Toward a neuroscientific understanding of the interaction between Down syndrome and Alzheimer's disease pathology

对唐氏综合症和阿尔茨海默病病理学之间相互作用的神经科学理解

• 批准号: 10723666
• 负责人: JENNIFER L BRUNO
• 金额: $ 12.58万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2028-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10723666
• 关键词: Adult; Age; Aging; Alzheimer' s Disease; Alzheimer' s disease diagnosis; Alzheimer' s disease pathology; Alzheimer’s disease biomarker; Amyloid; Biological Markers; Brain; Brain Pathology; Brain region; Clinical; Cognitive; Computing Methodologies; Corpus striatum structure; Data; Dementia; Development; Diagnosis; Diffusion; Diffusion Magnetic Resonance Imaging; Dimensions; Disease Progression; Down Syndrome; Enrollment; Functional Magnetic Resonance Imaging; General Population; Goals; Hippocampus; Individual; Intervention; K-Series Research Career Programs; Knowledge; Light; Liquid substance; Longevity; Magnetic Resonance Imaging; Measures; Memory; Modeling; Nerve Degeneration; Neuropsychology; Neurosciences; Outcome; Pathologic; Pathology; Patients; Pattern; Persons; Phenotype; Plasma; Population; Positron-Emission Tomography; Preventive treatment; Property; Research Personnel; Rest; Spectrum Analysis; Structure; Symptoms; Testing; Training; Translational Research; Validation; Work; biophysical properties; brain tissue; career; clinical translation; cohort; connectome; connectome based predictive modeling; design; executive function; follow-up; in vivo; innovation; insight; lifetime risk; mild cognitive impairment; multimodal neuroimaging; multimodality; neurofilament; neuroimaging; neuropathology; neuropsychiatry; novel; predictive marker; skills; social cognition; tau Proteins; therapy development; vector

This application will combine the neuroimaging expertise of the investigator with new knowledge of biomarkers for aging pathology, advanced computational methods and Down syndrome clinical translational research. The goal is to produce a unique skill set which will be used to advance the candidate’s career as an independent lifespan developmental cognitive neuroscientist focusing on Down syndrome. Neurodegenerative changes associated with Alzheimer's disease (AD) are present in almost all individuals with Down syndrome by age 40 years, and the lifetime risk of developing dementia is more than 90% in this population. Understanding patterns of neuropsychiatric and pathological brain changes before AD diagnosis is critical in order to facilitate interventions prior to onset of irreversible neuropsychiatric and pathological brain changes. Yet charting of pathological brain changes and diagnosis of dementia is extremely challenging in individuals with DS who have brain and neuropsychological differences present through the lifespan. Here we propose a computational neuroscientific framework in which we will utilize conventional resting state functional MRI, advanced quantitative MRI and multimodal biomarker data to disentangle brain and neuropsychological changes specific to DS and AD (within the context of DS). Specifically, we will test the overarching hypothesis that whole brain connectivity (i.e. connectomes based on resting state functional MRI) and brain microstructure (quantitative MRI) represent intermediate phenotypes between primary brain pathologies and neuropsychological outcomes in DS and AD. First, we will leverage data from the Alzheimer's Biomarkers Consortium — Down Syndrome (ABC-DS) to identify connectome-wide signatures specific to DS, and a separate set of signatures specific to AD in the context of DS. Then, we will examine relationships between connectome-wide signatures and AD pathology within the amyloid, tau and neurodegeneration (ATN) framework. Next, we will examine relationships between connectome-wide signatures and critical neuropsychological functions including memory, social cognition, and executive function dimensionally. Finally, we will enroll a novel cohort of adults with DS and collect complementary advanced MRI studies (not available in ABC-DS) and fluid biomarkers, to examine brain microstructural properties which may be more a) sensitive to neurodegenerative changes when compared to traditional MRI and b) complementary to PET imaging. Together, the results of this proposal will advance a mechanistic understanding of DS- and AD-specific pathological brain changes and how reorganization of functional networks relate to neuropsychological changes. Further, these data form the basis for a follow-up R01 combining ABC-DS emerging longitudinal data with advanced complementary MRI and multimodal biomarkers.

这项应用将把研究人员的神经成像专业知识与生物标志物的新知识结合起来。 用于衰老病理、先进的计算方法和唐氏综合征的临床翻译研究。这个 目标是培养一套独特的技能，用来推动候选人作为独立人士的职业生涯 关注唐氏综合症的发展性认知神经学家。神经退行性改变 与阿尔茨海默病(AD)相关的基因在几乎所有40岁以前的唐氏综合症患者中都存在 在这一人群中，患痴呆症的终身风险超过90%。理解模式 在AD诊断之前对神经精神和病理脑部变化进行诊断是至关重要的，以便 发病前干预不可逆的神经精神和病理性脑部改变。然而，地图上的 对于患有DS的人来说，脑部病理改变和痴呆症的诊断极具挑战性 大脑和神经心理的差异存在于人的一生中。在这里，我们提出了一种计算方法 我们将利用常规静息状态功能磁共振成像的神经科学框架，高级 定量MRI和多模式生物标记物数据解开特定的脑和神经心理变化 到DS和AD(在DS的上下文中)。具体地说，我们将测试最重要的假设，整个大脑 连接性(即基于静息状态功能MRI的连接体)和脑微结构(定量 MRI)代表了初级脑病理和神经心理结果之间的中间表型 DS和AD。首先，我们将利用阿尔茨海默氏症生物标记物联合会的数据 (ABC-DS)来标识特定于DS的连接组范围的签名，以及一组特定于 广告在DS的背景下。然后，我们将检查连接组范围的签名和AD之间的关系 淀粉样蛋白、tau蛋白和神经变性(ATN)框架内的病理学。接下来，我们将考察关系 在整个连接体的特征和关键的神经心理功能之间 认知、执行功能维度上。最后，我们将招募一组患有DS和DS的成人 收集补充的高级MRI研究(ABC-DS中不提供)和液体生物标记物，以检查大脑 可能对神经退行性变化更敏感的微结构特性 B)对正电子发射计算机断层成像的补充。总而言之，这项提案的结果将推动 对DS和AD特异性病理性脑变化的机制理解以及如何重组 功能网络与神经心理变化有关。此外，这些数据构成了后续行动的基础 R01将ABC-DS新兴纵向数据与先进的互补MRI和多模式相结合 生物标志物。