Pharmacogenomics of serotonin-specific reuptake inhibitors

描述（由申请人提供）：神经精神疾病，如抑郁症，尚未显示出结论性的联系或关联研究结果。今天，抑郁症的遗传性的很大一部分仍然无法解释。而不是重复的研究，试图确定遗传变异的基础抑郁症的病理生理学，我提出了一种不同的方法来评估遗传变异的安全性和有效性的主要类别的抗抑郁药。我 将确定患者的定量和离散表型的降钙素特异性再摄取 抑制剂（SSRI）反应（通过SSRI治疗前后的患者健康问卷-9测量）和SSRI相关的严重副作用，如异常出血和5-羟色胺综合征。在从电子病历和遗传流行病学（eMERGE）联盟中鉴定出这些表型后，我将对50，109名受试者进行全基因组关联研究（GWAS），以鉴定参与SSRI药理学的候选基因，然后利用重叠的外显子组序列数据来鉴定罕见的潜在致病突变。由于许多GWAS和罕见变异研究缺乏功能验证（即，鉴定的变异确实导致表型），我将使用基于酵母生长的测定作为蛋白质功能的直接测量，在模式生物酿酒酵母中功能性地验证这些鉴定的罕见突变。参与SSRI代谢的P450酶CYP 3A 4将用作酵母试验的概念验证。最后，我将使用这种酵母生长试验进行深度突变扫描，以创建所有可能突变及其对酶水解作用的药物基因组学图谱，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SSRI反应的药物基因组学表型以及SSRI相关出血和5-羟色胺综合征风险的GWAS，我可能会识别出许多候选基因，这些基因可能会进一步告知SSRI的代谢，运输和作用机制，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谱，我将为临床医生解释患者罕见突变的可能影响创造宝贵的资源。通过这个项目，我希望进一步努力将个性化的基因组医学引入临床实践，以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个会受到抑郁症的影响。

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.