Newborn Metabolic Screening for Prediction of Childhood Respiratory Phenotypes

新生儿代谢筛查用于预测儿童呼吸表型

• 批准号: 9090671
• 负责人: Tina V Hartert
• 金额: $ 23.89万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-04-01 至 2018-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9090671
• 关键词: 6 year old; Accounting; Address; Affect; Age of Onset; Alanine; Allergic; Allergic rhinitis; Animal Model; Arginine; Asthma; Atopic Dermatitis; Biochemical Pathway; Biological; Biological Factors; Biological Process; Birth; Carnitine; Cessation of life; Child; Childhood; Childhood Asthma; Chronic; Chronic Disease; Clinical; Cohort Studies; Complex; Data; Data Sources; Development; Diagnosis; Diagnostic; Disease; Disease Pathway; Early Intervention; Endocrine System Diseases; Enrollment; Environment; Environmental Exposure; Environmental Risk Factor; Etiology; Exploratory/Developmental Grant; Exposure to; Family; Frequencies; Functional disorder; Goals; Heterogeneity; Hospitalization; Hypersensitivity; IgE; Inborn Errors of Metabolism; Individual; Infant; Infection; Intervention; Lead; Life; Longitudinal Studies; Lower Respiratory Tract Infection; Lung; Lung Inflammation; Measurement; Measures; Medical; Metabolic; Modeling; Morbidity - disease rate; Nature; Neonatal Screening; Newborn Infant; Oxidative Stress; Perinatal Exposure; Pharmaceutical Preparations; Phenotype; Predisposition; Prevention; Public Health; Research; Respiratory Signs and Symptoms; Respiratory Tract Infections; Respiratory physiology; Respiratory syncytial virus; Risk; Risk Factors; Role; Sensitivity and Specificity; Severities; Supplementation; Symptoms; Tennessee; Testing; United States; Wheezing; asthma prevention; base; cohort; cost; design; early childhood; high risk; improved; mitochondrial dysfunction; novel; novel strategies; oxidation; population based; predictive modeling; prevent; programs; prospective; public health relevance; respiratory; respiratory health; screening; stressor; tool

 DESCRIPTION (provided by applicant): Childhood asthma is a devastating condition that incurs long-term medical and financial burdens for affected children and their families. But identifying young children at high risk to develop asthma has proven difficult. Current predictive models are simplistic and do not recognize the underlying complexity of asthma; however, more complex models tend to lose clinical utility. Yet such models are needed: asthma is one of the most common chronic childhood diseases, affecting seven million children in the United States alone. Recent studies suggest that clustering early childhood respiratory and allergy symptoms (i.e., wheezing, respiratory infections, atopic dermatitis) into distinct phenotypes may improve the ability to predict asthma development in children. However, little is known about the biologic risks underlying these phenotypes. Metabolic and mitochondrial dysfunction, for instance, has been associated with asthma, but critical gaps remain in our understanding of how it leads to development of the disease. Newborn metabolic screening is a public health initiative aimed at screening every child born for endocrine disorders and rare inborn errors of metabolism, including many disorders indicative of metabolic and mitochondrial dysfunction. This screening represents a unique data source that can be analyzed alongside perinatal and environmental exposures to further our understanding of asthma etiology. We hypothesize that individuals with mild metabolic disturbances at birth will be more prone to further metabolic and mitochondrial dysfunction leading to the development of respiratory and allergy phenotypes later in childhood when exposed to triggers in the environment or to other stressors. Using two prospective cohort studies from Tennessee designed to identify risk factors for asthma; we will address this hypothesis through the following specific study goal and aims. Specific Study Goal: Determine if inclusion of newborn metabolic screening data improves prediction of early childhood respiratory and allergy phenotypes. Aim 1: Identify clusters of respiratory phenotypes based on early childhood respiratory and allergy symptoms. Aim 2: Identify clinical, demographic, environmental and newborn metabolic screening metabolites that are predictive of infant respiratory morbidity and asthma and allergy phenotypic groups. Aim 3: Validate predictive models and determine the sensitivity and specificity of our model. Combining clinical and environmental data with data, such as neonatal screening measurements, routinely captured by state programs is a novel approach for creating predictive models that can be incorporated into clinically available tools, account for heterogeneity in asthma phenotypes, and uncover novel disease pathways. If this approach is successful, our predictive models will improve the diagnosis of asthma in childhood and possibly lead to prevention or strategies for early intervention of a significant illness that affects millions of children worldwide.

 描述（由申请人提供）：儿童哮喘是一种毁灭性的疾病，会给受影响的儿童及其家庭带来长期的医疗和经济负担。但事实证明，识别患有哮喘的高危儿童是困难的。目前的预测模型过于简单，没有认识到哮喘的潜在复杂性;然而，更复杂的模型往往失去临床实用性。然而，这样的模型是必要的：哮喘是最常见的慢性儿童疾病之一，仅在美国就影响着700万儿童。最近的研究表明，聚集早期儿童呼吸道和过敏症状（即，哮喘、呼吸道感染、特应性皮炎）转化为不同的表型可能提高预测儿童哮喘发展的能力。然而，对这些表型的生物学风险知之甚少。例如，代谢和线粒体功能障碍与哮喘有关，但我们对它如何导致疾病发展的理解仍然存在重大差距。新生儿代谢筛查是一项公共卫生举措，旨在筛查每一个出生的儿童是否患有内分泌失调和罕见的先天性代谢缺陷，包括许多表明代谢和线粒体功能障碍的疾病。这种筛查代表了一种独特的数据来源，可以与围产期和环境暴露一起分析，以进一步了解哮喘病因。我们假设，出生时轻度代谢紊乱的个体更容易发生进一步的代谢和线粒体功能障碍，导致在儿童期后期暴露于环境中的触发物或其他应激源时出现呼吸和过敏表型。使用田纳西州的两项前瞻性队列研究，旨在确定哮喘的危险因素;我们将通过以下特定的研究目标和目的来解决这一假设。具体研究目标：确定是否包括新生儿代谢筛查数据改善了早期儿童呼吸和过敏表型的预测。目的1：根据儿童早期呼吸道和过敏症状识别呼吸道表型簇。目标二：确定临床、人口统计学、环境和新生儿代谢筛查代谢物，这些代谢物可预测婴儿呼吸道发病率、哮喘和过敏表型组。目的3：验证预测模型并确定我们模型的灵敏度和特异性。将临床和环境数据与国家计划常规捕获的数据（如新生儿筛查测量）相结合，是创建预测模型的一种新方法，该模型可以纳入临床可用的工具中，解释哮喘表型的异质性，并发现新的疾病途径。如果这种方法成功，我们的预测模型将改善儿童哮喘的诊断，并可能导致预防或早期干预影响全球数百万儿童的重大疾病的策略。