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）的诊断、预后和治疗。然而，到目前为止，还没有大规模系统的多层次 “组学”研究已经与AT（N）定义的（淀粉样蛋白[A]、tau [T]、神经变性）结合进行。 [N])非裔美国人，墨西哥裔美国人和非西班牙裔白人之间的生物标志物。我们的数据表明 （1）基于组学的生物标志物在不同人群中存在差异，包括血浆AT（N）生物标志物，（2） 基于组学的生物标志物可以高度准确地检测临床诊断的轻度认知障碍 (MCI)和痴呆症，但（3）种族/民族群体之间的概况不同。最近， 我们的数据表明，蛋白质组学图谱在检测神经变性方面是准确的， 在种族/民族群体之间存在差异。鉴于记录的不同人种/种族AT（N）生物标志物的差异 多水平组学研究可能会突出新的人群特异性途径， 认知能力下降，MCI和AD。此外，随着最近FDA批准了一种疾病修饰淀粉样蛋白药物， 来自组学核心（核心D）的数据比以往任何时候都更重要，可以迅速地为新的、适当的 量身定制的临床试验核心D将监督收集、处理、分析、储存和分发 为所有项目（核心-项目交互）、核心（核心-核心交互）、 和全球研究者（跨队列相互作用）。目标1：生成高质量的基因组数据。目标二： 生成高质量的蛋白质组学数据。目标3：生成高质量的外泌体数据。目标4：产生高 质量代谢组学数据。目标5：为项目提供关键组学数据（核心-核心，核心-项目 相互作用）。目标6：向外部调查人员提供数据和专门知识。