Delirium, Acute Inflammation, and Rhythmic Transcriptomics (DART)

谵妄、急性炎症和节律转录组学 (DART)

• 批准号: 10727587
• 负责人: Sarah Kendall Smith
• 金额: $ 31.1万
• 依托单位: WASHINGTON UNIVERSITY
• 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 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10727587
• 关键词: Acute; Age; Analysis of Variance; Attention; Biological Markers; Blood specimen; Bypass; Cardiac Surgery procedures; Central Nervous System; Circadian Dysregulation; Circadian Rhythms; Clinical Data; Clinical Research; Cognition; Conscious; Critical Care; Critical Illness; Data; Data Set; Delirium; Development Plans; Dimensions; Elderly; Evaluation; Exhibits; Family member; Functional disorder; Funding; Future; Gene Expression Profiling; General Anesthesia; Genes; Hospitalization; Hospitals; Hour; Impairment; Incidence; Individual; Inflammation; Inflammatory Response; Injury; Interleukin-6; Interleukin-8; Leadership; Light; Link; Measurement; Measures; Mediating; Methods; Molecular; Morbidity - disease rate; Multiomic Data; Neurobiology; Neurology; Operative Surgical Procedures; Patients; Pattern; Periodicity; Perioperative; Physiological; Physiological Processes; Postoperative Period; Principal Component Analysis; Proteins; Proteomics; Research; Risk; Secure; Severities; System; TNF gene; Time; Tissue-Specific Gene Expression; United States; Whole Blood; body system; circadian; circadian pacemaker; clinically relevant; cohort; confusion assessment method; cost; data reduction; design; hospital care; innovation; machine learning algorithm; mortality; nervous system disorder; neurofilament; novel; patient stratification; postoperative delirium; predictive marker; programs; prospective; protein biomarkers; protein expression; systemic inflammatory response; theories; transcriptome sequencing; transcriptomics

PROJECT SUMMARY Postoperative delirium in older adults imposes massive burdens on patients, family members, and hospital systems with United States costs upwards of $32 billion. Despite this, the pathophysiology of postoperative delirium remains poorly understood and no therapies exist. Disruption of the circadian clock system is a putative contributor to postoperative delirium. The circadian clock system coordinates the timing of most physiologic processes including the systemic inflammatory response, whose dysfunction has been linked to postoperative delirium incidence and severity. It is unknown whether acute, perioperative disruption of the circadian clock system leads to an aberrant systemic inflammatory response to precipitate postoperative delirium. Elucidation of these dynamic, bidirectional relationships may yield novel predictive biomarkers and therapies to reduce delirium risk. We have recently validated a machine-learning algorithm, TimeSignature (TS), that uses transcriptomic data from whole blood to measure internal circadian transcriptomic time in a cohort of older adults. TS can be used to determine the transcriptomic angle, or the magnitude of discrepancy between internal transcriptomic time and true time of blood sampling in an individual. In this proposal, we aim to determine temporal links between changes in transcriptomic angle, systemic inflammation, and delirium severity in a cohort of older adults undergoing elective cardiac surgery. The central hypothesis is that patients stratified by delirium severity will exhibit distinct longitudinal molecular patterns of circadian rhythms and systemic inflammation perioperatively. In Aim 1, we will determine whether patients stratified by delirium severity exhibit distinct longitudinal patterns of transcriptomic angle across the perioperative continuum. Older adults stratified by delirium severity will undergo serial measurement of transcriptomic angle at three perioperative timepoints: on the day before cardiac surgery, on postoperative day (POD) 1, and POD 4. In Aim 2, we will evaluate whether incorporating proteomic biomarker data enhances distinguishing longitudinal patterns among delirium severity groups. The same patients from Aim 1 will undergo serial measurement of a comprehensive panel of protein biomarkers related to acute inflammation and neurobiological injury. The contribution of this proposal is significant because it represents critical first step in establishing the clinical relevance of molecular circadian rhythm disruptions during the perioperative period. The proposed research is innovative because it will shift current delirium research paradigms towards a precision-based approach ideally suited for hospitalized and critically-ill older adults undergoing major surgery.

项目概要 老年人术后谵妄给患者、家属和医院带来巨大负担 系统 美国成本高达 320亿美元。尽管如此，术后病理生理学 人们对谵妄的了解仍知之甚少，也没有治疗方法。 生物钟系统的破坏被认为是术后谵妄的原因之一。生物钟 系统协调大多数生理过程的时间安排，包括全身炎症反应， 其功能障碍与术后谵妄的发生率和严重程度有关。尚不清楚是否急性， 围手术期生物钟系统的破坏导致异常的全身炎症反应 诱发术后谵妄。阐明这些动态的双向关系可能会产生新颖的结果 降低谵妄风险的预测生物标志物和疗法。 我们最近验证了一种机器学习算法 TimeSignature (TS)，它使用转录组数据 从全血中测量一组老年人的内部昼夜节律转录组时间。可以用TS 确定转录组角度，或内部转录组时间之间的差异程度 以及个体采血的真实时间。在这个提案中，我们的目标是确定之间的时间联系 一组老年人的转录组角度、全身炎症和谵妄严重程度的变化 正在接受选择性心脏手术。中心假设是，按谵妄严重程度分层的患者会 表现出明显的昼夜节律纵向分子模式和围手术期全身炎症。 在目标 1 中，我们将确定按谵妄严重程度分层的患者是否表现出不同的纵向模式 整个围手术期连续体的转录组学角度。按谵妄严重程度分层的老年人将经历 在三个围手术期时间点连续测量转录组角度：心脏手术前一天， 术后第 1 天 (POD) 和 POD 4。在目标 2 中，我们将评估是否纳入蛋白质组生物标志物 数据增强了谵妄严重程度组之间纵向模式的区分。来自 Aim 的相同患者 1 将接受一系列与急性炎症相关的蛋白质生物标志物综合测量 和神经生物学损伤。该提案的贡献是重大的，因为它代表了关键的第一步 确定围手术期分子昼夜节律紊乱的临床相关性。 拟议的研究具有创新性，因为它将当前的谵妄研究范式转向 基于精确的方法非常适合住院和接受大手术的危重老年人。