Identifying the clinicopathologic basis of dementia-related psychosis

描述(申请人提供)：精神病经常作为神经退行性疾病的一种症状出现，但这一现象尚未得到充分的研究和广泛的误解。它通常是疾病的第一个迹象，这与临床医生识别疾病中最早受影响的大脑网络的能力直接相关，从而预测潜在的神经病理。精神病也给医疗和社会服务带来了沉重的负担，并加剧了痴呆症患者、他们的家人和他们的社会网络现有的压力。该项目的总体目标是对现有的两个大型数据集执行二次分析，以 确定三种老年性疾病不同类型妄想和幻觉的临床现象学、神经解剖学和神经病理学基础：阿尔茨海默病(AD)、行为变异额颞叶痴呆(BvFTD)和路易体痴呆(DLB)。要分析的两个研究数据库是在加州大学旧金山分校的记忆和衰老中心通过NIH国家老龄研究所提供的资金收集的。首先，在尸检确认的172个病例的病理队列中，我们将确定不同类型的妄想和幻觉如何能够预测不同的潜在神经病理诊断。其次，在540名临床诊断为AD、bvFTD和DLB的患者中，现有的结构性MRI数据将使用基于体素的形态计量学进行量化，以确定与不同的精神症状相关的大脑区域。最后，功能互联互通 将对210名受试者的静息状态功能磁共振数据进行分析，以确定特定类型的精神病和特定大脑网络功能障碍之间的更微妙联系。首先，我们假设精神病的基础是参与评估情景线索的核心网络的功能障碍，该网络对现实产生错误的推断，这种功能障碍是由于旋转内侧前额叶皮质受损和连接中断的结果，在神经退行性疾病中很常见。其次，有一个独特的感官输入系统，在每种疾病中都受到独特的影响，这决定了精神病的亚型和内容。在bvFTD中，由于岛叶损伤和突起网络功能障碍而导致的内脏感觉输入错误，会导致奇怪的、身体集中的精神病。在AD中，由海马区损伤和记忆网络功能障碍引起的错误的情节和自传体记忆输入会导致非奇怪的偏执妄想症。在DLB中，由于枕叶损伤和视觉网络功能障碍而导致的错误的感觉视觉输入会导致误认妄想和视觉幻觉。因此，更准确的临床特征 对精神病症状的分析可以产生有关受影响的局灶性大脑网络的关键信息，这反过来将导致对这些疾病患者的更早、更准确的诊断。

DESCRIPTION (provided by applicant): Psychosis frequently occurs as a symptom of neurodegenerative disease, but this phenomenon is understudied and widely misunderstood. It can often be the first sign of disease, which has direct relevance to clinicians' ability to identiy the earliest brain networks affected in disease, and thus the ability to predict the underlying neuropathology. Psychosis also places a heavy burden on medical and social services, and exacerbates existing strain on dementia patients, their families, and their social networks. The overarching goal of this project is to perform secondary analysis of two large existing datasets to identify the clinical phenomenology, neuroanatomy, and neuropathology underlying different types of delusions and hallucinations in three diseases of aging: Alzheimer's disease (AD), behavioral variant frontotemporal dementia (bvFTD) and dementia with Lewy bodies (DLB). The two research databases to be analyzed were collected at the UCSF Memory and Aging Center through funding provided by the NIH National Institute of Aging. First, in an autopsy-confirmed pathology cohort of 172 cases, we will determine how distinct types of delusions and hallucinations are able to predict the different underlying neuropathological diagnoses. Second, in a larger cohort of 540 clinically diagnosed patients with AD, bvFTD and DLB, existing structural MRI data will be quantified using voxel-based morphometry in order to identify brain regions that are associated with distinct psychotic presentations. Finally, functional connectivity analysis will be conducted on resting state fMRI data from 210 subjects to identify more subtle links between specific types of psychosis and dysfunction in specific brain networks. First, we hypothesize that the basis for psychosis is the dysfunction of a core network involved in appraisal of situational cues that produces faulty inferences about reality, and that this dysfunction occurs as a result of rostromedial prefrontal cortex damage and disconnection, and is common across neurodegenerative diseases. Second, there is a distinct sensory input system that is uniquely affected in each disease, which dictates the subtype and content of the psychosis. In bvFTD, faulty visceral sensory input, resulting from insular damage and salience network dysfunction, leads to bizarre and body-focused psychosis. In AD, faulty episodic and autobiographical memory input, resulting from hippocampal damage and memory network dysfunction, leads to non-bizarre paranoid delusions. In DLB, faulty sensory visual input, resulting from occipitotemporal damage and visual network dysfunction, leads to misidentification delusions and visual hallucinations. Thus, more precise clinical characterization of psychotic symptoms can yield critical information about the focal brain network affected, which in turn will lead to earlier, more accurate diagnosis for patients with these diseases.