Structural Variation and Hematological Traits

结构变异和血液学特征

• 批准号: 10657020
• 负责人: Daniel Evan Bauer
• 金额: $ 76.56万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10657020
• 关键词: 3-Dimensional; Algorithms; Area; Atlases; Biological; Biological Models; Biology; Blood; Blood Cells; Blood Platelets; Blood coagulation; Bone Marrow Cells; Cardiovascular Diseases; Cardiovascular system; Cells; Cellular biology; Chromatin; Circulation; Clinical; Clinical Trials Design; Collaborations; Collection; Complex; Computer software; DNA Sequence; Data; Data Set; Disease; Disease Outcome; Ensure; Erythrocytes; Experimental Designs; Genes; Genetic; Genetic study; Genome; Genomic Segment; Genomics; Genotype; Heart Diseases; Hematological Disease; Hematology; Hematopoiesis; Hematopoietic; Hemostatic function; Heritability; Human; Human Biology; Immune response; Individual Differences; Inflammation; Leadership; Leukocytes; Lung; Lung diseases; Measures; Methodology; Methods; Modeling; Molecular; Multiomic Data; National Heart, Lung, and Blood Institute; National Human Genome Research Institute; Outcome; Participant; Pathogenesis; Phase; Phenotype; Play; Population; Regulation; Repetitive Sequence; Research; Research Personnel; Resources; Role; Sample Size; Sampling; Sleep; Source; Structure; Technology; Testing; Thrombosis; Time; Trans-Omics for Precision Medicine; Variant; alpha Globin; biobank; candidate validation; clinical diagnosis; clinically relevant; cohort; database of Genotypes and Phenotypes; epidemiology study; epigenome editing; functional genomics; genetic architecture; genetic association; genome editing; genome sequencing; genome wide association study; genome-wide; genome-wide analysis; genomic variation; improved; insight; interdisciplinary approach; multi-ethnic; novel; oxygen transport; precision medicine; programs; stem cells; trait; transcriptome sequencing; translational genetics; treatment response; venous thromboembolism; whole genome; working group

Red blood cells, white blood cells, and platelets are important for the clinical diagnosis of intrinsic blood cell and hematopoietic disorders, and also as predictors of various heart, lung, and blood disease outcomes. Moreover, hematologic quantitative traits are highly heritable and serve as a model system for studying the genetic architecture of complex traits. While significant strides in understanding the genetic basis of hematological traits have been made over the past decade, the wealth of whole genome sequencing (WGS) data from emerging resources such as the NHLBI Trans-Omics for Precision Medicine (TOPMed) program provides an unprecedented opportunity to gain further insight in several key areas, including the role of structural variants (SVs). While a few common SVs (e.g., α-globin) are known to be associated with blood cell traits, a more systematic and agnostic genome-wide search for SVs in large samples is required to identify new biology. The centralized availability of deeply sequenced DNA from the NHLBI TOPMed and the NHGRI Centers for Common Disease Genomics (CCDG) programs, along with genome-wide data from UK Biobank and other cohorts, allows for full characterization of SVs genome-wide at population-scale. By improving the accuracy of genome-wide SV calling for WGS data as implemented in our new Genvisis software package and by validating candidate causal SVs using state-of-the-art gene-editing technologies in hematopoietic cells, our interdisciplinary approach will facilitate the translation of genetic association findings into mechanistic insights, discover new biology underlying hematopoiesis, and ultimately identify factors that account for individual differences in pathobiology or response to treatments. In Aim 1, using WGS data from TOPMed and CCDG participants, we will apply novel methodology to generate high-quality and more accurate SV calls than the SV calling algorithms currently available for both WGS and existing array data. In Aim 2, we will use the newly generated SV calls to conduct single-variant and gene-based segmental association analyses of SVs with blood cell traits and related clinical outcomes in up to 570,319 participants. Association findings will be replicated in up to 760,000 participants in populations/studies not used in the discovery phase. SVs that are significantly associated with blood cell traits will subsequently be tested for association with other blood disorders including clonal hematopoiesis of indeterminate potential (CHIP) and VTE. In Aim 3, targeted long-range sequencing will be performed in selected samples to precisely localize newly identified blood trait-associated SVs in complex genomic regions. We will also perform functional genomic annotation of replicated blood cell trait-SV associations followed by state-of-the art gene-editing approaches to understand novel mechanisms underlying genetic regulation of hematopoiesis. This model integrative approach to advancing precision medicine research in heart, lung, and blood diseases will demonstrate for the first time the role of SVs in the genetic architecture of hematologic traits and contribute to a better understanding of hematopoiesis and pave the way for new research into Precision Medicine for blood diseases.

红细胞，白细胞和血小板对于内在血细胞的临床诊断和 造血疾病，也作为各种心脏，肺和血液疾病结局的预测指标。而且， 血液学定量特征是高度遗传的，并且是研究通用的模型系统 复杂特征的建筑。在理解血液学特征的遗传基础方面的显着步骤 在过去的十年中制作了整个基因组测序（WGS）数据的财富 诸如NHLBI跨媒体学的资源（TOPMED）计划提供了 前所未有的机会，可以在几个关键领域获得进一步的见解，包括结构变体的作用 （SVS）。虽然已知一些常见的SV（例如α-珠蛋白）与血细胞性状相关，但更多 需要在大型样本中对SVS进行系统和不可知论的全基因组搜索才能识别新的生物学。这 来自NHLBI的深度测序DNA的集中式可用性和NHGRI中心的共同供应 疾病基因组学（CCDG）计划，以及来自英国生物库和其他同类群体的全基因组数据，允许 为了在人口尺度上全面表征SVS全基因组。通过提高全基因组SV的准确性 呼吁在我们的新genvisis软件包中实现的WGS数据，并通过验证候选人催化 使用造血细胞中最先进的基因编辑技术的SVS，我们的跨学科方法将 促进将遗传关联发现转化为机械见解，发现新的生物学的基础 造血，并最终确定说明病原体或反应个体差异的因素 进行治疗。在AIM 1中，使用来自TopMed和CCDG参与者的WGS数据，我们将采用新方法 与当前可用于的SV调用算法相比，要生成高质量和更准确的SV调用 WGS和现有数组数据。在AIM 2中，我们将使用新生成的SV调用进行单变量和 基于基因的SVS基因分段分析与血细胞性状和相关临床结果的分析 570,319名参与者。协会发现将在人口/研究中最多760,000名参与者中复制 在发现阶段不使用。与血细胞性状显着相关的SV随后将是 测试与其他血液疾病的关联，包括不确定潜力的克隆造血（CHIP） 和VTE。在AIM 3中，将在选定的样品中进行针对的远程测序，以精确本地化 新鉴定的复杂基因组区域中与血状特征相关的SV。我们还将执行功能基因组 复制的血细胞性状SV关联的注释，然后是最先进的基因编辑方法 了解造血的遗传调节基础的新型机制。这种模型集成方法 在心脏，肺和血液疾病中推进精确医学研究将首次证明 SV在血液学特征的遗传结构中的作用，并有助于更好地理解 造血为血液疾病精确医学的新研究铺平了道路。