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纤维跟踪模型的新型神经成像标记物、血管疾病和炎症的遗传多态性以及健康个体与年龄相关的认知能力下降之间的关系。最近的研究，包括我们实验室的数据，表明通过扩散张量成像（DTI）测量的皮质下白质的完整性和结构MRI的皮质下高强度是年龄相关认知差异的重要相关因素。皮层脑容量的变化也可以解释老年人认知功能的一些差异，但我们的数据表明，皮层下白质的改变与认知状态的关系更强。此外，研究表明，老年人的白质改变是可遗传的，这意味着遗传因素在轻度缺血性改变和相关炎症的发展中发挥了作用。在这个修订后的应用程序中，我们提供了令人信服的新的试点数据，证明了血管损伤的遗传多态性在成像和认知指标中的作用。我们还提供了来自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指标的敏感性，以解释认知衰老的差异。这些新的指标使我们能够检查量化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，并研究DTI与结构MRI、与微血管疾病（血管紧张素原、帕罗酮酶）和相关CMS炎症（c反应蛋白、IL- 6、TNF-a）相关的遗传多态性以及健康老年人认知状态之间的关系。这项研究将利用现有的数据库，其中包含1000多名年龄在31-80岁之间的人的遗传和神经认知数据，这些数据被分为五组（n = 200/组）。其中200人的神经成像数据目前可用，我们将招募另外120名年龄在51-80岁之间的人，以补充老年谱，并从DTI数据中获得新的纤维跟踪图。将对新招募的个体进行纵向跟踪，以检查遗传风险因素背景下白质和认知异常的演变和进展。将进行组比较和潜在变量建模，以检查健康老年人的神经影像学指标、遗传多态性和认知功能差异之间的关系。目前的研究将是第一个整合这些方法来检验一个与年龄相关的认知衰退模型，该模型涉及皮层下白质。研究结果将为我们对认知衰老的理解提供重要信息。

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.