GeoMx DSP enables layer-specific spatial transcriptomic profiling of the human retina: A proof-of-concept study from post-COVID-19 donor tissue

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Purpose To generate layer resolved spatial transcriptomic profiles of the human retina using NanoString GeoMx Digital Spatial Profiler (DSP) and evaluate whether this approach can be successfully applied to resolve spatially localized transcriptional changes across retinal compartments in diseased retina. Design Study of human postmortem retinal tissue using spatial transcriptomics with cross platform computational validation. Subjects Postmortem human retinal samples from donors with and without history of COVID-19. Methods Anatomically defined retinal layers were profiled using GeoMx DSP with layer-resolved region of interest (ROI) selection. Data were validated using retinal layer markers, and concordance with published scRNA-seq reference signatures was established. Differential expression and pathway level comparisons were performed between donors with and without a history of COVID-19 with emphasis on spatial localization of changes across retinal layers. Main Outcome Measures (1) Concordance of GeoMx layer resolved expression with known photoreceptor and RPE marker patterns and scRNA-seq reference signatures; (2) exploratory identification of candidate layer restricted gene expression differences in donors with a history of COVID-19, as a proof of concept application of the platform. Results GeoMx DSP captured biologically expected layer specific transcriptional changes across the human retina, including compartmentalized layer expression, and showed cross platform concordance with published scRNA-seq reference signatures. In an exploratory comparison of donors with and without a history of COVID-19, candidate gene expression differences were observed across specific retinal layers, suggesting spatially non uniform transcriptional patterns that warrant further investigation in larger independently validated cohorts. Conclusions Layer-resolved GeoMx DSP provides a robust approach for spatial transcriptomic analysis of human retina and enables scRNA informed interpretation through cross platform benchmarking. Exploratory application to donors with COVID-19 history identified spatially restricted transcriptional shifts across retinal compartments, illustrating the utility of layer resolved retinal spatial transcriptomics as a discovery framework for studying clinically relevant perturbations and informing future ocular disease and therapeutic research.

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