Epidemic; Future; Gene Expression; Genes; Genetic; Genome; Genome Mappings; Genomics; Goals; Growth; Haplotypes; Human; Hybrids; Hyperalgesia; Inbred Strain; Inbred Strains Mice; Informatics; Investigation; Laboratories; Maps; Methods; Modeling; Mus; Opioid; Output; Pain; Pain Research; Pain management; Pharmaceutical Preparations; Pharmacology; Phenotype; Physical Dependence; Physiological; Prevention strategy; Public Health; Publishing; Qualifying; Quantitative Trait Loci; Research; Research Personnel; Resources; Rodent; System; Techniques; Time; Tissues; Ursidae Family; Work; addiction; analytical tool; base; behavior test; chronic pain; clinically relevant; computer science; design; experience; flexibility; genetic analysis; genetic variant; genome sequencing; improved; insight; next generation; novel; opioid abuse; prevent; public health relevance; research study; response; statistics; success; tool; trait; treatment strategy

DESCRIPTION (provided by applicant): Opioids have become the cornerstone for treatment of moderate to severe acute and chronic pain of all types. Unfortunately, a group of maladaptations has been recognized as limiting the long-term effectiveness of these drugs including the phenomena of analgesic tolerance, opioid-induced hyperalgesia and physical dependence. Moreover, there has been a very sharp rise in the rate of opioid abuse paralleling the rise in their prescription for the treatment of pain. Our slow progress in uncovering the mechanisms responsible for opioid maladaptations and abuse has limited our ability to predict, prevent, and treat these problems. Genetic factors have been shown to influence the likelihood of abusing opioids as well as developing maladaptations both in humans and in rodent laboratory models. Understanding the basis for these effects would improve our understanding of the involved mechanisms and might suggest novel prevention or treatment strategies. To this point, however, progress in identifying specific genetic variants responsible for these effects has been limited. Whole genome haplotype based computational genetic mapping (HBCGM) offers a powerful approach to making novel genetic discoveries. In the proposed work we will overcome several key limitations to the use of HBCGM for exploring opioid abuse and in so doing will provide tools applicable to the analysis of a broad range of quantitative traits. Our fundamental goals are 1) to expand our murine whole genome sequence database to 30 widely available inbred strains thus providing the power to perform whole genome mapping, 2) expand our murine opioid response phenotype database to include strain- specific information for a range of clinically relevant opioid maladaptations, 3) to develop analytical tools helping investigators take advantage of the complex datasets generated in whole genome HBCGM experiments, and 4) to use our new sequence, phenotype and analytical tools to advance fundamentally our understanding of the genetic factors influencing responses to chronic opioid administration. Our group is uniquely qualified to undertake this tightly focused yet fundamentally important project. The research team includes investigators with expertise and experience in opioid pharmacology, genetics and computer science. Additional collaboration has been arranged with an expert on complementary integrative genomics approaches involving QTL results, expression data, and other strategies further enhancing the power of the project.

描述（由申请人提供）：阿片类药物已成为治疗所有类型的中度至重度急性和慢性疼痛的基石。不幸的是，一组适应不良已被公认为限制这些药物的长期有效性，包括镇痛耐受，阿片类药物诱导的痛觉过敏和身体依赖的现象。此外，阿片类药物滥用率急剧上升，与其治疗疼痛的处方增加相平行。我们在揭示阿片类药物适应不良和滥用机制方面的缓慢进展限制了我们预测，预防和治疗这些问题的能力。遗传因素已被证明会影响滥用阿片类药物的可能性，以及在人类和啮齿动物实验室模型中出现适应不良。了解这些影响的基础将提高我们对相关机制的理解，并可能提出新的预防或治疗策略。然而，在这一点上，在确定负责这些影响的特定遗传变异方面取得了进展， 被限制。基于全基因组单倍型的计算遗传作图（HBCGM）提供了一种强有力的方法，使新的遗传发现。在拟议的工作中，我们将克服使用HBCGM探索阿片类药物滥用的几个关键限制，这样做将提供适用于分析广泛数量性状的工具。我们的基本目标是1）将我们的鼠全基因组序列数据库扩展到30个广泛可用的近交系，从而提供进行全基因组作图的能力，2）扩展我们的鼠阿片样物质应答表型数据库以包括一系列临床相关阿片样物质适应不良的品系特异性信息，3）开发分析工具，帮助研究人员利用全基因组HBCGM实验中生成的复杂数据集，以及4）使用我们的新序列，表型和分析工具，从根本上推进我们对影响慢性阿片类药物给药反应的遗传因素的理解。我们的团队是唯一有资格承担这个重点突出但具有根本重要性的项目。研究团队包括在阿片类药物药理学，遗传学和计算机科学方面具有专业知识和经验的研究人员。与一位专家就互补的综合基因组学方法进行了额外的合作，包括QTL结果、表达数据和其他策略，进一步增强了该项目的力量。

项目成果

The Netrin-1 receptor DCC is a regulator of maladaptive responses to chronic morphine administration.

• DOI: 10.1186/1471-2164-15-345
• 发表时间: 2014-05-08
• 期刊: BMC genomics
• 影响因子: 4.4
• 作者: Liang DY;Zheng M;Sun Y;Sahbaie P;Low SA;Peltz G;Scherrer G;Flores C;Clark JD
• 通讯作者: Clark JD