Epigenome-wide variations and socio-environmental exposures in African American asthmatic children

非裔美国哮喘儿童的表观基因组变异和社会环境暴露

• 批准号: 10494245
• 负责人: Tesfaye B. Mersha
• 金额: $ 67.69万
• 依托单位: CINCINNATI CHILDRENS HOSP MED CTR
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-24 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10494245
• 关键词: Address; Affect; African American; African American population; Age; Air Pollution; Algorithms; Allergens; American; Asthma; Bioinformatics; Biological; Biometry; Caring; Cells; Child; Childhood; Childhood Asthma; Clinic; Clinical; Clinical Sciences; Communities; Complex; DNA Methylation; DNA Modification Process; DNA methylation profiling; Data; Disease; Environmental Exposure; Epigenetic Process; European; Exposure to; Gene Frequency; Genetic; Genetic Predisposition to Disease; Genome; Genotype; Geography; Goals; Green space; Hypersensitivity; Immune; Incidence; Individual; Intervention; Link; Maps; Measures; Mediating; Mediation; Methylation; Minority; Modeling; Neighborhoods; Ohio; Pathogenesis; Pediatrics; Phenotype; Public Health; Research; Research Personnel; Risk; Risk Factors; Sampling; Science; Site; Social Characteristics; Social Environment; Statistical Methods; Stress; Study models; Sum; Surrogate Markers; System; Testing; Time; Tobacco smoke; United States; United States National Institutes of Health; Variant; Violence; Work; asthma model; asthmatic; base; biobank; case control; clinical predictors; clinical risk; cohort; deprivation; epigenetic variation; epigenome; epigenome-wide association studies; gene function; genome wide methylation; genome-wide; improved; indexing; innovation; insight; methylation pattern; multi-ethnic; non-genetic; novel; population based; predictive marker; predictive modeling; programs; psychosocial; racial disparity; repository; risk prediction; risk prediction model; risk stratification; screening; sex; social; social epidemiology; socioeconomics

ABSTRACT Asthma is a major public health problem in the United States, affecting 11 million children. Despite advances in asthma care, African Americans (AAs) are 4 times more likely to be hospitalized and 5 times more likely to die from asthma than European Americans (EAs). Several factors could be responsible for the observed asthma racial disparities including genetic and non-genetic factors. While epigenetics appear to serve as a critical biological switch between genetic vulnerability and socio-environmental exposures, limited studies are available that directly map the socio- environmental exposures with asthmatic epigenome/genome information. In addition, current approach do not leverage existing geospatial data such as environmental exposure and neighborhood socioeconomic conditions to improve asthma risk prediction. In this proposal, we will utilize comprehensive geocoding algorithms, novel statistical methods to integrate social, clinical, environmental, genetic, and epigenetic data into a composite score for asthma risk stratification and prediction. The overall objective of this research is to conduct genome-wide Methyl-Seq analysis and leverage existing well-phenotyped AA pediatric asthma cohort with extensive socio-environmental exposures and ancestry-tailored multi-ethnic genotyping array (MEGA) data from Cincinnati Pediatrics Repository to accurately determine and develop ancestry- specific asthma risk stratification and prediction models. The objective of this application is to undertake an epigenome-wide association study (EWAS), incorporating geocoded neighborhood- and individual-level socio-environmental predictors, and novel analytical strategies to create a composite risk score incorporating methylation risk score (MRS), ancestry, environmental exposures and social characteristics to predict asthma. We will accomplish these objectives through the following Specific Aims: 1) Develop an ancestry-specific methylation risk score (MRS) for asthma and test its association with socio-environmental exposures contributing to asthma risk. 2) Determine the mediation effects of MRS between genetic ancestry and asthma risk. 3) Develop a multivariable risk predictive model for asthma incorporating MRS, genetic ancestry, clinical, and socio-environmental risk factors. The proposed research is innovative because this will be the first time a MRS approach will be used to develop a population-based risk profile in asthmatics. The study will provide insights in the use of risk stratification for screening and targeted interventions. This work is significant because it can serve as a model to study the composite effect of MRS, ancestry, socio-environmental, and clinical risk factors on racial disparities in other well-documented common complex diseases beyond asthma.

摘要 哮喘是美国的一个主要公共卫生问题，影响着1100万儿童。尽管 哮喘护理的进步，非洲裔美国人（AAs）住院的可能性是其他人的4倍， 死于哮喘的可能性是欧洲裔美国人的5倍。可能有几个因素 导致观察到的哮喘种族差异，包括遗传和非遗传因素。 虽然表观遗传学似乎是遗传脆弱性和 社会环境暴露，有限的研究可直接映射的社会， 环境暴露与哮喘表观基因组/基因组信息。此外，目前 这种方法不利用现有的地理空间数据，如环境暴露， 社区社会经济条件，以改善哮喘风险预测。在本提案中，我们 将利用全面的地理编码算法，新的统计方法，整合社会， 将临床、环境、遗传和表观遗传数据整合为哮喘风险的综合评分 分层预测这项研究的总体目标是在全基因组范围内 甲基序列分析和利用现有的良好表型AA儿童哮喘队列， 广泛的社会环境暴露和祖先定制的多种族基因分型阵列 （MEGA）数据从辛辛那提儿科知识库，以准确地确定和发展祖先- 特定哮喘风险分层和预测模型。本申请的目的是 进行表观基因组关联研究（EWAS），将地理编码的邻居- 和个人层面的社会环境预测，以及新的分析策略，以创建一个 结合甲基化风险评分（MRS）、血统、环境 暴露和社会特征来预测哮喘。我们将实现这些目标 通过以下具体目的：1）开发祖先特异性甲基化风险评分（MRS） 并测试其与导致哮喘的社会环境暴露之间的关系 风险2)确定MRS在遗传血统和哮喘风险之间的中介作用。第三章 开发一个多变量的哮喘风险预测模型，包括MRS、遗传血统、 临床和社会环境风险因素。这项研究具有创新性，因为 这将是MRS方法首次用于制定基于人群的风险概况， 哮喘患者该研究将提供使用风险分层进行筛查的见解， 有针对性的干预措施。这项工作是有意义的，因为它可以作为一个模型来研究 MRS、血统、社会环境和临床危险因素对种族 除了哮喘之外，其他有充分记录的常见复杂疾病的差异。