Assessing Photoreceptor Structure and Function in Normal and Diseased Retinae

摘要。 视力丧失是一个主要的健康问题，可能有遗传和后天的原因。工具 人类视网膜的非侵入性评估已经以令人难以置信的速度发展，现在有机会 探针结构和功能与单细胞分辨率。这些工具是推进我们理解的核心 人类视力在健康和疾病方面的局限性，以及提高我们开发和评估新的 视力丧失患者的治疗策略。我们研究计划的长期目标仍然是 开发和推广敏感的、非侵入性的、高分辨率的技术，以评估感光细胞 结构和功能。在过去的14年里，我们已经在健康的个体以及那些患有 广泛的视网膜和全身性疾病。以前，我们的重点一直是在视网膜结构的遗传 视网膜变性，由于对这些疾病的遗传基础的理解有所提高， 这些疾病的新治疗方法的出现。随着基于自适应光学（AO）的出现， 评估视网膜功能的工具，我们处于独特的地位，以扩大我们的研究和探测交叉点， 在人类视网膜中感光器结构和功能之间的关系。因此，这笔赠款的两个主要目标 阶段是评估视网膜/感光器结构，因为它适用于视力限制的治疗潜力 病理学和量化感光细胞镶嵌和视觉分辨率之间的关系中断。 我们组建了一个多学科研究团队，通过以下具体目标实现这些目标： 目的1）确定蓝视锥细胞个体视网膜中央凹中残余细胞群的身份 目的2）探讨视锥间距与邻近和邻近区域AO矫正视力之间的联系， 破坏的视锥嵌合体，以及目标3）量化具有以下病史的个体中的中央凹结构和功能： 早产正在使用的各种方法将提供深入了解中央凹解剖结构之间的联系， 感光器地形和视觉行为。这项工作预计将有积极的临床影响，填补 文献中的关键空白，并提供了一个增强的框架，以针对临床治疗，以及 了解早产对视网膜结构和功能的影响。我们的提案涉及研究 2021-2025年NEI战略计划“未来愿景”中概述的需求，差距和机遇： “探索和利用生物测量和视觉过程的理论模型之间的联系，” “进行仔细的临床表型分析，以确定疾病的可量化生物标志物， 诊断、风险预测和随时间推移的治疗效果评估，”“开发和验证成像 用于鉴定临床疾病生物标志物的方法;用于增强疾病诊断、分类和 预测;以及标准化不同设备之间的定量指标，”和“扩大激励措施， 验证和共享代码，开发易于在云中共享和/或操作的工具， 算法验证、文档、代码构造和注释的实践指南。

ABSTRACT . Vision loss represents a major health issue and can have both inherited and acquired origins. Tools for noninvasive assessment of the human retina have grown at an incredible pace and now afford the opportunity probe structure and function with single-cell resolution. These tools are central to advancing our understanding of the limits of human vision in health and disease as well improving our ability to develop and evaluate novel therapeutic strategies for patients with vision loss. The long-term goal of our research program remains to develop and disseminate sensitive, noninvasive, high-resolution techniques to assess photoreceptor structure and function. Over the past 14 years we have done this in healthy individuals as well as those with a wide range of retinal and systemic diseases. Previously, our focus has been on retinal structure in inherited retinal degenerations, owing to improved understanding of the genetic basis of these conditions and the emergence of novel therapeutic approaches for these conditions. With the advent of adaptive optics (AO) based tools for assessing retinal function we are uniquely positioned to expand our studies and probe the intersection between photoreceptor structure and function in the human retina. As such, the two major goals for this grant period are to evaluate retinal/photoreceptor structure as it applies to therapeutic potential in vision-limiting pathology and quantify the relationship between disruptions in the photoreceptor mosaic and visual resolution. We have assembled a multidisciplinary research team to achieve these goals through the following specific aims: Aim 1) Determine the identity of the remnant cell population in the fovea of individuals with blue cone monochromacy (BCM), Aim 2) Probe the link between cone spacing and AO-corrected acuity in contiguous and disrupted cone mosaics, and Aim 3) Quantify foveal structure and function in individuals with a history of premature birth. The diverse approaches being utilized will provide insight into the link between foveal anatomy, photoreceptor topography, and visual behavior. This work is expected to have a positive clinical impact by filling critical gaps in the literature and providing an enhanced framework for targeting clinical therapies in BCM as well as understanding the impact of prematurity on retinal structure and function. Our proposal addresses research needs, gaps, and opportunities outlined in the 2021-2025 NEI Strategic Plan, “Vision for the Future”: “Explore and exploit connections between biological measurements and theoretical models of visual processes,” “Conduct careful clinical phenotyping to identify quantifiable biomarkers of disease to allow for more accurate diagnosis, risk prediction, and evaluation of treatment efficacy over time,” “Develop and validate imaging methods for identifying clinical disease biomarkers; for enhancing disease diagnosis, classification, and prediction; and for standardizing quantitative metrics among different devices,” and “Expand incentives to validate and share code, develop tools that are readily shared and/or operated in the cloud, and develop best practice guidelines for algorithm validation, documentation, code construction, and commenting.”