The Scientific Value of Premature Infant Biospecimens Collection

早产儿生物样本采集的科学价值

基本信息

批准号：
10742586
负责人：
Stephanie Prescott
金额：
$ 19.46万
依托单位：
UNIVERSITY OF SOUTH FLORIDA
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-07-03 至 2025-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10742586
关键词：
Achievement Adult Age Antibiotics Apgar Score Bacterial Infections Biological Biometry Birth Birth Weight Blood Blood Transfusion Body mass index Cause of Death Clinical Clinical Data Collection Communicable Diseases Computer Analysis Critical Illness Data Delivery Rooms Detection Development Diagnosis Diet Differential Diagnosis Disease Documentation Ensure Environment Ethnic Origin Event Feces Foundations Functional disorder Future Genes Gestational Age Growth Head circumference Heterogeneity Hospitals Hour Human Image Immune response Immunologist Incidence Infant Infection Inflammatory Intake Length Life Life Style Low Birth Weight Infant Machine Learning Medical Methods Modeling Molecular Target Mycoses Neonatal Neonatal Intensive Care Units Organ Outcome Output Pathway Analysis Pathway interactions Patients Performance Pharmaceutical Preparations Phase Physiology Population Positioning Attribute Pregnancy Premature Infant Procedures Protocols documentation Provider Race Recovery Rectum Reproducibility Research Resolution Resuscitation Saliva Sample Size Sampling Science Sepsis Serum Site Skin Specialist Specimen Spottings Staging Standardization Stratification Support System Swab System Techniques Technology Testing Time Tissues Tube Urine Very Low Birth Weight Infant Virus Diseases clinical research site differential expression experimental study extreme prematurity gene interaction gene network high risk population machine learning method microbial microbiome molecular modeling multiple omics neonatal sepsis neonate predictive marker predictive modeling premature preservation rectal respiratory sample collection sex standard of care treatment response validation studies

项目摘要

Project Summary/Abstract The complexities of heterogeneity, stratification, and staging of sepsis have contributed to the poor translatability of current molecular models for diagnosis and treatment of human sepsis. The National Advisory General Medical Sciences Council advised using discovery approaches to characterize sepsis using human biospecimens. Sepsis, a life-threatening organ dysfunction caused by a dysregulated host response to a bacterial, viral, or fungal infection, is a major cause of death in premature (≤32 weeks) and low birth weight (≤ 1500g) infants and occurs in up to 25% of such infants.1-3 The ability to collect microbiome and tissue biospecimens longitudinally from multiple body sites under extremely controlled circumstances prior to, during, and throughout sepsis (culture proven), sepsis-like (culture negative critical illness), and "normal" growing premature infant conditions will allow our team to determine optimal sample collection, storage, and processing protocols using small volume samples to enhance sepsis research rigor, and to develop new strategies for sepsis detection by discerning pathways that contribute to the pathophysiology of sepsis in the premature neonatal population. In the R21 phase we will collect clinical information and stool, blood, and saliva specimens longitudinally from preterm infants (≤32 weeks and ≤1500g) on days 1, 3, 7, 14, 21, 28, 35, 42, and 49 of life, and additionally during suspected sepsis events. Standardization and documentation of sample collection, storage, and processing and sample validation studies will ensure rigor and reproducibility and inform the field. In the R33 phase we will collect samples from 2 clinical sites providing a test set for machine learning methods. Utility of the newly collected biospecimens and associated clinical data will be demonstrated by constructing a multi-omic network for predicting causal mechanisms from genes/metabolites/clinical parameters differentially expressed between clinically well neonates and those with culture proven sepsis and culture negative systemic inflammatory illness. We will make establish testable causal inferences and predictive models of microbial/host gene interactions and biologic mechanisms leading to sepsis that could form the foundation for future mechanistic studies. Our team of neonatal providers, immunologists, systems biologists, microbiome specialists, and bioinformaticians supported by two large Level IV NICUs are uniquely positioned to collect and analyze biospecimens and clinical data before, during, and after critical illness in patients with extreme prematurity.

项目概要/摘要脓毒症的异质性、分层和分期的复杂性导致了穷人当前用于诊断和治疗人类脓毒症的分子模型的可转化性。通用医学科学委员会建议使用发现方法来利用人类来表征脓毒症脓毒症，一种由宿主对某种物质的反应失调引起的危及生命的器官功能障碍。细菌、病毒或真菌感染是早产儿（≤32周）和低出生体重（≤ 1500g) 婴儿，此类婴儿的发生率高达 25%。1-3 收集微生物组和组织的能力在极端情况下，在之前、期间、期间从多个身体部位纵向采集生物样本以及整个脓毒症（培养证明）、脓毒症样（培养阴性危重病）和“正常”生长早产儿的情况将使我们的团队能够确定最佳的样本采集、储存和处理使用小体积样本来提高脓毒症研究严谨性的方案，并制定新策略通过识别导致早产儿败血症病理生理学的途径来检测败血症新生儿人口。在R21阶段，我们将纵向收集临床信息以及粪便、血液和唾液样本出生后第 1、3、7、14、21、28、35、42 和 49 天的早产儿（≤32 周且≤1500g），另外疑似脓毒症事件期间样本采集、储存和记录的标准化和记录。处理和样品验证研究将确保严谨性和可重复性，并为该领域提供信息。在 R33 阶段，我们将从 2 个临床站点收集样本，为机器学习方法提供测试集。新收集的生物样本和相关临床数据的效用将通过构建一个用于根据基因/代谢物/临床参数差异预测因果机制的多组学网络在临床状况良好的新生儿和培养证实败血症且系统培养阴性的新生儿之间表达我们将对微生物/宿主进行可测试的因果推论和预测模型。导致败血症的基因相互作用和生物机制可能为未来奠定基础机械研究。我们的团队由新生儿提供者、免疫学家、系统生物学家、微生物组专家和由两个大型 IV 级新生儿重症监护室支持的生物信息学家具有独特的优势来收集和分析极早产患者危重病之前、期间和之后的生物样本和临床数据。