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

对循环抗体库进行大规模高通量分析，用于识别诊断特征并用于中风分类

基本信息

批准号：
10457459
负责人：
Grant C O'Connell
金额：
$ 24.15万
依托单位：
CASE WESTERN RESERVE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-07-27 至 2024-06-30
项目状态：
已结题

项目摘要

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.

项目概要/摘要：目前，中风是美国第三大死亡原因和导致永久残疾的主要原因。由于与急性卒中干预相关的时间-效果关系，可以使用能够准确进行干预的工具分诊期间的中风诊断有可能简化护理并改善患者的早期治疗结果。运输、转移和转诊决定通常由紧急医疗服务人员做出神经学专业知识有限的护士和急诊医生使用基于症状的中风识别不幸的是，这些评估在分类场景中的准确性有限，目前是这样。据估计，高达 30% 的中风患者在第一次与临床医生接触时被误诊，导致因此，人们一直在推动识别中风特异性血液。可以在护理点快速测量的生物标志物，无需进行广泛的神经学检查即可提供帮助越来越明显的是，外围设备的专业知识可以做出更明智的早期分诊决策。免疫系统与中风病理学密切相关，并且可能是中风发展的目标不仅有对急性损伤的快速全身炎症反应，而且有新的证据。表明外周免疫变化可能先于症状出现，并在某些情况下引发急性症状外周血含有多达 1018 种独特的抗体，其目标抗原与近乎相关。个体一生中经历过的每一次适应性免疫反应，以及抗体库在个体血液中发现的可以作为其免疫历史的详细分子指纹以及在拟议的研究中，我们的目标是确定与中风相关的改变。循环抗体池可用于在分诊过程中帮助识别中风。将在紧急情况下从一组连续疑似中风的患者中采集外周血样本最终临床诊断后，患者将被分为已确诊的中风组。或由 330,000 个独特探针组成的肽阵列将用于全面评估。评估每个患者外周血抗体库的结合特征，以及机器学习这项工作将用于确定可以最佳地区分群体的结合模式。将是有史以来第一个采用综合方法来分析中风循环抗体库的方法全局搜索特定疾病的改变模式；结合使用的吞吐量水平强大的机器学习方法将增加识别诊断上稳健的生物标志物的几率此外，通过肽阵列鉴定的诊断有用的探针可以很容易地适用于。这种新颖、创新且高度转化的工作流程为临床使用提供了明确的途径。将解决临床急需的领域；我们完全期望找到一组候选肽探针为快速护理点中风分类诊断的开发提供直接基础。