Retinal Transcriptome and Cellular Landscape in Relation to the Progression of Diabetic Retinopathy.

ABSTRACT:

Purpose

Previous studies that identify putative genes associated with diabetic retinopathy are only focusing on specific clinical stages, thus resulting genes are not necessarily reflective of disease progression. This study identified genes associated with the severity level of diabetic retinopathy using the likelihood-ratio test (LRT) and ordinal logistic regression (OLR) model, as well as to profile immune and retinal cell landscape in progressive diabetic retinopathy using a machine learning deconvolution approach.

Methods

This study used a published transcriptomic dataset (GSE160306) from macular regions of donors with different degrees of diabetic retinopathy (10 healthy controls, 10 cases of diabetes, 9 cases of nonproliferative diabetic retinopathy, and 10 cases of p

SUBMITTER: Wang JH 

PROVIDER: S-EPMC9424969 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature