Genetic markers of white matter integrity in schizophrenia: Relationship to clini

精神分裂症白质完整性的遗传标记：与临床的关系

• 批准号: 7819475
• 负责人: VINCE D CALHOUN
• 金额: $ 50万
• 依托单位: THE MIND RESEARCH NETWORK
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7819475
• 关键词: Address; Adolescent; Affect; Anisotropy; Applications Grants; Area; Award; Bioinformatics; Biological Markers; Brain region; Child; Chronic; Clinical; Cognitive; Collaborations; Communication; Communities; DNA; Data; Data Set; Defect; Development; Diffusion Magnetic Resonance Imaging; Disease; Early treatment; Electroencephalography; Event; Family; Functional Magnetic Resonance Imaging; Functional disorder; Funding; Genes; Genetic; Genetic Markers; Genetic Polymorphism; Genetic Variation; Genotype; Goals; Grant; Gray unit of radiation dose; Human Resources; Image Analysis; Knowledge; Location; Magnetic Resonance Imaging; Maps; Measurement; Mental disorders; Methods; Mind-Body Method; Molecular Genetics; Monitor; Multivariate Analysis; Mutation; Myelin; Neurodevelopmental Disorder; Neurons; Neurotransmitters; Oligodendroglia; Pathology; Patients; Pattern; Phase; Population; Prevalence; Reporting; Research; Research Personnel; Risk; Role; Saliva; Sampling; Schizophrenia; Severities; Severity of illness; Single Nucleotide Polymorphism; Site; Social Functioning; Software Tools; Solid; Statistical Methods; Structure; Symptoms; Synapses; System; Technology; Temporal Lobe; Training; Treatment Efficacy; United States National Institutes of Health; Validation; Work; age related; base; cohort; critical period; dysmyelination; genome-wide; imaging modality; independent component analysis; innovation; myelination; neuroimaging; neuropsychiatry; novel; patient population; public health relevance; tool; treatment strategy; white matter

DESCRIPTION (provided by applicant): This application addresses broad Challenge Area (03) Biomarker Discovery and Validation and specific Challenge Topic 03-MH-101* Biomarkers in Mental Disorders. Specifically, we plan to use a combination of genetic and neuroimaging tools to identify novel biomarkers of clinical severity in patients with schizophrenia. Schizophrenia is a chronic and severely debilitating mental disorder affecting approximately 1% of the world's population. Multiple neurotransmitter systems have been implicated, as well as both gray and white matter abnormalities. These structural alterations are thought to underlie both synaptic miscommunication at local neuronal circuits and functional disconnectivity among distributed brain regions. Given the role of myelin in sub-serving rapid long-distance communication, it has been proposed that a disruption of oligodendrocyte function and myelin integrity may contribute to some of the symptoms of this illness. Supporting this idea, an increasing number of neuropathological, neuroimaging and molecular genetic studies demonstrate the presence of white matter pathology in patients with schizophrenia. Although schizophrenia is not a dysmyelinating disorder, it is important to note that: a) the onset of symptoms usually coincides with the peak of myelination in the frontal and temporal lobes, b) patients with schizophrenia often show an impaired age- related increase in white matter volumes in the these brain regions and c) specific disruption of myelin structure during this critical period is often associated with schizophrenia-like symptoms. Over 90 articles in the past 5 years have used diffusion tensor imaging (DTI) to characterize white matter abnormalities in chronic and first episode patients. The studies demonstrated myelin integrity defects in the subcortical white matter, particularly in the frontal and temporal lobes. However given that these studies were performed using a small number of patients, and there were some discrepancies about the location and extent of white matter pathology identified, several questions remain about the prevalence of myelin pathology in the patient population. Furthermore, the genetic contributions to these alterations and the significance of white matter pathology to clinical severity remain to be established. As shown in the diagram above, in this challenge grant, we propose to assess influence of white matter alterations and genetic variation to the different symptoms of schizophrenia. The contributions of specific gene polymorphisms to measurements of white matter integrity will be evaluated using 500 patients and control subjects. These measurements will be correlated with disease severity using multivariate statistical methods developed by the PI. Specifically we plan to: Aim 1: Employ available DTI data and DNA samples, collected in 250 well-characterized schizophrenia patients and healthy controls, to identify the putative genetic underpinnings of white matter tract abnormalities and correlate these with several measurements of clinical severity. The data and samples have been collected as part of previously and currently funded studies at two sites: The Mind Research Network (MRN) and the Olin Neuropsychiatry Research Center (ONRC). Aim 2: Use additional data collected at both sites (N=250) to perform a confirmatory analysis validating the observations made under Aim 1. We will also release a set of software tools to the community. Why is a Challenge grant mechanism ideal for the proposed research? 1) Our goal of using innovative approaches to identify candidate biomarkers for mental disorders that are suitable for subsequent validation efforts matches the goals of this RFA. The proposed use of genetic, neuroimaging and statistical tools also matches the technological approaches described in the RFA and represents a new direction in the field. There are currently no reliable biomarkers for schizophrenia, so the proposed search for biomarkers that can predict disease severity is of high impact. 2) A two year grant award is ideal for the proposed work. We have already acquired most of the MRI data and collected saliva samples as part of other NIH funded studies that used different imaging modalities (fMRI and EEG) in the same groups of patients. Therefore, the project will focus on the genotyping and DTI analyses and the statistical methods to search for specific biomarkers. 3) We have assembled a team of investigators with unique expertise and an excellent record of effective past collaborations to pursue these studies. Our plan to hire and train new personnel, and to employ unique genome wide and bioinformatics technologies using US-based companies such as Illumina, Inc., will have the added benefit of stimulating the economy. PUBLIC HEALTH RELEVANCE: The goal of this Challenge grant application is to identify novel biomarkers of clinical severity in patients with schizophrenia. There are currently no reliable biomarkers for schizophrenia, so the proposed use of sophisticated genotyping, neuroimaging and biostatistical tools for searching biomarkers that can predict disease severity in two large cohorts of patient has a high clinical impact. The identification of such biomarkers will not only increase our knowledge of the pathophysiology of schizophrenia but also, and most importantly, may help predict an increased risk for this illness even before the onset of symptoms.

描述（由申请人提供）：本申请涉及广泛的挑战领域（03）生物标志物发现和验证以及特定的挑战主题03-MH-101 * 精神疾病生物标志物。具体来说，我们计划使用遗传学和神经影像学工具的组合来识别精神分裂症患者临床严重程度的新生物标志物。精神分裂症是一种慢性和严重衰弱的精神障碍，影响着世界上大约1%的人口。多个神经递质系统已经牵连，以及灰色和白色物质异常。这些结构改变被认为是局部神经元回路突触错误通信和分布式脑区域之间功能断开的基础。鉴于髓鞘在辅助快速长距离通信中的作用，有人提出少突胶质细胞功能和髓鞘完整性的破坏可能导致这种疾病的一些症状。越来越多的神经病理学、神经影像学和分子遗传学研究证实精神分裂症患者存在白色物质病理学改变。虽然精神分裂症不是髓鞘形成障碍，但重要的是要注意：a）症状的发作通常与额叶和颞叶中髓鞘形成的峰值一致，B）精神分裂症患者通常显示这些脑区域中白色物质体积的受损的年龄相关性增加，和c）在此关键时期髓鞘结构的特异性破坏通常与精神分裂症样症状相关。在过去5年中，有超过90篇文章使用弥散张量成像（DTI）来表征慢性和首次发作患者的白色异常。研究表明，在皮质下白色物质中存在髓鞘完整性缺陷，特别是在额叶和颞叶。然而，考虑到这些研究是使用少量患者进行的，并且在确定的白色病变的位置和程度方面存在一些差异，因此关于患者人群中髓鞘病变的患病率仍存在一些问题。此外，这些改变的遗传贡献和白色物质病理学对临床严重程度的意义仍有待确定。如上图所示，在这项挑战性资助中，我们建议评估白色物质改变和遗传变异对精神分裂症不同症状的影响。将使用500例患者和对照受试者评价特定基因多态性对白色物质完整性测量的贡献。将使用PI开发的多变量统计方法将这些测量值与疾病严重程度相关联。具体而言，我们计划：目标1：采用现有的DTI数据和DNA样本，收集在250个良好的特点精神分裂症患者和健康对照，以确定推定的遗传基础的白色物质束异常，并与这些临床严重程度的几个测量。这些数据和样本是作为两个站点以前和现在资助的研究的一部分收集的：心灵研究网络（MRN）和奥林神经精神病学研究中心（ONRC）。目标2：使用在两个研究中心收集的额外数据（N = 250）进行确证性分析，验证目标1下的观察结果。我们还将向社区发布一套软件工具。为什么挑战奖助金机制是拟议研究的理想选择？1)我们的目标是使用创新的方法来识别适用于后续验证工作的精神障碍候选生物标志物，这与RFA的目标相匹配。遗传学、神经影像学和统计学工具的拟议使用也与RFA中描述的技术方法相匹配，代表了该领域的新方向。目前还没有可靠的精神分裂症生物标志物，因此建议寻找可以预测疾病严重程度的生物标志物具有很高的影响力。2)一个为期两年的补助金是理想的拟议工作。我们已经获得了大部分MRI数据，并收集了唾液样本，作为NIH资助的其他研究的一部分，这些研究在同一组患者中使用了不同的成像方式（fMRI和EEG）。因此，该项目将集中在基因分型和DTI分析和统计方法，以寻找特定的生物标志物。3)我们已经组建了一个具有独特专业知识的研究人员团队，并在过去的有效合作中保持了良好的记录，以进行这些研究。我们计划雇用和培训新的人员，并使用独特的全基因组和生物信息学技术，使用美国公司，如Illumina公司，会带来刺激经济的额外好处 公共卫生相关性：这项挑战拨款申请的目标是确定精神分裂症患者临床严重程度的新生物标志物。目前还没有可靠的精神分裂症生物标志物，因此建议使用复杂的基因分型，神经成像和生物统计工具来搜索可以预测两大队列患者疾病严重程度的生物标志物，具有很高的临床影响。这些生物标志物的鉴定不仅会增加我们对精神分裂症病理生理学的了解，而且最重要的是，甚至在症状出现之前，可能有助于预测这种疾病的风险增加。