Cerebellar Contributions to Disease Course in Youth At High-Risk of Psychosis

描述（由申请人提供）：拟议研究的长期目标是表征小脑-前额叶网络与精神病超高风险（UHR）个体症状严重程度和病程之间的关系。UHR个体发展为I轴精神障碍的风险要高得多，识别与症状学和病程相关的神经差异是开发精神病预测性生物标志物的关键第一步。这样的生物标记物将为更有针对性的预防性治疗打开大门。虽然纹状体功能相关的运动异常与转化为精神病有关，但我们也发现了明显的证据，表明UHR个体的症状严重程度与小脑有关。虽然小脑在精神分裂症中已经得到了很好的研究，其网络，特别是与前额皮质相关的网络，与精神分裂症中所见功能障碍的认知障碍框架有关，但在UHR人群中对小脑的研究相对不足。有证据表明，UHR组小脑容量下降，精神分裂症患者一级亲属静息状态小脑-皮层连通性下降，但关于这一主题的文献普遍较少。鉴于我们最近发现小脑功能障碍与症状严重程度之间的关系，以及小脑对精神分裂症和认知障碍的贡献，小脑网络是UHR人群研究的重要目标。在这里，我们的目的是1)研究各组在静息状态下小脑-前额叶皮层网络功能的差异；2)研究UHR和健康对照组在大脑结构和小脑-前额叶皮层网络结构连通性方面的差异。至关重要的是，我们还将研究这些网络的完整性（结构和功能）与这些网络中小脑和前额叶节点的体积之间的关系，以及使用两年纵向设计的症状严重程度、认知功能和病程。使用

DESCRIPTION (provided by applicant): The long-term goal of the proposed study is to characterize the relationship between cerebello-prefrontal networks with respect to symptom severity and course of illness in individuals at ultra high-risk (UHR) for psychosis. UHR individuals are at much higher risk for the development of an Axis I psychotic disorder, and identifying neural differences associated with symptomatology and the course of illness is a key first step towards the development of predictive biomarkers for psychosis. Such biomarkers would open the door to more targeted preventative therapeutics. While movement abnormalities associated with striatal function are associated with the conversion to psychosis, we have also found evidence distinctly implicating the cerebellum in symptom severity in UHR individuals. While the cerebellum has been well studied in schizophrenia, and its networks, particularly networks associated with the prefrontal cortex, are implicated in the cognitive dysmetria framework for the dysfunction seen in schizophrenia, it has been relatively understudied in UHR populations. There is some evidence to indicate cerebellar volumetric decreases in UHR groups, and there is decreased resting state cerebello-cortical connectivity in first-degree relatives of schizophrenia patients, but the literature on this topic is generally sparse. Given ou recent finding of a relationship between cerebellar dysfunction and symptom severity, along with the contributions of the cerebellum to schizophrenia and cognitive dysmetria, cerebellar networks are an important target for research in UHR populations. Here, we aim to 1) investigate group differences in resting state functional cerebello-prefrontal cortical networks and 2) investigate group differences in brain structure and structural connectivity of cerebello-prefrontal cortical networks between UHR and healthy controls. Crucially, we will also investigate the relationship between the integrity of these networks (structural and functional), and the volume of cerebellar and prefrontal nodes in these networks, with respect to symptom severity, cognitive function, and the course of illness using a two year longitudinal design. Using multi-modal neuroimaging we will collect resting state connectivity MRI (fcMRI) and diffusion tensor imaging (DTI) in conjunction with high-resolution anatomical scans annually. In addition, all participants will complete cognitive testing, along with clinical assessments to quantify symptom severity and disease progression in UHR individuals. I will receive key training in translational research and in both DTI and structural anatomical analysis methods. Knowledge of the relationships between cerebellar-prefrontal networks and the development of psychosis is crucial for gaining a complete picture of the etiology of schizophrenia. Doing so will help explain the role of the cerebellum in schizophrenia, and its etiology. Furthermore, this may facilitate the development of targeted interventions that may improve disease course and treatment outcomes in at-risk populations.