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BackgroundMicroscopic analysis of urine sediment is probably the most commonly used diagnostic procedure in nephrology. The urinary cells, however, have not yet undergone careful unbiased characterization.MethodsSingle-cell transcriptomic analysis was performed on 17 urine samples obtained from five subjects at two different occasions, using both spot and 24-hour urine collection. A pooled urine sample from multiple healthy individuals served as a reference control. In total 23,082 cells were analyzed. Urinary cells were compared with human kidney and human bladder datasets to understand similarities and differences among the observed cell types.ResultsAlmost all kidney cell types can be identified in urine, such as podocyte, proximal tubule, loop of Henle, and collecting duct, in addition to macrophages, lymphocytes, and bladder cells. The urinary cell–type composition was subject specific and reasonably stable using different collection methods and over time. Urinary cells clustered with kidney and bladder cells, such as urinary podocytes with kidney podocytes, and principal cells of the kidney and urine, indicating their similarities in gene expression.ConclusionsA reference dataset for cells in human urine was generated. Single-cell transcriptomics enables detection and quantification of almost all types of cells in the kidney and urinary tract.

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Introduction Although diabetic kidney disease (DKD) is responsible for more than half of all chronic and end-stage kidney disease (ESKD), the association of light (LM) and electron microscopic (EM) structural changes with clinical parameters and prognosis in DKD is incompletely understood. Methods This is an interim analysis of 62 patients diagnosed with biopsy-confirmed DKD from the multicenter TRIDENT (Transformative Research in Diabetic Nephropathy) study. Twelve LM and 8 EM descriptors, representing changes in glomeruli, tubulointerstitium, and vasculature were analyzed for their relationship with clinical measures of renal function. Patients were followed every 6 months. Results Multivariable linear regression analysis revealed that estimated glomerular filtration rate (eGFR) upon enrollment correlated the best with interstitial fibrosis. On the other hand, the rate of kidney function decline (eGFR slope) correlated the most with glomerular lesions including global glomerulosclerosis and mesangiolysis. Unbiased clustering analysis based on histopathologic data identified 3 subgroups. The first cluster, encompassing subjects with the mildest histologic lesions, had the most preserved kidney function. The second and third clusters had similar degrees of kidney dysfunction and structural damage, but differed in the degree of glomerular epithelial cell and podocyte injury (podocytopathy DKD subtype). Cox proportional hazard analysis showed that subjects in cluster 2 had the highest risk to reach ESKD (hazard ratio: 17.89; 95% confidence interval: 2.13–149.79). Glomerular epithelial hyperplasia and interstitial fibrosis were significant predictors of ESKD in the multivariate model. Conclusion The study highlights the association between fibrosis and kidney function and identifies the role of glomerular epithelial changes and kidney function decline.

Our study suggests that pre-operative exposure to progesterone favourably modulates the effect of surgical stress, and this might underlie its beneficial effect when administered prior to surgery.