Neuromarkers of age-related cognitive decline

描述（由申请人提供）：本研究的目的是研究基于DTI纤维追踪模型的新型神经影像学标志物、血管疾病和炎症的遗传多态性与健康个体中年龄相关的认知衰退之间的关系。最近的研究，包括我们实验室的数据，表明皮质下白色物质的完整性，如通过扩散张量成像（DTI）和皮质下高信号结构MRI测量是与年龄相关的认知差异的重要相关性。皮质脑体积的变化也可以解释老年人认知功能的一些差异，然而我们的数据表明，皮质下白色物质的改变与认知状态更密切相关。此外，研究表明，老年人的白色物质改变是可遗传的，暗示遗传因素在轻度缺血性变化和相关炎症的发展中的作用。在这个修订的申请中，我们提供了令人信服的新的试点数据，证明了遗传多态性对血管损伤在成像和认知指标方面的作用。我们还提供了我们最近工作的新数据，证明了我们基于量化纤维跟踪模型的新型DTI指标的灵敏度，以解释认知老化的差异。这些新的指标使我们能够检查量化的纤维长度变化对认知功能的影响。在本研究中，我们将扩展这些初步研究，并检查DTI和结构MRI之间的关系，与微血管疾病（血管紧张素原，帕氧磷酶）和相关CMS炎症（C-反应蛋白，IL- 6，TNF-α）相关的遗传多态性，以及健康老年人的认知状态。这项研究将利用现有的数据库，其中包含1,000多名年龄在31-80岁之间的人的遗传和神经认知数据（n = 200/组）。神经影像学数据目前可用于200这些人，我们将招募额外的120人之间的51-80岁，以补充年龄较大的频谱，并获得新的纤维跟踪地图的DTI数据。将纵向跟踪新招募的个体，以检查遗传风险因素背景下白色物质和认知异常的演变和进展。将进行组比较和潜变量建模，以检查神经影像学指标，遗传多态性和老年健康成人认知功能差异之间的关系。本研究将是第一个整合这些方法来研究模型的年龄相关的认知能力下降牵连皮层下白色的问题。这些结果将为我们理解认知老化提供重要信息。

DESCRIPTION (provided by applicant): The purpose of the present study is to investigate relationships between novel neuroimaging markers based on DTI fiber tracking models, genetic polymorphisms of vascular disease and inflammation, and age-related cognitive decline in healthy individuals. Recent studies, including data from our lab, indicate that the integrity of the subcortical white matter as measured by diffusion tensor imaging (DTI) and subcortical hyperintensities on structural MRI are important correlates of age-related cognitive differences. Cortical brain volume changes also account for some variance in cognitive function among the elderly, however our data suggest that alterations in the subcortical white matter more strongly correlate with cognitive status. In addition, studies have demonstrated that white matter alterations in the elderly are heritable, implicating the role of genetic factors in the development of mild ischemic changes and associated inflammation. In this revised application we provide compelling new pilot data demonstrating the role of genetic polymorphisms for vascular injury on both imaging and cognitive indices. We also provide new data from our recent work demonstrating the sensitivity of our novel DTI metrics based on quantified fiber tracking models to explain variance in cognitive aging. These novel metrics allow us to examine the impact of changes in quantified fiber lengths on cognitive function. In the present study we will extend these preliminary studies and examine relationships between DTI and structural MRI, genetic polymorphisms associated with microvascular disease (angiotensinogen, paroxonase) and related CMS inflammation (C-reactive protein, IL- 6, TNF-a), and cognitive status in the healthy elderly. The study will capitalize on an existing database containing genetic and neurocognitive data on more than 1,000 individuals stratified in five groups from age 31-80 (n = 200/group). Neuroimaging data is currently available for 200 of these individuals and we will recruit an additional 120 individuals between the ages of 51-80 to supplement the older age spectrum and obtain novel fiber tracking maps from the DTI data. Newly recruited individuals will be followed longitudinally to examine the evolution and progression of white matter and cognitive abnormalities in the context of genetic risk factors. Group comparisons and latent variable modeling will be conducted to examine relationships between the neuroimaging indices, genetic polymorphisms, and differences in cognitive function in older healthy adults. The present study will be the first to integrate these approaches to examine a model of age-related cognitive decline implicating the subcortical white matter. The results will significantly inform our understanding of cognitive aging.