权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Early Onset AD Consortium - the LEAD Study (LEADS)

早发性 AD 联盟 - LEAD 研究 (LEADS)

基本信息

批准号：
10461783
负责人：
LIANA G APOSTOLOVA
金额：
$ 1390.41万
依托单位：
INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-30 至 2024-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10461783
关键词：
Age Alzheimer&apos s Disease Alzheimer&apos s disease patient Alzheimer&apos s disease risk American Amyloid Amyloid beta-Protein Apolipoprotein E Atrophic Biological Markers Blood Brain Cerebrospinal Fluid Characteristics Clinical Clinical Research Clinical Trials Clinical assessments Cognitive Collection DNA Data Dementia Diagnosis Disease Disease Progression Early Onset Alzheimer Disease Elderly Episodic memory Exclusion Future Genes Genetic Genotype Goals Heritability Image Impairment Individual Inflammation Inherited Language Late Onset Alzheimer Disease Lead Lipids Liquid substance Magnetic Resonance Imaging Measures Medial Memory Methods Mutation National Institute on Alcohol Abuse and Alcoholism Nerve Degeneration Observational Study Outcome Outcome Measure PET positivity Participant Pathogenicity Pathway interactions Patients Performance Peripheral Blood Mononuclear Cell Persons Phenotype Plasma Population Positron-Emission Tomography Primary Progressive Aphasia Probability Procedures Psychometrics RNA Research Sampling Serum Signal Transduction Site Symptoms Syndrome Testing Therapeutic Trials Thinking Time Variant Visuospatial Work age related apolipoprotein E-4 autosomal dominant Alzheimer&apos s disease biomarker development cerebral atrophy clinical outcome measures clinical phenotype cognitive function cohort comorbidity design early onset genetic risk factor gray matter imaging biomarker innovation machine learning algorithm marginalization meetings neuroimaging next generation sequencing novel patient population presenilin-1 recruit risk variant serial imaging tau Proteins treatment trial unethical

项目摘要

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) 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). Patients will be assessed at three time points – baseline (both EOAD and controls), 12 months (EOAD all measures; controls – clinical and cognitive measures only) and 24 months (EOAD, all measures except PET). Methods will be harmonized with ADNI and DIAN. We will comprehensively characterize cognitive, imaging and biofluid changes over time in EOAD, and compare to a matched sample of LOAD participants identified in ADNI. We will employ machine learning algorithms to develop sensitive clinical and imaging measures of EOAD progression. 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%)的Eoad患者没有 APP或PSEN1/2有已知突变，只有~50%是APOE4携带者。与晚发性AD(负荷)不同， 30%-的EoAD有非遗忘性表现，导致漏诊或延误。尽管高度重视 Eoad患者积极进取，几乎没有并发症，通常被排除在大规模观察之外。生物标记物研究(如ADNI和DIAN)和治疗试验，由于他们年龄小，非遗忘症缺陷，或不存在已知的致病突变。此外，研究表明，Eoad的遗传率很高没有已知的突变或APOE4，这意味着这个群体可能会因新的遗传风险而丰富各种因素。新出现的淀粉样蛋白和tau蛋白的生物标志物在这一人群中还没有被系统地描述出来。临床和神经影像测量在LOAD中使用可能对基线缺陷和疾病不敏感 Eoad的进展，主要涉及非记忆认知域和后皮质神经退行性变。为了填补AD研究的这一空白，我们计划招募并纵向跟踪400个淀粉样蛋白PET- 符合NIA-AA标准的阳性Eoad受试者因AD或可能的AD痴呆(包括原发)而导致的MCI 健忘症、执行障碍、语言和视觉空间陈述)和100名年龄匹配的对照组。纵向早发性阿尔茨海默病研究(LEADS)的参与者将接受临床评估、心理测试、MRI、淀粉样蛋白([18F]Florbetaben)和tau([18F]AV1451)PET、脑脊液和采集DNA、RNA、血浆、血清和外周血单核细胞(PBMC)。患者将在三个时间点进行评估-基线(加载和对照)、12个月(加载全部测量；对照-仅临床和认知测量)和24个月(Eoad，除PET外的所有测量)。方法将与ADNI和DIAN协调。我们将全面描述认知、成像和 EOAD中生物流体随时间的变化，并与ADNI中确定的负荷参与者的匹配样本进行比较。我们将使用机器学习算法来开发Eoad的敏感临床和成像指标进步。一个探索性的目标是应用下一代测序来评估新的遗传风险因素治疗疾病。该研究还将建立Eoad研究站点网络，并为启动在这一人群中进行临床试验。