Biomarker Signatures for Delayed Cerebral Ischemia and Outcome Following Subarachnoid Hemorrhage

迟发性脑缺血的生物标志物特征和蛛网膜下腔出血后的结果

• 批准号: 10322173
• 负责人: Bradley Pearce Ander
• 金额: $ 64.14万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10322173
• 关键词: 3-Dimensional; Affect; Age; Aneurysm; Aneurysmal Subarachnoid Hemorrhages; Angiography; Arteries; Blood; Blood - brain barrier anatomy; Catheters; Cerebral Infarction; Cerebral Ischemia; Cerebral hemisphere hemorrhage; Cerebrovascular Spasm; Cerebrum; Clinical; Clinical Trials; Coagulation Process; Cognitive; Complication; Derivation procedure; Diagnosis; Early treatment; Endothelin Receptor Antagonist; Enrollment; FDA approved; Future; Gene Expression; Genes; Hemorrhage; Human; Image; Inflammation; Inflammatory; Ischemia; Ischemic Stroke; Lead; Machine Learning; Measures; Medical; Meta-Analysis; Modeling; Morbidity - disease rate; Myocardial dysfunction; Neurologic; Nimodipine; Outcome; Pathway interactions; Patients; Peripheral; Pharmaceutical Preparations; Phase; Placebos; Prevention; Pulmonary Edema; Quantitative Reverse Transcriptase PCR; Randomized Clinical Trials; Resources; Sensitivity and Specificity; Societies; Stroke; Subarachnoid Hemorrhage; Survivors; Systemic Inflammatory Response Syndrome; Thrombosis; Training; Validation; Vasospasm; Whole Blood; Work; base; biomarker signature; care costs; cerebral microvasculature; cohort; cost; improved; improved outcome; mortality; outcome prediction; patient stratification; peripheral blood; prevent; repaired; spreading depression; stroke patient; support vector machine; transcriptome; transcriptome sequencing; treatment trial; vascular risk factor; whole genome

Abstract Subarachnoid hemorrhage (SAH) accounts for 5% of all strokes, has a high mortality and the cost to society is similar to ischemic stroke since subjects are much younger. Though SAH fatality has decreased ~50% in the last 25 years due to immediate repair of aneurysms, improved medical management and nimodipine, nearly 1/3 of SAH patients develop delayed cerebral ischemia (DCI) often with cerebral infarction which is associated with poor outcomes. Though this was thought to be due delayed cerebral vasospasm, recent studies have shown that decreasing or preventing vasospasm does not improve outcomes. This has led to alternative hypotheses that combined effects of microvessel thrombosis and vasospasm combined with cortical spreading ischemia and peripheral and central inflammation may cause DCI. Thus, there is a great unmet need to assess potential treatment targets that contribute to DCI following SAH in humans and that could be used to predict DCI to begin early treatment and to predict outcome to better allocate resources. The premise of the proposal is based upon the findings that we have shown that gene expression in blood can predict SAH patients who develop vasospasm. This led us to Hypothesize that clotting and inflammatory molecules in blood interact with the brain microvasculature and other factors to cause Delayed Cerebral Ischemia (DCI) and delayed cerebral infarction following SAH which lead to poor outcomes. We propose that gene profiles in blood will predict DCI and predict outcomes using the modified Rankin Scale (mRS). R61 Phase. Specific Aim #1a: Perform RNA sequencing (RNAseq) on whole blood of a training cohort of patients 1, 2 and 3 days after a SAH but prior to DCI compared to matched vascular risk factor controls. Specific Aim #1b. Identify the most significantly regulated genes and pathways in blood at 1, 2 or 3d that distinguish SAH patients who develop DCI at 4-14 days from SAH patients who do not develop DCI. Specific Aim #1c: Use WGCNA to identify key hub genes and upstream genes expressed at 1, 2 or 3d after SAH and which are associated with developing DCI at 4-14d and might be causative. Specific Aim #1d. Use Support Vector Machine (SVM) learning to identify the least number of genes at 1, 2 or 3d from Aim #1b that best predict (1) SAH patients who develop DCI at 4-14 days (2) and predict mRS of 0, 1-3, 4-5, and 6 at 3 months. Specific Aim #1e. Confirm RNAseq with qRT-PCR and assess qRT-PCR accuracy and precision. R33 Phase. Specific Aim #2. In a separate validation cohort of SAH patients perform qRT-PCR on their peripheral blood to measure expression of genes derived in Aim #1 to predict using Support Vector Machine (SVM) on day 1, 2 and/or day 3 which patients will develop DCI at 4-14 days and which patients will have mRS=0 (no deficit), 1-2, 3-5 and mRS=6 (dead) at 3 months. Contexts of Use. The molecules/pathways that predict DCI and mRS could serve as future treatment or prevention targets of DCI. Predicting who will develop DCI would make it possible to treat DCI earlier. In addition, future clinical trials to prevent DCI following SAH would enroll just those patients predicted to develop DCI after SAH. Predicting mRS outcomes could be used to stratify patients in future DCI trials.

抽象的 蛛网膜下腔出血（SAH）占所有中风的5％，死亡率很高，成本为 社会与缺血性中风相似，因为受试者年轻得多。虽然死亡人数有所减少 由于立即维修动脉瘤，改善医疗管理和 尼莫迪平（Nimodipine 这与不良结果有关。尽管这被认为是由于脑血管痉挛的延迟 最近的研究表明，减少或预防血管痉挛并不能改善预后。这已经引起了 与替代假设结合了微血管血栓形成和血管痉挛的影响 皮质扩散缺血，周围和中央炎症可能导致DCI。因此，有一个很棒的 无法评估人类SAH后有助于DCI的潜在治疗目标的未满足，并且 可以用来预测DCI开始早期治疗并预测结果以更好地分配资源。这 该提案的前提是基于我们表明血液中基因表达的发现 预测患有血管痉挛的SAH患者。这导致我们假设凝结和炎症 血液中的分子与脑微举行和其他因素相互作用，导致大脑延迟 SAH后，缺血（DCI）并延迟脑梗塞，导致结果不佳。我们提出了这一点 血液中的基因谱将使用改良的Rankin量表（MRS）预测DCI并预测结果。 R61相。特定目标＃1A：对训练队列的全血进行RNA测序（RNASEQ） 在SAH后1、2和3天的患者中，与匹配的血管危险因素对照相比，DCI之前的患者在DCI之前。 特定目标＃1B。确定在1、2或3D的血液中最显着调节的基因和途径 区分不发展DCI的SAH患者在4-14天开发DCI的SAH患者。具体的 AIM＃1C：使用WGCNA识别SAH后1、2或3D表达的关键集线器基因和上游基因 与在4-14d开发DCI有关的，可能是病因。特定目标＃1D。使用支持 向量机（SVM）学习以最佳的目的识别1、2或3D的基因数量最少 预测（1）在4-14天（2）中发展DCI的SAH患者，并且在3个月时预测MRS 0、1-3、4-5和6。 特定目标＃1E。用QRT-PCR确认RNASEQ并评估QRT-PCR的精度和精度。 R33阶段。特定目标＃2。在单独的验证队列中，SAH患者对其进行QRT-PCR 外围血液以测量在AIM＃1中得出的基因表达，以预测使用支持向量机器 （SVM）在第1、2和/或/或第3天，患者将在4-14天发展DCI，哪些患者将有 MRS = 0（无赤字），1-2、3-5和MRS = 6（死亡）3个月。 使用上下文。预测DCI和MRS的分子/途径可以作为将来的治疗或 DCI的预防目标。预测谁将开发DCI将有可能较早治疗DCI。在 此外，未来的临床试验以防止SAH之后的DCI，只会招募那些预计会发展的患者 SAH后DCI。预测MRS结局可用于在未来的DCI试验中对患者进行分层。