Pharmacogenetic Optimization of Analgesic Prescribing in Sickle Cell Disease

描述（由申请人提供）：该提案描述了Cheedy Jaja博士为期三年的指导培训计划，旨在为他在镰状细胞病（SCD）药物治疗和镇痛药物遗传学方面建立坚实的基础，这对他过渡到具有SCD疼痛管理专业知识的独立转化研究科学家至关重要。设计了一个定制的学习计划，将教学课程和研究培训与SCD病理生理学，疼痛管理和药物遗传学的临床和实验室培训结合起来。SCD疼痛管理的权威Abdullah Kutlar博士将指导首席研究员的科学成长和发展，由备受尊敬的SCD研究人员和转化科学家组成的咨询委员会将提供科学和研究支持。拟议的指导培训利用了优秀的SCD研究和乔治亚医学院现有的临床资源，并包括一项前瞻性队列研究。这项研究试图通过挑战目前的“按需”阿片类药物策略来改变临床实践。虽然已知存在，但SCD患者中次优镇痛处方实践的确切发生率和患病率尚不清楚。缺乏这方面的信息是优化镇痛治疗进展的关键障碍。为了解决这一关键障碍，我们提出的研究方法是关注细胞色素P450基因的遗传多态性，这些基因已知在镇痛药物代谢中起作用，可以帮助识别治疗失败风险较高的患者。本研究旨在验证细胞色素CYP2C9、CYP2C19和CYP2D6代谢表型缺陷和次优镇痛处方与SCD患者ED就诊呈正相关的中心假设；并证明CYP450表型信息可用于估计因镇痛治疗失败而反复到ED就诊的风险。采用Tag-It突变技术测定CYP450基因型，采用药物量化量表测定次优处方发生率。中心假设如果得到证实，将建立CYP450表型缺陷和暴露于次优处方作为临床危险因素。该研究的风险预测规则将指导临床医生识别那些将从有针对性的个性化干预中受益的个体，以减少重复急诊室就诊的风险。该研究将通过证明次优处方在SCD镇痛治疗中很常见来解构当前的临床实践。具有建设性的是，该研究将建立CYP450表型的可行性，以确定可能从传统镇痛给药方案中获得成功镇痛缓解的患者或可能从镇痛转换中受益的患者。

DESCRIPTION (provided by applicant): This proposal describes a three year mentored training program for Dr. Cheedy Jaja to create a robust foundation in sickle cell disease (SCD) pharmacotherapy and analgesic pharmacogenetics essential for his transition to an independent translational research scientist with expertise in SCD pain management. A customized program of study that couples didactic coursework and research training with clinical and laboratory training in SCD pathophysiology, pain management and pharmacogenetics is designed. Dr. Abdullah Kutlar, a leading authority in SCD pain management will mentor the principal investigator's scientific growth and development, and an advisory committee of highly regarded SCD researchers and translational scientists will provide scientific and research support. The proposed mentored training draws on the excellent SCD research and clinical resources available at the Medical College of Georgia and encompasses a prospective cohort study. This study seeks to shift clinical practice by challenging the current "as-needed" opioids strategy. Although it is known to exist, the exact incidence and prevalence of suboptimal analgesic prescribing practices in SCD patients is unknown. The absence of this information is a critical barrier to progress in optimizing analgesic therapy. This proposed study approach to addressing this critical barrier is to focus on genetic polymorphisms in cytochrome P450 genes which are known to play a role in analgesic drug metabolism and could help identify patients with higher risk for therapy failure. The study is designed to test the central hypothesis that deficient cytochrome CYP2C9, CYP2C19 and CYP2D6 metabolic phenotypes and suboptimal analgesic prescribing are positively associated with ED visits in SCD patients; and to demonstrate that CYP450 phenotypes information can be used for estimating risks for repeated ED visits for analgesic therapy failure. The Tag-It Mutation Technique is used to determine CYP450 genotypes, and the Medication Quantification Scale is used to determine suboptimal prescribing incidence. The central hypothesis if confirmed, will establish deficient CYP450 phenotypes and exposure to suboptimal prescribing as clinical risk factors. The study risk prediction rules will guide clinicians in identifying individuals who would benefit from targeted, individualized intervention to reduce risks for repeated ED visits. The study will transform current clinical practice deconstructively by demonstrating that suboptimal prescribing is common in SCD analgesic therapy. Constructively, the study will establish feasibility of CYP450 phenotyping for identifying patients likely to achieve successful analgesic relief from conventional analgesic dosing regimens or patients who might benefit from analgesic switching. PUBLIC HEALTH RELEVANCE: This project addresses pain and its management with opioid analgesics in patients with sickle cell disease. By linking suboptimal prescribing of analgesics and deficiency in inherited metabolic capacity in SCD patients to frequent utilization of acute care resources, we may identify possible risk factors for poor pharmacotherapeutic outcomes in SCD patients and validate the need for genotyping to identify at-risk SCD patients for analgesic drugs failure.