The In Silico Genetic Analysis of Opioid Adaptations

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，一组适应不良被认为限制了这些药物的长期有效性，包括镇痛耐受、阿片类药物引起的痛觉过敏和身体依赖现象。此外，阿片类药物滥用率急剧上升，与此同时，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，这限制了我们预测、预防和治疗这些问题的能力。在人类和啮齿动物实验室模型中，遗传因素已被证明会影响滥用阿片类药物的可能性以及产生适应不良。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，到目前为止，在确定导致这些影响的特定遗传变异方面取得的进展

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.