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（由申请人提供）：哮喘是一种慢性呼吸道疾病，影响了超过2000万美国人和全球3亿人，这是由于多种遗传和环境因素的复杂相互作用而引起的。许多研究都搜索了有助于哮喘易感性的个体遗传变异，但是尚未实现对哮喘遗传基础的透彻理解。我们的主要假设是，可以通过考虑多个基因并结合包括人类哮喘和小鼠气道高反应性（AHR）数据来更好地理解哮喘易感性的遗传结构。该假设将通过特定目的来解决：（1）确定遗传变异，使人类诱发哮喘，并通过与AHR相关的区域绘制与AHR相关的区域来调节人类AHR的遗传变异，以对人类全基因组的缔合数据，（2）使用基因表达，使用基因数据，可增强蛋白质的相互作用，并以遗传素的方式和AHR searive和AHR的search和AHR的SEROT，并在HOLLENCLANE上进行了遗传，并在HOLLENAN中进行了遗传，并在HOLLEN中造成了遗传素质的搜索，并使用遗传素质的searim andmane search，shore和AHR。 （3）整合人类遗传变异，以创建哮喘的多元预测模型。特定目标1和2确定的新型变体将通过独立人类哮喘患者的复制来验证。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来验证。通过完成具体目标，我们希望取得进步，以发展哮喘的遗传学综合模型，尤其是以增强气道反应性为特征的哮喘的遗传学模型。 公共卫生相关性：通过完成该提案，我们希望确定调节哮喘风险的遗传变异。识别这种变体可以提供生物学见解，最终可能会更好地了解哮喘。此外，我们将创建一个哮喘的预测模型，这可能会导致对谁面临哮喘风险的临床预后测试的发展。