Abstract: FR-PO1175
Development of a Comprehensive Human Urine Single-Cell RNA Sequencing (scRNA-seq) Atlas for Enhanced Diagnostic Accuracy of Kidney Diseases
Session Information
- CKD: Mechanisms - 2
October 25, 2024 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: CKD (Non-Dialysis)
- 2303 CKD (Non-Dialysis): Mechanisms
Authors
- Abedini, Amin, University of Maryland Medical Center, Baltimore, Maryland, United States
- Kloetzer, Konstantin A., Medizinische Universitat Graz, Graz, Steiermark, Austria
- Susztak, Katalin, University of Pennsylvania, Philadelphia, Pennsylvania, United States
Background
Understanding the cellular composition of human urine is crucial for advancing diagnostic and therapeutic strategies for kidney and urinary tract diseases. Previous studies have provided insights into individual conditions, but a comprehensive, spatially resolved single-cell RNA-sequencing (scRNA-seq) atlas of human urine has been lacking.
Methods
We generated a human urine scRNA-seq atlas by integrating various published datasets. Deep generating modeling (scVI) was used for the data integration. Identified cell types were validated using kidney spatial transcriptomics. Additionally, we utilized the largest human kidney scRNA-seq atlas and MetaNeighbor analysis to further confirm our findings. Differentially expressed genes (DEGs) were identified and used to develop gene panels for the diagnosis of various conditions. We trained a logistic regression model with the gene expression data to evaluate the diagnostic performance of gene panels.
Results
Our integration of 86 samples yielded a comprehensive urine scRNA-seq atlas comprising 133,208 cells from various kidney conditions. This atlas captures a broad spectrum of cell types, including all kidney cell types, immune cells, and uroepithelial cells. The identified cell types were validated using kidney spatial transcriptomics. Importantly, identified cell types were successfully integrated and validated against the largest human kidney scRNA-seq data. The gene panels derived from DEGs demonstrated high sensitivity and specificity in diagnosing different conditions, supported by validation against a large human kidney scRNA-seq atlas.
Conclusion
The establishment of a spatially resolved human urine scRNA-seq atlas marks a significant advance in the non-invasive monitoring and diagnosis of kidney and urinary tract diseases. The validated gene panels offer promising tools for precise condition diagnosis, potentially changing current diagnostic practices and reduce our reliance on kidney biopsy.