Pharmacogenetics of Antipsychotic Drug Response

抗精神病药物反应的药物遗传学

• 批准号: 8450715
• 负责人: Jianping Zhang
• 金额: $ 18.1万
• 依托单位: FEINSTEIN INSTITUTE FOR MEDICAL RESEARCH
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-01 至 2017-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8450715
• 关键词: Address; Adverse drug effect; Adverse effects; Adverse event; Akathisia; Antipsychotic Agents; Attention; Award; Biological Assay; Blood; CYP2D6 gene; Candidate Disease Gene; Chronic; Clinical; Clinical Trials; DNA; Data; Data Set; Databases; Disease remission; Dose; Double-Blind Method; Drug Exposure; Drug Receptors; Drug effect disorder; Ensure; Exposure to; Funding; Future; Genetic Markers; Genetic Models; Genetic screening method; Genotype; Goals; Heterogeneity; Individual; Individual Differences; Intervention Studies; Left; Measurement; Mentorship; Metabolic syndrome; Methods; Molecular; Molecular Genetics; Molecular Target; National Institute of Mental Health; Outcome; Patients; Pharmaceutical Preparations; Pharmacogenetics; Pharmacogenomics; Phenotype; Pilot Projects; Positioning Attribute; Predisposition; Psychotropic Drugs; Randomized; Randomized Clinical Trials; Recruitment Activity; Refractory; Relative (related person); Research; Research Design; Research Personnel; Research Project Grants; Research Training; Risperidone; Saliva; Sample Size; Sampling; Schedule; Schizophrenia; Sedation procedure; Sensitivity and Specificity; Strategic Planning; Structure; Symptoms; Testing; Titrations; Training; Weight Gain; base; clinical decision-making; clinical practice; cohort; cost; design; drug clearance; drug discovery; drug efficacy; drug-induced weight gain; experience; first episode schizophrenia; genetic variant; genome wide association study; high risk; improved; innovation; medication compliance; outcome forecast; pharmacogenetic testing; predictive modeling; programs; prospective; randomized trial; receptor binding; response; tool; treatment as usual; treatment trial

DESCRIPTION (provided by applicant): Although antipsychotic drugs (APDs) are effective in improving symptoms for many patients with schizophrenia, they can also induce serious side effects and a large proportion of patients remain symptomatic despite treatment. Predictors of drug response are lacking and there is little empirical data available to guide clinicians in prognosis and clinical decision-making. Pharmacogenetics holds the promise of providing a useful tool to provide personalized treatment with optimal efficacy while minimizing side effects. However, pharmacogenetic studies to date have not yet provided clinically usable data, leaving this promise unfulfilled. In this K23 application, I proposed a structured training plan with the goals of gaining advanced training in clinical trial study design, pharmacogenomic analysis, and mechanisms of APD-induced weight gain, under the guidance of my experienced mentorship team. The objective is to become an independent investigator who can test practical pharmacogenetic hypotheses in randomized clinical trials. To accompany the training plan, I will conduct two separate but related pharmacogenetic research projects. Project 1 is a randomized, double-blind clinical trial, in which the clinical utility of pharmacogenetic testing in guiding AP treatment will be examined. Specifically, patients with schizophrenia will be recruited and genotyped for CYP2D6 prospectively. Patients who are poor or intermediate CYP2D6 metabolizers will be randomized to treatment with risperidone in either a treatment-as-usual condition (TAU) or a low-dose-titration condition (LDT). The primary hypothesis is that these patients, who may be at heightened vulnerability to side effects due to poor drug clearance, will have fewer side effects when assigned to the LDT condition compared to those in TAU group. This study will provide one of the first prospective data regarding the clinical value of pharmacogenetic testing in schizophrenia treatment. In Project 2, I propose to analyze a large pharmacogenetic database from several first-episode or drug-na¿ve cohorts to build a genetic model predicting APD response, particularly APD-induced weight gain, with high sensitivity and specificity. This large dataset consists of more than 1200 patients with minimal prior drug exposure and ensured medication adherence, overcoming many limitations in prior pharmacogenetic studies. Taken together, this application aims to utilize these data to better inform treatment decisions for schizophrenia patients, and also potentially provide molecular targets for new drug discovery. At the end of the combined training and research plan outlined in this application, I will be well positioned to design a randomized trial to test pharmacogenetic strategies aimed at minimizing APD-induced weight gain, for submission as an independent R01 application.

描述（由申请人提供）：尽管抗精神病药物（APD）可有效改善许多精神分裂症患者的症状，但它们也可引起严重的副作用，尽管接受了治疗，但大部分患者仍有症状。缺乏药物反应的预测因子，并且几乎没有经验数据可用于指导临床医生进行预后和临床决策。药物遗传学有望提供一种有用的工具，以提供个性化治疗，同时最大限度地减少副作用。然而，迄今为止的药物遗传学研究尚未提供临床可用的数据，使这一承诺无法实现。在K23申请中，我提出了一个结构化的培训计划，目标是在我经验丰富的导师团队的指导下，获得临床试验研究设计、药物基因组学分析和APD诱导体重增加机制方面的高级培训。目标是成为一名独立的研究者，能够在随机临床试验中检验实用的药物遗传学假设。为了配合培训计划，我将进行两个独立但相关的药物遗传学研究项目。项目1是一项随机、双盲临床试验，将检查药物遗传学检测在指导AP治疗中的临床效用。具体而言，将招募精神分裂症患者，并前瞻性进行CYP2D6基因分型。CYP2D6弱代谢或中等代谢的患者将在常规治疗条件（TAU）或低剂量滴定条件（LDT）下随机接受利培酮治疗。主要假设是，这些患者可能由于药物清除率差而更容易发生副作用，与TAU组相比，分配至LDT条件时的副作用更少。这项研究将提供第一个前瞻性的数据之一，关于精神分裂症治疗的药物遗传学测试的临床价值。在项目2中，我建议分析来自几个首次发作或药物初治队列的大型药物遗传学数据库，以建立一个预测APD反应的遗传模型，特别是APD诱导的体重增加，具有高灵敏度和特异性。这个大型数据集包括1200多名既往药物暴露最少并确保药物依从性的患者，克服了既往药物遗传学研究的许多局限性。总之，该应用旨在利用这些数据更好地为精神分裂症患者的治疗决策提供信息，并可能为新药发现提供分子靶点。在本申请中概述的联合培训和研究计划结束时，我将很好地设计一项随机试验，以测试药物遗传学 旨在最大限度地减少APD诱导的体重增加的策略，作为独立的R01申请提交。