Poly-omic Study of Asthma Exacerbations in Diverse Populations

不同人群哮喘加重的多组学研究

基本信息

批准号：
10094077
负责人：
Keoki Williams
金额：
$ 74.48万
依托单位：
HENRY FORD HEALTH SYSTEM
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-02-01 至 2023-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10094077
关键词：
Accounting Address African American Age Allergic inflammation American Asthma Blood Candidate Disease Gene Caring Cessation of life Child Clinical Clinical Data Cohort Studies Costa Rica DNA analysis Data Detection Disease Dizygotic Twins Emergency department visit Ethnic Origin European Event Exhalation Expenditure Facilities and Administrative Costs Future Genes Genetic Genetic Markers Genetic Predisposition to Disease Genetic Structures Genetic study Genomics Genotype Glean Helper-Inducer T-Lymphocyte Heritability Hospitalization IgE Individual Investigation Latino Life Maps Mass Spectrum Analysis Measures Medical Minority Minority Groups Monozygotic twins Morbidity - disease rate National Heart, Lung, and Blood Institute Nitric Oxide Pathway interactions Patient Self-Report Patients Personal Financing Pharmaceutical Preparations Phenotype Population Group Population Heterogeneity Predisposition Prevalence Protein Analysis Proteins Proteome Proteomics Quality of life Quantitative Trait Loci RNA Sequences RNA analysis Recording of previous events Research Design Risk Sampling Schools Serum Serum Proteins Surveys Time Trans-Omics for Precision Medicine Variant Whole Blood Work admixture mapping asthma exacerbation cohort cost differential expression economic impact experience gene product genetic epidemiology genetic risk factor genetic variant genome wide association study high risk periostin programs prospective racial disparity respiratory risk variant societal costs trait transcriptome transcriptomics translational genetics translational genomics whole genome

项目摘要

Asthma exacerbations contribute to considerable disease morbidity and account for nearly half of all asthma- related costs. Moreover, certain population groups, such as African American and Latino individuals, suffer disproportionately from these complications with rates of asthma-related emergency department visits, hospitalizations, and deaths nearly 3-5 times higher than those of European Americans. There are multiple reasons to believe that individuals who suffer severe exacerbations are genetically predisposed: 1) prior events are among the strongest predictors of future exacerbations, 2) genetic ancestry has been shown to be an independent predictor of exacerbations, and 3) calculations of exacerbation heritability suggest that 30-55% of this trait’s variance may be attributed to additive genetic effects. Nevertheless, we do not currently have genetic biomarkers that can be used clinically to reliably predict susceptibility to asthma exacerbations. Such measures could transform asthma care if they resulted in the early recognition and appropriate treatment of individuals at risk. In this application, we will utilize the enormous amount of whole genome sequence (WGS) data that is being generated on our Asthma Translational Genomics Collaborative (ATGC) as part of the NHLBI’s Trans-Omic Precision Medicine (TOPMed) Program. The ATGC comprises 8 cohort studies and 10,819 patients with asthma (7,530 African Americans and 3,081 Latinos). The Genetic Epidemiology of Asthma in Costa Rica (CRA) cohort with its WGS data will also participate (n=1,765). In Aim 1, we will focus on the genomics of asthma exacerbations through the following sub-aims: a) refine our estimates of exacerbation heritability using a WGS data; b) use admixture mapping to identify chromosomal regions likely to harbor risk variants for exacerbations; c) fine-map the aforementioned regions for risk variants using available WGS data; d) replicate these associations in other ATGC cohorts and in the CRA cohort; and e) assess variants for their association with future exacerbations using available prospective clinical data. In Aim 2, we will focus on the transcriptomics of asthma exacerbations. Namely, we will use RNA-sequence data derived from the whole blood transcriptome to identify genes whose expression associated with severe exacerbations (Aim 2a), and we will identify genes whose expression is associated with the genotype of variants identified in Aim 1 (Aim 2b). Aim 3 will focus on the proteomics of asthma exacerbations. Banked serum will be used to assess the proteome of individuals from phenotype extremes (i.e., serum collected from individuals prior to a severe exacerbation vs. serum from individuals with asthma who don’t experience exacerbations). Using mass spectrometry, we will broadly assess serum for proteins differentially expressed between these groups (i.e., an untargeted proteomic approach), and we will use the information gleaned from the genomic, transcriptomic, and untargeted proteomic analyses to assess specific proteins (i.e., a targeted proteomic approach) for expression differences in additional groups of individuals at phenotype extremes.

哮喘恶化导致相当大的疾病发病率，占所有哮喘的近一半。此外，某些人群，例如非洲裔美国人和拉丁美洲人，也遭受了相关费用。这些并发症与哮喘相关急诊就诊的比例不成比例，住院率和死亡人数比欧洲裔美国人高出近3-5倍。有理由相信遭受严重恶化的个体具有遗传倾向：1）先前的事件是未来病情恶化的最强预测因子之一，2) 遗传血统已被证明是急性加重的独立预测因素，3) 急性加重遗传力的计算表明，30-55% 这种性状的差异可能归因于附加遗传效应，但我们目前还没有。可以在临床上使用的遗传生物标志物来可靠地预测哮喘恶化的易感性。如果采取的措施能够早期识别和适当治疗，则可以改变哮喘护理在此应用中，我们将利用大量的全基因组序列 (WGS)。作为哮喘转化基因组学合作组织 (ATGC) 的一部分，我们正在生成数据 NHLBI 的跨组学精准医学 (TOPMed) 计划包括 8 项队列研究和 10,819 名哮喘患者（7,530 名非裔美国人和 3,081 名拉丁裔）。哥斯达黎加哮喘 (CRA) 队列及其 WGS 数据也将参与（n=1,765）。在目标 1 中，我们将重点关注。通过以下子目标对哮喘实验的基因组学进行研究：a）完善我们的估计使用 WGS 数据确定恶化遗传性；b) 使用混合图谱来识别可能发生恶化的染色体区域 c) 使用可用的信息来精细绘制所提到的风险变异区域； WGS 数据；d) 在其他 ATGC 队列和 CRA 队列中复制这些关联；e) 评估在目标 2 中，我们使用现有的前瞻性临床数据来确定其与未来恶化的关联。将重点关注哮喘恶化的转录组学，即我们将使用衍生的 RNA 序列数据。从全血转录组中识别其表达与严重恶化相关的基因（目标 2a），我们将鉴定其表达与中鉴定的变异体的基因型相关的基因。目标 1（目标 2b）将重点关注哮喘恶化的蛋白质组学。从极端表型评估个体的蛋白质组（即，在实验前从个体收集的血清）严重恶化与未经历恶化的哮喘患者的血清相比）。光谱分析法，我们将广泛评估血清中这些组之间差异表达的蛋白质（即，非靶向蛋白质组学方法），我们将使用从基因组、转录组学、和非靶向蛋白质组分析来评估特定蛋白质（即靶向蛋白质组方法）在表型极端的其他个体组中的表达差异。