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

小脑对精神病高危青少年疾病进程的影响

• 批准号: 8646069
• 负责人: Jessica Ann Bernard
• 金额: $ 4.92万
• 依托单位: UNIVERSITY OF COLORADO
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-30 至 2015-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8646069
• 关键词: Affect; Affective; Age; Behavioral; Biological Markers; Brain; Brain Stem; Cerebellar Diseases; Cerebellum; Clinical; Clinical assessments; Cognitive; Corpus striatum structure; Data; Development; Diffusion Magnetic Resonance Imaging; Disease; Disease Progression; Dysmetria; Etiology; Family; First Degree Relative; Functional Magnetic Resonance Imaging; Functional disorder; Future; Goals; Illness impact; Image; Individual; Intervention; Investigation; Knowledge; Lead; Link; Literature; Magnetic Resonance Imaging; Maps; Measures; Mental disorders; Mentorship; Methods; Metric; Motor; Movement; Participant; Patients; Population; Population Control; Populations at Risk; Prefrontal Cortex; Preventive; Psychotic Disorders; Reporting; Research; Resolution; Rest; Risk; Role; Scanning; Schizophrenia; Severities; Societies; Structure; Symptoms; Targeted Research; Techniques; Testing; Therapeutic; Therapeutic Intervention; Training; Translational Research; Treatment outcome; Walkers; Work; Youth; base; brain volume; cognitive function; gray matter; high risk; improved; innovation; insight; longitudinal design; morphometry; neuroimaging; neuropsychological; prospective; public health relevance; relating to nervous system; time use; translational approach; white matter

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.

描述（由申请人提供）：拟议的研究的长期目标是表征小脑前额外网络在症状严重程度和疾病进程中的关系，以供精神病患者（UHR）患者的病程。 UHR个体患有轴I精神病的风险要高得多，并且确定与症状相关的神经差异，疾病的过程是迈向精神病预测生物标志物发展的关键第一步。这样的生物标志物将为有针对性的预防性治疗剂打开大门。尽管与纹状体功能相关的运动异常与精神病的转化有关，但我们还发现证据明显地暗示了小脑在UHR个体中的症状严重程度。尽管小脑在精神分裂症中进行了很好的研究，并且其网络，尤其是与前额叶皮层相关的网络，与精神分裂症中的功能障碍的认知障碍障碍框架有关，但它在UHR种群中已相对研究。有证据表明UHR组的小脑体积减少，并且精神分裂症患者一级亲戚的静息状态小脑连通性降低，但有关该主题的文献通常很少。考虑到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异常的贡献，小脑网络是UHR种群研究的重要目标。在这里，我们的目的是1）研究静止状态功能性小脑前额外皮质网络的群体差异，2）研究UHR和健康控制之间小脑前额外皮质网络的大脑结构和结构连通性的群体差异。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）的完整性，以及这些网络中小脑和前额淋巴结的体积，就症状严重程度，认知功能以及使用两年的纵向设计而言，疾病的过程。使用 多模式神经影像学我们将收集静止状态连通性MRI（FCMRI）和扩散张量成像（DTI），并每年进行高分辨率的解剖扫描。此外，所有参与者将完成认知测试，以及临床评估，以量化UHR个体的症状严重程度和疾病进展。我将获得转化研究以及DTI和结构解剖分析方法的关键培训。小脑前额外网络与精神病发展之间的关系的了解对于获得精神分裂症病因的完整情况至关重要。这样做会有助于解释 小脑在精神分裂症中的作用及其病因。此外，这可能有助于 开发有针对性的干预措施，这些干预措施可能会改善高危人群的疾病过程和治疗结果。