Iowa CBDRP Comp A: BD-STEPS Core

爱荷华州 CBDRP 比较 A：BD-STEPS 核心

• 批准号: 10765306
• 负责人: KRISTIN CONWAY
• 金额: $ 60万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2027-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10765306
• 关键词: Iowa; CBDRP; Comp; BD; STEPS

PROJECT SUMMARY Major birth defects (BDs) affect morbidity and mortality of tens of thousands of newborns annually in the US. Environmental (i.e. non-inherited) exposures or gene variants are estimated to explain about one-third of BDs that occur. Since 1996, the Iowa Center for Birth Defects Research and Prevention (CBDRP) has played a leadership role in surveillance and research of major BDs. Partnerships with the State of Iowa Department of Health and Human Services and Iowa Registry for Congenital and Inherited Disorders have allowed the Iowa CBDRP timely access to comprehensive surveillance data on deliveries to Iowa resident mothers for enrollment in the National Birth Defects Prevention Study and Birth Defects Study To Evaluate Pregnancy exposureS (BD-STEPS). Using exposure and genomic data collected, the Iowa CBDRP has made substantial contributions to understanding the etiopathogenesis of major BDs, ranging from prevalence estimates to gene- environmental interaction effects, with this work being disseminated in high-impact journals. Findings published support multifactorial inheritance patterns that vary among BDs across system groups and among BD subtypes within a system group. These findings of a heterogeneous etiopathogenesis reinforces the need to continue to investigate major BD phenotypes individually. With this application, the Iowa CBDRP proposes to continue its successful participation in BD-STEPS by timely ascertaining and classifying pregnancies with and without specific major BDs (Aim 1) and developing and evaluating novel modes of exposure data collection (Aim 2). Using data collected, the Iowa CBDRP proposes to expand the traditional epidemiology approach by integrating a multi-omics systems epidemiology approach to more fully investigate risk factors for specific major BDs (Aim 3). The traditional epidemiology approach will be used to examine associations between BD- STEPS exposure data and defects, with international datasets used to conduct confirmation analyses. The systems epidemiology approach will incorporate state-of-the-art genomic studies and machine learning analytics to improve characterization of child phenomes and exposomes and examine gene-environmental interaction effects. Concurrent with the proposed study activities will be training bachelor’s, predoctoral and postdoctoral research scholars to advance the next generation of birth defect researchers (Aim 4). The proposed research and training are not only consistent with BD-STEPS required activities (RFA-DD-23-001) but expands and innovates such activities by improved delineation of exposure pathways and genetic susceptibilities influencing development of specific major BDs. The interdisciplinary expertise of our key personnel and collaborators, along with access to rich exposure and biological data from independent populations, provides the Iowa CBDRP unique resources among all CBDRPs in disseminating novel findings in peer-reviewed publications. Findings generated will provide critical insights into modifiable risk factors for major BDs and be used for family education, treatment improvements, and application of prevention strategies.

项目摘要 在美国，主要的出生缺陷（BDS）影响了数以万计的新生儿的发病率和死亡率。 估计环境（即非传染性）暴露或基因变体可以解释大约三分之一的BDS 发生这种情况。自1996年以来，爱荷华州先生缺陷研究与预防中心（CBDRP）发挥了 在监视和研究主要BDS中的领导作用。与爱荷华州部门的合作伙伴关系 卫生与公共服务以及爱荷华州先天性和遗传疾病的注册中心允许爱荷华州 CBDRP及时访问有关向爱荷华州居民母亲交付的综合监视数据 国家出生缺陷的预防研究和先天缺陷研究以评估怀孕 暴露（BD步骤）。使用收集的曝光和基因组数据，爱荷华州CBDRP已实现了大量 从患病率估计到基因的贡献 环境相互作用的影响，这项工作在高影响力期刊中被传播。研究结果发表 支持多因素的继承模式在系统组和BD之间的BD之间有所不同 系统组中的子类型。这些异质性疗法发生的发现加强了 继续分别研究主要的BD表型。使用此应用程序，爱荷华州CBDRP提案 通过及时确定和分类与和分类，继续成功参与BD步骤 没有特定的主要BD（AIM 1）并开发和评估新型暴露数据收集模式 （目标2）。使用收集的数据，爱荷华州CBDRP提案通过 整合多摩斯系统流行病学方法，以更全面地研究特定的风险因素 大型BD（目标3）。传统的流行病学方法将用于检查BD-之间的关联 步骤暴露数据和缺陷，用于进行确认分析的国际数据集。这 系统流行病学方法将结合最先进的基因组研究和机器学习 分析以改善儿童现象和外博体的特征并检查基因环境 相互作用效果。与拟议的研究活动同时进行培训， 博士后研究学者促进下一代出生缺陷研究人员（AIM 4）。这 拟议的研究和培训不仅与BD步骤所需的活动一致（RFA-DD-23-001） 但是，通过改善暴露途径和遗传的划定来扩展和创新 影响特定主要BD的发展的敏感性。我们密钥的跨学科专业知识 人员和合作者，以及独立的丰富接触和生物数据访问 种群在所有CBDRP中提供了爱荷华州CBDRP的独特资源，以传播新的发现 同行评审的出版物。产生的发现将为主要的主要风险因素提供关键的见解 BDS，用于家庭教育，治疗改善和预防策略的应用。