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Whole Transcriptome Studies of Patients with Transient Ischemic Attacks (TIAs)

短暂性脑缺血发作 (TIA) 患者的全转录组研究

基本信息

批准号：
9896876
负责人：
FRANK R SHARP
金额：
$ 54.48万
依托单位：
UNIVERSITY OF CALIFORNIA AT DAVIS
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-04-01 至 2022-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9896876
关键词：
Address Alternative Splicing Area Arterial Fatty Streak Atherosclerosis Biological Markers Blood Blood Platelets Blood Vessels Brain Cerebrum Clinical Coagulation Process Data Derivation procedure Diagnosis Diagnostic tests Diffusion Magnetic Resonance Imaging Epilepsy Event Exons Future Genes Genetic Transcription Goals Hour Immune Individual Ischemic Stroke Labyrinthine disorder Leukocytes Magnetic Resonance Imaging Measures Messenger RNA Meta-Analysis Methods Migraine Neurologic Patients Play Prevention therapy Publishing Quantitative Reverse Transcriptase PCR RNA ROC Curve Recurrence Resources Risk Risk Estimate Role Sensitivity and Specificity Site Stroke Stroke prevention Symptoms Testing Therapeutic Intervention Time Transcript Transient Ischemic Attack Validation Whole Blood base cohort emergency settings gene discovery high risk human subject improved learning algorithm mRNA Expression machine learning algorithm monocyte neutrophil novel peripheral blood platelet function prospective public health relevance release factor stroke risk transcriptome transcriptome sequencing

项目摘要

DESCRIPTION (provided by applicant): Transient ischemic attacks (TIA) are critical to identify because prevention therapy can reduce the risk of future vascular events by > 50%. Diagnostic testing and therapeutic intervention must start as soon as possible because 10-25% of TIAs have a stroke within 90 days. Because so many patients present emergently with transient neurological events the large majority of whom do not go on to have a stroke, methods for identifying TIAs at high risk for stroke have been sought so that work up and treatment can be targeted to those who need it most to save time, money and limited resources. Though the ABCD2 score and brain Diffusion Weighted Imaging-MRI (DWI-MRI) have improved prediction of which TIAs have a stroke, their sensitivity and specificity for prediction of individual cases i poor. In this proposal we propose that peripheral blood leukocytes and platelets play pivotal roles in which TIAs go on to have a stroke and by assessing RNA in whole blood we can evaluate leukocyte and platelet function in TIA patients who go on to have stroke versus those that do not have a stroke. We hypothesize that specific coagulation and immune genes are activated in TIA patients that predispose them to have a stroke by 90 days compared to those TIA patients who do NOT have a stroke by 90 days. A subset of these leukocyte and platelet mRNA genes will predict TIAs who have a stroke by 90 days. This hypothesis is addressed by the following specific aims. Aim #1 (Derivation Cohort): Demonstrate that mRNA expression measured using RNAseq from whole blood differs in a derivation cohort of TIAs that go on to have a stroke by 90 days compared to those TIAs who do not have a stroke by 90 days. Demonstrate that most mRNA found to be regulated using RNAseq are also significantly regulated when measured using qRT-PCR. Aim #2 (Derivation Cohort): Apply machine learning algorithms to the mRNA from Aim #1 to derive an optimal subset of mRNA regulated by both RNAseq and qRT-PCR that predict which TIAs have strokes by 90 days compared to those who do not with >95% sensitivity on cross-validation. Aim #3 (Validation Cohort): Use machine/prediction learning algorithms to demonstrate that the genes from Aim #2 when measured using qRT-PCR on an independent validation cohort predict which TIAs have a stroke by 90 days with >85% sensitivity. The goal of these studies is to discover mRNA profiles in blood that predict which TIA patients go on to have strokes by 90 days. When confirmed in future studies, this will direct in depth testing to those high risk TIAs most in need in order to prevent strokes, and decrease unnecessary testing in those with low risk of stroke. Equally as important, the genes discovered to be associated with high risk of stroke in TIA patients will represent potential novel stroke prevention targets.

描述（由申请人提供）：短暂性脑缺血发作 (TIA) 的识别至关重要，因为预防治疗可以将未来血管事件的风险降低 50% 以上。必须尽快开始诊断测试和治疗干预，因为 10-25% 的 TIA 会在 90 天内发生中风。由于许多患者突然出现短暂性神经系统事件，其中绝大多数不会继续发生中风，因此人们一直在寻找识别中风高风险 TIA 的方法，以便针对最需要的人进行检查和治疗，以节省时间、金钱和有限的资源。尽管 ABCD2 评分和脑弥散加权成像 MRI (DWI-MRI) 改善了对 TIA 中风的预测，但它们对个别病例预测的敏感性和特异性较差。在本提案中，我们提出外周血白细胞和血小板在 TIA 继续发生中风的过程中发挥着关键作用，通过评估全血中的 RNA，我们可以评估继续发生中风的 TIA 患者与未发生中风的患者的白细胞和血小板功能。我们假设 TIA 患者的特定凝血和免疫基因被激活，与 90 天内未发生中风的 TIA 患者相比，他们更容易在 90 天内发生中风。这些白细胞和血小板 mRNA 基因的一个子集将在 90 天前预测是否会发生中风 TIA。该假设通过以下具体目标来解决。目标#1（衍生队列）：证明使用 RNAseq 从全血中测量的 mRNA 表达在 90 天后发生中风的 TIA 衍生队列中与 90 天后未发生中风的 TIA 衍生队列中存在差异。证明使用 RNAseq 调节的大多数 mRNA 在使用 qRT-PCR 测量时也受到显着调节。目标#2（推导队列）：将机器学习算法应用到目标#1 的 mRNA 中，以获得由 RNAseq 和 qRT-PCR 调节的最佳 mRNA 子集，在 90 天前预测哪些 TIA 会发生中风，与那些没有发生中风的 TIA 相比，交叉验证的灵敏度 >95%。目标#3（验证队列）：使用机器/预测学习算法来证明，在独立验证队列中使用 qRT-PCR 测量时，来自目标#2 的基因可以在 90 天内预测哪些 TIA 会发生中风，灵敏度 >85%。这些研究的目标是发现血液中的 mRNA 谱，以预测哪些 TIA 患者会在 90 天后发生中风。当未来的研究得到证实时，这将指导对那些最需要预防中风的高风险 TIA 进行深入测试，并减少对中风风险低的人进行不必要的测试。同样重要的是，发现的与 TIA 患者中风高风险相关的基因将代表潜在的新型中风预防目标。