Classifying Schizophrenia:Leukocyte Multigene Signatures

描述（由申请人提供）：该提案旨在基于转录白细胞（白细胞）RNA的高密度微阵列测量，为开发精神分裂症患者的生物学分类提供数据。在最近完成的NIMH B-start拨款中，PI利用外周白细胞的全球基因表达分析作为精神分裂症的分类介质。初步的研究结果是惊人的；对来自7名精神分裂症患者和5名对照组的基因表达数据进行分层聚类，将所有样本分类到正确的组（精神分裂症患者或健康对照组）。这一令人兴奋的结果导致了目前的建议，其具体目标如下：(1)a.在两年的项目期间，从20名抗精神病药物治疗的精神分裂症患者，12名抗精神病药物治疗的精神分裂症患者和14名健康对照受试者中收集外周血白细胞，b.使用Affymetrix基因芯片微阵列技术来测量白细胞样本中的整体基因表达。(2)初步研究和提案中收集的白细胞基因表达数据集，最终分析58名受试者，将通过分层聚类和判别分析进行组合和分析，以识别和验证区分精神分裂症受试者与健康对照的多基因指纹。目前提出的研究，包括从神经安定素-初发性精神分裂症患者中收集样本，旨在避免神经安定素药物诱导基因表达变化的潜在混淆因素。我们乐观地认为，这项探索性研究的完成将导致创建一个多基因表达标记，可以将白细胞样本分类为精神分裂症患者或对照组，并可用于预测未知样本的类别。如果我们的方法的有效性在这个探索性研究中得到证明，我们对这项研究的长期目标是通过以下方式扩大这项工作的范围：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能力水平，并将该数据集复制到其他精神疾病中，包括双相情感障碍、分裂情感障碍和重度抑郁症。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可能的生物学亚型进行生物学诊断。这些生物特征可能反过来刺激靶向新型药物的开发。2. 进行一项后续研究，招募有成员患精神分裂症风险增加的家庭。这些家庭将使我们能够测试将精神分裂症分类的基因表达模式是否存在于发病前的受试者中，以及是否有可能预测疾病的风险，从而提供可能减轻疾病病程的早期治疗。精神分裂症生物学分类的公共卫生益处可能是巨大的，特别是如果在发病前阶段进行预测性测试是可能的，这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.