SCHIZOPHRENIA DIAGNOSIS: LEUKOCYTE MULTIGENE SIGNATURES

精神分裂症诊断：白细胞多基因特征

• 批准号: 7378350
• 负责人: JAMES Donald CLELLAND
• 金额: $ 0.51万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-04-01 至 2007-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7378350
• 关键词: SCHIZOPHRENIA; DIAGNOSIS; LEUKOCYTE; MULTIGENE; SIGNATURES

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. This project will test the feasibility of a biological classification of schizophrenic patients and matched control subjects, based on high-density microarray measurement of transcribed white blood cell (leukocyte) RNA. Previous studies have shown associations between white blood cell (leukocyte) gene expression levels and schizophrenia, by measurement of mRNA transcripts for individual genes. The investigators hypothesize that patients with schizophrenia exhibit a characteristic leukocyte multigene expression pattern or signature that differs from normal healthy control subjects. This study is designed to generate multigene expression data from both neuroleptic-medicated and neuroleptic-naive schizophrenic patients, in order to avoid the potential confounder of neuroleptic drug-derived gene expression changes. The data generated in this study will be used to create a classifying multigene expression profile using clustering and supervised learning algorithms. The overall objective of this project is to successfully create a classifying, multigene marker profile for schizophrenia that can correctly distinguish both medicated and non-medicated schizophrenic patients from control subjects. Micro-array analysis will be performed to measure the gene expression in leukocyte samples from 20 neuroleptic-naive schizophrenic patients, 12 neuroleptic-treated schizophrenic patients, and 14 age- matched healthy control subjects. To recruit neuroleptic-naive patient subjects, the investigators will screen schizophrenic patients who present at the Bellevue Hospital Center Comprehensive Psychiatric Emergency Program (CPEP), and Rockland County local community facilities. To recruit medicated schizophrenic subjects they will screen Schizophrenic patients who present at Rockland Psychiatric Center (RPC), Orangeburg, New York. Control subjects will be recruited through the Nathan Kline Institute Healthy Volunteer Pool (NKI HVP). The specific aims are as follows: 1a) To collect blood leukocytes from twenty neuroleptic-na¿ve schizophrenics, twelve medicated schizophrenics, and fourteen age-matched healthy control subjects over the two-year period of this project. 1b) Employ Affymetrix GeneChip microarray technology to measure global gene expression in the leukocyte samples. 2) To combine the leukocyte gene expression datasets from our preliminary study (n=12) with that of this project (n=46), and use clustering and classification algorithms to identify and validate multi-gene fingerprints that differentiate schizophrenic subjects from normal healthy controls.

本子项目是利用由NIH/NCRR资助的中心赠款提供的资源的众多研究子项目之一。子项目和研究者（PI）可能已经从另一个NIH来源获得了主要资金，因此可以在其他CRISP条目中表示。列出的机构是中心的，不一定是研究者的机构。该项目将测试精神分裂症患者和匹配对照受试者的生物学分类的可行性，基于高密度微阵列测量转录的白细胞（白细胞）RNA。先前的研究表明，通过测量单个基因的mRNA转录物，白细胞基因表达水平与精神分裂症之间存在关联。研究人员假设精神分裂症患者表现出不同于正常健康对照者的特征性白细胞多基因表达模式或特征。本研究旨在从服用抗精神病药和未服用抗精神病药的精神分裂症患者中获取多基因表达数据，以避免抗精神病药衍生基因表达变化的潜在混杂因素。本研究中生成的数据将用于使用聚类和监督学习算法创建分类多基因表达谱。该项目的总体目标是成功创建一个分类的精神分裂症多基因标记谱，可以正确区分药物治疗和非药物治疗的精神分裂症患者与对照受试者。微阵列分析将测量20名初治精神分裂症患者、12名接受过精神分裂症治疗的患者和14名年龄匹配的健康对照者的白细胞样本中的基因表达。为了招募未使用抗精神病药的患者，研究人员将筛选在贝尔维尤医院中心综合精神病学急诊项目（CPEP）和罗克兰县当地社区设施就诊的精神分裂症患者。为了招募药物治疗的精神分裂症受试者，他们将筛选在纽约州奥兰治堡罗克兰精神病学中心（RPC）就诊的精神分裂症患者。对照受试者将通过内森克莱恩研究所健康志愿者池（NKI HVP）招募。具体目的如下：1a)在本项目为期两年的时间内，收集20名抗精神病药物性精神分裂症患者、12名药物性精神分裂症患者和14名年龄匹配的健康对照者的血液白细胞。1b)采用Affymetrix基因芯片微阵列技术测量白细胞样本中整体基因表达。2)结合前期研究的白细胞基因表达数据集（n=12）和本项目的白细胞基因表达数据集（n=46），使用聚类和分类算法识别和验证区分精神分裂症受试者与正常健康对照的多基因指纹图谱。