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: 8724089
• 负责人: Blanca E Himes
• 金额: $ 23.7万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2016-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8724089
• 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; abstracting; 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

ABSTRACT 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.

摘要 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， 这是多种遗传和环境因素复杂相互作用的结果。许多研究都有 寻找导致哮喘易感性的个体基因变异，但彻底了解 对哮喘的遗传基础的研究尚未实现。我们的主要假设是基因结构 通过考虑多个基因并合并，可以更好地理解潜在的哮喘易感性 多种来源的基因组数据，包括人类哮喘和小鼠呼吸道高反应性(AHR) 数据。这一假设将通过具体的目标来解决，在这些目标中，我们将：(1)识别 通过定位近交系AHR相关区域使人类易患哮喘并调节人类AHR 小鼠品系与人类全基因组关联数据，(2)利用基因表达数据，已知蛋白质-蛋白质 相互作用和已知的功能通路，以加强对哮喘和AHR基因变异的寻找 人类，以及(3)整合单个人类遗传变异，以创建一个多变量预测模型 哮喘。由特定目标1和2确定的新变种将通过独立的复制来验证 人类人口的哮喘患者。在特定目标3中创建的预测模型将通过 哮喘患者独立人群中的复制和预测。通过完成特定的目标， 我们希望在开发哮喘遗传学的综合模型方面取得进展， 尤其是以呼吸道反应性增加为特征的哮喘。