Pharmacogenomics of Antidepressant Response

描述（由申请人提供）：重度抑郁症是一种常见的致残性精神疾病，通常用选择性5-羟色胺再摄取抑制剂抗抑郁药治疗。迄今为止的研究表明，抗抑郁反应与神经递质调节途径和抗抑郁代谢途径中的基因之间存在关联。基于这些观察结果，本申请旨在确定前所未有的临床样本中抗抑郁药反应的遗传决定因素，该样本接受单一抗抑郁药治疗，其治疗反应已被仔细确定。最终目标是阐明抗抑郁药反应的遗传决定因素，作为理解抗抑郁作用机制和开发新型抑郁症治疗药物的重要前提。我们的具体假设是，涉及对西酞普兰的反应的重要表型部分由可检测的遗传因素介导。我们建议对星星 *D（缓解抑郁症的序贯治疗替代方案）方案中获得的DNA（约1，400个）进行大规模遗传关联研究，这是一项涉及约4，000名DSM-IV重度抑郁症患者的大型多中心治疗研究。我们建议：1）基于先前的生物学或遗传学证据，针对反应表型与20种抗抑郁剂反应候选基因中的变体之间的关联对该样品进行基因分型，以及2）进行反应表型与约100，000种基于基因的DNA变体之间的全基因组关联研究。第二个具体目标是：1）测序与使用候选基因或全基因组方法鉴定的应答表型正相关的基因，以鉴定潜在的应答相关等位基因，以及2）开发精细的表型和新的假设，以测试与治疗应答结果的关联。功效计算表明，可以检测到表型分组之间的有意义的差异。检测DNA变异和抗抑郁药反应之间的任何关联，如果确定了占这些药物反应或耐受性差异很大一部分的基因型，最终可能会产生显著的临床影响。这些发现可以为我们确定临床上有用的药物治疗遗传预测因子并将其应用于患者人群的能力提供步骤。

DESCRIPTION (provided by applicant): Major Depressive Disorder is a common and disabling psychiatric illness, usually treated with a selective serotonin reuptake inhibitor antidepressant. Studies to date suggest that there are associations between antidepressant response and genes in both neurotransmitter regulatory pathways and antidepressant metabolism pathways. Based on these observations, this application is designed to identify genetic determinants for antidepressant response in a clinical sample of unprecedented size, treated with a single antidepressant, whose treatment response has been carefully ascertained. The ultimate goal is to elucidate genetic determinants of response to antidepressants as an important prerequisite to understanding the mechanism of antidepressant action and development of novel therapeutic agents for depression. Our specific hypothesis is that important phenotypes involving response to citalopram are in part mediated by detectable genetic factors. We propose a large-scale genetic association study on a collection of DNA's (about 1,400) obtained during the STAR*D (Sequenced Treatment Alternatives to Relieve Depression) protocol, a large multi-site treatment study involving about 4,000 persons with DSM-IV Major Depressive Disorder. We propose to: 1) genotype this sample for association between response phenotypes and variants in 20 antidepressant response candidate genes based on prior biological or genetic evidence, and 2) perform a whole genome association study between response phenotypes and about 100,000 gene-based DNA variants. Secondary specific aims are to: 1) sequence genes positively associated with response phenotypes identified using candidate gene or whole genome approaches to identify potential response-related alleles, and 2) develop refined phenotypes and novel hypotheses to test for association to treatment response outcomes. Power calculations suggest meaningful differences between phenotypic groupings can be detected. Detecting any association between DNA variations and antidepressant response could ultimately have a significant clinical impact if a genotype that accounts for a substantial portion of variance in response or tolerability of these medications is identified. These findings could provide steps toward our ability to define clinically useful genetic predictors of pharmacological treatment and apply them to patient populations.