Pharmacogenomics of serotonin-specific reuptake inhibitors

描述(由申请人提供)：神经精神障碍，如抑郁症，尚未显示出确凿的关联或关联研究结果。如今，抑郁症的很大一部分遗传性仍未得到解释。与其重复试图确定抑郁症病理生理学基础上的遗传变异的研究，我提出了一种不同的方法来评估主要类别抗抑郁药物的安全性和有效性的遗传变异。我 将确定具有5-羟色胺特异性重摄取的数量和离散表型的患者 抑制物(SSRI)的反应(通过SSRI治疗前后的患者健康问卷-9测量)，以及与SSRI相关的严重副作用，如异常出血和5-羟色胺综合征。在从电子医疗记录和遗传流行病学(Emerge)联盟中识别出这些表型后，我将对50,109名受试者进行全基因组关联研究(Gwas)，以识别与SSRI药理学有关的候选基因，然后利用重叠的外显子序列数据来识别罕见的、潜在的致病突变。由于许多GWAS和稀有变体研究缺乏功能验证(即，所识别的变体确实导致了表型)，我将使用基于酵母生长的试验作为蛋白质功能的直接测量，在模式生物酿酒酵母中对这些已识别的罕见突变进行功能性验证。与SSRI新陈代谢有关的P450酶CYP3A4将被用作酵母检测的概念证明。最后，我将使用这种酵母生长试验进行深度突变扫描，以创建所有可能的突变及其对酶水解的影响的药物基因组图，从而将DNA序列与蛋白质功能联系起来。这项工作将为理解SSRI药理学提供独特的资源。通过完成对SSRI反应的药物基因组表型以及SSRI相关出血和5-羟色胺综合征风险的GWAS研究，我可能会确定许多候选基因，这些基因可能进一步了解SSRI的代谢、转运和作用机制，从而促进基础科学。此外，通过功能验证和创建具有深度突变扫描的药物基因组图，我将为临床医生创建一个宝贵的资源，以解释他们患者罕见突变的可能影响。通过这个项目，我希望进一步努力将个性化的基因组医学应用于临床，降低抑郁症的发病率和死亡率。据疾病控制中心估计，美国每10个成年人中就有1人患有抑郁症。

DESCRIPTION (provided by applicant): Neuropsychiatric disorders, such as depression, have not shown conclusive linkage or association study results. Today, an enormous portion of heritability for depression remains unexplained. Rather than reiterating studies attempting to identify genetic variants underlying depression pathophysiology, I propose a different approach of evaluating genetic variation in the safety and efficacy of the major class of antidepressants. I will identify patients with the quantitative and discrete phenotypes of serotonin-specific reuptake inhibitor (SSRI) response (as measured through the Patient's Health Questionnaire-9 pre- and post-SSRI treatment), and SSRI-associated serious side effects, such as abnormal bleeding and serotonin syndrome. After identification of these phenotypes from the electronic Medical Records and Genetic Epidemiology (eMERGE) consortium, I will perform a genome-wide association study (GWAS) on 50,109 subjects to identify candidate genes involved in SSRI pharmacology and then leverage overlapping exome sequence data to identify rare, potentially causative mutations. As many GWAS and rare variant studies suffer from a lack of functional validation (i.e., that the identified variant truly causes the phenotype), I will functionally valiate these identified rare mutations in the model organism Saccharomyces cerevisiae using a yeast growth-based assay as a direct measure of protein function. The P450 enzyme CYP3A4, which has been implicated in SSRI metabolism, will be used as a proof of concept for the yeast assay. Finally, I will then use this yeast growth assay to perform deep mutational scanning to create a pharmacogenomic map of all possible mutations and their effect on enzyme hydrolysis, thereby linking DNA sequence to protein function. This work will provide a unique resource for understanding SSRI pharmacology. Through completion of a GWAS on the pharmacogenomic phenotypes of SSRI response and separately, risk of SSRI-associated bleeding and serotonin syndrome, I will likely identify numerous candidate genes that may further inform on the metabolism, transport, and mechanism of action of SSRIs, thereby furthering basic science. Moreover, through functional validation and creation of a pharmacogenomic map with deep mutational scanning, I will create an invaluable resource for clinicians to interpret the likely efect of their patient's rare mutation. Through this project, I hope to further the effort to bring personalized, genomic medicine into clinical practice, to decrease the morbidity and mortality of depression, which is estimated by the Center for Disease Control to affect 1 in 10 adults in the U.S.