Abstract: SA-PO0097
Integrating Mouse and Human Transcriptomic Signatures Reveals US Food and Drug Administration (FDA)-Approved Drug Repurposing Candidates
Session Information
- ADPKD and Cystic Kidney Disease - 3
October 24, 2026 | Location: Exhibit Hall A, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Genetic Diseases of the Kidneys
- 1201 Genetic Diseases of the Kidneys: Cystic (Monogenic)
Authors
- Howton, Timothy C., The University of Alabama at Birmingham Department of Cell Developmental and Integrative Biology, Birmingham, Alabama, United States
- Wilk, Elizabeth, The University of Alabama at Birmingham Department of Cell Developmental and Integrative Biology, Birmingham, Alabama, United States
- Soelter, Tabea M., The University of Alabama at Birmingham Department of Cell Developmental and Integrative Biology, Birmingham, Alabama, United States
- Lasseigne, Brittany N., The University of Alabama at Birmingham Department of Cell Developmental and Integrative Biology, Birmingham, Alabama, United States
Background
Autosomal dominant polycystic kidney disease (ADPKD) affects 1 in 400-1000 people globally and accounts for 6-10% of all adult patients on dialysis in the United States. Approximately 50% of patients progress to end-stage kidney disease. Currently, tolvaptan is the only FDA-approved therapeutic, and its use is limited by hepatotoxicity and poor tolerability. Therefore, there is a critical need to identify additional therapies. We used unsupervised pattern learning and signature reversion on mouse RNA-seq data and human microarray data to identify drug repurposing candidates for ADPKD that are more likely to be successful in both preclinical and clinical trials.
Methods
We performed Coordinated Gene Activity in Pattern Sets (CoGAPS) analysis on four independent mouse ADPKD RNA-seq datasets (Pkd1 and Pkd2 models). We then used ProjectR to transfer the resulting patterns onto human PKD1 microarray data after ortholog mapping. Disease signatures were generated by combining the genes with the highest loadings for significant disease-associated patterns (padj < 0.05, Wilcoxon rank-sum test, BH-adjusted). We performed signature reversion on the cross-species disease signatures by querying the LINCS L1000 2020 compounds database, restricted to kidney-derived cell lines (HA1E, NKDBA). We filtered the candidates for FDA-approved phase 4 compounds in ChEMBL and ranked them by consensus normalized connectivity scores.
Results
We identified disease-associated transcriptional patterns in all projected data sets. Our signature reversion analysis identified a prioritized list of FDA-approved candidates. The top-ranked compounds were enriched in known targeting of ADPKD-relevant pathways, including drugs targeting vasopressin, JAK-STAT, and EGFR signaling, as well as novel mechanistically relevant classes of drugs currently under evaluation. Consensus ranking across all data sets identified a prioritized suite of high-confidence candidates.
Conclusion
This analytical approach identified several putative drug repurposing candidates for ADPKD. Due to the cross-species nature of the analysis, we have higher confidence in the translatability than single-species approaches. This pipeline provides a prioritized list of FDA-approved drugs for experimental validation and demonstrates the value of integrating animal model data with human patient transcriptomics.
Acknowledgment
Data analysis was performed using custom scripts generated with the assistance of Claude Sonnet 4.6 (Anthropic); the authors take full responsibility for the integrity of the generated code and resulting data.
Funding
- Private Foundation Support