Metabolomic Profiling of Open-Angle Glaucoma Etiologic Endotypes: Tohoku Multi-Omics Glaucoma Study

Abstract

Purpose: The purpose of this study was to investigate biologically meaningful endotypes of open-angle glaucoma (OAG) by applying unsupervised machine learning to plasma metabolites.

Methods: This retrospective longitudinal cohort study enrolled consecutive patients aged ≥20 years with OAG at Tohoku University Hospital from January 2017 to January 2020. OAG was confirmed based on comprehensive ophthalmic examinations. Among the 523 patients with OAG with available clinical metabolomic data, 173 patients were longitudinally followed up for ≥2 years, with available data from ≥5 reliable visual field (VF) tests without glaucoma surgery. We collected fasting blood samples and clinical data at enrollment and nuclear magnetic resonance spectroscopy to profile 45 plasma metabolites in a targeted approach. After computing a distance matrix of preprocessed metabolites with Pearson distance, gap statistics determined the optimal number of OAG endotypes. Its risk factors, clinical presentations, metabolomic profiles, and progression rate of sector-based VF loss were compared across endotypes.

Results: Five distinct OAG endotypes were identified. The highest-risk endotype (endotype B) showed a significant faster progression of central VF loss (P = 0.007). Compared with patients with other endotypes, those with endotype B were more likely to have a high prevalence of dyslipidemia, cold extremities, oxidative stress, and low OAG genetic risk scores. Pathway analysis of metabolomic profiles implicated altered fatty acid and ketone body metabolism in this endotype, with 34 differentially enriched pathways (false discovery rate [FDR] < 0.05).

Conclusions: Integrated metabolomic profiles identified five distinct etiologic endotypes of OAG, suggesting pathological mechanisms related with a high-risk group of central vision loss progression in the Japanese population.

Figure 1.

Analytic workflow of this study. (a) A total of 544 (280 men and 264 women) participants with glaucoma with clinical and metabolomic data were initially recruited. After excluding those with exfoliation glaucoma (n = 2), primary angle-closure glaucoma (n = 3), and other types of glaucoma (n = 16), including childhood and secondary glaucoma, 523 patients with open-angle glaucoma (OAG) were included in this study. (b) Using the 45 plasma metabolites from 523 patients with OAG, we computed a distance matrix using Pearson distance and derived biologically distinct OAG endotypes by applying the partitioning around medoids. We used gap statistics to select an optimal number of profiles and determined five OAG endotypes. We applied the t-distributed stochastic neighbor embedding (t-SNE) method to visualize the metabolome endotypes. (c) We examined the differences in major clinical and genomic variables according to the five endotypes. For visualization, we used chord diagram, Venn diagram, and upset plots. (d) For 173 patients (out of 523) with OAG who had been followed for ≥2 years with results of ≥5 reliable visual field tests, we assessed the progression rate of sector-based glaucomatous visual field loss according to the five endotypes. (e) To examine the relationship of the metabolite profiles of the highest-risk group (highest progression of central visual field loss; endotype B) compared with those of the other groups (non-endotype B), we performed a functional pathway analysis. OAG, open-angle glaucoma; t-SNE, t-distributed stochastic neighbor embedding.

Figure 2.

Relationship between previously known risk factors for open-angle glaucoma progression and endotypes characterized by metabolites (n = 173). (a) Chord diagram showing the previously known risk factors for open-angle glaucoma (OAG) progression by metabolic-driven endotypes. The ribbons connect individual endotypes to previously known clinical and endotypes. The widths of the ribbon represent the proportion of patients with OAG within the endotype with the corresponding clinical and metabolomic characteristics. Then, it was scaled to a total of 100%. (b) Venn diagram of previously known risk factors for OAG progression and their intersections. The Venn diagram illustrates the composition of five clinical variables and their intersections. The numbers correspond to the number of patients with OAG in each subset and intersection. The cutoff points for age (56 years), central corneal thickness (CCT; 511 µm), pattern standard deviation (PSD; 12%), and intraocular pressure (IOP; 14 mm Hg) were the median values. (c) Upset plot corresponding to the presented Venn diagram. The plot illustrates the composition of five previously known OAG risk factors and their intersections visualized based on the five endotypes. Vertical stacked bar charts reflect the number of patients with glaucoma within each subset and intersection colored according to the endotypes. Horizontal bars indicate the number of patients with glaucoma in each clinical variable set. Black dots indicate the sets of subsets and intersections, and connecting lines indicate relevant intersections related to each stacked bar chart. CCT, central corneal thickness; IOP, intraocular pressure; OAG, open-angle glaucoma; PSD, pattern standard deviation.

Figure 3.

Differential metabolite expression and functional pathway analyses of endotype B versus non-endotype B (n = 523). (a) Heatmap and volcano plot of differentially expressed metabolites. For example (left), we included 45 metabolites with the most significant P values (two-sided raw P values), and the color bar indicates the scaled value of variance-stabilizing transformation. For the volcano plot (right), the threshold of log2 fold change was |0.58| (i.e. ≥|1.5|-fold change) and that of false discovery rate (FDR) was <0.1. Twelve differentially expressed metabolites met these criteria. (b) Functional pathway analysis. There were 34 differentially enriched pathways with a threshold of P value for FDR <0.05. (c) Enrichment analysis of metabolome data. For the Wilcoxon pathway enrichment analysis, we selected the top 25 pathways with the most significant FDRs, and enrichment ratios were shown. FDR, false discovery rate.