Massively high-throughput profiling of the circulating antibody pool for identification of diagnostic signatures with utility for stroke triage

项目摘要/摘要： 中风目前是美国第三大死亡原因和永久残疾的主要原因。 由于与急性卒中干预相关的时间-疗效关系，允许准确 分诊期间的卒中诊断有可能简化护理并改善患者的预后。早些时候 运送、转院和转诊的决定通常由急救医疗服务人员、分诊 使用基于症状的中风识别的有限神经学专业知识的护士和急诊医生 比例。不幸的是，这些评估在分类方案中表现出的准确性有限，目前 据估计，多达30%的中风患者在第一次与临床医生接触时被误诊，导致 危及生命的护理延误。因此，人们一直在推动识别特定于中风的血液 可以在护理点快速测量的生物标志物，以帮助临床医生，而不需要广泛的神经学 专业知识使早期的分诊决定更有见地。越来越明显的是，外围设备 免疫系统错综复杂地参与了中风的病理过程，可能是中风发生发展的靶点。 诊断。不仅有对急性损伤的快速全身炎症反应，而且有新的证据表明 提示外周免疫变化可能先于症状出现，在某些情况下会引发急性 事件本身。外周血液含有多达1018种独特的抗体，这些抗体针对的抗原与近 一个人一生中经历的每一次适应性免疫反应，以及抗体的全部 在个人血液中发现的可以作为他们免疫史的详细分子指纹 目前的免疫状态。在拟议的调查中，我们的目标是确定中风相关的改变 循环抗体库，可用于在分诊期间帮助识别中风。为了实现这一目标， 将从一组连续的疑似中风患者紧急情况下采集外周血液 科室入院。根据最终的临床诊断，患者将被分成确诊的中风组 或者是一个中风模仿组。由33万个独特探针组成的多肽阵列将被广泛用于 评估每个患者的外周血液抗体库的结合特性，并进行机器学习 将使用一种方法来确定能够以最佳方式区分不同群体的绑定模式。这部作品 将首次采用全面的方法来分析中风患者的循环抗体库 全球搜索特定于疾病的变化模式；吞吐量水平，与使用 强大的机器学习方法，将增加识别诊断可靠的生物标记物的几率 配置文件。此外，通过肽阵列鉴定的诊断有用的探针可以容易地用于 护理点，为临床使用提供了一条明确的途径。这一新颖、创新且高度可转换的工作流程 将解决一个迫切的临床需求领域；我们完全期待确定一组候选多肽探针，这将 为开发快速护理点卒中分诊诊断提供直接基础。

PROJECT SUMMARY/ABSTRACT: Stroke is currently the third leading cause of death and leading cause of permanent disability in the United States. Due to the time-efficacy relationship associated with acute stroke interventions, tools which allow for accurate stroke diagnosis during triage have the potential to streamline care and improve patient outcomes. Early transport, transfer, and referral decisions are often made by emergency medical services personnel, triage nurses, and emergency physicians with limited neurological expertise using symptom-based stroke recognition scales. Unfortunately, these assessments exhibit limited accuracy in triage scenarios, and it is currently estimated that up to 30% of patients experiencing stroke are misdiagnosed at first clinician contact, leading to life threatening delays in care. As a result, there has been a push for the identification of stroke-specific blood biomarkers which could be rapidly measured at the point-of-care to help clinicians without extensive neurological expertise make better-informed early triage decisions. It is becoming increasingly evident that the peripheral immune system is intricately involved in stroke pathology, and may be targetable for the development of stroke diagnostics. Not only is there a rapid systemic inflammatory response to the acute injury, but emerging evidence suggests that peripheral immune changes may precede symptom onset and in some cases trigger the acute event itself. The peripheral blood contains up to 1018 unique antibodies targeting antigens associated with nearly every adaptive immune response an individual has experienced in their lifetime, and the repertoire of antibodies found in an individual’s blood can serve as a detailed molecular fingerprint of their immune history as well as current immune status. In the proposed investigation, we aim to identify stroke-associated alterations to the circulating antibody pool which could be used to aid in stroke recognition during triage. To address this aim, peripheral blood will be sampled from a group of consecutive patients suspected of stroke at emergency department admission. Upon final clinical diagnosis, patients will be divided into either a confirmed stroke group or a stroke mimic group. Peptide arrays comprised of 330,000 unique probes will be used to comprehensively assess the binding characteristics of each patient’s peripheral blood antibody pool, and a machine-learning approach will be used to identify a pattern of binding which can optimally discriminate between groups. This work will be the first ever to take a comprehensive approach to profiling the circulating antibody pool in stroke to globally search for disease-specific patterns of alterations; the level of throughput, in combination with the use of powerful machine-learning methods, will increase the odds of identifying diagnostically robust biomarker profiles. Furthermore, diagnostically useful probes identified via peptide array can be readily adapted for use at the point-of-care, providing a clear path to clinical use. This novel, innovative, and highly translational workflow will address an area of dire clinical need; we fully expect to identify a set of candidate peptide probes which will provide the immediate foundation for the development of a rapid point-of-care stroke triage diagnostic.