Aqueous Humor Dynamic Components that Determine Intraocular Pressure Variance

决定眼压变化的房水动态成分

• 批准号: 8548511
• 负责人: Sayoko E Moroi
• 金额: $ 9.73万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-03-03 至 2016-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8548511
• 关键词: Accounting; Address; Adrenergic beta-Antagonists; Age of Onset; Aqueous Humor; Biological Markers; Blindness; Circadian Rhythms; Commit; Data; Databases; Disease Progression; Dose; Drug Prescriptions; Drug usage; Environmental Risk Factor; Experimental Designs; Eye; Frequencies; Future; Glaucoma; Goals; Individual; Knowledge; Latanoprost; Linear Models; Measures; Mediating; Medical; Medicine; Modeling; Molecular; Ocular Hypertension; Office Visits; Onset of illness; Open-Angle Glaucoma; Outcome; Outcome Measure; Patients; Pharmaceutical Preparations; Phase; Physiologic Intraocular Pressure; Physiological; Physiology; Placebos; Predictive Factor; Prostaglandins; Publishing; Randomized; Regimen; Risk; Staging; Testing; Time; Timolol; Treatment Efficacy; Treatment Failure; Treatment outcome; Variant; Venous Pressure level; Work; aqueous; base; cohort; follow-up; improved; new therapeutic target; response; wasting

DESCRIPTION (provided by applicant): Glaucoma is a major cause of blindness. The inability to predict a patient's IOP response to medications is a critical barrier for the clinician to consistently provide highly effective IOP-based treatments. Current trial-and- error approaches to glaucoma management are inefficient and have not addressed this barrier as there are no predictive factors for drug response. Our long-term goal is to improve outcomes by identifying biomarkers and environmental factors that profile a patient at risk for glaucoma by age-of-onset, rate of disease progression, "poor response" to treatment, and large IOP fluctuation. Our objective is to address this critical barrier by focusing on physiological factors that predict IOP response to drugs. Our central hypothesis is that individual aqueous humor dynamic components predict IOP response to medications. We will achieve our objective and work toward our goal by testing the central hypothesis through two aims. Aim 1: Test the hypothesis that aqueous humor inflow is a physiological marker of variation in timolol-mediated IOP response between individuals. Aim 2: Test the hypothesis that aqueous humor outflow is a physiological marker of variation in latanoprost-mediated IOP response between individuals. The overall experimental design will be a comprehensive comparison of physiological components of IOP in the same individual under control conditions without treatment and under experimental conditions with treatment using the two most commonly used drug classes, beta-blockers (Aim 1) and prostaglandins (Aim 2). The main outcome measures are the physiological components of IOP, namely, aqueous humor inflow, outflow facility, episcleral venous pressure, and uveoscleral outflow. The relationships among these four physiological components to IOP will be analyzed by generalized linear models. These results will provide a critically needed database on physiological components of IOP under baseline and treated conditions in the same cohort. Our team is committed to build upon these extensive physiology data from controls to the next phase by studying patients with ocular hypertension and early stages of open-angle glaucoma. Such a model would form the basis for future studies to investigate molecular and environmental interactions on IOP-based treatment outcomes and new therapeutic targets. Our results will advance understanding of IOP response variance to medications by dissecting the physiological components of drug response variations between individuals. This knowledge will bring us closer to predicting therapeutic efficacy, and decreasing treatment failures by identifying patients who are poor responders a priori. Prescribing medications based on a patient's profile of drug response will eliminate time wasted on ineffective drug prescriptions and result in more efficient medical management with fewer follow-up office visits to assess poor efficacy.

描述（由申请人提供）：青光眼是失明的主要原因。无法预测患者对药物的IOP反应是临床医生持续提供高效的基于IOP的治疗的关键障碍。目前青光眼管理的试错法效率低下，并且没有解决这个障碍，因为没有药物反应的预测因素。我们的长期目标是通过确定生物标志物和环境因素来改善结果，这些生物标志物和环境因素通过发病年龄、疾病进展速度、对治疗的“不良反应”和大的IOP波动来描述青光眼风险患者。我们的目标是通过关注预测IOP对药物反应的生理因素来解决这一关键障碍。我们的中心假设是，个体的房水动态成分预测IOP对药物的反应。我们将通过两个目标来检验中心假设，从而实现我们的目标，并朝着我们的目标努力。目的1：检验以下假设：房水流入是个体间噻吗洛尔介导的IOP反应变化的生理标志物。目的2：检验以下假设：房水流出是个体间拉坦前列素介导的IOP反应变异的生理标志物。总体实验设计将是在未治疗的对照条件下和使用两种最常用的药物类别（β受体阻滞剂（目的1）和阿糖胞苷（目的2））治疗的实验条件下，对同一个体的IOP生理组分进行全面比较。主要结果测量是IOP的生理成分，即，房水流入、流出设施、巩膜上静脉压和葡萄膜巩膜流出。这四个生理成分与IOP之间的关系将通过广义线性模型进行分析。这些结果将提供同一队列中基线和治疗条件下IOP生理组分的急需数据库。我们的团队致力于通过研究高眼压和早期开角型青光眼患者，从对照组到下一阶段建立这些广泛的生理学数据。这样的模型将成为未来研究的基础，以研究分子和环境相互作用对基于IOP的治疗结果和新的治疗靶点的影响。我们的研究结果将通过剖析个体之间药物反应差异的生理成分来促进对药物的IOP反应差异的理解。这些知识将使我们更接近于预测治疗效果，并通过识别先验的不良反应患者来减少治疗失败。根据患者的药物反应特征开药将消除浪费在无效药物处方上的时间，并导致更有效的医疗管理，减少后续办公室访问以评估不良疗效。