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:
- 金额:$ 1390.41万
- 依托单位:
- 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:
- 关键词:AgeAlzheimer&aposs DiseaseAlzheimer&aposs disease patientAlzheimer&aposs disease riskAmericanAmyloidAmyloid beta-ProteinApolipoprotein EAtrophicBiological MarkersBloodBrainCerebrospinal FluidCharacteristicsClinicalClinical ResearchClinical TrialsClinical assessmentsCognitiveCollectionDNADataDementiaDiagnosisDiseaseDisease ProgressionEarly Onset Alzheimer DiseaseElderlyEpisodic memoryExclusionFutureGenesGeneticGenotypeGoalsHeritabilityImageImpairmentIndividualInflammationInheritedLanguageLate Onset Alzheimer DiseaseLeadLipidsLiquid substanceMagnetic Resonance ImagingMeasuresMedialMemoryMethodsMutationNational Institute on Alcohol Abuse and AlcoholismNerve DegenerationObservational StudyOutcomeOutcome MeasurePET positivityParticipantPathogenicityPathway interactionsPatientsPerformancePeripheral Blood Mononuclear CellPersonsPhenotypePlasmaPopulationPositron-Emission TomographyPrimary Progressive AphasiaProbabilityProceduresPsychometricsRNAResearchSamplingSerumSignal TransductionSiteSymptomsSyndromeTestingTherapeutic TrialsThinkingTimeVariantVisuospatialWorkage relatedapolipoprotein E-4autosomal dominant Alzheimer&aposs diseasebiomarker developmentcerebral atrophyclinical outcome measuresclinical phenotypecognitive functioncohortcomorbiditydesignearly onsetgenetic risk factorgray matterimaging biomarkerinnovationmachine learning algorithmmarginalizationmeetingsneuroimagingnext generation sequencingnovelpatient populationpresenilin-1recruitrisk variantserial imagingtau Proteinstreatment trialunethical
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.
项目概要
虽然患阿尔茨海默病 (AD) 的风险随着年龄的增长而增加,但大约 5% 的 AD 患者
65 岁之前出现症状(约 280,000 名美国人)。绝大多数(90%-95%)的 EOAD 患者没有
APP 或 PSEN1/2 存在已知突变,并且只有约 50% 是 APOE4 携带者。与迟发性 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。尽管被高度
EOAD 患者有积极性且几乎没有合并症,因此通常被排除在大规模观察之外
由于年龄小、非记忆删除,因此进行生物标志物研究(例如 ADNI 和 DIAN)和治疗试验
缺陷,或缺乏已知的致病突变。此外,研究表明 EOAD 具有高遗传力
不存在已知突变或 APOE4,表明该人群可能因新的遗传风险而丰富
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。
LOAD 中采用的临床和神经影像学测量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
神经变性。为了填补 AD 研究的这一空白,我们计划招募并纵向跟踪 400 名淀粉样蛋白 PET-
EOAD 阳性受试者,符合因 AD 或可能的 AD 痴呆(包括原发性痴呆)导致的 MCI 的 NIA-AA 标准
记忆删除、执行障碍、语言和视觉空间表现)和 100 名年龄匹配的对照。
纵向早发性阿尔茨海默病研究 (LEADS) 的参与者将接受临床研究
评估、心理测试、MRI、淀粉样蛋白 ([18F]Florbetaben) 和 tau ([18F]AV1451) PET、CSF 和
抽血用于收集 DNA、RNA、血浆、血清和外周血单核细胞 (PBMC)。
将在三个时间点对患者进行评估——基线(EOAD 和对照)、12 个月(EOAD 所有
措施;对照 – 仅临床和认知测量)和 24 个月(EOAD,除 PET 之外的所有测量)。
方法将与 ADNI 和 DIAN 保持一致。我们将全面表征认知、成像和
EOAD 中的生物流体随时间变化,并与 ADNI 中确定的 LOAD 参与者的匹配样本进行比较。
我们将采用机器学习算法来开发 EOAD 的敏感临床和影像测量
进展。探索性目标将应用下一代测序来评估新的遗传风险因素
为了疾病。该研究还将建立一个 EOAD 研究地点网络,并为启动
对该人群进行的临床试验。
项目成果
期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Atypical Alzheimer Disease Variants.
- DOI:10.1212/con.0000000000001082
- 发表时间:2022-06-01
- 期刊:
- 影响因子:0
- 作者:Polsinelli, Angelina J;Apostolova, Liana G
- 通讯作者:Apostolova, Liana G
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LIANA G APOSTOLOVA其他文献
LIANA G APOSTOLOVA的其他文献
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{{ truncateString('LIANA G APOSTOLOVA', 18)}}的其他基金
Leveraging Neuroimaging Biomarkers to Understand the Role of Social Networks in Alzheimer's Disease
利用神经影像生物标志物了解社交网络在阿尔茨海默病中的作用
- 批准号:
10426092 - 财政年份:2018
- 资助金额:
$ 1390.41万 - 项目类别:
Leveraging Neuroimaging Biomarkers to Understand the Role of Social Networks in Alzheimer's Disease
利用神经影像生物标志物了解社交网络在阿尔茨海默病中的作用
- 批准号:
10180831 - 财政年份:2018
- 资助金额:
$ 1390.41万 - 项目类别:
Early Onset AD Consortium - the LEAD Study (LEADS)
早发性 AD 联盟 - LEAD 研究 (LEADS)
- 批准号:
10219685 - 财政年份:2018
- 资助金额:
$ 1390.41万 - 项目类别:
Early Onset AD Consortium - the LEAD Study (LEADS)
早发性 AD 联盟 - LEAD 研究 (LEADS)
- 批准号:
9788208 - 财政年份:2018
- 资助金额:
$ 1390.41万 - 项目类别:
Early Onset AD Consortium - the LEAD Study (LEADS)
早发性 AD 联盟 - LEAD 研究 (LEADS)
- 批准号:
9912388 - 财政年份:2018
- 资助金额:
$ 1390.41万 - 项目类别:
Leveraging Neuroimaging Biomarkers to Understand the Role of Social Networks in Alzheimer's Disease
利用神经影像生物标志物了解社交网络在阿尔茨海默病中的作用
- 批准号:
9593940 - 财政年份:2018
- 资助金额:
$ 1390.41万 - 项目类别:














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