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，也是造成最大成本负担的原因 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机械化的 对参与SMI的大脑回路的了解。这种理解对于开发针对以下目标的治疗方法至关重要 改善这些疾病的潜在生物原因。在精神症状中，重要的相似之处 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 这两种疾病都显示出显著的遗传重叠，然而精神分裂症并不常见于躁狂症 和抑郁症阶段，这是双相情感障碍的标志。这些发现表明，常见和疾病- 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，还有多个维度。与大多数神经精神疾病有关的大脑区域之一 障碍，包括精神分裂症和双相情感障碍，是海马体结构(HF)。高频参与了 情绪、压力调节和记忆形成。这一建议提出了一个海马区回路的模型。 双相情感障碍的功能障碍使系统假说驱动的研究成为可能。这项提议的目的是检验这一点。 识别常见和疾病特异性高频回路的双相情感障碍海马区回路功能障碍模型 精神分裂症和双相情感障碍与健康志愿者之间的异常。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)和连接性 映射。除了类别组比较之外，这项研究还将检查这些大脑之间的关系 影像测量和维度神经认知、症状和功能结果描述。这项研究建立在 精神分裂症新的神经影像生物标志物--高位前海马CA1区的发现 脑血容量(CBV)，使用高分辨率CBV图进行评估；最近重复了这一发现。调查结果来自 这一系列研究正在推动精神分裂症的新治疗策略，这些策略使用高海马区CBV作为 基于成像的生物标记物来评估治疗目标的投入。这项提议旨在遵循类似的研究战略。 治疗双相情感障碍。据我们所知，拟议的研究是第一次利用高分辨率的CBV映射 双相情感障碍的海马体电路，并首次利用高分辨率静息状态连接性分析 精神分裂症和双相情感障碍患者的海马区回路。这项拟议的研究与NIH/NIMH的研究一致 战略目标是“推进新的分析和工具，以开发疾病的生物标记物和治疗发现”，并将 提供新的治疗目标，使新的治疗评估成为可能，并推进个性化干预的道路。 可以使用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底物 更有效地预测治疗结果，并更有效地评估治疗的临床反应。识别 与双相情感障碍和精神分裂症相关的独特神经底物也将促进发育和 为对当前治疗无效的个人测试新的治疗方法。重要的是，他们还可能持有 承诺及早发现并预防疾病。

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.