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Diabetic retinopathy (DR) is one of the complications of diabetic mellitus and a major cause of blindness worldwide.Early detection and treatment for DR could reduce the risk of blindness.With the development of high-throughput omics, proteomics and metabolomics have shown great advantages in early diagnosis, exploration of pathogenesis, and discovery of new therapeutic targets in DR.Although traditional biomarkers such as duration of diabetes and HbA1c are good predictors for the progression of DR, there is still a lack of independent predictors that can reflect the pathogenesis of DR.Advances in artificial intelligence and machine learning have facilitated the exploration of novel biomarkers for DR, making the novel biomarkers more noninvasive, robust and sensitive.In clinical practice, the analysis of proteins and metabolites in patients with varied prognosis may help clinicians understand the heterogeneity of patients to develop precision medicine in DR.This review summarized the progress in the technology and strategy of proteomics and metabolomics in biomarker discovery, pathogenesis, and precision medicine of DR to promote clinical and translational research in this field.
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Contributor Information
Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Branch of National Clinical Research Center for Ocular Disease, Eye Institute and School of Optometry, Tianjin Medical University Eye Hospital, 300384 China
Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Branch of National Clinical Research Center for Ocular Disease, Eye Institute and School of Optometry, Tianjin Medical University Eye Hospital, 300384 China
Singapore Eye Research Institute, Singapore 999002