Improving Sepsis Care with Deep RNA Sequencing Data

利用深度 RNA 测序数据改善脓毒症护理

• 批准号: 10665687
• 负责人: Sean Farrell Monaghan
• 金额: $ 39.86万
• 依托单位: RHODE ISLAND HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10665687
• 关键词: Alternative Splicing; Bacteria; Biology; Caring; Cells; Cessation of life; Computational Biology; Computer Analysis; Computing Methodologies; Critical Illness; Data; Diagnosis; Disease; Entropy; Event; Excision; Exons; Functional disorder; Genes; Genetic Transcription; Human; Immune response; Intensive Care Units; Intervention; Introns; Joining Exons; Molecular; Outcome; Patients; Population; Proteins; RNA; RNA Splicing; RNA metabolism; Resources; Sampling; Sepsis; Translations; Triage; Virus; Whole Blood; anti-PD1 antibodies; comparison control; diagnostic value; improved; microbial; new therapeutic target; novel; outcome prediction; pathogen; potential biomarker; precision medicine; septic patients; transcriptome sequencing

Project Summary/Abstract Sepsis is responsible for one out of every five deaths worldwide. It is therefore essential to better understand better diagnose and treat sepsis. We propose to use deep RNA sequencing of the whole blood of sepsis patients to better identify the pathogen causing the disease, triage the appropriate resources, predict outcomes, and identify novel therapeutic targets. Utilizing novel methods of computational analysis of deep RNA sequencing data we will assess microbial populations, RNA biology (specifically RNA splicing entropy and RNA lariats) and identify novel treatment targets/identify patients likely to benefit. Some RNA sequencing data that does not match the species it came from (human) is typically discarded. We will look at this typically discarded data for microbial (bacteria and viruses) populations to improve diagnostic ability. To assess the host response we will study RNA biology. RNA splicing is a basic molecular function that occurs in all cells directly after RNA transcription, but before protein translation in which introns are removed and exons are joined together. Over 90% of human genes with multiple exons have alternative splicing events. We hope to assess if RNA splicing entropy could be a potential biomarker in sepsis. Introns are typically degraded rapidly after removal during splicing, however, the presence of these lariats could signify RNA metabolism dysfunction and we will correlate this to outcomes. RNA sequencing data will also allow for application of novel interventions, such as PD-1 antibodies, to patients most likely to benefit; essentially applying precision medicine to a critically ill patient. We will utilize whole blood from humans with sepsis and compare to control patients in the intensive care unit without sepsis. Samples will be collected serially over the course of the stay in the intensive care unit. We hypothesize that data from deep RNA sequencing obtained during sepsis can be quantified and improve care.

项目概要/摘要 全球五分之一的死亡由脓毒症造成。因此有必要更好地理解 更好地诊断和治疗脓毒症。我们建议对脓毒症全血进行深度RNA测序 患者更好地识别引起疾病的病原体，分类适当的资源，预测 结果，并确定新的治疗靶点。利用深度计算分析的新方法 我们将评估微生物种群、RNA 生物学（特别是 RNA 剪接熵）的 RNA 测序数据 和 RNA 套索）并确定新的治疗目标/确定可能受益的患者。一些RNA测序 与来自物种（人类）不匹配的数据通常会被丢弃。我们通常会看看这个 丢弃微生物（细菌和病毒）种群的数据以提高诊断能力。评估主机 对此我们将研究RNA生物学。 RNA剪接是直接发生在所有细胞中的基本分子功能 在 RNA 转录之后，但在蛋白质翻译之前，其中内含子被移除并外显子被连接 一起。超过 90% 的具有多个外显子的人类基因具有选择性剪接事件。我们希望评估是否 RNA 剪接熵可能是脓毒症的潜在生物标志物。内含子通常在 然而，这些套索的存在可能意味着 RNA 代谢功能障碍，并且在剪接过程中被去除。 我们会将其与结果联系起来。 RNA测序数据也将允许应用新的干预措施， 例如PD-1抗体，最有可能使患者受益；本质上是将精准医学应用于危重患者 生病的病人。我们将利用脓毒症患者的全血，并在重症监护中与对照患者进行比较 监护病房无脓毒症。样本将在重症监护病房住院期间连续收集。 我们假设脓毒症期间获得的深度 RNA 测序数据可以量化并改进 关心。