Proteomic aging clock and brain structure, cognitive decline and the risk of Alzheimers Disease and related dementias

项目摘要 为了在临床诊断阿尔茨海默病（AD）和阿尔茨海默病之前评估生物衰老， 相关痴呆症（ADRD），我们将创建和验证蛋白质组衰老时钟（PAC）的前瞻性 基于人群的动脉粥样硬化风险社区（ARIC）队列。血液蛋白质组学方法 在20年的随访中，使用高度灵敏的SomaScan测定法收集了三次。PAC很容易 测量，可以准确地预测衰老过程，并与年龄相关的疾病， mortality.我们的主要目标是在无AD/ADRD参与者中创建和验证PAC，并测试是否 这些PAC可预测ADRD、认知能力下降和脑成像中可见的结构异常的风险， 实质丢失、白色高信号和小梗死。我们将评估两个已发布的PAC， 创建两个新的PAC：（1）PAC基于AD/ADRD患者的实际年龄， 混合年龄，和（2）PAC的基础上，在中年和晚年之间的蛋白质水平的变化（目标1）。此外，本发明还 我们将检验较高的PAC值（与实际年龄无关）和较高的个体内差异是否 从中年到晚年的PAC值与AD/ADRD的高风险相关（目标2）， 在认知功能和结构异常可见的大脑成像在晚年（目的3）。所有的 协会将按性别和种族分层。使用现有的ARIC数据将允许快速和成本- 有效地检验我们的假设。PAC的定量及其与AD/ADRD的关系的澄清是 对于理解衰老在这种疾病的病理生物学中的作用至关重要， 风险，并通过改变生活方式和抗衰老疗法有效地提供个性化的预防/治疗。

PROJECT SUMMARY To assess biological aging before clinical diagnosis of Alzheimer’s Disease (AD) and Alzheimer's-disease- related dementias (ADRD), we will create and validate proteomic aging clocks (PACs) in the prospective population-based Atherosclerosis Risk in the Community (ARIC) cohort. The blood proteomics measures have been collected three times over 20 years of follow-up using highly sensitive SomaScan assay. PACs are easily measured, can accurately predict the aging process, and are associated with age-related diseases and mortality. Our main objectives are to create and validate PACs in AD/ADRD-free participants and test whether these PACs predict risk of ADRD, cognitive decline and structural abnormalities visible in brain imaging such as parenchymal loss, white matter hyperintensities, and small infarcts. We will assess two published PACs and create two new PACs: (1) PAC based on the association with chronological age in AD/ADRD-free persons of mixed age, and (2) PAC based on the change in protein levels between midlife and late-life (Aim 1). Further, we will test whether higher PAC value (independent of chronological age) and higher intra-individual difference in the PAC values from midlife to late-life are associated with higher risk of AD/ADRD (Aim 2), and with decline in cognitive function and with structural abnormalities visible in brain imaging in late-life (Aim 3). All the associations will be stratified by sex and race. The use of existing ARIC data will allow for quick and cost- efficient testing of our hypotheses. The quantification of PAC and clarification of its relations with AD/ADRD are essential for understanding the role of aging in the pathobiology of this disease, identifying individuals at high risk, and efficiently delivering personalized prevention/treatment via lifestyle change and anti-aging therapies.