Genetic Architecture of Cerebral Edema after Stroke

项目总结 脑水肿是神经恶化的主要原因，也是住院死亡的主要原因。 中风后。这种病理性的积水导致可以测量的脑体积的增加。 在大多数半球中风后。这种脑肿胀不仅增加了脑突出的风险，而且还损害了 中风的恢复和梗塞的增长一样多。然而，关键的生物学因素和分子机制 介导脑水肿形成的因素仍不明确。这种知识鸿沟阻碍了发展。 有针对性的干预措施，以减轻脑外伤等各种情况下的浮肿后果， 肿瘤、出血性和缺血性中风。患者之间的差异很大，有些患者 表现为恶性水肿，其他则无至轻度肿胀，尽管中风的大小和严重程度相似。这个 这项提议的中心目标是将成像与遗传学相结合，以识别关键的生物途径和 与脑水肿有牵连的介质。我们将获得NINDS资助的3506名患者的连续CT扫描 中风遗传学研究(Genisis)和1,000人正在参加ERA网络神经元资助的研究(IBioStroke)。 我们将应用自动化分析管道来获得水肿病的定量多维测量结果 严肃性。我们的主要生物标志物是脑脊液的置换(Δ脑脊液)，作为 中风后形成的肿胀体积。然而，我们也将测量半球脑脊液比率 皮损吸水表现为额外的水肿型。我们将模拟浮肿的形成(与时间有关 从中风开始)来评估生物因素，如年龄、性别、血糖、血压、 和肾功能，影响浮肿的形成。我们的中心假设是水肿病患者间的变异性 形成可能与有针对性的临床因素，如高血糖和信息性遗传有关 不同之处。我们的初步数据表明，Δ脑脊液具有重要的可遗传成分。特定目标 1致力于量化关键临床因素，如高血糖和血压与水肿的关系。 队形。我们将利用基因组数据来进一步剖析哪些因素是导致水肿形成的原因， 使用孟德尔随机化。我们还将量化水肿和出血性转化对 中风恢复了。《特定目标2》将确定与中风后脑水肿相关的基因和途径。它 将在这一大型队列中采用具有多种水肿表型的全基因组关联(GWAS)方法。 我们将使用功能注释工具进一步确定基因和通路的优先顺序。《特定目标3》将剖析共享 通过分析水肿与出血等特征的关系来对比特定于水肿的损伤机制 转化、白质损伤和小血管病变。它将利用现有的大型数据集来推动 来自目标2的基因发现的力量。一旦完成，这项工作将提供第一幅全面的图景 卒中后脑水肿的遗传结构，并提供对分子的公正的、新的见解 可以为药物发现提供信息的目标。

PROJECT SUMMARY Cerebral edema is a major contributor to neurological deterioration and the leading cause of in-hospital death after stroke. This pathologic water accumulation results in an increase in brain volume that can be measured after most hemispheric strokes. This brain swelling not only raises the risk of cerebral herniation but also impairs stroke recovery as much as infarct growth does. However, the key biologic factors and molecular mechanisms that mediate formation of cerebral edema remain poorly defined. This knowledge gap has hindered development of targeted interventions to mitigate the consequences of edema in conditions as diverse as brain trauma, tumors, and hemorrhagic as well as ischemic strokes. There is significant variability between patients, with some exhibiting malignant edema and others with none to mild swelling despite similar stroke sizes and severities. The central objective of this proposal is to integrate imaging with genetics to identify key biologic pathways and mediators implicated in cerebral edema. We will acquire serial CT scans from 3,506 patients in an NINDS-funded stroke genetics study (GENISIS) and 1,000 being enrolled in an ERA-NET NEURON-funded study (iBioStroke). We will apply automated analysis pipelines to obtain quantitative multi-dimensional measurements of edema severity. Our primary biomarker is the displacement of cerebrospinal fluid (ΔCSF) that serves as a surrogate for the volume of swelling that has developed after stroke. However, we will also measure hemispheric CSF ratio and lesional water uptake as additional edema phenotypes. We will model edema formation (in relation to time from stroke onset) to evaluate the degree to which biologic factors, such as age, sex, glucose, blood pressure, and renal function, influence edema formation. Our central hypothesis is that inter-patient variability in edema formation can be linked to both targetable clinical factors such as hyperglycemia and informative genetic differences. Our preliminary data has suggested that ΔCSF has a significant heritable component. Specific Aim 1 seeks to quantify the relationship of key clinical factors, such as hyperglycemia and blood pressure, to edema formation. We will leverage genomic data to further dissect which factors are causative in edema formation, using Mendelian randomization. We will also quantify the impact of edema and hemorrhagic transformation on stroke recovery. Specific Aim 2 will identify genes and pathways associated with cerebral edema after stroke. It will employ genome-wide association (GWAS) approaches with multiple edema phenotypes in this large cohort. We will further prioritize genes and pathways using functional annotation tools. Specific Aim 3 will dissect shared versus edema-specific injury mechanisms by analyzing edema in relation to traits such as hemorrhagic transformation, white matter injury and small-vessel disease. It will leverage large existing datasets to boost the power of gene discovery from Aim 2. Once complete, this work will provide the first comprehensive picture of the genetic architecture of cerebral edema after stroke and provide unbiased, novel insights into molecular targets that can inform drug discovery.