Neural Circuitry Resilience in Psychotic Disorders: A Multimodal Ultra-High Field Neuroimaging Study

摘要：精神分裂症患者的远期社会效果良好率低至14%。正因为如此， 相当数量的SZ受试者患有严重和持久的残疾。一个重要的促成因素 精神分裂症长期预后差的原因是认知障碍，这些障碍对目前的治疗方法具有抵抗力。 因此，研究认知障碍的新机制以设计新的治疗方法是至关重要的。 最近的证据表明，连接它们的大脑皮层区域和白质通路适应 病理生理过程。这种适应可以减轻选定认知域的损害 希望针对选定的网络进行干预，以改善结果。使用最先进的非侵入性 神经成像技术，皮质神经束(突触、树突及其分支， 轴突终末和中间神经元)和白质完整性的水扩散特性测量 可以研究白质纤维。该项目的目标是描述大脑皮层的并发变化 白质纤维束中的神经纤维和水扩散的各向异性作为神经回路适应性的模型 (NCA)及其对SZ受试者与健康对照受试者(HC)认知表现的影响。 我们将在超高磁场(7特斯拉)下使用磷磁共振波谱(31P MRS) 通过测量神经细胞膜磷脂(MPL)代谢产物提供更高的敏感性来研究Neuropil 整个大脑有多个解剖学上定义明确的区域。MPLS是神经细胞的关键成分 自然形成脂质双层的膜，分隔细胞内和细胞外环境。在.期间 发育和疾病，膜的合成和降解之间的不平衡可以可靠地 被抓了。总的来说，较高的MPL前体水平与膜扩张有关，而较高的MPL水平与膜扩张有关 分解产物显示神经膜收缩。由于这样的动态变化突出地 在神经纤维层观察，31PMRS可以提供比结构成像更特异的测量神经纤维层的方法。 测量包括神经纤维以及神经元间隙、微血管和神经元胞体。轴突 定向弥散和密度成像(NODI)-一种测量水扩散的最新方法 沿白质束和轴突密度-将更多地用于检查白质通路的完整性 比较老的扩散张量成像方法更可靠。这项提议的创新性通过以下几个方面得到强调 MPL代谢物和各向异性的同步变化作为NCA与认知障碍相关的指标 因为使用单一模式成像不能测量多个组织中的适应性变化。使用我们的模型 通过使用多模式31P MRS-NODI数据，我们试图检验NCA与认知之间的关联 全脑表现(目标1)。此外，与NCA相关的因素尚不清楚。自深圳以来 是一种高度可遗传的疾病，而炎症与SZ有关，我们将考察选定的 遗传和外周炎性标志物(白介素6、白介素6和C反应蛋白)对NCA的影响。我们的 研究发现，补体C4a(C4a)基因拷贝数与神经纤维变化、IL-6和 C反应蛋白水平与神经纤维层和脑白质各向异性的改变。基于这些证据，我们的下一个目标是 确定C4a拷贝数和外周免疫介质水平与NCA测量的相关性 SZ组和HC组(目标2)。应用集成的最先进的方法来检查一个不太了解的 深圳NCA的概念使这一建议非常独特，并可能对新的治疗方法产生重大影响 设计。这些努力可能使我们能够针对新的干预措施，如定制的适应区域 采用经颅磁刺激的认知增强疗法和电刺激策略 (TMS)或以选定网络为目标的经颅直流电刺激(TDC)。

Abstract: Good long-term social outcome of schizophrenia (SZ) subjects is as low as 14%. Because of this, substantial number of SZ subjects suffer from severe and protracted disability. An important contributing factor to poor long-term outcome in schizophrenia is cognitive impairments that are resistant to current treatments. Therefore, it is critical to examine novel mechanisms underlying cognitive impairments to design new treatments. Recent evidence suggests that brain cortical regions and white matter pathways that connect them adapt to pathophysiological processes. Such adaptation can mitigate impairments in selected cognitive domains offering hopes to target selected networks for interventions to improve outcome. Using state-of-art non-invasive neuroimaging techniques, adaptation between the cortical neuropil (synapses, dendrites and its branches, axonal endings and interneurons) and white matter integrity measured using characteristics of water diffusion in white matter fibers can be investigated. The goal of this project is to characterize concurrent changes in cortical neuropil and anisotropy of water diffusion in white matter fiber tracts as a model of neural circuitry adaptability (NCA) and its impact on cognitive performance among SZ subjects compared to healthy control subjects (HC). We will use phosphorus magnetic resonance spectroscopy (31P MRS) at ultra-high magnetic field (7 Tesla) that provides greater sensitivity to investigate neuropil by measuring membrane phospholipid (MPL) metabolites in multiple anatomically well-defined regions across the entire brain. MPLs are critical ingredients of neuronal membranes that naturally form lipid bilayers separating the intra- and extra-cellular environments. During development and disease, imbalance between synthesis and degradation of membranes can be reliably captured. Broadly, higher MPL precursor levels are associated with membrane expansion while higher MPL breakdown products suggest neuropil membrane contraction. Since such dynamic changes are prominently observed in the neuropil, 31P MRS can provide a more specific measure of neuropil than structural imaging measures that includes neuropil as well as interneuronal space, microvasculature and neuronal soma. Neurite Orientation Dispersion and Density Imaging (NODDI) - a state-of-the-art method to measure diffusion of water along white matter tracts and neurite density- will be used to examine integrity of white matter pathways more reliably than the older method of diffusion tensor imaging. Innovative nature of this proposal is highlighted by concurrent changes in MPL metabolites and anisotropy as measures of NCA in relation to cognitive impairments since using single modality imaging cannot measure adaptive changes in multiple tissues. Using our model of NCA by employing multi-modal 31P MRS-NODDI data, we seek to examine association of NCA with cognitive performance across the whole-brain (aim 1). Additionally, factors associated with NCA are unknown. Since SZ is a highly heritable disorder, and inflammation is associated with SZ, we will examine the contribution of selected genetic and peripheral inflammatory markers (Interleukin-6, IL6 and C-reactive protein, CRP) to NCA. Our studies found association of Complement C4A (C4A) gene copy numbers with neuropil changes, and of IL-6 and CRP levels with alterations in neuropil and white matter anisotropy. Based this evidence, our next aim is to determine the association of C4A copy numbers and peripheral immune mediator levels with measures of NCA among SZ and HC (aim 2). Application of integrated state-of-the-art methods to examine a less well understood concept of NCA in SZ makes this proposal highly unique and can have significant impact on novel treatment designs. These efforts may allow us to target adaptable tracts for novel interventions such as customized cognitive enhancement therapies and electrical stimulation strategies using transcranial magnetic stimulation (TMS) or transcranial direct current stimulation (tDCS) targeted to selected networks.