Early Onset AD Consortium - the LEAD Study (LEADS)

早发性 AD 联盟 - LEAD 研究 (LEADS)

• 批准号: 10219685
• 负责人: LIANA G APOSTOLOVA
• 金额: $ 107.21万
• 依托单位: INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-30 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10219685
• 关键词: Administrative Supplement; Age; Alzheimer' s Disease; Alzheimer' s disease patient; Alzheimer' s disease risk; American; Amyloid; Amyloid beta-Protein; Atrophic; Autopsy; Biological Markers; Blood; Brain; Cerebrospinal Fluid; Characteristics; Clinical; Clinical Trials; Clinical assessments; Cognitive; Collection; DNA; Data; Diagnosis; Disease; Disease Progression; Elderly; Episodic memory; Etiology; Funding; Future; Genes; Genetic; Genotype; Goals; Heritability; Image; Impaired cognition; Impairment; Individual; Inflammation; Inherited; Italy; Language; Late Onset Alzheimer Disease; Life; Light; Lipids; Liquid substance; Magnetic Resonance Imaging; Measures; Medial; Memory; Methods; Mutation; Nerve Degeneration; Neurodegenerative Disorders; Observational Study; Outcome; Outcome Measure; Participant; Pathogenicity; Pathology; Pathway interactions; Patients; Pattern; Performance; Peripheral Blood Mononuclear Cell; Plasma; Population; Positron-Emission Tomography; Presenile Alzheimer Dementia; Psychometrics; RNA; Research; Signal Transduction; Site; Suggestion; Symptoms; Testing; Therapeutic Trials; Thinking; Time; Visuospatial; Work; apolipoprotein E-4; autosomal dominant Alzheimer' s disease; biomarker development; brain tissue; clinical biomarkers; clinical outcome measures; clinical phenotype; cognitive function; cohort; comorbidity; design; fluorodeoxyglucose; fluorodeoxyglucose positron emission tomography; genetic risk factor; gray matter; imaging biomarker; machine learning algorithm; meetings; neurofilament; neuroimaging; next generation sequencing; novel; patient population; predictive modeling; presenilin-1; recruit; serial imaging; sex; tau Proteins; treatment trial

Project Summary While the risk of Alzheimer’s disease (AD) increases with advancing age, approximately 5% of AD patients develop symptoms before age 65 (~280,000 Americans). The vast majority (90%-95%) of EOAD patients do not have a known mutation in APP or PSEN1/2, and only ~50% are APOE4 carriers. Unlike late-onset AD (LOAD), 30-64% of EOAD have non-amnestic presentations, leading to missed or delayed diagnosis. Despite being highly motivated and having few comorbidities, EOAD patients are commonly excluded from large scale observational biomarker studies (e.g. ADNI and DIAN) and therapeutic trials due to their young age, non- amnestic deficits, or absence of known pathogenic mutations. Furthermore, studies suggest high heritability in EOAD in the absence of known mutations or APOE4, signifying that this population may be enriched for novel genetic risk factors. Emerging biomarkers of amyloid and tau have not been systematically characterized in this population. Clinical and neuroimaging measures employed in LOAD may be insensitive to baseline deficits and disease progression in EOAD, which predominantly involve non-memory cognitive domains and posterior cortical neurodegeneration. To fill this gap in AD research, we plan to recruit and longitudinally follow 400 amyloid PET-positive EOAD subjects meeting NIA-AA criteria for MCI due to AD or probable AD dementia (including primary amnestic, dysexecutive, language and visuospatial presentations), 200 subjects meeting clinical criteria with negative amyloid PET (EOnonAD) and 100 age-matched controls. Participants in the Longitudinal Early-onset Alzheimer’s Disease Study (LEADS) will undergo clinical assessments, psychometric testing, MRI, amyloid ([18F]Florbetaben) and tau ([18F]AV1451) PET, CSF and blood draw for collection of DNA, RNA, plasma, serum and peripheral blood mononuclear cells (PBMC). EOnonAD participants and controls will also receive [18]FDG PET. All participants are followed annually (controls up to 24 months; impaired participants up to 48 months). Methods will be harmonized with ADNI and DIAN. We will comprehensively characterize cognitive, imaging and biofluid changes over time in EOAD and EOnonAD and compare to age-matched controls and sex and stage- matched LOAD participants identified in ADNI. We will employ machine learning algorithms to develop sensitive clinical and imaging measures of EOAD progression. Additionally, we will characterize demographic, clinical, neuroimaging, and fluid biomarker measures in EOnonAD cases to explore the possible etiologies of cognitive impairment. An exploratory aim will apply next generation sequencing to assess for novel genetic risk factors for disease. The study will also establish a network of EOAD research sites and set the stage for the launch of clinical trials in this population.

项目摘要 尽管随着年龄的增长，阿尔茨海默氏病（AD）的风险增加了 在65岁之前开发符号（约28万美国人）。绝大多数（90％-95％）的EOAD患者没有 在APP或PSEN1/2中具有已知的突变，APOE4载体只有〜50％。与晚发广告（负载）不同， 30-64％的EOAD具有非静态演示，导致诊断遗漏或延迟。尽管很高 EOAD患者的动机和几乎没有合并症，通常被排除在大规模观察中 生物标志物研究（例如ADNI和DIAN）以及由于年龄，非际贫困性或 缺乏已知的致病突变。此外，研究表明在不存在的情况下，EOAD具有很高的遗传力 已知的突变或APOE4，表明该人群可能会富含新的遗传危险因素。 淀粉样蛋白和TAU的新兴生物标志物在该人群中尚未系统地表征。临床 在负载中采取的神经影像措施可能对基线防御和疾病进展不敏感 在EOAD中，主要涉及非记忆认知结构域和后皮质神经变性。 为了填补广告研究中的这一空白，我们计划招募并纵向跟随400个淀粉样蛋白宠物阳性EOAD 符合由于AD或有问题的AD痴呆而符合MCI NIA-AA标准的主题 DySexecectectectect，语言和视觉演示），200个受试者满足临床标准为负面 淀粉样蛋白宠物（EONONAD）和100个年龄匹配的对照。纵向早期的参与者 阿尔茨海默氏病研究（Leads）将接受临床评估，心理测试，MRI，淀粉样蛋白 （[18F] Florbetaben）和Tau（[18F] AV1451）PET，CSF和血液抽血，用于收集DNA，RNA，等离子体，串行 和外周血单核细胞（PBMC）。 EONONAD的参与者和控件也将获得[18] FDG 宠物。每年遵循所有参与者（最多24个月的对照；最多48个月的参与者受损）。 方法将与ADNI和DIAN协调。我们将全面地描述认知，成像和 在EOAD和EONONAD中，生物流体随着时间的流逝而变化，并与年龄匹配的对照，性别和阶段进行比较。 匹配的负载参与者在ADNI中确定。我们将采用机器学习算法来发展敏感的 EOAD进展的临床和成像测量。此外，我们将表征人口统计，临床， 神经影像学和流体生物标志物措施在Eononad病例中探索认知可能的病因 损害。探索性目标将应用下一代测序，以评估新的遗传风险因素 疾病。该研究还将建立一个EOAD研究站点网络，并为启动 该人群的临床试验。