Biomarker Signatures for Delayed Cerebral Ischemia and Outcome Following Subarachnoid Hemorrhage

摘要 蛛网膜下腔出血（SAH）占所有卒中的5%，具有高死亡率和治疗费用。 社会与缺血性中风相似，因为受试者更年轻。尽管蛛网膜下腔出血死亡率有所下降， 在过去25年中，由于动脉瘤的即时修复、医疗管理的改善和 尼莫地平治疗SAH后，约1/3的SAH患者发生迟发性脑缺血（DCI），常伴有脑梗死 这与不良结果有关。虽然这被认为是由于迟发性脑血管痉挛， 最近的研究表明，减少或预防血管痉挛并不能改善结果。这导致 微血管血栓形成和血管痉挛的联合作用， 皮层扩散性缺血和外周及中枢炎症可引起DCI。因此， 未满足的需求，以评估潜在的治疗目标，这些目标有助于人类SAH后的DCI， 可用于预测DCI以开始早期治疗，并预测结果以更好地分配资源。的 该建议的前提是基于我们已经表明血液中的基因表达可以 预测发生血管痉挛的SAH患者。这让我们假设凝血和炎症 血液中的分子与脑微血管系统和其他因素相互作用， SAH后缺血（DCI）和迟发性脑梗死导致预后不良。我们建议 血液中的基因谱将预测DCI并使用改良的兰金量表（mRS）预测结果。 R61阶段。具体目标#1a：对培训队列的全血进行RNA测序（RNAseq） 与匹配的血管风险因素对照相比，SAH后1、2和3天但DCI前的患者。 具体目标#1B。在1、2或3天确定血液中最显著调节的基因和途径， 区分在4-14天发生DCI的SAH患者与未发生DCI的SAH患者。具体 目的#1c：使用WGCNA鉴定SAH后1、2或3天表达的关键枢纽基因和上游基因， 与4- 14日龄DCI的发生有关，可能是导致DCI的原因。具体目标#1使用支持 向量机（SVM）学习，以识别在目标#1b的第1、2或3d的最少数量的基因， 预测（1）在4-14天发生DCI的SAH患者（2），并预测3个月时mRS为0、1-3、4-5和6。 具体目标#1。使用qRT-PCR确认RNAseq并评估qRT-PCR准确度和精密度。 R33阶段。具体目标#2在SAH患者的单独验证队列中，对其进行qRT-PCR。 外周血，测量目标#1中衍生的基因表达，使用支持向量机进行预测 (SVM)在第1、2和/或3天，哪些患者将在第4-14天发生DCI，哪些患者将具有 3个月时mRS=0（无功能缺损）、1-2、3-5和mRS=6（死亡）。 使用的背景。预测DCI和mRS的分子/途径可以作为未来的治疗或治疗方法。 DCI的预防目标。预测谁将发展DCI将使早期治疗DCI成为可能。在 此外，未来预防SAH后DCI的临床试验将只招募那些预测会发生DCI的患者， 蛛网膜下腔出血后的总督察预测mRS结局可用于在未来的DCI试验中对患者进行分层。

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.