GENETICS AND PREDICTION OF CEREBRAL EDEMA AFTER HEMISPHERIC STROKE

半球卒中后脑水肿的遗传学和预测

基本信息

批准号：
10237306
负责人：
Rajat Dhar
金额：
$ 17.41万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-01 至 2022-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10237306
关键词：
Accounting Alzheimer&apos s Disease Area Attenuated Bioinformatics Biological Biology Blood - brain barrier anatomy Brain Brain Edema Brain Injuries Cell Death Cerebral Edema Cessation of life Clinical Complex Complication Coupled Data Data Set Deterioration Development Disease Drug Targeting Edema Enrollment Foundations Funding Genes Genetic Genetic Markers Genetic Polymorphism Genetic Risk Genetic Variation Genetic study Genomic approach Genomics Genotype Goals Grant Hemorrhage Heritability Heterogeneity Image Infarction Inflammation Intervention Knowledge Lead Learning Malignant - descriptor Measurement Measures Medical Genetics Mentors Methods Modeling Modernization Molecular Nature Neurologic Operative Surgical Procedures Outcome Pathway Analysis Pathway interactions Patients Phenotype Process Research Residual state Risk Scanning Severities Site Stroke Structure Subgroup Swelling Techniques Testing Therapeutic Intervention Time Training Traumatic Brain Injury Variant Work X-Ray Computed Tomography acute stroke aggressive therapy automated algorithm cohort endophenotype follow-up genetic architecture genetic makeup genetic variant genome wide association study genome-wide genotyped patients high risk imaging genetics improved individual response innovation novel marker post stroke precision medicine quantitative imaging rare variant stroke patient success tau Proteins trait tumor

项目摘要

PROJECT SUMMARY The greatest contributor to neurological deterioration in the first week after stroke is development of brain swelling around the area of infarction. However, only half of those with large strokes develop malignant cerebral edema sufficient to compress adjacent brain structures and threaten survival. Clinical factors including stroke size do not explain the degree of edema that develops. Instead, it is likely that intrinsic differences in cellular mechanisms and biologic pathways activated after stroke contribute to the observed heterogeneity in swelling. We believe that identifying the genetic factors underlying this biologic variability will provide important actionable knowledge that could lead to improved targeted treatments for edema and better prediction of who is at risk. In order to study the biology of cerebral edema, we need to capture the full spectrum of its severity with an accurate and quantifiable measure of swelling. We have developed a novel marker of edema severity that measures amount of CSF pushed out of the brain as the stroke swells. This measure (∆CSF) has been validated in a preliminary study and we will now refine it by modeling ∆CSF at any time point (whenever CT is performed, using 400 scans already acquired coupled to an automated algorithm we have developed). This intermediate phenotype will capture rate of edema formation and be able to quantify which patients have relatively malignant trajectories vs. those who are relatively protected (given their stroke severity and infarct size) against developing edema. We are continuing to acquire CT scans from subjects enrolled in a large multi-site acute stroke study that already has almost 3,000 patients genotyped (supported by my primary mentor, Jin-Moo Lee’s R01 grant studying neurological improvement after stroke). We will measure rate of ∆CSF in this larger (and still expanding) cohort and quantify the residual variability (adjusting for clinical covariates) in order to ascertain for potential genetic component. Our genomic analyses of this edema endophenotype will include GCTA, a means of estimating total heritability, followed by genome-wide association study to identify common polymorphisms associated with our continuous measure of edema. This unbiased discovery approach will be supplemented by modern evolving means of uncovering rare variants and genetic pathways that could further explain heritability of edema and provide refined biologic targets. I will also learn to evaluate the functional significance of any potential genetic markers identified with these analyses. I will be mentored in these bioinformatics and quantitative genomic methods by Dr. Carlos Cruchaga, a geneticist with special expertise in dissecting complex traits using quantitative endophenotypes (e.g. CSF tau levels as intermediate phenotypes for Alzheimer’s disease). This project represents not only the first study of the genetic basis of cerebral edema but also a first step in a research pathway that will continue as I move toward independent funding to further understand edema, a disease with immense significance across all forms of brain injury. I plan to continue building upon my training and data by replicating and sequencing promising targets and expanding upon them by studying convergent phenotypes such as hemorrhagic transformation after stroke. I will also leverage my training to construct a clinical-genetic risk score for edema after stroke, incorporating the most informative genetic markers for malignant edema. Ultimately, the information gained on biology of edema could inform therapeutic interventions to block edema as we move towards a precision-medicine approach to managing brain injury.

项目摘要中风后的第一周，神经系统恶化的最大贡献是脑素的发展但是，在梗塞区域肿胀。大脑水肿足以压缩相邻的大脑结构并威胁临床因素包含中风的大小不能解释发展的水肿。中风后激活的细胞机制和生物途径的差异有助于观察到肿胀中的异质性。将提供重要的可行知识，可以改善污染物的污染物更好地预测谁处于危险之中。为了研究脑水肿的生物学，我们需要通过准确量化的肿胀度量。从中风隆起的脑电图量（∆ CSF）的量度已在初步研究中验证，我们现在将通过在任何时间点对∆ CSF进行建模（每当使用已经获得的400次扫描到我们已经开发的自动化算法的双扫描进行了CT。塞氏表型将捕获形成水肿的速率，并能够量化哪些患者具有相对恶性轨迹与THO相对保护梗塞大小）反对发展水肿。我们将继续从参加大型多站点急性研究的受试者中获取CT扫描，该研究已经有近3,000名患者基因分型（Jin-Moo Lee的R01赠款研究中风后的神经学改善）。扩展）队列并量化残余变异性（调整临床协变量），以便确定潜在的遗传成分。 GCTA，一种估计总遗传力的手段，然后进行全基因组关联研究以识别与我们连续的水肿量度相关的常见多态性现代进化的方法将揭示方法的稀有变体和遗传可以解释水肿的遗传力并提供精致的生物学靶标的途径。学会评估用这些人识别的任何潜在遗传标记的功能意义。我将受到Carlos Cruchaga博士的生物信息学和定量基因组方法的指导具有定量内表型（例如CSF）在解剖性状特征方面具有特殊专业知识的遗传学家 tau水平为阿尔茨海默氏病的中间表型）。该项目不仅代表了大脑水肿遗传基础的第一个故事，而且代表了当我走向独立进一步了解水肿时，将包含一个研究途径，我计划继续在我的脑损伤中具有巨大意义的疾病。通过复制和测序有希望的目标并通过研究来扩展培训和数据中风后的收敛表型。构建中风后水肿的临床遗传风险评分，并纳入最多的信息遗传最终的恶性水肿标记。当我们朝着管理中的精确医学方法时，治疗性干预措施可以阻止水肿脑损伤。