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精神疾病，通常使用选择性血清素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，本应用程序旨在确定抗抑郁药反应的遗传决定因素，在前所未有的临床样本中，用单一抗抑郁药治疗，其治疗反应已被仔细确定。最终目标是阐明抗抑郁药物反应的遗传决定因素，这是理解抗抑郁药物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，涉及西酞普兰反应的重要表型部分是由可检测的遗传因素介导的。我们建议对STAR*D （Sequenced Treatment Alternatives to relief Depression）方案中获得的DNA（约1400个）进行大规模遗传关联研究，STAR*D是一项涉及约4000名DSM-IV重度抑郁症患者的大型多点治疗研究。我们建议：1)基于先前的生物学或遗传学证据，对该样本进行基因分型，以确定20个抗抑郁反应候选基因的反应表型与变异之间的关联；2)对反应表型与约100,000个基于基因的DNA变异进行全基因组关联研究。次要的具体目标是：1)测序与反应表型呈正相关的基因，使用候选基因或全基因组方法识别潜在的反应相关等位基因，以及2)开发完善的表型和新的假设，以测试与治疗反应结果的关联。功率计算表明表型组之间可以检测到有意义的差异。检测DNA变异与抗抑郁药物反应之间的任何关联，如果确定了一种基因型，该基因型在这些药物的反应或耐受性中占很大一部分差异，则可能最终具有重大的临床影响。这些发现可以为我们确定药物治疗的临床有用的遗传预测因子并将其应用于患者群体的能力提供步骤。

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.