A Set of Global Metabolomic Biomarker Candidates to Predict the Risk of Dry Eye Disease

Abstract

Purpose: We used ultraperformance liquid chromatography coupled with quadrupole/time-of-flight tandem mass spectrometry (UPLC-Q/TOF-MS/MS) to analyze the metabolic profile of reflex tears from patients with dry eye disorders. Methods: We performed a cross-sectional study involving 113 participants: 85 patients diagnosed with dry eye syndrome (dry eye group, DEG) and 28 healthy subjects (control group, CG). Reflex tears (20–30 μl) were collected from the tear meniscus of both eyes of each subject with a Schirmer I test strip. Mass spectrometry data were acquired with a standard workflow by UPLC-Q/TOF-MS/MS. Metabolites were quantitatively analyzed and matched with entries in the Metlin, Massbank and HMDB databases. LASSO regression was conducted to detect important metabolites. Multiple logistic regression was used to find the significant metabolic biomarker candidates for dry eye syndrome. Open database sources, including the KEGG and MetaboAnalyst, were used to identify metabolic pathways. Results: After the LASSO regression and multiple logistic regression analysis, 41 out of 57 metabolic biomarker candidates were significantly correlated with fluorescein breakup time (FBUT), 3 out of 20 with Ocular Surface Disease Index (OSDI) score, and 18 out of 57 with fluorescein staining (FL). Taking the overlap of these three sets, 48 out of 51 metabolites contributed to dry eye incidence. Metabolic pathway analysis revealed that the main pathways were glucose metabolism, amino acid metabolism and glutathione metabolism. Conclusion: Dry eye syndrome induces changes in the tear metabolic profile, which reveals the relationship between changes in metabolites and symptoms of dry eye syndrome. Funding Statement: This study was supported by the Youth project of Shanghai Municipal Commission of Health and Family Planning (grant number 17ZR1427100), the Scientific Research Foundation of Shanghai Municipal Commission of Health and Family Planning (grant number 201840336), the Shanghai Municipal Commission of Health and Family Planning (grant number 20194Y0238), the National Natural Science Foundation of China (grant numbers 81300771), The Project of Key Disciplines of Medicine in Yangpu District of Shanghai (grant number YP16ZA02). Declaration of Interests: The authors declare no conflicts of interest. Ethical Approval Statement: The study was performed in accordance to principles of the Declaration of Helsinki and study protocol were reviewed and approved by the Ethics Committee of Yangpu District Central Hospitial. Informed consent was obtained from each participant enrolled in this study.