HABS-HD - Core D - Omics Core

HABS-HD - 核心 D - 组学核心

• 批准号: 10708872
• 负责人: Sid E O'Bryant
• 金额: $ 896.21万
• 依托单位: UNIVERSITY OF NORTH TEXAS HLTH SCI CTR
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-30 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10708872
• 关键词: African American population; Alzheimer' s Disease; Alzheimer' s disease diagnosis; Alzheimer’s disease biomarker; Amyloid; Amyloid beta-42; Bioinformatics; Biological Assay; Biological Markers; Biostatistics Core; Blood; Clinical Trials; Collaborations; Collection; Data; Data Analyses; Data Set; Dementia; Diagnostic; Disease; Ethnic Population; Fatty Acids; Glycolysis; Health; Impaired cognition; International; Investigation; Marker Discovery; Mass Spectrum Analysis; Methods; Methylation; Mexican Americans; Modeling; Molecular Weight; Nerve Degeneration; Neurons; Not Hispanic or Latino; Oxidative Phosphorylation; Participant; Pathology; Pathway interactions; Pharmaceutical Preparations; Plasma; Population; Population Heterogeneity; Prognosis; Proteins; Proteomics; Protocols documentation; Publishing; Qualifying; Quality Control; Research Personnel; Sampling; System; Technology; Update; Validation; Visit; Work; aging brain; biobank; biomarker validation; clinical diagnosis; cohort; exosome; follow-up; genome repository; genome sequencing; genome wide association study; genomic data; health disparity; lipid metabolism; metabolomics; mild cognitive impairment; novel; novel marker; oxidation; racial population; tau Proteins; transcriptomics; whole genome

HABS-HD OMICS CORE (CORE D) - ABSTRACT Biofluids, including blood and CSF, alone or in combination, may provide sensitive biomarkers for Alzheimer’s disease (AD) diagnosis, prognosis, and theragnosis. To date, however, no large-scale systematic multi-level “omics” study has been conducted in combination with AT(N) defined (amyloid [A], tau [T], neurodegeneration [N]) biomarkers among African Americans, Mexican Americans, and non-Hispanic whites. Our data suggests that (1) omics-based biomarkers vary across diverse populations, including plasma AT(N) biomarkers, (2) omics-based biomarkers can be highly accurate in detecting clinically diagnosed mild cognitive impairment (MCI) and dementia across populations, but (3) the profiles differ between racial/ethnic groups. More recently, our data suggests that a proteomic profile is accurate in detecting neurodegeneration, but again the profiles vary between racial/ethnic groups. Given the documented differences in AT(N) biomarkers by racial/ethnic groups, it is likely that multi-level omics investigations will highlight novel population-specific pathways for cognitive decline, MCI and AD. Additionally, with the recent FDA approval of a disease modifying amyloid drug, the data from the Omics Core (Core D) is more important than ever and can rapidly inform novel, appropriately tailored, clinical trials. Core D will oversee the collection, processing, assays, storage and distribution of samples to provide critical data to all Projects (Core – Project Interactions), Cores (Core-Core interactions), and to global investigators (Cross-Cohort Interactions). Aim 1: Generate high quality genomic data. Aim 2: Generate high quality proteomic data. Aim 3: Generate high quality exosome data. Aim 4: Generate high quality metabolomic data. Aim 5: Provide critical omics data for projects (Core-Core, Core-Project Interactions). Aim 6: Provide data and expertise to external investigators.

HABS -HD OMICS核心（核心D） - 摘要 生物流体，包括血液和CSF，单独或组合，可能为阿尔茨海默氏症提供敏感的生物标志物 疾病（AD）诊断，预后和热疾病。但是，迄今为止，没有大规模的系统多层次 已经与AT（N）定义（淀粉样蛋白[A]，Tau [T]，神经变性进行了“ OMICS”研究 [n]）非裔美国人，墨西哥裔美国人和非西班牙裔白人的生物标志物。我们的数据建议 （1）基于OMICS的生物标志物在潜水员种群中各不相同，包括（N）生物标志物的等离子体，（2） 基于OMIC的生物标志物可以高度准确地检测临床诊断性轻度认知障碍 （MCI）和痴呆症的人群之间，但（3）种族/族裔群体之间的概况不同。最近， 我们的数据表明，蛋白质组学特征在检测神经退行性方面是准确的，但再次剖面 种族/族裔之间有所不同。鉴于种族/族裔在AT（N）生物标志物上的差异 小组，多层次的OMICS调查可能会突出显示新颖的人群特异性途径 认知下降，MCI和AD。此外，随着FDA最近批准修饰淀粉样蛋白药物的疾病， 来自OMICS核心（核心D）的数据比以往任何时候都重要，并且可以快速告知小说，适当地 量身定制的临床试验。核心D将监督收集，处理，测定，存储和分布 为所有项目（核心 - 项目交互），内核（核心核心交互）提供关键数据的样本， 以及全球研究人员（跨核心相互作用）。目标1：生成高质量的基因组数据。目标2： 生成高质量的蛋白质组学数据。 AIM 3：生成高质量的外泌体数据。目标4：产生高 质量代谢组数据。目标5：为项目提供关键的OMIC数据（核心，核心项目 互动）。目标6：向外部调查人员提供数据和专业知识。