Genetic Architecture of Cerebral Edema after Stroke

点击翻译按钮获取中文摘要

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.