Multi-omic dissection of clonal hematopoiesis-associated diseases

克隆造血相关疾病的多组学解剖

• 批准号: 10644764
• 负责人: Zhi Yu
• 金额: $ 13.73万
• 依托单位: BROAD INSTITUTE, INC.
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2025-09-14
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10644764
• 关键词: Address; Adult; Aging; Attention; Biological Process; Blood; Chronic; Chronic Disease; Chronic Obstructive Pulmonary Disease; Clonal Expansion; Coronary Arteriosclerosis; DNA; DNMT3a; Data; Development; Dimensions; Disease; Dissection; Gene Expression; Gene Expression Profile; Genes; Genetic; Genomics; Goals; Heart failure; Hematological Disease; Hematopoiesis; Hematopoietic stem cells; Immune; Individual; Inflammasome; Inflammation; Interleukin-1 beta; Interleukin-6; Lead; Liver diseases; Measures; Mediating; Mediation; Methods; Modeling; Modification; Molecular; Multiomic Data; Mutation; Myocardial Infarction; National Heart, Lung, and Blood Institute; Normal tissue morphology; Osteoporosis; Participant; Pathologic; Pathway Analysis; Pathway interactions; Phase; Plasma Proteins; Population; Proteins; Proteomics; Proxy; Risk; Sampling; Somatic Mutation; Statistical Methods; Stroke; Structure; Testing; Tissue-Specific Gene Expression; Trans-Omics for Precision Medicine; Work; age related; biobank; cell type; chronic liver disease; deep learning; disease phenotype; disorder risk; early onset; improved; insight; instrument; learning strategy; machine learning method; multiple omics; personalized strategies; precision medicine; prevent; protein protein interaction; proteomic signature; response; self renewing cell; single-cell RNA sequencing; statistical and machine learning; therapeutic target; trait; transcriptome sequencing; transcriptomics; venous thromboembolism

Project Summary Self-renewing cell populations accumulate somatic mutations with aging and/or in response to environmental insult and chronic inflammation. Most of these mutations in normal tissues have no functional consequence. In rare cases, these somatic mutations can confer a selective advantage leading to clonal expansion in hematopoietic stem cells, a phenomenon termed 'Clonal Hematopoiesis of Indeterminate Potential' (CHIP). CHIP has been associated with a selective range of non-hematopoietic conditions, including coronary artery disease, stroke, heart failure, venous thromboembolism, chronic obstructive pulmonary disease, chronic liver diseases, and osteoporosis. However, the molecular mechanisms by which CHIP specifically promotes these diseases remain largely unknown. The overarching goal of this proposal is to molecularly connect CHIP with the development of associated diseases through developing and applying statistical and machine learning methods to multi-omics data in the NHLBI Trans-Omics for Precision Medicine (TOPMed), UK Biobank, and Mass General Brigham Biobank (MGBB). Specifically, I propose the following aims. In Aim 1, I will develop a statistical method that combines multiple proteins implicated in the same pathway to improve discovery and facilitate translational insights for proteomics-based association analyses. The combined protein quantitative traits generated by this method will be used in the following aims. In Aim 2, I will examine how the presence of CHIP and each CHIP driver gene specifically promote certain diseases through (1) identifying the proteomic signatures of CHIP and quantifying the mediation effects to associated diseases and (2) evaluating the potential modifications of CHIP-associated diseases by the expression levels of genes implicated in diverse molecular factors. In Aim 3, I will evaluate how the progression of CHIP promotes associated diseases. I will examine associations between longitudinal change in the number and size of CHIP clones and incident disease risks, as well as generate bulk and single-cell RNA sequencing data among CHIP carriers with or without osteoporosis, a disease strongly associated with CHIP but understudied, and test for differential gene expressions between the two groups. This project's successful execution will identify the mechanisms underlying CHIP-associated disease risks to prioritize therapeutic targets and advance precision medicine goals.

项目摘要 自我更新的细胞群体随着衰老和/或响应环境变化而积累体细胞突变。 侮辱和慢性炎症。正常组织中的大多数突变没有功能性后果。在 在极少数情况下，这些体细胞突变可以赋予选择性优势，导致克隆扩增， 造血干细胞，一种被称为“不确定潜能的克隆造血”（CHIP）的现象。 CHIP与一系列非造血系统疾病相关，包括冠状动脉 疾病、中风、心力衰竭、静脉血栓栓塞、慢性阻塞性肺病、慢性肝病 疾病和骨质疏松症。然而，CHIP特异性促进这些的分子机制 疾病在很大程度上仍然未知。该提案的总体目标是将CHIP与 通过开发和应用统计和机器学习来发展相关疾病 NHLBI Trans-Omics for Precision Medicine（TOPMed），UK Biobank中的多组学数据方法，以及 Mass General Brigham Biobank（MGBB）具体而言，我提出以下目标。在目标1中，我将开发一个 一种统计方法，将同一途径中涉及的多种蛋白质结合起来，以改善发现， 促进基于蛋白质组学的关联分析的翻译见解。结合蛋白定量 通过该方法产生的性状将用于以下目的。在目标2中，我将研究 CHIP和每个CHIP驱动基因通过以下方式特异性地促进某些疾病：（1）鉴定 CHIP的签名，并量化对相关疾病的介导作用;（2）评估CHIP的 CHIP相关疾病的潜在修饰是通过涉及多种疾病的基因表达水平来实现的。 分子因素在目标3中，我将评估CHIP的进展如何促进相关疾病。我会 检查CHIP克隆数量和大小的纵向变化与事件之间的关联 疾病风险，以及在CHIP携带者中生成批量和单细胞RNA测序数据， 没有骨质疏松症，这是一种与CHIP密切相关但研究不足的疾病， 两组之间的表情。该项目的成功实施将确定 潜在的CHIP相关疾病风险，以优先考虑治疗目标并推进精准医学 目标.