Background: Urinary proteome predict antiproteinuric treatment outcome in human.
Objectives: To characterize the urinary proteome of dogs with renal proteinuria. Animals: Twenty-five client-owned dogs with persistent renal proteinuria and naïve to renin-angiotensin-aldosterone system (RAAS) inhibitors.
Methods: Retrospective study using banked urine from a previous clinical trial, which compared the efficacy of enalapril and telmisartan for antiproteinuric therapy in dogs. Urine collected at baseline (i.e., before RAAS inhibitor administration) was used for this study. A workflow was established for proteomic analysis of canine urine, using tandem mass spectrometry and the software MaxQuant and R. This analysis screened samples for the presence of all known canine proteins and performed relative protein quantification. Data were analyzed for (1) correlation between selected clinical parameters and urinary protein composition (as represented by the first principal component [PC1]); and (2) PC1’s ability to predict changes in clinical parameters following 30 days of enalapril or telmisartan treatment.
Results: A total of 318 proteins were identified across all samples; among which, 109 were identified in >50% of samples and entered further analysis. Urinary protein composition, as represented by PC1, positively correlated with baseline blood creatinine concentration (ρ, 0.64; p < .001) and urinary protein-to-creatinine ratio (ρ, 0.52; p, .009). PC1 predicted blood creatinine elevation after telmisartan therapy (𝛽1, 2.44; p, .005). The top 5 contributors of PC1 included plasma retinol-binding protein, cystatin-C like protein, and cystatin-E/M in positive direction; and deoxyribonuclease-1 and uromodulin in negative direction. Conclusions and Clinical Importance: Urinary proteome shows promise in predicting treatment outcomes.
