In vivo imaging of the immune response in human uveitis: linking cellular level optical biomarkers to the immune environment of the living eye

About This Grant

Uveitis is responsible for up to 10% of blindness in the US and is a leading cause of vision loss worldwide. Associated with diverse mechanisms of inflammation driven by a range of causes, diagnosis is challenging because it often relies on serological testing or systemic assessments rather than direct ocular measurements. Microglia and other retinal cells and circulating immune cells, as well as the cytokines they produce such as IFN- γ, TNF-α, IL-1, IL-6, and IL-12 influence uveitis pathophysiology as they shape the immune environment within the eye. However, there is a major gap in the understanding of how these key players of the immune response differ across the myriad forms of uveitis. Most of our knowledge comes from animal models due to a lack of tools for real time assessment of immune responses in the eye. We recently showed, for the first time, how adaptive optics ophthalmoscopy (AOO) methods can assess the immune response in posterior uveitis (PU), which affects the retina and/or choroid, in real time in the living eye. Our non-invasive, label-free approach offers promise to revolutionize the diagnostic toolkit for PU and may provide rigorous new biomarkers for evaluating treatment efficacy in the clinic and in clinical trials. It is known that the immune environment differs in infectious and non- infectious uveitis, so we will begin by defining these immunological differences quantitatively using conventional immunological assays including flow cytometry and cytokine analysis in a case-control study of well characterized patients (Aim 1). Next, we will test the hypothesis that these differences allow the use of AOO to detect morphological and dynamic changes of immune cells associated with the retina. Our preliminary findings suggest that AOO can also detect certain pathogens, and we will define the types of microbes that are causing infectious uveitis. We will also determine the other inflammatory biomarkers accessible to AOO in PU, such as vascular changes. Finally, in longitudinal study of a subset of patients, we will track the changes of these biomarkers over time in response to treatment. We predict that imaging will reveal distinct and significant differences between infectious and non-infectious uveitis, specifically: 1) the morphology and dynamic activity of immune cells moving in and through the retina, 2) the profiles of specific microbes related to infectious uveitis pathology, and 3) vascular and other microscopic retinal changes. To realize our goal of transforming the clinical toolkit for real-time monitoring of inflammation, we also need rigorous tools to generate quantitative metrics from the inflammatory biomarkers. We will develop these quantitative tools and generate new imaging protocols for uveitis (Aim 2). This will allow us to establish a novel analytical pipeline to analyze the retina in real-time to increase diagnostic efficiency and improve treatment monitoring. Together, the knowledge and tools developed here will lay the foundation needed to use these new technologies to improve patient care, including rapid diagnosis and real-time treatment monitoring.