Pharmacogenetics of the Antidepressant Response in Geriatric Major Depression

老年重度抑郁症抗抑郁反应的药物遗传学

基本信息

批准号：
7670264
负责人：
GREER M MURPHY
金额：
$ 34.08万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2006
资助国家：
美国
起止时间：
2006-08-01 至 2011-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7670264
关键词：
11-beta-Hydroxysteroid Dehydrogenases Adrenal Cortex Hormones Adrenergic Agents Adrenergic Receptor Adverse effects Adverse event Affect Age-Years Aging Antidepressive Agents Binding Proteins Bioinformatics Biological Brain Brain-Derived Neurotrophic Factor CREB1 gene CREBBP gene Candidate Disease Gene Clinical Clinical Data Code Cognition Corticotropin-Releasing Hormone Corticotropin-Releasing Hormone Receptors DNA DNA Markers DNA Resequencing Data Data Set Databases Distress Dose Double-Blind Method Elderly Etiology Frequencies Genes Genetic Markers Genetic Polymorphism Genetic Variation Genomics Genotype Glucocorticoid Receptor Goals Haplotypes Healthcare Linkage Disequilibrium Major Depressive Disorder Membrane Transport Proteins Mental disorders Methods Mineralocorticoid Receptor Mirtazapine Moods NR3C1 gene NR3C2 gene NTRK2 gene Neurobiology Neurotrophic Tyrosine Kinase Receptor Type 2 Norepinephrine Nucleic Acid Regulatory Sequences Outcome Outcome Measure Paroxetine Patients Pharmaceutical Preparations Pharmacogenetics Plasma Proteins Psychiatry Publishing Randomized Regulation Research Personnel Resistance Resources Sampling Selective Serotonin Reuptake Inhibitor Serotonin Serotonin Agents Severities Signal Transduction Signaling Molecule Single Nucleotide Polymorphism Site System Testing Therapeutic Therapeutic Effect Treatment outcome V1b vasopressin receptor Variant Weight Work adrenergic base biological systems cognitive change depression dosage geriatric major depression insight neurotransmission neurotrophic factor noradrenergic novel older patient primary outcome programs prospective receptor response reuptake

项目摘要

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.

描述（由申请人提供）：一些患者对抗抑郁药的反应良好，而另一些患者则没有。抗抑郁反应中患者之间差异的生物学基础知之甚少。药物遗传学寻求可以预测药物治疗结果的DNA标记。我们有来自前瞻性，双盲，随机的药物遗传学研究的DNA和临床数据，该研究对246名认知完整的患者65岁及以上患有严重抑郁症，他们接受了米氮平或帕罗西汀治疗24周。该数据集对于药物遗传学特别有价值，因为帕罗西汀和米氮平的对比作用，并且由于老年患者极易受到药物不良事件的影响。到目前为止，分析揭示了编码血清素能和肾上腺素能受体以及再摄取转运蛋白的基因中的重要预测因子。现在，我们建议使用这种独特的DNA和临床资源来确定抗抑郁药和副作用的其他新型遗传标记。我们将专注于两个相互作用的系统，即神经营养蛋白和HPA轴。神经营养蛋白，其受体和相关信号转导效应子在抗抑郁药的治疗作用中很重要。我们将针对BDNF系统，该系统由抗抑郁药强烈调节。 HPA轴功能障碍可能是抑郁症病因的关键，并且正常化的HPA轴功能具有治疗价值。将检查参与皮质类固醇调节和作用的基因，可能会加剧抑郁症并被米氮平（Mirtazapine）下调。在24名受试者的发现样本中，将对所选基因进行编码和调节区域的重新取证。通过重新取证确定的SNP将被选择以进一步研究其潜在功能意义的基于生物信息学评估，并且将在所有246个样本中进行基因分型。推断的单倍型以及未基于的外交型将用作预测因素，并具有适当的多次测试对照。此外，将根据Perlegen数据库中验证的SNP的连锁不平衡数据来使用间接候选基因方法。主要结果指标将是情绪变化（HDRS-17，CD），不良事件的严重程度，治疗中断的频率和认知变化。分析中将包括依从性，给药和血浆药物水平等关键协变量。基因组控制也将进行测试。这项工作将为两种相互关联的生物系统的老年患者提供针对性的药物遗传学分析，这在抗抑郁药治疗中很重要。重度抑郁症是老年人中普遍的精神障碍。许多患者对抗抑郁药治疗具有抗药性。一种识别可能受益于抗抑郁治疗的患者的方法将减少患者的困扰并节省医疗保健费用。