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Abstract: TH-PO417

The Spatially Resolved Transcriptome Signatures of Glomeruli in CKD

Session Information

Category: Glomerular Diseases

  • 1301 Glomerular Diseases: Fibrosis and Extracellular Matrix

Authors

  • Perin, Laura, Chindren's Hospital Los Angeles, Los Angeles, California, United States
  • Soloyan, Hasmik, Chindren's Hospital Los Angeles, Los Angeles, California, United States
  • Clair, Geremy, Pacific Northwest National Laboratory, Richland, Washington, United States
  • Cravedi, Paolo, Mount Sinai Health System, New York, New York, United States
  • Angeletti, Andrea, Istituto Giannina Gaslini, Genova, Liguria, Italy
  • Al-Rabadi, Laith, University of Utah Health, Salt Lake City, Utah, United States
  • De Filippo, Roger E., Chindren's Hospital Los Angeles, Los Angeles, California, United States
  • Da Sacco, Stefano, Chindren's Hospital Los Angeles, Los Angeles, California, United States
  • Lemley, Kevin V., Chindren's Hospital Los Angeles, Los Angeles, California, United States
  • Sedrakyan, Sargis, Chindren's Hospital Los Angeles, Los Angeles, California, United States
Background

Using Digital Spatial Profiling (DPS), we described for the first-time the human spatial glomerular transcriptomic map that may characterize the molecular mechanisms underlying progressive diseases in Alport syndrome (AS), focal segmental glomerulosclerosis (FSGS), and membranous nephropathy (MN).

Methods

Nanostring GeoMX DSP was performed in paraffin sections of AS, FSGS, and MN (normal biopsies from partial nephrectomy were used as control). Tabular and glomerular regions of interest (ROI, n=106) were manually selected and sequenced following Naostring protocols. After QC analysis (dynamic range and gene expression above noise), and subsequent Q3 normalization, data processing was performed in R v4.0.2 using the package RomicsProcessor v1.0.0. Different analytical tools were used to determine similitudes/differences between healthy and diseased glomeruli.

Results

By DPS, we revealed significant heterogeneity of transcriptional programs among glomeruli within the same disease as well as across different diseases. By regression analysis we showed that increasing pathology scores in AS, FSGS, and MN correlated with specific increasing or decreasing genes, mostly associated with cellular adhesion. By trajectory analysis we revealed that glomeruli (from all 3 diseases) having low pathology scores showed transcriptional signatures that were significantly different from non-diseased glomeruli, indicating that histological features may not always represent transcriptional changes. We identified a transcriptional signature comprised of genes (ADAMTS13, HOXB8, and ZNF346) and pathways for SRP-dependent co-translational protein targeting to membrane and selenocysteine synthesis that were modulated in all diseased glomeruli. By correlation analysis, we identified new glomerular cell-specific genes that highly correlated with known podocyte markers (WT1, NPHS1, NPHS2), glomerular endothelial cells (EHD3), and mesangial cells (PDGFRb).

Conclusion

Defining transcriptional programs at the single glomerulus level is a powerful way of gaining insight into the pathophysiology of kidney disease with the potential of clarifying biological processes key to understanding mechanisms of disease progression and allowing the discovery of potential new therapeutic targets for CKD patients.

Funding

  • NIDDK Support