Discovery of Plasma Biomarkers of Delayed Cerebral Ischemia after Subarachnoid Hemorrhage

蛛网膜下腔出血后迟发性脑缺血血浆生物标志物的发现

• 批准号: 10358411
• 负责人: Huimahn Alex Choi
• 金额: $ 65.58万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-15 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10358411
• 关键词: Address; Affect; Area; Binding Proteins; Biological Assay; Biological Markers; Biological Process; Blinded; Blood; Blood Tests; Brain; Brain Aneurysms; Brain hemorrhage; Caring; Cerebral Aneurysm; Cerebral Ischemia; Cerebral hemisphere hemorrhage; Characteristics; Clinical; Clinical Research; Clinical Trials Design; Complex; Complication; Data; Detection; Development; Exposure to; Focal Neurologic Deficits; Functional disorder; GDF8 gene; Glycoproteins; Goals; Health; Hospitals; Hour; Individual; Intensive Care Units; Interferon Type II; Intervention; Intervention Studies; Investigation; Lead; Leucine; Logistic Regressions; Measures; Morbidity - disease rate; Neurologic Deficit; Patients; Pattern; Performance; Phase; Plasma; Plasma Proteins; Population; Preparation; Process; Prospective cohort; Proteins; Proteomics; Public Health; Randomized Clinical Trials; Reproducibility; Research; Resource Allocation; Resources; Risk; Rupture; Sampling; Sensitivity and Specificity; Series; Subarachnoid Hemorrhage; Subarachnoid Space; Technology; Testing; Treatment Side Effects; United States National Institutes of Health; base; biomarker signature; biomarker validation; candidate marker; cohort; detection assay; detection method; effective therapy; guanylate; high risk; improved; individualized medicine; innovation; machine learning model; member; minimally invasive; neurexophilin; novel; patient stratification; prevent; prognostic; prognostic assays; prognostic performance; prognostic value; prognostication; prospective; protein biomarkers; public health relevance; response; risk stratification; scavenger receptor; screening; statistical and machine learning; validation studies

Subarachnoid Hemorrhage (SAH) is a debilitating type of hemorrhagic stroke that affects ~50,000 annually in the US. It is caused by a rupture of a cerebral aneurysm and hemorrhage into the subarachnoid space around the brain. In those who survive the initial bleed, ~30% of the patients develop a serious secondary complication called delayed cerebral ischemia (DCI). DCI typically occurs at 4-21 days after SAH and is characterized by focal neurological deficits. Though DCI is a potentially preventable contributor to morbidity after SAH, interventional studies targeting DCI have failed. A major hindrance in SAH research is our inability to prognosticate which SAH patient will develop DCI. This leads to all SAH patients being observed for prolonged periods in the intensive care unit leading to higher rates of in-hospital complications, potential delay in treatment and misappropriated resources. Furthermore, because of the inability to risk-stratify SAH patients, randomized clinical trials require large populations, are expensive and have failed to identify effective treatments. Inclusion of subjects who are less likely to develop DCI, have led to exposing them to unwanted side effects from the treatment with no potential benefits. Identification of patients who will develop DCI is an unmet clinical need. Currently, there are no biomarkers with sufficient sensitivity and specificity to serve as a clinically useful screening test. This proposal therefore addresses a major unmet clinical need: a lack of a biomarker that can prognosticate DCI. Through a series of previous clinical studies, we have demonstrated that SAH leads to increases in systemic pathophysiological responses. We showed that an early elevated pathophysiological response, quantified by measuring plasma protein biomarkers, was associated with the development of DCI. We have expanded this line of investigation and via targeted proteomic profiling in pilot cohorts. First, we identified 6 plasma proteins that are prognostic of DCI within 48 hours of SAH. Second, using multivariate statistical and machine learning approaches, we identified a biomarker signature (a combination of proteins) that improved DCI prognostication. In this study, we propose to identify and confirm additional candidate biomarkers, develop and internally validate protein detection technology and verify the proof of concept in a prospective cohort. Performance characteristics of the candidate markers and the signature will be determined and validated for clinical use. Development of effective, minimally invasive biomarkers for DCI prognostication will lead to significant improvements in SAH management. Public/Health/Relevance: SAH has detrimental effects on individual health and the economy as a whole. The proposed research is relevant to public health as it will improve prognostication of DCI (an avoidable complication after SAH). This would lead to discovery of proteins that prognosticate DCI, improve our understanding of the pathophysiology of DCI and lead to improvements in design of clinical trials targeting DCI.

蛛网膜下腔出血 (SAH) 是一种使人衰弱的出血性中风，每年影响约 50,000 人 美国。它是由脑动脉​​瘤破裂并出血到周围的蛛网膜下腔引起的 大脑。在初次出血后幸存的患者中，约 30% 的患者会出现严重的继发并发症 称为迟发性脑缺血（DCI）。 DCI 通常发生在 SAH 后 4-21 天，其特点是局灶性 神经功能缺陷。尽管 DCI 是 SAH 后发病率的一个潜在的可预防因素，但介入治疗 针对 DCI 的研究失败了。 SAH 研究的一个主要障碍是我们无法预测哪种 SAH 患者会出现 DCI。这导致所有 SAH 患者在重症监护室接受长时间观察 护理病房导致院内并发症发生率较高、可能延误治疗和挪用 资源。此外，由于无法对SAH患者进行风险分层，随机临床试验需要 人口众多、费用昂贵且未能找到有效的治疗方法。纳入的受试者是 不太可能发生 DCI，导致他们遭受治疗带来的不良副作用，而无需任何治疗 潜在的好处。识别将发生 DCI 的患者是一个未满足的临床需求。目前，有 没有具有足够敏感性和特异性的生物标志物可用作临床上有用的筛查测试。这个提议 因此解决了一个未满足的主要临床需求：缺乏可以预测 DCI 的生物标志物。通过一个 之前的一系列临床研究，我们已经证明 SAH 会导致全身性 病理生理反应。我们表明，早期升高的病理生理反应，通过量化 测量血浆蛋白生物标志物与 DCI 的发展相关。我们已经扩展了这个 调查线并通过试点队列中的目标蛋白质组分析。首先，我们鉴定了 6 种血浆蛋白 是 SAH 48 小时内 DCI 的预后。二、利用多元统计和机器学习 通过这些方法，我们确定了一种可以改善 DCI 预测的生物标志物特征（蛋白质组合）。 在这项研究中，我们建议识别和确认其他候选生物标志物，开发和内部验证 蛋白质检测技术并在前瞻性队列中验证概念证明。性能特点 将确定并验证候选标记和签名的数量以供临床使用。发展 用于 DCI 预测的有效、微创生物标志物将导致 SAH 的显着改善 管理。 公共/健康/相关性：SAH 对个人健康和整体经济产生不利影响。拟议的研究与公共卫生相关，因为它将改善 DCI（SAH 后可避免的并发症）的预后。这将导致预测 DCI 的蛋白质的发现，提高我们对 DCI 病理生理学的理解，并导致针对 DCI 的临床试验设计的改进。