Structure-Function Relationships in Dystonia: A Network Approach

描述（由申请人提供）：原发性肌张力障碍通常始于儿童晚期或青春期，传统上被归因于基底神经节功能障碍，但在尸检中这些结构没有明显的特定组织病理学病变。事实上，原发性肌张力障碍的挑战反映在其临床定义中：在没有可识别的大脑病变的情况下，存在不自主的持续肌肉收缩。由于缺乏明确的神经病理学，这种疾病难以理解和治疗。我们最近的工作支持了一个新的范式，了解肌张力障碍作为一种神经发育回路障碍。利用遗传性肌张力障碍的部分潜伏期和肌张力障碍运动在睡眠中消失的事实，我们采用新的磁共振扩散张量成像（DTI）方法在显式和非显式突变携带者中检查运动回路活动。我们做出了令人惊讶的发现，表现和非表现的突变携带者都表现出小脑-丘脑-皮质束的中断，并且非表现的个体在丘脑-皮质投射通路中表现出额外的远端中断。这种远端缺陷在临床上是“保护性的”：它阻断了异常小脑输出到运动皮层的传输。我们的工作已经产生了一个新的模型，运动电路功能障碍的基础肌张力障碍，我们将测试在这个建议，我们试图确定的纤维束完整性（微观结构）和神经激活反应（功能）的变化，调节临床反射，占表型差异，并调节治疗反应原发性肌张力障碍。在具体目标1中，我们将通过检查DYT 1和DYT 6突变的显性和非显性携带者的结构-功能关系来表征遗传性原发性肌张力障碍的运动回路异常。我们将评估通路的微观结构（使用DTI）和电路功能，使用H215 O PET测量脑血流量在任务性能和休息状态和功能磁共振成像定位任务相关的神经激活反应。在具体目标2中，我们将识别散发性肌张力障碍的回路异常，进行DTI/纤维束成像研究和大脑激活实验，并将结果与遗传性疾病患者的结果进行比较。最后，在具体目标3中，我们试图了解脑深部电刺激（DBS）在肌张力障碍中的工作原理，并确定患者反应的预测因素。DBS可以有效治疗严重的原发性肌张力障碍，但并非所有患者都同样受益，症状可能在最初的缓解期后再次出现。受试者将接受术前成像，然后在慢性刺激开始后的多个术后时间点参与一系列研究。所得扫描数据将用于：（a）测量随着治疗反应的发展网络活动的连续变化;（B）识别与临床治疗反应相关的基线微结构变化模式;以及（c）开发定量术前成像描述符以预测个体受试者的治疗反应。

DESCRIPTION (provided by applicant): Primary dystonia, which often begins in late childhood or adolescence, has traditionally been attributed to basal ganglia dysfunction, but no specific histopathological lesions of these structures are evident on postmortem examination. In fact, the challenge of primary dystonia is reflected in its clinical definition: the presence of involuntary, sustained muscle contractions in the absence of identifiable brain lesions. This lack of clear neuropathology has this illness difficult to understand and treat. Our recent work supports a new paradigm for understanding dystonia as a neurodevelopmental circuit disorder. Taking advantage of the partial penetrance of inherited dystonia and the fact that dystonic movements disappear during sleep, we employed new magnetic resonance diffusion tensor imaging (DTI) methods in manifesting and non- manifesting mutation carriers to examine motor circuit activity. We made the surprising discovery that both manifesting and non-manifesting mutation carriers exhibit disruptions of the cerebello-thalamo-cortical tract, and that non-manifesting individuals show additional, distal disruptions in the thalamo-cortical projection pathways. This distal defect is clinically "protective": it blocks transmission of the aberrant cerebellar output to the motor cortex. Our work has given rise to a new model for the motor circuitry dysfunction underlying dystonia, which we will test in this proposal as we seek to identify the changes in fiber tract integrity (microstructure) and neural activation responses (function) that regulate clinical penetrance, account for phenotypic differences, and modulate treatment response in primary dystonia. In Specific Aim 1 we will characterize motor circuit abnormalities in hereditary primary dystonia by examining structure-function relationships in manifesting and non-manifesting carriers of the DYT1 and DYT6 mutations. We will assess pathway microstructure (using DTI) and circuit function using H215O PET to measure cerebral blood flow during task performance and in the rest state and fMRI to localize task-related neural activation responses. In Specific Aim 2 we will identify circuit abnormalities in sporadic dystonia, conducting DTI/tractography studies and brain activation experiments and comparing the results to those obtained in patients with hereditary forms of the disease. Finally, in Specific Aim 3, we seek to understand how deep brain stimulation (DBS) works in dystonia when it does work, and identify predictors of patient response. DBS can be effective in treating severe primary dystonia, but not all patients benefit equally, and symptoms can re-emerge after an initial period of abatement. Subjects will undergo preoperative imaging and then participate in a series of studies at multiple postoperative time points following the start of chronic stimulation. The resulting scan data will be used to: (a) measure serial changes in network activity as the treatment response develops; (b) identify patterns of microstructural change at baseline that correlate with clinical treatment response; and (c) develop quantitative preoperative imaging descriptors to predict treatment response in individual subjects.