Specificity of Hippocampal Subregion Cerebral Blood Volume Abnormalities in Psychiatric Disorders

项目摘要 严重精神疾病（SMI）是全球残疾的主要原因，也是造成全球残疾的最大成本负担。 所有的非传染性疾病。临床神经科学的主要挑战之一是实现一种机制， 了解SMI中涉及的大脑回路。这种理解对于开发针对以下疾病的治疗至关重要： 改善这些疾病的潜在生物学原因。在精神病综合征中， 精神分裂症和双相情感障碍之间存在差异。例如，情绪和精神病症状发生在 这两种疾病，他们显示出显着的遗传重叠，但精神分裂症并不常见的躁狂症， 和双相情感障碍的标志性抑郁症阶段。这些发现表明，常见的和疾病- 特定的神经回路改变与精神分裂症和双相情感障碍有关，我们将从一个 除了分类的视角之外，还有维度。其中一个与大多数神经精神疾病有关的大脑区域 包括精神分裂症和双相情感障碍在内的精神疾病的最大障碍是海马结构（HF）。HF参与了 情绪、压力调节和记忆形成。这个提议提出了一个海马电路的模型 双相情感障碍的功能障碍，使系统的假设驱动的研究。本提案的目的是测试这一点， 双相情感障碍的海马回路功能障碍模型，通过识别常见和疾病特异性HF回路 与健康志愿者相比，精神分裂症和双相情感障碍之间的异常。为了实现这一目标， 拟议的研究将利用最先进的高分辨率海马脑血容量（CBV）和连通性 映射.除了分类组比较，这项研究还将研究这些大脑之间的关系， 影像学测量和维度神经认知、症状和功能结果概况。该研究建立在 发现精神分裂症的有前途的新神经影像学生物标志物，即高前海马CA 1 脑血容量（CBV），使用高分辨率CBV绘图评估;最近重复的发现。的结果 这一系列的研究正在推动精神分裂症的新治疗策略，即使用高前海马CBV作为治疗策略。 基于成像的生物标志物来评估治疗靶点接合。这一建议旨在遵循类似的研究策略 治疗躁郁症据我们所知，这项研究首先利用高分辨率的CBV映射， 双相情感障碍的海马电路，并首次利用高分辨率静息状态连接分析， 精神分裂症和双相情感障碍的海马回路。这项研究符合NIH/NIMH的 战略目标是“推进新的测定和工具，以开发疾病的生物标志物和治疗发现”，并将 提供新的治疗目标，实现新的治疗评估，并推进个性化干预的道路。 区分与精神分裂症和双相情感障碍相关的共同和独特的神经基质， 更有效地预测治疗结果，更有效地评估对治疗的临床反应。识别 与双相情感障碍和精神分裂症相关的独特神经基质也将促进发展， 对目前治疗效果不佳的患者进行新疗法的测试。重要的是，它们也可能 早期发现和疾病预防的承诺。

Project Summary Severe mental illnesses (SMI) are the leading cause of global disability and responsible for the largest cost burden among all the non-communicable diseases. One of the major challenges for clinical neuroscience is achieving a mechanistic understanding of the brain circuitry involved in SMI. Such understanding is critical to developing treatments aimed at ameliorating the underlying biological causes of these disorders. Among the psychiatric syndromes, important similarities and differences exist between schizophrenia and bipolar disorder. For instance, mood and psychotic symptoms occur in both disorders and they show significant genetic overlap, yet schizophrenia does not commonly present with the manic and depressive illness phases that are the hallmark of bipolar disorder. These findings suggest that common and disease- specific neural circuitry alterations are associated with schizophrenia and bipolar disorder, which we will examine from a dimensional in addition to a categorical perspective. One of the brain regions implicated in most neuropsychiatric disorders, including schizophrenia and bipolar disorder, is the hippocampal formation (HF). The HF is involved in emotion, stress regulation, and memory formation. This proposal puts forward a model of hippocampal circuitry dysfunction in bipolar disorder to enable systematic hypothesis driven research. The aim of this proposal is to tests this hippocampal circuitry dysfunction model of bipolar disorder by identifying common and disease-specific HF circuitry abnormalities between schizophrenia and bipolar disorder in comparison to healthy volunteers. To achieve this aim, the proposed study will utilize state-of-the-art high-resolution hippocampal cerebral blood volume (CBV) and connectivity mapping. In addition to categorical group comparisons, this study will also examine relationships between these brain imaging measures and dimensional neurocognitive, symptom, and functional outcome profiles. The study builds upon the discovery of the promising novel neuroimaging biomarker for schizophrenia, namely high anterior hippocampal CA1 cerebral blood volume (CBV), assessed using high-resolution CBV mapping; a finding recently replicated. Findings from this line of research are driving new treatment strategies for schizophrenia that use high anterior hippocampal CBV as an imaging based biomarker to assess treatment target engagement. This proposal aims to follow a similar research strategy for bipolar disorder. To our knowledge, the proposed study is first to utilize high-resolution CBV mapping of hippocampal circuitry in bipolar disorder, and first to utilize high-resolution resting state connectivity analyses of hippocampal circuitry in both schizophrenia and bipolar disorder. The proposed research is in line with NIH/NIMH's strategic goal to “advance novel assays and tools to develop biomarkers of disease and for therapeutic discovery”, and will provide new treatment targets, enable new treatment evaluation, and advance the path towards personalized interventions. Differentiation of common and unique neural substrates associated with schizophrenia and bipolar disorder could be used to predict treatment outcome more effectively and to more effectively assess clinical responses to treatment. Identifying the unique neural substrates associated with bipolar disorder and schizophrenia would also facilitate the development and testing of new treatments for individuals who do not respond well to current treatments. Importantly, they may also hold the promise of early detection and illness prevention.