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: 10483194
• 负责人: Sayoko E Moroi
• 金额: $ 40.91万
• 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 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10483194
• 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; 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，降低眼压(IOP)可以减缓青光眼的进展。 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。临床科学中的一个空白是我们对影响结果的其他风险因素缺乏了解。我们的 长期目标是通过识别生物标记物、行为和环境因素来改善结果 一起根据发病年龄、进展速度、治疗反应差、 眼压波动大。我们专注于两种眼压模式，这两种模式继续困扰着临床医生 提供一致和有效的眼压治疗：(1)眼压对药物的反应，从无应答者到 (2)眼压波动，从小到大，后者导致进行性变化 视野丧失。不幸的是，预测这些眼压模式的生物标记物可能会改善临床 决策尚未确定--这是临床医生为哪些患者确定的关键障碍 更早或更积极的治疗将减轻青光眼相关的视力损失。科学的前提是 这些机制(即房水流动、流出设施、巩膜上静脉压和计算的葡萄膜巩膜 流)预测患者的眼压模式。我们将检验中心假设，眼压反应的变化 对药物和眼压波动的预测可以通过房水动态(AHD)因素来预测 调节眼压。我们建议在200名高眼压或开角型眼病患者中测试我们的假设。 青光眼(OAG)，因为这两种情况都是在眼压药物反应的药物试验中调查的。有两个目标： 目的1.验证AHD因素预测眼压药物反应的假说。在议定书1中，AHD因素 将在不治疗的情况下在基线下测量，并在随机顺序的1周治疗后进行测量 先用0.5%噻吗洛尔，然后洗脱期，再用0.005%拉坦前列素，反之亦然。目标2.测试 房水流动和流出设施预测眼压波动的假说。在协议2中，眼压波动 将在非临床环境中使用Icare®Home眼压计在多天的基线和 在方案1期间进行单一治疗。临床影响：我们将AHD方法应用于 了解药物反应和眼压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。捆绑这些关系将提供新的知识， 形成未来表型-基因型研究的基础，以确定药物反应和眼压的遗传风险等位基因 波动，导致药物反应的综合风险评分结合临床和遗传风险概况 眼压波动。能够确定哪些患者需要更早和更积极的治疗将 最终实现更高效的医疗管理，减少为评估治疗而进行的后续办公室访问 更有效，更少的治疗失败，并减少青光眼相关失明。

项目成果

Size Matters for Interplicata Diameter: A Case-Control Study of Plateau Iris.

尺寸对 Interplicata 直径很重要：高原虹膜的病例对照研究。

• DOI: 10.1016/j.ogla.2020.06.007
• 发表时间: 2020
• 期刊: Ophthalmology. Glaucoma
• 作者: Garza,PhilipS;Man,Xiaofei;Queen,JoannaH;Ayres,BernadeteM;McClendon,Tanya;Parrish,ElizabethA;Reed,DavidM;Moroi,SayokoE
• 通讯作者: Moroi,SayokoE