Abstract: TH-PO879
The Feasibility and Utility of Urinary Single-Cell Sequencing
Session Information
- Diabetic Kidney Disease: Basic - I
November 07, 2019 | Location: Exhibit Hall, Walter E. Washington Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Diabetic Kidney Disease
- 601 Diabetic Kidney Disease: Basic
Authors
- Zhou, Tong, University of Pennsylvania, Philadelphia, Pennsylvania, United States
- Devalaraja-Narashimha, Kishor B., Regeneron Pharmaceuticals, Tarrytown, New York, United States
- Shrestha, Rojesh, University of Pennsylvania, Philadelphia, Pennsylvania, United States
- Hogan, Jonathan J., Hospital of the University of Pennsylvania, Haddonfield, New Jersey, United States
- Palmer, Matthew, University of Pennsylvania, Philadelphia, Pennsylvania, United States
- Townsend, Raymond R., University of Pennsylvania School of Medicine, Villanova, Pennsylvania, United States
- Guarnieri, Paolo, Boehringer Ingelheim, Ridgefield, Connecticut, United States
- Wei, Yi, Regeneron Pharmaceuticals, Tarrytown, New York, United States
- Sarov-Blat, Lea, GSK, Collegeville, Pennsylvania, United States
- Boustany, Carine, Boehringer Ingelheim, Ridgefield, Connecticut, United States
- Morton, Lori, Regeneron Pharmaceuticals, Tarrytown, New York, United States
- Susztak, Katalin, University of Pennsylvania, Philadelphia, Pennsylvania, United States
Background
At present, histological assessment of renal biopsies remains the only approach to firmly diagnose renal diseases. However, it requires an invasive procedure which is associated with a small but existent risk for the patient. As kidney cells are continuously shed into the urine, we sought to investigate whether urinary single cell sequencing(SCS) can be used to predict changes occurring in renal biopsy samples. Here we report on the feasibility and utility of urinary SCS in the TRIDENT (Transformative research in diabetic nephropathy) cohort.
Methods
Patients with diabetes undergoing clinically indicated kidney biopsy were enrolled into the TRIDENT study, and were consented to participate in this ancillary study. Urine samples, spot and 24-hour collections, were obtained twice at one-month interval from 5 subjects for a total of 20 specimen. Urine scRNA-Seq was performed using 10xGenomics Chromium system. Results were correlated with kidney tissue pathology and compartment specific RNA sequencing.
Results
High-quality data was generated for 4 patients. Total number of cells detected in urine varied between 185-7260 across individuals but was not different between spot and 24-hour specimen and samples collected over a month. Cell identity was matched using mouse single cell gene expression markers. 20 different kidney cell types were identified in addition to the identity of several cell types are still being matched. Neutrophils and an unknown cell type (possibly bladder cells) were the predominant cell type in the urine. Endothelial and collecting duct intercalated cells were only detected in the spot urine sample, but all other cells were present in both collection. Urinary podocyte number correlated with proteinuria and eGFR. Urinary fibroblasts correlated with the degree of fibrosis measured histologically in renal biopsies obtained from the same patients. Urinary cell proportions correlated with renal bulk mRNA cell proportions.
Conclusion
Urine scRNA-Seq is feasible. This method can provide an insight into renal molecular, cellular, and histological changes. Urinary cell number and proportions seem stable and correlated with kidney specific changes. Overall, urinary scRNA-Seq may provide a non-invasive approach to diagnosing renal diseases.