Pharmacogenetics of the Antidepressant Response in Geriatric Major Depression

描述（由申请人提供）：一些患者对抗抑郁药反应良好，而另一些则不然。不同患者抗抑郁反应差异的生物学基础尚不清楚。药物遗传学寻求能够预测药物治疗结果的DNA标记。我们有一项前瞻性、双盲、随机药物遗传学研究的DNA和临床数据，研究对象是246名65岁及以上认知完整的重度抑郁症患者，他们接受米氮平或帕罗西汀治疗24周。由于帕罗西汀和米氮平的对比作用，以及老年患者极易受到药物不良事件的影响，该数据集对药物遗传学特别有价值。迄今为止的分析已经揭示了编码血清素能和肾上腺素能受体和再摄取转运体的基因的显著预测因子。我们现在建议使用这种独特的DNA和临床资源来确定抗抑郁药疗效和副作用的其他新的遗传标记。我们将重点讨论两个相互作用的系统，神经营养因子和HPA轴。神经营养因子及其受体和相关的信号转导效应器在抗抑郁药的治疗效果中起重要作用。我们将针对BDNF系统，这是由抗抑郁药强烈调节。下丘脑轴失调可能是抑郁症发病的关键，调节下丘脑轴功能具有治疗价值。参与皮质类固醇调节和作用的基因将被检查，这些基因可能会加剧抑郁症并被米氮平下调。编码和调控区域的重测序将在24个受试者的发现样本中选择基因进行。通过重测序确定的snp将被选择用于基于生物信息学评估其潜在功能意义的进一步研究，并对所有246个样本进行基因分型。推断的单倍型和未分期的双倍型将被用作预测因子，并对多次测试进行适当的控制。此外，基于Perlegen数据库中验证的snp的连锁不平衡数据，将采用间接候选基因方法。主要结局指标将是情绪变化（HDRS-17， CDS）、不良事件严重程度、治疗中断频率和认知变化。关键协变量，如依从性、剂量和血浆药物水平将包括在分析中。基因组控制也将进行测试。这项工作将提供一个有针对性的药物遗传学分析，在老年患者的两个相互关联的生物系统出现在抗抑郁治疗的重要。重度抑郁症是老年人普遍存在的精神疾病。许多病人对抗抑郁药物治疗有抗药性。一种识别可能从抗抑郁治疗中受益的患者的方法将减少患者的痛苦并节省医疗保健费用。

DESCRIPTION (provided by applicant): Some patients respond well to antidepressants, whereas others do not. The biological basis for differences among patients in antidepressant response is poorly understood. Pharmacogenetics seeks DNA markers that can predict medication treatment outcomes. We have DNA and clinical data from a prospective, double-blind, randomized pharmacogenetic study of 246 cognitively intact patients 65 years of age and older with major depression who were treated with either mirtazapine or paroxetine for 24 weeks. This dataset is particularly valuable for pharmacogenetics because of the contrasting actions of paroxetine and mirtazapine, and because older patients are highly vulnerable to medication adverse events. Analysis thus far has revealed significant predictors in genes encoding serotonergic and adrenergic receptors and reuptake transporters. We now propose to use this unique DNA and clinical resource to identify additional novel genetic markers for antidepressant efficacy and side effects. We will focus on two interacting systems, neurotrophins and the HPA axis. Neurotrophins, their receptors, and related signal transduction effectors are important in the therapeutic effects of antidepressants. We will target the BDNF system, which is strongly modulated by antidepressants. HPA axis dysregulation is likely to be key in the etiology of depression, and normalizing HPA axis function has therapeutic value. Genes involved in the regulation and actions of corticosteroids, which may exacerbate depression and are downregulated by mirtazapine, will be examined. Resequencing of coding and regulatory regions will be performed for selected genes in a discovery sample of 24 subjects. SNPs identified by resequencing will be chosen for further study based bioinformatic assessment of their potential functional significance, and genotyping will be performed in all 246 samples. Inferred haplotypes as well as unphased diplotypes will be used as predictors, with appropriate controls for multiple testing. In addition, an indirect candidate gene approach will be utilized based on linkage disequilibrium data from validated SNPs in the Perlegen database. The primary outcome measures will be change in mood (HDRS-17, CDS), the severity of adverse events, the frequency of treatment discontinuations, and cognitive changes. Key covariates such as compliance, dosing, and plasma drug levels will be included in the analyses. Genomic controls will also be tested. This work will provide a targeted pharmacogenetic analysis in geriatric patients of two interrelated biological systems emerging as important in antidepressant therapeutics. Major depression is a prevalent psychiatric disorder among the elderly. Many patients are resistant to antidepressant medication treatment. A method for identifying patients likely to benefit from antidepressant treatment would decrease patient distress and save health care dollars.