Bedside Genomics in Severe Trauma

描述（由申请人提供）：严重创伤不仅仍然是住院和发病的主要原因，而且也是45岁以下个体死亡的主要原因。创伤后感染、脓毒症和MSOF的频率仍然太频繁，这在很大程度上是由于宿主对严重创伤的免疫反应的异质性，以及无法准确识别入院后早期具有免疫异常的患者，因此这些患者具有复杂结局的高风险。我们的总体假设是，严重钝性创伤后人血白细胞转录组的早期变化（<12-24小时）可用于鉴定将具有不良临床结果的患者，以及最终可能受益于靶向先天性和适应性免疫应答的干预治疗的患者。我们建议开发一个临床床旁平台，基于总的和富集的血液白细胞群体的基因组表达模式，在此基础上开发一个快速的基于基因组学的诊断在床边严重受伤的患者，这可以整合到临床治疗方案。有三个具体目标：（1）使用来自400多名创伤患者的现有RNA样本和来自“炎症”Glue Grant的2,300多名创伤患者的数据库，开发基于白细胞转录组的统计模型，该模型可以被验证用于预测严重创伤后的复杂临床结果;（2）开发一种护理点装置，该装置可以在床边分离血液白细胞和PMN，并使用NanoString技术在几小时内确定mRNA丰度;以及（3）在75名严重创伤患者中前瞻性地验证统计模型和床旁设备，以识别具有复杂临床轨迹的风险的患者。该计划的成功完成将创建一个基于基因组学的诊断，可以在临床环境中提供及时的基因组数据，预测危重创伤患者的临床结局。这一奋进的成功将大大有助于实现整合生物技术，基因组学和生物信息学的目标，改变临床实践，并为危重患者提供个性化医疗的概念。 公共卫生相关性：这项研究的数据将有助于开发一种临床诊断测试，以预测严重创伤后的患者结局，并发现可以帮助医生为个体患者选择个性化药物治疗的特征。

DESCRIPTION (provided by applicant): Severe trauma not only remains a major cause of hospitalization and morbidity, but is also the leading cause of death in individuals under the age of 45. The frequency of post-trauma infections, sepsis, and MSOF remain all too frequent due, in large part, to the heterogeneity of the host immune response to severe trauma, and the inability to accurately identify patients who have immunological abnormalities early after admission and who are therefore at high risk of complicated outcomes. Our overarching hypothesis is that early changes in the human blood leukocyte transcriptome (<12-24 hrs) after severe blunt trauma can be used to identify patients who will have an adverse clinical outcome, and who ultimately may benefit from intervention therapies targeting innate and adaptive immune responses. We propose to develop a clinical bed-side platform, based on genomic expression patterns from total and enriched blood leukocyte populations, on which to develop a rapid genomics-based diagnostic at the bedside in severely injured patients, which can be integrated into clinical treatment programs. There are three specific aims: (1) Using existing RNA samples from over 400 trauma patients and a database of over 2,300 trauma patients from the "Inflammation" Glue Grant, develop statistical models based on the leukocyte transcriptome that can be validated for predicting a complicated clinical outcome after severe trauma; (2) develop a point of care device that can isolate blood leukocytes and PMNs at the bedside and determine mRNA abundance in a matter of hours using a NanoString" technology; and (3) validate prospectively in 75 severe trauma patients the statistical model and point of care device to identify patients at risk of having a complicated clinical trajectory. Successful completion of the program will create a genomics-based diagnostic that can provide in the clinical setting, timely genomic data predictive of clinical outcomes in critically ill trauma patients. Success in this endeavor will go far to reach the goals to integrate biotechnology, genomics and bioinformatics, to change clinical practice, and to invigorate the concept of personalized medicine in the critically ill patient. PUBLIC HEALTH RELEVANCE: Data from this study would help develop a clinical diagnostic test to predict patient outcomes after severe trauma, and to discover signatures that could help doctors select a personalized drug therapy for an individual patient.