INTEGRATIVE GENOMICS APPROACHES TO MODEL THE GENETIC ARCHITECTURE OF ASTHMA

综合基因组学方法来模拟哮喘的遗传结构

• 批准号: 8189641
• 负责人: Blanca E Himes
• 金额: $ 13.78万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-15 至 2013-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8189641
• 关键词: Address; Affect; American; Architecture; Asthma; Biological; Bronchodilator Agents; Chronic; Chronic Obstructive Airway Disease; Clinical; Complex; Data; Data Sources; Development; Disease; Environment; Environmental Risk Factor; Gene Expression; Genes; Genetic; Genetic Models; Genomics; Human; Human Genetics; Human Genome; Inbred Strains Mice; Individual; Lead; Lung diseases; Machine Learning; Maps; Methods; Modeling; Mus; Pathway interactions; Patients; Population; Predisposition; Risk; Source; Surveys; Testing; Variant; Work; airway hyperresponsiveness; base; computer based statistical methods; genetic variant; genome wide association study; improved; insight; mouse development; mouse genome; novel; predictive modeling; prognostic; protein protein interaction; response; trait

DESCRIPTION (provided by applicant): Asthma, a chronic respiratory disease affecting over 20 million Americans and 300 million people worldwide, results from the complex interaction of multiple genetic and environmental factors. Many studies have searched for individual genetic variants that contribute to asthma susceptibility, but a thorough understanding of the genetic basis of asthma has not been achieved. Our main hypothesis is that the genetic architecture underlying asthma susceptibility can be better understood by considering multiple genes and incorporating multiple sources of genomic data, including human asthma and mouse airways hyperresponsiveness (AHR) data. This hypothesis will be addressed via specific aims in which we will: (1) identify genetic variants that predispose humans to asthma and modulate human AHR by mapping regions associated with AHR in inbred strains of mice to human genome-wide association data, (2) use gene expression data, known protein-protein interactions, and known functional pathways to enhance the search for asthma and AHR genetic variants in humans, and (3) integrate individual human genetic variants to create a multivariate predictive model of asthma. Novel variants identified by Specific Aims 1 and 2 will be validated by replication in independent human populations of asthmatics. The predictive model created in Specific Aim 3 will be validated through replication and prediction in independent human populations of asthmatics. By completing the specific aims, we hope to make progress towards the development of a comprehensive model of the genetics of asthma, particularly of asthma characterized by increased airways responsiveness. PUBLIC HEALTH RELEVANCE: By completing this proposal, we hope to identify genetic variants that modulate asthma risk. Identifying such variants could provide biological insights that may eventually lead to a better understanding of asthma. Additionally, we will create a predictive model of asthma, which could potentially lead to the development of a clinical prognostic test of who is at risk for developing asthma.

描述(申请人提供)：哮喘是一种慢性呼吸道疾病，影响着2000多万美国人和全球3亿人，是多种遗传和环境因素复杂相互作用的结果。许多研究都在寻找导致哮喘易感性的个体基因变异，但还没有彻底了解哮喘的遗传基础。我们的主要假设是，通过考虑多个基因并结合包括人类哮喘和小鼠呼吸道高反应性(AHR)数据在内的多种基因组数据来源，可以更好地了解哮喘易感性的遗传结构。我们将通过特定的目标来解决这一假说，其中我们将：(1)通过将近交系小鼠中与AHR相关的区域与人类基因组范围的关联数据进行映射，来识别使人类易患哮喘并调节人类AHR的基因变异；(2)利用基因表达数据、已知的蛋白质-蛋白质相互作用和已知的功能途径来加强对人类哮喘和AHR基因变异的搜索；以及(3)整合单个人类基因变异，以创建哮喘的多变量预测模型。由特定的AIMS 1和2确定的新变种将通过在独立的哮喘患者人群中复制来验证。在特定目标3中创建的预测模型将通过在独立的哮喘患者人群中进行复制和预测来验证。通过完成具体目标，我们希望朝着哮喘遗传学的全面模式的发展取得进展，特别是以呼吸道反应性增强为特征的哮喘。 公共卫生相关性：通过完成这项提案，我们希望确定调节哮喘风险的基因变异。识别这些变异可以提供生物学见解，最终可能导致对哮喘的更好理解。此外，我们将创建哮喘的预测模型，这可能会导致开发一种临床预后测试，以确定谁有发展成哮喘的风险。