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Abstract: TH-OR001

Single-Cell Transcriptomic Phenotypes of Kidney Recovery and Nonrecovery Following Acute Injury

Session Information

Category: Acute Kidney Injury

  • 103 AKI: Mechanisms

Authors

  • Cetin, Sena Zeynep, Charite - Universitatsmedizin Berlin, Berlin, BE, Germany
  • Schuebel, Yael, Charite - Universitatsmedizin Berlin, Berlin, BE, Germany
  • Shihab, Mohammad, Charite - Universitatsmedizin Berlin, Berlin, BE, Germany
  • Eckardt, Kai-Uwe, Charite - Universitatsmedizin Berlin, Berlin, BE, Germany
  • Balzer, Michael S., Charite - Universitatsmedizin Berlin, Berlin, BE, Germany

Group or Team Name

  • Balzer Lab.
Background

Acute kidney injury (AKI) affects over 13 million people annually and is a major driver of chronic kidney disease (CKD). While previous single-cell studies have analyzed human AKI, longitudinal insights into (non)recovery remain lacking.

Methods

Using fluorescence-activated cell sorting and scRNA-seq, we analyzed live urine-derived kidney cells from AKI patients during peak creatinine levels and within 2 weeks post-AKI. Follow-up samples were classified as recovery (≥30% creatinine reduction) or non-recovery (<30% reduction, persistent dialysis need, oliguria, or anuria). This approach allowed us to track kidney cell dynamics without invasive biopsies. For comparison purposes, we included 1 CKD sample.

Results

Sample classification correlated with MAKE30. We captured diverse kidney cell types, primarily tubular epithelial and immune cells. Recovery samples featured an enrichment of distal developmental cells (SOX4, SOX9, KLF4, CD24, KRT17, SCNN1G) and pathways linked to EGFR, epidermis development, and keratinocyte differentiation. Non-recovery samples exhibited high CD4 T cell fractions and activation of WNT, IL6-JAK-STAT3, IL1, and VEGF pathways. Injured tubular cells (HIF1A, LAPTM5, CD44, SLC8A1) were most abundant in CKD but lowest in recovery, while healthy proximal tubule cells were highest in recovery and lowest in CKD.

Cell states were validated with single-cell data from human primary cells, previous urine-derived kidney cells, kidney tissue, and urine-derived tubuloids. Gene anchor-based mapping demonstrated overlap with orthogonal primary cell and kidney tissue datasets. Unbiased integration from gene counts and pathway-derived replicability analysis each showed considerable concordance of our dataset with previous urine-derived kidney cell transcriptomes (controls, AKI, DKD, and FSGS; n=133k cells). Transcriptomes pseudobulked by disease state showed our urine AKI samples correlated highly with AKI tissue and gentamycin-treated urine-derived tubuloids, while urine CKD and urine non-recovery samples did not.

Conclusion

By enabling the tracking of kidney adaptation post-AKI through a non-invasive approach our study provides the first temporally resolved view of kidney cell states in AKI recovery and non-recovery, highlighting key molecular pathways and potential therapeutic targets.

Funding

  • Private Foundation Support

Digital Object Identifier (DOI)