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Abstract: SA-PO1011

Unsupervised Characterization of the NURTuRE Cohort Reveals Gene Expression and Tissue Remodeling Dynamics Along a Synthetic CKD Progression Axis

Session Information

  • CKD: Pathobiology - II
    November 05, 2022 | Location: Exhibit Hall, Orange County Convention Center‚ West Building
    Abstract Time: 10:00 AM - 12:00 PM

Category: CKD (Non-Dialysis)

  • 2203 CKD (Non-Dialysis): Mechanisms

Authors

  • Bohnenpoll, Tobias, Evotec International GmbH, Göttingen, Niedersachsen, Germany
  • Dergai, Mykola, Evotec International GmbH, Göttingen, Niedersachsen, Germany
  • Olson, N. Eric, Chinook Therapeutics, Inc., Seattle, Washington, United States
  • Cox, Jennifer H., Chinook Therapeutics, Inc., Vancouver, British Columbia, Canada
  • Pospiech, Johannes, Evotec International GmbH, Göttingen, Niedersachsen, Germany
  • Michel, Niklas, Evotec International GmbH, Göttingen, Niedersachsen, Germany
  • Romoli, Simone, Chinook Therapeutics, Inc., Vancouver, British Columbia, Canada
  • Ragan, Seamus, Chinook Therapeutics, Inc., Seattle, Washington, United States
  • Mcconnell, Mark, Chinook Therapeutics, Inc., Seattle, Washington, United States
  • Radresa, Olivier, Evotec International GmbH, Göttingen, Niedersachsen, Germany
  • Andag, Uwe, Evotec International GmbH, Göttingen, Niedersachsen, Germany
  • King, Andrew J., Chinook Therapeutics, Inc., Oakland, California, United States
Background

We combined molecular groups identified by unsupervised characterization of the QUOD and NURTuRE patient cohorts into a synthetic disease progression axis (sDPA) ranging from healthy to severe CKD. We aim to explore gene expression and tissue remodeling dynamics along this pseudotime trajectory to drive the discovery of new precision treatments.

Methods

A data-driven selection of QUOD (healthy, n = 36) and NURTuRE (CKD, n = 139) kidney transcriptomes (FFPE, RNAseq) was combined into a sDPA via principal component analysis. Clusters of genes with similar expression dynamics were derived by local regression and hierarchical clustering. Cell specific signatures were employed to explore tissue remodeling dynamics.

Results

Molecular stratification aligned with clinical CKD progression, with eGFR and urea decreasing or increasing along the sDPA, respectively (Fig. A). Clustering genes by their expression dynamics revealed early, intermediate and late changes with stable or variable slopes, potentially reflecting disease initiating events and adaptive responses (Fig. B). Exploration of cell-type specific signature expression suggested that gene expression dynamics correspond to tissue remodeling, with the loss of proximal tubules preceding podocyte loss (Fig. C). Interestingly, increasing parietal epithelial cell signature dynamics resembled interstitial remodeling as reflected by increasing immune and fibroblast signatures.

Conclusion

Unsupervised cohort characterization of kidney transcriptomes and integration into a pseudotime disease progression axis has the potential to unravel cellular and molecular mechanisms of CKD.

Funding

  • Commercial Support