Abstract

Due to commonalities in pathophysiology, age-related macular degeneration (AMD) represents a uniquely accessible model to investigate therapies for neurodegenerative diseases, leading us to examine whether pathways of disease progression are shared across neurodegenerative conditions. Here we use single-nucleus RNA sequencing to profile lesions from 11 postmortem human retinas with age-related macular degeneration and 6 control retinas with no history of retinal disease. We create a machine-learning pipeline based on recent advances in data geometry and topology and identify activated glial populations enriched in the early phase of disease. Examining single-cell data from Alzheimer’s disease and progressive multiple sclerosis with our pipeline, we find a similar glial activation profile enriched in the early phase of these neurodegenerative diseases. In late-stage age-related macular degeneration, we identify a microglia-to-astrocyte signaling axis mediated by interleukin-1β which drives angiogenesis characteristic of disease pathogenesis. We validated this mechanism using in vitro and in vivo assays in mouse, identifying a possible new therapeutic target for AMD and possibly other neurodegenerative conditions. Thus, due to shared glial states, the retina provides a potential system for investigating therapeutic approaches in neurodegenerative diseases.

Single-nucleus RNA-seq was used to profile 11 retinas with varying stages of age-related macular degeneration and 6 control retinas. The authors identified shared glial states across neurodegeneration, indicating that the retina provides a human system for investigating therapeutic approaches in neurodegeneration.

Details

Title
Single-cell analysis reveals inflammatory interactions driving macular degeneration
Author
Kuchroo, Manik 1 ; DiStasio, Marcello 2   VIAFID ORCID Logo  ; Song, Eric 3   VIAFID ORCID Logo  ; Calapkulu, Eda 3 ; Zhang, Le 4   VIAFID ORCID Logo  ; Ige, Maryam 5 ; Sheth, Amar H. 5   VIAFID ORCID Logo  ; Majdoubi, Abdelilah 3 ; Menon, Madhvi 6 ; Tong, Alexander 7   VIAFID ORCID Logo  ; Godavarthi, Abhinav 8 ; Xing, Yu 3 ; Gigante, Scott 9   VIAFID ORCID Logo  ; Steach, Holly 10 ; Huang, Jessie 7 ; Huguet, Guillaume 11   VIAFID ORCID Logo  ; Narain, Janhavi 12 ; You, Kisung 13 ; Mourgkos, George 3 ; Dhodapkar, Rahul M. 5 ; Hirn, Matthew J. 14   VIAFID ORCID Logo  ; Rieck, Bastian 15   VIAFID ORCID Logo  ; Wolf, Guy 11   VIAFID ORCID Logo  ; Krishnaswamy, Smita 16   VIAFID ORCID Logo  ; Hafler, Brian P. 17   VIAFID ORCID Logo 

 Yale University, Department of Neuroscience, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710) 
 Yale University, Department of Pathology, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710) 
 Yale University, Department of Ophthalmology and Visual Science, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710) 
 Yale University, Department of Neuroscience, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710); Yale University, Department of Neurology, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710) 
 Yale School of Medicine, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710) 
 University of Manchester, Division of Infection, Immunity and Respiratory Medicine, Manchester, UK (GRID:grid.5379.8) (ISNI:0000000121662407) 
 Yale University, Department of Computer Science, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710) 
 Yale University, Department of Applied Math, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710) 
 Yale University, Computational Biology, Bioinformatics Program, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710) 
10  Yale University School of Medicine, Department of Immunobiology, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710) 
11  Mila—Quebec AI institute, Montréal, Canada (GRID:grid.510486.e); Université de Montréal, Department of Mathematics and Statistics, Montréal, Canada (GRID:grid.14848.31) (ISNI:0000 0001 2292 3357) 
12  Rutgers University, Department of Computer Science, New Brunswick, USA (GRID:grid.430387.b) (ISNI:0000 0004 1936 8796) 
13  Yale University, Department of Genetics, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710) 
14  Michigan State University, Department of Computational Mathematics, Science and Engineering, East Lansing, USA (GRID:grid.17088.36) (ISNI:0000 0001 2150 1785); Michigan State University, Department of Mathematics, East Lansing, USA (GRID:grid.17088.36) (ISNI:0000 0001 2150 1785) 
15  ETH Zurich, Department of Biosystems Science and Engineering, Zurich, Switzerland (GRID:grid.5801.c) (ISNI:0000 0001 2156 2780) 
16  Yale University, Department of Computer Science, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710); Yale University, Department of Genetics, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710) 
17  Yale University, Department of Pathology, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710); Yale University, Department of Ophthalmology and Visual Science, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710); Broad Institute of MIT and Harvard, Cambridge, USA (GRID:grid.66859.34) (ISNI:0000 0004 0546 1623) 
Pages
2589
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2809985378
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.