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

基本信息

批准号：
9250797
负责人：
Tina V Hartert
金额：
$ 18.76万
依托单位：
UNIVERSITY OF IOWA
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-04-01 至 2019-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9250797
关键词：
6 year old 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 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 Prospective cohort Prospective cohort study 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 public health relevance respiratory respiratory health screening stressor tool

项目摘要

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（由适用提供）：儿童哮喘是一种毁灭性的疾病，可为受影响的儿童及其家人带来长期的医疗和金融烧伤。但是，确定患哮喘的高风险的幼儿被证明很困难。当前的预测模型是简单的，无法识别哮喘的潜在复杂性。但是，更复杂的模型往往会失去临床实用性。然而，需要这样的模型：哮喘是最常见的慢性儿童疾病之一，仅在美国就影响了700万儿童。最近的研究表明，将儿童早期呼吸道和过敏症状聚类（即喘息，呼吸道感染，特应性皮炎）分为不同的表型可能会提高预测儿童哮喘发育的能力。但是，对于这些表型的生物风险知之甚少。例如，代谢和线粒体功能障碍与哮喘有关，但对疾病如何导致疾病发展的理解仍然存在关键差距。新生儿代谢筛查是一项公共卫生倡议，旨在筛选每个因内分泌疾病和罕见的代谢错误而出生的孩子，其中包括许多疾病，表明了代谢和线粒体功能障碍。该筛选代表了一个独特的数据源，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。我们假设出生时患有轻度代谢灾害的个体将更容易进一步代谢和线粒体功能障碍，从而导致童年后期呼吸道和过敏表型的发展，而在环境中或其他压力因子中暴露于触发器时。使用田纳西州的两项前瞻性队列研究，旨在识别哮喘的危险因素；我们将通过以下特定的研究目标和目标解决这一假设。具体研究目标：确定纳入新生儿代谢筛查数据是否改善了早期儿童呼吸和过敏表型的预测。目标1：根据早期呼吸和过敏症状确定呼吸表型簇。目标2：确定可预测婴儿呼吸发病率目标的临床，人口统计学，环境和新生代谢筛查代谢产物3：验证预测模型并确定我们模型的敏感性和特异性。将临床和环境数据与数据（例如新生儿筛查测量结果）相结合，通常由州计划捕获，是一种创建可以纳入临床上可用工具的预测模型的新方法，说明了哮喘表型中的异质性，并发现了新的疾病途径。如果这种方法成功，我们的预测模型将改善童年时期哮喘的诊断，并可能导致预防或策略对重大疾病的早期干预，从而影响全球数百万儿童。

项目成果

期刊论文数量（1）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Initial Metabolic Profiles Are Associated with 7-Day Survival among Infants Born at 22-25 Weeks of Gestation.

DOI：
10.1016/j.jpeds.2018.03.032
发表时间：
2018-07
期刊：
The Journal of pediatrics
影响因子：
0
作者：
Oltman SP;Rogers EE;Baer RJ;Anderson JG;Steurer MA;Pantell MS;Partridge JC;Rand L;Ryckman KK;Jelliffe-Pawlowski LL
通讯作者：
Jelliffe-Pawlowski LL