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.

抽象的 哮喘是一种慢性呼吸道疾病，影响了全球超过2000万美国人和3亿人 来自多个遗传和环境因素的复杂相互作用的结果。许多研究有 搜索有助于哮喘易感性的单个遗传变异，但彻底理解 尚未实现哮喘的遗传基础。我们的主要假设是遗传结构 可以通过考虑多个基因并纳入潜在的哮喘易感性来更好地理解 基因组数据的多种来源，包括人哮喘和小鼠气道高反应性（AHR） 数据。该假设将通过特定目的来解决：（1）确定遗传变异的遗传变异 通过与AHR相关的近交区域的映射区域来调节哮喘的诱因，并调节人类AHR 小鼠菌株与人类全基因组关联数据，（2）使用基因表达数据，已知蛋白质蛋白 相互作用以及已知的功能途径，以增强对哮喘和AHR遗传变异的搜索 人类和（3）整合人类遗传变异，以创建一个多元预测模型 哮喘。特定目标1和2确定的新型变体将通过独立复制来验证 哮喘患者的人口。特定目标3中创建的预测模型将通过 哮喘患者独立人群的复制和预测。通过完成具体目标， 我们希望在发展哮喘遗传学的综合模型方面取得进步 特别是哮喘的特征是气道反应性提高。