Heliyon (May 2023)

Azelaic acid and guanosine in tears improve discrimination of proliferative from non-proliferative diabetic retinopathy in type-2 diabetes patients: A tear metabolomics study

  • Xin Wen,
  • Tsz Kin Ng,
  • Qingping Liu,
  • Zhenggen Wu,
  • Guihua Zhang,
  • Mingzhi Zhang

Journal volume & issue
Vol. 9, no. 5
p. e16109

Abstract

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Background: Diabetic retinopathy (DR) is the microvascular ocular complication of diabetes mellitus (DM), which can lead to irreversible blindness and visual impairment if not properly treated. Tears can be collected non-invasively, and the compositions of tears could be the potential biomarkers for ocular diseases. Here we aimed to delineate the metabolomics signature in tears collected from Chinese type-2 DM patients with DR. Methods: The metabolomics profiles of tear samples from 41 Chinese type-2 DM patients with DR and 21 non-diabetic subjects were determined by the untargeted liquid chromatography-mass spectrometry. The associated pathways of the differentially abundant metabolites were delineated, and the receiver operating characteristic curve analysis was conducted to identify the metabolites differentiating non-proliferative DR (NPDR) from proliferative DR (PDR). Results: Total 14 differentially abundant metabolites were identified between total DR and non-diabetic subjects, and 17 differentially abundant metabolites were found between the NPDR and PDR subjects. Moreover, total 18 differentially abundant metabolites were identified between the NPDR and PDR subjects with stratification in DR duration and blood glucose level. d-Glutamine and d-glutamate metabolism was significantly highlighted in the PDR group as compared to the non-diabetic group. For the predictive performance, azelaic acid combined with guanosine achieved the area under receiver operating characteristic curve of 0.855 in the comparison between NPDR and PDR groups. Conclusion: This study revealed the metabolomics changes in tear samples of DR patients. The metabolites in tears could be the potential biomarkers in the DR analysis.

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