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.

红血球、白血球和血小板对于临床诊断固有血细胞和 造血功能紊乱，也是各种心、肺和血液疾病结局的预测因子。此外， 血液学数量性状具有高度的遗传性，可作为研究遗传的模式系统。 具有复杂特征的建筑。虽然在理解血液学特征的遗传基础方面取得了重大进展 在过去的十年里，来自新兴的全基因组测序(WGS)数据的丰富 NHLBI Trans-Omics for Precision Medicine(TOPMed)计划等资源提供了 在几个关键领域获得进一步洞察的前所未有的机会，包括结构变体的作用 (SVS)。虽然已知一些常见的SVs(例如α-珠蛋白)与血细胞特性有关，但更多的 为了识别新的生物学，需要在大样本中系统地和不可知的全基因组搜索SVS。这个 NHLBI TOPMed和NHGRI公共中心深度测序DNA的集中可用性 疾病基因组学(CCDG)计划，以及来自英国生物库和其他队列的全基因组数据，允许 以在种群规模上全面描述SVS全基因组。通过提高全基因组SV的准确性 调用我们新的Genvisis软件包中实现的WGS数据，并通过验证候选原因 在造血细胞中使用最先进的基因编辑技术，我们的跨学科方法将 促进将遗传关联发现转化为机械性见解，发现新的生物学基础 造血，并最终确定导致病理生物学或反应的个体差异的因素 为治疗干杯。在目标1中，使用TOPMed和CCDG参与者的WGS数据，我们将应用新的方法 生成比目前两者可用的SV呼叫算法更高质量和更准确的SV呼叫 WGS和现有数组数据。在目标2中，我们将使用新生成的SV调用进行单变量和 以基因为基础的SVS与血细胞性状和相关临床结局的相关性分析 570,319名参与者。该协会的发现将在人口/研究中的多达76万名参与者中重复 在发现阶段不使用。与血细胞特征显著相关的SVS随后将 测试与其他血液疾病的相关性，包括克隆性造血不确定潜能(CHIP) 和VTE。在目标3中，将在选定的样本中执行定向远程测序，以精确定位 在复杂基因组区域新发现的与血液性状相关的SVS。我们还将进行功能基因组学 复制的血细胞性状-SV关联的注释以及最新的基因编辑方法 了解造血基因调控的新机制。这种模式综合的方法 推进心、肺、血疾病的精准医学研究将首次演示 SVS在血液学特征遗传结构中的作用并有助于更好地理解 为血液病精准医学的新研究铺平道路。