Effects of metabolic phenotype on functional connectivity in aging and Alzheimer’s Disease

代谢表型对衰老和阿尔茨海默病功能连接的影响

• 批准号: 10745270
• 负责人: Zachary D Green
• 金额: $ 3.63万
• 依托单位: UNIVERSITY OF KANSAS MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-19 至 2027-02-18
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10745270
• 关键词: Affect; Aging; Alzheimer disease detection; Alzheimer' s Disease; Alzheimer' s disease brain; Alzheimer' s disease diagnosis; Alzheimer' s disease diagnostic; Alzheimer' s disease pathology; Alzheimer' s disease risk; Alzheimer’s disease biomarker; American; Amyloid; Amyloid beta-Protein; Award; Biological Markers; Blood Glucose; Blood Vessels; Brain; Brain Pathology; Brain imaging; Brain region; Cerebrovascular Disorders; Cerebrum; Classification; Clinical; Cognitive; Complex; Data; Data Set; Dementia; Diabetes Mellitus; Diagnosis; Diagnostic; Disease; Doctor of Philosophy; Early Diagnosis; Elderly; Ethnic Origin; Evaluation; Fasting; Functional Magnetic Resonance Imaging; Functional disorder; Genetic; Genetic Risk; Genotype; Glucose; Goals; Health; Heterogeneity; Hippocampus; Hypertension; Impaired cognition; Impairment; Individual; Inflammatory; Latino; Link; Measures; Mediating; Metabolic; Metabolic dysfunction; Metabolism; Monitor; Nerve Degeneration; Neurobehavioral Manifestations; Neurosciences; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Outcome; Pathogenesis; Pathology; Patients; Persons; Pharmaceutical Preparations; Phenotype; Physicians; Population; Positioning Attribute; Prediabetes syndrome; Predisposition; Rest; Risk; Risk Factors; Role; Sample Size; Scientist; Signal Transduction; Site; Structure; Subgroup; Training; Vascular Diseases; Work; aging brain; amyloid pathology; apolipoprotein E-4; base; blood oxygen level dependent; brain health; cardiometabolic risk; cardiometabolism; career; carrier status; cohort; dementia risk; disorder risk; epidemiologic data; epidemiology study; genetic risk factor; glucose metabolism; health data; hyperphosphorylated tau; imaging biomarker; improved; in vivo; lipid metabolism; metabolic phenotype; mild cognitive impairment; neural correlate; neuroimaging; neuropathology; non-demented; potential biomarker; precision medicine; recruit; skills; socioeconomics

Summary/Abstract Alzheimer’s Disease (AD), the most common cause of dementia, affects over 6.2 million Americans and 50 million individuals worldwide. Ten to fifteen years prior to the onset of cognitive symptoms, AD pathology begins to appear in the brain. While the primary pathology associated with AD include amyloid beta and hyperphosphorylated tau, the pathogenesis of AD remains elusive. Other changes in the AD brain include derangements in cerebral glucose metabolism. Recent epidemiological studies have highlighted an association between AD and systemic metabolic impairment (i.e. diabetes). This indicates a major role of altered metabolism in AD, and warrants examination of how metabolic risk may contribute to brain health and dementia risk. Biomarker studies of brain structure and function offer potential opportunities for early detection of AD, and for improving our understanding of factors relating to disease risk. Functional connectivity, a measure of correlated neural activity in two brain regions can be measured by resting-state functional magnetic resonance imaging (rsfMRI). This functional neuroimaging approach has emerged as a potential biomarker for AD diagnosis and disease monitoring. Importantly, metabolic risk has previously been associated with altered functional connectivity. However, data regarding early forms of metabolic risk, like prediabetes, is lacking. Additionally, functional connectivity studies often suffer from limited sample size and a lack of diversity. We intend to analyze the existing rsfMRI data of individuals recruited into the Health and Aging Brain Among Latino Elders (HABLE) Study, a diverse cohort of approximately 2,000 individuals. In our first aim, we will characterize the effect of metabolic risk (prediabetes or Type 2 Diabetes status assessed by blood glucose, diagnosis, or medication use) on functional connectivity in cognitively healthy individuals. As part of this aim, we will also examine the role of APOE4, a foremost genetic risk factor of AD that is closely related to cerebrovascular dysfunction. In our second aim, we will examine functional networks across the AD diagnostic spectrum, and examine to what degree metabolic risk mediates changes in these networks. We will then assess the relationship between cardiometabolic risk score and functional connectivity across the entire cohort.

总结/摘要 阿尔茨海默病（AD）是痴呆症的最常见原因，影响超过620万美国人和50 全球百万人。认知症状发作前10至15年，AD病理学 开始出现在大脑中。虽然与AD相关的主要病理学包括淀粉样蛋白β和淀粉样蛋白β。 尽管tau蛋白过度磷酸化，但AD的发病机制仍然难以捉摸。AD大脑的其他变化包括 大脑葡萄糖代谢紊乱。最近的流行病学研究强调了 AD和全身性代谢损害（即糖尿病）之间的关系。这表明了改变的主要作用 代谢，并保证检查代谢风险如何可能有助于大脑健康， 痴呆风险大脑结构和功能的生物标志物研究为早期检测提供了潜在的机会 以及提高我们对疾病风险相关因素的理解。功能连通性，a 在两个脑区域中相关神经活动的测量可以通过静息状态功能测量。 磁共振成像（rsfMRI）。这种功能性神经影像学方法已经成为一种潜在的 用于AD诊断和疾病监测的生物标志物。重要的是，代谢风险以前一直是 与功能连接改变有关。然而，关于早期代谢风险的数据，如 糖尿病前期缺乏。此外，功能连接性研究通常受到样本量有限和 缺乏多样性。我们打算分析现有的rsfMRI数据的个人招募到健康和 拉丁裔老年人大脑老化（HABLE）研究，一个由大约2,000人组成的多样化队列。在我们 第一个目标，我们将描述代谢风险（糖尿病前期或2型糖尿病状态， 血糖、诊断或药物使用）对认知健康个体的功能连接的影响。作为 作为这一目标的一部分，我们还将研究APOE 4的作用，APOE 4是AD的最重要的遗传风险因素， 与脑血管功能障碍有关在我们的第二个目标中，我们将检查整个AD的功能网络， 诊断谱，并检查代谢风险在多大程度上介导了这些网络的变化。我们将 然后评估心脏代谢风险评分与整个系统的功能连接之间的关系， 队列。