Topological analysis of single-cell hierarchy reveals inflammatory glial landscape of macular degeneration

Abstract

Purpose : Age-related macular degeneration (AMD) is a neurodegenerative disease that is among the leading causes of blindness worldwide. The molecular pathways that lead to chronic inflammation and vision loss in AMD are not well understood. Our hypothesis is that functional changes in glia influence neurodegeneration in AMD, and these changes may be targeted to halt disease progression and preserve vision.

Methods : To identify cell populations that drive AMD progression, we isolated frozen retinal nuclei from the macula of lesion and non-lesion control samples and performed single-nucleus RNA-sequencing on 11 AMD tissue samples and 6 control tissue samples, creating the first single-cell dataset of AMD pathology. We used a suite of computational tools based on topological data analysis and data diffusion geometry to identify salient levels of the hierarchy, automatically characterize clusters, identify pathogenic populations, and rapidly compute differentially expressed genes between clusters of interest.

Results : We identified two populations of activated glia enriched in the nonexudative form of AMD, one microglial subset and one astrocyte subset. Applying our single cell dataset to other degenerative diseases revealed the same activated glial states in Alzheimer’s disease and multiple sclerosis, indicating a common glial signature during neurodegeneration. In neovascular AMD, we identified a microglia-to-astrocyte signaling axis driving VEGFA expression and angiogenesis characteristic of disease pathogenesis. We validated this mechanism using in vitro and in vivo assays, identifying a possible new therapeutic target for AMD.

Conclusions : We apply our computational framework to a new dataset: the first single-cell transcriptomic atlas of AMD across disease stages. The algorithm identified and characterized specific subpopulations of microglia and astrocytes enriched in nonexudative AMD displaying activation signatures related to phagocytosis, lipid metabolism, and lysosomal function. This set of analyses has clear implications for potential therapeutics for AMD. Currently, anti-VEGF therapy is the primary intervention approved to treat AMD and is only effective in the most advanced stage of disease. Our unbiased topological analysis not only identified the cell-type specificity of VEGFA expression but also identified pathogenic signaling interactions that promote AMD disease progression.

This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.