Poly-omic Study of Asthma Exacerbations in Diverse Populations

不同人群哮喘加重的多组学研究

• 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
• 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

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.

哮喘恶化导致疾病的大量发病率，几乎占所有哮喘的一半 相关费用。此外，某些人口群体，例如非裔美国人和拉丁裔人， 与哮喘相关的急诊科的发生率不成比例地从这些并发症中， 住院和死亡的死亡几乎是欧美人的3-5倍。有多个 认为遭受严重加重的个人通常会倾向于：1）事件 是未来加剧的强大预测指标，2）遗传血统已被证明是 加重的独立预测因子，3）加重遗传的计算表明30-55％ 该性状的差异可能归因于加性遗传效应。但是，我们目前没有 可以在临床上用于可靠的遗传生物标志物预测哮喘加重的敏感性。这样的 措施是否会导致早期认可并适当治疗哮喘 在此应用中，我们将利用大量的整个基因组序列（WGS） 作为我们哮喘转化基因组学协作（ATGC）的数据作为一部分 NHLBI的跨摩尼克精密医学（TopMed）计划。 ATGC包括8个队列研究和 10,819例哮喘患者（7,530名非裔美国人和3,081名拉丁裔）。遗传流行病学的 哥斯达黎加（CRA）队列的哮喘与其WGS数据也将参与（n = 1,765）。在AIM 1中，我们将集中精力 关于哮喘加重通过以下子信息的基因组学：a）完善我们对 使用WGS数据加剧遗传力； b）使用混合映射来识别可能的染色体区域 港口风险变体，以加剧； c）使用现有 WGS数据； d）在其他ATGC队列和CRA队列中复制这些关联；和e）评估 使用可用的前瞻性临床数据与未来加重的变体。在AIM 2中，我们 将专注于哮喘加重的转录组学。即，我们将使用得出的RNA序列数据 从整个血液转录组到识别其表达与严重恶化相关的基因 （AIM 2A），我们将确定其表达与在 目标1（目标2b）。 AIM 3将重点放在哮喘加重的蛋白质组学上。储存的血清将习惯 从极端表型中评估个体的蛋白质组（即，从个体收集的血清 严重加重与没有哮喘患者患者的血清）。使用质量 光谱法，我们将广泛评估这些群体之间不同表达的蛋白质的血清（即 未靶向的蛋白质组学方法），我们将使用从基因组，转录组中收集的信息 以及未靶向的蛋白质组学分析，以评估特定蛋白质（即，靶向蛋白质组学方法） 极端表型的其他个体的表达差异。