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

基本信息

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
项目类别：
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&apos s Disease Alzheimer&apos s disease diagnosis Alzheimer&apos 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

项目摘要

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.

该应用程序将研究者的神经影像专业知识与生物标志物的新知识相结合用于衰老病理学、先进计算方法和唐氏综合症临床转化研究。目标是培养一套独特的技能，用于促进候选人作为独立人士的职业生涯专注于唐氏综合症神经退行性变化的寿命发育认知神经科学家。与阿尔茨海默病 (AD) 相关的基因几乎存在于 40 岁之前患有唐氏综合症的所有个体中年，该人群终生患痴呆症的风险超过 90%。在 AD 诊断之前了解神经精神和病理性大脑变化至关重要，以便促进在不可逆的神经精神和病理性大脑变化发生之前进行干预。对于患有 DS 的患者来说，病理性大脑变化和痴呆症的诊断极具挑战性大脑和神经心理学的差异在整个生命周期中都存在，在这里我们提出了一种计算方法。神经科学框架，我们将利用传统的静息态功能 MRI、先进的 MRI 和多模态生物标志物数据可解开大脑和特定定量神经心理变化 DS 和 AD（在 DS 的背景下），我们将测试整个大脑的总体假设。连接性（即基于静息态功能 MRI 的连接组）和大脑微观结构（定量 MRI）代表原发性脑病理学和神经心理学结果之间的中间表型首先，我们将利用来自阿尔茨海默病生物标志物联盟——唐氏综合症的数据。 (ABC-DS) 来识别特定于 DS 的连接组范围签名，以及一组特定于然后，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，我们将研究它们之间的关系。连接组范围的特征和关键的神经心理学功能（包括记忆、社交）之间的关系最后，我们将招募一群患有 DS 和执行功能的新人群。收集补充的高级 MRI 研究（ABC-DS 中不可用）和液体生物标志物，以检查大脑与相比，微观结构特性可能对神经退行性变化更敏感传统 MRI 和 b) PET 成像的补充，该提案的结果将推动 a) 对 DS 和 AD 特异性病理性脑变化的机制理解以及如何重组此外，这些数据构成了后续研究的基础。 R01 将 ABC-DS 新兴纵向数据与先进的互补 MRI 和多模态相结合生物标志物。