Structural and Neurometabolic White Matter Integrity in the Deficit Syndrome

缺陷综合征中的结构和神经代谢白质完整性

基本信息

项目摘要

 DESCRIPTION (provided by applicant): The current system of psychiatric diagnosis does not include characteristics that delineate patterns of symptoms, severity of illness or prognostic features. This greatly hinders progress in our understanding of mental illness and development of more specific treatments. The deficit syndrome is thought to be a more homogeneous subgroup of schizophrenia that is characterized by primary and enduring negative symptoms. It is associated with greater global impairment, lower quality of life, and poorer long-term outcome. We propose to use multimodal neuroimaging to study 20 schizophrenia patients with the deficit syndrome, 20 schizophrenia patients without the deficit syndrome, and 20 matched healthy controls. We will use (1) Diffusion Tensor Imaging to measure structural white matter integrity, (2) Magnetic Resonance Spectroscopy to measure neurometabolic white matter integrity, and (3) resting state functional MRI to measure functional connectivity to test the hypotheses that white matter integrity and related functional connectivity patterns differ between deficit and non-deficit schizophrenia. Using complementary neuroimaging techniques will allow generating a broad characterization of structural and neurometabolic white matter abnormalities and their functional consequences in the deficit syndrome. The results of proposed study might not only lead to identification of biomarkers that can assist in identification of patients at risk for developing the deficit syndrome before the clinical picture manifests, it will also provide the training necessary to prepare the candidate for an independent research career with focus on translational research in psychotic disorders.
 描述(由申请人提供):目前的精神病学诊断系统不包括描述症状模式、疾病严重程度或预后特征的特征。这极大地阻碍了我们对精神疾病的理解和开发更具体的治疗方法。缺陷综合征被认为是精神分裂症的一个更同质性的亚群,其特征是最初和持久的阴性症状。它与更大的全球损害、较低的生活质量和较差的长期结果有关。我们建议使用多模式神经成像来研究20例有缺陷综合征的精神分裂症患者,20例没有缺陷综合征的精神分裂症患者,以及20名匹配的健康对照。我们将使用(1)扩散张量成像来测量结构白质完整性,(2)磁共振波谱来测量神经代谢白质完整性,以及(3)静息状态功能磁共振来测量功能连通性,以测试缺陷型和非缺陷型精神分裂症之间脑白质完整性和相关功能连通性模式不同的假设。使用互补的神经成像技术将能够对结构和神经代谢白质异常及其在缺陷综合征中的功能后果进行广泛的表征。拟议的研究结果不仅可能导致识别生物标记物,这些生物标记物可以帮助在临床图像显现之前识别有患缺陷综合征风险的患者,而且还将提供必要的培训,为候选人准备独立的研究生涯,专注于精神障碍的翻译研究。

项目成果

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Nina Vanessa Kraguljac其他文献

Nina Vanessa Kraguljac的其他文献

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{{ truncateString('Nina Vanessa Kraguljac', 18)}}的其他基金

Mapping heterogeneity of brain microstructural abnormalities in psychiatric disorders with normative modelling
通过规范模型绘制精神疾病中大脑微结构异常的异质性
  • 批准号:
    10658680
  • 财政年份:
    2023
  • 资助金额:
    $ 17.74万
  • 项目类别:
Contribution of Glutamate Excess and Inflammation to Progressive White Matter Changes in Psychosis
谷氨酸过量和炎症对精神病进行性白质变化的影响
  • 批准号:
    10993958
  • 财政年份:
    2023
  • 资助金额:
    $ 17.74万
  • 项目类别:
Contribution of Glutamate Excess and Inflammation to Progressive White Matter Changes in Psychosis
谷氨酸过量和炎症对精神病进行性白质变化的影响
  • 批准号:
    10657727
  • 财政年份:
    2019
  • 资助金额:
    $ 17.74万
  • 项目类别:
Contribution of Glutamate Excess and Inflammation to Progressive White Matter Changes in Psychosis
谷氨酸过量和炎症对精神病进行性白质变化的影响
  • 批准号:
    10002296
  • 财政年份:
    2019
  • 资助金额:
    $ 17.74万
  • 项目类别:
Contribution of Glutamate Excess and Inflammation to Progressive White Matter Changes in Psychosis
谷氨酸过量和炎症对精神病进行性白质变化的影响
  • 批准号:
    10200644
  • 财政年份:
    2019
  • 资助金额:
    $ 17.74万
  • 项目类别:
Contribution of Glutamate Excess and Inflammation to Progressive White Matter Changes in Psychosis
谷氨酸过量和炎症对精神病进行性白质变化的影响
  • 批准号:
    9815787
  • 财政年份:
    2019
  • 资助金额:
    $ 17.74万
  • 项目类别:
Contribution of Glutamate Excess and Inflammation to Progressive White Matter Changes in Psychosis
谷氨酸过量和炎症对精神病进行性白质变化的影响
  • 批准号:
    10435426
  • 财政年份:
    2019
  • 资助金额:
    $ 17.74万
  • 项目类别:
Structural and Neurometabolic White Matter Integrity in the Deficit Syndrome
缺陷综合征中的结构和神经代谢白质完整性
  • 批准号:
    9033607
  • 财政年份:
    2015
  • 资助金额:
    $ 17.74万
  • 项目类别:
Structural and Neurometabolic White Matter Integrity in the Deficit Syndrome
缺陷综合征中的结构和神经代谢白质完整性
  • 批准号:
    9763644
  • 财政年份:
    2015
  • 资助金额:
    $ 17.74万
  • 项目类别:
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