INTEGRATIVE GENOMICS OF CLINICAL SUBTYPES IN COPDGENE

COPDGENE 中临床亚型的综合基因组学

• 批准号: 8965166
• 负责人: CRAIG P HERSH
• 金额: $ 91.16万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2019-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8965166
• 关键词: Acute; Address; Affect; Biological; Biological Assay; Biological Markers; Blood; Blood specimen; Chest; Chronic Obstructive Airway Disease; Clinical; Communities; Complement; Complex; Data; Data Set; Diagnosis; Disease; Environmental Exposure; Functional disorder; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Genes; Genetic; Genetic Variation; Genomics; Genotype; Goals; Guidelines; Heterogeneity; Image; Lead; Learning; Lung; Machine Learning; Malignant Neoplasms; Measures; Messenger RNA; Methods; MicroRNAs; Molecular; Molecular Profiling; Non-Malignant; Parents; Pathway interactions; Patients; Phase; Phenotype; Population Study; Pulmonary Emphysema; Quantitative Trait Loci; RNA; RNA Sequences; Recording of previous events; Research Personnel; Resources; Sampling; Sepsis; Single Nucleotide Polymorphism; Spirometry; Structure of parenchyma of lung; Subgroup; Symptoms; Techniques; Testing; Tissue Sample; Transcript; X-Ray Computed Tomography; base; clinically relevant; differential expression; disease classification; disease natural history; disorder subtype; exome; experience; follow-up; genetic epidemiology; genome sequencing; genome wide association study; genome-wide; improved; novel; peripheral blood; precision medicine; public health relevance; rare variant; response; small airways disease; trait; transcriptome sequencing

 DESCRIPTION (provided by applicant): Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease, which is not captured by the degree of airflow limitation measured by spirometry. One of the goals of the Genetic Epidemiology of COPD Study (COPDGene) is to define meaningful subgroups of COPD, leading to a new disease classification. These clinical and statistical approaches are utilizing the extensive phenotype data collected in COPDGene, including chest CT scans. The "Integrative Genomics of Clinical Subtypes in COPDGene" study will use RNA sequencing and miRNA for subtyping, different from the main COPDGene study. The hypothesis is that different COPD subtypes will have distinct pathophysiology, which can be identified through gene expression signatures, miRNA profiling and integrative genomics studies. Genomewide genotyping data can be used to test for associations with the subtypes. However, traditional genomewide association studies may be underpowered to detect subtype effects. Gene expression is an important intermediate phenotype between genotypes and complex traits, and can be easily assayed in peripheral blood. In this proposal, we will use expression quantitative trait locus (eQTL) analysis to identify functional single nucleotide polymorphisms (SNPs) affecting expression of differentially expressed genes and miRNAs. We will address the following Specific Aims: (1) Gene expression profiling in COPD subtypes: We will collect peripheral blood RNA samples from subjects in COPDGene, perform RNA sequencing and miRNA profiling and test for differentially expressed transcripts and miRNAs for two clinical subtype comparisons: (A) emphysema-predominant vs. airway-predominant COPD and (B) frequent vs. infrequent acute exacerbations. We will validate the blood associations by RNA-sequencing in COPD lung tissue samples. (2) Molecular subtypes of COPD: We will use statistical and machine learning methods to define molecular subtypes based on the RNA sequencing and miRNA data. We will validate the molecular subtypes with the clinical, imaging and longitudinal follow-up data. (3) Integrative genomics of COPD subtypes: We will integrate the gene and miRNA expression data with genomewide SNP data to identify eQTL SNPs associated with transcript levels of the differentially expressed and subtype-defining genes and miRNAs from Aims 1 and Aim 2. The eQTL SNPs will be tested for association with the clinical subtypes in the full COPDGene Study population. This proposal will be distinct yet complement the parent COPDGene Study by using mRNA and miRNA expression data to identify genetic influences on COPD subtypes, which could identify biomarkers of disease subtypes or novel pathways and targets, moving towards the goal of precision medicine in COPD. The gene expression, miRNA and eQTL datasets will serve as resources for COPDGene and the community of COPD investigators.

 描述（由申请人提供）：慢性阻塞性肺病 (COPD) 是一种异质性疾病，无法通过肺活量测定法测量的气流受限程度来捕获。COPD 遗传流行病学研究 (COPDGene) 的目标之一是定义。这些临床和统计方法正在利用 COPDGene 中收集的广泛表型数据，包括胸部 CT 扫描。 COPDGene 中的临床亚型基因组学”研究将使用 RNA 测序和 miRNA 进行亚型分型，与 COPDGene 主要研究不同。假设不同的 COPD 亚型将具有不同的病理生理学，可以通过基因表达特征、miRNA 分析和综合基因组学来识别全基因组基因分型数据可用于测试与亚型的关联，但是，传统的全基因组关联研究可能不足以检测基因表达的影响。基因型和复杂性状之间的重要中间表型，可以在外周血中轻松检测。在本提案测定中，我们将使用表达数量性状基因座（eQTL）分析来识别影响差异表达基因和表达的功能性单核苷酸多态性（SNP）。我们将解决以下具体目标： (1) COPD 亚型的基因表达谱分析：我们将在 COPDGene 中收集受试者的外周血 RNA 样本，进行 RNA 测序和 miRNA 分析并测试。两种临床亚型比较的差异表达转录本和 miRNA：(A) 肺气肿为主型与气道为主型 COPD 和 (B) 频繁与不频繁急性加重我们将通过 COPD 肺组织样本中的 RNA 测序来验证血液关联。 (2) COPD的分子亚型：我们将使用统计和机器学习方法根据RNA测序和miRNA数据来定义分子亚型。 (3) COPD亚型的整合基因组学：我们将基因和miRNA表达数据与全基因组SNP数据整合，以识别与目标1和目标2中差异表达和亚型定义基因和miRNA的转录水平相关的eQTL SNP。将在整个 COPDGene 研究人群中测试 SNP 与临床亚型的关联。该提案将是独特的，但又是对父提案的补充。 COPDGene 研究通过使用 mRNA 和 miRNA 表达数据来识别对 COPD 亚型的遗传影响，从而可以识别疾病亚型的生物标志物或新的通路和靶点，朝着 COPD 精准医疗的目标迈进。基因表达、miRNA 和 eQTL 数据集将服务于 COPD 的精准医疗。作为 COPDGene 和 COPD 研究人员社区的资源。