Proteomics

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Urinary proteomics anlaysis of Type 2 Diabetic Nephropathy

ABSTRACT: Type 2 Diabetic Nephropathy (T2DN), in the setting of type 2 diabetes, is the world占쎌뀼 leading cause of chronic kidney disease and end-stage kidney disease (ESKD). The increasing prevalence and heterogeneous phenotype of T2DN complicate the approach to treating patients. While kidney biopsy is the gold standard for exclusion of non-DN diagnoses and confirming diagnosis of DN, it is imperfect in predicting progression to ESKD. Artificial intelligence (AI) has the potential to improve classification of T2DN, predict progression risk, and via integration with urinary proteomic profiles identify novel urinary biomarkers, taken together augmenting and going beyond current pathology practice.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Urine

DISEASE(S): Type 2 Diabetes Mellitus

SUBMITTER: Dohyun Han  

LAB HEAD: Dohyun Han

PROVIDER: PXD037505 | Pride | 2025-07-28

REPOSITORIES: Pride

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Dataset's files

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Action DRS
20190405_urine_library_F1.raw Raw
20190405_urine_library_F10.raw Raw
20190405_urine_library_F11.raw Raw
20190405_urine_library_F12.raw Raw
20190405_urine_library_F13.raw Raw
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Publications

<h4>Introduction</h4>Mechanisms underlying diabetic kidney disease (DKD) progression remain incompletely understood. This study used untargeted and targeted mass spectrometry-based proteomics in 2 independent cohorts to capture rapidly progressive DKD.<h4>Methods</h4>We conducted untargeted and targeted mass spectrometry on urine samples from Korean patients with type 2 diabetes and biopsy-confirmed diabetic nephropathy (SNUH-DN cohort; <i>n</i> = 64) and a DKD subgroup of the Chronic Renal Insu  ...[more]

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