biostudies-literatureUnknownLucarelli N<h4>Background</h4>The heterogeneous phenotype of diabetic nephropathy (DN) from type 2 diabetes complicates appropriate treatment approaches and outcome prediction. Kidney histology helps diagnose DN and predict its outcomes, and an artificial intelligence (AI)-based approach will maximize clinical utility of histopathological evaluation. Herein, we addressed whether AI-based integration of urine proteomics and image features improves DN classification and its outcome prediction, altogether augmenting and advancing pathology practice.<h4>Methods</h4>We studied whole slide images (WSIs) of periodic acid-Schiff-stained kidney biopsies from 56 DN patients with associated urinary proteomics data. We identified urinary proteins differentially expressed in patients who developed end-stage kidnemedRxiv : the preprint server for health sciences2023.04.28.23289272https://www.ebi.ac.uk/biostudies/studies/S-EPMC10187347biostudies-literatureDiscovery of Novel Digital Biomarkers for Type 2 Diabetic Nephropathy Classification via Integration of Urinary Proteomics and Pathology.PMC10187347Rosenberg AZJen KYZee JYun DSarder PTomaszewski JEHan DHan SSLucarelli NGinley BMoon KCfalseDiscovery of Novel Digital Biomarkers for Type 2 Diabetic Nephropathy Classification via Integration of Urinary Proteomics and Pathology.<h4>Background</h4>The heterogeneous phenotype of diabetic nephropathy (DN) from type 2 diabetes complicates appropriate treatment approaches and outcome prediction. Kidney histology helps diagnose DN and predict its outcomes, and an artificial intelligence (AI)-based approach will maximize clinical utility of histopathological evaluation. Herein, we addressed whether AI-based integration of urine proteomics and image features improves DN classification and its outcome prediction, altogether augmenting and advancing pathology practice.<h4>Methods</h4>We studied whole slide images (WSIs) of periodic acid-Schiff-stained kidney biopsies from 56 DN patients with associated urinary proteomics data. We identified urinary proteins differentially expressed in patients who developed end-stage kidne2023-01-01T00:00:00Z2023 May2026-05-14T03:17:27.631Z2026-05-14T03:08:39.255ZS-EPMC101873473720541310.1101/2023.04.28.23289272