Leveraging multi-omics to maximize the scientific value of pediatric sepsis biorepository and advance patient endotyping

利用多组学最大限度地发挥儿科脓毒症生物样本库的科学价值并推进患者内分型

• 批准号: 10731811
• 负责人: Mihir R Atreya
• 金额: $ 24.16万
• 依托单位: CINCINNATI CHILDRENS HOSP MED CTR
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-05 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10731811
• 关键词: Address; Affect; Antibiotics; Bioinformatics; Biological; Biology; Blood specimen; Characteristics; Child; Childhood; Clinical; Clinical Data; Clinical Trials; Collection; Communities; CpG Islands; Critical Illness; Critically ill children; DNA; DNA Methylation; DNA methylation profiling; Data; Data Set; Databases; Derivation procedure; Development; Dimensions; Disease; Electronic Health Record; Ensure; Epigenetic Process; Equity; Evolution; Factor Analysis; Feasibility Studies; Foundations; Functional disorder; Funding; Future; Gene Expression; Gene Expression Profiling; Gene Expression Regulation; Genes; Genetic Transcription; Health; Human; Immune response; Infection; Knowledge; Laboratories; Life; Link; Malignant Childhood Neoplasm; Messenger RNA; Methodology; Methods; Methylation; Modeling; Molecular; Morbidity - disease rate; National Institute of General Medical Sciences; Nature; Organ; Outcome; Pathway interactions; Patient Care; Patient-Focused Outcomes; Patients; Pattern; Pharmaceutical Preparations; Phase; Phased Innovation Awards; Precision therapeutics; Process; Quality Control; RNA; Reporting; Research; Research Personnel; Role; Sampling; Scientific Advances and Accomplishments; Sepsis; Septic Shock; Series; Specimen; Subgroup; Testing; Therapeutic; Time; Validation; Whole Blood; bead chip; biobank; biological heterogeneity; clinically relevant; clinically significant; cohort; data integration; disorder subtype; efficacious treatment; epigenome; epigenomics; gene regulatory network; improved; methylome; methylomics; mortality; multiple omics; novel; patient response; patient subsets; pediatric patients; pediatric sepsis; performance tests; power analysis; precision medicine; prevent; public health emergency; repository; scale up; septic patients; systemic inflammatory response; targeted treatment; transcriptome; transcriptome sequencing; transcriptomics; treatment response

Leveraging multi-omics to maximize the scientific value of pediatric sepsis biorepository and advance patient endotyping. PROJECT SUMMARY: Sepsis is major pediatric health problem and kills more children than cancer in the U.S each year. Primarily driven by a dysfunctional host response to an infection, a subset of patients with persistent or progressive multiple organ dysfunctions disproportionately contribute to sepsis morbidity and mortality. Yet, there are no disease modifying therapies currently available beyond early antibiotics and organ support. Biological heterogeneity among patients has significantly impeded scientific progress and advances in patient care. Although precision medicine approaches have been used to begin to sift through patient-level differences, we fundamentally lack a comprehensive understanding of disease mechanisms. Thus, there is a crucial need to maximize the use of existing pediatric sepsis biorepositories to unravel causal pathways, facilitate rapid identification of biologically relevant patient subclasses more likely to benefit from targeted therapies. To bridge this gap, we seek to utilize state-of-the-art multi-omics approaches to explore the scientific value of our vast collection of biospecimens from critically ill children with sepsis. While gene-expression profiling has been used to identify biologically relevant endotypes, it is increasingly evident that interrogation of single layer of molecular data is likely insufficient. Recent studies suggest that the epigenomic changes, including differential DNA methylation at CpG islands, closely regulate gene-expression in human sepsis. Through this phased innovation award, we seek to determine whether integrated analyses of methylomic and transcriptomic datasets at scale can provide a comprehensive understanding of mechanisms and inform patient endotyping. We further seek to determine whether clinical data linked with patient biospecimens can be used to predict endotype membership, with operational implications for predictive enrichment in future clinical trials. Milestone-driven developmental activities in the R21 phase will focus on stringent quality control of DNA and RNA samples within our biorepository to determine suitability for high throughput methods. We will then generate pilot DNA methylation profiling and RNA sequencing data for study planning and to demonstrate feasibility of integrated analyses. In the R33 phase, we will scale efforts to generate robust methylomic and transcriptomic datasets. We will leverage the bioinformatic capabilities of the investigator team to derive and validate novel multi-omic endotypes and determine their clinical significance. Finally, we will develop a classifier model to predict endotype membership using clinical data within the derivation cohort and test its generalizability in a large electronic health record-based dataset of >15,000 critically ill children with sepsis and multiple organ dysfunctions. Through the successful execution of this proposal, we seek to generate a rich dataset to drive future mechanistic research in human sepsis and develop an actionable framework for rapid and equitable identification of pediatric sepsis subclasses who may benefit from targeted sepsis therapeutics.

利用多组学最大限度地发挥儿科脓毒症生物样本库的科学价值并推进患者内分型。 项目概要： 败血症是主要的儿科健康问题，在美国每年导致的儿童死亡人数比癌症还要多。主要是 由宿主对感染的功能失调反应驱动，一部分患者出现持续性或进行性的症状 多器官功能障碍不成比例地导致脓毒症发病率和死亡率。然而，还没有 目前除了早期抗生素和器官支持之外还有疾病缓解疗法。生物 患者之间的异质性严重阻碍了科学进步和患者护理的进步。 尽管精准医学方法已被用来开始筛选患者水平的差异，但我们 从根本上缺乏对疾病机制的全面认识。因此，迫切需要 最大限度地利用现有的儿科脓毒症生物样本库来揭示因果途径，促进快速 识别更有可能受益于靶向治疗的生物学相关患者亚类。 为了弥补这一差距，我们寻求利用最先进的多组学方法来探索科学价值 我们收集了大量来自脓毒症危重儿童的生物样本。虽然基因表达谱已经 被用来识别生物学相关的内型，越来越明显的是，单层的询问 分子数据可能还不够。最近的研究表明表观基因组变化，包括 CpG 岛的差异 DNA 甲基化密切调节人类脓毒症的基因表达。通过这个 阶段性创新奖，我们寻求确定甲基组学和转录组学的综合分析是否 大规模数据集可以提供对机制的全面理解并为患者内分型提供信息。 我们进一步寻求确定与患者生物样本相关的临床数据是否可以用于预测 内型成员资格，对未来临床试验中的预测丰富具有操作意义。 R21 阶段里程碑驱动的开发活动将重点关注严格的 DNA 质量控制 和我们生物样本库中的 RNA 样本，以确定高通量方法的适用性。我们随后将 生成试点 DNA 甲基化分析和 RNA 测序数据，用于研究规划和演示 综合分析的可行性。在 R33 阶段，我们将加大力度产生强大的甲基组学和 转录组数据集。我们将利用研究团队的生物信息能力来导出和 验证新的多组学内型并确定其临床意义。最后，我们将开发一个 分类器模型使用推导队列中的临床数据预测内型成员资格并测试其 在基于电子健康记录的大型数据集中的普遍性，该数据集包含超过 15,000 名患有脓毒症和 多器官功能障碍。通过成功执行该提案，我们力求创造丰富的成果 数据集，以推动人类败血症的未来机制研究，并开发一个可操作的框架，以快速 以及公平地识别可能受益于靶向脓毒症治疗的儿科脓毒症亚类。