Understanding ethno-racial differences in AT(N)-defined heterogeneity profiles

了解 AT(N) 定义的异质性概况中的民族差异

• 批准号: 10723248
• 负责人: Karin Meeker
• 金额: $ 12.69万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-15 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10723248
• 关键词: Acculturation; Affect; Alzheimer' s Disease; Alzheimer' s disease related dementia; Alzheimer’s disease biomarker; Amyloid; Area; Atrophic; Biological Markers; Black Populations; Brain imaging; Brain region; Classification; Clinical; Clinical Trials; Cognitive; Communities; Community Health; Data; Disease; Education; Ethnic Origin; Genetic; Genotype; Goals; Health; Heterogeneity; Hippocampus; Household; Image; Income; Individual; Investigation; Lateral; Liquid substance; Literature; Machine Learning; Magnetic Resonance Imaging; Measures; Medial; Mediating; Mentors; Mexican Americans; National Institute on Aging; Nerve Degeneration; Neuroanatomy; Not Hispanic or Latino; Outcome; Parietal; Pathogenesis; Pathologic; Pattern; Phase; Population Heterogeneity; Positioning Attribute; Positron-Emission Tomography; Regional Disease; Research; Research Personnel; Resources; Sampling; Socioeconomic Status; Training; Underrepresented Minority; Work; aging brain; apolipoprotein E-4; cerebral atrophy; clinical heterogeneity; cohort; deprivation; design; disease heterogeneity; diverse data; ethnic diversity; ethnoracial; ethnoracial disparity; follow-up; functional outcomes; health disparity; imaging biomarker; indexing; individualized medicine; machine learning method; multi-racial; neuroimaging; neuroimaging marker; precision medicine; racial difference; racial diversity; recruit; social; social health determinants; stem; structural determinants; tau Proteins; tau aggregation

PROJECT ABSTRACT Alzheimer disease (AD) is a highly heterogeneous disorder which varies in presentation within and across diverse communities and backgrounds. Neuroanatomically, heterogeneity is observed in the topographical patterns of amyloid (A), tau (T), and neurodegeneration (N) markers used to stage AD. For example, patterns of tau accumulation and brain atrophy are highly correlated and have been subtyped by advanced multivariate and machine learning methods into those involving typical AD regions (e.g., medial-temporal, lateral temporoparietal), hippocampal-sparing, limbic-predominant regions or minimal atrophy, while amyloid accumulation can be subtyped into frontal, parietal, and occipital regions. Notably, spatial subtypes are associated with distinct cognitive, genetic (e.g., APOE e4 genotype), and fluid biomarker profiles, thus suggesting that clinical heterogeneity may in part stem from neuroanatomical heterogeneity. Although neuroanatomical heterogeneity in AD has important implications for cognitive and functional outcomes as well as patient-specific treatments, there is a large gap in the literature regarding AD biomarker topographical patterns in ethno-racial groups. Similarly, it is largely unknown to what extent structural and social determinants of health (SSDOH) affect heterogeneity. The present study fills a critical gap in the literature by including under-represented minorities and relevant SSDOH factors in the investigation of heterogeneity in AT(N) imaging markers. Using data from the racially and ethnically diverse Health and Aging Brain Study – Health Disparities (HABS-HD), this study will A) determine AD heterogeneity profiles (i.e., spatial subtypes and magnitude) for A, T, and N neuroimaging markers (i.e., magnetic resonance imaging [MRI], amyloid and tau positron emission tomography [PET]) using a machine learning approach; B) assess within and between group differences in heterogeneity profiles across Mexican-Americans, Blacks, and non-Hispanic Whites (NHW); and C) assess overall effects of SSDOH (e.g., area deprivation index, acculturation, education etc.) on A, T, and N heterogeneity profiles within and between ethno-racial groups. Biomarker cut-points and group-level composites used to classify individuals in research and clinical settings are often informed through the identification of AD-specific or AD-vulnerable brain regions. However, the identified AD-sensitive regions and associated cut-points are typically derived from one group (i.e., NHWs) and applied to all. Characterizing heterogeneity in AT(N) imaging markers using a diverse and representative sample is therefore crucial to informing whether AD-sensitive regions are similar across individuals and thus whether current cut-points are appropriate.

项目摘要 阿尔茨海默病（Alzheimer disease，AD）是一种高度异质性的疾病， 不同的社区和背景。神经解剖学上，在地形图中观察到异质性。 用于AD分期的淀粉样蛋白（A）、tau（T）和神经变性（N）标志物的模式。例如，模式 tau蛋白积累和脑萎缩高度相关，并已通过先进的多变量 和机器学习方法到涉及典型AD区域的那些（例如，内侧颞侧 颞顶），保留冠状动脉，边缘占主导地位的地区或最低限度的萎缩，而淀粉样蛋白 积累可以分为额叶、顶叶和枕叶区域。值得注意的是，空间子类型 与不同的认知，遗传（例如，APOE e4基因型）和流体生物标志物谱，因此 提示临床异质性可能部分源于神经解剖学异质性。虽然 AD的神经解剖学异质性对认知和功能结果也有重要意义 作为患者特异性治疗，关于AD生物标志物地形图的文献中存在很大的空白 在民族种族群体中的模式。同样，在很大程度上也不知道结构和社会 健康决定因素（SSDOH）影响异质性。本研究填补了文献中的一个关键空白， 包括代表性不足的少数民族和相关的SSDOH因素的异质性调查， AT（N）成像标记物。 使用来自种族和民族多样化的健康和老龄化大脑研究的数据， 健康差异（HABS-HD），这项研究将 A）确定AD异质性谱（即，空间子类型和 幅值）对于A、T和N神经成像标记（即，磁共振成像[MRI]、淀粉样蛋白和tau蛋白 正电子发射断层扫描[PET]）使用机器学习方法; B）评估组内和组间 墨西哥裔美国人、黑人和非西班牙裔白人（NHW）的异质性差异;以及 C）评估SSDOH的总体效果（例如，地区贫困指数、文化适应、教育等）在A、T和N上 民族-种族群体内部和之间的异质性概况。生物标志物临界点和组水平 用于在研究和临床环境中对个体进行分类的复合材料通常通过 识别AD特异性或AD易感脑区。然而，确定的AD敏感区域和 相关的切割点通常源自一个组（即，NHWs）并适用于所有人。表征 因此，使用多样化和代表性样品的AT（N）成像标记物的异质性对于 告知AD敏感区域在个体之间是否相似，因此当前的分界点是否 适当