Evaluating and Extending Our Hypothetical Model of Alzheimer's Biomarkers

评估和扩展我们的阿尔茨海默病生物标志物假设模型

• 批准号: 8580664
• 负责人: CLIFFORD R. JACK
• 金额: $ 55.97万
• 依托单位: MAYO CLINIC ROCHESTER
• 依托单位国家: 美国
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-06-01 至 2018-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8580664
• 关键词: Address; Age; Age-Years; Aging; Alzheimer' s Disease; Alzheimer' s disease model; Amyloid; Amyloidosis; Autopsy; Biological Markers; Blood Vessels; Brain; Categories; Cerebrospinal Fluid; Cerebrovascular Disorders; Clinic; Clinical; Cohort Studies; Counseling; County; Critiques; Data; Dementia; Development; Disease; Disease Progression; Disease model; Disputes; Enrollment; Epidemiology; Evaluation; Evolution; Functional Magnetic Resonance Imaging; Functional disorder; Goals; Grant; Image; Individual; Magnetic Resonance Imaging; Measurable; Measures; Minority; Modeling; Nerve Degeneration; Neuronal Injury; Participant; Pathogenesis; Pathology; Patients; Persons; Phase; Positron-Emission Tomography; Prevalence; Risk; Risk Factors; Sample Size; Sampling; Secondary Prevention; Study Section; Study Subject; Symptoms; Testing; Therapeutic Clinical Trial; Therapy Clinical Trials; Time; Validation; aged; amyloid imaging; base; cohort; design; falls; fluorodeoxyglucose positron emission tomography; follow-up; inclusion criteria; insight; mild cognitive impairment; novel diagnostics; population based; pre-clinical; prevention clinical trial; public health relevance; response; tau Proteins; trend; volunteer

DESCRIPTION (provided by applicant): A central insight gained from the current cycle of AG011378 is that in someone destined to develop Alzheimer's disease (AD) dementia, different biomarkers become abnormal in a sequential manner. Based on results from the current grant cycle, we proposed a biomarker-based disease model which posits that amyloid biomarkers become abnormal first, perhaps 15 years before the onset of overt clinical symptoms. Neuronal injury biomarkers become abnormal next, followed later by incident mild cognitive impairment (MCI). While we believe the model is largely correct, some in the field dispute this and therefore empiric evaluation is needed. This renewal will evaluate and extend our hypothetical biomarker model by following a large, population- based cohort of cognitively normal (CN) subjects studied with biomarkers for up to 10 years, and thus address major gaps in understanding disease progression. The central objective of this renewal is to understand how imaging biomarkers of AD pathophysiology (AD-P) change in the preclinical and early MCI phases of AD in relation to each other, and then to identify practical implications of sequential biomarker change. A notable strength of this renewal is our large - perhaps the largest in the world - existing cohort of CN subjects from an epidemiologically defined sample who have already undergone all imaging studies at baseline. Subjects for this renewal (n~1500) will be participants in the Mayo Clinic Study of Aging, an epidemiological sample of non- demented subjects in Olmsted County, MN. As outlined in the Introduction, we have significantly revised this A1 application in response to the study section critique. Aim 1. Establish cut-points for amyloid PET, TF-fMRI, FDG-PET, sMRI, CSF A¿42 and tau demarcating normal from abnormal. A major question in the field at present is how to appropriately define AD biomarker cut-points that separate normal from abnormal. Aim 2. Model validation: test the hypothesis that AD imaging biomarkers become abnormal in a specific temporal order. Our initial model was consistent with the amyloid cascade hypothesis in that amyloid biomarkers become abnormal first followed by FDG-PET and MR. However, this has been challenged. We will formally test this hypothesis using three different approaches and will extend and refine our existing model of biomarker evolution based on these findings. These results could alter current notions of AD pathogenesis. Aim 3. To integrate AD-P biomarker evidence with other predictors to enhance risk prediction for incident MCI. This will provide practical guidance for using AD biomarkers for clinical counseling. Aim 4. To provide practical guidance for using AD biomarkers in secondary prevention clinical trials.

描述（由申请人提供）：从AG 011378的当前周期中获得的核心见解是，在注定发展阿尔茨海默病（AD）痴呆的人中，不同的生物标志物以顺序方式变得异常。基于当前资助周期的结果，我们提出了一个基于生物标志物的疾病模型，该模型假定淀粉样蛋白生物标志物首先变得异常，可能在明显临床症状出现之前15年。神经元损伤生物标志物接下来变得异常，随后发生轻度认知障碍（MCI）。虽然我们认为该模型在很大程度上是正确的，但该领域的一些人对此提出异议，因此需要进行经验评估。 本次更新将通过跟踪一个大型的、基于人群的认知正常（CN）受试者队列，对我们假设的生物标志物模型进行长达10年的评估和扩展，从而解决理解疾病进展的主要差距。此次更新的中心目标是了解AD病理生理学（AD-P）的成像生物标志物在AD的临床前和早期MCI阶段如何相互变化，然后确定连续生物标志物变化的实际意义。该更新的一个显著优势是我们的大规模（可能是世界上最大的）现有CN受试者队列，这些受试者来自流行病学定义的样本，在基线时已经接受了所有成像研究。本次更新的受试者（n~1500）将是马约诊所老龄化研究的参与者，该研究是明尼苏达州奥姆斯特德县非痴呆受试者的流行病学样本。正如引言中所概述的，我们已经对A1应用程序进行了重大修改，以回应研究部分的批评。 目标1.建立淀粉样蛋白PET、TF-fMRI、FDG-PET、sMRI、CSF A ² 42和tau的分界点，区分正常与异常。目前该领域的一个主要问题是如何适当地定义区分正常与异常的AD生物标志物分界点。 目标2.模型验证：检验AD成像生物标志物在特定时间顺序中变得异常的假设。我们最初的模型与淀粉样蛋白级联假说一致，即淀粉样蛋白生物标志物首先变得异常，然后是FDG-PET和MR。我们将使用三种不同的方法正式测试这一假设，并将根据这些发现扩展和完善我们现有的生物标志物进化模型。这些结果可能会改变目前的AD发病机制的概念。 目标3.将AD-P生物标志物证据与其他预测因子相结合，以增强对MCI事件的风险预测。这将为使用AD生物标志物进行临床咨询提供实际指导。 目标4。为AD生物标志物在二级预防临床试验中的应用提供实践指导。