Early Onset AD Consortium - the LEAD Study (LEADS)

项目摘要 虽然阿尔茨海默病（AD）的风险随着年龄的增长而增加，但大约5%的AD患者 在65岁之前出现症状（约28万美国人）。绝大多数（90%-95%）EOAD患者没有 在APP或PSEN 1/2中有已知的突变，只有约50%是APOE 4携带者。与晚发型AD（LOAD）不同， 30-64%的EOAD具有非遗忘性表现，导致漏诊或延迟诊断。尽管高度 有动机且合并症很少，EOAD患者通常被排除在大规模观察性研究之外。 生物标志物研究（例如ADNI和DIAN）和治疗试验，由于其年龄较小，非遗忘缺陷，或 不存在已知的致病突变。此外，研究表明，在没有EOAD的情况下， 已知的突变或APOE 4，这意味着该人群可能富含新的遗传风险因素。 淀粉样蛋白和tau蛋白的新兴生物标志物尚未在该人群中进行系统表征。临床 LOAD中采用的神经影像学测量可能对基线缺陷和疾病进展不敏感 在EOAD中，主要涉及非记忆认知域和后皮质神经变性。 为了填补AD研究中的这一空白，我们计划招募并纵向随访400例淀粉样PET阳性的EOAD患者 由于AD或可能的AD痴呆（包括原发性遗忘， 执行障碍、语言和视觉空间呈现），200例符合临床标准的受试者， 淀粉样蛋白PET（EOnonAD）和100名年龄匹配的对照。参与者在纵向早发 阿尔茨海默病研究（LEADS）将进行临床评估，心理测试，MRI，淀粉样蛋白 （[18 F]Florbetaben）和tau（[18 F] AV 1451）PET、CSF和血样采集，用于DNA、RNA、血浆、血清 和外周血单核细胞（PBMC）。EOnonAD参与者和对照组也将接受[18]FDG 彼前每年对所有参与者进行随访（对照组最长24个月;受损参与者最长48个月）。 方法将与ADNI和DIAN协调。我们将全面描述认知，成像和 EOAD和EOnonAD中生物流体随时间的变化，并与年龄匹配的对照组以及性别和分期进行比较。 匹配ADNI中识别的LOAD参与者。我们将采用机器学习算法来开发敏感的 EOAD进展的临床和影像学指标。此外，我们将描述人口统计学，临床， EOnonAD病例的神经影像学和液体生物标志物测量，以探索认知功能障碍的可能病因。 损伤一个探索性的目标将应用下一代测序来评估新的遗传风险因素， 疾病这项研究还将建立一个EOAD研究网站网络，并为推出 在这个人群中进行临床试验。

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.