Aim: An advanced proteomics platform for protein biomarker discovery in diabetic chronic kidney disease (DKD) was developed, validated and implemented. Materials & methods: Three Type 2 diabetes mellitus patients and three control subjects were enrolled. Urinary peptides were extracted, samples were analyzed on a hybrid LTQ-Orbitrap Velos Pro instrument. Raw data were searched using the SEQUEST algorithm and integrated into Proteome Discoverer platform. Results & discussion: Unique peptide sequences, resulted sequence coverage, scoring of peptide spectrum matches were reported to albuminuria and databases. Five proteins that can be associated with early DKD were found: apolipoprotein AI, neutrophil gelatinase-associated lipocalin, cytidine deaminase, S100-A8 and hemoglobin subunit delta. Conclusion: Urinary proteome analysis could be used to evaluate mechanisms of pathogenesis of DKD.
Keywords: albuminuria; diabetes mellitus Type 2; inflammation; proximal tubule dysfunction; urinary proteomics.