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病（AD）痴呆可能依赖于尽早干预 AD病理级联反应中的一个点，假设是淀粉样蛋白β（Aβ）的积累。标准 用于Aβ检测的PET方法基于广泛的皮质Aβ负荷，并且通常无法捕获早期Aβ。 拟议的K 01项目将开发优化的空间范围措施，以便能够可靠地识别 在淀粉样变的早期阶段比以前研究的个体。这种方法应该提供更多的 用于研究早期A β在AD病理级联中的作用的A β定位的动态生物标志物， 在未来的预防试验中作为一个更敏感的结果的潜力。目标1将使用纵向数据 从来自哈佛老化脑研究（HABS）的临床正常（CN）个体中，1）开发优化的 空间范围度量基于对不同可能方法如何 计算模拟噪声的空间响应范围; 2）验证最优模型的灵敏度和特异性 空间范围方法（EXT），以预测未来3-11年的A130累积，以及3）在一个 AHEAD 3-45研究中标准PET屏幕的独立样本未能评估对齐 血浆Aβ+和EXT+之间的关系，以检测最早的Aβ沉积。目标2将使用EXT来评估 使用血浆生物标志物（ptau 217）和flortaucipir-PET检测tau的最早变化，并评估EXT是否可能 与标准皮质Aβ-PET相比， 接近。目的3将评价是否改进了EXT最早期A β沉积物的定量 允许更灵敏地检测与新兴疾病相关的长期和即时认知变化 一个小女孩。这些发现将有助于为未来的预防试验提供一个框架，以便在疾病早期进行干预 比以前尝试过的更好。此外，EXT方法还将开辟广泛的 潜在的未来方向，以研究新出现的Aβ如何与AD发病机制中的其他重要因素（即， 炎症、突触功能）建立独立的研究项目。帮助米歇尔·法雷尔医生 为了实现这些目标，一个来自哈佛医学院的多学科指导小组已经成立 社区补充PET物理学和药代动力学，血浆生物标志物， 先进的统计分析和临床试验Reisa Sperling博士将担任主要导师， 研究和职业发展，并提供临床试验设计和实施方面的培训， 计划研究的转化潜力。基思约翰逊博士和朱莉普莱斯博士将担任共同导师 提供PET研究方面的全面培训。导师团队将通过两项研究来完善 顾问（Rob Rissman博士：血浆生物标志物，Brian Healy博士：统计学）和两位贡献者（J. Alex博士 Becker：PET模拟; Kathryn Papp博士：日常数字认知评估）。这种全面的训练 该计划将促进法雷尔博士的研究和成长为一个独立的临床转化科学家。