Longitudinal Study of MRI, Clinical, and Genetic Biomarkers of Cognitive Impairment and Alzheimer's Disease in Elderly American Indians

美国印第安人老年认知障碍和阿尔茨海默病的 MRI、临床和遗传生物标志物的纵向研究

• 批准号: 9485172
• 负责人: DEDRA S BUCHWALD
• 金额: $ 33.64万
• 依托单位: UNIVERSITY OF COLORADO DENVER
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-30 至 2022-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9485172
• 关键词: 3-Dimensional; Activities of Daily Living; Address; Adverse effects; Advisory Committees; Affect; Alaska Native; Alleles; Alzheimer disease prevention; Alzheimer' s Disease; Alzheimer' s disease risk; American Indians; Amyloid Proteins; Apolipoprotein E; Asians; Atrophic; Behavioral; Biological Markers; Brain; Brain region; Cause of Death; Cerebrovascular Disorders; Cerebrovascular Trauma; Cessation of life; Clinical; Clinical Data; Cognitive; Communities; Computer software; Data; Data Collection; Dementia; Detection; Development; Dose; Elderly; Elements; Enrollment; Ethnic Origin; Exhibits; Genes; Genetic; Genetic Markers; Genetic Risk; Health Personnel; Heart; Hippocampus (Brain); Hyperlipidemia; Hypertension; Impaired cognition; Latino; Link; Longitudinal Studies; Magnetic Resonance Imaging; Maps; Measures; Medial; National Institute on Aging; Neurodegenerative Disorders; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Outcome; Parietal; Participant; Pathologic; Patients; Pattern; Phase; Physical Function; Population; Prevalence; Prevention; Process; Protocols documentation; Race; Recruitment Activity; Reporting; Research; Risk Assessment; Risk Factors; Sampling; Sampling Studies; Subgroup; Synapses; Therapeutic Intervention; Time; Tribes; Variant; Work; abeta accumulation; aged; base; cerebral atrophy; cingulate cortex; clinical biomarkers; clinical risk; cognitive function; cognitive testing; cohort; disorder prevention; disorder risk; early experience; early onset; effective therapy; ethnic minority population; follow-up; functional loss; functional outcomes; health disparity; high risk; imaging biomarker; improved; low socioeconomic status; magnetic resonance imaging biomarker; member; mild cognitive impairment; neuron loss; northern plains; outcome forecast; performance tests; population based; pre-clinical; precision medicine; predict clinical outcome; racial minority; regional atrophy; response; tailored health care; tau aggregation; treatment response

ABSTRACT Precision medicine is the emerging practice of delivering healthcare tailored to patients on the basis of specific factors that contribute to disease risk, prognosis, and treatment response. The prospect of applying precision medicine to neurodegenerative disorders such as Alzheimer's disease (AD) is especially promising. Genetic markers, most notably variation in the apolipoprotein E gene, and measures of vascular brain injury and cerebral atrophy assessed by MRI have emerged as useful biomarkers of preclinical AD and risk of clinical disease. More than 3 million American Indians (AIs), Alaska Natives, Blacks, Latinos, and Asians suffer from AD, and experience earlier onset of cognitive impairment and AD than Whites. The few studies of AD in AIs are limited by small, single-community samples. We will use data from the Strong Heart Study (SHS) and ancillary Cerebrovascular Disease and its Consequences in American Indians (CDCAI) study to evaluate cognitive function, AD risk factors, and MRI-defined biomarkers of AD in older AIs. The SHS collected data from 4,549 AIs aged 45-74 years from tribes in the Southwest, Southern Plains, and Northern Plains in 3 phases from 1988 to 2000. The CDCAI study assessed cognitive function and MRI-defined vascular brain injury in 818 surviving SHS participants in 2010-2013 and is reassessing surviving participants with the same MRI and cognitive tests. We will use statistical mapping software to reprocess MRIs from both the original and follow-up CDCAI examinations and will create 3-dimensional brain maps for older AIs. We will quantify cerebral atrophy in brain regions preferentially affected by AD such as the hippocampus, parahippocampal, medial temporal, and parietal regions, and the posterior cingulate cortex. We will compare structural patterns on MRI at both CDCAI time points with normative data on AD patients from other populations. We will define probable AD cases by assessing change in MRI-defined loss in regions selectively affected by AD, in combination with AD-related cognitive test performance and activities of daily living; and examine associations of probable AD with risk factors and functional outcomes. Our Specific Aims are to: 1) establish AI-specific normative values of MRI atrophy in brain regions selectively affected by AD, and evaluate AD-related regional atrophy in combination with cognitive and behavioral changes to calculate prevalence of probable AD; 2) use genetic, sociodemographic, and clinical data on risk factors for AD observed in other populations to identify correlates of probable AD in elderly AIs; and 3) estimate associations of MRI markers of probable AD with measures of cognitive and physical function, independent of the effects of vascular brain injury. AD is the leading cause of dementia and of death in the US. The CDCAI sample is the only population-based cohort of AIs with MRI data and genetic biomarkers relevant to AD. We will leverage these unique data to address key elements of PM, namely, risk assessment and detection of preclinical pathophysiologic processes of AD among AIs.

摘要 精准医疗是一种新兴的医疗实践，它根据特定的 影响疾病风险、预后和治疗反应的因素。应用精度的前景 治疗神经退行性疾病如阿尔茨海默病（AD）的药物尤其有希望。遗传 标志物，最明显的是载脂蛋白E基因的变异，以及血管性脑损伤的测量， 通过MRI评估的脑萎缩已经成为临床前AD和临床疾病风险的有用生物标志物。 疾病超过300万美国印第安人（AI），阿拉斯加原住民，黑人，拉丁美洲人和亚洲人患有 AD，并且比白人更早发生认知障碍和AD。人工智能中AD的少数研究 受到小的单一社区样本的限制。我们将使用强大心脏研究（SHS）的数据， 美国印第安人辅助性脑血管疾病及其后果（CDCAI）研究，以评估 认知功能、AD风险因素和MRI定义的老年AI中AD的生物标志物。SHS收集的数据 来自西南部、南部平原和北方平原部落的4,549名年龄在45 - 74岁之间的人工智能， 从1988年到2000年。CDCAI研究评估了认知功能和MRI定义的血管脑 2010 - 2013年，818名幸存的SHS参与者受伤，并正在重新评估幸存的参与者， 核磁共振和认知测试我们将使用统计映射软件重新处理原始和 随访CDCAI检查，并将为老年AI创建三维大脑地图。我们将量化大脑 在优先受AD影响的脑区域中的萎缩，例如海马、海马旁、内侧 颞叶、顶叶和后扣带皮层。我们会比较核磁共振成像的结构模式 在两个CDCAI时间点与来自其他人群的AD患者的正常数据。我们将概率定义为 通过评估选择性受AD影响的区域中MRI定义的损失的变化，结合 AD相关认知测试表现和日常生活活动;并检查可能的AD相关性 风险因素和功能结果。我们的具体目标是：1）建立人工智能特定的规范价值观 在选择性受AD影响的脑区域中的MRI萎缩，并评估AD相关的区域萎缩， 结合认知和行为变化来计算可能的AD的患病率; 2）使用遗传， 在其他人群中观察到的AD风险因素的社会人口统计学和临床数据，以确定相关性 老年AI中可能的AD; 3）估计可能的AD的MRI标记物与以下指标的相关性： 认知和身体功能，独立于血管性脑损伤的影响。AD是导致 痴呆症和死亡在美国。CDCAI样本是唯一具有MRI数据的基于人群的AI队列 和与AD相关的遗传生物标志物。我们将利用这些独特的数据来解决PM的关键要素， 即风险评估和检测认可机构中AD的临床前病理生理过程。