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Abstract: SA-PO407

Identifying New CKD Drug Targets from Genetic Analysis

Session Information

Category: Genetic Diseases of the Kidneys

  • 1002 Genetic Diseases of the Kidneys: Non-Cystic

Authors

  • Buvall, Lisa, AstraZeneca, Molndal, Sweden
  • Reznichenko, Anna, AstraZeneca, Molndal, Sweden
  • Granqvist, Anna, AstraZeneca, Molndal, Sweden
  • Zhou, Alex Xianghua, AstraZeneca, Molndal, Sweden
  • Williams, Julie, AstraZeneca, Molndal, Sweden
  • Cederblad, Linda, AstraZeneca, Molndal, Sweden
  • Cameron-Christie, Sophia, AstraZeneca, Molndal, Sweden
  • Bohlooly, Mohammad, AstraZeneca, Molndal, Sweden
  • Haefliger, Carolina, AstraZeneca, Molndal, Sweden
  • Laerkegaard Hansen, Pernille B., AstraZeneca, Molndal, Sweden
Background

Identifying successful drug candidates to treat patients with Chronic Kidney Disease (CKD) is challenging due to the heterogenicity of the CKD population. As a result, no efficient treatment options to halt or reverse CKD development are today available. It’s known that drug target genes associated with clinical phenotypes are more likely to succeed in pharmaceutical development. Thereby, in an unprecedent approach to identify CKD disease drivers we have performed whole exome sequence on 3315 CKD patients and 9563 controls to search for rare mutations in CKD patients.

Methods

Collapsing analysis generated a list with 417 enriched suggestive rare mutations in CKD patients. These genes where then prioritized through a comprehensive workflow aiming to validate the hits as potential drug targets. First the genes were filtered by bioinformatics analyses with genes being ranked and selected based on their gene expression correlating to renal function and CKD stage. In addition, integrative omics analyses were performed to give information on kidney enrichment and predict renal cell type expression.

Results

The analysis leveraged 93 genes with a strong CKD correlation. In the next step we ranked the genes based on literature data supporting a link to CKD relevant biology. The 31 genes with the highest scores went into experimental in vitro and in vivo validation. Loss of function phenotypes were investigated by siRNA KD in 2D and 3D human (organoid) renal cell systems. Gain of function phenotypes were investigated by overexpression or by studying KD protection in the presence of CKD stressors. In parallel, the importance of the genes on renal function was evaluated using CRISPR based gene knock-out of genes in zebrafish with the top ranked four genes being further processed using CRISPR knock-out mice.

Conclusion

This extensive workflow, that was processed within only one year, identified the first novel CKD target to have the potential to be first in class and as a result this gene entered our pipeline for drug discovery.

Funding

  • Commercial Support