Plasma metabolomic profiling of diabetic macular edema

Abstract

Diabetic macular edema (DME), a sight-threatening retinopathy, is a leading cause of vision loss in persons with diabetes mellitus. Despite strict control of systemic risk factors, a fraction of patients with diabetes developed DME, suggesting the existence of other potential pathogenic factors underlying DME. This study aimed to investigate the plasma metabotype of patients with DME and to identify novel metabolite markers for DME. Biomarkers identified from this study will provide scientific insight and new strategies for the early diagnosis and intervention of DME. To match clinical parameters between case and control subjects, patients with DME (DME, n = 30) or those with diabetes but without DME (Control, n = 30) were assigned to the present case-control study. Distinct metabolite profiles of serum were examined using liquid chromatography-mass spectrometry (LC-MS). A total of 190 distinct metabolites between DME and Control groups were identified (VIP > 1, Fold Change > 1.5 or < 0.667, and P < 0.05). The distinct metabolites between DME and Control groups were enriched in 4 KEGG pathways, namely, Glutamate Metabolism, Carnitine Synthesis, Oxidation of Branched Chain Fatty Acids, and Phytanic Acid Peroxisomal Oxidation. Finally, 4 metabolites were selected as candidate biomarkers for DME, namely, 5-Phospho-beta-D-ribosylamine, Succinic acid, Ascorbyl glucoside, and Glutathione disulfide. The area under the curve for these biomarkers were 0.693, 0.772, 0.762, and 0.771, respectively. This study suggested that impairment in the metabolism and 4 potential metabolites were identified as metabolic dysregulation associated with DME, which might provide insights into potential new pathogenic pathways for DME. 5-Phospho-beta-D-ribosylamine was first identified as a novel metabolite marker, with no previous reports linking it to diabetes or DME. This discovery may offer valuable insights into potential new pathogenic pathways associated with DME.

Keywords: Diabetic macular edema; LC-MS; Metabolic profiling; Metabolomics; Type 2 diabetes.

Fig. 1

Inclusion and exclusion flowchart of the case-control study. OCT, optical coherence tomography.

Fig. 2

Fundus imaging signs of a patient with diabetic macular edema (DME) were shown. (a) Image captured by fundus photography. (b) Images captured by optical coherence tomography (OCT). (c) Image captured by fluorescein fundus angiography (FFA). Parts a, b, and c were derived from the same eye.

Fig. 3

Workflow overview of the comprehensive analysis of metabolomics in type-2 diabetes patients with DR.

Fig. 4

Score plots of the PCA and PLS-DA models. (a) Score plot of the PCA model for samples collected from 2 isolates of sample data; (b) the 2 groups were well separated in the PLS-DA score plot, indicating that they had markedly different metabolic characteristics.

Fig. 5

Metabolomics pathway analysis. (a) Pathway enrichment analysis overview, in which four pathways were enriched, including Glutamate Metabolism, Carnitine Synthesis, Oxidation of Branched Chain Fatty Acids and Phytanic Acid Peroxisomal Oxidation. (P < 0.05). (b) Network of the enriched pathways. Each node represents a metabolite set with its color based on its p value, and its size is based on fold enrichment (hits/expected). Two metabolites sets are connected by an edge if the number of their shared metabolites is over 25% of the total number of their combined metabolite sets.

Fig. 6

Receiver operating characteristic (ROC) curve analysis was performed to evaluate the use of metabolites as biomarkers for DME. (a) The AUC of 4 biomarkers (5-Phospho-beta-D-ribosylamine, Ascorbyl glucoside, Succinic acid, Glutathione disulfide) are 0.693, 0.772, 0.762, 0.771, respectively. (b–e) The intensity level of 4 biomarkers in DME and control group, respectively (Median ± IQR). **p < 0.01, ***p < 0.001.