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Abstract: SA-OR01

Studying Proteinuria in COVID-19 to Define Markers of Severity and New Treatments

Session Information

Category: Coronavirus (COVID-19)

  • 000 Coronavirus (COVID-19)

Authors

  • Gupta, Yask, Columbia University Irving Medical Center, New York, New York, United States
  • Ke, Juntao, Columbia University Irving Medical Center, New York, New York, United States
  • Martino, Jeremiah, Columbia University Irving Medical Center, New York, New York, United States
  • Liu, Qingxue, Columbia University Irving Medical Center, New York, New York, United States
  • Kil, Byum hee, Columbia University Irving Medical Center, New York, New York, United States
  • Lim, Tze Yin, Columbia University Irving Medical Center, New York, New York, United States
  • Jin, Gina Ying, Columbia University Irving Medical Center, New York, New York, United States
  • Ahram, Dina, Columbia University Irving Medical Center, New York, New York, United States
  • Steers, Nicholas J., Columbia University Irving Medical Center, New York, New York, United States
  • Sanna-Cherchi, Simone, Columbia University Irving Medical Center, New York, New York, United States
Background

The recent SARS-CoV-2 pandemic has led to ~375,000 fatalities worldwide as of June 1st. Nearly, 43% of COVID-19 patients have been reported to have proteinuria, which can result from direct podocyte infection, podocytopathy related to cytokine storm, or both. This association between respiratory viruses, proteinuria, and primary kidney disease has also been observed in the context of respiratory syncytial virus (RSV), where patients can develop nephrotic syndrome. Therefore, studying primary and virus-dependent models of proteinuria and podocyte injury is critical to shed light into COVID-19 pathobiology, severity of disease and potential treatments.

Methods

We accessed transcriptomic data (RNA-seq) for lung cell lines (A549) infected with three different viruses and identified differentially expressed genes (DEGs) for SARS-CoV-2, RSV and IAV. In parallel, we also investigated DEGs for FSGS and MCD using LIMMA R package. We investigated the statistical correlation between the log-fold change of DEGs (Nephroptic syndrome and SARS-COV-2) using R. Pathway analysis was performed using WebGestalt. Possible drugs correcting the skewed gene expression in FSGS and SARS-COV-2 were identified using the Connectivity map (cMAP).

Results

120 gene signatures were specific to SARS-CoV-2. By using gene expression data from glomeruli of FSGS/MCD we identified 902 DEGs for FSGS and 5 for MCD. Out of these, 6 were overlapping and upregulated in COVID-19 and FSGS/MCD (B2M, EIF2AK2, IFI16, IFI27, TCIM and UBE2L6). Strikingly, IFI27 has been recently reported as a marker of disease severity in COVID-19. We found significant positive correlation between the log2 fold change of 94 FSGS/MCD genes intersecting with the 120 COVID-19. The results were specific to glomeruli and to high proteinuric diseases, supporting a common cellular response in lung and podocytes. We then searched the cmap data and identified 59 drugs significantly inversely associated with SARS-COV-2 and 72 for FSGS. Out of these, 7 drugs were in common, representing novel potential drugs for COVID-19 and podocytopathies.

Conclusion

Overall, our results suggest transciptional congruency between NS and SARS-COV-2 which can possibly be used to design novel therapies treat these diseases.