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Abstract: SA-OR073

A Computational Drug Screening Approach to Identify Compounds Targeting Renal Age-Associated Molecular Profiles

Session Information

Category: CKD (Non-Dialysis)

  • 2103 CKD (Non-Dialysis): Mechanisms

Authors

  • Perco, Paul, Medical University Innsbruck, Innsbruck, Austria
  • Koppelstaetter, Christian, Medical University Innsbruck, Innsbruck, Austria
  • Leierer, Johannes, Medical University Innsbruck, Innsbruck, Austria
  • Rudnicki, Michael, Medical University Innsbruck, Innsbruck, Austria
  • Kerschbaum, Julia, Medical University Innsbruck, Innsbruck, Austria
  • Kronbichler, Andreas, Medical University Innsbruck, Innsbruck, Austria
  • Melk, Anette, Hannover Medical School, Hannover, Germany
  • Mayer, Gert J., Medical University Innsbruck, Innsbruck, Austria
Background

Aging is a key driver for chronic kidney disease (CKD) and counterbalancing of renal aging processes depicts a way of preventing development and progression of CKD.

Methods

We generated a set of renal age-associated genes (RAAGs) making use of two transcriptomics datasets complemented by information extracted from scientific literature and dedicated aging databases. We evaluated the association of RAAG expression with CKD progression in an independent trancriptomics dataset of 63 CKD patients with a median follow-up time of 6.9 years. Genes showing concordant expression in aging and CKD were used to computationally screen for compounds reversing expression patterns using the L1000 Characteristic Direction Signature Search Engine. The impact on gene expression of key RAAGs in a human renal proximal tubular cell culture model of renal aging was validated for selected compounds.

Results

31 of the 634 identified RAAGs were significantly associated with CKD progression. 23 RAAGs (74%) showed concordant regulation with CKD progression, i.e. being upregulated in progressive CKD patients as well as with increasing age or vice versa. Among the top-ranked compounds reversing expression of these RAAGs were drugs being in use in the clinical setting in the context of diabetes and kidney disease, namely rosiglitazone, valsartan, captopril, and atorvastatin. All four compounds significantly affected gene expression in a beneficial way in the cell culture model of renal aging. Rosiglitazone had the strongest impact on RAAG expression in HK2 cells significantly downregulating levels of TNFRSF11B (p-value < 0.001), MMP7 (p-value = 0.007), CFB (p-value < 0.001), LTF (p-value = 0.029), and C3 (p-value = 0.002) as compared with untreated controls.

Conclusion

We have (i) generated a list of RAAGs, (ii) identified a subset being also associated with CKD progression, and (iii) identified compounds that have a positive impact on expression levels of the RAAG/CKD signature in renal proximal tubular cells.

Funding

  • Government Support - Non-U.S.