Sex-specific Molecular Profiling to Understand Pathology and Identify Causal Genes and Drug Targets for Alzheimer's Disease

通过性别特异性分子分析来了解阿尔茨海默病的病理学并识别致病基因和药物靶点

• 批准号: 10300830
• 负责人: YunJu Sung
• 金额: $ 274.07万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-30 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10300830
• 关键词: Age; Alleles; Alzheimer' s Disease; Alzheimer' s disease risk; Alzheimer’s disease biomarker; Amyloid beta-Protein; Astrocytes; Automobile Driving; Biological; Biological Markers; Biology; Brain; CRISPR/Cas technology; Cells; Cerebrospinal Fluid; Characteristics; Clinic; Clinical; Collection; Communities; DNA Methylation; Data; Diagnostic; Disease; Disease Progression; Drug Targeting; Ethnic Origin; Etiology; FDA approved; Female; Functional disorder; Gene Expression; Gene Expression Regulation; Gene Proteins; Gene Targeting; Genes; Genetic; Genetic Markers; Genetic Variation; Genomics; Genotype-Tissue Expression Project; Germ Cells; Goals; Human; Induced pluripotent stem cell derived neurons; Inherited; Innate Immune Response; Interdisciplinary Study; Knowledge Portal; Life Expectancy; Lysosomes; Maps; Memory; Mendelian randomization; Methylation; Microglia; Molecular; Molecular Profiling; Multiomic Data; Nerve Degeneration; Neurons; Participant; Pathogenicity; Pathology; Pathway interactions; Pharmaceutical Preparations; Plasma; Proteomics; Quantitative Trait Loci; Race; Reporting; Reproducibility; Request for Applications; Research; Resources; Role; Sampling; Series; Sex Differences; Sex Differentiation; TREM2 gene; Technology; Therapeutic; Tissues; United States National Institutes of Health; Universities; Washington; Woman; aging brain; causal variant; clinically translatable; connectome; data sharing; disorder risk; epigenomics; genetic architecture; genetic variant; genome wide association study; genome-wide; high dimensionality; high risk; individualized medicine; individualized prevention; induced pluripotent stem cell; insight; lipidomics; male; metabolomics; molecular marker; multiple omics; neuroimaging; new therapeutic target; novel; predictive modeling; preventive intervention; proteomic signature; response; risk variant; sex; specific biomarkers; stem cell model; tau Proteins; transcriptomics

Abstract Alzheimer's disease (AD) is a highly heterogeneous multifactorial disease. Genetic influences on AD are strong as shown by several pathogenic genes and over 50 AD loci identified through genome-wide association studies (GWAS). There are also clear sex differences in AD risk and progression. Women are at a higher risk of developing AD and present faster progression. A recent GTEx study also highlights sex differences in the genetic regulation of gene expression. Despite these established sex differences, sex-specific molecular findings in AD are still limited. The objective of this study is therefore to generate detailed sex-specific multi- tissue molecular profiles of AD and decipher the genetic architecture that underlies AD. We propose to identify sex-specific functional mechanisms underlying the genetic architecture of AD. We will generate multiple layers of -omics data, including DNA methylation, gene expression, proteomics, metabolomics, and lipidomics, from several large and well characterized studies. A series of well-powered sex-specific omics characterization across multiple tissues can help identify novel drug targets and provide critical insights for clinically translatable interventions for prevention and treatment. We will then map additional GWAS loci by performing sex-specific multi-omic quantitative trait loci and co-localization for each -omic layers. We will identify the causal genes, proteins, and additional -omic analytes by performing Mendelian randomization. Analyzing such omics data will elucidate a causal path from sex-specific genetic variation to AD risk, onset and progression. The human multi- omic data will finally be combined with induced pluripotent stem cell (iPSC) models to identify novel sex- specific FDA-approved therapeutics. We have assembled a very productive and interdisciplinary research team with expertise in all the aspect of the proposal. All aims in this proposal will be conducted and reported in compliance with NIH guidance on scientific rigor and reproducibility. Our preliminary data already identified several genes and proteins that are associated with AD risk and cerebrospinal fluid biomarkers in a sex- specific manner. All the raw data will be shared via NIA-approved mechanism (including AD Knowledge Portal, NIAGADS). This rich resource will benefit the field for additional analyses beyond the ones proposed here.

摘要 阿尔茨海默病（AD）是一种高度异质性的多因素疾病。遗传因素对AD的影响 通过全基因组关联鉴定的几个致病基因和超过50个AD位点显示出强 研究（GWAS）。在AD风险和进展方面也存在明显的性别差异。女性的风险更高 发展成AD的可能性并呈现更快的进展。最近的一项GTEx研究也强调了 基因表达的遗传调控。尽管存在这些既定的性别差异，性别特异性分子 在AD中的发现仍然有限。因此，本研究的目的是产生详细的性别特异性多- AD的组织分子谱，并破译AD的遗传结构。我们建议确定 性别特异性功能机制的遗传结构的AD。我们将生成多个图层 组学数据，包括DNA甲基化，基因表达，蛋白质组学，代谢组学和脂质组学，来自 几项大型且特征明确的研究。一系列性能良好的性别特异性组学表征 可以帮助识别新的药物靶点，并为临床上可翻译的 预防和治疗的干预措施。然后，我们将通过进行性别特异性分析， 多组数量性状基因座和每个组层的共定位。我们会找出致病基因， 蛋白质和另外的组学分析物。分析这些组学数据将 阐明从性别特异性遗传变异到AD风险、发病和进展的因果关系。人类的多- 组学数据最终将与诱导多能干细胞（iPSC）模型相结合，以确定新的性别- FDA批准的特定疗法。我们进行了一项非常富有成效的跨学科研究， 在提案的各个方面拥有专业知识的团队。本建议书中的所有目标将在 符合NIH关于科学严谨性和再现性的指导。我们的初步数据已经确定 与AD风险相关的几种基因和蛋白质以及性别中的脑脊液生物标志物- 具体方式。所有原始数据将通过NIA批准的机制（包括AD知识门户， NIAGADS）。这一丰富的资源将使该领域在这里提出的分析之外进行更多的分析。