Insights Into Immune-Related Diseases Born from Population Genomics

对群体基因组学产生的免疫相关疾病的见解

基本信息

批准号：
10449317
负责人：
Paul John Norman
金额：
$ 72万
依托单位：
UNIVERSITY OF COLORADO DENVER
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-07-06 至 2025-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10449317
关键词：
Address Affect African American African ancestry Algorithms Alleles Allergic Allergic Disease American Amerindian Antibody Formation Asthma Atopic Dermatitis Autoimmune Autoimmune Diseases Bioinformatics Cell physiology Cell-Mediated Cytolysis Cells Cessation of life Child Chromosome 19 Chromosome 6 Chronic Complex Country DNA Data Development Disease Education European Exhibits Extrinsic asthma Family Frequencies Genes Genetic Genetic Polymorphism Genetic Variation Genomic Segment Genomics Genotype Goals Graph HLA Antigens Haplotypes Health High Prevalence Hispanic Histocompatibility Antigens Class I Histocompatibility Antigens Class II Homozygote Human Human Genome Hypersensitivity IgE Immune Immune response Immunity Immunoglobulins Immunologics Incidence Individual Infection Inflammatory Intervention Killer Cells Knowledge Lead Link Major Histocompatibility Complex Major Histocompatibility Complex Gene Measures Mediating Medical Methodology Methods Natural Immunity Natural Killer Cells Nature Outcome Pathway interactions Patients Population Population Group Predisposition Pregnancy Prevalence Production Prognosis Property Proteins Receptor Cell Reproduction Resistance Resolution Respiratory physiology Role Serum Severities Signal Transduction Specificity Structure Study Subject Syndrome T-Lymphocyte Testing Transplantation Variant Work adaptive immunity allergic response arm bioinformatics pipeline causal variant chronic inflammatory lung disease cohort combinatorial cost effective cost estimate design flexibility genetic association genome-wide hematopoietic cell transplantation insight novel pathogen pressure receptor reproductive success response targeted sequencing tool user-friendly

项目摘要

The major histocompatibility complex (MHC) of chromosome 6 and the killer cell immunoglobulin-like receptor (KIR) region of chromosome 19 are among the most variable and medically important regions of the human genome. The MHC encodes the highly polymorphic human leukocyte antigens (HLA) that are central to immunity and reproduction, and another 140 genes, many with supporting roles in immunity. A subset of HLA allotypes interact with KIR, which are expressed by Natural Killer (NK) cells, modulating their activities in initiating and controlling the immune response. Specific alleles as well as compound genotypes of MHC and KIR have been implicated in susceptibility or resistance to infectious, allergic, inflammatory, and autoimmune diseases, as well as to outcomes of hematopoietic cell transplantation and reproductive success. Asthma is one of the most common inflammatory diseases affecting over 30 million Americans, with 5,000 deaths per year. Atopic dermatitis (AD) occurs in 20% of children and predisposes to asthma. Together they pose significant burden on the health and economy of the country, costing an estimated $82 billion per year. Common to these diseases are a strong genetic component, an environmental or infection trigger, and complex interplay between innate and adaptive immunity. Accordingly, there are long standing associations with MHC diversity and asthma susceptibility, which have been confirmed by recent large scale genome studies, but they remain poorly refined due to the complexity and difficulty of sequencing the region. For the same reasons, the KIR region has never been studied to high resolution in AD or asthma. To overcome difficulties in analyzing these complex genomic regions, we developed a targeted sequencing and bioinformatics approach to analyze MHC and KIR regions at high throughput and resolution. In Aim 1 we will use the methods to analyze the complete MHC genomic regions from 5,000 patients and 5,000 controls, investigating each gene as well as their pathways of interaction. We will study well defined cohorts of individuals from diverse backgrounds, focusing on African ancestry, which associates with the highest prevalence and poorest outcome. We will sequence the entire MHC with high accuracy to determine the full context of any variants associated with asthma susceptibility. In Aim 2 we will perform the first high resolution analysis of NK cell diversity in asthma, supported by directed functional analyses of the activity and specificity of NK cells in disease. By combining high- resolution analysis of KIR and HLA genes with known functional properties of these interactions, we will be able to determine the role of NK cell diversity in asthma. To enhance our methodology and solve the most difficult genomic structural variation, in Aim 3 we will design and implement the first methods to target long-read sequencing specifically to the MHC and KIR regions, and a bioinformatics pipeline to annotate and analyze the data. In doing so we will expand the MHC reference set and tools for large-scale analysis. Through these three Aims we will accelerate understanding of the natural immunity of atopic asthma and begin to identify novel targets for intervention

6 号染色体的主要组织相容性复合体 (MHC) 和杀伤细胞免疫球蛋白样受体 19 号染色体的 (KIR) 区域是人类变异最大、医学上最重要的区域之一基因组。 MHC 编码对免疫至关重要的高度多态性人类白细胞抗原 (HLA) 和生殖，以及另外 140 个基因，其中许多在免疫中发挥支持作用。 HLA 同种异型的一个子集与自然杀伤 (NK) 细胞表达的 KIR 相互作用，调节其启动和激活的活性控制免疫反应。 MHC 和 KIR 的特定等位基因以及复合基因型已被确定还涉及对传染性、过敏性、炎症性和自身免疫性疾病的易感性或抵抗力关于造血细胞移植和生殖成功的结果。哮喘是最常见的炎症性疾病之一，影响超过 3000 万美国人，导致 5000 人死亡每年。 20% 的儿童患有特应性皮炎 (AD)，并且容易患哮喘。他们一起摆出姿势对该国的健康和经济造成重大负担，估计每年造成 820 亿美元的损失。常见的这些疾病的原因包括强大的遗传因素、环境或感染触发因素以及复杂的相互作用先天性免疫和适应性免疫之间。因此，MHC 多样性与长期存在关联和哮喘易感性，这些已被最近的大规模基因组研究证实，但它们仍然存在由于对该区域进行测序的复杂性和难度，其精细化程度较差。出于同样的原因，KIR 地区从未对 AD 或哮喘进行过高分辨率研究。为了克服分析这些复杂基因组区域的困难，我们开发了一种靶向测序和以高通量和分辨率分析 MHC 和 KIR 区域的生物信息学方法。在目标 1 中我们将使用分析 5,000 名患者和 5,000 名对照者的完整 MHC 基因组区域的方法，调查每个基因以及它们的相互作用途径。我们将研究来自不同群体的明确定义的个体群体背景，重点关注非洲血统，这与最高的患病率和最差的结果相关。我们将以高精度对整个 MHC 进行测序，以确定与相关的任何变异的完整背景哮喘易感性。在目标 2 中，我们将对哮喘中的 NK 细胞多样性进行首次高分辨率分析，疾病中 NK 细胞的活性和特异性的定向功能分析支持。通过结合高通过对 KIR 和 HLA 基因以及这些相互作用的已知功能特性进行分辨率分析，我们将能够确定 NK 细胞多样性在哮喘中的作用。增强我们的方法论并解决最困难的问题基因组结构变异，在目标 3 中，我们将设计并实现第一个针对长读的方法专门针对 MHC 和 KIR 区域进行测序，以及用于注释和分析的生物信息学流程数据。在此过程中，我们将扩展 MHC 参考集和大规模分析工具。通过这三我们的目标是加快对特应性哮喘自然免疫的了解，并开始确定新的靶点进行干预