Abstract
PurposeWe 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 obtained from patients with dry eye disorders.MethodsWe performed a cross-sectional study involving 113 subjects: 85 patients diagnosed with dry eye syndrome (dry eye group) and 28 healthy volunteers (control group). Reflex tears (20–30 μl) were collected from the tear meniscus of both eyes of each subject using a Schirmer I test strip. MS 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. Least absolute shrinkage and selection operator (LASSO) regression was conducted to detect important metabolites. Multiple logistic regression was used to identify the significant metabolic biomarker candidates for dry eye syndrome. Open database sources, including the Kyoto Encyclopedia of Genes and Genomes and MetaboAnalyst, were used to identify metabolic pathways.ResultsAfter the LASSO regression and multiple logistic regression analysis, 4 of 20 metabolic biomarker candidates were significantly correlated with Ocular Surface Disease Index score, 42 of 57 with fluorescein breakup time, and 26 of 57 with fluorescein staining. By focusing on the overlap of these three sets, 48 of 51 metabolites contributed to the incidence of dry eye and there were obvious changes in different age groups. Metabolic pathway analysis revealed that the main pathways were glucose metabolism, amino acid metabolism, and glutathione metabolism.ConclusionDry eye syndrome induces changes in the metabolic profile of tears, and the trend differs with age. This evidence reveals the relationship between changes in metabolites, symptoms of dry eye syndrome, and age.
Highlights
Dry eye disease (DED) is one of the most common ocular surface diseases, with a prevalence of 20–50%, and is becoming a significant global health problem (Najafi et al, 2013; Stapleton et al, 2017)
The Tear Film and Ocular Surface Dry Eye Workshop II (TFOS DEWS II) in 2017 provided a new definition: “Dry eye is a multifactorial disease of the ocular surface characterized by a loss of homeostasis of the tear film, and accompanied by ocular symptoms, in which tear film instability and hyperosmolarity, ocular surface inflammation and damage, and neurosensory abnormalities play etiological roles (Wolffsohn et al, 2017).”
According to a report from the 2017 TFOS DEWS II, a diagnostic test battery for DED, including the screening 5Item Dry Eye Questionnaire (DEQ-5) and Ocular Surface Disease Index (OSDI), confirms that a patient may have DED and triggers the diagnostic testing of non-invasive breakup time, osmolarity, and ocular surface staining with fluorescein and lissamine green (Wolffsohn et al, 2017)
Summary
Dry eye disease (DED) is one of the most common ocular surface diseases, with a prevalence of 20–50%, and is becoming a significant global health problem (Najafi et al, 2013; Stapleton et al, 2017). According to a report from the 2017 TFOS DEWS II, a diagnostic test battery for DED, including the screening 5Item Dry Eye Questionnaire (DEQ-5) and Ocular Surface Disease Index (OSDI), confirms that a patient may have DED and triggers the diagnostic testing of non-invasive breakup time, osmolarity, and ocular surface staining with fluorescein and lissamine green (Wolffsohn et al, 2017). The questionnaire score can roughly distinguish between dry eyes and non-dry eyes, a study conducted by Liu et al (2019) showed that the perception of dry eye symptoms is not obvious due to lower corneal sensitivity. It is affected by subjectivity, level of education, living environment, etc. The development of a diagnostic method with precise, stable, sensitive, specific, and convenient operation is urgently warranted
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