Gene-Environment Interactions with Ozone in Experimental Asthma

实验性哮喘中基因-环境与臭氧的相互作用

• 批准号: 9266695
• 负责人: Samir Kelada
• 金额: $ 1.13万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-01-05 至 2019-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9266695
• 关键词: Acute; Address; Affect; Air Pollutants; Air Pollution; Alleles; Allergens; Animal Model; Applications Grants; Asthma; Bioinformatics; Biological; CD4 Positive T Lymphocytes; Candidate Disease Gene; Cardiovascular Diseases; Cell Count; Child health care; Data; Dendritic Cells; Development; Environmental Health; Epidemiology; Exposure to; Gene Expression; Genes; Genome; Goals; Health; Heritability; Hour; House Dust Mite Allergens; Human; Hypersensitivity; IgE; Immune; Immune response; Immune system; Inbred Strain; Inbreeding; Incidence; Individual; Link; Lung; Lung diseases; Maps; Measures; Mediating; Modeling; Molecular; Mus; National Institute of Environmental Health Sciences; Neutrophil Infiltration; Neutrophilia; Outcome; Oxidative Stress; Ozone; Pathway interactions; Phenotype; Physiological; Population; Population Heterogeneity; Predisposition; Process; Pyroglyphidae; Quantitative Trait Loci; Recombinants; Research; Research Personnel; Risk; Rodent Model; Sampling; Serum; Statistical Models; Strategic Planning; Testing; Training; Transcript; Variant; air filter; airway hyperresponsiveness; airway inflammation; allergic airway disease; base; cost; design; disease phenotype; gene environment interaction; genetic predictors; genetic resource; genome-wide; genomic predictors; immune function; innovation; insight; macrophage; methacholine; mouse model; novel; ozone exposure; population based; predicting response; response; transcriptome sequencing

 DESCRIPTION (provided by applicant): Exposure to air pollution is associated with adverse health outcomes and people with pre- existing cardiovascular or respiratory disease are more susceptible. In particular, exposure to ozone is associated with exacerbations of asthma. There is also evidence from several studies that exposure to ozone is associated with the development of asthma, though these findings are not always consistent. Gene-environment interactions (GxE) have been proposed as an explanation for the inconsistency of the ozone -to-asthma association across studies. The investigators submit that by identifying these GxE in a mouse model of ozone-induced allergic airway disease (AAD) using an unbiased, genome-wide approach they can gain insight into the mechanisms by which ozone affects pulmonary and immune responses in the lung. To identify these GxE, the investigators will leverage a new mouse genetics resource, the Collaborative Cross (CC). The CC consists of a panel of recombinant inbred lines derived from eight-way crosses using a diverse set of inbred strains and provides ideal features for studying GxE and identifying the underlying molecular processes. Based on prior studies showing that ozone primes the immune system towards an allergy-prone phenotype, the investigators have designed a study in which mice are first exposed to ozone (or filtered air), and then are subjected to house dust mite (HDM) allergen sensitization and challenge (ozone-to-HDM) through the airway. In Aim 1, the investigators will characterize population level variation and heritability of AAD phenotypes in response to ozone-to-HDM among 100 CC lines. Based on this distribution, they will identify strains that have extreme responses (high and low) to ozone-to-HDM. These strains will be used in Aim 2 to test whether responses to ozone alone (neutrophilia and airway hyper-responsiveness) predict response to ozone-to-HDM and whether known effects of ozone on several immune parameters (macrophage, CD4+ T-cell, and dendritic cell number and activation status) are correlated with response to ozone-to-HDM. In Aim 3, the investigators will identify novel genetic and genomic predictors of response to ozone-to-HDM using genome- wide approaches. Specifically, they will measure lung gene expression using RNA-sequencing, and identify quantitative trait locus (QTL) and gene expression QTL (eQTL). Finally, by merging the QTL and eQTL data, the investigators will identify candidate genes for QTL using advanced statistical modeling and bioinformatic approaches. In summary, this grant application utilizes innovative and yet feasible approaches to identify genes and pathways that mediate the effect of ozone on subsequent response to allergen, and the results will offer new avenues of research into the health effects of ozone.

 描述（由申请人提供）：暴露于空气污染与不良健康结果相关，患有心血管或呼吸系统疾病的人更容易受到影响。特别是，接触臭氧与哮喘恶化有关。几项研究也有证据表明，接触臭氧与哮喘的发生有关，尽管这些发现并不总是一致。基因-环境相互作用（GxE）已被提议作为臭氧与哮喘关联的不一致的解释。研究人员提出，通过使用公正的全基因组方法在臭氧诱导的过敏性气道疾病 (AAD) 小鼠模型中识别这些 GxE，他们可以深入了解臭氧影响肺部和肺部免疫反应的机制。为了识别这些 GxE，研究人员将利用一种新的小鼠遗传资源，即协作交叉 (CC)。 CC 由一组重组自交系组成，这些重组自交系源自使用多种自交系的八向杂交，并为研究 GxE 和识别潜在的分子过程提供了理想的特征。先前的研究表明，臭氧会使免疫系统产生易过敏的表型，研究人员设计了一项研究，其中小鼠首先暴露于臭氧（或过滤空气），然后通过气道接受屋尘螨（HDM）过敏原致敏和挑战（臭氧到HDM）。在目标 1 中，研究人员将描述 100 个 CC 系中 AAD 表型对臭氧至 HDM 反应的群体水平变异和遗传力。根据这种分布，他们将识别对臭氧-HDM 有极端反应（高和低）的菌株。这些菌株将用于目标 2，以测试仅对臭氧的反应（中性粒细胞增多和气道高反应性）是否可以预测对臭氧-HDM 的反应，以及臭氧对多种免疫参数（巨噬细胞、CD4+ T 细胞、树突状细胞数量和激活状态）的已知影响是否与对臭氧-HDM 的反应相关。在目标 3 中，研究人员将使用全基因组方法确定对臭氧-HDM 反应的新遗传和基因组预测因子。具体来说，他们将使用 RNA 测序测量肺基因表达，并识别数量性状基因座 (QTL) 和基因表达 QTL (eQTL)。最后，通过合并 QTL 和 eQTL 数据，研究人员将使用先进的统计模型和生物信息学方法识别 QTL 的候选基因。总之，这项拨款申请利用创新且可行的方法来识别介导臭氧对随后过敏原反应的影响的基因和途径，其结果将为研究臭氧对健康的影响提供新的途径。 臭氧。