Classifying Schizophrenia:Leukocyte Multigene Signatures

描述（由申请人提供）：本提案旨在基于转录的白色血细胞（白细胞）RNA的高密度微阵列测量，产生用于开发精神分裂症患者生物学分类的数据。在最近完成的NIMH B-启动赠款，PI已利用全球基因表达分析外周血白细胞作为分类介质的精神分裂症。初步的研究结果是惊人的;来自7名精神分裂症患者和5名对照的基因表达数据的层次聚类，导致所有样本被分类到正确的组（精神分裂症患者或健康对照）。这一令人兴奋的结果导致了本建议的具体目标：（1）a。在该项目的两年时间内，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名接受过抗精神病药物治疗的精神分裂症患者和14名健康对照受试者的外周血白细胞，以及B.目的：应用Affyssin基因芯片技术检测白细胞基因表达。(2)在初步研究和提案中收集的白细胞基因表达数据集，导致58名受试者的最终分析，将通过分层聚类和判别分析进行合并和分析，以识别和验证区分精神分裂症受试者和健康对照的多基因指纹。目前提出的研究，其中包括收集样本的抗精神病药初治的精神分裂症患者，旨在避免潜在的混杂因素的抗精神病药诱导的基因表达变化。我们乐观地认为，完成这项拟议的探索性研究将导致创建一个多基因表达签名，可以分类白细胞样本到精神分裂症患者或对照组，并可用于预测类未知的样品。如果我们的方法的有效性在这项探索性研究中得到证明，我们这项研究的长期目标是通过以下方式增加这项工作的范围：1。将我们的精神分裂症数据集中的受试者数量增加到可接受的统计功效水平，并复制其他精神疾病（包括双相情感障碍、双相情感障碍和重度抑郁症）的数据集。这将使我们能够测试这些分类特征，从而尝试对精神疾病和这些疾病的可能生物亚型进行生物学诊断。这些生物学特征可能反过来刺激靶向新药的开发。 2.进行一项后续研究，招募有患精神分裂症风险增加的成员的家庭。这些家族将使我们能够测试在发病前的受试者中是否存在对精神分裂症进行分类的基因表达模式，以及是否有可能预测疾病的风险，从而提供可能减轻疾病进程的早期治疗。精神分裂症的生物学分类对公共卫生的益处可能很大，特别是如果在发病前阶段进行预测性测试是可能的，这就提高了有针对性的预防性治疗的可能性。

DESCRIPTION (provided by applicant): This proposal is designed to produce data for development of a biological classification of schizophrenic patients, based on high-density microarray measurement of transcribed white blood cell (leukocyte) RNA. In a recently completed NIMH B-start grant, the PI has utilized global gene expression analysis of peripheral leukocytes as a classification medium for schizophrenia. The preliminary study results were striking; hierarchical clustering of the gene expression data from seven schizophrenic patients and five controls, resulted in classification of all the samples into their correct group (schizophrenic patients or healthy controls). This exciting result has led to the present proposal with the following Specific Aims: (1) a. To collect peripheral blood leukocytes from twenty neuroleptic-naive schizophrenics, twelve neuroleptic-treated schizophrenics, and fourteen healthy control subjects over the two-year period of the project, and b. To employ Affymetrix GeneChip mieroarray technology to measure global gene expression in the leukocyte samples. (2) The leukocyte gene expression datasets collected during the preliminary study and the proposal, resulting in a final analysis of 58 subjects, will be combined and analyzed by hierarchical clustering and discriminate analyses to identify and validate multi-gene fingerprints that differentiate schizophrenic subjects from healthy controls. The current proposed study, which incorporates the collection of samples from neurolepfic-naive schizophrenic patients, is designed to avoid the potential confounding factor of neuroleptic-medication induced gene expression changes. We are optimistic that completion of this proposed exploratory study will lead to the creation of a multigene expression signature that can classify leukocyte samples into schizophrenic patient or control groups and that can be used to predict the class of unknown samples. If the validity of our approach is demonstrated in this exploratory study, our longer-term aims for this research are to increase the scope of this work by: 1. Increasing the number of subjects in our schizophrenic dataset to the level of acceptable statistical power and also duplicating this dataset for other psychiatric disorders including bipolar disorder, schizoaffective disorder and major depression. This will allow us to test these classification signatures and thus attempt biological diagnosis of psychiatric disorders and possible biological subtypes of those disorders. These biological signatures may, in turn, stimulate the development of targeted novel medications. 2. Perform a follow-up study recruiting families with members at increased risk of developing schizophrenia. These families will allow us to test whether gene expression patterns that classify schizophrenia are present in premorbid subjects and whether it is possible to predict risk of illness, and thus provide early treatment that might mitigate the course of the disorder. The public health benefits of a biological classification of schizophrenia are potentially large, especially if predictive testing in the premorbid stage is possible, raising the possibility of targeted preventative treatment.