Evaluating and Extending Our Hypothetical Model of Alzheimer's Biomarkers

描述(申请人提供)：从AG011378的当前周期中获得的一个核心见解是，在注定要发展为阿尔茨海默病(AD)痴呆症的人中，不同的生物标记物会以连续的方式变得异常。基于当前赠款周期的结果，我们提出了一个基于生物标记物的疾病模型，该模型假设淀粉样蛋白生物标记物首先变得异常，可能在临床症状出现前15年出现。其次是神经元损伤生物标志物的异常，其次是偶发性轻度认知障碍(MCI)。尽管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了异议，因此需要进行经验评估。这次更新将评估和扩展我们的假想生物标记物模型，跟踪使用生物标记物研究的大量基于人群的认知正常(CN)受试者长达10年，从而解决在理解疾病进展方面的主要差距。这一更新的中心目标是了解AD病理生理学成像生物标记物(AD-P)在AD临床前和早期MCI阶段的相互关系，然后确定连续生物标记物变化的实际意义。这一更新的一个显著优势是我们现有的大量CN受试者队列，这些受试者来自流行病学定义的样本，他们已经在基线水平上接受了所有的影像研究。此次更新的受试者(n~1500人)将是梅奥诊所老龄化研究的参与者，这是明尼苏达州奥姆斯特德县的非痴呆受试者的流行病学样本。正如导言中所概述的，我们已针对研究部分的批评对此A1应用程序进行了重大修订。目的1.建立淀粉样蛋白PET、Tf-fMRI、FDG-PET、sMRI、CSFA？42和tau的分界点。目前该领域的一个主要问题是如何恰当地确定区分正常和异常的AD生物标志物切点。目的2.模型验证：检验AD成像生物标志物在特定时间顺序异常的假设。我们最初的模型与淀粉样级联假说是一致的，因为淀粉样生物标记物首先变得异常，然后是FDG-PET和MR，然而，这一点受到了挑战。我们将使用三种不同的方法正式测试这一假设，并将基于这些发现扩展和完善我们现有的生物标记物进化模型。这些结果可能会改变目前对AD发病机制的看法。目的3.将AD-P生物标记物证据与其他预测因素相结合，以加强对MCI事件的风险预测。这将为临床咨询中使用AD生物标志物提供实用指导。目的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。

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.