Ophthalmology science · 2026
GeoMx Digital Spatial Profiler Enables Layer-Specific Spatial Transcriptomic Profiling of the Human Retina: A Proof-of-Concept Study from Post-Coronovirus Disease 2019 Donor Tissue.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Jidigam Vijay K, Upadhyay Mala, Yang Wei, Bonilha Vera L, Rao Sujata
Аннотация
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 coronavirus disease 2019 (COVID-19).
METHODS: Anatomically defined retinal layers were profiled using GeoMx DSP with layer-resolved region of interest selection. Data were validated using retinal layer markers, and concordance with published single-cell RNA sequencing (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 retinal pigment epithelium 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 nonuniform 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.
FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
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 coronavirus disease 2019 (COVID-19).
METHODS: Anatomically defined retinal layers were profiled using GeoMx DSP with layer-resolved region of interest selection. Data were validated using retinal layer markers, and concordance with published single-cell RNA sequencing (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 retinal pigment epithelium 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 nonuniform 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.
FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.