Chief Supervisor

Prof. ZHOU Lei

Project Title

Synopsis

Diabetic peripheral neuropathy is one of the main complications of diabetes, the main symptom in the eyes is progressive nerve fiber loss. However, the origin of diabetic corneal neuropathy remains largely unexplored. Current research focuses mainly on using aqueous humor, vitreous humor, and serum samples to identify diagnostic biomarkers. However, the proteomic and metabolomic landscape of large-scale tear samples remains elusive. Here, we aim to perform a comprehensive integrated proteomic and metabolomic profiling of the diabetic corneal neuropathy cohort. Comparing the proteome and metabolome profiling of tear samples at different time points, we will reveal a catalog of dysregulated proteins and metabolites. Moreover, a protein co-expression network will be constructed, which will provide a comprehensive view of the biological features of each progression subtype. Applying a network-based method and a machine-learning model, we will select a combination of potential protein and metabolite signatures that can predict disease progression. Finally, we will use the predictive signature-related proteins/metabolites to perform a drug discovery using complied cell line data. Taken together, our integrated analysis characterizes distinct states of diabetic corneal neuropathy, thus providing a potential therapeutic outlook for improving patient disease outcomes.