Optimizing PET spatial extent measures to detect the earliest amyloid-beta and tau accumulation and associated cognitive decline in preclinical Alzheimer's disease

优化 PET 空间范围测量以检测临床前阿尔茨海默病中最早的淀粉样蛋白 β 和 tau 积累以及相关的认知能力下降

• 批准号: 10721474
• 负责人: Michelle Elizabeth Farrell
• 金额: $ 12.85万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2028-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10721474
• 关键词: Acceleration; Alzheimer disease prevention; Alzheimer' s Disease; Alzheimer’s disease biomarker; Amyloid beta-Protein; Amyloidosis; Binding; Biological Markers; Biometry; Clinical; Clinical Data; Clinical Trials; Clinical Trials Design; Cognition; Cognitive; Communities; Complement; Computing Methodologies; Data; Dementia; Deposition; Detection; Disease; Disease Progression; Drug Kinetics; Early Diagnosis; Evaluation; Exhibits; Future; Growth; Heterogeneity; Impaired cognition; Individual; Inflammation; Intervention; Investigation; Learning; Maps; Measures; Mentors; Mentorship; Methods; Neocortex; Nerve Degeneration; Noise; Outcome; Participant; Pathogenesis; Pathologic; Physics; Pittsburgh Compound-B; Plasma; Positron-Emission Tomography; Predisposition; Prevention trial; Price; Primary Prevention; Process; Proliferating; Research; Risk; Role; Sampling; Sensitivity and Specificity; Statistical Data Interpretation; Stereotyping; Symptoms; Testing; Training; Translational Research; abeta accumulation; abeta deposition; aging brain; career; clinical translation; cognitive change; cognitive testing; digital; experience; follow-up; glial activation; improved; in vivo; longitudinal positron emission tomography; medical schools; multidisciplinary; neocortical; novel; pre-clinical; predictive marker; prevent; primary endpoint; programs; radiotracer; screening; secondary endpoint; simulation; statistics; synaptic function; tau Proteins; tau aggregation; translational potential; translational scientist; β-amyloid burden

Successful prevention of Alzheimer’s disease (AD) dementia may rely on intervention at the earliest possible point in the AD pathological cascade, hypothesized to be the accumulation of amyloid-beta (Aβ). The standard PET approach for Aβ detection is based on widespread cortical Aβ burden and often fails to capture early Aβ. The proposed K01 project will develop optimized spatial extent measures that allow for robust identification of individuals in an earlier stage of amyloidosis than previously studied. This approach should provide a more dynamic biomarker of A localization for investigating early A‘s role in the AD pathological cascade and has the potential to serve as a more sensitive outcome in future prevention trials. Aim 1 will use longitudinal data from clinically normal (CN) individuals from the Harvard Aging Brain Study (HABS) to 1) develop an optimized spatial extent metric based on a scientifically rigorous investigation of how different possible methods for computing spatial extent respond to simulated noise, 2) validate the sensitivity and specificity of the optimal spatial extent approach (EXT) to predict future A accumulation over 3-11 years, and 3) implement EXT in an independent sample of standard PET- screen fails from the AHEAD 3-45 Study to assess the alignment between plasma Aβ+ and EXT+ for detecting the earliest Aβ deposits. Aim 2 will use EXT to evaluate the earliest changes in tau using plasma biomarkers (ptau217) and flortaucipir-PET and assess whether EXT may provide a better predictive marker of those at risk for tau proliferation than standard cortical Aβ-PET approaches. Aim 3 will evaluate whether the improved quantification of the earliest A deposits with EXT allows for more sensitive detection of long-term and immediate cognitive changes associated with emerging A. These findings will help provide a framework for future prevention trials to intervene earlier in the disease process than has previously been attempted. Furthermore, the EXT approach will open a wide range of potential future directions to study how emerging Aβ relates to other important factors in AD pathogenesis (i.e. inflammation, synaptic function) to establish an independent research program. To help Dr. Michelle Farrell achieve these aims, a multidisciplinary mentorship team has been assembled from the Harvard Medical School community to complement didactic coursework in PET physics and pharmacokinetics, plasma biomarkers, advanced statistical analysis, and clinical trials. Dr. Reisa Sperling will serve as the primary mentor overseeing research and career progress and providing training in clinical trial design and conduct to maximize the translational potential of the planned research. Dr. Keith Johnson and Dr. Julie Price will serve as co-mentors to provide comprehensive training in PET research. The mentorship team will be rounded out by two research advisors (Dr. Rob Rissman: plasma biomarkers, Dr. Brian Healy: statistics) and two contributors (Dr. J. Alex Becker: PET simulations; Dr. Kathryn Papp: daily digital cognitive assessments). This comprehensive training plan will facilitate Dr. Farrell’s research and growth into an independent clinical translational scientist.

成功预防阿尔茨海默氏病（AD）痴呆可能会尽早依靠干预 AD病理级联体的点，假设是淀粉样蛋白β（Aβ）的积累。标准 Aβ检测的PET方法是基于宽度的皮质Aβ伯恩，通常无法捕获早期的Aβ。 拟议的K01项目将制定优化的空间范围衡量标准，以允许对 在淀粉样变性的早期阶段比以前研究的个体。这种方法应该提供更多 A本地化的动态生物标志物，用于调查A在AD病理级联中的作用，并具有 在未来的预防试验中成为更敏感结果的潜力。 AIM 1将使用纵向数据 从哈佛大学衰老大脑研究（HAB）的临床正常（CN）个体到1） 基于科学严格研究的空间范围度量 计算空间范围响应模拟噪声，2）验证最佳的灵敏度和特异性 空间范围方法（EXT）预测3 - 11年以来未来的A积累，3） 标准PET屏幕的独立样本从前进的3-45研究中失败，以评估对齐方式 在血浆Aβ+和EXT+之间检测最早的Aβ沉积物之间。 AIM 2将使用EXT评估 使用等离子体生物标志物（PTAU217）和Flortaucipir-pet最早的TAU变化以及EXT是否可以 与标准皮质Aβ-PET相比 方法。 AIM 3将评估是否改进了最早的A沉积物的量化 允许对与新兴相关的长期和直接认知变化进行更敏感的检测 A。这些发现将有助于为将来的预防试验提供框架，以便在疾病中进行介绍 过程比以前尝试过的过程。此外，EXT方法将开放 研究Aβ如何与AD发病机理中其他重要因素相关的潜在未来方向（即 炎症，突触功能）建立独立的研究计划。帮助米歇尔·法雷尔博士 达到这些目标，哈佛医学院已经组装了一个多学科心态团队 完成宠物物理和药代动力学的教学课程，血浆生物标志物， 高级统计分析和临床试验。 Reisa Sperling博士将作为主要的心理监督 研究和职业进步，并提供临床试验设计的培训，并进行最大化 计划研究的转化潜力。 Keith Johnson博士和Julie Price博士将担任联席 提供宠物研究的全面培训。 Mentalship团队将通过两项研究来解决 顾问（Rob Rissman博士：等离子生物标志物，Brian Healy博士：统计）和两个贡献者（J. Alex博士 贝克尔：宠物模拟； Kathryn Papp博士：每日数字认知评估）。这种全面的培训 计划将促进Farrell博士的研究和成长成为一位独立的临床转化科学家。