Biomarkers of Cerebral Cavernous Angioma with Symptomatic Hemorrhage (CASH)

伴有症状性出血的脑海绵状血管瘤 (CASH) 的生物标志物

基本信息

批准号：
10214712
负责人：
ISSAM A AWAD
金额：
$ 65.04万
依托单位：
UNIVERSITY OF CHICAGO
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-07-15 至 2025-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10214712
关键词：
Affect Age Algorithms American Anticoagulants Automobile Driving Behavior Benchmarking Benign Biological Markers Blood Blood - brain barrier anatomy Blood Tests Blood Vessels Blood capillaries Brain Pathology Brain hemorrhage Cavernous Hemangioma Cerebrovascular Disorders Cerebrum Characteristics Clinical Clinical Management Clinical Trials Complement Complex Computational Biology Cross-Sectional Studies Data Data Element Deposition Diagnosis Diagnostic Diagnostic Sensitivity Discriminant Analysis Disease Enrollment Exhibits Future Genetic Genotype Goals Hemorrhage IL6 gene Image Immune Individual Inflammation Inflammatory Interleukin-1 beta Iron Knowledge Lesion Machine Learning Magnetic Resonance Imaging Measures Mediating Modeling Monitor Natural Immunity Patients Perfusion Peripheral Pilot Projects Plasma Plasma Proteins Population Predisposition Process Prognosis Proteins RNA Research Research Personnel Risk Sampling Seizures Sensitivity and Specificity Signal Transduction Site Subgroup Techniques Testing Time Uncertainty Validation Variant Vascular Diseases Vascular Endothelial Growth Factors Vascular Permeabilities Vitamin D Deficiency accurate diagnosis angiogenesis base biomarker development biomarker discovery candidate marker clinical application clinically relevant cohort contrast enhanced data harmonization disorder subtype follow-up gut microbiome high risk imaging biomarker indexing machine learning algorithm microbiome nervous system disorder neurovascular unit novel novel marker peripheral blood premature prognostic prognostic value recruit response sex statistics supervised learning support vector machine synergism therapeutic development transcriptome trial readiness

项目摘要

Biomarkers of Cerebral Cavernous Angioma with Symptomatic Hemorrhage (CASH) PROJECT SUMMARY Cerebral cavernous angioma (CA) is a capillary microangiopathy affecting more than a million Americans, predisposing them to a premature risk of brain hemorrhage. Fewer than 200,000 cases who have suffered a recent symptomatic hemorrhage (SH) are most likely to re-bleed again with serious clinical sequelae, and are the primary focus of therapeutic development. Genetic mechanisms of CA have been extensively studied, and consequent signaling aberrations in the neurovascular unit. These include proliferative dysangiogenesis, blood- brain barrier hyperpermeability, inflammation and immune mediated processes, anticoagulant vascular domain, and gut microbiome-driven mechanisms. Plasma levels of molecules reflecting these mechanisms and measures of vascular permeability and hemorrhage leak on magnetic resonance imaging (MRI) have been correlated with CA hemorrhage in pilot studies. It would be desirable to optimize these biomarkers to accurately diagnose CASH, to prognosticate the risk of future SH, and to monitor cases after a bleed and in response to therapy. This would influence clinical management, and select higher risk cases for clinical trials. Additional candidate biomarkers are emerging from ongoing mechanistic and differential transcriptome studies, which would be expected to further enhance the sensitivity and specificity of diagnosis and prediction of CASH. Weighed combinations of levels of plasma proteins and characteristic micro-ribonucleic acids (miRNA) may further strengthen biomarker associations. Plasma biomarkers may reflect (and potentially replace) more cumbersome and expensive imaging biomarkers for monitoring CA hemorrhage. We here assemble leading clinical CA researchers and propose to deploy advanced statistical and computational biology approaches (including supervised machine learning) for the integration of novel candidate biomarkers, rejecting non-correlated candidates, and determining the best clustering and weighing of combined biomarker contributions. In Specific Aim 1 we assess these biomarkers in a large CA cohort from multiple sites, to discover the best plasma biomarkers and validate them in sex, age and relevant clinical subgroups. In Specific Aim 2 we compare changes in MRI measures of vascular permeability and hemorrhage with plasma biomarkers over time. In Specific Aim 3 we query the biomarkers in non-CA subjects, to identify potential confounders in the clinical context. This project leverages the synergy of established CA research consortia, and integrates analytic and computational biology expertise to develop blood tests for better CASH diagnosis and prognosis. The project tests a novel integrational approach of biomarker development in a mechanistically defined cerebrovascular disease with a relevant context of use. This approach is applicable to other neurological diseases with similar pathobiologic features.

伴有症状性出血的脑海绵状血管瘤 (CASH) 的生物标志物项目概要脑海绵状血管瘤（CA）是一种影响超过一百万美国人的毛细血管病，使他们过早出现脑出血的风险。遭受感染的病例不到20万最近的症状性出血 (SH) 最有可能再次出血并产生严重的临床后遗症，并且治疗发展的主要焦点。 CA的遗传机制已被广泛研究，并且神经血管单元中随之而来的信号畸变。这些包括增殖性血管生成障碍、血液- 脑屏障通透性过高、炎症和免疫介导的过程、抗凝血管域、和肠道微生物组驱动的机制。反映这些机制和措施的血浆分子水平磁共振成像（MRI）上的血管通透性和出血漏与试点研究中的 CA 出血。希望优化这些生物标志物以准确诊断 CASH，预测未来 SH 的风险，并监测出血后的病例和对治疗的反应。这会影响临床管理，选择风险较高的病例进行临床试验。其他候选生物标志物正在从正在进行的机械和差异转录组研究中出现，预计这些研究将进一步提高CASH诊断和预测的敏感性和特异性。权重组合血浆蛋白和特征性微核糖核酸 (miRNA) 的水平可能会进一步增强生物标志物协会。血浆生物标志物可能反映（并可能取代）更繁琐和昂贵的成像用于监测 CA 出血的生物标志物。我们在这里聚集了领先的临床 CA 研究人员并提议部署先进的统计和计算生物学方法（包括监督机器学习）整合新的候选生物标志物，拒绝不相关的候选物，并确定最佳的组合生物标志物贡献的聚类和权重。在具体目标 1 中，我们评估了这些生物标志物来自多个地点的大型 CA 队列，以发现最佳的血浆生物标志物并在性别、年龄和性别方面对其进行验证相关的临床亚组。在具体目标 2 中，我们比较了血管通透性 MRI 测量值的变化随着时间的推移，血浆生物标志物会出现出血。在特定目标 3 中，我们查询非 CA 中的生物标志物受试者，以确定临床背景中潜在的混杂因素。该项目利用了现有机构的协同作用 CA 研究联盟，整合分析和计算生物学专业知识，开发血液测试更好的 CASH 诊断和预后。该项目测试了一种新颖的生物标记物整合方法具有相关使用背景的机械定义的脑血管疾病的发展。这种做法适用于具有相似病理生物学特征的其他神经系统疾病。