Abstract
Purpose :
Retinopathy of prematurity (ROP) is the leading cause of blindness in children in the US. Although interventions such as anti-VEGF and laser have high success rates in treating severe ROP, current treatment and preventative strategies still have their limitations. The purpose of this study is to identify drugs and chemicals for ROP with comprehensive safety profiles and tolerability using a computational bioinformatics approach.
Methods :
We generated a list of genes associated with ROP to date by querying PubMed Gene which draws from animal models, human studies, and genomic studies in the NCBI database. Gene enrichment analysis was performed on the ROP gene list using the ToppGene program which utilizes multiple drug-gene interaction databases to predict compounds with significant associations to the ROP gene list. We selected compounds with adjusted p-value <0.05. Compounds with significant toxicities or without known clinical indications were filtered out from the final drug list.
Results :
The NCBI query identified 47 ROP genes with pharmacologic annotations present in ToppGene. Enrichment analysis revealed multiple drugs and chemical compounds related to the ROP gene list. The top ten most significant compounds associated with ROP include ascorbic acid (P=7.76x10-21), simvastatin (P=1.44x10-18), N-acetylcysteine (P=1.60x10-17), niacin (P=4.24x10-15), castor oil (P=4.48x10-15), penicillamine (P=2.04x10-14), curcumin (P=2.74x10-14), losartan (P=2.88x10-14), capsaicin (P=3.00x10-14), and metformin (P=4.30x10-14). Antioxidants, NSAIDs, antihypertensives, and anti-diabetics are the most prevalent top drug classes derived from this analysis, and many of these compounds have the potential to be readily repurposed for ROP as new prevention and treatment strategies.
Conclusions :
This bioinformatics analysis creates an unbiased approach for drug discovery by identifying compounds associated to the known genes and pathways of ROP. Many compounds identified in our study have known safety profiles and/or have demonstrated favorable results in preclinical studies for ROP. While predictions from bioinformatic studies require preclinical/clinical studies to validate their results, this approach could guide future investigations for complex pathologies like ROP.
This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.