Selecting Best Neuroleptic Treatment for Veterans with Schizophrenia

描述(由申请人提供)： 拟议的研究的主要目标是开始将基础和临床研究转化为创新的临床评估和治疗。脑功能成像以及动物2-脱氧葡萄糖研究表明，抗精神病药物对纹状体活动有很强的影响。该项目是我们和其他人的一系列研究的后续研究，这些研究发现纹状体的相对代谢率较低，通过18-F-2-脱氧葡萄糖正电子发射断层扫描(FDG-PET)来预测抗精神病药物的反应。我们将在基线(第0天)和为期4周的利培酮治疗试验结束时，对大量未用药的精神分裂症患者(n=；另外还有16名患者，允许20%的自然减损)进行功能磁共振成像和感觉运动门控(Stritle的被动和主动注意预脉冲抑制(PPI))。利用功能磁共振成像，该项目将扩展早期的FDG-PET研究，该研究表明，低背侧尾状核活性预测抗精神病药物的反应。我们还将获得健康对照组(n=32；磨损加3)的fMRI和PPI测量作为基准，以比较利培酮治疗有效亚组与治疗无反应亚组尾状核和PPI活性是否更正常化。我们的试验数据表明，PPI指标是尾状核功能的潜在替代指标，并最终可能成为有用的中间治疗预测指标。我们也有新的试点数据表明，用fMRI测量的尾状核活动较低和较差的PPI显示出预测精神分裂症患者对为期4周的利培酮试验的更好反应的趋势。我们预计该项目将耗时四年：3个月的启动时间，39个月的患者和健康对照对照组获取时间，6个月的数据分析和撰写科学手稿的时间。该项目将在詹姆斯·J·彼得斯退伍军人医疗中心进行，涉及从三个地点招募的患者：詹姆斯·J·彼得斯和纽约港退伍军人医疗中心，以及西奈山医院(J.J.彼得斯VAMC附属公司)。约三分之二的患者样本将在J.J.彼得斯VAMC进行招募、诊断和治疗。三分之一的患者样本将从纽约港VAMC招募，来自西奈山的患者将仅出于自然减员目的招募。健康对照组将从詹姆斯·J·彼得斯VAMC招募。功能磁共振成像和心理生理学测试将在西奈山为所有研究参与者举行，那里有最先进的头部专用3T磁共振扫描仪和认知心理生理学实验室。这项拟议研究的主要目标是开始识别预测精神分裂症患者抗精神病治疗反应的潜在生物标志物。目前，还没有生物标记物来帮助精神病学家确定哪种抗精神病药物对特定患者会产生最佳反应。相反，为特定患者选择抗精神病药物涉及一个复杂的反复试验过程。证明尾状核和感觉运动门控措施作为预测精神分裂症患者治疗反应的生物标志物的有效性，可能会将生态有效的工具从工作台带到床边。

DESCRIPTION (provided by applicant): The proposed research has the primary goal of beginning to translate basic and clinical research into innovative clinical assessment and therapeutics. Functional brain imaging, as well as, animal 2-deoxyglucose studies have demonstrated that antipsychotic drugs have robust effects on striatal activity. This project is a follow-up to a series of studies of ours and others that have found low relative metabolic rates in the striatum as assessed by 18-F-2-deoxyglucose positron emission tomography (FDG-PET) to predict antipsychotic response. We will acquire fMRI and sensorimotor gating (passive- and active-attention prepulse inhibition (PPI) of startle) in a large sample of unmedicated schizophrenia patients (n=64; plus an additional 16 patients to allow for 20% attrition) at baseline (Day 0) and at the end of a 4-week risperidone treatment trial. Using fMRI, this project will extend earlier FDG-PET studies which showed low dorsal caudate activity predicts antipsychotic response. We will also obtain fMRI and PPI measures in a healthy-control group (n=32; plus 3 for attrition) as a benchmark for comparing whether caudate and PPI activity is more normalized with risperidone treatment in the responder subgroup compared with the treatment non-responder subgroup. Our pilot data suggest that PPI measures are a potential proxy for caudate function and may eventually serve as useful intermediary treatment predictors. We also have new pilot data indicating that low caudate activity measured with fMRI and poor PPI show a trend for predicting better response to a 4-week risperidone trial in schizophrenia patients. We anticipate that this project will take four years: three months for startup, 39 months for patient and healthy control comparison group acquisition, and 6 months for data analysis and writing scientific manuscripts. The project will be conducted at the James J. Peters VA Medical Center and involve patients recruited from three sites: the James J. Peters and New York Harbor VA Medical Centers, and Mount Sinai Hospital (J.J. Peters VAMC affiliate). Approximately two-thirds of the patient sample will be recruited, diagnosed and treated at the J.J. Peters VAMC. One-third of the patient sample will be recruited from the NY Harbor VAMC and patients from Mount Sinai will be recruited for attrition purposes only. Healthy controls will be recruited from the James J. Peters VAMC. The fMRI and psychophysiological testing sessions will take place at Mount Sinai for all study participants where a state-of-the-art head-dedicated 3T MRI scanner and the Cognitive Psychophysiology Laboratory are located. The primary objective of the proposed research is to begin to identify potential biomarkers for predicting antipsychotic treatment response in patients with schizophrenia. Currently, there is no biological marker to assist psychiatrists in determining which antipsychotic medication will give the optimal response in a given patient. Instead, the selection of an antipsychotic medication for a particular patient involves a complex trial- and-error process. Demonstration of the usefulness of caudate and sensorimotor gating measures as biomarkers for predicting treatment response in schizophrenia patients could bring ecologically-valid tools from bench to bedside.