Multi-cohort study of factors that influence Alzheimer's disease biomarker and dementia timing

影响阿尔茨海默病生物标志物和痴呆时间的因素的多队列研究

• 批准号: 10591179
• 负责人: TOBEY JAMES BETTHAUSER
• 金额: $ 77.04万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-01 至 2027-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10591179
• 关键词: Acceleration; Accounting; Affect; Age; Age of Onset; Aging; Alzheimer disease prevention; Alzheimer' s Disease; Alzheimer' s disease brain; Alzheimer' s disease pathology; Alzheimer' s disease patient; Alzheimer' s disease risk; Alzheimer’s disease biomarker; Amyloid; Amyloid beta-Protein; Amyloid deposition; Autopsy; Biological; Biological Aging; Biological Assay; Biological Factors; Biological Markers; Brain; Brain scan; Cerebrospinal Fluid; Clinic; Clinical; Clinical Trials; Clinical Trials Design; Cognition; Cohort Studies; Combined Modality Therapy; Data; Dementia; Demographic Factors; Detection; Disease; Disease Progression; Economic Conditions; Education; Environmental Risk Factor; Event; Genetic; Health; Health behavior; Heterogeneity; Image; Impaired cognition; Individual; Intervention; Investigation; Link; Liquid substance; Magnetic Resonance Imaging; Measurable; Measures; Mediator; Memory; Methods; Modeling; Modification; Monitor; Nerve Degeneration; Neurobehavioral Manifestations; Neurofibrillary Tangles; Onset of illness; Participant; Pathologic; Pathology; Patients; Persons; Phase; Positron-Emission Tomography; Prevention therapy; Proteins; Public Health; Registries; Research; Research Design; Risk; Risk Factors; Sampling; Shapes; Social Conditions; Source; Standardization; Stereotyping; Sum; Symptoms; Techniques; Testing; Thinking; Time; Translating; Translations; Universities; Variant; Vascular Diseases; Washington; Wisconsin; Work; apolipoprotein E-4; brain based; brain volume; cohort; comorbidity; cost; dementia risk; demographics; effective therapy; experience; improved; insight; neighborhood disadvantage; neuroimaging; neuroimaging marker; neuropathology; novel; novel strategies; optimal treatments; polygenic risk score; pre-clinical; prevent; recruit; response; risk prediction; sex; social factors; social health determinants; sociocultural determinant; sociodemographics; tau Proteins; timeline; tool; uptake

PROJECT SUMMARY/ABSTRACT Advances in imaging and fluid-based biomarkers of Alzheimer’s disease (AD) including amyloid (A), tau (T) and neurodegeneration (N), allow detection of underlying disease pathology decades before the onset of dementia. Despite over a decade of AD biomarker research, the field still lacks the ability to accurately predict if and when individuals with preclinical AD (those with biomarker detectable pathology in the absence of cognitive symptoms) will experience dementia. Identifying factors that slow or quicken this preclinical timeframe is needed to improve dementia risk prediction for preclinical AD patients and to inform optimal treatment windows for clinical trials aiming to slow or prevent cognitive decline and impairment. Until recently, studying these factors was precluded by observing different people for short periods of time that began studies in different disease stages with no way to identify when disease began for individual participants. Our team developed and validated new methods that provide individualized estimated amyloid onset age (EAOA) from amyloid biomarkers. EAOA can be used to rearrange biomarker and clinical observations along an AD-specific timeline (i.e., an Amyloid Clock) anchored to the start of preclinical AD. This project will apply this novel approach to existing data from that Washington University Knight ADRC, the Wisconsin Alzheimer’s Disease Research Center, the Wisconsin Registry for Alzheimer’s Prevention, the, the Mayo Clinic Study of Aging and the Alzheimer’s Disease Neuroimaging Initiative to investigate factors across cohorts that influence the timing and trajectories of AD biomarkers and dementia. This study was initiated based on our preliminary findings showing considerable differences between individuals and cohorts regarding 1) when amyloid onset occurs, 2) the time between amyloid onset and dementia onset, and 3) factors that affect AD biomarker and dementia trajectories in AD. In addition, studies from our center and others have begun to link AD pathology, change in brain volume, and changes in cognition to social determinants of health (SDoH) like neighborhood disadvantage. However, possible links between SDoH and the timing and trajectories of AD biomarkers and dementia are not well-understood. Our hypothesis is that observed individual and cohort differences in AD trajectories are due to a combination of demographic, environmental, sociocultural, and biologic factors, and study design and sample composition. We will test this overall hypothesis in three specific aims: 1) identify common factors across multiple cohorts that influence the timing and trajectories of ATN biomarkers; 2) identify common factors across multiple cohorts that affect the time from amyloid onset to dementia; and 3) explore inter-cohort differences in AD biomarker and dementia trajectories. This study will leverage existing data in several well-characterized studies to provide new insights into mechanisms that explain when preclinical AD begins and how long this preclinical phase lasts. This is expected to improve AD dementia risk prediction for individuals and identify optimal windows for disease modifying and prevention therapies.

项目概要/摘要 阿尔茨海默病 (AD) 的成像和基于液体的生物标志物的进展，包括淀粉样蛋白 (A)、tau (T) 和 神经退行性变（N），可以在痴呆症发作前数十年检测到潜在的疾病病理。 尽管AD生物标志物研究已有十多年，该领域仍然缺乏准确预测是否以及何时发生的能力 患有临床前 AD 的个体（在没有认知症状的情况下具有生物标志物可检测到的病理学的个体） 将会患上痴呆症。需要确定减缓或加快临床前时间的因素来改进 临床前 AD 患者的痴呆风险预测，并为临床试验提供最佳治疗窗口 旨在减缓或预防认知能力下降和损害。直到最近，研究这些因素仍被排除在外 通过短时间观察不同的人，在不同的疾病阶段开始研究，没有办法 确定个体参与者疾病开始的时间。我们的团队开发并验证了新方法 根据淀粉样蛋白生物标志物提供个性化的估计淀粉样蛋白发病年龄（EAOA）。 EOA 可用于 沿着 AD 特异性时间线（即淀粉样蛋白时钟）重新排列生物标志物和临床观察结果 到临床前 AD 的开始。该项目将把这种新颖的方法应用于华盛顿的现有数据 奈特大学 ADRC、威斯康星州阿尔茨海默病研究中心、威斯康星州登记处 阿尔茨海默病预防、梅奥诊所衰老研究和阿尔茨海默病神经影像计划 调查影响 AD 生物标志物和痴呆的时间和轨迹的因素。 这项研究是基于我们的初步结果显示个体之间存在巨大差异而发起的 以及关于 1) 淀粉样蛋白发作何时发生、2) 淀粉样蛋白发作和痴呆发作之间的时间的队列， 3) 影响 AD 生物标志物和 AD 痴呆轨迹的因素。此外，我们中心的研究和 其他人已经开始将 AD 病理学、脑容量变化和认知变化与社会决定因素联系起来 健康（SDoH），如邻里劣势。然而，SDoH 和时间安排之间可能存在联系 AD 生物标志物和痴呆症的轨迹尚不清楚。我们的假设是观察到的个体 AD 轨迹的群体差异是由于人口、环境、社会文化、 和生物因素，以及研究设计和样本组成。我们将分三步检验这个总体假设 具体目标：1）确定多个队列中影响 ATN 时间和轨迹的共同因素 生物标志物； 2) 确定多个队列中影响从淀粉样蛋白出现到出现时间的共同因素 失智; 3) 探索 AD 生物标志物和痴呆轨迹的队列间差异。这项研究将 利用几项特征明确的研究中的现有数据，为解释机制提供新的见解 临床前 AD 何时开始以及该临床前阶段持续多长时间。这有望改善 AD 痴呆症 对个人进行风险预测并确定疾病缓解和预防治疗的最佳窗口。