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Related Experiment Video

Updated: Jul 5, 2026

Comparative Proteomic Analysis of Whole Kidney, Medulla, and Cortical Tubules in Diabetic Pathogenesis of Kidney Injury in Mice

Comparative Proteomic Analysis of Whole Kidney, Medulla, and Cortical Tubules in Diabetic Pathogenesis of Kidney Injury in Mice

Published on: May 2, 2025

Urinary proteomics in diabetes and CKD.

Kasper Rossing¹, Harald Mischak, Mohammed Dakna

¹Steno Diabetes Center, Niels Steensens Vej 2, DK 2820 Gentofte, Denmark. krossing@dadlnet.dk

Journal of the American Society of Nephrology : JASN

|May 2, 2008

Summary

Researchers identified urinary biomarkers to detect diabetic nephropathy early. This proteomic analysis accurately distinguishes diabetes, predicts disease progression, and differentiates it from other kidney diseases.

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Proteomic Profile of EPS-Urine through FASP Digestion and Data-Independent Analysis

Published on: May 8, 2021

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Last Updated: Jul 5, 2026

Comparative Proteomic Analysis of Whole Kidney, Medulla, and Cortical Tubules in Diabetic Pathogenesis of Kidney Injury in Mice

Comparative Proteomic Analysis of Whole Kidney, Medulla, and Cortical Tubules in Diabetic Pathogenesis of Kidney Injury in Mice

Published on: May 2, 2025

Proteomic Profile of EPS-Urine through FASP Digestion and Data-Independent Analysis

Published on: May 8, 2021

Area of Science:

Nephrology
Proteomics
Biomarker Discovery

Background:

Diabetic nephropathy is a leading cause of chronic kidney disease.
Early detection and accurate diagnosis are crucial for effective management.
Current diagnostic methods have limitations in sensitivity and specificity.

Purpose of the Study:

To identify and validate urinary biomarkers for diabetes and diabetic nephropathy.
To differentiate diabetic nephropathy from nondiabetic proteinuric renal diseases.
To assess the prognostic value of urinary biomarkers for disease progression.

Main Methods:

High-resolution capillary electrophoresis coupled with electrospray-ionization mass spectrometry (CE-ESI-MS).
Analysis of urinary proteomes in 305 individuals.
Validation in blinded datasets.

Main Results:

A panel of 40 biomarkers distinguished diabetes from healthy individuals (89% sensitivity, 91% specificity).
A model with 65 biomarkers identified diabetic nephropathy with 97% sensitivity and specificity.
Biomarkers predicted progression to overt nephropathy and differentiated it from other renal diseases (81% sensitivity, 91% specificity).
Reduced collagen type I fragments were observed in patients with diabetes or nephropathy.

Conclusions:

Urinary proteome analysis offers a promising approach for early detection of diabetic nephropathy.
Biomarker panels can provide prognostic information and aid in differential diagnosis.
This method may improve patient outcomes through timely intervention.