权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

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：
10337191
负责人：
Keoki Williams
金额：
$ 73.95万
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 2025-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10337191
关键词：
Accounting Address African American African American population 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 Latino Population 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.

哮喘加重导致相当多的疾病发病率，占所有哮喘病例的近一半