The In Silico Genetic Analysis of Opioid Adaptations

描述(申请人提供)：阿片类药物已成为治疗所有类型的中到重度急性和慢性疼痛的基石。不幸的是，一组适应不良被认为限制了这些药物的长期有效性，包括止痛耐受、阿片类药物引起的痛敏和身体依赖等现象。此外，阿片类药物滥用的比率急剧上升，同时他们治疗疼痛的处方也在增加。我们在揭示阿片类药物适应不良和滥用的机制方面进展缓慢，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发展适应不良的可能性。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，到目前为止，在识别导致这些影响的特定遗传变异方面取得了进展 是有限的。基于全基因组单倍型的计算遗传作图(HBCGM)为新的基因发现提供了一种强有力的方法。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)将我们的小鼠全基因组序列数据库扩大到30个广泛可用的近交系，从而提供进行全基因组测绘的能力；2)扩展我们的小鼠阿片反应表型数据库，以包括一系列临床相关阿片类药物适应不良的菌株特定信息；3)开发分析工具，帮助研究人员利用全基因组HBCGM实验中产生的复杂数据集；以及4)利用我们新的序列、表型和分析工具，从根本上提高我们对影响慢性阿片类药物治疗反应的遗传因素的理解。我们的团队是唯一有资格承担这一密切关注但从根本上重要的项目。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。还安排了与一位专家就互补的整合基因组学方法进行合作，涉及QTL结果、表达数据和其他策略，进一步增强了项目的力量。

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.