Integrative Genomic Approaches for Understanding Sex Differences in Alzheimer's Disease

了解阿尔茨海默病性别差异的综合基因组方法

基本信息

项目摘要

Project Summary Women make up nearly two-thirds of all Alzheimer's disease (AD) cases in the United States and these differences are likely due to contributions from differential genetic and environmental effects between the sexes. While several candidate gene studies have identified sex-specific associations, no large-scale, genome- wide, sex-specific association analysis of AD has been conducted. Furthermore, the functional underpinnings of sex-specific genetic associations and how they relate to expression and epigenetic variations, are still largely unknown. We hypothesize that multiple genetic, epigenetic and gene-expression changes operate in a sex-specific manner to explain at least part of the sex disparity in AD prevalence. To this end, we propose new strategies for integrative analysis of DNA variants, gene expression, splicing and DNA methylation in a sex- aware framework, which will allow us to prioritize variants with the most regulatory potential and provide additional insight into the biological mechanisms of sex differences in AD. To accomplish these goals we will leverage existing large-scale genetic data from several consortia studies in AD, as well as expression and methylation data from brain tissue of AD cases and healthy individuals. We propose the following specific aims: 1) Evaluate the sex-specific genetic architecture of AD through association and genetic correlation analysis; 2) Conduct transcriptome-wide association analyses to identify sex-specific changes relevant to AD; 3) Conduct region-centric analysis to identify sex-specific DNA methylation changes that contribute to AD; and 4) Prioritize sex-specific loci and develop sex-specific polygenic risk scores for AD through integrative analysis. Successful completion of this project will deliver the first large scale sex-specific genome-wide analysis of AD. It will also provide a paradigm for comprehensive and integrative analysis of genomic and epigenomic datasets in a sex-aware framework. By focusing on integrative analysis of multiple types of `omics data, our study will provide a more complete understanding of the genetic and epigenetic programs underlying sex differences in AD, which will lead to better prevention, diagnosis and individualized treatment strategies.
项目摘要 在美国,女性占所有阿尔茨海默病(AD)病例的近三分之二, 差异可能是由于不同的遗传和环境影响之间的贡献, 性别虽然几个候选基因的研究已经确定了性别特异性协会,没有大规模的,基因组- 广泛的,性别特异性的关联分析AD已经进行。此外,职能基础 性别特异性遗传关联以及它们如何与表达和表观遗传变异相关, 大部分未知。我们假设,多个遗传,表观遗传和基因表达的变化在一个特定的基因组中起作用。 性别特异性的方式来解释AD患病率的性别差异。为此,我们提出新的 性别中DNA变异、基因表达、剪接和DNA甲基化的综合分析策略- 这将使我们能够优先考虑具有最大监管潜力的变体,并提供 进一步深入了解AD性别差异的生物学机制。为了实现这些目标,我们将 利用现有的大规模遗传数据,从几个财团的研究,在AD,以及表达和 来自AD病例和健康个体的脑组织的甲基化数据。我们提出以下具体建议: 目的:1)通过关联分析和遗传相关分析,评价AD的性别特异性遗传结构 2)进行全转录组关联分析以鉴定与AD相关的性别特异性变化; 3)进行以区域为中心的分析,以确定导致AD的性别特异性DNA甲基化变化;以及 4)优先考虑性别特异性位点,并通过综合分析开发AD的性别特异性多基因风险评分。 该项目的成功完成将提供第一个大规模的AD性别特异性全基因组分析。 它还将为基因组和表观基因组数据集的全面和综合分析提供范例 in a sex-aware性别await意识framework框架.通过对多种组学数据的综合分析,我们的研究将 提供了一个更完整的了解遗传和表观遗传程序的性别差异的基础, AD,这将导致更好的预防,诊断和个性化治疗策略。

项目成果

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Brian William Kunkle其他文献

Brian William Kunkle的其他文献

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{{ truncateString('Brian William Kunkle', 18)}}的其他基金

Core E: Data Management
核心E:数据管理
  • 批准号:
    10333059
  • 财政年份:
    2022
  • 资助金额:
    $ 76.63万
  • 项目类别:
Core E: Data Management
核心E:数据管理
  • 批准号:
    10654538
  • 财政年份:
    2022
  • 资助金额:
    $ 76.63万
  • 项目类别:
Integrative Genomic Approaches for Understanding Sex Differences in Alzheimer's Disease
了解阿尔茨海默病性别差异的综合基因组方法
  • 批准号:
    10612724
  • 财政年份:
    2019
  • 资助金额:
    $ 76.63万
  • 项目类别:

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