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: 10004052
• 负责人: Sayoko E Moroi
• 金额: $ 54.65万
• 依托单位: OHIO STATE UNIVERSITY
• 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 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10004052
• 关键词: Adrenergic beta-Antagonists; Aftercare; Age; Age of Onset; Aqueous Humor; Behavioral; Biological Markers; Blindness; Characteristics; Clinical; Clinical Sciences; Cornea; Data Set; Databases; Environmental Exposure; Environmental Risk Factor; Eye; FDA approved; Future; Genetic Risk; Genotype; Glaucoma; Goals; Grant; Health Services; Healthcare; Home environment; Individual; Knowledge; Latanoprost; Lead; Linear Models; Measures; Mediating; Medical; Methods; Newly Diagnosed; Ocular Hypertension; Office Visits; Open-Angle Glaucoma; Outcome; Outcome Measure; Patients; Pattern; Pharmaceutical Preparations; Phenotype; Physical activity; Physiologic Intraocular Pressure; Positioning Attribute; Practice Guidelines; Predictive Factor; Prostaglandins; Protocols documentation; Randomized; Randomized Clinical Trials; Risk; Risk Factors; Safety; Testing; Timolol; Treatment Efficacy; Treatment Failure; Variant; Venous Pressure level; Visual Fields; aggressive therapy; aqueous; clinical decision-making; clinical risk; cohort; cost; design; disorder risk; experience; follow-up; improved; improved outcome; individual response; innovation; response; risk variant; secondary outcome; sex; trait; treatment response

Abstract Randomized clinical trials (RCTs) show that reducing intraocular pressure (IOP) slows glaucoma progression. Despite the clinician’s use of these RCTs, practice guidelines, and experience, patients still progress to blindness. A gap in clinical science is our lack of knowledge on other risk factors that impact outcomes. Our long-term goal is to improve outcomes by identifying biomarkers, behavioral and environmental factors, that together profile a patient at risk for disease by age-of-onset, rate of progression, poor response to treatment, and large IOP fluctuation. We focus on two IOP patterns that continue to confound the clinician’s ability to provide consistent and effective IOP treatments: (1) IOP response to medications, ranging from non-responder to super responder, and (2) IOP fluctuation, ranging from small to large, with the latter leading to progressive visual field loss. Unfortunately, biomarkers that foretell these IOP patterns, which could improve clinical decision-making have yet to be identified -- a critical barrier to the clinician identifying patients for whom earlier or more aggressive treatment will mitigate glaucoma-related vision loss. The scientific premise is that these mechanisms (i.e., aqueous flow, outflow facility, episcleral venous pressure, and calculated uveoscleral flow) predict a patient’s IOP patterns. We will test the central hypothesis that variations in IOP response to drugs and IOP fluctuation can be predicted by the aqueous humor dynamic (AHD) factors that regulate IOP. We propose to test our hypothesis in 200 patients with ocular hypertension (OHT) or open-angle glaucoma (OAG), as both conditions are investigated in drug trials for IOP drug response. There are two aims: Aim 1. Test the hypothesis that AHD factors predict the IOP drug response. In Protocol 1, AHD factors will be measured under baseline without treatment, and after a randomized order of 1-week treatments with timolol 0.5% followed by a washout period and then latanoprost 0.005% or vice versa. Aim 2. Test the hypothesis that aqueous flow and outflow facility predict IOP fluctuation. In Protocol 2, IOP fluctuation will be measured in the non-clinic setting using the Icare® Home tonometer over multiple days at baseline and under monotherapy treatment during Protocol 1. Clinical Impact: Our approach to apply AHD methods to understand variation in drug response and IOP fluctuation is innovative. We predict that AHD factors will explain drug response and IOP fluctuation. Tying-down these relationships will provide new knowledge that will form the basis of future phenotype-genotype studies to identify genetic risk alleles of drug response and IOP fluctuation, resulting in an integrated risk score combining clinical and genetic risk profiles for drug response and IOP fluctuation. The ability to determine which patient needs earlier and more aggressive treatment will ultimately lead to more efficient medical management with fewer follow-up office visits to assess treatment efficacy, fewer treatment failures, and decreased glaucoma-related blindness.

摘要 随机临床试验（RCT）表明，降低眼内压（IOP）可减缓青光眼进展。 尽管临床医生使用了这些随机对照试验、实践指南和经验，但患者仍然进展到 失明临床科学的一个差距是我们缺乏对影响结果的其他风险因素的了解。我们 长期目标是通过识别生物标志物、行为和环境因素来改善结果， 通过发病年龄、进展速度、对治疗的不良反应， 眼压波动大。我们重点关注两种持续混淆临床医生能力的IOP模式， 提供一致和有效的IOP治疗：（1）IOP对药物的反应，从无反应者 （2）眼压波动，从小到大，后者导致进行性 视野丧失不幸的是，预测这些IOP模式的生物标志物，这可以改善临床 决策尚未确定-这是临床医生识别患者的关键障碍， 早期或更积极的治疗将减轻青光眼相关的视力丧失。科学的前提是， 这些机制（即，房水流量、流出设施、巩膜外静脉压和计算的葡萄膜巩膜 流量）预测患者的IOP模式。我们将检验中心假设， 药物和眼压波动可以预测的房水动力学（AHD）因素， 调节眼压。我们建议在200例高眼压症（OHT）或开角型青光眼患者中验证我们的假设。 青光眼（OAG），因为在IOP药物反应的药物试验中研究了这两种病症。有两个目标： 目标1.检验AHD因素预测IOP药物反应的假设。在第1号议定书中， 将在未治疗的基线下测量，并在随机化顺序的1周治疗后， 噻吗洛尔0.5%，随后洗脱期，然后拉坦前列素0.005%，反之亦然。目标2.测试 假设房水流动和流出设施预测IOP波动。在方案2中，IOP波动 将在非诊所环境中使用Icare® Home眼压计在基线时测量多日， 在方案1期间接受单药治疗。临床影响：我们将AHD方法应用于 了解药物反应和IOP波动的变化是创新的。我们预测，AHD因素将 解释药物反应和眼压波动。将这些关系联系起来将提供新的知识， 形成未来表型-基因型研究的基础，以确定药物反应和IOP的遗传风险等位基因 波动，导致综合风险评分结合了药物反应的临床和遗传风险特征 和IOP波动。确定哪些患者需要更早和更积极的治疗的能力将 最终导致更有效的医疗管理，减少后续办公室访问以评估治疗 有效性，更少的治疗失败，并减少与青光眼相关的失明。