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: 8822140
• 负责人: Jessica Ann Bernard
• 金额: $ 4.6万
• 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 2015-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8822140
• 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）：拟议研究的长期目标是表征精神病超高风险（UHR）个体的症状严重程度和病程之间的小脑-前额叶网络之间的关系。 UHR 个体患 Axis I 精神障碍的风险要高得多，识别与症状和病程相关的神经差异是开发精神病预测生物标志物的关键第一步。这些生物标志物将为更有针对性的预防性治疗打开大门。虽然与纹状体功能相关的运动异常与精神病的转变有关，但我们还发现证据明显表明小脑与 UHR 个体的症状严重程度有关。虽然小脑在精神分裂症中得到了很好的研究，并且它的网络，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，它的研究相对不足。有一些证据表明 UHR 组的小脑体积减少，并且精神分裂症患者的一级亲属静息状态下小脑皮质连接性降低，但有关该主题的文献普遍很少。鉴于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影响，小脑网络是 UHR 人群研究的重要目标。在这里，我们的目标是 1) 研究静息状态功能性小脑前额皮质网络的群体差异，2) 研究 UHR 和健康对照之间大脑结构和小脑前额皮质网络结构连接的群体差异。至关重要的是，我们还将使用两年的纵向设计，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，以及症状严重程度、认知功能和病程。使用 多模态神经影像 我们每年将收集静息态连接 MRI (fcMRI) 和弥散张量成像 (DTI) 以及高分辨率解剖扫描。此外，所有参与者都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。我将接受转化研究以及 DTI 和结构解剖分析方法方面的重要培训。了解小脑前额叶网络与精神病发展之间的关系对于全面了解精神分裂症的病因至关重要。这样做将有助于解释 小脑在精神分裂症中的作用及其病因学。此外，这可能有利于 制定有针对性的干预措施，可以改善高危人群的病程和治疗结果。