Merging Temporal Changes in Clinical Informatics, Transcriptomics, and Cytokine Profiles to Understand the Host Response to Bacteremia

作为一名ICU内科医生和免疫学家，我一直致力于了解脓毒症， 这种疾病每年影响美国近200万人。败血症是一种危及生命的疾病 当身体对感染的反应损害自身组织时出现的一种状态。大踏步前进 已经为改善败血症患者的临床护理做出了努力，但死亡率 保持20%的比例有几个原因：首先，每种引起败血症的病原体，无论是细菌、病毒或 真菌本身携带的毒力因子会影响宿主的反应，但不幸的是， 研究的重点是将败血症患者作为一个群体进行研究，而不是区分患者 基于微生物原因。其次，研究人员经常在患者出现症状后进行研究 脓毒症引起的器官衰竭但许多人因常见的脓毒症而感染 病原体，如金黄色葡萄球菌，但永远不会发展成败血症；理解“适当” 对病原体的反应是理解病原体的“不适当”反应的关键 败血症。最后，许多败血症研究都发生在筒仓中；临床研究人员将重点放在 电子病历，而基础科学家分析生物数据。太多时候，这些 群体不合作共享信息，即使理解生物 临床数据的意义可能具有重要的价值。为了解决这些问题，我提出了一个独特的 了解宿主对感染的反应的方法，结合了生物数据和 金黄色葡萄球菌菌血症患者的临床电子病历(EMR)数据。 通过对宿主对由单一病原体引起的感染的反应的限制分析 我们可以控制由病原菌特异性因素引起的变异性。此外, 通过研究所有金黄色葡萄球菌菌血症患者，而不仅仅是那些患有 脓毒症，我们既可以理解适当的宿主反应，也可以了解不适当的宿主 这是败血症发展的特征。我们的样本银行是从S。 金黄色葡萄球菌菌血症患者我们将同时分析细胞mRNA转录本和血浆 蛋白质/细胞因子水平，从每个患者的不同时间点收集。我们会 将这些分析的结果与电子病历中发现的临床数据相结合，以提供相关性 宿主的生物学反应与其临床表现之间的关系。我们的每位患者 然后，数据将具有前所未有的粒度，然后我们可以使用它来应用机器学习 识别预测结果(如死亡率)的多方面内型的技术。一旦我们 已经建立了这些内型模型，我们将使用从新收集的试点数据来验证它们 入选的金黄色葡萄球菌或大肠杆菌菌血症患者。这种方法将允许 美国确定所有感染中调节失调的宿主反应的共同因素，以及 这些可能是针对感染类型的。了解这两个 适当和不适当的宿主对感染的反应，以及理解哪些 宿主反应的某些方面是病原体特有的(哪些不是)将允许发育 治疗这种毁灭性疾病的新疗法。

As an ICU physician and an immunologist, I have devoted my research career to understanding sepsis, a disease that affects nearly 2 million people annually in the USA. Sepsis is a life-threatening condition that arises when the body's response to infection injures its own tissues. Great strides have been made towards improving the clinical care of the septic patient, but the mortality rate remains >20% for several reasons: First, each sepsis-causing pathogen, be it bacterial, viral, or fungal, carries its own virulence factors that affect the host response, but unfortunately, much research has focused on studying septic patients as a group, rather than distinguishing patients based on microbiologic cause. Second, researchers often study patients once they manifest sepsis-induced organ failure yet many people sustain infections due to common sepsis pathogens, like Staphylococcus aureus, but never develop sepsis; understanding the "appropriate" response to a pathogen is critical to understanding the "inappropriate" response of sepsis. Finally, much sepsis research occurs in silos; clinician researchers focus on the electronic medical record, while basic scientists analyze biologic data. Too often, these groups do not collaborate to share information, even though understanding the biologic significance of clinical data may be of great value. To address these issues, I propose a unique approach to understand the host response to infection that incorporates both biologic data and clinical electronic medical record (EMR) data from patients with S. aureus bacteremia. By limiting analysis of the host response to infections caused by a single pathogen at a single site, we can control for the variability induced by pathogen-specific factors. In addition, by studying all patients with S. aureus bacteremia, and not simply those patients with sepsis, we can understand both the appropriate host response as well as the inappropriate host response that characterizes the development of sepsis. With our bank of samples collected from S. aureus bacteremia patients we will analyze both cellular mRNA transcripts and plasma protein/cytokine levels, collected at different time points from each patient. We will combine the results of these analyses with clinical data found in the EMR to provide a correlation between the biology of the host response and its clinical manifestations. Our per-patient data, then, will have unprecedented granularity which we can then use to apply machine learning techniques to identify multi-faceted endotypes that predict outcomes (such as mortality). Once we have built these endotype models, we will validate them using pilot data collected from newly enrolled patients with either S. aureus or E. coli bacteremia. This approach will allow us to identify factors common to the dysregulated host response across all infections, as well as those that may be specific to the type of infection. Understanding both the appropriate and the inappropriate host response to infection, and understanding which aspects of the host response are pathogen-specific (and which are not) will allow development of novel therapies for this devastating disease.