SCHIZOPHRENIA DIAGNOSIS: LEUKOCYTE MULTIGENE SIGNATURES

该子项目是利用NIH/NCRR资助的中心赠款提供的资源的许多研究子项目之一。子项目和研究者（PI）可能从另一个NIH来源获得主要资金，因此可以在其他CRISP条目中表示。所列机构为中心，不一定是研究者所在机构。该项目将测试精神分裂症患者和匹配的对照受试者的生物学分类的可行性，基于转录的白色血细胞（白细胞）RNA的高密度微阵列测量。先前的研究已经通过测量单个基因的mRNA转录物显示了白色血细胞（白细胞）基因表达水平与精神分裂症之间的关联。研究人员假设精神分裂症患者表现出与正常健康对照受试者不同的特征性白细胞多基因表达模式或特征。本研究的目的是产生多基因表达数据，从精神病药物治疗和精神病药物初治的精神分裂症患者，以避免潜在的混淆的精神病药物衍生的基因表达变化。本研究中产生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。本项目的总体目标是成功地创建一个分类，多基因标记物的精神分裂症，可以正确区分药物和非药物治疗的精神分裂症患者从控制科目。将进行微阵列分析以测量来自20名未经抗精神病药治疗的精神分裂症患者、12名经抗精神病药治疗的精神分裂症患者和14名年龄匹配的健康对照受试者的白细胞样品中的基因表达。为了招募未接受过抗精神病药物治疗的患者受试者，研究者将筛选在贝尔维尤医院中心综合精神病紧急项目（CPEP）和罗克兰县当地社区设施中的精神分裂症患者。为了招募药物治疗的精神分裂症受试者，他们将筛选在纽约奥兰治堡的罗克兰精神病中心（RPC）的精神分裂症患者。对照受试者将通过Nathan Kline研究所健康志愿者库（NKI HVP）招募。 具体目标如下：1a）在本项目的两年时间内，收集20名未接受过抗精神病药物治疗的精神分裂症患者、12名药物治疗的精神分裂症患者和14名年龄匹配的健康对照受试者的血液白细胞。1b）采用Affyscore基因芯片微阵列技术来测量白细胞样品中的整体基因表达。2)结合联合收割机前期研究（n=12）和本课题研究（n=46）的白细胞基因表达数据集，采用聚类和分类算法，对区分精神分裂症患者和正常对照的多基因指纹进行识别和验证。

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.