Metabolic characterization of diabetic retinopathy: An 1H-NMR-based metabolomic approach using human aqueous humor

Abstract Patients with a long duration of diabetes mellitus (DM) usually have accompanied complications such as diabetic retinopathy (DR), which is a leading cause of blindness and visual impairment among working-age persons in developed countries; nevertheless, some patients have no complications. Thus, various studies, including genomic, transcriptomic, and proteomic studies, have been conducted to identify potential biomarkers for predicting DR and to reveal the underlying disease mechanism. Although metabolomics could be a powerful tool for characterizing aqueous eye fluids and revealing the metabolic signatures of common ocular diseases such as DR, studies about its relationship with DR are limited. Moreover, to our knowledge, no previous study has applied a metabolomic approach to investigate the aqueous humor in DR. Therefore, we performed an NMR-based metabolomic study of the aqueous humor of patients with DM and cataract (DM, n = 13), DR and cataract (DR, n = 14), and senile cataract (CON, n = 7) to investigate the metabolic alterations accompanying the development of DR. Principal component analysis, average change analysis, and heatmap analysis revealed that lactate, succinate, 2-hydroxybutyrate, asparagine, dimethylamine, histidine, threonine, and glutamine were the most altered metabolites that potentially play roles in the development and progression of DR. The highly activated alanine, aspartate, and glutamate metabolic pathway was selected using pathway analysis. The phenotypic metabolomic analyses of the aqueous humor indicated an alteration in the metabolic pathways of energy metabolism and amino acids in DR patients which was to some extent suggestive of the pathophysiological process of mitochondrial dysfunction and oxidative stress/endothelial damage. It provides a proof of concept that metabolomic analysis using the aqueous humor of DM patients may be a reliable method to improve the accuracy of predicting the development and progression of DR.