Transcriptome changes in the aqueous humor of diabetic patients

Abstract

Purpose : To determine the changes in the exogenous RNA transcriptome of the aqueous humor in patients with diabetes mellitus without diabetic retinopathy or with proliferative diabetic retinopathy, and to screen for genes linked with diabetic retinopathy progression.

Methods : Aqueous humor (100 ul) was collected in case-control cohorts of 15 healthy controls, 14 diabetic patients without diabetic retinopathy, 12 patients with nonproliferative diabetic retinopathy, and 14 patients with proliferative diabetic retinopathy. We were able to obtain total RNA sequencing results from 14 healthy controls, 5 patients with diabetes without diabetic retinopathy, and 7 patients with proliferative diabetic retinopathy. Genes differentially expressed between patients with or without diabetes as well as diabetic patients with or without diabetic retinopathy were identified using DESeq2.

Results : Three hundred thirty-eight genes were found to be differentially abundant in the aqueous humor (False Discovery Rate < 0.1) of diabetic patients without retinopathy vs controls, and 44 genes in diabetic patients without diabetic retinopathy vs with diabetic retinopathy. CACNB2 and CACNG8, two voltage-gated calcium channel proteins highly expressed in retinal cells and linked to VEGF signaling, and SLC22A11, a glucose transporter, were the top three up-regulated gene in the proliferative diabetic retinopathy cohort.

Conclusions : We were able to discern differences in the RNA composition of the aqueous humor of patients with diabetes with or without diabetic retinopathy compared to healthy controls. Our top candidate, CACNB2, has been previously associated with VEGF regulation in GWAS studies and confirms the role of VEGF signaling in diabetic retinopathy. Aqueous humor is a relatively easy to obtain biofluid, and our results reveals it contains a diverse transcriptome which has potential for disease progression monitoring and discovery of disease-associated gene networks.

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