Background
Diabetic retinopathy (DR) is the major ocular complication of diabetes mellitus, and is a problem with significant global health impact. Epidemiologic projections show that the global burden of DR is not only increasing, but also shifting from high-income countries towards middle- and low-income areas. The identification of potential intervention targets for diabetic retinopathy is an important goal.
Methods
In this study, we collected vitreous fluid samples from the DR patients, analyzed the samples using LC-MS approach, and identified the differential metabolites through metabolomic analysis. Then, the differentially expressed genes were identified through the systematic transcriptomic analysis of DR-related dataset from Gene Expression Omnibus (GEO), followed by network profiling of metabolic-reaction-enzyme-gene.
Results
In this experiment, a total of 79 differential metabolites and 23 hub genes were discovered, of which 6 different metabolites and 3 hub genes were further evaluated as more potential biomarkers based on network analysis. According to the KEGG enrichment analysis, the potential biomarkers and gene-encoded proteins were found to be involved in the arginine biosynthesis, alanine, aspartate and glutamate metabolism, arginine and proline metabolism, and HIF-1 signaling pathway metabolism which was of significance for the diagnosis and treatment of DR. In particular, the combination of metabolites (Fumaric acid, Oxoglutaric acid, Proline, Farnesyl pyrophosphate) as well as the combination of HMOX1, NOS3, GPT exerted more accurate discrimination abilities between DR and non-DR groups, providing new ideas and basis for understanding disease progression and targeted therapy of DR.
Conclusion
By integrating metabolomics and transcriptomics, this study identified 6 different metabolites and 3 hub genes, whuich could provide a novel insight into the pathogenesis of DR and could be used as novel targets for the therapy of DR.